Science, Faculty of
Earth, Ocean and Atmospheric Sciences, Department of
DSpace
UBCV
Hazell, Arthur James Scott
Master of Science - MSc
University of British Columbia
Unconventional shale reservoirs are commonly exploited by drilling horizontal wellbores up to several kilometers in length. Hydraulic fracture completions of a wellbore are designed, in part, based on the geomechanical properties of the reservoir. The completion program is executed in a series of stages, typically spaced at regular intervals along the length of the lateral, without consideration of variable lithology and geomechanical properties that may exist along the length of the borehole. Assessing the geomechanical properties and stress conditions along the lateral has proven difficult due to the cost and challenge of obtaining core samples for analyses. Drill cuttings derived during drilling provide an opportunity to characterize the reservoir geomechanical properties, including the elastic moduli. If such small samples can be tested reliably and be shown to be scalable to the reservoir, the geomechanical variability along a wellbore can be measured and exploited with planned hydraulic fracture completions at geomechanical sweet spots. In this thesis, the utility of instrumented indentation for characterizing geomechanical variation in shale core chips and drill cuttings is evaluated. Indentation testing on mineral and shale samples assesses the effects of indentation and sample parameters on indentation results, suggesting that samples of size 841 µm, tested at 50 – 200 mN load, with at least 83 standard indentations are likely to provide repeatable and representative mean indentation results. Indentation can characterize geomechanical variability between shale core chips and drill cuttings samples with centimeter differences in sample depth. Repeatable indentation results are compared for indentation tests, as well as unoriented and oriented subsamples; oriented subsamples showed 2 – 18 % greater mean indentation modulus in samples with bedding oriented parallel to the direction of indentation, compared to bedding perpendicular, indicating the effects of mechanical anisotropy on indentation results. Moderate correlations are presented between mean indentation modulus and static (R² = 0.53) and dynamic (R² = 0.45) Young’s moduli, for Montney Formation shales. Geomechanical correlations with mineralogy suggest mean indentation results are controlled by dominant, stiff components of shale, with minimal influence from clay composition. Variability in indentation results can be applied as an index through geomechanical depth profiles.
UTILITY OF INSTRUMENTED INDENTATION FOR THE OPTIMIZATION OF HORIZONTAL WELLBORE COMPLETIONS WITH EXAMPLES FROM THE MONTNEY FORMATION OF ALBERTA AND BRITISH COLUMBIA by Arthur James Scott Hazell B.Sc., The University of British Columbia, 2016 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Geological Sciences) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2021 © Arthur James Scott Hazell, 2021 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled: UTILITY OF INSTRUMENTED INDENTATION FOR THE OPTIMIZATION OF HORIZONTAL WELLBORE COMPLETIONS WITH EXAMPLES FROM THE MONTNEY FORMATION OF ALBERTA AND BRITISH COLUMBIA submitted by Arthur James Scott Hazell in partial fulfillment of the requirements for the degree of Master of Science in Geological Sciences Examining Committee: R. Marc Bustin, Professor, Department of EOAS, UBC Supervisor Erik Eberhardt, Professor, Department of EOAS, UBC Supervisory Committee Member Lori Kennedy, Associate Professor, Department of EOAS, UBC Supervisory Committee Member Stuart Sutherland, Professor of Teaching, Department of EOAS, UBC Additional Examiner iii Abstract Unconventional shale reservoirs are commonly exploited by drilling horizontal wellbores up to several kilometers in length. Hydraulic fracture completions of a wellbore are designed, in part, based on the geomechanical properties of the reservoir. The completion program is executed in a series of stages, typically spaced at regular intervals along the length of the lateral, without consideration of variable lithology and geomechanical properties that may exist along the length of the borehole. Assessing the geomechanical properties and stress conditions along the lateral has proven difficult due to the cost and challenge of obtaining core samples for analyses. Drill cuttings derived during drilling provide an opportunity to characterize the reservoir geomechanical properties, including the elastic moduli. If such small samples can be tested reliably and be shown to be scalable to the reservoir, the geomechanical variability along a wellbore can be measured and exploited with planned hydraulic fracture completions at geomechanical sweet spots. In this thesis, the utility of instrumented indentation for characterizing geomechanical variation in shale core chips and drill cuttings is evaluated. Indentation testing on mineral and shale samples assesses the effects of indentation and sample parameters on indentation results, suggesting that samples of size 841 µm, tested at 50 – 200 mN load, with at least 83 standard indentations are likely to provide repeatable and representative mean indentation results. Indentation can characterize geomechanical variability between shale core chips and drill cuttings samples with centimeter differences in sample depth. Repeatable indentation results are compared for indentation tests, as well as unoriented and oriented subsamples; oriented subsamples showed 2 – 18 % greater mean indentation modulus in samples with bedding oriented parallel to the direction of indentation, compared to bedding iv perpendicular, indicating the effects of mechanical anisotropy on indentation results. Moderate correlations are presented between mean indentation modulus and static (R2 = 0.53) and dynamic (R2 = 0.45) Young’s moduli, for Montney Formation shales. Geomechanical correlations with mineralogy suggest mean indentation results are controlled by dominant, stiff components of shale, with minimal influence from clay composition. Variability in indentation results can be applied as an index through geomechanical depth profiles. v Lay Summary This thesis explores the utility of a microscopic method, instrumented indentation, as a technique of assessing mechanical properties of Montney Formation shales and thereby deriving critical data for designing of hydraulic fracture completions. By identifying geomechanical variation in long horizontal wells, hydraulic fracture completions can be planned at geomechanically-favourable depths rather than even interval spacing. Planned completions could contribute to the optimization of hydraulic fracture stages, by either reducing the number of stages necessary to stimulate a reservoir, or by improving the success of each stage. This may lead to improved resource recovery, while minimizing cost, risk, and environmental impact through reduced water, proppant, and additive inputs. In this way, an improved understanding of indentation mechanics in Montney Formation shales will contribute to providing more efficient and environmentally conscious energy to Canada and the world. vi Preface The author, Scott Hazell, was responsible for all research on which this thesis is based. Initial goals of this research were outlined as part of a Natural Sciences and Engineering Research Council of Canada (NSERC) Collaborative Research and Development (CRD) consortium with researchers from the University of Calgary (U of C) and University of British Columbia (UBC). Specific research questions were updated with input from Dr. R. Marc Bustin (supervisor). Preliminary sample sets, including shale core plugs and core chips, were provided by the NSERC CRD consortium. Public mechanical data from core analyses was compiled by Daniel Laird. The author sampled additional shale core chips and drill cuttings at the BC Oil and Gas Commission (BCOGC) Core Research Facility (CRF) in Fort St. John, BC, and at the Alberta Energy Regulator (AER) Core Research Centre (CRC) in Calgary, AB. Sample preparation and analyses were performed within The Department of Earth and Ocean Sciences at the University of British Columbia. Indentation sample preparation and analyses were completed by the author. XRD preparation and testing were completed by the author and Andrea Sanlorenzo, with instrumentation assistance from Lan Kato. Quantitative XRD phase analyses were completed by Dr. R. Marc Bustin. Parts of this research are reported in annual NSERC CRD update reports and presented to consortium partners. Parts of this research were also presented at the CSPG Rock Analysis Workshop, on March 21, 2019 in Calgary, AB. Some of the data from this research was provided to consortium partners for use and comparison within other consortium research. vii The author was responsible for writing all chapters of this thesis, with suggestions and edits from Dr. R. Marc Bustin, Dr. Erik Eberhardt, Dr. Lori Kennedy, and Dr. Stuart Sutherland. Additional edits were provided by colleagues, June Cho and Andrew Lee. viii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ....................................................................................................................... viii List of Tables ............................................................................................................................... xii List of Figures ............................................................................................................................. xvi List of Symbols ......................................................................................................................... xxix List of Abbreviations ............................................................................................................... xxxi Acknowledgements ................................................................................................................ xxxiii Dedication ............................................................................................................................... xxxiv Chapter 1: Introduction ................................................................................................................1 1.1 Motivation ....................................................................................................................... 1 1.2 Thesis Objectives ............................................................................................................ 4 1.3 Study Area, Wells and Formations of Interest ................................................................ 4 1.4 Thesis Organization ...................................................................................................... 10 Chapter 2: The Influence of Sample and Testing Parameters on Instrumented Indentation Results for Homogeneous Minerals and Heterogeneous Shales ..............................................11 2.1 Introduction ................................................................................................................... 11 2.2 Samples and Methods ................................................................................................... 15 2.2.1 Samples ..................................................................................................................... 15 2.2.2 Sample Preparation ................................................................................................... 15 ix 2.2.3 Hardness and Indentation Testing ............................................................................. 18 2.2.3.1 Background ....................................................................................................... 18 2.2.3.2 The Oliver and Pharr Method of Instrumented Indentation .............................. 19 2.2.3.3 Instrumented Indentation in this Study ............................................................. 23 2.2.4 Data Filtering, Contact Point Selection, and Contact Stiffness Threshold ............... 29 2.3 Results and Discussion ................................................................................................. 32 2.3.1 Indentation Results for Measurements on Homogeneous Samples .......................... 32 2.3.2 Effect of Sample Size on Indentation Results........................................................... 38 2.3.3 Effect of Maximum Indentation Load on Indentation Results ................................. 46 2.3.4 Effect of Number of Indentation Measurements on Indentation Results ................. 50 2.3.5 Effect of Measurement Type on Indentation Results ............................................... 56 2.3.6 Repeatability and Variability of Indentation Results in Shale .................................. 64 2.3.6.1 Indentation Test Mean Indentation Results ...................................................... 70 2.3.6.2 Subsample Mean Indentation Results ............................................................... 77 2.3.6.2.1 Unoriented Subsample Mean Indentation Results ...................................... 78 2.3.6.2.2 Assessing Geomechanical Anisotropy in Oriented Subsamples of Shale ... 84 2.3.6.3 Sample Mean Indentation Results .................................................................... 91 2.4 Chapter Conclusions ................................................................................................... 100 Chapter 3: Instrumented Indentation Analyses of Heterogeneous Shales: Comparing Drill Cuttings, Core Chips, and Core Plug Data..............................................................................105 3.1 Introduction ................................................................................................................. 105 3.2 Samples and Methods ................................................................................................. 107 3.2.1 Samples ................................................................................................................... 107 x 3.2.2 Sample Preparation ................................................................................................. 108 3.2.2.1 Indentation Samples ........................................................................................ 108 3.2.2.2 X-Ray Diffraction Samples ............................................................................. 109 3.2.3 Hardness and Indentation Testing ........................................................................... 110 3.2.3.1 Background ..................................................................................................... 110 3.2.3.2 The Oliver and Pharr Method of Instrumented Indentation ............................ 112 3.2.3.3 Instrumented Indentation in this Study ........................................................... 116 3.2.4 X-Ray Diffraction ................................................................................................... 120 3.3 Results and Discussion ............................................................................................... 122 3.3.1 Variability and Repeatability of Indentation Results .............................................. 122 3.3.2 An Overview of Geomechanical and Mineralogical Results and Comparison ...... 126 3.3.3 Comparing Shale Core Chips and Core Plug Data ................................................. 136 3.3.3.1 Shell Groundbirch 06-28-078-19W6 (025466) .............................................. 136 3.3.3.2 7GEN Redrock 01-20-063-08W6 (469253) ................................................... 141 3.3.3.3 7GEN Karr 09-23-064-04W6 (414232).......................................................... 147 3.3.3.4 7GEN HZ Karr 12-12-064-04W6 (466328) ................................................... 152 3.3.3.5 7GEN Kakwa 13-28-064-05W6 (456240) ...................................................... 157 3.3.4 Comparing Shale Core Chips, Drill Cuttings and Core Plug Data ......................... 163 3.3.4.1 Petronas et al., HZ Altares A01-32-083-25W6 (27400) ................................. 165 3.3.4.1.1 Comparison by Sample Type: Core Chips versus Drill Cuttings ............. 169 3.3.4.2 Progress Jedney C-004-F/094-G-08 (29010) .................................................. 176 3.3.4.2.1 Comparison by Sample Type: Core Chips versus Drill Cuttings ............. 181 3.4 Chapter Conclusions ................................................................................................... 186 xi Chapter 4: Conclusions .............................................................................................................198 4.1 Conclusions ................................................................................................................. 198 4.2 Industry Applications .................................................................................................. 202 4.2.1 Instrumented Indentation as an Application to Planned Completions .................... 202 4.3 Future Research and Recommendations ..................................................................... 205 Bibliography ...............................................................................................................................207 Appendices ..................................................................................................................................227 Appendix A - Data Quality, Troubleshooting, and Data Correction and Filtering ................ 227 A.1 Indentation Load-Displacement Curves ................................................................. 227 A.2 Contact Point Correction......................................................................................... 234 A.3 Initial Loading Displacement Jump ........................................................................ 238 A.4 Incomplete Loading and Spring Compliance Issues ............................................... 241 A.5 Unfiltered versus Filtered Data Comparison and the Effects of Contact Stiffness Threshold on Indentation Results. ...................................................................................... 247 Appendix B - Repeatability of Mean Indentation Results for Standard and CSS Measurement Types in Shale Drill Cuttings .................................................................................................. 255 Appendix C - Indentation Results, Geomechanical Depth Profiles, and Mineralogy of A01-32-083-25W6, Separated by Sampling Depth Interval ................................................................ 263 xii List of Tables Table 2.1: Measurement parameters and indentation results for different measurement types on quartz............................................................................................................................................. 31 Table 2.2: Indentation results and literature values for filtered standard measurements of Dolomite, Calcite, and Quartz. ..................................................................................................... 35 Table 2.3: Sample size labelling and mesh size to metric conversion. ......................................... 39 Table 2.4: Indentation results for 50 mN maximum load measurements made on dolomite, calcite and quartz, sorted by sample size. ................................................................................................ 42 Table 2.5: Indentation results for filtered measurements made on Montney-28 subsamples. ...... 43 Table 2.6: Test information and indentation results for measurements made on dolomite, calcite, and quartz, sorted by maximum indentation load. ........................................................................ 49 Table 2.7: Suggested number of indentations for dolomite, calcite, and quartz of various sample sizes. .............................................................................................................................................. 52 Table 2.8: Minimum suggested number of indentations for combined tests on core chip samples of well C-004-F/094-G-08. ........................................................................................................... 55 Table 2.9: Range of indentation parameters for Standard, LSS, and CSS measurement types in this study. ...................................................................................................................................... 56 Table 2.10: Indentation results for standard and constant strain sinus measurements on shale samples. Bold samples have standard and CSS results which were not repeatable. .................... 61 Table 2.11: Mean indentation modulus and standard deviation for repeated indentation testing in shale subsamples. Bolded values didn’t show repeatability. ........................................................ 74 xiii Table 2.12: Mean EIT for unoriented subsamples of shale. Bolded values do not show repeatability................................................................................................................................... 82 Table 2.13: Indentation results for oriented subsamples of shale. Bold values are not repeatable........................................................................................................................................................ 89 Table 2.14: Indentation results for samples of well 06-28-078-19W6, in order of descending sample depth. ................................................................................................................................ 95 Table 3.1: Indentation results and core plug data for samples of well 06-28-078-19W6. .......... 139 Table 3.2: Young's and Indentation Moduli for samples of well 01-20-063-08W6. .................. 142 Table 3.3: Indentation results, XRD mineralogy, and core plug data for samples of well 09-23-064-04W6. .................................................................................................................................. 149 Table 3.4: Indentation results, XRD mineralogy, and core plug data for samples of well 12-12-064-04W6. .................................................................................................................................. 153 Table 3.5: Indentation results, XRD mineralogy, and core plug data for samples of well 13-28-064-05W6. .................................................................................................................................. 158 Table 3.6: Indentation results, core plug data, and XRD mineralogy for core chips and drill cuttings samples. ......................................................................................................................... 166 Table 3.7: Range of indentation results, core plug data, and XRD mineralogy for core chips and drill cuttings sample types of A01-32-083-25W6. Square brackets indicate # of core plug data points ........................................................................................................................................... 171 Table 3.8: Es, Ed, and EIT for samples of well C-004-F/094-G-08, organized by sample depth...................................................................................................................................................... 178 xiv Table 3.9: Range of indentation results, core plug data, and XRD mineralogy for core chips and drill cuttings sample types of C-004-F/094-G-08. Square brackets indicate # of core plug data points. .......................................................................................................................................... 182 Table 3.10: Linear relationships between geomechanical moduli, separated by well and presented for all data and all data (excluding 12-12 and 13-28 samples). .................................................. 194 Table 3.11: Positive and negative correlations between indentation results, XRD mineralogy, and core plug mechanical data of wells 06-28, 01-20, 09-23, 12-12, and 13-28. ............................. 195 Table 3.12: Relationships between indentation results, mineralogy, and core plug mechanical data for samples of well A01-32-083-25W6. Data is presented for all samples and separated by sample type. Only linear correlations with R2 ≥ 0.3 are displayed; strong correlations (R2 ≥ 0.70) are bolded. CC = core chips; DC = drill cuttings. ....................................................................... 196 Table 3.13: Relationships between indentation results, mineralogy, and core plug mechanical data for samples of well C-004-F/094-G-08. Data is presented for all samples and separated by sample type. Only linear correlations with R2 ≥ 0.3 are displayed; strong correlations (R2 ≥ 0.70) are bolded. CC = core chips; DC = drill cuttings. ....................................................................... 197 Table A.1: Example dataset for select indentation measurements of sample RM1-A, well C-004-G/094-G-08 ................................................................................................................................. 233 Table A.2: Detected versus corrected contact point data. ........................................................... 238 Table A.3: Measurement parameters and unfiltered and filtered indentation results for indentations on 4 mesh sized dolomite. ...................................................................................... 248 Table A.4: Unfiltered versus filtered standard indentation measurement results for Set 1 shale samples. ....................................................................................................................................... 251 xv Table A.5: Comparing contact stiffness threshold in unfiltered and filtered indentation results of well 01-20-063-08W6 shale samples. ......................................................................................... 254 xvi List of Figures Figure 1.1: Schematic cross-section of the Montney Formation (Davies and Hume, 2016). ......... 5 Figure 1.2: Study area (inset) and wells of interest that are located in BC, connected by A – A’. 7 Figure 1.3: Study area (inset) and wells of interest that are located in AB, connected by B – B’. 8 Figure 1.4: Well log stratigraphic section of the Doig Phosphate and Montney Formation of 06-28-078-19W6. ................................................................................................................................. 9 Figure 2.1: Flowchart of instrumented indentation testing and data analysis in this study. ......... 14 Figure 2.2: Homogeneous mineral samples in polished, epoxied sample pucks. Sample size decreases left to right. Top left: Calcite, 4, 8 and >50 mesh. Top right: Quartz 4 and 4-20 mesh. Bottom, upper row: dolomite 4, 8, 20, 50 mesh; lower row: dolomite 70, 100, 170, and 230 mesh. ............................................................................................................................................. 16 Figure 2.3: Schematic diagram demonstrating shale subsamples oriented with bedding parallel (X1) versus bedding perpendicular (X3) to the direction of indentation. ..................................... 17 Figure 2.4: Polished heterogeneous laminated shale sample 7G-7 from sample Set 1, Montney Formation. Subsample 7G-7a (left) is oriented with bedding parallel, and 7G-7b (right) perpendicular, to direction of indentation. .................................................................................... 17 Figure 2.5: Example of an indentation measurement load-displacement curve, with annotation of indentation phases and variables (based on Oliver and Pharr, 2004). .......................................... 20 Figure 2.6: Schematic cross-section of indentation with key geometric variables of loading and unloading (based on Oliver and Pharr, 2004). .............................................................................. 21 Figure 2.7: Schematic, plan-view diagram distinguishing indentation measurements (black squares), indentation tests (encompassed by red squares), and subsamples of a shale sample (core xvii chips). Indentation results in this study are presented for individual indentation measurements, indentation tests, subsamples (multiple tests), and samples (multiple subsamples). .................... 26 Figure 2.8: Grid indentation set-up (white squares, background image) and example of sample surface before and after indentation measurements (inlays) on >4 mesh dolomite ..................... 27 Figure 2.9: ‘Jump’ in displacement upon initial loading, from 1124 nm to 2610 nm, representing over a third of the maximum indentation displacement for this measurement. This jump is likely due to pre-mature contact detection of the sample surface by the indenter tip. Inset (A) displays the associated P-h curve, which appears normal; and inset (B) displays a video microscope image of the residual indentation, labelled by the number 74. ................................................................ 30 Figure 2.10: Unfiltered and filtered indentation modulus data for standard, constant strain sinus, and linear strain sinus measurement type testing on quartz. Box-and-Whisker plots display median as the middle line; mean is denoted by an ‘x’ and is listed in Table 2.1; the interquartile range (IQR = Q3-Q1) and quartiles as upper (Q3) and lower (Q1) bounds of the box; and minimum (Q1-1.5*IQR) and maximum (Q3+1.5*IQR) as whiskers. .......................................... 32 Figure 2.11: EIT and HIT for all filtered indentation measurements on dolomite, calcite, and quartz............................................................................................................................................. 34 Figure 2.12: Indentation Modulus data for all filtered, standard indentation measurements on homogeneous samples of dolomite, calcite, and quartz. The range of literature indentation and Young’s moduli overlay data from this study (dashed outlines). ................................................. 36 Figure 2.13: Indentation Hardness data for all filtered, standard indentation measurements on homogeneous samples of dolomite, calcite, and quartz. ............................................................... 37 Figure 2.14: Indentation Modulus for 50mN maximum indentation load measurements on dolomite (blue) and calcite (red), sorted by sample size (decreasing size to the right). ............... 40 xviii Figure 2.15: Indentation measurement results for 50mN maximum indentation load measurements on dolomite (blue) and calcite (red), separated by mesh size. Dolomite of 170 mesh (yellow diamonds) and 230 mesh (orange triangles) are filtered from the dataset due to influence of epoxy on indentation results. .................................................................................... 41 Figure 2.16: Indentation modulus results for Montney-28 subsamples of >18, 18-20, and <20 mesh size. ...................................................................................................................................... 44 Figure 2.17: Indentation measurement results for 50mN maximum indentation load measurements on Montney - 28, separated by mesh size: > 18 mesh (circles), 18-20 mesh (diamonds), and < 20 mesh (triangles). ........................................................................................ 45 Figure 2.18: Indentation Modulus for dolomite (blue), calcite (red), and quartz (green), sorted by maximum indentation load (increasing Pmax left to right). ......................................................... 47 Figure 2.19: Indentation results for filtered measurements on dolomite (blue), calcite (red), and quartz (green), sorted by maximum indentation load. .................................................................. 48 Figure 2.20: Running mean of EIT for all indentation measurements on dolomite, calcite, and quartz samples, sorted by sample size. A maximum N = 100 is displayed. ................................. 53 Figure 2.21: Running mean EIT for indentations on core chip samples of well C-004-F/094-G-08. A maximum N = 100 is displayed. ............................................................................................... 55 Figure 2.22: EIT for standard and CSS measurements samples of well 01-20-063-08W6. Standard and CSS comparisons for a given sample are plotted as dark and light shades of the same colour (i.e. dark red and red display sample #1 standard [left] and CSS [right] results). Additional standard and CSS measurement comparisons are listed in Table 2.10. ........................................ 58 Figure 2.23: Standard and constant strain sinus indentation measurement comparisons for all 43 shale samples tested. ..................................................................................................................... 63 xix Figure 2.24: Indentation test, subsample, and sample mean indentation results. Inset shows a schematic diagram of sample 7G-4 (encompassed by a dashed black line), showing subsamples (blue lines) 7G-4a and 7G-4b, and example indentation test grids (red squares) composed of many indentation measurements. .................................................................................................. 66 Figure 2.25: Indentation results for indentation tests, and subsamples, of sample 7G-4. ............ 67 Figure 2.26: Indentation test, subsample, and sample mean EIT results. Inset shows a schematic diagram of sample 7G-7 (encompassed by a dashed black line), showing subsamples (blue lines) 7G-7a and 7G-7b, and example indentation test grids (red squares) composed of many indentation measurements. ............................................................................................................ 68 Figure 2.27: Indentation results for indentation tests, and subsamples, of sample 7G-7. ............ 69 Figure 2.28: Indentation modulus results for repeated indentation tests on shale subsamples of well 1-20-063-08W6. Colour pairs indicate repeated tests, with Test 1 on the left and Test 2 on the right of each pair. Each indentation test represents the results from N indentation measurements (Table 2.11). .......................................................................................................... 71 Figure 2.29: Indentation modulus results for repeated indentation tests on subsamples of Set 1 and Set 2 Montney Formation shales. Colour pairs indicate repeated tests, with Test 1 on the left and Test 2 on the right of each pair. Each indentation test represents the results from many indentation measurements. ............................................................................................................ 72 Figure 2.30: Indentation modulus results for repeated indentation tests for Montney Formation subsamples from wells 6-28-78-19W6, A01-32-83-25W6, C-004-F/094-G-08, and other shales. Colour pairs indicate repeated tests, with Test 1 on the left and Test 2 on the right of each pair. Each indentation test represents the results from many indentation measurements. .................... 73 xx Figure 2.31: Mean Indentation Modulus results for repeated tests on subsamples of shale core chips. Data for this figure is displayed in Table 2.11. .................................................................. 75 Figure 2.32: Indentation results for unoriented subsamples of shale. Associated data is listed in Table 2.12. .................................................................................................................................... 79 Figure 2.33: EIT results for indentation measurements on unoriented shale subsamples. Sample sets are colour-coded by well and subsamples of a sample are indicated by colour shades. Samples listed in the legend (top to bottom) are plotted left to right. .......................................... 80 Figure 2.34: Indentation modulus results indentation measurements of subsamples of other shales. Colour pairs indicate subsamples. Samples listed in the legend (top to bottom) are plotted left to right..................................................................................................................................... 81 Figure 2.35: Mean Indentation modulus of compared oriented subsamples of shale. .................. 85 Figure 2.36: EIT results for indentation measurements on oriented subsamples of wells 06-28-078-19W6 (yellow), 09-23-064-04W6 (green), and C-004-F/094-G-08 (purple). Subsamples oriented with bedding parallel to the direction of indentation are labelled as “X1”; perpendicular are labeled “X3”. ........................................................................................................................... 87 Figure 2.37: EIT results for indentation measurements on oriented subsamples of sample Set 1. Subsamples oriented with bedding parallel to the direction of indentation are labelled with “X1”, whereas subsamples with bedding perpendicular are labelled with “X3”. ................................... 88 Figure 2.38: Mean indentation modulus versus mean indentation hardness, sorted by formation........................................................................................................................................................ 92 Figure 2.39: Mean indentation modulus versus mean indentation hardness, sorted by well........ 92 Figure 2.40: Indentation Modulus for samples of well 06-28-078-19W6. Samples are ordered descending in depth from left to right. Colour groups indicate stratigraphic groupings xxi (Grey=Doig Phosphate; Purple=MNTN E1; Pink=MNTN E4; Blue=MNTN D; Green=MNTN C; Red=MNTN B). ....................................................................................................................... 93 Figure 2.41: Indentation Modulus versus Depth for samples of well 06-28-078-19W6. ............. 94 Figure 2.42: Mean Indentation Hardness versus Indentation Modulus for samples of well 06-28-078-19W6. .................................................................................................................................... 94 Figure 2.43: Indentation Modulus vs Depth for PHOS (top), MNTN E1 (middle), and MNTN E4 (bottom) samples of well 06-28-078-19W6. Error bars display standard deviation of mean EIT. 98 Figure 2.44: Indentation Modulus vs Depth for MNTN D (top), MNTN C (middle), and MNTN B (bottom) samples of well 06-28-078-19W6. Error bars display standard deviation of mean EIT........................................................................................................................................................ 99 Figure 3.1: Polished heterogeneous shale samples of sample Set 1. From left to right: 7G-1 to 7G-4 (top); 7G-6 to 7G-9 (middle); 7G-10 to 7G-13, 7G-15 (bottom). Subsamples in Set 1 are oriented with bedding parallel (left) and perpendicular (right) to direction of indentation. ....... 109 Figure 3.2: XRD smear mount samples of well 01-20-063-08W6. ............................................ 110 Figure 3.3: Example of an indentation measurement load-displacement curve, with annotation of indentation phases and variables (based on Oliver and Pharr, 2004). ........................................ 113 Figure 3.4: Schematic cross-section of indentation with key geometric variables of loading and unloading (based on Oliver and Pharr, 2004). ............................................................................ 113 Figure 3.5: Schematic, plan-view diagram distinguishing indentation measurements (black squares), indentation tests (encompassed by red squares), and subsamples of a shale sample (core chips). Indentation results in this study are presented for individual indentation measurements, indentation tests, subsamples (multiple tests), and samples (multiple subsamples). .................. 118 xxii Figure 3.6: Grid indentation set-up (white squares, background image) and example of sample surface before and after indentation measurements (inlays) on >4 mesh dolomite ................... 119 Figure 3.7: Example of an XRD diffractogram, with analyzed phases of sample RM4-A. ....... 121 Figure 3.8: Mean EIT results for comparisons of indentation test (top-left), oriented and unoriented subsamples (middle-right), and standard and CSS measurement types (bottom-left)...................................................................................................................................................... 124 Figure 3.9: Summary of sample types and results examined in this study. Chapter 2 focused on upscaling indentation results (highlighted in orange). Chapter 3 focuses on the comparison of indentation results, XRD mineralogy, and core plug data (highlighted in red). ......................... 125 Figure 3.10: Sample mean indentation results for core chips and drill cuttings shale samples, organized by formation. .............................................................................................................. 127 Figure 3.11: Sample mean indentation results for core chips and drill cuttings shale samples, organized by well. ....................................................................................................................... 128 Figure 3.12: Es-EIT (top), Ed- EIT (middle), and Es-Ed (bottom) cross-plots for all mean indentation results and core plug static and dynamic Young’s modulus data. 1:1 ratio is displayed as dotted black line...................................................................................................................... 130 Figure 3.13: Geomechanical correlations between mean EIT, Es, and Ed for samples of wells 01-20-063-08W6, 12-12-063-04W6, and 09-23-064-04W6. ........................................................... 131 Figure 3.14: Geomechanical correlations between mean EIT, Es, and Ed for samples of wells 13-28-064-05W6, 06-28-078-19W6, A01-32-083-25W6, and C-004-F/094-G-08. ........................ 132 Figure 3.15: XRD mineralogy of core chip and drill cuttings (DC) shale samples, sorted by well (top) and formation (bottom). Values are normalized weight % for quartz and feldspar, carbonates, and clays. ................................................................................................................. 134 xxiii Figure 3.16: XRD mineralogy versus mean EIT, mean HIT, depth, Es, and Ed (columns, left to right) for all samples in this study. Mineralogy is displayed as wt. % of quartz, carbonates, feldspar, and clays (rows, top to bottom). ................................................................................... 135 Figure 3.17: Geomechanical-depth profiles for stratigraphic units of well 06-28-078-19W6. Top to bottom, left column: Doig Phosphate (PHOS) and Montney Formation lobes MNTN E1 and MNTN E4; right column: MNTN D, MNTN C, and MNTN B. ................................................ 140 Figure 3.18: Geomechanical depth profile of well 01-20-063-08W6, displaying similar trends in Es, Ed, and mean EIT between samples. ..................................................................................... 143 Figure 3.19: XRD mineralogy versus mean EIT, mean HIT, and depth (columns, left to right) for samples of well 01-20-063-08W6. Mineralogy is displayed as wt. % of quartz, carbonates, feldspar, and clays (rows, top to bottom). ................................................................................... 144 Figure 3.20: XRD mineralogy (wt. %) versus static (Es) and dynamic (Ed) Young's modulus from core plug data of well 01-20-063-08W6. ........................................................................... 145 Figure 3.21: Geomechanical depth profile of well 09-23-064-04W6. ........................................ 150 Figure 3.22: XRD mineralogy versus geomechanical moduli for samples of well 09-23-064-04W6. .......................................................................................................................................... 151 Figure 3.23: Geomechanical-depth profile of well 12-12-064-04W6. ....................................... 154 Figure 3.24: XRD mineralogy versus geomechanical moduli for samples of well 12-12-064-04W6. .......................................................................................................................................... 156 Figure 3.25: Geomechanical-depth profile of well 13-28-064-05W6. ....................................... 159 Figure 3.26: XRD mineralogy versus geomechanical moduli for samples of well 13-28-064-05W6. .......................................................................................................................................... 162 xxiv Figure 3.27: Standard indentation results from shale core chips and drill cuttings of well A01-32-083-25W6. .................................................................................................................................. 164 Figure 3.28: Standard indentation results from shale core chips and drill cuttings of well C-004-F/094-G-08. ................................................................................................................................. 164 Figure 3.29: Geomechanical depth profile of all samples of well A01-32-083-25W6. Geomechanical depth profiles are separated by sampling depth intervals in Appendix C. ........ 167 Figure 3.30: XRD mineralogy versus geomechanical moduli for all samples of well A01-32-083-25W6. R2 is displayed in the bottom-left corner for each plot. .................................................. 168 Figure 3.31: Indentation results for all shale core chips samples of well A01-32-083-25W6. .. 172 Figure 3.32: Indentation results for all shale drill cuttings samples of well A01-32-083-25W6...................................................................................................................................................... 173 Figure 3.33: XRD mineralogy versus geomechanical moduli for core chips samples of well A01-32-083-25W6. ............................................................................................................................. 174 Figure 3.34: XRD mineralogy versus indentation results for drill cuttings samples of well A01-32-083-25W6. ............................................................................................................................. 175 Figure 3.35: Geomechanical depth profile for all samples of well C-004-F/094-G-08. ............. 179 Figure 3.36: Geomechanical moduli (columns) versus XRD mineralogy (weight %, rows), for all core chips and drill cuttings samples of well C-004-F/094-G-08. .............................................. 180 Figure 3.37: Geomechanical moduli (columns) versus XRD mineralogy (weight %, rows), for core chips samples of well C-004-F/094-G-08. .......................................................................... 183 Figure 3.38: Mean EIT (left column), mean HIT (middle column), and depth (right column) relationships with weight % XRD mineralogy (rows, top to bottom: Quartz; Carbonates; Feldspar; and Clays), for drill cuttings samples of well C-004-F/094-G-08. ............................. 184 xxv Figure 3.39: Geomechanical correlations for Montney Formation samples. Plots show mean EIT versus Es (top) and Ed (bottom) core plug data. Geomechanical data for 12-12 and 13-28 are excluded to poor sampling reliability and samples from disaggregated core of the Belloy Formation. ................................................................................................................................... 189 Figure 4.1: Actual completions vs “planned” completions based on hypothetical mean EIT from drill cuttings samples. Hypothetical and estimated drill cuttings results are extended for a 5 m sampling interval. ........................................................................................................................ 204 Figure A.1: Video microscope images (top) and load-displacement curves (bottom) for indentation measurements 1, 16, 17, and 19 of sample RM1-A, well C-004-G/094-G-08. Indentations were made on mineral grains, displaying residual indentations. ........................... 229 Figure A.2: Video microscope images (top) and load-displacement curves (bottom) for indentation measurements 7, 8, 9, and 21 of sample RM1-A, well C-004-G/094-G-08. Indentations were made in locations of low topography or matrix but still display surface contact and complete P-d curves. ............................................................................................................ 232 Figure A.3: Correct contact point selection (modified from Indentation Software Manual, Anton Paar). ........................................................................................................................................... 235 Figure A.4: Detected (top) and corrected (bottom) contact point for measurement 2, dolomite 4 mesh sample) .............................................................................................................................. 236 Figure A.5: Jump in displacement during initial loading and contact, with inlays of the P-d curves (left) and a video microscope image of the residual indentation (right). ........................ 240 Figure A.6: Load-displacement (top), load (middle), and displacement (bottom) curves for indentation measurements 11, 16, 25, 26, and 27 of sample RM1-A. ........................................ 242 xxvi Figure A.7: video microscope images of indentation measurements 11, 16, 25, 26, and 27 of sample RM1-A, well C-004-G/094-G-08. Residual indentations can be seen in the middle of the red dotted triangle. ...................................................................................................................... 243 Figure A.8: Theoretical spring compliance correction to change the approach phase slope of the load curve (modified from A Indentation Software Manual, p.118). ......................................... 245 Figure A.9: Contact point correction window in indentation software, displaying non-rectilinear load curve approach slope due to spring compliance error. ........................................................ 246 Figure A.10: Unfiltered and filtered indentation modulus data for standard indentations on >4 mesh sized dolomite. ................................................................................................................... 248 Figure A.11: Unfiltered (left) and filtered (right) colour-paired EIT results for standard measurements on samples of Set 1 Montney Formation shales. ................................................ 250 Figure A.12: Unfiltered versus filtered mean EIT for standard measurements on Set 1 Montney Formation shales. ........................................................................................................................ 252 Figure A.13: Indentation modulus results for unfiltered (top) and filtered (bottom) measurements at 500 µN/µm and 1000 µN/µm contact stiffness threshold for shale samples of well 01-20-063-08W6. Colours indicate stiffness threshold pairs and samples (i.e. dark red indicates sample #1 at 1000 µN/µm stiffness threshold; light red indicates sample #1 at 500 µN/µm). ........................ 253 Figure B.1: Mean EIT for Standard and CSS measurements on core chip and drill cuttings subsamples. Combined core chips and drill cuttings correlation is R2 = 0.91. ........................... 256 Figure B.2: Standard and CSS indentation results for drill cuttings of shallow sampling depth, well C-004. .................................................................................................................................. 257 Figure B.3: Standard and CSS indentation results for drill cuttings of moderate sampling depth, well C-004. .................................................................................................................................. 258 xxvii Figure B.4: Standard and CSS indentation results for drill cuttings of deep sampling depth, well C-004........................................................................................................................................... 259 Figure B.5: Standard and CSS indentation results for drill cuttings of shallow sampling depth, well A01-32. ............................................................................................................................... 260 Figure B.6: Standard and CSS indentation results for drill cuttings of moderate and deep sampling depths, well A01-32. ................................................................................................... 261 Figure B.7: EIT results for standard and CSS measurements on core chips and drill cuttings, plotted as colour pairs (i.e. darkest yellow = DC-1780m standard [left] and CSS [right]). ....... 262 Figure C.1: Indentation results for first sampling depth interval (2310 – 2345 m) samples of well A01-32-083-25W6. ..................................................................................................................... 263 Figure C.2: Geomechanical-depth profile for first sampling depth interval (2310 – 2345 m) samples of well A01-32-083-25W6. ........................................................................................... 264 Figure C.3: XRD mineralogy versus geomechanical moduli for first sampling depth interval (2310 – 2345 m) samples of well A01-32-083-25W6. ............................................................... 265 Figure C.4: Indentation results for second sampling depth interval (2455 – 2465 m) samples of well A01-32-083-25W6. ............................................................................................................. 266 Figure C.5: Geomechanical-depth profiles for second sampling depth interval (2455 – 2465 m) samples of well A01-32-083-25W6. ........................................................................................... 267 Figure C.6: XRD mineralogy versus geomechanical moduli for second sampling depth interval (2455 – 2465 m) samples of well A01-32-083-25W6. ............................................................... 268 Figure C.7: Indentation results for the third sampling depth intveral (2524 – 2542 m) samples of well A01-32-083-25W6. ............................................................................................................. 269 xxviii Figure C.8: Geomechanical-depth profile for the third sampling depth interval (2524 – 2542 m) samples of well A01-32-083-25W6. ........................................................................................... 270 Figure C.9: XRD mineralogy versus geomechanical moduli for the third sampling depth interval (2524 – 2542 m) samples of well A01-32-083-25W6. ............................................................... 271 xxix List of Symbols Symbol Definition Units 𝐴 or 𝐴𝑃 Area of indentation, or Projected contact area 𝑚2 E Young’s modulus GPa Es Static Young’s Modulus GPa Ed Dynamic Young’s Modulus GPa EdlowP Dynamic Young’s Modulus at low axial confining pressure GPa EdhighP Dynamic Young’s Modulus at high axial confining pressure GPa 𝐸𝑟 Reduced or deduced modulus GPa E* Plane strain modulus GPa 𝐸𝐼𝑇 or EIT Indentation Modulus GPa 𝐸𝑖 Young’s modulus of indenter tip GPa h Indentation depth under applied test force; displacement m ℎ𝑐 Contact depth of the indenter at 𝐹𝑚 m ℎ𝑚 or ℎ𝑚𝑎𝑥 Maximum indentation depth; maximum displacement m ℎ𝑝 or ℎ𝑓 Permanent indentation depth m ℎ𝑟 Tangent indentation depth m ℎ𝑆 Sink-in depth m H Hardness MPa 𝐻𝐼𝑇 or HIT Indentation Hardness MPa 𝐻𝑉𝐼𝑇 Vicker’s hardness calculated from 𝐻𝐼𝑇 Vickers (kgf/mm2) xxx m Power law exponent n/a P; F Load or Force mN Pmax; Fmax Maximum load mN S Stiffness N / m 𝛼 Power law fitting constant n/a β Correction factor n/a ϵ Geometric constant n/a ϕ Half-angle constant ° ν Poisson’s ratio n/a ν𝑖 Poisson’s ratio of indenter tip n/a ν𝑆 Poisson’s ratio of sample n/a MPa MegaPascal 106 𝑃𝑎 GPa GigaPascal 109 𝑃𝑎 mN milliNewton 10−3 𝑁 µm Micrometer 10−6 𝑚 nm Nanometer 10−9 𝑚 ± Plus/Minus n/a xxxi List of Abbreviations AB Alberta AER Alberta Energy Regulator BC British Columbia BCOGC British Columbia Oil and Gas Commission CC Core Chips CRC Core Research Centre CRD Collaborative Research and Development CRF Core Research Facility CSS Constant Strain Sinus DC Drill Cuttings Fm. Formation IQR Interquartile Range LSS Linear Strain Sinus N Number of Indentation Measurements Nmin Minimum suggested number of indentation measurements NE North East NHT2 Anton Paar NHT2 Indenter NSERC Natural Sciences and Engineering Research Council of Canada P-h Load-displacement Q1 First Quartile xxxii Q3 Third Quartile SD Standard Deviation SE Standard Error of the Mean SUB Subsample TXC Triaxial Compression UBC University of British Columbia UCS Uniaxial Compression U of C University of Calgary WCSB Western Canadian Sedimentary Basin xxxiii Acknowledgements To all of the faculty, staff, and students that I have encountered, worked with, and befriended at UBC, I thank you from the bottom of my heart. Attending this institution has provided memories and experiences that I will cherish for the rest of my life. To my supervisor, Dr. Marc Bustin, thank you for your continuous support and countless opportunities. I appreciate your wisdom, realism, and unique sense of humour. Thank you for not giving up on me. A special thanks to those I love most in this world: my parents, sisters, girlfriend and friends. Thank you for supporting me through this journey of higher education. Your unwavering love is the reason I have made it this far. xxxiv Dedication To my loving family, friends, and colleagues: What do you call a geologist that looks back fondly on his time in university? Sedimental. 1 Chapter 1: Introduction 1.1 Motivation The application of multi-stage hydraulic fracturing completions in horizontal wellbores has significantly improved production from unconventional shale reservoirs worldwide (King, 2012). The lateral length of horizontal wells have progressively increased through time in order to access more reservoir (Spain et al., 2015; Siegel, 2014), and longer wells require more completion intervals (stages); however, it has been suggested that up to 60 % of the stages do not contribute to production (Miller et al., 2011) due to failure of fracture initiation and propagation, or closure of fractures. Design of hydraulic fracturing is based, in part, on understanding geomechanical properties along a wellbore lateral. Therefore, in order to optimize fracture completions and production, it is important to understand mineralogy, rock mechanics, and geomechanics of unconventional shale reservoirs (Cadwallader et al., 2015; Britt and Schoeffler, 2009). Drill cuttings samples, sampled at regular intervals during the drilling of a well, can be analyzed with X-Ray diffraction (XRD) to quantify mineralogy, whereas instrumented indentation can be used to characterize geomechanical properties of a wellbore (e.g. Glover et al., 2016). Instrumented indentation has been used to characterize the mechanical properties of shale samples, but few studies have extensively applied the technique to very small samples and actual drill cuttings. The technique was first developed to characterize the indentation mechanical properties of homogeneous materials, such as thin films (e.g. Mencik et al., 1997; Saha and Nix, 2001), metals, ceramics, and minerals (e.g. Joslin and Oliver, 1990; Oliver and Pharr, 1992; Broz et al., 2006). More recently, instrumented indentation has been applied to heterogeneous 2 materials, including cement, cement asphalt, and cement pastes (e.g. Constantinides et al., 2003; Barbhuiya and Caracciolo, 2017; Brown et al., 2018), bone (e.g. Donnelly et al., 2006; Tai et al., 2006) and other biomaterials (Katti et al., 2006), metal cathodes (Amanieu et al., 2014), clays (e.g. Pal-Bathija et al., 2008; Pant, 2013), and kerogen and organic content (e.g. Zeszotarski et al., 2004; Alstadt et al., 2015). In addition, various rocks including granite (Viktorov et al., 2014), sandstone (Sun et al., 2016), carbonates (e.g. Lebedev et al., 2014; Ban et al., 2014; Vialle et al., 2018), coal (Yu et al., 2018), and shales have been analyzed with instrumented indentation. In shales, indentation experiments have primarily focused on formations across the United States, including the Antrim (e.g. Monfared et al., 2018), Bakken (e.g. Liu et al., 2018), Barnett (Abousleiman et al, 2009), Collingwood (e.g. Shukla et al., 2013), Eagle Ford (e.g. Gupta et al., 2018), Fayetteville (e.g. Abedi et al., 2016a), Green River (e.g. Alstadt, Katti and Katti, 2015), Haynesville (e.g. Akrad, Miskimins and Prasad, 2011), Kimmeridge (e.g. Goodarzi et al., 2017), Marcellus (e.g. Mason et al., 2014), Monterey (Ante et al., 2018), Niobrara (e.g. Corapcioglu, Miskimins and Prasad, 2014), Ordovician (e.g. Kumar et al., 2012), Pottsville (e.g. Du and Radonjic, 2018), Tuscaloosa Marine Shale (Miller, 2016), Woodford (Li and Sakhaee-Pour, 2016), and Wolfcamp (Mighani et al., 2015) Formations. Indentation studies have also tested shale samples from the Longmaxi Formation in China (e.g. Han et al., 2015), and the Vaca Muerta Formation (Boulenouar et al., 2017) and samples from the Middle Magdalena Valley basin (Carreno P., et al., 2018) of South America. The few studies that have applied instrumented indentation to the Montney Formation (Qiu et al., 2018; Glover et al., 2016) focused on indentation mechanical properties of shale core chips. Where instrumented indentation holds the most promise for geomechanical wellbore characterization is its ability to test small samples, such as shale drill cuttings. As a by-product of 3 the drilling process, drill cuttings offer a recoverable, cost-effective and depth-controlled source of samples to be characterized. Several previous studies have investigated the ability of instrumented indentation to test artificial or actual drill cuttings. For example, Abousleiman et al. (2009) investigated drill cutting sized Woodford shale chips, sieved as low as No. 20 mesh size, making 1350 indentations across a block of epoxy and core chip cuttings. Kumar et al. (2012) crushed and tested two core plugs of Woodford shale into 3 – 5 mm artificial cuttings demonstrating no effect of epoxy on indentation results, which had mean values in between vertical and horizontal core plug indentation results. Han et al. (2018) tested actual drill cuttings from the Longmaxi Formation. Indentation results on drill cuttings averaged 20.2 GPa, showing good agreement with a well-log interpreted static elastic modulus of 21.4 GPa. Martogi and Abedi (2019) used artificially made cuttings from shales with known mechanical properties to assign transverse isotropic properties to anisotropic, but randomly oriented, drill cuttings. Glover et al. (2016) compared artificial cuttings from core plug ends of the Wolfcamp Formation, receiving similar results indentation moduli results to static Young’s modulus (Es) results from triaxial compression testing. In addition to artificial cuttings, actual drill cuttings from the Eagleford Formation were then indented with 10’s to 100’s of measurements per sample depth interval (Glover et al., 2016). The resulting mean indentation modulus versus static Young’s modulus cross-plot shows limited linear correlation. An additional nine, 5 – 10 m intervals were sampled, indented, and used to create a geomechanical wellbore profile for planned completions optimization (Glover et al., 2016). 4 1.2 Thesis Objectives Building on previous indentation studies that analyzed shale drill cuttings, the primary objective of this study is to assess the utilization of instrumented indentation for characterizing the geomechanical variability of core chips and drill cuttings based on those sampled from the Montney Formation. Mean indentation results from shale core chips and drill cuttings are compared to core plug mechanical properties, in attempt to correlate and upscale geomechanical moduli. X-ray diffraction is used to quantify mineralogy of samples, adding context to indentation results. Through the creation of wellbore geomechanical and mineralogical profiles, it is intended these objectives can contribute towards identifying optimization opportunities where hydraulic fracturing stages can target depths or intervals with favourable wellbore conditions. 1.3 Study Area, Wells and Formations of Interest The area of interest for this study is the Western Canadian Sedimentary Basin (WCSB), specifically in northeast British Columbia (BC) and western Alberta (AB). The main formation of interest in this study area is the lower Triassic Montney Formation (Figure 1.1). The Montney Formation is the most productive unconventional reservoir in Canada (Davies et al., 2018), containing an estimated 12,719 billion m3 (449 Tcf) of natural gas, 2,308 million m3 (14,521 million barrels) of natural gas liquids, and 179 million m3 (1,125 million barrels) of oil (NEB, 2013). Since 2005, multi-stage hydraulic fracturing and horizontal drilling technologies have made the unconventional siltstones of this significant resource a viable target for development (NEB, 2013). 5 Figure 1.1: Schematic cross-section of the Montney Formation (Davies and Hume, 2016). The Montney Formation is bounded by a basal contact that is unconformable throughout most of the basin (Zonneveld and Moslow, 2018). It largely overlays the Permian Belloy Formation, with underlying strata progressively eroded to the Carboniferous Debolt Fm. in the northeast corner of the basin (Zonneveld and Moslow, 2018). In the study area, the Doig Formation conformably overlays the Montney (Edwards et al., 1994), though the Montney Formation is eroded and overlain by the Coplin unconformity to the East. The maximum thickness of the Montney Formation is approximately 350m, thinning to the west and south (Edwards et al., 1994). The formation is interpreted as a shallow-water marine, interbedded sandstone and shale of deltaic origin, transitioning basinward as western-trending, deeper-water, inner to distal-shelf deposits interpreted as turbidites and tempestites (Edwards et al., 1994). Figure 1.2 and Figure 1.3 show the wells of interest in this study in map view, connected by two cross-section lines: A – A’ connected wells located in BC, and B-B’ connected wells 6 located in Alberta. In BC, samples were studied from wells C-004-F/094-G-08 (C-004), A01-32-083-25W6 (A01-32), and 06-28-078-19W6 (06-28). Figure 1.4 shows the stratigraphy of the Doig Phosphate and Montney Formation of well 06-28. In AB, samples were studied from wells 01-20-063-08W6 (01-20), 13-28-064-05W6 (13-28), 09-23-064-04W6 (09-23), and 12-12-064-04W6 (12-12). Additional Montney Formation samples were sourced from an undisclosed well, as part of a consortium research group (outlined in Chapter 2). Additional samples were acquired and tested from the Duvernay Formation of the WCSB in Canada, as well as the Barnett, Eagleford, Haynesville, and Wolfcamp Formations in the United States. 7 Figure 1.2: Study area (inset) and wells of interest that are located in BC, connected by A – A’. 8 Figure 1.3: Study area (inset) and wells of interest that are located in AB, connected by B – B’. 9 Figure 1.4: Well log stratigraphic section of the Doig Phosphate and Montney Formation of 06-28-078-19W6. 10 1.4 Thesis Organization This thesis is organized into 4 chapters, with Chapters 2 and 3 designed to be able to be read as standalone manuscripts. Chapter 1 introduces the theme of the thesis and provides a brief overview of the study area and formation of interest. Chapter 2 evaluates the influence of sample and indentation measurement parameters on indentation results. Upscaling and repeatability of mean indentation results are assessed at various scales of measurement, in homogeneous mineral and heterogeneous shale samples. Chapter 3 provides further analyses of heterogeneous shale samples through instrumented indentation and X-ray diffraction (XRD). Indentation and XRD analyses are performed on shale core chips and drill cuttings, then indentation results, XRD mineralogy, and core plug mechanical data are compared to assess geomechanical and mineralogical relationships. These comparisons demonstrate the utility of instrumented indentation and XRD analyses for characterizing geomechanical and mineralogical variability of a wellbore. Chapter 4 presents thesis conclusions, applications of this research to industry and to planned hydraulic fracture completions and discusses possible extensions of this research. 11 Chapter 2: The Influence of Sample and Testing Parameters on Instrumented Indentation Results for Homogeneous Minerals and Heterogeneous Shales 2.1 Introduction Horizontal wells, with lateral lengths of several kilometers and multiple isolated stages of hydraulic fracture completions, have become the prevalent way of exploiting shale reservoirs (King, 2010; King, 2012; Clarkson et al., 2016). While lithology and geomechanical properties along the lateral length of a wellbore may change, hydraulic fracture completions are treated the same and often spaced at even intervals. Characterizing changes in lithology and the variability of geomechanical properties is an important step towards optimizing hydraulic fracture completions in horizontal wellbores (Spain et al., 2015). With an understanding of the variability along a wellbore lateral, planned completions stages can be placed in locations of optimal lithology and geomechanical properties for fracture initiation and propagation. Typically, core plugs that are used to test geomechanical properties are sampled from recovered cored intervals of a well; however, core from lateral portions of a horizontal wellbore are difficult and expensive to recover. Drill cuttings present a cost-effective alternative to core and core plug samples (Abousleiman et al., 2009), as they are byproducts of the drilling process that can be sampled regularly while drilling, including through the lateral portion of a horizontal well. The ability to characterize lithology and geomechanical properties from small samples remains a challenge; however, instrumented indentation is a technique that can characterize mechanical properties to the nanoscale. 12 Instrumented indentation has been applied to the characterization of mechanical properties of homogeneous materials since the mid 1980’s (Loubet et al., 1984; Doerner and Nix, 1986; Oliver and Pharr, 1992; 2004). Presently, instrumented indentation applies the Oliver and Pharr (1992; 2004) technique, which calculates an indentation hardness and modulus based on an indenter tip penetrating a sample to a designated maximum load or displacement. Instrumented indentation assumes that the sample being tested is homogeneous and has isotropic mechanical properties. Initially, the technique was applied to a variety of materials, such as thin films, ceramics, metals, and minerals (e.g. Oliver and Pharr, 1992; Saha and Nix, 2001; Broz et al., 2006). More recently, instrumented indentation has been used to characterize heterogeneous materials, such as cements (e.g. Constantanides et al., 2003), biomaterials (e.g. Donnelly et al., 2006), and rocks such as shale (e,g, Ulm et al., 2006). Applying this technique to heterogeneous samples adds complexity to indentation results, as each component has unique mechanical properties. The multiphase composition of shales, for example, causes variation in mechanical properties by component and scale (Ulm et al., 2007). Previous researchers have used instrumented indentation to gain a better understanding of the nanoscale mechanical behavior of shale and the cause of shale anisotropy at various scales (e.g. Constantinides et al., 2006; Ulm and Abousleiman, 2007; Ortega et al., 2007; Bobko and Ulm (2007). Instrumented indentation has also been applied to drill cutting sized shale samples (e.g. Abousleiman et al., 2009; Kumar et al., 2012) and actual drill cuttings (e.g. Glover et al., 2016), comparing indentation results to more common methods of geomechanical analysis such as compression testing of core samples. To assess the utility of indentation results as an index of rock moduli in heterogenous shale drill cuttings samples, several assumptions need to be tested (Figure 2.1). First, the effects 13 of indentation measurement parameters, including sample size, maximum indentation load, number of measurements, and measurement type were examined for their effects on indentation results. Optimal indentation parameters were selected for subsequent indentation measurements on shale samples, to ensure representative results from indentation measurements. Second, indentation results from measurements on shale core chips were assessed at multiple scales, using mean indentation results and a measure of repeatability to demonstrate reliability of indentation results. Indentation results were compared at multiple scales of measurement, starting with indentation tests on a single subsample, where each mean indentation test result combined the results of many indentation measurements. Repeatability of indentation test results assessed the similarity of indentation results for two or more tested areas of a single subsample. Indentation results were then compared for shale subsamples, where each subsample mean indentation result combined the results of all indentation measurements from all indentation tests performed on that subsample. Repeatability of subsample indentation results assessed the similarity of indentation results for two or more subsamples of the same shale sample. Lastly, indentation results were compared between samples, where each sample mean indentation result combined the results of all indentation measurements, from all indentation tests, from all subsamples of that sample. Sample mean indentation results were used to demonstrate variability in indentation mechanical properties between samples and the usefulness of instrumented indentation as a technique. 14 Figure 2.1: Flowchart of instrumented indentation testing and data analysis in this study.15 2.2 Samples and Methods 2.2.1 Samples Single crystals of the minerals dolomite, calcite, and quartz, and shales of the Montney, Belloy, and Doig Formations of northeast British Columbia and Alberta, make of the majority of samples tested in this study. Eleven samples from other shale formations – including the Duvernay, Barnett, Eagleford, Haynesville, and Wolfcamp Formations – were sourced in house and tested, for comparison. In total, 124 shale samples were collected from the same sample depths as core plugs (or directly from core plugs) that were previously tested by uniaxial and triaxial compression tests. Public geomechanical data from these core plugs was compared to indentation results in subsequent studies. 2.2.2 Sample Preparation Mineral samples were crushed and sieved into sample sizes between 4 mesh (4760 µm) and 230 mesh (63 µm), and mounted in 2.5 cm diameter, circular plexiglass tubing with epoxy (Figure 2.2). Shale samples were crushed into subsamples and mounted with bedding oriented parallel (X1), perpendicular (X3), or at random (unoriented), with respect to the direction of indentation (Figure 2.3; Figure 2.4). To minimize the effects of sample surface roughness on indentation results, samples were ground with 240 and 600 grit silicon carbide paper, then polished sequentially with 0.3 µm aluminum oxide powder and colloidal silica. Between grinding and polishing steps, the samples were rinsed and placed in an ultrasonic bath for 2 minutes. Samples were dried for at least 24 hours before indentation testing. 16 Figure 2.2: Homogeneous mineral samples in polished, epoxied sample pucks. Sample size decreases left to right. Top left: Calcite, 4, 8 and >50 mesh. Top right: Quartz 4 and 4-20 mesh. Bottom, upper row: dolomite 4, 8, 20, 50 mesh; lower row: dolomite 70, 100, 170, and 230 mesh. 17 Figure 2.3: Schematic diagram demonstrating shale subsamples oriented with bedding parallel (X1) versus bedding perpendicular (X3) to the direction of indentation. Figure 2.4: Polished heterogeneous laminated shale sample 7G-7 from sample Set 1, Montney Formation. Subsample 7G-7a (left) is oriented with bedding parallel, and 7G-7b (right) perpendicular, to direction of indentation. 18 2.2.3 Hardness and Indentation Testing 2.2.3.1 Background One of the earliest comparisons of hardness is Mohs (1825) hardness scale, which is better classified as a measure of scratch resistance than hardness (Broz et al., 2006) because it measures the ability of one material to scratch another. Hardness, H, indicating the resistance of a material to permanent deformation (Fischer-Cripps, 2004; Broz et al., 2006), is numerically equal to the contact area, A, under a maximum load, Pmax (Oliver and Pharr, 1992; 2004), defined as: 𝐻 =𝑃𝑚𝑎𝑥𝐴 (1) Indentation methods, including Brinell, Knoop, Vicker’s, and Rockwell tests, were developed to test hardness by using a material of known mechanical properties to indent a material of unknown properties (Fischer-Cripps, 2004). Indentation methods differ by the way indentation results are calculated, the scale of indentation, and the geometry of the indenter tip used; in this study, indentation methods are divided into manual and instrumented indentation. Manual indentation methods, including traditional versions of Brinell, Knoop, Vicker’s and Rockwell tests, require the user to measure the area of the residual indentation impression in order to calculate hardness (Oliver & Pharr, 1992; Fischer-Cripps, 2004). Indentation displacements for manual indentation methods are often measured in millimeters (10-3 m). Instrumented indentation testing, with measurement precision at the micrometer (10-6 m) and nanometer (10-9 m) scales, is automated, recording load and displacement at a selected frequency throughout loading and unloading cycles. Indentation hardness is then calculated 19 based on an area that is a function of the depth of indenter penetration into a sample and the geometry of the indenter tip (Fischer-Cripps, 2004). For nanoscale (indentation displacement of 10-9 m to 10-6 m) instrumented indentation testing, a 3-sided, pyramidal Berkovich indenter is most commonly used as it’s easier to construct the Berkovich tip to an accurate, single point (50 – 200 nm tip radius) (Fischer-Cripps, 2004), compared to 4-sided, pyramidal Vickers or Knoop indenters. Accurate indenter tip shape geometry is important as the indentation area used in the hardness calculation is measured by a calibrated area function of indenter displacement and geometry. At low loads, and minimal displacement of the indenter into a sample, only a small portion of the indenter may penetrate the sample, therefore the indenter tip needs to be as true to the geometry of the rest of the indenter as possible to obtain accurate results. At higher loads and displacements, more of the indenter penetrates the sample, therefore the exact geometry of the indenter tip is less important than the geometry of the indenter at a point higher up on the indenter. 2.2.3.2 The Oliver and Pharr Method of Instrumented Indentation The current standard for instrumented indentation testing of homogeneous materials (ASTM E2546 – 15, 2015) is largely based on the techniques proposed by Oliver and Pharr (1992; 2004). In the Oliver and Pharr technique (1992; 2004), instrumented indentation begins with an approach phase where the indenter tip (a Berkovich diamond, in this study) is lowered until contact is made with the sample surface, initiating the loading phase. During the loading phase, load, P, and displacement, h, are measured as the indenter tip penetrates the sample material. The load increases until a (preset) maximum indentation load, Pmax, or maximum displacement, hmax, is reached. An optional hold phase may be set at the maximum load or 20 displacement, after which the indenter is unloaded. Load, hold, and unload phases may be customized to desired loading rates or durations. Figure 2.5 shows an example of a load-displacement (P-h) curve received from each instrumented indentation measurement. Figure 2.6 shows a schematic cross-section of an indentation through loading and unloading cycle, displaying important geometric variables such as the permanent depth of penetration, hf. Figure 2.5: Example of an indentation measurement load-displacement curve, with annotation of indentation phases and variables (based on Oliver and Pharr, 2004). 21 Figure 2.6: Schematic cross-section of indentation with key geometric variables of loading and unloading (based on Oliver and Pharr, 2004). Using the initial slope of the unloading section of the P-h curve, elastic unloading stiffness, S, is calculated as: 𝑆 = 𝑑𝑃𝑑ℎ (2) Unloading curves are approximated by a power law relation: 𝑃 = 𝛼(ℎ𝑚𝑎𝑥 − ℎ𝑓)𝑚 (3) Where α and 𝑚 are power law fitting constants. According to Oliver & Pharr (2004), it is assumed that the pyramidal Berkovich indenter behavior can be modeled by a conical indenter by applying a half-angle, ϕ, of 70.3° to give the same depth-to-area relationship; that contact surfaces sink as flat elastic half-space models of similar geometry; and that pile up of sample material around a residual indentation is negligible. Following these assumptions, sink-in, hs, is estimated as: 22 ℎ𝑠 = ϵPmaxS, (4) where ϵ = 0.75 is a geometric constant of the indenter. Using hs to approximate contact surface displacement, the depth that contact is made between the indenter and sample, hc = hmax - hs, is: ℎ𝑐 = ℎ𝑚𝑎𝑥 − 𝜖𝑃𝑚𝑎𝑥S , (5) An indenter shape area function, F(ℎ𝑐), is created through the calibration of the indenter tip. Knowing the difference between displacement caused by initial contact, and maximum displacement, the indenter area function is used to calculate the contact area of the indentation: 𝐴𝑃 = 𝐹(ℎ𝑐) (6) Indentation Hardness can then be estimated as: 𝐻𝐼𝑇 =𝑃𝑚𝑎𝑥𝐴𝑝 (7) HIT is a measure of apparent hardness – the material resistance to the combined plastic and elastic deformation (Fischer-Cripps, 2011). For this reason, it tends to be less than true hardness in materials with significant elastic recovery (Fischer-Cripps, 2011). Unloading stiffness also allows the calculation of indentation elastic moduli through the following equations: Reduced Modulus, 𝐸𝑟: 𝐸𝑟 = √𝜋 𝑆2 𝛽 √𝐴𝑝(ℎ𝑐) (8) Where β is a dimensionless correction factor; β = 1.034 for a Berkovich diamond indenter. 23 Plane Strain Modulus, 𝐸∗, can then be calculated using 𝐸𝑟, the elastic modulus of the indenter (𝐸𝑖) , and Poisson’s ratio of the indenter (𝑣𝑖): 𝐸∗ = 11𝐸𝑟−1 − 𝑣𝑖2𝐸𝑖 (9) Where 𝐸𝑖 = 1141 GPa, and 𝑣𝑖 = 0.07 for a diamond Berkovich tip indenter. Using an estimated Poisson’s ratio of the sample being indented, 𝑣𝑠, Indentation Modulus, 𝐸𝐼𝑇, can be calculated: 𝐸𝐼𝑇 = 𝐸∗(1 − 𝑣𝑠2) (10) The default 𝑣𝑠 = 0.30 was used for dolomite and calcite samples in this study; for quartz a 𝑣𝑠 =0.17 was used. Based on the Poisson’s ratios associated with pre-existing static and dynamic measurements on shale core plug data, a 𝑣𝑠 = 0.25 was used for indentation measurements on shale. Uncertainty in a Poisson’s ratio of 0.25 ± 0.1 results in an approximate 5% uncertainty in resulting elastic modulus (Hay and Pharr, 2000). 2.2.3.3 Instrumented Indentation in this Study Instrumented indentation in this study is performed using an Anton Paar NHT2 Indenter (NHT2). A single indentation is referred to as an indentation measurement (Figure 2.7). Indentation measurements are calibrated on a fused silica standard with a mean EIT of 73.2 ± 0.3 GPa and mean HIT of 9450 ± 550 MPa. The motorized stage of the NHT2 Indenter allows for pre-selection of multiple indentation measurement sites, which can be automatically analyzed in 24 the order they are selected. A pre-selected list of multiple indentation measurements made subsequently is referred to as an indentation test (Figure 2.7). Indentation software is used to pre-select measurement sites in grid patterns (Figure 2.8), or as individual points where sample size is limited. Spacing between indentation measurements, and from sample-epoxy boundaries, is selected as 100 µm or 200 µm to ensure sufficient indentation spacing of at least 10 times indentation depth (Sudharshan Phani and Oliver, 2019). Indentation tests are performed on mineral and shale samples to assess the effects of sample size, maximum indentation load, number of indentation measurements, and measurement type (Figure 2.1). Optimal sample and indentation parameters will be applied to subsequent indentation studies on Montney Formation shales. Standard and Sinus measurement types are tested in this study. Standard measurements follow the load-hold-unload cycle of instrumented indentation, with load increasing linearly to a designated 𝑃𝑚𝑎𝑥 (or maximum displacement). Sinus measurements differ by applying a sine wave oscillation during the loading process, providing a depth-related analysis within 1 cycle of indentation. Sinus measurements are further defined by loading method into Linear Strain Sinus (LSS) and Constant Strain Sinus (CSS) measurements: LSS measurements load with a linear increase in strain, whereas CSS measurements load with a constant strain rate. CSS measurements are particularly useful where the mechanical properties of the sample material are strain rate dependent, or a depth-based assessment of indentation results are desired. Regardless of indentation type, prior to data analysis indentation results are filtered and corrected for data quality assurance. 25 In this study, indentation results are presented at various scales of measurement (Figure 2.7): • An indentation result is calculated for each indentation measurement. • Mean indentation results presented for an indentation test combine the results of all indentation measurements in that test. • Mean indentation results presented for a subsample combine the results of all indentation measurements for all tests on that subsample. • Mean indentation results presented for a sample combine the results of all indentation measurements, for all tests, on all subsamples of that sample. 26 Figure 2.7: Schematic, plan-view diagram distinguishing indentation measurements (black squares), indentation tests (encompassed by red squares), and subsamples of a shale sample (core chips). Indentation results in this study are presented for individual indentation measurements, indentation tests, subsamples (multiple tests), and samples (multiple subsamples). 27 Figure 2.8: Grid indentation set-up (white squares, background image) and example of sample surface before and after indentation measurements (inlays) on >4 mesh dolomite Repeatability of indentation results is also tested at multiple scales of measurement. Repeatability of indentation testing is assessed using two-sample t-Tests assuming unequal variances. For a significance level of 0.05, this t-Test measures the probability that the difference of sample mean indentation result is within a 95% confidence interval of a common population mean. Mean indentation results that display a t-statistic lower than the critical value are designated as similar, or repeatable. When the t-statistic for compared indentation test results is 28 greater than the critical value, indentation results are examined for factors affecting repeatability, such as measurement parameters, representative testing and sampling, and shale anisotropy. Repeated testing (i.e. Test 1, Test 2, etc.) indicates two or more indentation tests performed on the same subsample, where each test is composed of many indentation measurements (Figure 2.1; Figure 2.7). Repeatability assesses whether mean indentation results from Test 1 is statistically similar to results from Test 2, suggesting: (i) the reliability of instrumented indentation as a technique for characterizing indentation mechanical properties; and (ii) whether individual indentation tests provide results that are representative of subsample indentation mechanical properties. Where mean indentation results are statistically different for repeated tests on the same subsample, possible explanations for this difference are given. Repeatability of indentation results are also compared for different subsamples of the same sample. Subsample indentation results combine the results of all indentation tests on a given subsample. Comparing mean indentation results from multiple subsamples of the same sample allows: (i) the assessment of subsample heterogeneity (i.e. the effects of orientation and mechanical anisotropy); and (ii) the determination whether indentation results from individual subsamples are representative of sample indentation mechanical properties. Where mean indentation results are statistically different for subsamples of the same sample, possible explanations are given. In addition to comparing indentation test and subsample results, repeatability is used to compare sample indentation results. Sample indentation results combine the results of all indentation tests on all subsamples of a sample. Comparing sample mean indentation results assesses: (i) the variability of indentation results between samples; and (ii) the usefulness of instrumented indentation as a technique for characterizing indentation mechanical properties. 29 2.2.4 Data Filtering, Contact Point Selection, and Contact Stiffness Threshold Data quality assurance in this research involved data filtering, correcting the contact point for every indentation measurement, and assessing contact stiffness threshold. Common errors, occurring due to instrument error related to material surface contact detection, include jumps in displacement upon initial loading (Figure 2.9), contact point detection and correction, and incomplete and erroneous loading. The parameter that defines initial contact between the indenter and sample material – contact stiffness threshold – is also compared at 500 µN/µm and 1000 µN/µm. The processes of troubleshooting and minimizing error are described in greater detail in Appendix A . In this study, “unfiltered’ indentation data includes results from all measurements; “filtered” data has removed measurements with erroneous and incomplete data, contact detection complications, and jumps in displacement. Both unfiltered and filtered datasets have corrected contact points, where possible. An example of unfiltered versus filtered data is displayed in Table 2.1 and Figure 2.10. Data presented throughout this paper is filtered unless otherwise stated. 30 Figure 2.9: ‘Jump’ in displacement upon initial loading, from 1124 nm to 2610 nm, representing over a third of the maximum indentation displacement for this measurement. This jump is likely due to pre-mature contact detection of the sample surface by the indenter tip. Inset (A) displays the associated P-h curve, which appears normal; and inset (B) displays a video microscope image of the residual indentation, labelled by the number 74. 31 Sample Measurement Parameters Measurement Type Mean EIT, Unfiltered (GPa) Mean EIT, Filtered (GPa) Quartz Sample Size 4 mesh (4760 um) Maximum Indentation Load 100 mN Stiffness Threshold 500 µN/µm Standard 86.9 ± 8.2 (N = 25) 79.6 ± 4.1 (N = 9) Constant Strain Sinus 79.2 ± 12.1 (N = 25) 80.0 ± 2.6 (N = 12) Linear Strain Sinus 78.6 ± 8.9 (N = 25) 78.1 ± 9.1 (N = 18) Table 2.1: Measurement parameters and indentation results for different measurement types on quartz. 32 Figure 2.10: Unfiltered and filtered indentation modulus data for standard, constant strain sinus, and linear strain sinus measurement type testing on quartz. Box-and-Whisker plots display median as the middle line; mean is denoted by an ‘x’ and is listed in Table 2.1; the interquartile range (IQR = Q3-Q1) and quartiles as upper (Q3) and lower (Q1) bounds of the box; and minimum (Q1-1.5*IQR) and maximum (Q3+1.5*IQR) as whiskers. 2.3 Results and Discussion 2.3.1 Indentation Results for Measurements on Homogeneous Samples Instrument calibration on fused silica provides reference indentation results to which indentation results from measurements of other materials are compared. Mean EIT measurements on the fused silica reference standard measure 73.3 ± 1.0 GPa, compared to the certified EIT of 33 73.2 ± 0.3 GPa. Mean HIT results measure 9705 ± 305 MPa compared to reference standard HIT of 9450 ± 550 MPa. Following calibration measurements on fused silica, indentation measurements are made on random crystal faces of samples of single crystal dolomite, calcite, and quartz. Filtered indentation results for standard measurements made on dolomite, calcite, and quartz, are combined to assess the variation in indentation modulus and indentation hardness across all measurement parameters. Figure 2.11 combines results from standard measurements made at 𝑃𝑚𝑎𝑥 of 5, 25, 50, 100, 200, and 500 mN; on 4, 8, 20, 50, 70, and 100 mesh sample sizes; for tests of any number of indentation measurements; at 500 or 1000 µN/µm contact stiffness thresholds. Measurements made on 170 and 230 mesh size samples are not included in combined indentation results, as indentation results on samples this small are inaccurate and not representative of the material being tested. Mean indentation modulus for all measurements made on dolomite, calcite, and quartz in this study are compared to literature values of indentation and Young’s moduli (Table 2.2), comparing the instrumented indentation technique in this study to other indentation studies, and common methods of geomechanical analysis. The influence of sample size, maximum indentation load, number of indentation measurements, and measurement type are investigated, then the repeatability of indentation results are discussed for tests on shale core chip samples. 34 Figure 2.11: EIT and HIT for all filtered indentation measurements on dolomite, calcite, and quartz. 35 Sample Mean 𝑬𝑰𝑻 (GPa) Literature E or 𝑬𝑰𝑻 (GPa) Source Dolomite 92.6 ± 13.8 E: 87 - 142 Bakri and Zaoui, 2011 Calcite 57.9 ± 3.5 E: 69 – 98 Simmons & Wang, 1971 𝐸𝐼𝑇: 78.1 ± 5.2 Broz et al., 2006 𝐸𝐼𝑇: 79 ± 1; 83 ± 1; 87 ± 1 Kumar et al., 2012 𝐸𝐼𝑇: 66.05 ± 2.12 (geological) 𝐸𝐼𝑇: 65.51 ± 1.93 (biogenic) Bohm et al., 2019 Quartz 82.5 ± 5.2 E: 90 – 100 Simmons & Wang, 1971 E: 77 – 96 Mavko et al., 2009 E*: 117 ± 3 Broz et al., 2006 E*: 99 ± 1 Kumar et al., 2012 Sample Mean 𝑯𝑰𝑻 (MPa) Literature H or 𝑯𝑰𝑻 (MPa) Source Dolomite 4185 ± 591 – – Calcite 1951 ± 125 𝐻𝐼𝑇: 2210 ± 160 Broz et al., 2006 𝐻𝐼𝑇: 2750 ± 50 (geological) 𝐻𝐼𝑇: 4380 ± 320 (biogenic) Bohm et al., 2019 Quartz 9067 ± 1146 𝐻𝐼𝑇: 14540 ± 420 Broz et al., 2006 Table 2.2: Indentation results and literature values for filtered standard measurements of Dolomite, Calcite, and Quartz. 36 Figure 2.12: Indentation Modulus data for all filtered, standard indentation measurements on homogeneous samples of dolomite, calcite, and quartz. The range of literature indentation and Young’s moduli overlay data from this study (dashed outlines). 37 Figure 2.13: Indentation Hardness data for all filtered, standard indentation measurements on homogeneous samples of dolomite, calcite, and quartz. Mean EIT results for all standard indentation measurements on dolomite, calcite, and quartz are 92.6 ± 13.8 GPa, 57.9 ± 3.5 GPa, and 82.5 ± 5.2 GPa, (Figure 2.12). Mean EIT of dolomite and quartz overlap with core plug literature Young’s moduli values of 87 – 142 GPa (Bakri and Zaoui, 2011) and 77 – 100 GPa (Simmons & Wang, 1971; Mavko et al., 2009). Calcite mean EIT is lower than literature E of 69 – 98 GPa (Simmons & Wang, 1971) and EIT of 65.5 ± 1.9 to 87 ± 1 GPa (Broz et al., 2006; Kumar et al., 2012; Bohm et al., 2019). 38 Mean 𝐻𝐼𝑇 results are 4185 ± 591 MPa, 1951 ± 125 MPa, and 9067 ± 1146 MPa for standard indentation measurements on dolomite, calcite, and quartz (Table 2.2; Figure 2.13). Mean 𝐻𝐼𝑇 of calcite is close to literature values of 2210 ± 160 MPa (Broz et al., 2006) and 2750 ± 50 (Bohm et al., 2019). Mean 𝐻𝐼𝑇 for quartz in this study is less than literature 𝐻𝐼𝑇 of 14540 ± 420 (Broz et al., 2006). Variation in indentation mechanical properties can be attributed to source and crystal orientation (Broz et al., 2006; Kumar et al., 2012; Bohm et al., 2019), as well as the combination of indentation results for measurements across a wide range of samples and measurement parameters. As expected for homogeneous materials, instrumented indentation can be used to distinguish each mineral, which plot in distinct ranges of EIT and HIT (Figure 2.11). In the following sections, indentation results are analyzed for the effects of sample size, maximum indentation load, number of indentations measurements, and measurement type. Repeatability of indentation results, and the variability indentation results between samples, are then assessed at various scales. 2.3.2 Effect of Sample Size on Indentation Results For instrumented indentation to be an effective tool for characterizing the mechanical properties of drill cuttings, the technique must yield reliable measurements on small sample sizes. The effect of sample size on indentation results is thus assessed to see how small samples can be before indentation measurements became unreliable. In general, samples size must be large enough that indentation measurements can be made without influence from sample boundaries or other indentations. Sudharshan Phani and Oliver (2019) suggest minimum indentation spacing between indentations of 1.5 times the indent contact’s lateral width, or 10 39 times indentation depth, halving common spacing criteria of 20 times indentation depth suggested by Samuels and Mulhearn (1957). Sudharshan Phani and Oliver (2019) made their conclusions based on large arrays of indentations (1225 indents) and finite element analysis on fused silica, aluminum, copper, polycarbonate, calcium fluoride, nickel and molybdenum, measured to defined maximum indentation depths (600 – 1000 nm). Their measurements were made at varying ratios of indent spacing to maximum indentation depth (5 to 20) and results showed insignificant deviation in hardness for indentation spacing ≥10 times indentation depth (Sudharshan Phani and Oliver, 2019). To assess the effects of particle size dolomite, calcite, and quartz are tested at sample sizes ranging from >4 mesh to <230 mesh (Table 2.3). Label Sample Mesh Size Sample Size, X (µm) 4 mesh > 4 mesh X ≥ 4760 8 mesh 4 - 8 mesh 4760 > X ≥ 2380 20 mesh 8 - 20 mesh 2380 > X ≥ 841 50 mesh 20 – 50 mesh 841 > X ≥ 297 70 mesh 50 – 70 mesh 297 > X ≥ 210 100 mesh 70 - 100 mesh 210 > X ≥ 177 170 mesh 100 - 170 mesh 177 > X ≥ 88 230 mesh < 230 mesh 63 > X Table 2.3: Sample size labelling and mesh size to metric conversion. Indentation spacing recommendations of at least 10 times indentation depth (Sudharshan Phani and Oliver, 2019) are applied to all indentation measurements. Dolomite is sieved and tested at all listed mesh sizes; calcite is tested at 4, 8, and >50 mesh; and quartz at 4 and 4-20 40 mesh size. Calcite and quartz are not tested at all sample sizes due to experimental time constraints, or due to filtering of poor-quality indentation data. Indentation results are compared for measurements made at 𝑃𝑚𝑎𝑥 of 50 mN (Figure 2.14; Figure 2.15), as this maximum indentation load was applied on every sample size. Indentation results made at other 𝑃𝑚𝑎𝑥 show similar trends with sample size. Figure 2.14: Indentation Modulus for 50mN maximum indentation load measurements on dolomite (blue) and calcite (red), sorted by sample size (decreasing size to the right). 41 Figure 2.15: Indentation measurement results for 50mN maximum indentation load measurements on dolomite (blue) and calcite (red), separated by mesh size. Dolomite of 170 mesh (yellow diamonds) and 230 mesh (orange triangles) are filtered from the dataset due to influence of epoxy on indentation results. Dolomite samples of size 100 mesh (177 µm) or larger have mean 𝐸𝐼𝑇 between 83.7 ± 9.2 GPa and 103.3 ± 13.2 GPa, which are repeatable and in agreement with values reported by Bakri and Zaoui (2011) of 87 to 142 GPa. Mean 𝐸𝐼𝑇 for dolomite of 170 mesh and 230 mesh sample sizes are not repeatable when compared to results from larger sample sizes of dolomite and are below literature values, measuring 72.3 ± 10.8 GPa, and 51.1 ± 8.0 GPa. Mean maximum displacement also increases from approximately 750 nm for sample sizes 4 mesh through 100 mesh, to 806 nm and 880 nm for 170 mesh and 230 mesh sample sizes. At 170 and 230 mesh sample size, the mechanical properties of underlying or surrounding epoxy is influencing 42 dolomite indentation results: epoxy has an approximate mean EIT of 5 GPa, HIT of 200 MPa, and relatively high hmax for any given load. The relatively low indentation modulus and hardness, and high hmax, of surrounding epoxy lowers mean indentation results of dolomite due to a composite indentation response of epoxy and 170 mesh size or smaller dolomite. Calcite of 4, 8, and >50 mesh sample sizes have mean 𝐸𝐼𝑇 (56.5 ± 3.7 to 59.1 ± 4.4 GPa) and 𝐻𝐼𝑇 (1903 ± 127 to 1972 ± 99 MPa) results that are repeatable. Sample Sample Size Number of Indentations, N Mean hmax (nm) Mean EIT (GPa) Standard Error of the Mean EIT (GPa) Mean Indentation Hardness, HIT (MPa) Dolomite 4 mesh 93 748 ± 37 99.3 ± 15.1 1.6 4430 8 mesh 21 734 ± 26 86.4 ± 10.0 1.2 4846 20 mesh 28 723 ± 41 103.3 ± 13.2 2.1 4786 50 mesh 60 778 ± 46 85.9 ± 13.0 1.6 4210 70 mesh 21 780 ± 36 87.5 ± 10.6 8.2 4139 100 mesh 48 762 ± 27 83.7 ± 9.2 4.9 4449 170 mesh 23 806 ± 43 72.3 ± 10.8 2.5 4074 230 mesh 41 880 ± 72 51.1 ± 8.0 2.2 3818 Calcite 4 mesh 15 1102 ± 34 59.1 ± 4.4 1.1 1926 8 mesh 60 1090 ± 23 58.6 ± 3.1 0.6 1972 > 50 mesh 59 1111 ± 31 56.5 ± 3.7 0.4 1903 Table 2.4: Indentation results for 50 mN maximum load measurements made on dolomite, calcite and quartz, sorted by sample size. 43 In homogeneous dolomite of sample size ≥100 mesh, and calcite ≥50 mesh, indentation results are reliably measured. In heterogeneous shales, the complexity of shale composition, scale, and fabric may result in variation in mechanical properties (Ulm et al., 2007) and must be considered when comparing indentation results. To test for the effects of shale sample size on indentation results, sample Montney-28 was subsampled into >18 mesh (> 1000 µm), 18-20 mesh (1000-841 µm), and <20 mesh (< 841 µm) sample sizes. These sample sizes are representative of the smallest lengths of artificial and actual shale drill cuttings from previous studies, which have ranged 1000 – 5000 µm (Abousleiman et al., 2009; Kumar et al., 2012; Glover et al., 2015). Sixty to 110 indentation measurements are made on 4 or 5 subsamples, per sample. Measurements are made in a grid pattern, or point-selected where grids are not feasible due to sample size. Indentations are made with maximum indentation loads of 100 mN and 200 µm spacing between indentations and sample edges. Only filtered indentation measurements are included in mean indentation results (Table 2.5). Sample Sample Size Number of Indentations, N Mean EIT Standard Deviation (GPa) Standard Error of Mean EIT (GPa) Mean Indentation Hardness, HIT (MPa) Mean hmax (nm) Montney – 28 >18 mesh 37 53.4 ± 11.1 1.8 4779 1247 ± 263 18-20 mesh 94 53.8 ± 13.1 1.3 4933 1224 ± 258 <20 mesh 26 47.9 ± 15.5 3.0 4383 1377 ± 396 Table 2.5: Indentation results for filtered measurements made on Montney-28 subsamples. 44 Figure 2.16: Indentation modulus results for Montney-28 subsamples of >18, 18-20, and <20 mesh size. 45 Figure 2.17: Indentation measurement results for 50mN maximum indentation load measurements on Montney - 28, separated by mesh size: > 18 mesh (circles), 18-20 mesh (diamonds), and < 20 mesh (triangles). For Montney-28 subsamples of sizes >18 mesh size, 18 – 20 mesh, and <20 mesh, mean 𝐸𝐼𝑇 results are 53.4 ± 11.1 GPa, 53.8 ± 13.1 GPa, and 47.9 ± 15.5 GPa (Table 2.5; Figure 2.16; Figure 2.17). No significant difference is found between mean subsample indentation moduli at a 95% confidence level, based on two-tail t-Tests, suggesting the sample size of the tested shale does not impact mean results. In summary, indentation testing can be performed on sample sizes as small as 100 mesh (177 µm) in minerals, and < 20 mesh (< 841 µm) in shale, without any influence on indentation results. Variation is observed in both mineral and shale samples: in minerals, variation is due to 46 fractures, crystal orientation, and sample surface roughness; whereas the multi-component, multi-scale nature of shale adds additional complexity to indentation results, expressed through higher standard deviation (SD) of mean indentation results. 2.3.3 Effect of Maximum Indentation Load on Indentation Results With indentation testing, the area of an indentation scales with an increasing maximum indentation load. When testing heterogeneous, multi-component materials, such as shales, maximum indentation load (or displacement) should be selected based on scale of interest. For example, in fine-grained shales, loads which achieve nanoscale displacement often measure individual material phases (e.g. Bobko and Ulm, 2007), whereas higher loads reaching microscale displacement measure properties of the composite material (e.g. Bennett et al., 2015), depending on rock composition, fabric, and the placement of indentation measurements. In this study, the scale of interest guiding maximum indentation load is one that: (i) creates an indentation area and displacement large enough to measure a composite material response; and (ii) produces repeatable indentation results, in shale samples. Load-controlled indentation measurements are made on dolomite, calcite, and quartz samples at Pmax between 5 mN and 500 mN. Sample types are not tested at the same maximum indentation loads due to experimental time constraints, or due to filtering of poor-quality indentation data. As the relatively hard components of shale, dolomite, calcite, and quartz load experiments are used to determine Pmax for subsequent testing in shales. 47 Figure 2.18: Indentation Modulus for dolomite (blue), calcite (red), and quartz (green), sorted by maximum indentation load (increasing 𝑷𝒎𝒂𝒙 left to right). 48 Figure 2.19: Indentation results for filtered measurements on dolomite (blue), calcite (red), and quartz (green), sorted by maximum indentation load. Dolomite samples display an overall trend of decreasing 𝐸𝐼𝑇 with increasing 𝑃𝑚𝑎𝑥 (Figure 2.18; Table 2.6), though the range of indentation results aren’t significantly affected by load (Figure 2.19). Mean 𝐸𝐼𝑇 ranges from 100.7 ± 13.3 GPa at a 𝑃𝑚𝑎𝑥 of 5 mN to 82.2 ± 7.8 GPa at 500 mN 𝑃𝑚𝑎𝑥. Mean 𝐸𝐼𝑇 values are repeatable for t-Test comparisons when comparing 5 mN and 25 mN loads, and between 50, 100, and 200 mN loads, suggesting an influence of load on indentation results. Excluding measurements made at 𝑃𝑚𝑎𝑥 of 500 mN, mean 𝐸𝐼𝑇 results compare well to literature Young’s modulus values for dolomite of 87 – 142 GPa (Bakri and Zaoui, 2011). 49 Calcite samples tested to maximum indentation loads of 25 mN and 50 mN produce repeatable mean 𝐸𝐼𝑇 of 58.3 ± 3.1 GPa and 57.7 ± 3.7 GPa, and 𝐻𝐼𝑇 of 1994 ± 133 MPa and 1937 ± 118 MPa. Quartz samples indented to a 𝑃𝑚𝑎𝑥 between 10 mN and 200 mN have 𝐸𝐼𝑇 results ranging 81.4 ± 7.3 GPa to 85.1 ± 3.2 GPa. Mean indentation results for quartz do not show a distinct trend, are repeatable, and are comparable to literature Young’s modulus for quartz of 77 – 96 GPa (Mavko et al., 2009). Sample Max Indentation Load (mN) Number of Indentations, N Mean Indentation Modulus, EIT (GPa) Mean EIT Standard Deviation (GPa) Standard Error of Mean (GPa) Mean Indentation Hardness, HIT (MPa) Dolomite 5 8 100.7 13.3 4.7 4444 25 33 99.8 13.0 2.3 4788 50 271 92.1 14.8 0.9 4431 100 174 92.3 12.3 0.9 3871 200 39 90.2 9.7 1.6 3822 500 8 82.2 7.8 2.8 4058 Calcite 25 44 58.3 3.1 0.5 1994 50 134 57.7 3.7 0.4 1937 Quartz 10 16 81.4 7.3 1.8 8378 25 24 82.3 5.4 1.1 8697 50 15 85.1 2.3 0.6 9531 100 31 81.7 4.5 1.2 8958 200 27 85.1 3.2 0.6 10046 Table 2.6: Test information and indentation results for measurements made on dolomite, calcite, and quartz, sorted by maximum indentation load. 50 Overall, indentation measurements in homogeneous materials produce repeatable indentation mechanical responses for moderate maximum indentation loads of 50 mN to 200 mN. Indentation measurements at high and low extremes of Pmax are more susceptible to errors in measurement. For example, sample surface roughness may lead to erroneous surface contact detection by the indenter at low loads. At the highest Pmax (500 mN for the NHT2), the larger indented area and greater displacement may measure a more inclusive, composite response, but this response is also at greater risk of influence from surrounding or underlying epoxy, imperfect leveling of the sample surface, and more prone to the effects of macro- or micro-fractures, or irregularities, in the sample. Depending on the capabilities of the instrument, type of sample material, and scale of interest, different values of Pmax should be selected. In this study, a composite mechanical response is targeted; therefore, the highest maximum indentation load that provides repeatable indentation results – 200 mN – is selected for subsequent standard indentation measurements on Montney Formation shales. 2.3.4 Effect of Number of Indentation Measurements on Indentation Results The number of indentation measurements, N, made on a sample is an important variable as a minimum N is required for mean indentation results to be representative of a multi-component material. The number of indentation measurements possible is limited by sample type, sample size, indentation size, and spacing between indentations and from sample edges. In previous indentation studies of shales, N generally ranged between 100 to 500 (e.g. Bobko and Ulm, 2007; Shukla et al., 2013; Bennett et al., 2015; Abedi et al., 2016a, 2016b; Yang et al., 2016; Boulenar et al., 2017; Fu et al., 2017; Li et al., 2018). 51 In most papers, no direct method for determining minimum N is stated. For grid nanoindentation (e.g. Bobko and Ulm, 2007), N is based on a grid size that is much larger than the area of an indentation and the size of individual material phases. At higher loads, when measuring composite materials, this separation of scale criterion breaks down as indentation measurements become larger than constituent phases. For 350 mN load indentations, a running mean of indentation results is used by Miller (2016) to suggest a minimum N = 40 for Tuscaloosa Marine Shale, and Liu et al. (2017) suggests a N = 80 for Bakken Formation shales. Though not explicitly stated, it is interpreted that these two works select minimum N based on where additional measurements no longer significantly change running mean results. Other studies have suggested minimum N based on indentation grids being larger than a representative elementary area of a sample (e.g. Liu et al., 2018). In this study, a running mean is calculated using indentation results from different indentation tests on mineral and shale samples. The number of indentation measurements dictates the number of indentation results that are included in the running mean of each sample. Indentation results are considered ‘stable’ when additional indentation measurements no longer cause the running mean of EIT to fluctuate outside of 2 standard error (SE) of the final mean value. The minimum N required to meet this 2 SE threshold for a given sample is described as the minimum suggested N, Nmin. The highest value of Nmin for each sample type provides a guideline for future studies, suggesting the minimum number of indentation measurements that should be made on each sample for representative mean indentation results. When the stability cutoff is applied to indentation results from testing on dolomite, calcite, and quartz of different sample sizes, a stable running mean is observed for Nmin between 6 and 61 (Figure 2.20; Table 2.7). Taking the highest Nmin value for indentation testing on 52 mineral samples, N ≥ 61 is suggested for future studies to provide representative mean indentation results for dolomite, calcite, or quartz. While a lower N may provide representative mean indentation results in some samples, a higher N better accounts for any heterogeneities that may be present in a sample or set of samples. Sample Number of Indentations, N Mean EIT (GPa) 2*Standard Error of the Mean, 2*SE Mean EIT ± 2*SE Minimum Suggested N, Nmin Dolomite 4 mesh 306 94.2 ± 13.4 1.5 92.7 – 95.7 60 Dolomite 8mesh 40 90.7 ± 11.1 3.5 87.2 – 94.2 22 Dolomite 20 mesh 66 101.0 ± 14.5 3.6 97.4 – 104.2 37 Dolomite 50 mesh 60 85.9 ± 12.9 3.3 82.6 – 89.2 12 Dolomite 70 mesh 21 87.5 ± 10.4 4.5 83.0 – 92.0 10 Dolomite 100 mesh 48 83.7 ± 9.1 2.6 81.1 – 86.3 32 Calcite 4 mesh 15 59.1 ± 4.4 2.2 56.9 – 61.3 6 Calcite 8 mesh 84 58.3 ± 3.0 0.7 57.6 – 59.0 61 Calcite >50 mesh 79 57.1 ± 3.8 0.8 56.3 – 57.9 27 Quartz 4 mesh 46 81.5 ± 5.3 1.6 79.9 – 83.1 29 Quartz 4-20 mesh 81 83.1 ± 5.1 1.1 82.0 – 84.2 37 Table 2.7: Suggested number of indentations for dolomite, calcite, and quartz of various sample sizes.53 Figure 2.20: Running mean of EIT for all indentation measurements on dolomite, calcite, and quartz samples, sorted by sample size. A maximum N = 100 is displayed. 54 Due to the complexity of shale, it is expected that the minimum number of indentation measurements required for indentation results to stabilize would be higher than in mineral samples. The stability cutoff is applied to the running mean indentation results of shale core chips samples from well C-004-F/094-G-08, resulting in Nmin ranging 3 to 83 (Figure 2.21; Table 2.8). Taking the highest Nmin value, N ≥ 83 is suggested for future studies to provide representative mean indentation results on Montney Formation shales. Sample Number of Indentations, N Mean EIT (GPa) 2*SE Mean EIT ± 2*SE Suggested Minimum N RM1-A 177 36.2 ± 12.6 1.9 34.3 – 38.1 67 RM2-C 139 39.6 ± 15.1 2.6 37.0 – 42.2 26 RM3-A 88 45.3 ± 12.0 2.6 42.7 – 47.9 22 RM4-A 107 31.7 ± 12.6 2.4 29.3 – 34.1 3 RM5-A 296 47.7 ± 11.0 1.3 46.4 – 49.0 77 RM6-C 186 49.3 ± 13.8 2.0 47.3 – 51.3 60 RM7-A 171 46.4 ± 16.3 2.5 43.9 – 48.9 15 RM8-C 241 39.7 ± 12.0 1.5 38.2 – 41.2 83 RM9-A 152 41.3 ± 14.6 2.4 38.9 – 43.7 23 DC-1780m 60 41.6 ± 12.7 3.8 39.7 – 43.5 28 DC-1780m – CSS 64 33.5 ± 15.3 1.9 31.6 – 35.4 61 DC-1785m 48 25.4 ± 7.1 2.5 22.9 – 27.9 13 DC-1785m – CSS 64 29.6 ± 10.0 3.3 26.3 – 32.3 45 DC-1790m 46 25.5 ± 7.5 3.1 22.4 – 28.6 7 DC-1790m – CSS 71 31.0 ± 13.1 2.0 29.0 – 33.0 39 DC-1800m 54 41.8 ± 13.7 4.4 37.4 – 46.2 14 DC-1800m – CSS 56 46.5 ± 16.4 2.2 44.5 – 48.5 41 DC-1870m 22 31.9 ± 10.6 3.0 28.9 – 34.9 6 DC-1870m – CSS 59 32.2 ± 11.4 3.7 28.5 – 35.9 7 DC-1880m 37 36.9 ± 12.3 3.6 33.3 – 40.5 17 DC-1880m – CSS 73 39.3 ± 15.4 4.5 34.8 – 43.8 23 DC-1890m 30 38.3 ± 10.6 3.4 34.9 – 41.7 3 DC-1890m – CSS 79 46.5 ± 15.1 4.0 42.5 – 50.5 35 DC-1965m 21 21.5 ± 9.9 3.2 18.3 – 24.7 4 55 Sample Number of Indentations, N Mean EIT (GPa) 2*SE Mean EIT ± 2*SE Suggested Minimum N DC-1965m – CSS 57 27.0 ± 12.0 3.9 23.1 – 30.9 37 DC-1970m 26 25.2 ± 6.7 2.5 22.7 – 27.7 3 DC-1970m – CSS 52 26.6 ± 9.0 4.3 22.3 – 30.9 5 DC-1975m 36 31.4 ± 12.0 4.0 27.4 – 35.4 8 DC-1975m – CSS 54 35.5 ± 14.8 2.6 32.9 – 38.1 18 DC-1980m 23 24.4 ± 5.7 3.4 21.0 – 27.8 4 DC-1980m – CSS 71 33.5 ± 14.3 4.0 29.5 – 37.5 12 DC-1985m 37 33.8 ± 10.6 3.9 29.9 – 37.7 6 DC-1985m – CSS 59 35.1 ± 15.0 2.4 32.7 – 37.5 47 DC-1990m 40 32.3 ± 9.8 3.8 28.5 – 36.1 16 DC-1990m - CSS 47 35.5 ± 13.1 3.5 32 - 39 11 Table 2.8: Minimum suggested number of indentations for combined tests on core chip samples of well C-004-F/094-G-08. Figure 2.21: Running mean EIT for indentations on core chip samples of well C-004-F/094-G-08. A maximum N = 100 is displayed. 56 On average, running mean indentation results are observed to stabilize at Nmin = 30 for mineral samples and Nmin = 41 for shales; however, in order to maximize the probability of measuring representative results from all samples in a dataset, the highest value of Nmin is suggested: N ≥ 61 in mineral samples and N ≥ 83 in shales. 2.3.5 Effect of Measurement Type on Indentation Results Standard and Sinus measurement types are tested to see whether indentation results are repeatable between indentation type, and if there is any quantitative benefit to using one measurement type over the other. Standard measurements offer faster and more flexible indentation parameters, whereas sinus measurements are useful for measuring changes to indentation parameters (i.e. hardness and stiffness) with depth; furthermore, constant strain sinus measurements are useful for testing materials that are strain rate dependent. Table 2.9 outlines indentation measurement parameters for each measurement type, across all measurements in this study. Measurement Type Standard Linear Strain Sinus Constant Strain Sinus Max Load, Fmax (mN) 5 – 500 100 – 200 100 Loading Rate (mN/min) 2*[Load] 0.5*[Load] n/a Sinus Frequency (Hz) n/a 1.0 1.0 Sinus Amplitude (mN) n/a 10 10 Pause / Hold (s) 10 10 10 Loading Rate / Load (1/s) n/a n/a 0.0500 Minimum Load (mN) n/a n/a 1.0 Table 2.9: Range of indentation parameters for Standard, LSS, and CSS measurement types in this study. 57 Standard, CSS, and LSS measurement types are directly compared on 4 mesh size quartz using measurement parameters of Pmax = 100 mN and 500 µN/µm stiffness threshold (Table 2.1; Figure 2.10). Mean EIT results for filtered Standard, CSS, and LSS indentations on quartz are 79.6 ± 4.0 GPa, 80.0 ± 2.6 GPa, and 78.1 ± 9.1 GPa (Table 2.1; Figure 2.10). Mean indentation results for different measurement types are repeatable and representative of literature values for quartz (Mavko et al., 2009). Measurement type does not influence mean indentation results in this sample of quartz. In shale samples, standard and CSS measurement types are compared in 42 tests (Figure 2.22; Table 2.10). Thirty-two of these comparisons were from well 06-28-078-19W6, spanning the stratigraphy of the Montney Formation and overlying Doig Phosphate. Standard indentation measurements are performed at Pmax = 200mN whereas CSS measurements are performed at the instrument maximum of Pmax = 100 mN. 58 Figure 2.22: EIT for standard and CSS measurements samples of well 01-20-063-08W6. Standard and CSS comparisons for a given sample are plotted as dark and light shades of the same colour (i.e. dark red and red display sample #1 standard [left] and CSS [right] results). Additional standard and CSS measurement comparisons are listed in Table 2.10. 59 Well Sample Standard - mean EIT (GPa) CSS - mean EIT (GPa) Difference EIT (%) 6-28-078-19W6 MNTN B - TXC-1 42.4 ± 13.5 (N = 36) 46.4 ± 10.4 (N = 43) 9.4 MNTN B - TXC-2 Test 1 42.1 ± 12.1 (N = 24) 43.6 ± 12.8 (N = 31) 3.5 MNTN B - TXC-2 Test 2 39.4 ± 9.4 (N = 22) 42.9 ± 7.8 (N = 30) 8.9 MNTN B - TXC-3 44.0 ± 11.4 (N = 55) 46.4 ± 14.7 (N = 78) 5.5 MNTN B - TXC-4 44.2 ± 13.4 (N = 63) 47.4 ± 14.8 (N = 73) 7.0 MNTN B - TXC-5 36.6 ± 10.8 (N = 61) 45.3 ± 11.6 (N = 81) 24.0 MNTN B - UCS-1 SUB 1 34.9 ± 9.1 (N = 37) 32.5 ± 9.6 (N = 45) -6.7 MNTN B - UCS-1 SUB 2 31.4 ± 11.4 (N = 21) 41.1 ± 14.3 (N = 46) 30.6 MNTN B - UCS-3 SUB 1 38.0 ± 9.5 (N = 14) 46.9 ± 17.3 (N = 17) 23.2 MNTN B - UCS-3 SUB 2 38.4 ± 8.9 (N = 16) 35.8 ± 11.9 (N = 12) -6.7 MNTN C - TXC-1 32.9 ± 9.5 (N = 24) 37.2 ± 10.9 (N = 40) 13.2 MNTN C - TXC-2 41.5 ± 13.2 (N = 57) 47.5 ± 15.3 (N = 67) 14.5 MNTN C - TXC-3 37.9 ± 10.0 (N = 41) 40.2 ± 13.3 (N = 44) 6.1 MNTN C - TXC-4 46.5 ± 14.4 (N = 69) 48.4 ± 15.5 (N = 60) 4.2 MNTN C - UCS-1 44.5 ± 12.2 (N = 65) 49.6 ± 13.9 (N = 87) 11.6 60 Well Sample Standard - mean EIT (GPa) CSS - mean EIT (GPa) Difference EIT (%) MNTN C - UCS-2 39.9 ± 10.9 (N = 47) 47.9 ± 13.3 (N = 64) 20.2 MNTN C - UCS-3 46.7 ± 11.0 (N = 18) 43.3 ± 13.5 (N = 32) -7.3 MNTN D - TXC-1 48.5 ± 13.1 (N = 48) 49.4 ± 15.5 (N = 58) 1.9 MNTN D - TXC-2 47.9 ± 10.7 (N = 69) 51.2 ± 15.1 (N = 83) 6.8 MNTN D - TXC-4 44.7 ± 11.6 (N = 64) 46.9 ± 14.0 (N = 78) 5.0 MNTN D - UCS-1 43.0 ± 11.5 (N = 66) 46.7 ± 13.0 (N = 68) 8.7 MNTN D - UCS-3 35.6 ± 8.5 (N = 61) 39.9 ± 13.5 (N = 79) 12.0 MNTN E1 - TXC-2 47.7 ± 16.1 (N = 52) 50.1 ± 15.5 (N = 63) 5.1 MNTN E1 - TXC-3 54.0 ± 14.9 (N = 32) 51.2 ± 14.9 (N = 66) -5.1 MNTN E1 - TXC-4 50.1 ± 13.8 (N = 45) 50.3 ± 15.5 (N = 72) 0.4 MNTN E1 - TXC-5 42.0 ± 11.1 (N = 60) 46.6 ± 15.1 (N = 63) 11.1 MNTN E4 - TXC-2 48.1 ± 15.4 (N = 62) 52.3 ± 14.4 (N = 68) 8.7 MNTN E4 - UCS-1 43.1 ± 13.3 (N = 78) 47.3 ± 14.1 (N = 80) 9.8 PHOS - TXC-2 63.7 ± 10.4 (N = 48) 60.3 ± 12.5 (N = 64)) -5.4 PHOS - TXC-3 62.6 ± 11.3 (N = 41) 64.0 ± 13.3 (N = 53) -5.1 61 Well Sample Standard - mean EIT (GPa) CSS - mean EIT (GPa) Difference EIT (%) PHOS - UCS-1 66.9 ± 13.0 (N = 47) 66.7 ± 16.1 (N = 66) -0.2 PHOS - UCS-2 60.0 ± 14.4 (N = 58) 61.9 ± 12.9 (N = 54) 3.1 1-20-063-08W6 #1 56.1 ± 14.1 (N = 85) 59.8 ± 14.6 (N = 84) 6.5 #4 63.6 ± 9.2 (N = 90) 66.3 ± 11.4 (N = 82) 4.2 #4 – 500 µN/µm 66.8 ± 10.2 (N = 43) 66.7 ± 11.0 (N = 83) -0.3 #19 68.6 ± 11.6 (N = 91) 69.6 ± 14.5 (N = 97) 1.5 #25 51.5 ± 12.4 (N = 74) 54.7 ± 15.0 (N = 93) 6.3 #31 55.0 ± 13.3 (N = 75) 58.8 ± 16.7 (N = 81) 6.9 #36 70.3 ± 13.8 (N = 65) 70.6 ± 17.1 (N = 76) 0.5 13-28-064-05W6 RMA-11 HZ 62.5 ± 4.9 (N = 105) 58.3 ± 4.0 (N = 115) -6.9 1-12-054-06W6 C1B7 - SUB 1 25.6 ± 5.2 (N = 41) 26.2 ± 5.4 (N = 59) 2.2 C1B7 - SUB 2 25.1 ± 4.8 (N = 50) 29.6 ± 7.2 (N = 92) 18.0 Other Shales Wolfcamp Talon 20.8 ± 3.2 (N = 30) 22.7 ± 4.5 (N = 63) 9.0 Table 2.10: Indentation results for standard and constant strain sinus measurements on shale samples. Bold samples have standard and CSS results which were not repeatable. 62 Cross-plotted mean EIT for standard and CSS measurement types demonstrate strong linear correlation (R2 = 0.93) for shale sample comparisons (Figure 2.23). Mean EIT for standard and CSS measurements are repeatable for 34 of the 43 comparisons, based on t-Tests. The 9 comparisons with mean EIT values that are not repeatable include samples MNTN B – TXC-5 and UCS-1 SUB 2; MNTN C – TXC-2, – UCS-1, and – UCS-2; MNTN D – UCS-3; RMA-11 HZ; C1B7 - SUB 1 and C1B7 – SUB 2; and Wolfcamp Talon. Differences between compared standard and CSS results may have been caused by several different factors. For example, indentation parameters vary between indentation tests: standard measurements are measured to a maximum indentation load of 200 mN, whereas CSS measurements are measured at the instrument limit Pmax of 100 mN. In general, indentation displacement and area would be greater for a higher indentation load, resulting in a more composite material response. The difference in maximum indentation load may explain why 79% of comparisons showed lower mean EIT in standard indentations than CSS measurements. Alternatively, each indentation test may have measured local heterogeneities in the shale subsample, influencing indentation results due to sampling bias. In the 9 samples that do not demonstrate repeatability between standard and CSS results, mean EIT of each measurement type still overlaps within 1 standard deviation of the mean. For example, MNTN C – UCS-1 has standard and CSS mean EIT results of 44.5 ± 12.2 and 49.6 ± 13.9 GPa. 63 Figure 2.23: Standard and constant strain sinus indentation measurement comparisons for all 43 shale samples tested. Standard, CSS, and LSS measurement types, tested at the same maximum indentation load of 100 mN, demonstrate no significant difference in indentation results in quartz. In shale samples, 79% of standard and CSS measurement comparisons are repeatable, while 100% of indentation results have mean EIT values that overlap within 1 standard deviation. Indentation results are consistently higher for CSS measurements than standard measurements, attributed to the higher maximum indentation load of standard indentations. In general, different indentation measurement types are comparable when tested at the same indentation parameters. No significant trends or correlations are observed that would lead to using one measurement type 64 over the other in indentation testing on shales. Standard indentation measurements are the primary indentation type applied to all samples tested in this study since it is faster and it is possible to test at higher maximum indentation loads. For nanoscale, depth-related analysis of indentation mechanical properties (i.e. how hardness changes with depth), or for sample materials that are strain-rate dependent, constant strain sinus indentation type is still advantageous. 2.3.6 Repeatability and Variability of Indentation Results in Shale Variability in indentation results are observed across all sample types as a result of sample properties and indentation parameters. Indentation results from testing of composite materials, such as shales, show variability due to the different mechanical properties and distribution of the various components. In this section, indentation results are grouped to show how variability changes with scale of measurement. Comparisons are made for indentation results of repeated indentation tests (combining the results of many indentation measurements per test), subsamples (combining the results of two or more indentation tests per subsample), and samples (combining the results of two or more subsample mean indentation results). It is then assumed that, when combined, indentation test results are representative of subsample mean indentation mechanical properties; and that combined subsample indentation results are representative of sample mean indentation mechanical properties. Comparisons at these three scales of measurement aim to answer the questions of repeatability and variability: • How many indentation tests are necessary to provide representative subsample indentation mechanical properties? 65 • How many subsamples should be tested to provide representative sample indentation mechanical properties? • What are the effects of sample orientation on subsample indentation results? • Can sample mean indentation mechanical properties characterize variability between samples? Examples of how indentation results vary with indentation test, subsample, and sample are given for samples 7G-4 (Figure 2.24; Figure 2.25) and 7G-7 (Figure 2.26; Figure 2.27). Following subsections further explore indentation results at each scale of measurement, outlined in these examples. 66 Figure 2.24: Indentation test, subsample, and sample mean indentation results. Inset shows a schematic diagram of sample 7G-4 (encompassed by a dashed black line), showing subsamples (blue lines) 7G-4a and 7G-4b, and example indentation test grids (red squares) composed of many indentation measurements. 67 Figure 2.25: Indentation results for indentation tests, and subsamples, of sample 7G-4.68 Figure 2.26: Indentation test, subsample, and sample mean EIT results. Inset shows a schematic diagram of sample 7G-7 (encompassed by a dashed black line), showing subsamples (blue lines) 7G-7a and 7G-7b, and example indentation test grids (red squares) composed of many indentation measurements.69 Figure 2.27: Indentation results for indentation tests, and subsamples, of sample 7G-7. 70 2.3.6.1 Indentation Test Mean Indentation Results At the smallest scale of results comparison, mean EIT and repeatability are used to compare indentation results for two or more indentation tests on a single subsample. The purpose of this comparison is to assess whether results from individual indentation tests are representative of subsample indentation mechanical properties. This assessment compliments work done to estimate the minimum number of indentation measurements necessary for reliable results on a given material, as it suggests how many indentation tests should be performed to account for heterogeneity in subsamples. Indentation test results can then be combined to describe mean subsample indentation results. In this study, 23 pairs of indentation test results are compared (totaling 46 indentation tests across 19 different subsamples) to assess variability and repeatability of indentation test results ( Figure 2.28; Figure 2.29; Figure 2.30). Out of the 23 comparisons, 18 demonstrate repeatable mean EIT test results (Table 2.11), based on t-Testing at a 0.05 significance level. Repeatable mean indentation test results showed differences in mean EIT of 0.1 – 6.4% between tests. Five subsamples – 7G-4b, 7G-7a, 7G-10a, 7G-11b, and WM9 – have mean indentation test results that are not repeatable. Subsamples that do not show repeatability between indentation test results have differences in mean EIT of 7.7% to 17.7%. 71 Figure 2.28: Indentation modulus results for repeated indentation tests on shale subsamples of well 1-20-063-08W6. Colour pairs indicate repeated tests, with Test 1 on the left and Test 2 on the right of each pair. Each indentation test represents the results from N indentation measurements (Table 2.11). 72 Figure 2.29: Indentation modulus results for repeated indentation tests on subsamples of Set 1 and Set 2 Montney Formation shales. Colour pairs indicate repeated tests, with Test 1 on the left and Test 2 on the right of each pair. Each indentation test represents the results from many indentation measurements. 73 Figure 2.30: Indentation modulus results for repeated indentation tests for Montney Formation subsamples from wells 6-28-78-19W6, A01-32-83-25W6, C-004-F/094-G-08, and other shales. Colour pairs indicate repeated tests, with Test 1 on the left and Test 2 on the right of each pair. Each indentation test represents the results from many indentation measurements. 74 Well Sample Test 1 - mean EIT (GPa) Test 2 - mean EIT (GPa) 1-20-063-08W6 #1 57.7 ± 12.9 (N = 157) 56.1 ± 14.1 (N = 85) #4 63.7 ± 11.3 (N = 162) 63.6 ± 9.2 (N = 90) #19 63.6 ± 10.1 (N = 34) 61.9 ± 10.8 (N = 103) #25 53.4 ± 14.9 (N = 49) 53.3 ± 14.3 (N = 136) #31 56.0 ± 14.2 (N = 94) 55.0 ± 13.3 (N = 75) #36 74.4 ± 15.3 (N =109) 70.3 ± 13.8 (N = 65) 6-28-078-19W6 MNTN B - TXC-2 42.1 ± 14.2 (N = 24) 39.4 ± 13.3 (N = 22) A01-32-083-25W6 RMA-12-VT - SUB 1 49.6 ± 14.0 (N = 9) 52.0 ± 13.8 (N = 78) RMA-12-VT - SUB 2 55.4 ± 12.6 (N = 40) 54.5 ± 12.5 (N = 44) C-004-F-094-G-008 RM6-C 50.6 ± 13.8 (N = 32) 49.3 ± 16.5 (N = 186) RM7-A 45.8 ± 16.2 (N = 111) 47.6 ± 15.0 (N = 60) RM9-C 43.1 ± 14.6 (N = 21) 41.0 ± 15.3 (N = 131) Set 1 - 13-28-64-5W6 7G-3b 52.1 ± 10.6 (N = 8) 54.1 ± 10.1 (N = 87) 7G-4a 43.8 ± 11.8 (N = 43) 42.1 ± 9.1 (N = 75) 7G-4b 34.3 ± 9.6 (N = 53) 37.8 ± 11.6 (N = 61) 7G-7a 53.2 ± 11.8 (N = 88) 57.9 ± 14.2 (N = 110) 7G-7b 49.0 ± 12.6 (N = 28) 48.1 ± 9.0 (N = 40) 7G-10a 48.1 ± 6.7 (N = 85) 39.5 ± 8.4 (N = 36) 7G-11b 49.2 ± 11.3 (N = 67) 53.0 ± 9.4 (N = 108) 7G-12a 47.4 ± 9.6 (N = 74) 48.9 ± 10.7 (N = 131) 7G-12b 54.3 ± 9.4 (N = 149) 54.6 ± 10.8 (N = 51) Set 2 - 2-28-64-5W6 2V1 46.5 ± 13.6 (N = 54) 47.6 ± 7.5 (N = 28) Other Shales WM9 40.6 ± 7.5 (N = 32) 37.3 ± 9.7 (N = 112) Table 2.11: Mean indentation modulus and standard deviation for repeated indentation testing in shale subsamples. Bolded values didn’t show repeatability. 75 Where indentation test results do not demonstrate repeatability, mean EIT of each test still overlaps within 1 standard deviation of the mean. For example, indentation test results of 7G-4b are not repeatable, with mean EIT results of 34.3 ± 9.6 GPa in test 1 and 37.8 ± 11.6 GPa in test 2. The difference between mean values is 3.5 GPa, whereas the standard deviation for each mean is much greater (9.6 and 11.6 GPa). Similarly, indentation test results for subsample 7G-7a are not repeatable at values of 53.2 ± 11.8 GPa and 57.9 ± 14.2 GPa; a difference of 4.7 GPa between mean EIT values for each test is relatively small compared to the standard deviation of the mean (11.8 and 14.2 GPa). Test 1 and test 2 mean EIT results show a strong linear correlation (R2 = 0.89) across all compared tests (Figure 2.31), supporting repeatability of mean test results. Figure 2.31: Mean Indentation Modulus results for repeated tests on subsamples of shale core chips. Data for this figure is displayed in Table 2.11. 76 Variability is expected between indentation test results due to the multi-component, multiscale nature of shale. Indentation tests, each of which includes many indentation measurements, only characterizes the portion of the shale subsample that the test covers. Where compared indentation tests show repeatability, indentation test mean results are similar to one another with 95 % confidence; this suggests that each indentation test has provided an indentation result that is representative of indentation mechanical properties of the subsample tested. Where indentation test results differ, the subsample may be locally heterogeneous at the location of the indentation tests, or individual indentation test results may not be fully representative of subsample indentation mechanical properties. In the former case, indentation tests do not have to be repeatable to be representative of the portion of the subsample they tested. When combined, differing results from two or more indentation tests made on the same subsample can still provide representative mean subsample indentation results. In the latter case, the number of indentations could be limited by the size of a subsample or data filtration, giving test results that are not fully representative of the tested area; however, when combined with additional indentation measurements from other tests across a subsample, a representative subsample mean indentation result can still be achieved. Overall, individual indentation test results provide good estimates of subsample indentation mechanical properties, given 78% repeatability of compared indentation test results. In 100% of comparisons, indentation test mean EIT values overlap within 1 standard deviation, supporting repeatable indentation test results while accounting for local heterogeneity within the subsample. Across the dataset, the strong linear correlation for compared indentation test mean EIT supports instrumented indentation as an effective technique of characterizing indentation mechanical properties of shale subsamples, even at the small scale of an individual indentation 77 test. These results confirm the ability of instrumented indentation testing to measure representative indentation results on small samples of shale. If subsample indentation results were to be upscaled and representative of sample indentation mechanical properties, indentation testing would be a useful technique to characterizing the variation between shale samples of drill cuttings size. 2.3.6.2 Subsample Mean Indentation Results Subsample mean indentation results are the second scale of measurement compared in this study. Subsample mean indentation results combine the results from all indentation measurements, of all indentation tests, performed on a given subsample. Shale subsamples are further separated into two categories: unoriented and oriented. Unoriented subsamples refer to pieces of one shale sample that was embedded in epoxy without attention to the orientation of sample bedding, with respect to the direction of indentation. If instrumented indentation is to be applied to shale drill cuttings, it would be difficult to distinguish bedding orientation in such small samples; therefore, the ability to measure repeatable and representative subsample indentation results from unoriented subsamples is essential. Conversely, oriented subsamples refer to pieces of a shale sample that were mounted in epoxy with the bedding oriented either parallel (X1) or perpendicular (X3), with respect to the direction of indentation. The characterization of oriented subsamples allows the evaluation of the effects of mechanical anisotropy on mean indentation results. Regardless of subsample orientation, comparing subsample mean indentation results analyzes the number of subsamples required for the reliable characterization of shale variability. In total, 29 subsample comparisons are performed in this study: 13 comparisons of unoriented subsamples, and 15 comparisons of oriented subsamples. 78 2.3.6.2.1 Unoriented Subsample Mean Indentation Results Mean EIT and repeatability of unoriented subsamples are compared to assess the number of subsamples required to produce representative sample results. Subsamples were labelled in the order they were tested (i.e. SUB 1, SUB 2, SUB 3). Amongst unoriented subsample comparisons, samples RMA-10-VT and RMA-70-VT each had 3 subsamples tested (e.g. RMA-10-VT - SUB 1, - SUB 2, and - SUB 3); in these two cases, comparisons were made between SUB 1 and SUB 2, and SUB 1 and SUB 3, but not between SUB 2 and SUB 3 to avoid weighting the resulting correlation (Figure 2.32; Table 2.12). Overall, cross-plotted mean EIT results for unoriented subsamples show a strong linear correlation (R2 = 0.94), where labelling was randomly assigned and subsample 1 is plotted on the x-axis and subsample 2 or subsample 3 is plotted on the y-axis (Figure 2.32). 79 Figure 2.32: Indentation results for unoriented subsamples of shale. Associated data is listed in Table 2.12. 80 Figure 2.33: EIT results for indentation measurements on unoriented shale subsamples. Sample sets are colour-coded by well and subsamples of a sample are indicated by colour shades. Samples listed in the legend (top to bottom) are plotted left to right. 81 Figure 2.34: Indentation modulus results indentation measurements of subsamples of other shales. Colour pairs indicate subsamples. Samples listed in the legend (top to bottom) are plotted left to right.82 Well Sample SUB 1 - mean EIT (GPa) SUB 2 or 3 - mean EIT (GPa) Mean EIT Ratio (SUB 1:SUB 2 or 3) 9-23-064-04W6 MP1 - SUB 1 and 2 64.3 ± 7.3 (N = 136) 69.0 ± 7.0 (N = 55) 0.93 A01-32-083-25W6 RMA-10-VT - SUB 1 and 2 46.1 ± 11.3 (N = 85) 48.5 ± 10.5 (N = 42) 0.95 RMA-10-VT - SUB 1 and 3 46.1 ± 11.3 (N = 85) 45.1 ± 11.8 (N = 41) 1.02 RMA-21-HZ 51.8 ± 10.8 (N = 84) 51.1 ± 13.0 (N = 31) 1.01 RMA-45-HZ 63.2 ± 11.8 (N = 101) 62.6 ± 13.6 (N = 87) 1.01 RMA-70-VT - SUB 1 and 2 50.0 ± 10.9 (N = 45) 47.1 ± 10.8 (N = 33) 1.06 RMA-70-VT - SUB 1 and 3 50.0 ± 10.9 (N = 45) 45.2 ± 9.9 (N = 38) 1.11 C-004-F-094-G-008 RM8-C 37.9 ± 13.0 (N = 80) 40.5 ± 11.4 (N = 161) 0.94 1-12-054-06W6 Duvernay - C1B6b 39.1 ± 5.7 (N = 51) 41.3 ± 6.8 (N = 96) 0.95 Duvernay - C1B7 25.6 ± 5.2 (N = 41) 25.1 ± 4.8 (N = 50) 1.02 Duvernay - C1B11 49.5 ± 13.5 (N = 176) 46.1 ± 11.5 (N = 157) 1.07 Other Shales Eagleford 30.8 ± 4.4 (N = 69) 32.4 ± 4.2 (N = 83) 0.95 HAX (Haynesville) 32.4 ± 5.3 (N = 54) 35.8 ± 6.7 (N = 83) 0.91 Table 2.12: Mean EIT for unoriented subsamples of shale. Bolded values do not show repeatability. Out of the 13 unoriented subsample comparisons, 9 have repeatable mean indentation results (Figure 2.33; Figure 2.34; Table 2.12). Repeatability of subsample results suggests that compared subsample mean indentation results are statistically similar with 95 % confidence. This result also indicates that each subsample mean indentation result compared is representative of sample indentation mechanical properties. In addition to repeatability, mean EIT of compared subsamples are within 1 standard deviation of each other. For example, the difference in mean 83 EIT for compared subsamples of C1B6a is 2.2 GPa, whereas 1 standard deviation from the mean EIT of each subsample are 5.7 and 6.8 GPa. Similarly, C1B11 displays a difference of 3.4 GPa for subsample standard deviations of 13.5 and 11.5 GPa; Eagleford has a mean EIT difference of 1.6 GPa for standard deviations of 4.4 and 4.2 GPa; and HAX has a difference of 3.4 GPa for standard deviations of 5.3 and 6.7 GPa. Variability in subsample mean indentation results are expected, due to the multi-component, multi-scale complexity of shale, and varying indentation parameters. For indentation tests, variability in results is likely due to the limited number of measurements, after filtering, not fully characterizing subsample indentation mechanical properties. For subsample indentation results, the increased number of measurements from combining indentation test results provides a mean indentation result that averages a larger number of individual measurements, thus providing an indentation result that is more representative of a subsample than individual indentation tests. In relatively homogeneous subsamples, which demonstrate repeatability and similar mean EIT values, either subsample mean indentation result can be used to describe sample indentation mechanical properties. In relatively heterogeneous subsamples, with mean indentation results that do not demonstrate repeatability (e.g. 7G-4a and 7G-4b), additional measurements may be necessary to fully characterize heterogeneity in individual subsamples. When non-repeatable subsample indentation results are combined, the resulting sample mean indentation result can still be representative of sample indentation mechanical properties. In general, individual, unoriented subsamples provide good estimates of sample indentation mechanical properties, with 100% of compared subsamples having mean EIT values within 1 standard deviation of each other; a strong linear relationship (R2 = 0.94) between compared subsample mean EIT; and 69% repeatability for subsample mean EIT comparisons. 84 Where possible, multiple subsamples of a given shale sample should be tested in order to capture as much heterogeneity as possible within indentation results; however, indentation testing of an individual subsample provides representative, repeatable results in the majority of compared results. One possible factor leading to variation in subsample mean indentation results, sample orientation, is assessed in the following section. 2.3.6.2.2 Assessing Geomechanical Anisotropy in Oriented Subsamples of Shale In this study, the effects of bedding orientation on indentation results are analyzed through 15 comparisons of subsample mean indentation results (Figure 2.36; Figure 2.37). Oriented subsamples are embedded in epoxy with their bedding oriented either parallel (X1) or perpendicular (X3) to the direction of indentation (Figure 2.3; Figure 2.4). Subsample orientation is approximate due to visual placement of the subsample, movement during drying of epoxy, or polishing along inexact lineations or bedding planes; therefore, results presented are the best representation of X1 and X3 indentation results given experimental constraints. In total, indentation results from 15 oriented subsample comparisons are analyzed, resulting in a strong linear correlation (R2 = 0.89) between X1 and X3 mean EIT (Figure 2.35). Out of the 15 comparisons, 12 demonstrate mean EIT repeatability, with 95 % confidence (Table 2.13). As with unoriented subsamples, mean indentation results from oriented subsamples are reproducible and representative of sample indentation mechanical properties; however, the linear correlation between X1 and X3 oriented subsamples (R2 = 0.89) isn’t as strong as compared unoriented subsamples (R2 = 0.94), possibly indicative of the influence of bedding orientation causing variation between subsamples. 85 Figure 2.35: Mean Indentation modulus of compared oriented subsamples of shale. In order to quantify indentation mechanical anisotropy, indentation results of oriented subsamples are compared using a ratio of results from bedding parallel to bedding perpendicular samples (X1:X3). Ratios of X1:X3 for EIT and HIT were compared, where a ratio of 1.0 suggests indentation mechanical isotropy, whereas greater than 1.0 is indicative of mechanical anisotropy, as observed in previous studies (e.g. Sondergeld et al., 2010; Sone and Zoback, 2013; Han et al., 2018). In this study, the 15 oriented subsample comparisons have mean EIT X1:X3 ranging from 0.97 to 1.18. Twelve of the comparisons have mean EIT X1:X3 between 1.02 and 1.18, indicating EIT anisotropy in 80 % of compared subsamples (Table 2.13). The three remaining comparisons have an EIT X1:X3 slightly less than 1.0 (0.97, 0.99, and 0.99), suggesting minimal influence of 86 bedding on indentation results for these subsample comparisons; this is likely the result of relatively homogeneous subsamples or subsample orientations which shifted during epoxy mounting. Shukla et al. (2013) note that mean indentation results from randomly oriented core chip samples are between X1 and X3. Subsamples demonstrating similar mean indentation results are potentially randomly oriented somewhere between X1 and X3, with results representing the mean between these two oriented extremes. Mechanical anisotropy in shale is the result of the distribution and alignment of clay minerals, in addition to the composition and maturity of that shale (Sone and Zoback, 2013). Indentation of a shale sample oriented with bedding parallel to the direction of indentation will generally measure a sample in a direction with a greater distribution of minerals and less alignment than when testing a sample with bedding oriented perpendicular to the direction of indentation; thus, a parallel-oriented sample will have more resistance to elastic deformation and be relatively stiff compared to a relatively aligned and more flexible, perpendicularly-oriented sample. 87 Figure 2.36: EIT results for indentation measurements on oriented subsamples of wells 06-28-078-19W6 (yellow), 09-23-064-04W6 (green), and C-004-F/094-G-08 (purple). Subsamples oriented with bedding parallel to the direction of indentation are labelled as “X1”; perpendicular are labeled “X3”. 88 Figure 2.37: EIT results for indentation measurements on oriented subsamples of sample Set 1. Subsamples oriented with bedding parallel to the direction of indentation are labelled with “X1”, whereas subsamples with bedding perpendicular are labelled with “X3”. 89 Well Sample EIT of Parallel (X1) sample (GPa) EIT of Perpendicular (X3) sample (GPa) X1:X3 for mean EIT HIT of Parallel (X1) sample (MPa) HIT of Perpendicular (X3) sample (MPa) X1:X3 for mean HIT 6-28-078-19W6 MNTN B - UCS-1 34.9 ± 9.0 (N = 37) 31.4 ± 11.2 (N = 21) 1.11 1798 2377 0.76 MNTN B - UCS-3 38.0 ± 9.6 (N = 14) 38.4 ± 10.2 (N = 16) 0.99 2602 2402 1.08 9-23-064-04W6 MP3 - SUB 2 and 1 58.9 ± 12.4 (N = 24) 55.7 ± 12.0 (N = 97) 1.06 4575 3851 1.19 MP3 - SUB 3 and 1 54.1 ± 12.7 (N = 59) 55.7 ± 12.0 (N = 97) 0.97 4575 4188 1.09 C-004-F-094-G-008 RM5-A 47.9 ± 10.6 (N = 205) 47.1 ± 11.9 (N = 91) 1.02 3337 4143 0.81 RM6-C 49.5 ± 14.3 (N = 218) 46.4 ± 13.1 (N = 96) 1.07 4004 4051 0.99 Set 1 13-28-64-5W6 7G-2 65.0 ± 11.1 (N = 186) 65.4 ± 9.9 (N = 59) 0.99 5753 5533 1.04 7G-3 56.6 ± 10.1 (N = 78) 55.5 ± 11.2 (N = 129) 1.02 5857 6139 0.95 7G-4 42.7 ± 11.2 (N = 118) 36.2 ± 9.4 (N = 114) 1.18 3555 3803 0.93 7G-6 64.1 ± 11.1 (N = 76) 54.9 ± 8.2 (N = 79) 1.17 4494 5160 0.87 7G-7 55.8 ± 11.9 (N = 198) 48.5 ± 13.2 (N = 68) 1.15 4899 4730 1.04 7G-8 62.3 ± 11.8 (N = 80) 59.9 ± 9.3 (N = 46) 1.04 5156 5106 1.01 7G-9 53.6 ± 11.5 (N = 121) 50.8 ± 10.2 (N = 108) 1.05 5019 4740 1.06 7G-10 45.5 ± 9.2 (N = 121) 39.9 ± 9.8 (N = 76) 1.14 3583 4223 0.85 7G-11 57.0 ± 10.2 (N = 113) 51.6 ± 10.4 (N = 175) 1.10 4551 5057 0.90 Table 2.13: Indentation results for oriented subsamples of shale. Bold values are not repeatable.90 In previous studies, the orientation of shale samples has been shown to affect indentation results (e.g. Bennett et al., 2015). In these studies, mean EIT is found to be greater in samples with bedding oriented parallel to the direction of indentation testing than samples with bedding oriented perpendicular to testing (e.g. Shukla et al., 2013; Bennett et al., 2015; Han et al., 2018). The results in this study support previous findings, with higher mean EIT for X1 oriented subsamples than X3 oriented subsamples in 80 % of comparisons. Overall, oriented subsample mean indentation results demonstrate indentation mechanical anisotropy, measured as 2 – 18% higher mean EIT in subsamples with bedding oriented parallel to the direction of testing, than subsamples oriented bedding perpendicular; however, the effects of anisotropy do not significantly affect the upscaling of subsample mean indentation results to a representative value for sample indentation mechanical properties. Oriented subsample indentation results demonstrate repeatability in 12 of 15 mean EIT comparisons, suggesting individual oriented subsamples provide good estimates of sample indentation mechanical properties. While one subsample may provide a good estimate of sample indentation mechanical properties, testing of multiple subsamples ensures a representative sample characterization in case of local subsample heterogeneity. Compared mean EIT values within 1 standard deviation, and strong linear correlation, between subsample mean EIT results further supports oriented subsample indentation results as being representative of sample indentation mechanical properties. Subsamples, whether oriented randomly or purposefully, provide repeatable indentation results that we assume are representative of indentation mechanical properties of their parent sample when combined and averaged. Mean indentation mechanical properties of a sample can then be used to assess the variability in mechanical properties between samples. 91 2.3.6.3 Sample Mean Indentation Results In this study, indentation results from multiple indentation tests, across several subsamples, can be upscaled to represent sample indentation mechanical properties. Hence, sample mean indentation results can then be used to assess the indentation mechanical variability between samples (Figure 2.38; Figure 2.39). For example, indentation results from samples of well 06-28 display variability in indentation mechanical properties through the stratigraphy of the Montney Formation (Figure 2.40). The 29 core chip samples are subdivided and labeled by stratigraphic units denoted by the original operator of the well (Figure 2.41; Figure 2.42; Table 2.14). In order of descending depth, samples are from the Doig Phosphate (PHOS), Montney E lobe (MNTN E1 and MNTN E4), Montney D lobe (MNTN D), Montney C lobe (MNTN C), and Montney B lobe (MNTN B). Shale core chips sampled in this study are taken from slabs of core cut adjacent to core plugs that were tested in previous studies with triaxial (TXC) or uniaxial compression tests (UCS). In this study, sample labeling expresses the type of previous core plug testing; for example, PHOS – UCS-2 represents a sample from the Doig Phosphate that is sampled adjacent to a core plug previously tested with uniaxial compression. Two or more samples are taken from each stratigraphic unit, some of which are collected at similar sampling depths only centimeters apart. Variability in sample mean indentation results, and repeatability, is used to compare and distinguish samples, including those sampled close to one another. Two samples that demonstrate repeatability have mean EIT values that are similar with 95 % confidence, whereas sample results that are not repeatable do not have statistically similar mean EIT. In the case of sample comparisons, repeatability does not indicate two samples are from the same location, but it can distinguish two samples that have significantly different mean results. 92 Figure 2.38: Mean indentation modulus versus mean indentation hardness, sorted by formation. Figure 2.39: Mean indentation modulus versus mean indentation hardness, sorted by well.93 Figure 2.40: Indentation Modulus for samples of well 06-28-078-19W6. Samples are ordered descending in depth from left to right. Colour groups indicate stratigraphic groupings (Grey=Doig Phosphate; Purple=MNTN E1; Pink=MNTN E4; Blue=MNTN D; Green=MNTN C; Red=MNTN B). 94 Figure 2.41: Indentation Modulus versus Depth for samples of well 06-28-078-19W6. Figure 2.42: Mean Indentation Hardness versus Indentation Modulus for samples of well 06-28-078-19W6. 95 Sample Depth (m) N Mean EIT (GPa) Mean HIT (MPa) PHOS - UCS-2 2592.94 58 60.0 ± 14.5 2404 PHOS - TXC-3 2592.98 41 62.6 ± 11.1 2431 PHOS - UCS-1 2593.02 47 66.9 ± 13.1 2601 PHOS - TXC-2 2593.06 48 63.7 ± 10.5 2558 MNTN E1 - TXC-2 2611.41 52 47.7 ± 16.0 2824 MNTN E1 - TXC-3 2611.46 32 54.0 ± 14.7 3276 MNTN E1 - TXC-4 2611.73 45 50.1 ± 13.7 4469 MNTN E1 - TXC-5 2611.84 60 40.8 ± 10.9 3324 MNTN E4 - UCS-1 2643.46 78 43.0 ± 12.1 3095 MNTN E4 - TXC-2 2643.50 62 48.9 ± 15.0 2996 MNTN D - TXC-4 2682.44 64 43.9 ± 11.0 3009 MNTN D - TXC-1 2682.50 48 48.5 ± 13.1 3226 MNTN D - UCS-1 2682.54 66 43.8 ± 11.7 3225 MNTN D - UCS-3 2683.02 61 35.4 ± 8.4 3375 MNTN D - TXC-2 2683.06 69 48.7 ± 11.4 3173 MNTN C - UCS-3 2733.71 18 46.7 ± 10.9 2196 MNTN C - UCS-1 2733.75 65 43.3 ± 11.8 3318 MNTN C - UCS-2 2733.78 47 39.9 ± 11.2 2804 MNTN C- TXC-1 2733.81 24 32.9 ± 10.1 2449 MNTN C - TXC-2 2733.85 57 42.1 ± 13.4 2956 MNTN C - TXC-3 2733.91 41 37.9 ± 10.4 2526 MNTN C - TXC-4 2734.37 69 46.3 ± 14.4 3342 MNTN B - TXC-5 2770.28 61 36.1 ± 11.1 2824 MNTN B - UCS-1 2770.32 58 33.6 ± 10.0 2167 MNTN B - TXC-3 2770.35 55 44.1 ± 11.4 3239 MNTN B - TXC-2 2770.48 46 40.8 ± 11.1 3239 MNTN B - TXC-1 2770.51 36 42.4 ± 13.3 2927 MNTN B - TXC-4 2770.55 63 45.3 ± 13.4 2763 MNTN B - UCS-3 2770.62 30 38.2 ± 9.9 2509 Table 2.14: Indentation results for samples of well 06-28-078-19W6, in order of descending sample depth. 96 The four PHOS samples are the shallowest samples tested from well 06-28, representing total vertical depths between 2592.94 m and 2593.06 m, with 4 cm spacing between each sample. Samples PHOS UCS-2, TXC-3, UCS-1, and TXC-2 have mean EIT results of 60.6 ± 14.5, 62.6 ± 11.1, 66.9 ± 13.1, and 63.7 ± 10.5 GPa. Variation in mean EIT can be used to differentiate between PHOS samples; however, a significant difference outside of the standard deviation of mean EIT is not observed between PHOS samples. Relatively high mean EIT values (60.6 ± 14.5 to 66.9 ± 13.1 GPa) differentiate the stratigraphically higher PHOS samples from other samples of the Montney Formation in this well (Figure 2.43). Stratigraphically below PHOS samples are MNTN E1 samples, at depths of 2611.41 m to 2611.84 m. Indentation results of PHOS TXC-2 and the next underlying sample, MNTN E1 - TXC-2 have significantly different mean EIT values of 63.7 ± 10.5 GPa and 47.7 ± 16.0 GPa. MNTN E1 samples have mean EIT results of ranging 40.8 ± 10.9 to 54.0 ± 14.7 GPa (Table 2.14). Once again, sample mean EIT differentiates indentation mechanical properties of these samples (Figure 2.43). Indentation results for the 3 shallowest samples of MNTN E1 have similar indentation mechanical properties, whereas MNTN E1 - TXC-5, sampled from a depth of 2611.84 m, has a mean EIT that is significantly different from overlying TXC-4 (2611.73 m). In this example, variation in mean indentation results is determined for samples 11 cm apart, quantifying a change in indentation mechanical properties across a small depth difference of the E1 stratigraphic unit. Approximately 30 m below MNTN E1 samples, MNTN E4 UCS-1 (2643.46 m) and TXC-2 (2643.50 m) display significantly different mean EIT results of 43.0 ± 12.1 and 48.9 ± 97 15.0 GPa (Figure 2.43). While only 4 cm apart, indentation testing captures the variation in mechanical properties between these two samples. Underlying MNTN E1 and E4 are MNTN D samples, at depths between 2682.44 m and 2683.06 m (Figure 2.44). MNTN D samples display fluctuating mean EIT results ranging 35.4 ± 8.4 to 48.7 ± 11.4 GPa (Table 2.14). MNTN D TXC-4, TXC-1 and UCS-1 were sampled 4 to 6 cm apart from each other, with UCS-1 48 cm above UCS-3 and 52cm above TXC-2. Higher MNTN D samples measure relatively similar indentation mechanical properties compared to lower MNTN D samples (UCS-3 and TXC-2). Significant differences in mean EIT are observed when comparing results of TXC-4 with UCS-3 or TXC-2, and between UCS-3 and TXC-2 (a 4 cm difference in depth) (Figure 2.44). Seven samples of MNTN C were sampled and tested with instrumented indentation, with the shallowest 6 sample depths ranging 2733.71 to 2733.91 m, and the deepest sample at 2734.37 m. MNTN C samples have mean EIT results ranging 32.9 ± 10.1 to 46.7 ± 10.9 GPa (Table 2.14). Once again, variability in sample indentation mechanical properties show significant change across sampling depth differences of mere centimeters (Figure 2.44). MNTN B samples are the deepest samples tested from the Montney Formation of well 06-28. Mean EIT for the seven MNTN B samples range from 33.6 ± 10.0 to 45.3 ± 13.4 GPa, sampled from depths of 2770.28 to 2770.55 m (Table 2.14). Variability between MNTN B subsamples display similar trends to other stratigraphic groups: mean sample indentation results demonstrate a mix of similar, small variation, and significant changes in indentation results (Figure 2.44). 98 Figure 2.43: Indentation Modulus vs Depth for PHOS (top), MNTN E1 (middle), and MNTN E4 (bottom) samples of well 06-28-078-19W6. Error bars display standard deviation of mean EIT. 99 Figure 2.44: Indentation Modulus vs Depth for MNTN D (top), MNTN C (middle), and MNTN B (bottom) samples of well 06-28-078-19W6. Error bars display standard deviation of mean EIT. 100 2.4 Chapter Conclusions In this chapter, the utility of instrumented indentation in characterizing indentation mechanical variability is evaluated. Instrumented indentation is applied to mineral samples of dolomite, calcite, and quartz to assess the effects of indentation measurement parameters where sample composition is relatively constant. Sample size, maximum indentation load, number of indentation measurements, and indentation type are assessed for their effects on indentation results. Mean indentation results and repeatability of repeated indentation testing on single subsamples, and subsample indentation results from a single sample of shale, are compared to assess how representative indentation results are from each scale of measurement. Mean indentation results from unoriented and oriented subsamples are compared to evaluate the effects of sample orientation and mechanical anisotropy on indentation results. Lastly, upscaled indentation results from shale samples are compared to demonstrate the utility of instrumented indentation for characterizing variability of indentation results between shale samples. For instrumented indentation to be applicable to characterizing shale drill cuttings, the technique must produce reliable indentation results on small samples. In this study, repeatable indentation results are measured on dolomite of sample size 100 mesh (177 µm) and larger, and Montney Formation shales of sample size 20 mesh (841 µm) and larger. In previous studies, artificial and actual drill cuttings 1 – 5 mm in length were successfully tested for their mechanical properties (Abousleiman et al., 2009; Kumar et al., 2012; Glover et al., 2015); therefore, results from this study confirmed previous studies that instrumented indentation can be applied to drill cuttings sized samples without any effect from sample size. Chapter 3 applies instrumented indentation to characterize actual drill cuttings samples. 101 Maximum indentation load should be selected based on the desired scale of interest, as indentation area increases with load. In this study, a larger indentation area and composite material response of multiple shale components is targeted, in order to measure average indentation mechanical properties of a shale sample. Maximum indentation loads between 50 mN and 200 mN do not significantly affect indentation results in mineral or shale samples. A maximum indentation load of 200 mN is selected for standard indentation measurements in Montney Formation shales, as it is the highest load found to measure repeatable and representative results, while indenting the most amount of area per measurement. The number of indentation measurements required to characterize the indentation mechanical properties of a sample is difficult to define, as it depends on several factors including the sample material, sample size, and indentation parameters. In this study, a running average is applied to indentation results, with a cutoff of two times the standard error of the mean indicating a stable mean indentation result. Using this cutoff, a minimum suggested number of indentations of 83 is suggested for Montney Formation shale samples of this study. Previous studies focusing on the composite response of shales many components have applied a running average to determine a minimum number of indentations of 40 (Miller, 2016) and 80 (Lui et al., 2016) on Bakken Formation shales. In general, indentation studies employing grid indentation state that a large number of indentation measurements should be made over a representative area of a sample (e.g. Constanides et al., 2006). The suggested minimum number of indentations of 83, from the running mean cutoff in this study, can be used as a guideline to increase the likelihood of measuring mean indentation results that are representative of the shale sample; however, in 102 larger samples, or highly heterogeneous samples, additional indentation measurements should be considered to ensure a representative mean indentation result is measured. Standard and Sinus measurement types are evaluated for their effects on indentation results, but no distinct advantage or disadvantages are observed in this study. Compared indentation results from standard and CSS measurements on the same subsample demonstrate 79% repeatability of mean EIT with 95 % confidence, overlap in mean EIT values within 1 standard deviation, and a strong linear correlation (R2 = 0.93) between compared standard and CSS indentation results. Standard indentation measurements are used to test all samples within this study because indentation measurements are quicker and allow larger areas of a sample to be measured due to higher possible maximum indentation loads of 200 mN compared to an instrument maximum of 100 mN for CSS measurements. A larger indented area covers more components of a shale sample, providing an averaged, composite indentation response. Mean indentation results and repeatability are compared at various scales of measurement to assess reliability of measurements and the number of tests or subsamples to test for representative mean indentation results. Compared results from repeated indentation tests show 78 % repeatability across 23 comparisons, overlap in mean EIT values within 1 standard deviation, and a strong linear correlation (R2 = 0.89) between mean EIT of compared tests. Indentation results from repeated indentation tests suggest that individual indentation tests can provide repeatable results that are representative of subsample indentation mechanical properties. Compared indentation results from unoriented subsamples show 69 % repeatability across 13 comparisons, 100 % overlap in mean EIT values within 1 standard deviation, and a strong linear correlation between mean EIT of compared subsamples (R2 = 0.94). Instrumented indentation 103 measures indentation results from unoriented subsamples that are representative of indentation mechanical properties of shale samples; however, variation in subsample indentation results may be present due to local heterogeneity and subsample orientation. Similarly, compared indentation results from oriented subsamples show 80 % repeatability across 15 comparisons, 100% overlap in mean EIT values within 1 standard deviation, and a strong linear correlation between mean EIT results (R2 = 0.89). In addition to oriented subsamples providing representative sample indentation mechanical properties, mean EIT X1:X3 is greater than 1.0 in 80 % of oriented subsample comparisons, indicating the influence of mechanical anisotropy on indentation results. Subsamples oriented with bedding parallel to the direction of indentation have 2 – 18 % higher mean EIT than subsamples with bedding oriented perpendicular to the direction of indentation, in 12 of 15 comparisons. The remaining 3 oriented subsample comparisons have mean EIT X1:X3 of 0.97, 0.99, and 0.99 suggesting limited influence of orientation on indentation results in these three samples, possibly due to local relative homogeneity of subsamples. Indentation mechanical anisotropy is caused by the preferential alignment and distribution of clay minerals within shale subsamples; depending whether bedding is parallel or perpendicular to the direction of indentation, the alignment of minerals contributes to the stiffness or flexibility of the sample. Due to the difficulty of determining the orientation of small samples of shale, such as drill cuttings, the ability to measure repeatable subsample indentation results is important. Repeatability of 69 % and 80 % suggests that indentation of both unoriented and oriented samples provide indentation results that are representative of sample indentation mechanical properties, but also express subsample heterogeneity and influence of bedding orientation. Thus, 104 multiple subsamples should be tested to account for local heterogeneity and differences in bedding orientation, as would be the case when testing shale drill cuttings. Indentation results for a shale sample combine indentation measurements from all tests and subsamples of that sample. Sample indentation results can be used to characterize the variability in indentation mechanical properties between samples, even at small differences in depth. The utility of instrumented indentation is demonstrated through the characterization of samples through the stratigraphy of well 06-28-078-19W6. Significant differences in mean EIT are observed between stratigraphic units (e.g. PHOS and MNTN E1) or within stratigraphic units between samples with centimeter differences in sampling depths (e.g. MNTN E1 – TXC-4 at 2611.73cm and TXC-5 at 2611.84 cm). If applied to shale drill cuttings, sampled at frequent intervals, instrumented indentation can measure the indentation mechanical variation throughout a wellbore. Even within the lateral portion of a horizontally drilled well, indentation results can characterize the subtle variation in geomechanical properties within the same geological unit. 105 Chapter 3: Instrumented Indentation Analyses of Heterogeneous Shales: Comparing Drill Cuttings, Core Chips, and Core Plug Data. 3.1 Introduction Extraction of hydrocarbons from shale reservoirs is facilitated by hydraulic fracturing carried out from multi-well pads of horizontally drilled wellbores, that extend kilometers in lateral length (King, 2010; King, 2012). For example, in British Columbia, an estimated 98% of wells in production in 2017 were hydraulically fractured (BCOGC, 2018). As the lateral lengths of horizontal wells are drilled longer, an increasing number of hydraulic fracture stages are required to access the reservoir (Spain et al., 2015). It has been argued that 40 – 60 % of fracture stages and perforation clusters may not contribute to production (Miller et al., 2011) due to failure of fracture initiation or propagation. Completions are generally spaced at even intervals without regard for geomechanical variation along the wellbore (Glover et al., 2015), which may be a contributing factor in stage failure. A better understanding of geomechanical and mineralogical variability along a wellbore, combined with formation-specific knowledge, might allow for more successful planned completions (Britt and Schoeffler, 2009; King, 2010; Sondergeld et al., 2010; Cadwallader et al., 2015). One technique that has been applied to characterizing geomechanical variation of shale samples is instrumented indentation (e.g. Ulm et al., 2006). Most indentation studies have focused on various formations in the United States (e.g. Abedi et al., 2016), China (e.g. Han et al., 2015), and South America (e.g. Boulenouar et al., 2017). To the authors knowledge, the 106 Montney Formation of northeast BC and Alberta has been assessed in very few instrumented indentation studies (e.g. Qiu et al., 2019); therefore, applying instrumented indentation to samples of the Montney Formation in this study adds value by ensuring the technique is applicable to one of the most productive formations in Canada. Also, the majority of previous indentation studies on shale have used relatively large shale core chips samples, or artificial drill cuttings (e.g. Abousleiman et al., 2009). This study tests both shale core chips and actual drill cuttings, assessing the utilization of the technique for characterizing small sample sizes. Actual drill cuttings have only been tested in a handful of studies (e.g. Glover et al., 2016) and strong relationships have not been demonstrated between geomechanics or mineralogy of core chips and drill cuttings samples. Indentation mechanical results have been compared to core plug mechanical results with good correlation (e.g. Kumar et al., 2012; Shukla et al., 2013), as well as to XRD mineralogy to investigate relationships between composition and indentation results (e.g. Han et al., 2018); however, these studies did not include actual drill cuttings samples, nor did they include samples from the Montney Formation. This study aims to characterize the indentation mechanical variation of core chips and drill cuttings from Montney Formation shales, while evaluating for correlation between indentation results and core plug mechanical data or X-ray diffraction (XRD) mineralogy. If sampled every few meters, drill cuttings can be analyzed with instrumented indentation and indentation results can be used to define wellbore geomechanical and mineralogical variability at a high resolution. Indentation results, correlated to core plug mechanical data or XRD mineralogy, could be used to plan hydraulic fracture completions in geomechanically favourable locations along the wellbore lateral. 107 3.2 Samples and Methods 3.2.1 Samples Mechanical data from previous uniaxial and triaxial testing on shale core plug samples guided sample selection in this study. Wells and sample depths of interest were selected based on the quantity, quality, and variety of core plug static (Es) and dynamic (Ed) Young’s modulus data. Using compiled core plug data, 77 samples of heterogeneous shale were identified and collected from the Montney Formation (64 samples), underlying Belloy Formation (8 samples), and overlying Doig Formation (5 samples). These samples were collected from wells 06-28-078-19W6 (06-28), 01-20-063-08W6 (01-20), 09-23-064-04W6 (09-23), 12-12-064-04W6 (12-12), 13-28-064, 05W6 (13-28), A01-32-083-25W6 (A01-32), and C-004-F/094-G-08 (C-004). In addition to core chip samples, 21 drill cuttings samples from the Montney Formation were collected from wells A01-32 and C-004. Drill cuttings samples were collected from vials representing 5-m depth intervals that aligned with the closest available depths of core chip samples of these wells. Drill cuttings samples were labelled starting with ‘DC’, then the depth they were sampled. For example, sample DC-1780m indicates drill cuttings from a sampling depth of 1780m. Of the 77 samples with core plug data, 64 core chips (from wells 01-20, 09-23, 12-12, 13-28, A01-32, C-004), and all 21 drill cuttings (from wells A01-32 and C-004), were subsampled for X-Ray diffraction mineralogical analyses. 108 3.2.2 Sample Preparation 3.2.2.1 Indentation Samples Shale samples are crushed then representative, mm-scale core chip subsamples (or drill cuttings) are mounted in 2.5 cm diameter, circular plexiglass tubing with epoxy (Figure 3.1). Shale core chip subsamples are mounted with bedding oriented parallel (X1), perpendicular (X3), or at random, with respect to the direction of indentation testing. To minimize the effects of sample surface roughness on indentation results, samples are ground with 240 and 600 grit silicon carbide paper, then polished with 0.3 µm aluminum oxide powder followed by colloidal silica. Between grinding and polishing steps, the samples are rinsed and placed in an ultrasonic bath for 2 minutes. Samples are dried for at least 24 hours before indentation testing. 109 Figure 3.1: Polished heterogeneous shale samples of sample Set 1. From left to right: 7G-1 to 7G-4 (top); 7G-6 to 7G-9 (middle); 7G-10 to 7G-13, 7G-15 (bottom). Subsamples in Set 1 are oriented with bedding parallel (left) and perpendicular (right) to direction of indentation. 3.2.2.2 X-Ray Diffraction Samples X-ray diffraction samples (Figure 3.2) are prepared following the modified smear mount method presented by Munson et al. (2016). Shale core chips and drill cuttings are manually crushed with a cast iron pestle and mortar. A portion of crushed sample material is mixed with ethanol and hand ground for several minutes, using an agate pestle and mortar. The sample-ethanol slurry is then transferred evenly onto 2.54 cm diameter glass slides and allowed to dry. 110 Figure 3.2: XRD smear mount samples of well 01-20-063-08W6. 3.2.3 Hardness and Indentation Testing 3.2.3.1 Background Hardness, H, indicating the resistance of a material to permanent deformation (Fischer-Cripps, 2004; Broz et al., 2006), is numerically equal to the contact area, A, under a maximum load, Pmax (Oliver and Pharr, 1992; 2004), defined as: 𝐻 =𝑃𝑚𝑎𝑥𝐴 (1) Indentation methods, including Brinell, Knoop, Vicker’s, and Rockwell tests, were developed to test hardness by using a material of known mechanical properties to indent a 111 material of unknown properties (Fischer-Cripps, 2004). Indentation methods differ by the way indentation results are calculated, the scale of indentation, and the geometry of the indenter tip used. In this study, indentation methods are divided into manual and instrumented indentation. Manual indentation methods, including traditional versions of Brinell, Knoop, Vicker’s and Rockwell tests, require the user to measure the area of the residual indentation impression in order to calculate hardness (Oliver & Pharr, 1992; Fischer-Cripps, 2004). Indentation displacements for manual indentation methods are often measured in millimeters (10-3 m). Instrumented indentation testing, with measurement precision at the micrometer (10-6 m) and nanometer (10-9 m) scales, is automated, recording load and displacement at a selected frequency throughout loading and unloading cycles. Indentation hardness is then calculated based on an area that is a function of the depth of indenter penetration into a sample and the geometry of the indenter tip (Fischer-Cripps, 2004). For nanoscale (indentation displacement of 10-9 m to 10-6 m) instrumented indentation testing, a 3-sided, pyramidal Berkovich indenter is most commonly used as it’s easier to construct the Berkovich tip to an accurate, single point (50 – 200 nm tip radius) (Fischer-Cripps, 2004), compared to 4-sided, pyramidal Vickers or Knoop indenters. Accurate indenter tip shape geometry is important as the indentation area used in the hardness calculation is measured by a calibrated area function of indenter displacement and geometry. At low loads, and minimal displacement of the indenter into a sample, only a small portion of the indenter may penetrate the sample, therefore the indenter tip needs to be as true to the geometry of the rest of the indenter as possible to obtain accurate results. At higher loads and displacements, more of the indenter 112 penetrates the sample, therefore the exact geometry of the indenter tip is less important than the geometry of the indenter at a point higher up on the indenter. 3.2.3.2 The Oliver and Pharr Method of Instrumented Indentation The current standard for instrumented indentation testing of homogeneous materials (ASTM E2546 – 15, 2015) is largely based on the techniques proposed by Oliver and Pharr (1992; 2004). In the Oliver and Pharr technique (1992; 2004), instrumented indentation begins with an approach phase where the indenter tip (a Berkovich diamond, in this study) is lowered until contact is made with the sample surface, initiating the loading phase. During the loading phase, load, P, and displacement, h, are measured as the indenter tip penetrates the sample material. The load increases until a (preset) maximum indentation load, Pmax, or maximum displacement, hmax, is reached. An optional hold phase may be set at the maximum load or displacement, after which the indenter is unloaded. Load, hold, and unload phases may be customized to desired loading rates or durations. Figure 3.3 shows an example of a load-displacement (P-h) curve received from each instrumented indentation measurement. Figure 3.4 shows a schematic cross-section of an indentation through loading and unloading cycles, displaying important geometric variables such as the permanent depth of penetration, hf. 113 Figure 3.3: Example of an indentation measurement load-displacement curve, with annotation of indentation phases and variables (based on Oliver and Pharr, 2004). Figure 3.4: Schematic cross-section of indentation with key geometric variables of loading and unloading (based on Oliver and Pharr, 2004). 114 Using the initial slope of the unloading section of the P-h curve, elastic unloading stiffness, S, is calculated as: 𝑆 = 𝑑𝑃𝑑ℎ (2) Unloading curves are approximated by a power law relation: 𝑃 = 𝛼(ℎ𝑚𝑎𝑥 − ℎ𝑓)𝑚 (3) Where α and 𝑚 are power law fitting constants. According to Oliver & Pharr (2004), it is assumed that the pyramidal Berkovich indenter behavior can be modeled by a conical indenter by applying a half-angle, ϕ, of 70.3° to give the same depth-to-area relationship; that contact surfaces sink as flat elastic half-space models of similar geometry; and that pile up of sample material around a residual indentation is negligible. Following these assumptions, sink-in, hs, is estimated as: ℎ𝑠 = ϵPmaxS, (4) where ϵ = 0.75 is a geometric constant of the indenter. Using hs to approximate contact surface displacement, the depth that contact is made between the indenter and sample, hc = hmax - hs, is: ℎ𝑐 = ℎ𝑚𝑎𝑥 − 𝜖𝑃𝑚𝑎𝑥S , (5) An indenter shape area function, F(ℎ𝑐), is created through the calibration of the indenter tip. Knowing the difference between displacement caused by initial contact, and maximum displacement, the indenter area function is used to calculate the contact area of the indentation: 𝐴𝑃 = 𝐹(ℎ𝑐) (6) Indentation Hardness can then be estimated as: 115 𝐻𝐼𝑇 =𝑃𝑚𝑎𝑥𝐴𝑝 (7) HIT is a measure of apparent hardness – the material resistance to the combined plastic and elastic deformation (Fischer-Cripps, 2011). For this reason, it tends to be less than true hardness in materials with significant elastic recovery (Fischer-Cripps, 2011). Unloading stiffness also allows the calculation of indentation elastic moduli through the following equations: Reduced Modulus, 𝐸𝑟: 𝐸𝑟 = √𝜋 𝑆2 𝛽 √𝐴𝑝(ℎ𝑐) (8) Where β is a dimensionless correction factor; β = 1.034 for a Berkovich diamond indenter. Plane Strain Modulus, 𝐸∗, can then be calculated using 𝐸𝑟, the elastic modulus of the indenter (𝐸𝑖) , and Poisson’s ratio of the indenter (𝑣𝑖): 𝐸∗ = 11𝐸𝑟−1 − 𝑣𝑖2𝐸𝑖 (9) Where 𝐸𝑖 = 1141 GPa, and 𝑣𝑖 = 0.07 for a diamond Berkovich tip indenter. Using an estimated Poisson’s ratio of the sample being indented, 𝑣𝑠, Indentation Modulus, 𝐸𝐼𝑇, can be calculated: 116 𝐸𝐼𝑇 = 𝐸∗(1 − 𝑣𝑠2) (10) Based on the Poisson’s ratios associated with pre-existing static and dynamic measurements on shale core plug data, a 𝑣𝑠 = 0.25 is used for indentation measurements on shale core chips and drill cuttings. Uncertainty in a Poisson’s ratio of 0.25 ± 0.1 results in an approximate 5% uncertainty in resulting elastic modulus (Hay and Pharr, 2000). 3.2.3.3 Instrumented Indentation in this Study Instrumented indentation in this study is performed using an Anton Paar NHT2 Indenter (NHT2). A single indentation is referred to as an indentation measurement (Figure 3.5). Indentation measurements are calibrated on a fused silica standard with a mean EIT of 73.2 ± 0.3 GPa and mean HIT of 9450 ± 550 MPa. The motorized stage of the NHT2 Indenter allows for pre-selection of multiple indentation measurement sites, which can be automatically analyzed in the order they are selected. A pre-selected list of multiple indentation measurements made subsequently is referred to as an indentation test (Figure 3.5). Indentation software is used to pre-select measurement sites in grid patterns (Figure 3.6Figure 2.8), or as individual points where sample size is limited. Spacing between indentation measurements, and from sample-epoxy boundaries, is selected as 100 µm or 200 µm to ensure sufficient indentation spacing of at least 10 times indentation depth (Sudharshan Phani and Oliver, 2019). Standard and Sinus measurement types are analyzed in this study. Standard measurements follow the load-hold-unload cycle of instrumented indentation, with load increasing linearly to a designated 𝑃𝑚𝑎𝑥 (or maximum displacement). Sinus measurements differ 117 by applying a sine wave oscillation during the loading process, providing a depth-related analysis within 1 cycle of indentation. Sinus measurements are further defined by loading method into Linear Strain Sinus (LSS) and Constant Strain Sinus (CSS) measurements: LSS measurements load with a linear increase in strain, whereas CSS measurements load with a constant strain rate. CSS measurements are particularly useful where the mechanical properties of the sample material are strain rate dependent, or a depth-based assessment of indentation results are desired. Regardless of indentation type, prior to data analysis indentation results are filtered and corrected for data quality assurance. In this study, indentation results are presented as a sample mean indentation result, which averages the results of all indentation measurements, for all indentations tests, on all subsamples of a given sample (Figure 3.5). 118 Figure 3.5: Schematic, plan-view diagram distinguishing indentation measurements (black squares), indentation tests (encompassed by red squares), and subsamples of a shale sample (core chips). Indentation results in this study are presented for individual indentation measurements, indentation tests, subsamples (multiple tests), and samples (multiple subsamples). 119 Figure 3.6: Grid indentation set-up (white squares, background image) and example of sample surface before and after indentation measurements (inlays) on >4 mesh dolomite In this study, repeatability refers to similarity of compared results based on two-sample t-Tests assuming unequal variances. For a significance level of 0.05, this t-Test assesses the probability that the difference of sample mean indentation results are within a 95% confidence interval of a common population mean. Mean indentation results that display a t-statistic lower than the critical value are designated as similar, or repeatable. When the t-statistic for compared 120 indentation test results is greater than the critical value, indentation results are examined for factors affecting repeatability, such as measurement parameters, representative testing and sampling, and shale anisotropy. 3.2.4 X-Ray Diffraction X-Ray diffraction data is collected using a Bruker AXS D8 Focus with normal-focus CoKα radiation. Diffraction results are gathered for a 2ϴ range of 3-80°, at a step size of 0.03°, with 0.7 s per step while spinning at 15 rpm. Phase quantification is done using the Rietveld method of phase analysis (Rietveld, 1967; Figure 3.7). 121 Figure 3.7: Example of an XRD diffractogram, with analyzed phases of sample RM4-A. 122 3.3 Results and Discussion 3.3.1 Variability and Repeatability of Indentation Results In Chapter 2, the influence of indentation measurement parameters on indentation results are assessed for mineral and shale core chip samples. Across multiple scales of comparison, instrumented indentation produces representative but variable indentation results (Figure 3.8): • Compared mean EIT results from indentation tests shows 78 % repeatability and strong linear correlation (R2 = 0.89) between compared results. Indentation test mean EIT results overlap within 1 standard deviation, in 100 % of comparisons. This suggests that mean indentation results from individual indentation tests provide good estimates of subsample indentation mechanical properties; however, multiple indentation tests should be performed on a subsample to fully characterize its subsample indentation mechanical properties. • Compared mean EIT results from unoriented subsamples show 69 % repeatability and strong linear correlation (R2 = 0.94) between compared results. Unoriented subsample mean EIT results overlap within 1 standard deviation in 100 % of comparisons. This suggests that mean indentation results from unoriented subsamples provide good estimates of sample indentation mechanical properties; however, multiple subsamples should be tested to fully characterize sample indentation mechanical properties. • Compared mean EIT results from oriented subsamples show 80 % repeatability and strong linear correlation (R2 = 0.89) between compared results. Oriented subsample mean EIT results overlap within 1 standard deviation in 100 % of comparisons. Indentation mechanical anisotropy is assessed using a ratio of X1:X3 for indentation results, where X1 indicates a subsample with bedding oriented parallel to the direction of indentation 123 and X3 indicates bedding oriented perpendicular to the direction of indentation. Mean EIT X1:X3 are greater than 1.0 for 80 % of compared oriented subsamples, indicating mechanical anisotropy effects on indentation results due to sample orientation. This suggests that mean indentation results from oriented subsamples provide good estimates of sample indentation mechanical properties; and supports testing of multiple subsamples to fully characterize heterogeneities and differences in orientation of shale subsamples, in order to fully characterize sample indentation mechanical properties. • Compared mean EIT results from standard and constant strain sinus indentation measurements on shale core chip subsamples show good linear correlation (R2 = 0.93) between these two measurement types. Standard and CSS mean indentation results were repeatable in 79% of comparisons, though mean EIT results tend to be slightly higher from CSS measurements than standard measurements. Higher mean EIT for CSS is explained by the lower CSS Pmax of 100 mN, compared to standard 200 mN, measuring a less composite material response. Standard type indentations are selected for further indentation testing for faster indentation testing and access to higher possible maximum indentation loads. The results presented in Chapter 2 demonstrate that instrumented indentation is an effective technique for characterizing variability in indentation mechanical properties of shale core chip samples. Chapter 2 focused on upscaling indentation test and subsample results as representative sample mean indentation results (Figure 3.9, boxes highlighted in orange). This chapter focuses on the comparison of indentation results from indentation of shale core chips and drill cuttings samples with core plug static and dynamic Young’s modulus data and XRD mineralogy (Figure 3.9, highlighted in red). 124 Figure 3.8: Mean EIT results for comparisons of indentation test (top-left), oriented and unoriented subsamples (middle-right), and standard and CSS measurement types (bottom-left). 125 Figure 3.9: Summary of sample types and results examined in this study. Chapter 2 focused on upscaling indentation results (highlighted in orange). Chapter 3 focuses on the comparison of indentation results, XRD mineralogy, and core plug data (highlighted in red). 126 3.3.2 An Overview of Geomechanical and Mineralogical Results and Comparison In this study, three types of results are compared: sample mean indentation results, core plug mechanical data, and XRD mineralogy (Figure 3.9). Sample indentation results and XRD mineralogy are measured from shale core chips and drill cuttings samples, whereas core plug mechanical data is compiled triaxial and uniaxial compression data from previous studies. Shale core chips samples were generally sampled from core slabs cut adjacent to previously tested core plugs, rather than directly from original core plugs, due to core lab restrictions; therefore, in this study it is assumed that core chips samples are representative of original core plugs in order to compare indentation results with core plug data. Shale drill cuttings were available at 5 m depth intervals in wells A01-32 and C-004. Drill cuttings samples were taken from depth intervals closest to the depths of core chips samples and core plug data, to best approximate sampling depths and compare results. Variation in mean indentation results for shale core chips and drill cuttings samples, organized by formation (Figure 3.10) and by well (Figure 3.11), demonstrates the utility of instrumented indentation for characterizing indentation mechanical properties of shale. Each core chip or drill cuttings sample is represented by a unique mean EIT value, averaging up to hundreds of indentation measurements across multiple subsamples. 127 Figure 3.10: Sample mean indentation results for core chips and drill cuttings shale samples, organized by formation. 128 Figure 3.11: Sample mean indentation results for core chips and drill cuttings shale samples, organized by well.129 To check for broad geomechanical correlations across the dataset in this study, mean EIT from core chips samples are compared to core plug static and dynamic Young’s moduli (Figure 3.12). Static and dynamic Young’s moduli are plotted as a test of reliability of core plug data, as Es and Ed have a widely documented relationship (e.g. Zhang, 2006). Where the correlation between Es and Ed is weak, the reliability of core plug data is considered weak and correlations with mean EIT may be unreliable. Across all samples, mean EIT has weak linear correlations with Es (R2 = 0.30) and with Ed (R2 = 0.19), whereas core plug Es and Ed data demonstrate a strong linear correlation (R2 = 0.73). To explore whether mean EIT has a better relationship with Es or Ed for individual wells, geomechanical data is separated by well (Figure 3.13; Figure 3.14): • Mean EIT and Es have a strong relationship for samples of well 09-23 (R2 = 0.94); moderate in 01-20 (R2 = 0.62); weak in 06-28 (R2 = 0.31), A01-32 (R2 = 0.32), and 12-12 R2 = 0.24); and negligible in 13-28 (R2 = 0.01) and C-004 (R2 = 0.00). • Mean EIT and Ed show a strong relationship for samples of well 09-23 (R2 = 0.96); moderate in 01-20 (R2 = 0.44); weak in A01-32 (R2 = 0.14), and negligible in 12-12 (R2 = 0.00) and C-004 (R2 = 0.00). • Core plug Es and Ed data show a strong relationship in samples of wells C-004 (R2 = 0.87), 09-23 (R2 = 0.82), A01-32 (R2 = 0.78), and 01-20 (R2 = 0.75), but negligible correlation is observed in well 12-12 (R2 = 0.01). These relationships are explored, on a well by well basis, in the following sections. 130 Figure 3.12: Es-EIT (top), Ed- EIT (middle), and Es-Ed (bottom) cross-plots for all mean indentation results and core plug static and dynamic Young’s modulus data. 1:1 ratio is displayed as dotted black line. 131 Figure 3.13: Geomechanical correlations between mean EIT, Es, and Ed for samples of wells 01-20-063-08W6, 12-12-063-04W6, and 09-23-064-04W6. 132 Figure 3.14: Geomechanical correlations between mean EIT, Es, and Ed for samples of wells 13-28-064-05W6, 06-28-078-19W6, A01-32-083-25W6, and C-004-F/094-G-08. 133 In addition to geomechanical testing and comparison, XRD mineralogy is assessed for 49 core chips and 21 drill cuttings samples of shale. The mineralogy for all shale samples tested in this study is compared in ternary diagrams of normalized weight percentage of clays, carbonates, and combined quartz and feldspar (Figure 3.15). A large amount of variation in mineralogy is observed, questioning whether there may be a relationship to the variation in indentation mechanical results. Across all samples tested in this study, only weak correlations are observed between mineralogy and geomechanical moduli (Figure 3.16): Mean EIT shows a weak negative linear correlation with quartz (R2 = 0.18), negative correlation with feldspar (R2 = 0.05), and positive correlation with carbonates (R2 = 0.20); Es and Ed core plug data show similar trends, demonstrating weak linear correlation with quartz (R2 = 0.10 and 0.11), feldspar (R2 = 0.13 and 0.06 ), and carbonates (R2 = 0.10 and 0.20). In subsequent sections, more detailed comparisons and analyses between mineralogy, indentation results, and core plug mechanical data are presented for each well. 134 Figure 3.15: XRD mineralogy of core chip and drill cuttings (DC) shale samples, sorted by well (top) and formation (bottom). Values are normalized weight % for quartz and feldspar, carbonates, and clays. 135 Figure 3.16: XRD mineralogy versus mean EIT, mean HIT, depth, Es, and Ed (columns, left to right) for all samples in this study. Mineralogy is displayed as wt. % of quartz, carbonates, feldspar, and clays (rows, top to bottom). 136 3.3.3 Comparing Shale Core Chips and Core Plug Data In wells 06-28, 01-20, 09-23, 12-12, and 13-28, core chips are the only sample type tested because drill cuttings were not available for sampling. Out of these wells, XRD analyses are performed on samples of wells 01-20, 09-23, 12-12, and 13-28. Indentation results, mineralogy, and core plug mechanical data are compared to explain variation and relationships between different results. The following subsections explore these comparisons by well. 3.3.3.1 Shell Groundbirch 06-28-078-19W6 (025466) Twenty-nine core chips are sampled from well 06-28 and results are compared to core plug data (Table 3.1). XRD is not performed on these samples due to the disaggregated nature of the core and likelihood of error in sampling, and to preserve epoxied shale core chip samples for further indentation testing. Core chips are sampled throughout the stratigraphy of the Montney Formation and overlying Doig Phosphate from six stratigraphic units: samples labeled PHOS are sourced from the Doig Phosphate, whereas samples labeled MNTN are sourced from different stratigraphic units of the Montney Formation, as denoted by the original data source (i.e. MNTN B indicates Montney Formation, lobe B). These stratigraphic units are outlined in Figure 1.4. Each stratigraphic unit is displayed as a geomechanical-depth profile in Figure 3.17, comparing core chip sample mean EIT to static Young’s modulus core plug data. Across all 29 samples, mean EIT has a negligible linear correlation with Es (R2 = 0.01) (Figure 3.14); however, this relationship improves for some individual stratigraphic units in this well. Moderate EIT-Es correlations are observed for the 4 samples from MNTN E1 (R2 = 0.54), and the 7 samples of MNTN B (R2 = 0.53). In all samples, mean EIT is greater than Es (50% load). Static unloading modulus, or Es (100% unloading), gives the Young’s moduli of fully loaded core plug samples. 137 Es (100% unloading) values are similar in value to mean EIT, and greater than Es (50% load), in all samples (Table 3.1). The linear correlation between Es (100% unloading) and mean EIT is very weak (R2 = 0.05) when comparing all 19 samples; only MNTN D samples display a significant improvement in Es-EIT correlation for different Es measurements, from R2 = 0.05 at 50% load (6 samples) to R2 = 0.48 at 100% unloading (4 samples). Geomechanical depth profiles of 06-28 are unique because of their scale (Figure 3.17): in each stratigraphic unit, samples are spaced 0.04 m to 0.66 m apart. Even at the centimeter scale, variability between indentation results is present. Geomechanical moduli show moderate to poor correlations within each stratigraphic unit; however, the general geomechanical depth profiles of indentation moduli closely follow static Young’s moduli). These results support the use of mean indentation results as an index for geomechanical variability at a high resolution within a formation, even though there is no clear correlation between mean EIT and Es for across all samples of this well.138 Core Plug Data Indentation Data Well Sample Depth (m) Es – 50% load (GPa) Unloading Modulus, Es – 100% unloading (GPa) EIT – Standard (GPa) EIT – CSS (GPa) 06-28-078-19W6 PHOS - UCS-2 2592.94 25.6 – 60.0 ± 14.4 61.9 ± 13.0 PHOS - TXC-3 2592.98 28.8 41.5 62.6 ± 11.3 64.0 ± 13.3 PHOS - UCS-1 2593.02 21.8 – 66.9 ± 13.0 66.7 ± 16.2 PHOS - TXC-2 2593.06 29 35.9 63.7 ± 10.4 60.3 ± 12.7 MNTN E1 - TXC-2 2611.41 27.2 37 47.7 ± 16.1 50.1 ± 15.7 MNTN E1 - TXC-3 2611.46 27.8 50.7 54.0 ± 14.9 51.2 ± 14.9 MNTN E1 - TXC-4 2611.73 24.6 35.3 50.1 ± 13.8 50.3 ± 15.6 MNTN E1 - TXC-5 2611.84 33.1 40 42.0 ± 11.1 46.6 ± 15.2 MNTN E4 - UCS-1 2643.46 22.8 – 43.1 ± 13.3 47.3 ± 14.6 MNTN E4 - TXC-2 2643.5 24 38.3 48.1 ± 15.4 52.3 ± 14.7 MNTN D - TXC-4 2682.44 31.7 39.8 44.7 ± 11.6 46.9 ± 14.1 MNTN D - TXC-1 2682.5 27.6 33.8 48.5 ± 13.1 49.4 ± 15.8 MNTN D - UCS-1 2682.54 35.8 – 43.0 ± 11.5 46.7 ± 13.2 MNTN D - UCS-3 2683.02 21.3 – 35.6 ± 8.5 39.9 ± 13.5 MNTN D - TXC-2 2683.06 27.1 32.3 47.9 ± 10.7 51.2 ± 15.1 MNTN C - UCS-3 2733.71 23.3 – 46.7 ± 11.0 43.3 ± 13.7 MNTN C - UCS-1 2733.75 24.1 – 44.5 ± 12.2 49.6 ± 14.3 MNTN C - UCS-2 2733.78 24.5 – 39.9 ± 10.9 47.9 ± 13.4 139 Core Plug Data Indentation Data Well Sample Depth (m) Es – 50% load (GPa) Unloading Modulus, Es – 100% unloading (GPa) EIT – Standard (GPa) EIT – CSS (GPa) MNTN C - TXC-1 2733.81 26 31.9 32.9 ± 9.5 37.2 ± 10.9 MNTN C - TXC-2 2733.85 29.5 38.1 41.5 ± 13.2 47.5 ± 15.5 MNTN C - TXC-3 2733.91 33.1 41.1 37.9 ± 10.0 40.2 ± 13.3 MNTN C - TXC-4 2734.37 28.6 37.1 46.5 ± 14.4 48.4 ± 15.5 MNTN B - TXC-5 2770.28 27.3 40.5 36.6 ± 10.8 45.3 ± 12.0 MNTN B - UCS-1 2770.32 15.1 – 33.6 ± 10.1 36.8 ± 14.8 MNTN B - TXC-3 2770.35 25.4 36.1 40.8 ± 11.4 46.4 ± 15.2 MNTN B - TXC-2 2770.48 27.2 37.3 40.8 ± 11.2 43.2 ± 10.7 MNTN B - TXC-1 2770.51 26.4 32.1 42.4 ± 13.5 46.4 ± 10.8 MNTN B - TXC-4 2770.55 26.7 39.5 44.2 ± 13.4 47.4 ± 15.9 MNTN B - UCS-3 2770.62 21 – 38.2 ± 9.9 42.3 ± 16.1 Table 3.1: Indentation results and core plug data for samples of well 06-28-078-19W6.140 Figure 3.17: Geomechanical-depth profiles for stratigraphic units of well 06-28-078-19W6. Top to bottom, left column: Doig Phosphate (PHOS) and Montney Formation lobes MNTN E1 and MNTN E4; right column: MNTN D, MNTN C, and MNTN B. 141 3.3.3.2 7GEN Redrock 01-20-063-08W6 (469253) Six core chips are sampled from the Montney Formation of well 01-20 and characterized by instrumented indentation and XRD (Table 3.2). Samples #1 and #4 are sampled near the top of the Montney Formation, at depths of 3880.3 m and 3894.2 m. Samples #19, #25, #31, and #36 are sampled throughout the middle Montney Formation, at depths between 3966.88 m and 4048.46 m. Geomechanical and mineralogical variability is observed between samples (Table 3.2; Figure 3.18): mean EIT ranges from 52.9 to 65.6 GPa; Es ranges from 55.9 to 86.6 GPa; and Ed ranges from 58.7 to 82.2 GPa. Mean EIT shows a moderate linear correlation with Es (R2 = 0.62) and dynamic Young’s modulus at low axial confining pressure, EdlowP (R2 = 0.44) (Figure 3.13). In comparison, core plug Es has a strong linear correlation with EdlowP (R2 = 0.75). XRD results demonstrate compositional variability of 18 % to 34 % quartz, 6 % to 35 % carbonates, 9 % to 21 % feldspars, 16 % to 49 % clays, 2 % to 6 % other minerals (Table 3.2). Indentation results, XRD mineralogy, and core plug data are compared to assess the relationships of geomechanical moduli, mineralogy, and depth of samples (Figure 3.19; Figure 3.20). The strongest relationship observed is the moderate, negative linear correlation of mean EIT with quartz (R2 = 0.47). Weak correlations are observed for mean HIT and quartz (R2 = 0.21), mean EIT and clay (R2 = 0.21), quartz with depth (R2 = 0.20), and clay with depth (R2 = 0.31). Weak correlation is also observed when comparing Es or Ed core data to mineralogy. For example, quartz and carbonates increase with decreasing Es (R2 = 0.27 and 0.29) or Ed (R2 = 0.22 and 0.27); feldspar and clay increase with increasing Es (R2 = 0.19 and 0.32) and Ed (R2 = 0.28 and 0.23). 142 Core Plug Data Indentation Data X-Ray Diffraction Mineralogy Well Sample Depth (m) Es (GPa) Low Axial Confining Pressure [2900 psi] EdlowP (GPa) High Axial Confining Pressure [23 – 40*103 psi] EdhighP (GPa) Mean EIT (GPa) N Quartz (wt. %) Carbonates (wt. %) Feldspar (wt. %) Clays (wt. %) Others (wt. %) 01-20-063-08W6 #1 3880.31 62.0 67.0 71.9 57.1 ± 13.3 242 33.8 34.7 13.7 16.0 1.8 #4 3894.23 78.0 75.2 79.7 64.1 ± 10.6 295 34.0 17.9 19.7 24.4 4.1 #19 3966.88 86.6 82.2 86.7 64.6 ± 10.7 268 17.9 6.2 21.2 48.9 5.7 #25 3998.22 55.9 64.4 66.6 52.9 ± 13.9 259 32.3 15.2 19.2 31.0 2.3 #31 4026.18 64.9 58.7 65.0 55.5 ± 13.7 169 33.9 18.8 16.7 28.6 2.1 #36 4048.46 67.4 65.6 71.4 65.6 ± 16.8 263 18.6 29.8 9.4 37.8 4.5 Table 3.2: Young's and Indentation Moduli for samples of well 01-20-063-08W6. 143 Figure 3.18: Geomechanical depth profile of well 01-20-063-08W6, displaying similar trends in Es, Ed, and mean EIT between samples. 144 Figure 3.19: XRD mineralogy versus mean EIT, mean HIT, and depth (columns, left to right) for samples of well 01-20-063-08W6. Mineralogy is displayed as wt. % of quartz, carbonates, feldspar, and clays (rows, top to bottom). 145 Figure 3.20: XRD mineralogy (wt. %) versus static (Es) and dynamic (Ed) Young's modulus from core plug data of well 01-20-063-08W6. 146 Overall, geomechanical moduli and mineralogy demonstrate weak to moderate relationships in samples of well 01-20. Greater amounts of clay, and lower quartzappears to result in higher mean EIT, Es, and Ed in 01-20 samples; however, no strong relationships are observed between geomechanical moduli and mineralogy in samples of this well (Figure 3.19; Figure 3.20). These observations may appear counterintuitive to the idea that greater amounts of relatively stiff components (i.e. quartz, carbonates, and feldspars) leads to a higher indentation modulus, suggesting other contributing factors in 01-20 samples. Possible considerations may include the relative abundance of mineralogical components. Carbonates (i.e. dolomite in Montney Formation samples in this study) has a higher mean EIT than quartz and feldspars. Relatively high carbonate compositions overprinting of displacing quartz or feldspar might lead to a relatively high sample mean EIT. Additionally, high clay content and mineral alignment may result in anisotropic effects on indentation results, potentially increasing mean EIT. Aside from a weak increase in clay with depth (R2 = 0.31), mineralogy is variable with sample depth. Mineralogical variability with depth may be due to samples sourced from depths significantly different from one another across the stratigraphy of the Montney Formation. Indentation modulus demonstrates moderate linear correlations with static (R2 = 0.62) and dynamic (R2 = 0.44) Young’s moduli core plug data, which provide an index to the established relationship between Es and Ed (R2 = 0.75) (Figure 3.13). Geomechanical depth profiles show similar trends amongst geomechanical moduli (Figure 3.18). For samples of 01-20, mean EIT provides a moderate prediction of Es and Ed and representative characterization of indentation mechanical variability with depth. 147 3.3.3.3 7GEN Karr 09-23-064-04W6 (414232) Four core chips samples, labeled MP1 to MP4, are tested from well 09-23. MP1 is sampled from the Doig Phosphate at a depth of 2951.5 m, whereas MP2, MP3, and MP4 are sampled from the upper Montney Formation at depths of 2961.15, 2971,15, and 3005.20 m (Table 3.3). Geomechanical variability is observed between sample indentation results, though with different patterns than well 01-20: mean EIT results plot as intermediate values between higher Ed and lower Es, and mean EIT skews closer to Ed (Figure 3.21). The relative values of indentation, static, and dynamic Young’s moduli follow the same trend between samples, with MP1 demonstrating the highest value, MP3 in the middle, and MP2 and MP4 as relative lows. For example, mean EIT of MP1 through MP4 were 68.4, 50.6, 55.6, and 50.9 GPa. Strong linear correlations are observed between all three geomechanical values (Figure 3.13): R2 = 0.94 for Es-EIT, R2 = 0.96 for Ed-EIT, and R2 = 0.82 for Es-Ed; however, these correlations are based on only 4 datapoints and may be unreliable. The change in lithology between the Doig Phosphate (MP1) and the Montney Formation (MP2, MP3, and MP4) is marked by a decrease in indentation and mechanical moduli, as well as a significant change in mineralogy (Table 3.3). Mineralogy in sample MP1 consists of approximately 78% carbonates, 15% clays, and only 2% quartz and 4% feldspar in MP1. In contrast, samples MP2, MP3, and MP4 were composed of a more balanced mineralogy of 15 – 25% carbonates, 33 – 44% quartz, 16 – 22% feldspars, and 19 – 26% clays. Geomechanical moduli and mineralogy of 09-23 samples show a mix of strong to weak relationships (Figure 3.22): mean EIT, Es, and Ed have strong negative correlation with quartz (R2 = 0.90, 0.83, and 0.88) and feldspar (R2 = 0.87, 0.96, and 0.73); strong positive correlation 148 with carbonates (R2 = 0.97, 0.99, and 0.88); and moderate negative correlation with clays (R2 = 0.49, 0.62, and 0.36). These relationships between geomechanical moduli and mineralogy can be explained relative abundance of stiff components in samples: samples with greater abundance of dolomite relative to quartz or feldspar will have a greater sample mean EIT due to the relatively high indentation modulus of dolomite. Mineralogy also trends with depth: clays (R2 = 0.99) and feldspar (R2 = 0.73) increase strongly with depth, whereas carbonates decrease moderately (R2 = 0.45). Quartz also displays a weak positive correlation with depth (R2 = 0.16). 149 Core Plug Data Indentation Data X-Ray Diffraction Mineralogy Well Sample Depth (m) Es (GPa) Ed (GPa) Mean EIT (GPa) N Quartz (wt. %) Carbonates (wt. %) Feldspar (wt. %) Clays (wt. %) Others (wt. %) 09-23-064-04W6 MP1 2951.5 60.0 78.5 68.4 ± 8.7 264 2.4 77.5 3.9 15.4 0.9 MP2 2961.15 39.7 52.9 50.6 ± 12.4 89 44.5 19.9 15.8 18.5 1.4 MP3 2971.15 39.9 64.1 55.6 ± 12.7 180 37.1 25.5 15.8 19.4 2.2 MP4 3005.2 35.0 57.3 50.9 ± 12.8 127 33.5 15.2 22.2 26.4 2.7 Table 3.3: Indentation results, XRD mineralogy, and core plug data for samples of well 09-23-064-04W6. 150 Figure 3.21: Geomechanical depth profile of well 09-23-064-04W6. 151 Figure 3.22: XRD mineralogy versus geomechanical moduli for samples of well 09-23-064-04W6.152 In summary, samples of 09-23 show strong geomechanical relationships between mean EIT and core plug Es and Ed data, and strong correlations are observed between geomechanical moduli and mineralogy. Dolomite and quartz displace one another in relative abundance in 09-23 samples; since dolomite has a higher mean EIT than quartz, higher sample mean EIT values trending positively with dolomite abundance makes sense. With only 4 samples, these relationships should be used with caution when predicting geomechanical moduli from indentation modulus; regardless, within these samples, mean EIT can be used to distinguish geomechanical and mineralogical variation between samples. 3.3.3.4 7GEN HZ Karr 12-12-064-04W6 (466328) Six core chips of well 12-12 are sampled at depths between 2910.20 and 3107.4 m (Table 3.4). Sample 2 and Sample 5 are sampled near the top of the Montney Formation; Sample 13 and Sample 22 in the middle of the formation; Sample 35 within the lower Montney Formation; and Sample 40 is sampled near the base of the Montney Formation. Samples of 12-12 show mixed trends amongst geomechanical moduli (Figure 3.23). Static Young’s modulus is highest in Sample 2 (60.8 GPa), followed by Ed (53.6 GPa), then mean EIT (47.8 GPa). In all other samples, Ed has the highest moduli values; Es > EIT in Sample 5, Sample 13, and Sample 22; and Es < EIT in Sample 35 and Sample 40. Dynamic Young’s moduli at high axial confining pressures are greater than Ed at low pressures, with values differing by 1.0 to 4.7 GPa. As expected by the highly fluctuating moduli values, resulting correlations are negligible, except for the weak correlation between Es and EIT (R2 = 0.24). Poorly correlated results may suggest that a limited number of samples spanning across the depth of a formation may not result in useful geomechanical comparison. 153 Core Plug Data Indentation Data X-Ray Diffraction Mineralogy Well Sample Depth (m) Es (GPa) Ed -Low Axial Confining Pressure (GPa) Ed - High Axial Confining Pressure (GPa) Mean EIT (GPa) N Quartz (wt. %) Carbonates (wt. %) Feldspars (wt. %) Clays (wt. %) Others (wt. %) 01-20-063-08W6 Sample 2 2910.24 60.8 53.6 55.6 47.8 ± 14.8 90 40.2 24.6 23.9 7.7 3.7 Sample 5 2925.25 64.7 67.0 71.8 50.5 ± 14.1 174 34.0 32.2 20.0 7.4 6.5 Sample 13 2965.16 55.6 67.5 69.3 36.0 ± 13.3 70 36.8 25.2 22.1 10.1 5.8 Sample 22 3010.84 60.6 71.8 72.8 48.3 ± 14.9 58 34.0 31.6 19.1 10.6 4.6 Sample 35 3076.68 34.0 65.6 67.5 41.1 ± 14.0 141 34.9 20.4 22.5 16.5 5.8 Sample 40 3107.38 47.0 71.3 73.7 46.4 ± 13.1 185 32.5 28.8 18.7 16.6 3.5 Table 3.4: Indentation results, XRD mineralogy, and core plug data for samples of well 12-12-064-04W6. 154 Figure 3.23: Geomechanical-depth profile of well 12-12-064-04W6. 155 Even though samples are spread across the stratigraphy of the Montney Formation, mineralogy shows limited variability (Table 3.4). Mean indentation results and core plug Young’s moduli are compared to mineralogy to assess whether the slight mineralogical variability is related to geomechanical variability (Figure 3.24). Strong relationships are observed, including decreasing clay with Es (R2 = 0.82), and decreasing quartz (R2 = 0.87) and feldspar with Ed (R2 = 0.78). Moderate to weak positive relationships are found between carbonates and mean EIT (R2 = 0.43), mean HIT (R2 = 0.21), Es (R2 = 0.51), and Ed (R2 = 0.29). Clay and mean HIT also have a moderate negative correlation (R2 = 0.46), and clay decreases strongly with depth (R2 = 0.95). Geomechanical moduli show relatively poor relationships with one another (Figure 3.14), the best relationship being weak correlation between mean EIT and Es (R2 = 0.24). Weak correlation between Es and Ed data suggests poor reliability of core plug data in this well; however, similar relationships between geomechanical moduli and mineralogy suggests mineralogy may be representative of both core chip samples and core plug data. Indentation results for 12-12 samples are useful for characterizing mineralogical variation between samples, and mean EIT trends follow core plug geomechanical moduli; however, geomechanical correlations are not very useful as core plug data may be unreliable. 156 Figure 3.24: XRD mineralogy versus geomechanical moduli for samples of well 12-12-064-04W6.157 3.3.3.5 7GEN Kakwa 13-28-064-05W6 (456240) In well 13-28, 8 samples are sourced from a relatively small depth interval of 4429.11 m to 4445.64 m (Table 3.5). Samples are taken from highly disaggregated core of the Belloy Formation, which is stratigraphically below the Montney Formation. Geomechanical results demonstrate a high level of variability (Figure 3.25), with mean EIT ranging between 35.0 ± 5.7 to 62.5 ± 4.9 GPa and Es ranging between 27.7 GPa and 58.5 GPa. Mean EIT values are relatively moderate compared to highly variable Es core data. A weak correlation is observed between mean indentation modulus and static Young’s modulus core data (R2 = 0.31) (Figure 3.14). Due to the disaggregated nature of the core, sampling depths of core chips may have differed from original core plugs, which could have led to significant geomechanical variability. Overall, mean EIT follows a similar geomechanical depth profile as static Young’s modulus core data, with the exception of sample RMA-1 HZ-2. Sample RMA-1 HZ-2 has a mean EIT (38.5 ± 4.5 GPa) that is significantly lower than Es (58.5 GPa), shifting the geomechanical depth profile of mean EIT in the opposite direction of Es. This difference is attributed to sampling error due to disaggregated core, and differences in mechanical properties of the sample and original core plug, rather than instrument or measurement error. 158 Core Plug Data Indentation Data X-Ray Diffraction Mineralogy Well Sample Depth (m) Es (GPa) Mean EIT (GPa) N Quartz (wt. %) Carbonates (wt. %) Feldspars (wt. %) Clays (wt. %) Others (wt. %) 13-28-064-05W6 RMA-1 HZ-2 4429.11 58.5 38.5 ± 4.5 67 21.0 20.8 10.7 45.9 1.5 RMA-2 HZ 4430.78 51.9 58.1 ± 14.6 195 46.5 8.9 10.9 31.3 2.4 RMA-3 HZ-3 4432.79 44.1 38.8 ± 7.7 189 54.6 2.3 11.8 27.9 3.5 RMA-5 VT 4433.96 46.7 41.6 ± 8.5 47 50.3 2.3 12.2 31.8 3.4 RMA-6 VT 4436.55 37.5 35.0 ± 5.7 67 29.4 44.5 15.6 8.4 2.2 RMA-7 VT 4437.96 29.7 37.8 ± 9.1 47 67.6 9.5 13.1 6.9 3.0 RMA-8 HZ 4440.27 27.7 41.0 ± 4.4 84 52.5 6.8 18.0 18.8 3.9 RMA-11 HZ 4445.64 57.5 62.5 ± 4.9 105 4.1 87.4 4.9 2.9 0.7 Table 3.5: Indentation results, XRD mineralogy, and core plug data for samples of well 13-28-064-05W6. 159 Figure 3.25: Geomechanical-depth profile of well 13-28-064-05W6. 160 Mineralogy of 13-28 samples is highly variable, ranging 4 – 68% quartz, 2 – 87% (calcite-dominant) carbonates, 5 – 18 % feldspars, 3 – 46% clays, and 1 – 4 % other minerals (Table 3.5). RMA-11 HZ has the most distinct mineralogy with a composition, with 87% calcite, as well as the highest indentation modulus within the sample set of 62.5 GPa and the second highest Es (57.5 GPa). RMA-2 HZ also has a relatively high mean EIT of 58.1 GPa but a limited carbonate content of approximately 9%. After RMA-11 HZ, RMA-6-VT has the second highest carbonate content at approximately 45%, but the lowest mean EIT (35.0 GPa). Moderate to weak relationships are observed between geomechanical moduli and mineralogy (Figure 3.26). Weak to moderate negative correlations are observed for quartz with mean EIT (R2 = 0.21) and Es (R2 = 0.49). Weak to moderate positive correlations are seen between carbonates and mean EIT (R2 = 0.27), Es (R2 = 0.16), and depth (R2 = 0.43). Feldspar has moderate negative correlations with mean EIT (R2 = 0.51) and Es (R2 = 0.67). Clays show a weak positive correlation with Es (R2 = 0.20), and moderate negative correlation with depth (R2 = 0.74). For samples of 13-28, indentation results appear as useful as static Young’s modulus data from core plugs in characterizing variation in samples. Geomechanical moduli show similar correlations with mineralogy, including negative correlations with quartz and feldspar, and weak positive correlation with carbonates. Once again, quartz and feldspar are likely replaced by relative abundance of carbonate (as grains or cementation). Dolomite has a higher mean EIT than quartz and feldspar, resulting in a relative increase in sample mean EIT for samples with higher carbonate content. Overall, no strong correlation with mineralogy is observed for mean EIT or Es. The weak correlation (R2 = 0.31) between mean EIT indentation results and Es core data suggests indentation does not predict core plug data well. Mean EIT and Es show a similar trend with 161 depth, though Es core plug data is relatively variable. In general, mean EIT may be used as an index to characterize variability in samples of the Belloy Formation, but results are not directly related to other geomechanical moduli with high confidence. 162 Figure 3.26: XRD mineralogy versus geomechanical moduli for samples of well 13-28-064-05W6.163 3.3.4 Comparing Shale Core Chips, Drill Cuttings and Core Plug Data In addition to shale core chips, drill cuttings samples from the Montney Formation are tested by instrumented indentation and XRD. Indentation and XRD analyses of drill cuttings samples allows for the characterization of mechanical and mineralogical variability within a wellbore from samples that are byproducts of the drilling process. Drill cuttings are subsampled from BCOGC drill cuttings collections, which were sampled at 5 m depth intervals during drilling. Drill cuttings samples are not taken from the exact depth as shale core chip samples or core plug data, because drill cuttings are only available at specific 5 m depth intervals; in contrast, core chips and core plugs can be sampled at any depth where recovered core is available. Due to these differences in sampling, indentation results from drill cuttings are restricted to provide estimates of geomechanical and mineralogical properties at regular depth intervals (i.e. every 5 m depth). Sampling of drill cuttings at closely spaced depth intervals would allow for drill cuttings to be sampled at the same depths as core chips or core plug data; unfortunately, sampling of this scale was not possible for this study. In total, 8 drill cuttings and 15 core chips are sampled from well A01-32, and 13 drill cuttings and 9 core chips are sampled from well C-004. Mean indentation results from testing on shale core chips and drill cuttings are organized by well and separated by sample type (Figure 3.27; Figure 3.28). Indentation results, mineralogy, and core plug mechanical data are further explored for each well, in the following sections. 164 Figure 3.27: Standard indentation results from shale core chips and drill cuttings of well A01-32-083-25W6. Figure 3.28: Standard indentation results from shale core chips and drill cuttings of well C-004-F/094-G-08. 165 3.3.4.1 Petronas et al., HZ Altares A01-32-083-25W6 (27400) Twenty-three samples from well A01-32-083-25W6 are analyzed by instrumented indentation and XRD. Fifteen of these 23 samples are core chips, sampled adjacent to previously tested core plugs. The remaining 8 samples are drill cuttings samples, chosen from the 5 m depth interval that best aligned to core chip and core plug sample depths. Indentation results and mineralogy from testing of core chips and drill cuttings samples are compared with static and dynamic Young’s modulus core data (Table 3.6; Figure 3.29). Geomechanical moduli are variable between samples, with mean EIT ranging 37.6 – 63.7 GPa, Es ranging 15.0 – 50.5 GPa, and Ed ranging 25.5 – 56.4 GPa (Figure 3.29). Moderate to weak correlations are observed for mean EIT with Es (R2 = 0.32) and Ed (R2 = 0.14), whereas Es and Ed core plug data have a strong relationship (R2 = 0.78) (Figure 3.14). Mineralogy also displays significant variability, and moderate to weak relationships, amongst geomechanical moduli (Figure 3.30): negative linear correlations are observed between quartz and mean EIT (R2 = 0.51), mean EIT (R2 = 0.20), and Es (R2 = 0.26); carbonates show a moderate positive relationship with mean EIT (R2 = 0.41); feldspars have a weak negative correlation with mean EIT (R2 = 0.15) and decrease moderately with sample depth (R2 = 0.60); and clays show a weak trend with depth (R2 = 0.11), across all core chips and drill cuttings samples. To examine whether these geomechanical and mineralogical relationships hold for shale core chips and drill cuttings individually, mean indentation results, core plug mechanical data, and mineralogy are separated by sample type, for further analysis in the following section. 166 Core Plug Data Indentation Data X-Ray Diffraction Mineralogy Well Sample Depth (m) Es (GPa) Ed (GPa) EIT – Standard (GPa) N Quartz (wt. %) Carbonates (wt. %) Feldspars (wt. %) Clays (wt. %) Others (wt. %) A01-32-083-25W6 RMA-01-HZ 2314.12 23.1 – 40.1 ± 17.3 51 33.6 14.9 29.2 20.9 1.5 RMA-02-VT 2314.16 17.6 – 46.1 ± 12.4 135 34.6 10.9 26.8 26.1 1.6 DC-2315m 2315 – – 45.7 ± 12.6 90 20.6 13.2 14.6 50.5 1.1 RMA-10-VT 2322.89 29.8 – 46.5 ± 11.2 168 34.9 9.4 26.8 27.3 1.7 DC-2325m 2325 – – 40.5 ± 13.4 80 30.9 19.5 22.9 24.9 1.7 RMA-12-VT 2325.39 16.3 25.5 53.3 ± 13.2 171 28.2 15.3 24.3 30.1 2.2 DC-2330m 2330 – – 41.8 ± 12.1 84 30.9 25.6 23.4 18.1 2.1 RMA-19-HZ 2333.21 50.5 55.8 56.7 ± 10.8 139 25.2 16.7 21.2 35.2 1.7 RMA-21-HZ 2334.72 40.1 56.4 51.6 ± 11.5 115 30.3 11.9 26.1 29.2 2.6 DC-2335m 2335 – – 42.9 ± 11.5 85 31.8 22.0 24.9 18.7 2.7 RMA-45-HZ 2456.23 41.9 48.9 62.9 ± 13.4 188 18.8 42.4 11.3 26.2 1.2 RMA-46-VT 2456.26 34.0 – 63.7 ± 12.0 128 18.1 49.9 9.6 21.3 1.1 DC-2460m 2460 – – 43.6 ± 10.7 83 38.1 16.2 20.1 24.0 1.7 RMA-52-VT 2460.97 29.9 49.9 48.7 ± 12.9 179 34.3 11.6 19.8 33.0 1.4 DC-2465m 2465 – – 47.3 ± 14.4 70 38.2 16.0 21.1 22.9 1.8 RMA-61-VT 2526.5 41.0 45.0 49.7 ± 12.5 164 32.0 13.9 14.3 37.3 2.6 RMA-62-VT 2526.62 15.0 30.6 42.3 ± 12.3 72 35.4 13.0 15.4 34.1 2.1 DC-2530m 2530 – – 37.6 ± 11.2 63 36.2 12.2 16.5 32.4 2.7 RMA-66-VT 2530.51 25.6 – 46.5 ± 14.0 62 31.0 13.1 13.8 39.3 2.8 RMA-65-HZ 2530.63 27.7 42.2 53.0 ± 12.9 123 30.9 20.4 13.5 32.7 2.6 RMA-69-HZ 2532.54 41.7 47.3 50.4 ± 13.8 76 27.5 20.5 13.5 35.7 2.8 RMA-70-VT 2532.58 27.6 – 47.6 ± 10.8 116 25.9 19.7 12.7 39.1 2.6 DC-2535m 2535 – – 37.7 ± 11.7 65 34.9 13.6 16.3 32.2 3.0 Table 3.6: Indentation results, core plug data, and XRD mineralogy for core chips and drill cuttings samples. 167 Figure 3.29: Geomechanical depth profile of all samples of well A01-32-083-25W6. Geomechanical depth profiles are separated by sampling depth intervals in Appendix C. 168 Figure 3.30: XRD mineralogy versus geomechanical moduli for all samples of well A01-32-083-25W6. R2 is displayed in the bottom-left corner for each plot.169 3.3.4.1.1 Comparison by Sample Type: Core Chips versus Drill Cuttings Indentation and XRD results from A01-32 are separated by sample type to see how geomechanical and mineralogical results and relationships compare to a combined dataset. Where core chips and drill cuttings have similar mean indentation results, mineralogy and relationships, it is assumed that both sample types are representative of the same depths and lithologies. Core chips samples have mean EIT results between 40.1 – 63.7 GPa, mean HIT ranging 2216 – 3737 MPa, and a compositional range of 18 – 35% quartz, 9 – 50 % carbonates, 10 – 29% feldspars, 21 – 39% clays, and 1 – 3 % pyrite (Table 3.6; Table 3.7; Figure 3.31). Strong negative linear correlations are observed between quartz and mean EIT (R2 = 0.77) and feldspar with depth (R2 = 0.77); moderate positive correlations are observed between carbonates and mean EIT (R2 = 0.65), and clays with depth (R2 = 0.38); and weak negative correlation is observed between feldspar and mean EIT (R2 = 0.23) (Figure 3.33; Table 3.12). Core chips samples RMA-45-HZ and RMA-46-VT display relatively high indentation moduli (62.9 GPa and 63.7 GPa) and have distinct, carbonate-rich mineralogy compared to other samples. Static Young’s modulus data for these two samples are relatively moderate (42 and 34 GPa), suggesting the core plug sampling location is possibly inconsistent with the original core plug location; static core plug data is inaccurate; or that there is a difference between microscale indentation results and macroscale core plug geomechanical properties. Excluding RMA-45-HZ and RMA-46-VT, indentation results and mineralogy of core chips samples of well A01-32 are relatively consistent: mean EIT ranges 40.1 – 56.7 GPa and mineralogy ranges 25 – 35 % quartz, 9 – 21 % carbonates, 13 – 29 % feldspar, 21 – 39 % clays, and 1 – 3 % pyrite. 170 Drill cuttings samples have mean EIT results between 37.6 – 47.3 GPa, mean HIT between 2434 – 4771 MPa, and a compositional range of 21 – 38 % quartz, 12 – 26 % carbonates, 15 – 25 % feldspars, 18 – 50 % clays, and 2 – 3 % pyrite (Figure 3.32; Table 3.6; Table 3.7Figure 3.7). Drill cuttings show weak to negligible correlations between mean EIT and mineralogy; moderate to weak, negative correlations are observed for mean HIT with quartz (R2 = 0.67) and clay (R2 = 0.27); and quartz increases (R2 = 0.53), whereas carbonates (R2 = 0.41) and feldspars (R2 = 0.22) decrease, moderately with depth (Figure 3.34; Table 3.12). DC-2315m has relatively high clay composition (50%) and hardness (4771 MPa), compared to other samples; with DC-2315m excluded from the dataset, mineralogy reduces from 31 – 38% quartz, 12 – 26% carbonates, 16 – 25% feldspar, 18 – 32 % clays, and 2 – 3% pyrite; additionally, the range of hardness reduces to 2434 – 3515 MPa. 171 Core Chips Drill Cuttings # of Samples 15 8 Geomechanical Moduli Mean EIT (GPa) 40.1 – 63.7 37.6 – 47.3 Es (GPa) 15.0 – 50.5 n/a Ed (GPa) 25.5 – 56.4 [9] n/a Mineralogy Quartz (wt. %) 18 – 35 21 – 38 Carbonates (wt. %) 9 – 50 12 – 26 Feldspar (wt. %) 10 – 29 15 – 25 Clays (wt. %) 21 – 39 18 – 51 Others (wt. %) 1 – 3 1 – 3 Table 3.7: Range of indentation results, core plug data, and XRD mineralogy for core chips and drill cuttings sample types of A01-32-083-25W6. Square brackets indicate # of core plug data points172 Figure 3.31: Indentation results for all shale core chips samples of well A01-32-083-25W6. 173 Figure 3.32: Indentation results for all shale drill cuttings samples of well A01-32-083-25W6. 174 Figure 3.33: XRD mineralogy versus geomechanical moduli for core chips samples of well A01-32-083-25W6. 175 Figure 3.34: XRD mineralogy versus indentation results for drill cuttings samples of well A01-32-083-25W6. With the exceptions of outlier samples RMA-45-HZ, RMA-46-VT, and DC-2315m, core chips and drill cuttings samples show good overlap in geomechanical and mineralogical variability (Table 3.7). Core chips mean EIT ranges 40.1 – 56.7 GPa, versus 37.6 – 47.3 GPa for drill cuttings; mean HIT ranges 2216 – 3737 MPa versus 2434 – 3515 MPa; and mineralogy 176 ranges 25 – 35 % quartz, 9 – 21 % carbonates, 13 – 29 % feldspar, 21 – 39 % clays, and 1 – 3 % pyrite compared to 31 – 38% quartz, 12 – 26% carbonates, 16 – 25% feldspar, 18 – 32 % clays, and 2 – 3% pyrite (Table 3.7). Core chips samples have strong to weak relationships between indentation modulus and mineralogy, compared to weak to negligible relationships from drill cuttings. In addition, no common trend is observed between mineralogy and depth between sample types. Perhaps drill cuttings samples are representative of different lithology than core chips due to differences in sampling depth or mixing of drill cuttings from multiple sampling depths; this would explain differences in mineralogy with depth and possibly different relationships between mineralogy and mean EIT. Overall, indentation results from drill cuttings of A01-32 are not representative of the core chip samples tested in this study; however, indentation results from drill cuttings can still be used to differentiate between other drill cuttings samples. 3.3.4.2 Progress Jedney C-004-F/094-G-08 (29010) Twenty-two samples from well C-004-F/094-G-08 are tested by instrumented indentation and XRD. Nine of these samples are core chips, sampled at depths adjacent to previously tested core plugs. The remaining thirteen samples are drill cuttings sampled at 5 m or 10 m depth intervals that align with core chip sample depths. Indentation results and mineralogy are compared with static and dynamic Young’s modulus core data to assess overall relationships within the dataset (Figure 3.35). Mean EIT ranges from 21.5 – 48.5 GPa, compared to core plug static (16.5 – 30.2 GPa) and dynamic (40.6 – 54.4 GPa) Young’s moduli data (Table 3.8; Figure 3.35). No correlation is observed between mean EIT and either Es or Ed; however, indentation modulus does show similar geomechanical depth patterns as core plug data (Figure 3.14). Core chips mean EIT 177 results are relatively similar to Ed values, whereas Es values are lower than Ed in all samples. Drill cuttings mean EIT results are generally intermediate in value between Ed and Es. There is significant mineralogical variability, with compositions ranging 24 – 47 % quartz, 6 – 25 % carbonates, 11 – 38 % feldspar, 10 – 49 % clays, and 1 – 7 % other minerals (Table 3.8; Table 3.11). Moderate to weak correlations are observed between geomechanical moduli and mineralogy, including weak to moderate positive correlations for mean EIT with quartz (R2 = 0.12) and feldspar (R2 = 0.46), and a negative with clays (R2 = 0.23); mean HIT shows similar relationships with quartz (R2 = 0.10), feldspar (R2 = 0.36) and clays (R2 = 0.23); static Young’s modulus has weak to moderate positive correlation with quartz (R2 = 0.12), carbonates (R2 = 0.12) and feldspar (R2 = 0.52), and strong negative correlation with clays (R2 = 0.83); and dynamic Young’s modulus has weak correlation with quartz (R2 = 0.31), carbonates (R2 = 0.05), feldspar (R2 = 0.33), and moderate with clays (R2 = 0.63) (Figure 3.36). With depth, quartz (R2 = 0.31), carbonates (R2 = 0.58), and feldspar (R2 = 0.47) generally decrease, and clays increase (R2 = 0.74) (Figure 3.36). To examine whether geomechanical and mineralogical relationships in all samples of C-004 hold for shale core chips and drill cuttings individually, the dataset is separated by sample type for further analysis in the following section. 178 Core Plug Data Indentation Data X-Ray Diffraction Mineralogy Well Sample Depth (m) Es (GPa) Ed (GPa) Mean EIT (GPa) N Quartz (wt. %) Carbonates (wt. %) Feldspars (wt. %) Clays (wt. %) Others (wt. %) C-004-F/094-G-08 DC-1780m 1780 – – 41.6 ± 12.7 60 37.5 17.7 26.2 16.5 2.2 RM1-A 1783.15 30.2 54.4 36.2 ± 12.6 177 39.4 19.6 25.0 13.9 2.1 DC-1785m 1785 – – 25.4 ± 7.1 48 47.4 17.7 26.9 5.9 2.1 RM2-C 1789.77 27.9 48.3 39.6 ± 15.1 139 38.8 20.4 29.8 10.1 0.9 DC-1790m 1790 – – 25.5 ± 7.5 46 47.0 17.9 27.4 5.7 2.1 RM3-A 1797.67 25.2 44.4 45.3 ± 12.0 88 32.9 19.1 33.8 12.9 1.4 DC-1800m 1800 – – 41.8 ± 13.7 54 38.3 24.9 25.9 7.1 3.8 RM4-A 1866.64 21.0 42.9 41.1 ± 16.3 261 34.6 18.8 22.7 22.5 1.5 DC-1870m 1870 – – 31.9 ± 10.6 22 35.9 15.7 18.6 26.6 3.3 RM5-A 1879.65 26.8 48.8 47.7 ± 11.0 296 40.7 9.8 34.6 13.3 1.7 DC-1880m 1880 – – 36.9 ± 12.3 37 40.3 13.5 20.3 23.3 2.7 RM6-C 1886.91 27.5 50.0 48.5 ± 14.0 314 41.0 6.2 37.7 14.7 0.5 DC-1890m 1890 – – 38.3 ± 10.6 30 42.1 14.2 19.4 23.3 1.0 DC-1965m 1965 – – 21.5 ± 9.9 21 24.2 13.4 10.5 48.8 3.1 RM7-A 1965.99 17.9 42.3 46.4 ± 16.3 171 38.4 12.2 21.9 25.1 2.4 DC-1970m 1970 – – 25.2 ± 6.7 26 29.2 5.9 11.9 45.8 7.3 DC-1975m 1975 – – 31.4 ± 12.0 36 35.9 9.9 16.6 34.7 2.9 RM8-C 1975.22 16.5 41.0 39.7 ± 12.0 241 38.1 10.3 19.9 29.1 2.6 DC-1980m 1980 – – 24.4 ± 5.7 23 24.4 12.1 11.9 49.4 2.2 DC-1985m 1985 – – 33.8 ± 10.6 37 32.3 12.5 14.8 37.2 3.2 RM9-A 1985.96 19.0 40.6 41.3 ± 14.6 152 36.6 9.1 20.4 31.6 2.3 DC-1990m 1990 – – 32.3 ± 9.8 40 35.0 12.6 15.4 33.9 3.1 Table 3.8: Es, Ed, and EIT for samples of well C-004-F/094-G-08, organized by sample depth. 179 Figure 3.35: Geomechanical depth profile for all samples of well C-004-F/094-G-08. 180 Figure 3.36: Geomechanical moduli (columns) versus XRD mineralogy (weight %, rows), for all core chips and drill cuttings samples of well C-004-F/094-G-08.181 3.3.4.2.1 Comparison by Sample Type: Core Chips versus Drill Cuttings Indentation and XRD results from core chips and drill cuttings samples of well C-004 are separated based on sample type, to evaluate how results and relationships compare to the combined dataset. The 9 core chip samples have a mean EIT ranging 36.2 – 48.5 GPa and a compositional range varying 33 – 41 % quartz, 6 – 20 % carbonates, 20 – 38 % feldspars, 10 – 32 % clays, and 1 – 3 % pyrite (Table 3.8; Table 3.9). Moderate to weak relationships are observed between mean EIT and mineralogy, including positive correlations with quartz (R2 = 0.14) and feldspar (R2 = 0.36), and negative correlation with carbonates (R2 = 0.37) and clays (R2 = 0.04) (Figure 3.37; Table 3.13). Mean HIT has weak to moderate relationships, in the same direction as mean EIT, with quartz (R2 = 0.43), feldspar (R2 = 0.62), carbonates (R2 = 0.38), and clays (R2 = 0.18).With depth, core plug sample compositions decrease in carbonates (R2 = 0.57) and feldspar (R2 = 0.28) and increase in clay (R2 = 0.79). The 13 drill cuttings samples have mean EIT between 21.5 – 41.8 GPa, and a compositional range of 24 – 47 % quartz, 6 – 25 % carbonates, 11 – 27 % feldspars, 6 – 49 % clays, 1 – 4 % pyrite, and 1 – 5 % other minerals (Table 3.8; Table 3.9). Mean EIT has a weak positive correlation with quartz (R2 = 0.11), carbonates (R2 = 0.21), and feldspar (R2 = 0.20), and negative correlation with clays (R2 = 0.20) (Figure 3.38; Table 3.13). Similar weak relationships are observed for mean HIT with quartz (R2 = 0.05), carbonates (R2 = 0.31), feldspar (R2 = 0.15), and clays (R2 = 0.15). Moderate to strong correlations are observed with depth, as quartz (R2 = 0.56), carbonates (R2 = 0.63), and feldspar (R2 = 0.89) decrease, while clays increase (R2 = 0.84). 182 Core Chips Drill Cuttings # of Samples 9 13 Geomechanical Moduli Mean EIT (GPa) 36.2 – 48.5 21.5 – 41.8 Es (GPa) 16.5 – 30.2 n/a Ed (GPa) 40.6 – 54.4 n/a Mineralogy Quartz (wt. %) 33 – 41 24 – 47 Carbonates (wt. %) 6 – 20 6 – 25 Feldspar (wt. %) 20 – 38 11 – 27 Clays (wt. %) 10 – 32 6 – 49 Others (wt. %) 1 – 3 1 – 7 Table 3.9: Range of indentation results, core plug data, and XRD mineralogy for core chips and drill cuttings sample types of C-004-F/094-G-08. Square brackets indicate # of core plug data points. 183 Figure 3.37: Geomechanical moduli (columns) versus XRD mineralogy (weight %, rows), for core chips samples of well C-004-F/094-G-08. 184 Figure 3.38: Mean EIT (left column), mean HIT (middle column), and depth (right column) relationships with weight % XRD mineralogy (rows, top to bottom: Quartz; Carbonates; Feldspar; and Clays), for drill cuttings samples of well C-004-F/094-G-08. Overall, core chips and drill cuttings samples of C-004 show good overlap in indentation results and mineralogy (Table 3.8; Table 3.9); however, drill cuttings have a larger range of indentation results and mineralogy than core chips samples. Core chips mean EIT ranges 36.2 – 185 48.5 GPa versus 21.5 – 41.8 GPa for drill cuttings. Mineralogy ranges 33 – 41 % quartz, 6 – 20 % carbonates, 20 – 38 % feldspar, 10 – 32 % clays, and 1 – 3 % pyrite for core chips compared to 24 – 47 % quartz, 6 – 25 % carbonates, 11 – 27 % feldspar, 6 – 49 % clays, and 1 – 7 % pyrite for drill cuttings. Both core chips and drill cuttings show strong to moderate correlation between depth and increasing clay or decreasing carbonates and feldspar. Similar changes to mineralogy with depth suggests that each sample type is testing samples representative of similar sampling depths across the well. Each sample type shows moderate to weak relationships between indentation results and mineralogy, though not always in the same direction. Core chips mean EIT and HIT correlate positively with quartz and feldspar and negatively with carbonates and clays. In contrast, drill cuttings mean EIT and HIT correlate positively with quartz, carbonates, and feldspar, but negatively with clays. The difference in these correlations may be the result of scale: core chips are millimeter to centimeter scale, whereas drill cuttings can be millimeter to sub-millimeter scale. Only 1 or 2 subsamples make up a core chip sample, therefore each core chip sample is composed of a mix of shale components that are indented as a composite material. Many cuttings compose a drill cuttings sample, with each cutting potentially composed of only a few components, and multiple cuttings potentially representing a range in depth. Indentation testing of core chips would measure a composite material response of a whole core chip, whereas testing of drill cuttings may only access the portion of mineralogy present in each drill cutting. Also, mechanical anisotropic effects, due to bedding orientation and cementation, may not contribute to indentation results in shale drill cuttings as significantly as they might influence results in core chips samples. As a result, a higher mean EIT would be expected to be measured from drill cuttings consisting of harder and stiffer components (i.e. quartz, carbonate, and feldspar) than 186 cuttings consisting of softer and more flexible components (i.e. clays). This expected trend is not observed in all samples. In many cases, the relative abundance of stiffer components also affects correlation between mineralogy and geomechanical moduli: carbonates have a higher mean EIT, which increases sample mean EIT when carbonates are relatively abundant compared to quartz of feldspars. Relative abundance and interaction of mineralogy should be examined in future testing for additional context of indentation results. Drill cuttings samples with individual cuttings of fewer components would also explain the larger range of compositions for drill cuttings samples. In summary, indentation results from drill cuttings are less likely to represent a composite material response than relatively larger core chips. Alternatively, drill cuttings may just be representative of different sampling depths than core chips, due to sampling limitations of drill cutting recovery versus depth-specific core chip sampling. 3.4 Chapter Conclusions The ability to use instrumented indentation to measure indentation mechanical properties of shale drill cuttings enables the characterization of geomechanical variability along a horizontal wellbore. In this study, mean indentation results from core chips and drill cuttings samples of shale are successfully measured with instrumented indentation and compared between samples; however, across all samples tested in this study, indentation results show weak relationships with core plug geomechanical data (Figure 3.12) and mineralogy (Figure 3.16). Analysis of indentation results by well improved results, leading to mixed correlations between mean indentation results and core plug mechanical data (Table 3.10), and stronger relationships between geomechanical moduli and mineralogy (Table 3.11; Table 3.12; Table 3.13). 187 Core chips indentation results for individual wells show mixed correlations with core plug mechanical data (Table 3.10) and mineralogy (Table 3.11; Table 3.12; Table 3.13). For example, Mean EIT has a strong correlation with Es and Ed for the 4 samples of 09-23, but the limited number of samples in this well reduces the reliability of these relationships. Mean EIT also shows moderate to weak correlations with Es for samples of 01-20, 12-12, 13-28, and A01-32, and with Ed for samples of 01-20 and A01-32. Overall, mean EIT has a worse correlation with Es or Ed than the core plug data show between each other. Relatively weak correlations may be due to differences in scale or sampling depth of core chips, compared to original core plugs. Core chip samples, on the millimeter scale, are much smaller than core plug samples and may not be fully representative of core plug lithology or heterogeneity; or, perhaps core chips provide indentation results that are representative of the slabs from which they were sampled, but were cut adjacent to original core plug locations; or, simply, mean indentation modulus may just not correlate well with static or dynamic core plug data on an individual sample or well basis. In addition to different sampling depths, core chips and drill cuttings will have undergone different levels of degradation prior to being tested with indentation. Drill cuttings will have been affected both chemically and mechanically by the drill bit, drilling fluids, and recovery of the cuttings; whereas core plugs may be affected during the coring process, testing of core plugs, and further crushing into core chip samples. Differences in sampling methods and sample types are the likely cause of difference in mechanical results between core chips, drill cuttings, and core plug data. After additional analysis of core chip and core plug data from 12-12, Es and Ed core plug data was found to be unreliable; therefore, correlations between mean EIT and core plug mechanical data are excluded from overall geomechanical correlations. Mean EIT correlations 188 with Es data from 13-28 are also disregarded due to potential sampling error from disaggregated core of inaccurate depth, and because samples are from the Belloy Formation. Following the filtration of 12-12 and 13-28 data, new overall geomechanical correlations are provided for the Montney Formation samples in this study: mean EIT has a moderate linear correlation of R2 = 0.53 with Es, and R2 = 0.45 with Ed (Figure 3.39). Similar to previous indentation studies (e.g. Glover et al., 2016; Shukla et al., 2013), indentation modulus is better predicted within a formation than across all samples of various formations. This correlation is still weaker than the correlation between core plug static and dynamic moduli (R2 = 0.79), but it demonstrates that instrumented indentation results are able to estimate core plug mechanical properties with moderate confidence. 189 Figure 3.39: Geomechanical correlations for Montney Formation samples. Plots show mean EIT versus Es (top) and Ed (bottom) core plug data. Geomechanical data for 12-12 and 13-28 are excluded to poor sampling reliability and samples from disaggregated core of the Belloy Formation. 190 In addition to moderate geomechanical correlations across a filtered dataset, geomechanical depth profiles for each well of show similar patterns for mean indentation results and core plug mechanical data (Figure 3.17; Figure 3.18; Figure 3.21; Figure 3.23; Figure 3.25; Figure 3.29; Figure 3.35). Geomechanical depth profiles demonstrate how mean EIT could be used as an analogue for static and dynamic Young’s moduli, when characterizing geomechanical variation with depth. Mean EIT may not provide an exact match to Es or Ed, but relative differences in mean EIT between close samples can be used to characterize indentation mechanical variation along a wellbore. Relative differences in mechanical properties could be targeted and exploited with planned hydraulic fracture completions at geomechanically favourable depths. A wide range of mineralogical variability is observed between shale samples (Figure 3.15), and mixed relationships are observed between geomechanical moduli and mineralogy for each well (Table 3.11; Table 3.12; Table 3.13). In general, both core chips indentation results and core plug mechanical data have similar correlations with mineralogy and trend in the same direction. For example, mean EIT from core chips samples show moderate to strong positive correlations with carbonates in wells 09-23, 12-12 and A01-32; negative correlation with quartz in 01-20, 09-23, and A01-32; and negative correlation with feldspar in 09-23 and 13-28; and moderate negative correlation with clay in 09-23 (Table 3.11; Table 3.12; Table 3.13). Similarly, either Es or Ed have moderate to strong positive correlations with carbonates in wells 09-23, 12-12; negative correlation with quartz in 09-23, 12-12, and 13-28; negative correlation with feldspar in 09-23, 12-12, and 13-28; and negative correlation with clay in 09-23, 12-12, and C-004. For core chip samples and core plug data, geomechanical correlations with mineralogy only vary in well C-004 (Table 3.13). Mean EIT from C-004 samples show moderate positive 191 correlation with feldspar and negative correlation with carbonates. Es and Ed core plug mechanical results show moderate positive correlation with feldspar and quartz, and negative correlation with clay. The different relationships observed for C-004 can be attributed to the smaller range in carbonates and relatively high quartz and feldspar content of C-004 core chip samples. Observed relationships between mean EIT and mineralogy indicate that mean EIT is related to the dominant stiff components of a sample. Compared to core plug data, core chips show no moderate to strong relationships with clay composition suggesting clay composition doesn’t significantly influence mean EIT results. Clay composition may have a larger influence on core plug mechanical results, or other clay-rich shales, but this is not the case for the Montney Formation, which may be considered a dolomitic siltstone. Whether or not other factors (such as fabric, microstructures, particle size, or facies) affect indentation results is out of the scope of this investigation. Overall, mineralogy shows strong relationships with geomechanical moduli; however, these relationships may differ well to well depending on the dominant mineralogy of samples. Core chip samples and core plug data demonstrate similar mechanical-mineralogical relationships for stiffer mineralogical components of shale. Drill cuttings samples from A01-32 and C-004 present different relationships between mean EIT and mineralogy. Overall, mineralogy of drill cuttings from both wells show overlap with mineralogy of core chip samples; however, indentation results and relationships differ significantly. Drill cuttings of A01-32 show a different trend in mineralogy with depth than core chips, as well as negligible correlation between mean EIT and mineralogy. Therefore, drill cuttings from A01-32 are not representative of core chips samples, possibly due to differences in sample depths between sample types. Drill cuttings are sampled at 5 m intervals during the drill process, compared to core chips that are sampled directly from core at distinct depths. 192 Drill cuttings and core chips of C-004 both show similar trends in mineralogy with depth of increasing clay and decreasing in carbonates and feldspar; however, different moderate correlations are seen between geomechanical moduli and mineralogy (Table 3.13). In both sample types, weak correlations trend in the same direction: positive for mean EIT with quartz and feldspar, and negative with clay (Figure 3.37; Figure 3.38); however, due to the low correlation coefficients, these trends are unreliable. Differences in relationships between sample types is likely due to differences in sample scale and sampling methods. For example, drill cuttings are representative of a range in depths, compared to specific sample depths of core chips and original core plugs. Drill cuttings will degrade differently than core plugs due to destruction during the drilling process and exposure to drilling fluids; drilling fluids may also influence clay composition, either through weathering or insufficient cleaning prior to XRD analysis. Overall, drill cuttings do not show similar relationships between geomechanical moduli and mineralogy, and indentation results from drill cuttings may not be representative of nearby core chip sample depths. This is likely due to differences in sample depth and lithology rather than the indentation technique. The size and recovery of drill cuttings may affect composition with preferential preservation of certain minerals; however, the influence of underlying epoxy on smaller drill cutting samples is unlikely as repeatable indentation results were obtained on samples of drill cutting size (< 841 µm). Based on mineralogical trends with depth, indentation results are more representative of core chip samples in C-004 than in A01-32. Geomechanical depth profiles show that indentation results from drill cuttings provide a good analogue for core chip results and core plug data in C-004, but relatively poor in A01-32. Instrumented indentation can be applied to drill cuttings samples to characterize variability in indentation results between other drill cuttings samples; however, these results should be considered representative only of 193 the depth interval from which they are sampled. For example, the indentation results from drill cuttings in this sample could be considered an estimate of the mechanical of the 5 m depth intervals they are sampled from. Horizontal wellbores tend to land within a single target formation of interest. Instrumented indentation can be applied to drill cuttings samples collected at regular depth intervals to characterize the geomechanical variation of a target formation along the lateral of the wellbore. If collected at regular intervals, mean indentation results from drill cuttings could be used as a relative index of indentation mechanical properties along a wellbore. Further testing and correlation of drill cuttings with core chip and core plug mechanical properties is required before drill cuttings indentation results can be used to estimate core scale mechanical properties. Indentation results from core chips show moderate correlations with static and dynamic Young’s moduli for Montney Formation shales, presented in this study. Alternatively, core plugs could be sampled at regular intervals along the horizontal wellbore, that better align with drill cutting depth intervals, to create correlations between drill cuttings and core plug data for individual wells or well pads.194 Linear Geomechanical Relationships Well # of Core Chips Samples Mean EIT-Es (R2) Mean EIT-Ed (R2) Es-Ed (R2) 06-28-078-19W6 29 0.01 n/a n/a 01-20-063-08W6 6 0.62 0.44 0.75 09-23-064-04W6 4 0.94 0.96 0.82 12-12-064-04W6 6 0.24 0.00 0.01 13-28-064-05W6 (Belloy Fm) 8 0.31 n/a n/a A01-32-083-25W6 15 0.32 0.14 [9] 0.78 [9] C-004-F/094-G-08 9 0.00 0.00 0.87 All Samples 77 0.30 0.19 0.73 Samples, excluding 12-12 and 13-28 63 0.53 0.45 0.79 [57] Table 3.10: Linear relationships between geomechanical moduli, separated by well and presented for all data and all data (excluding 12-12 and 13-28 samples). 195 Table 3.11: Positive and negative correlations between indentation results, XRD mineralogy, and core plug mechanical data of wells 06-28, 01-20, 09-23, 12-12, and 13-28. Well # of Samples Positive Correlations R2 Negative Correlations R2 EIT-Es EIT-Ed Es-Ed 06-28-078-19W6 29 N/A – N/A – 0.01 – – 01-20-063-08W6 6 Depth-Clays Es-Clays 0.31 0.32 EIT-Quartz 0.47 0.62 0.44 0.75 09-23-064-04W6 4 EIT-Carbonates Depth-Feldspar Depth-Clay Es-Carbonates Ed-Carbonates 0.97 0.73 0.99 0.99 0.88 EIT-Quartz EIT-Feldspar EIT-Clay HIT-Clays Depth-Carbonates Es-Quartz Es-Feldspar Es-Clay Ed-Quartz Ed-Feldspar Ed-Clay 0.90 0.87 0.45 0.37 0.45 0.83 0.96 0.62 0.88 0.73 0.36 0.94 0.96 0.82 12-12-064-04W6 6 EIT-Carbonates Depth-Clays Es-Carbonates 0.43 0.95 0.51 HIT-Clays Depth-Quartz Es-Clays Ed-Quartz Ed-Feldspar 0.46 0.45 0.82 0.87 0.78 0.24 0.00 0.01 13-28-064-05W6 (Belloy Fm) 8 Depth-Carbonates 0.43 EIT-Feldspar Depth-Clay Es-Quartz Es-Feldspar 0.51 0.74 0.49 0.67 0.31 – – 196 Table 3.12: Relationships between indentation results, mineralogy, and core plug mechanical data for samples of well A01-32-083-25W6. Data is presented for all samples and separated by sample type. Only linear correlations with R2 ≥ 0.3 are displayed; strong correlations (R2 ≥ 0.70) are bolded. CC = core chips; DC = drill cuttings. Well Data Organization # of Samples Positive Correlations R2 Negative Correlations R2 EIT-Es EIT-Ed Es-Ed A01-32-083-25W6 All Samples 23 EIT-Carbonates 0.41 EIT-Quartz Depth-Feldspar 0.51 0.60 0.32 0.14 0.78 Sample Type Core Chips 15 EIT-Carbonates Depth-Clays 0.65 0.38 EIT-Quartz Depth-Feldspar 0.77 0.77 0.32 0.14 0.78 Drill Cuttings 8 HIT-Quartz Depth-Quartz 0.67 0.53 Depth-Carbonates 0.41 – – – 197 Table 3.13: Relationships between indentation results, mineralogy, and core plug mechanical data for samples of well C-004-F/094-G-08. Data is presented for all samples and separated by sample type. Only linear correlations with R2 ≥ 0.3 are displayed; strong correlations (R2 ≥ 0.70) are bolded. CC = core chips; DC = drill cuttings.Well Data Organization # of Samples Positive Correlations R2 Negative Correlations R2 EIT-Es EIT-Ed Es-Ed C-004-F/094-G-08 All Samples 22 EIT-Feldspar HIT-Feldspar Depth-Clays Es-Feldspar Ed-Quartz Ed-Feldspar 0.46 0.46 0.74 0.52 0.31 0.33 Depth-Quartz Depth-Carbonates Depth-Feldspar Es-Clays Ed-Clays 0.31 0.58 0.47 0.83 0.63 0.01 0.00 0.87 Sample Type Core Chips 9 EIT-Feldspar HIT-Carbonates Depth-Clays Es-Feldspar Ed-Quartz Ed-Feldspar 0.36 0.38 0.79 0.52 0.31 0.33 EIT-Carbonates HIT-Quartz HIT-Feldspar Depth-Carbonates Es-Clays Ed-Clays 0.37 0.43 0.62 0.57 0.52 0.63 0.01 0.00 0.87 Drill Cuttings 13 HIT-Carbonates Depth-Clays 0.31 0.84 Depth-Quartz Depth-Carbonates Depth-Feldspar 0.56 0.63 0.89 – – – 198 Chapter 4: Conclusions 4.1 Conclusions Instrumented indentation is a technique originally used to test hardness and indentation modulus of homogeneous materials, such as thin films, metals, and polymers. The technique has since been applied to heterogeneous materials, including shale. Furthermore, indentation testing of shale has investigated indentation mechanical properties of artificial and actual drill cuttings of shale. This thesis extends previous research on artificial and actual drill cuttings of shale, with a focus on the Montney Formation of Northeast BC and Alberta. Within this research, the utility of instrumented indentation for characterizing geomechanical variation in shale drill cuttings is assessed. Initial testing in the study was directed at evaluating the effects of sample size, maximum indentation load, number of indentation measurements, and measurement type on indentation results. To ensure indentation techniques are applicable to small sample sizes, such as drill cuttings, sub-millimeter samples of dolomite and shale are tested. Repeatable indentation results are measured on dolomite samples of 100 mesh size (177 µm) and larger, and Montney Formation shales of sample size 20 mesh (841 µm) and larger, suggesting millimeter-sized drill cuttings can be tested reliably. Maximum indentation loads between 50 mN and 200 mN do not significantly affect mean indentation results. A maximum indentation load of 200 mN is selected for testing in this study, in order to test the largest area of sample per indent and receive composite material responses. To estimate the minimum number of measurements required for representative indentation results, a running mean is applied to indentation results of mineral samples and shale. A cutoff of two times the standard error of mean EIT is used to calculate a 199 minimum suggested number of indentation measurements to receive stable indentation results. A suggested minimum number of measurements of 83 is given for shale samples from the Montney Formation; however, additional measurements are recommended for highly heterogeneous samples to ensure a representative mean indentation result. No significant difference in indentation results is observed between standard and constant strain sinus indentation types. Standard indentations are applied to indentation testing in all samples of this study and are recommended because they are faster and measure higher loads than sinus measurements. Higher indentation loads allow for the measurement of a larger area, thus providing a more composite material response from each indentation. The findings from initial testing of indentation and sample parameters were applied to further indentation testing on Montney Formation shale samples, presented in Chapter 3. Repeatability of indentation results is assessed at different scales of measurement, examining how well each scale of measurement characterized mean indentation mechanical properties of a sample. Indentation results are compared for all indentation tests, subsample mean indentation results, and sample mean indentation results. Indentation tests show repeatability of 78 %, and strong linear correlation (R2 = 0.94), between compared indentation test mean EIT results. Unoriented and oriented subsamples show 69 % and 80 % repeatability, and strong linear correlations (R2 = 0.94 and 0.83), between compared mean EIT results. Indentation results from both unoriented and oriented subsamples suggest that subsample mean EIT provides a good estimate of sample indentation mechanical properties, but that multiple subsamples should be tested to characterize a shale sample due to heterogeneity and differences in orientation. Indentation mechanical anisotropy is also assessed in oriented subsamples, using a ratio of mean EIT for samples with bedding oriented parallel, versus bedding oriented perpendicular, to the 200 direction of indentation. Indentation mechanical anisotropy is observed in 80 % of oriented subsamples, with mean EIT for bedding-parallel samples being 2 – 18 % higher than for bedding-perpendicular samples. Overall, shale sample mechanical properties are best represented by several indentation tests on multiple subsamples of a shale sample. Sample mean indentation results are able to characterize indentation mechanical variability between samples, such as the 29 samples of well 06-28-078-19W6, even with only a few centimeters difference in depth between samples. Instrumented indentation is capable of characterizing indentation mechanical variability between samples, but correlations for mean EIT and core plug geomechanical data or mineralogy is weak across all samples tested in this study. For individual wells, indentation results from core chip data display mixed geomechanical correlations, and improved relationships with mineralogy, compared to the complete dataset. Additional analysis of samples on a well-by-well basis led to discarding data from wells 12-12 and 13-28 from geomechanical moduli correlations. Samples from 12-12 are excluded due to unreliable core plug mechanical data, whereas 13-28 samples were sampled from disaggregated core from the Belloy Formation. Updated correlations and formulae between mean EIT and core plug Es (R2 = 0.53, y = 0.40x + 34.12) or Ed (R2 = 0.45, y = 0.46x + 26.88) are presented for the Montney Formation, providing an estimate of core plug mechanical data from indentation results. Geomechanical depth profiles for individual wells are also introduced, demonstrating how variation in mean EIT with depth can provide a relative index for other geomechanical moduli along the depth of a wellbore. In addition to geomechanical trends, mineralogy is compared to geomechanical moduli for both core chips and drill cuttings samples. Where relationships with mineralogy exist, different geomechanical moduli trend in the same direction. In most wells, geomechanical 201 moduli show moderate to strong positive correlation with carbonates and negative correlation with quartz and feldspar. Dolomite, the dominant carbonate mineral in the Montney Formation samples in this study, has a higher mean EIT than quartz or feldspar; therefore, where dolomite is relatively abundant or overprints other minerals a higher sample mean EIT may be measured. Mean EIT values do not show any moderate to strong correlation with clays, suggesting minimum influence of clay composition on indentation results in Montney Formation shales. In contrast, Es and Ed show negative correlation with clay, suggesting a more significant influence on core plug results, possibly due increased effects of mechanical anisotropy or other influences of clay on macroscale fabric or structure. Based on relationships with mineralogy, mean EIT is largely controlled by the dominant, stiff components in Montney Formation shales. Overall, drill cuttings samples do not show indentation results or geomechanical-mineralogical relationships that are representative of core chip results or core plug data. A01-32 drill cuttings show different trends in mineralogy with depth, as well as different correlations between mean EIT and mineralogy than core chips samples. C-004 drill cuttings show similar trends in mineralogy with depth as core chips, and share weak relationships between geomechanical moduli and mineralogy; however, analyses do not provide good evidence that drill cuttings sampled at 5 m intervals can be compared directly to depth-specific core chip samples. Drill cuttings are not shown to be useful for upscaling to core plug mechanical properties; however they still present an opportunity to characterize heterogeneity along a wellbore: if sampled at small depth intervals (e.g. 1 m) during the drilling process, drill cuttings can be used to create a relative comparison of indentation mechanical variability. Even in the lateral portion of a horizontal well there will be subtle variation in depth, lithology, and heterogeneity than can be measured with indentation testing. Additional, more accurate sampling 202 of drill cuttings and core plugs at specific depths is required to derive a correlation between indentation modulus from drill cuttings and core plug mechanical properties; however, if established, an indentation modulus index could be used in planned completions of hydraulic fractures, by selecting zones of geomechanical favourability for fracture initiation or propagation. 4.2 Industry Applications The primary industry application of this research is within the energy industry, specifically for planned completions of hydraulic fractures in oil and gas wells. Instrumented indentation provides a method of characterizing geomechanical variability from shale drill cuttings. Geomechanical properties can then be identified and hydraulic fractures can be planned to exploit locations which are mechanically favorable to fracture initiation and propagation. Additional applications may include rock mechanical analysis applied to geothermal exploitation or surface activities. 4.2.1 Instrumented Indentation as an Application to Planned Completions Instrumented indentation is an effective technique for characterizing variability of indentation modulus between core chips and drill cuttings samples. This variability can be mapped along the depth of a wellbore by testing drill cuttings sampled at regular depth intervals during the drilling process. Drill cuttings could be analyzed with instrumented indentation, resulting in a geomechanical depth profile of a wellbore, at depths of interest. In addition to geomechanics, drill cuttings could be tested for mineralogy using XRD, providing a check on geomechanical variation and quality of indentation results. With knowledge of the 203 geomechanical and mineralogical variation along a wellbore, and knowledge of local reservoir properties, hydraulic fracture completions could be planned at depths that are most favourable to fracture initiation or propagation. Figure 4.1 demonstrates a hypothetical case for planned completions in well C-004-F/094-G-08. While C-004 is a vertical well with actual hydraulic fracture placements selected at the top, middle, and base of the designated pay zone, it is treated as a horizontal well with approximately evenly spaced completions for this example. In this example, mean EIT of drill cuttings are sampled at 5 m intervals and are used to characterize the geomechanical variability throughout the depth of the wellbore. Measured indentation results are plotted, along with “Estimated Drill Cutting mean EIT” for depths within 5 m of a tested drill cutting sample. For the purpose of this example, “Hypothetical Drill Cutting mean EIT” is plotted where there is no nearby data; this would be replaced by measured indentation results from drill cuttings collected at 5 m intervals. “Planned” hydraulic fracture completions could then be placed based on optimal mean EIT values, given local reservoir properties. In this hypothetical example, “Planned Completions” are placed at high values of indentation modulus to promote fracture initiation and propagation, assuming lowest breakdown pressures. If optimal depths for fracture initiation can be targeted, planned completions may significantly affect well productivity in horizontal laterals several kilometers in length and with dozens of fracture stages. 204 Figure 4.1: Actual completions vs “planned” completions based on hypothetical mean EIT from drill cuttings samples. Hypothetical and estimated drill cuttings results are extended for a 5 m sampling interval.205 4.3 Future Research and Recommendations The next steps for future research should be a complete, in-house suite of analyses, including: (i) uniaxial/triaxial compression testing of shale core plugs, sampled at depth intervals that have distinct log or lithological properties; (ii) instrumented indentation and XRD analysis of core chips subsampled from core plugs; and, (iii) instrumented indentation and XRD analysis of drill cuttings, sampled at regular depth intervals throughout the entire area of interest of a wellbore (including the lateral of a horizontally drilled well). In this study, a large amount of variability is observed for sample depth differences of only a few centimeters. Indentation testing on future samples should be completed from core chip subsamples that are sampled directly from core plugs, rather than adjacent slabs of core. This would minimize geomechanical and mineralogical variability and error from sampling. Drill cuttings should be sampled at regular intervals, at as high of a sampling resolution as possible, throughout the entire depth of interest of the study wellbore. If possible, drill cuttings should be sampled through both the vertical portion and lateral portion of a horizontal wellbore, in order to confirm the ability of indentation techniques to characterize indentation mechanical variation in the lateral portion of a wellbore. Future studies should focus on the lateral portion of horizontal wellbores and the identification of geomechanically-optimal placement of hydraulic fracture completions. Production from wells completed with planned completions should be compared to wells completed with completions staged at regularly spaced, unplanned intervals. Indentation results should also be compared to any other geomechanically, mineralogical, or production data for a given well. 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Zonneveld, John-Paul, and Thomas F. Moslow. 2018. "Palaeogeographic setting, lithostratigraphy, and sedimentary framework of the Lower Triassic Montney Formation of western." Bulletin of Canadian Petroleum Geology 66 (1): 93-127. 227 Appendices Appendix A - Data Quality, Troubleshooting, and Data Correction and Filtering Within the thousands of indentation measurements performed for this research, several trends in indentation load-displacement curves and results started to appear. These patterns were noticeable in indentation sets in both homogeneous mineral and heterogeneous shale samples. Some affected the quality of indentation results, technical and hardware issues caused months of delay in data collection, while the majority were just the result of the process of instrumented indentation. The following subsections outline some of the observations and the solutions which were applied to ensuring only quality data was analyzed in this research. A.1 Indentation Load-Displacement Curves Indentation load-displacement curves were observed to come in all shapes, as the result of varying material properties and indentation measurement parameters. Figure A.1 and Figure A.2 offer examples of variability in load-displacement curves in heterogeneous shale. In this example indentation parameters are constant: indentations were performed in a 15 x 15 grid of standard indentations; a maximum indentation load of 200 mN was selected and indentations were spaced 200 µm apart. Of the 225 indentation measurements, 48 were filtered out for reasons explained in following sections. A subset of indentation results is displayed in Table A.1, presenting key variables and results for indentation measurements which we will explore in the following subsections. Within these results, and relating to curves displayed in Figure A.1, indentation measurements 1, 16, 17, and 19 all represent indentations performed on material which appears 228 light under the optical microscope. The primary components of these localities are likely relatively hard mineral components of the shale such as carbonates, feldspars, and quartz. Between these four measurements. indentation modulus is relatively high (31.5 – 44.3 GPa) whereas hardness varies (1248 – 4653 MPa). Measurements 16 and 17 are visually and mechanically the most similar: EIT results are 40.6 GPa and 37.5 GPa, and HIT results are 4653 MPa and 4399 MPa. Indentation 17 appears to have a pop-in feature (Hainsworth, Chandler and Page, 1998; Mukhopadhyay and Paufler, 2006) in the P-d curve around P=170 mN, possibly the result of the proximity and possible displacement as the indentation approached the grain boundary. Indentations 16 and 17 also display the greatest amount of elastic recovery, explaining the higher hardness and smaller residual indentation size relative to measurements 1 and 19. Indentation 1 has the highest EIT of the 4 measurements at 44.3 GPa but a moderate HIT of 2139 MPa. Induced fractures are visible at the extremities of the residual indentation, supporting the reduced hardness as a measure of resistance to permanent deformation. Indentation 19, while similar in residual size and fracturing to measurement 1, appears to have indented into a more composite material of light and dark (i.e. mineral grains and matrix). Indentation results support this observation, measuring the lowest EIT and HIT of the 4 indentations at 31.5 GPa and 1248 MPa. The limited resistance to deformation and elastic response are supported by low HIT and EIT, as well as the highest indentation displacement. 229 Figure A.1: Video microscope images (top) and load-displacement curves (bottom) for indentation measurements 1, 16, 17, and 19 of sample RM1-A, well C-004-G/094-G-08. Indentations were made on mineral grains, displaying residual indentations. 230 In contrast, measurements 7, 8, 9, and 21 are examples of indentations performed primarily on dark materials – likely matrix, organics, or pore space (Figure A.2). Indentation modulus is relatively low for these measurements, ranging from 12.6 GPa to 22.8 GPa. Once again, indentation hardness varies significantly from 1834 MPa to 4211 MPa. Indentations 9 and 21 display significant pop-in features in their P-d curves (i.e. measurement 21, P=130 mN), possibly due to indentation into pore space or the fracturing of grains; measurement 8 also displays a minor pop-in around P=95mN. Regardless, indentation results are calculated from the unloading curve, validating these indentation measurements. Overall, there is significant distinction within P-d curves for these measurements, despite all visual observations to be similarly indistinct. Measurement 7 displays a P-d curve with high max displacement but also high elastic recovery. A low EIT of 20.6 GPa supports the elastic nature of the measurement location, while the relatively high HIT (2346 MPa) compared to measurements 8, 9, and 21 indicates an underlying resistance to permanent deformation. Measurements 8 and 9 display greater maximum displacement but less elastic recovery than measurement 7 – this is expressed in higher stiffness (0.337 and 0.516 mN/nm) and EIT (22.8 GPa and 22.4 GPa). Resulting HIT values of 1357 MPa and 562 MPa are much lower than measurement 7, which is demonstrated visually with permanent deformation in the form of residual indentations that are visible with difficulty. Composite material surroundings and inclusion of more competent grains may help explain these softer yet more plastic materials, in comparison to at measurement 7. Measurement 21 is an enigma within these four measurements, displaying the lowest EIT (12.6 GPa) and HIT (453 MPa). Increased indentation depth is the overall cause of the results, 231 possibly due to indentation into pore space (and thus the unresisted displacement through the distance of the pore). Alternatively, organic matter or other softer materials in high abundance can help explain the high displacement and elasticity. Based on indentation load-displacement curves, indentation results, and visual analysis, instrumented indentation in heterogeneous materials is observed to represent material properties in three dimensions. Where indentation curves may appear the same, the residual indentation may be visually different. Conversely, visually an indentation may appear the same but recorded indentation results may vary significantly. It is through the combination of data analysis and visual inspection that one can best understand indentation datasets. 232 Figure A.2: Video microscope images (top) and load-displacement curves (bottom) for indentation measurements 7, 8, 9, and 21 of sample RM1-A, well C-004-G/094-G-08. Indentations were made in locations of low topography or matrix but still display surface contact and complete P-d curves. 233 Group Measurement EIT (GPa) HIT (MPa) Fm (mN) hc (nm) S (mN/nm) RM1-A 1 44.3 2319 200 1844 0.492 7 20.6 2346 200 1834 0.232 8 22.8 1357 200 2420 0.337 9 22.4 562 200 3778 0.516 11 39.1 2025 65 1117 0.267 16 40.6 4653 200 1294 0.32 17 37.5 4399 200 1333 0.305 19 31.5 1248 200 2526 0.482 21 12.6 453 200 4211 0.327 25 50.5 2234 36 781 0.241 26 54.1 4155 130 1100 0.359 27 35.2 779 31 1236 0.266 Table A.1: Example dataset for select indentation measurements of sample RM1-A, well C-004-G/094-G-08 234 A.2 Contact Point Correction Contact point is the detected or selected point of surface contact between indenter and sample material. It is achieved when the indenter overcomes a defined contact stiffness threshold, after which indentation into a material begins. Contact point is best selected at the first break in approach slope of the displacement curve and the first point with non-zero force of the load curve (Figure A.3). It should be noted that it is often hard to see the initial change in slope in the load curve, when indenting at high maximum indentation loads; therefore, the displacement curve slope change may be more useful for contact point selection. 235 Figure A.3: Correct contact point selection (modified from Indentation Software Manual, Anton Paar). 236 The contact point for every indentation measurement of every sample tested were corrected following this best practice. For example, Figure A.4 displays detected and corrected contact point for an indentation measurement in dolomite. The red arrow displays how the contact point was shifted to the left (the red crosshairs indicate exact CP location. Figure A.4: Detected (top) and corrected (bottom) contact point for measurement 2, dolomite 4 mesh sample) 237 The correct selection of contact point is essential because the contact point determines key height variables hm and hr. In turn, incorrect hm and hr will lead to inaccurate calculation of S, Ap, and indentation moduli (i.e. EIT, HIT). For example, the contact point correction in Figure A.4 shifts the detected contact point from 67.6 s (Pd = 2171.52 nm) to a corrected contact point at 64.8 s (Pd = 2118.47 nm). This change increases calculated EIT and HIT approximately 6% and 11%, respectively. A difference of less than 3 seconds (or 53.05 nm) significantly changes the result of an indentation measurement. Table A.2 shows how other indentation parameters and results are affected. 238 Group Measurement Parameter Unit Value - Detected Contact Point Value - Corrected Contact Point Change (%) DOL 4mesh - Variable Loads 2 HIT (O&P) MPa 5356 4767 11.01 HVIT (O&P) Vickers 496 441 11.01 EIT (O&P) GPa 113 106 6.30 E* (O&P) GPa 125 117 6.30 Er (O&P) GPa 112 106 5.71 hm (O&P) nm 970 1023 -5.47 Fm (O&P) mN 99.959 100.079 -0.12 S (O&P) mN/nm 0.6 0.6 0 Poisson's ratio Nu 0.3 0.3 0 hc (O&P) nm 842 895 -6.28 hr (O&P) nm 794 847 -6.65 hp (O&P) nm 573 625 -9.01 Epsilon (O&P) 0.7 0.7 0.0 Ap (O&P) nm² 18662420 20995998 -12.50 m (O&P) 2.3 2.3 -0.27 CIT % 2.7 2.6 5.33 RIT % -1.0 -1.0 0.10 Welast pJ 11838 11877 -0.33 Wplast pJ 24701 24777 -0.31 Wtotal pJ 36539 36654 -0.32 nit % 32.4 32.4 -0.02 X mm 9.0 9.0 0 Y mm 38.1 38.1 0 Table A.2: Detected versus corrected contact point data. A.3 Initial Loading Displacement Jump A common error, likely associated with contact point detection, is a jump in displacement during the initial contact and loading of an indentation measurement. For example, Figure A.5 shows the load and displacement curves versus time for measurement 74 on 4 mesh sized dolomite. On initial contact there is an immediate jump in displacement from approximately 239 1124.26 nm to 2610.22 nm. This displacement change of almost 1.5 µm, represents over a third of the total recorded displacement reached by the instrument in this measurement of approximately 4.1 µm. Because of this relatively large change in displacement, the calculated value of maximum displacement differs significantly depending where the contact point is selected along the displacement curve. At the displayed contact point selection hm is 1676.24 nm and EIT is 71.1 GPa. The detected contact point is 1 data point lower than displayed and calculated hm as 2267.90 nm and EIT as 49.7 GPa. Selecting the contact point at the top – 1 data point higher than displayed) or base of the displacement jump gives and hm and EIT ranges of 1478.90 nm to 2953.08 nm and 82.8 GPa to 36.9 GPa, respectively. Selection of contact point towards the top of the displacement curve give indentation results that best represent the material being indented; however, due to such a large shift in indentation results based on contact point selection, curves displaying large jumps in displacement upon initial loading were filtered. Unfiltered indentation datasets have contact point selected near the top of the displacement jump, with individual consideration for material and surface conditions. This phenomenon is suspected to be caused by pre-mature contact surface detection, as increasing the contact stiffness threshold from 500 µN/µm to 1000 µN/µm significantly reduced its occurrence in indentation measurements. 240 Figure A.5: Jump in displacement during initial loading and contact, with inlays of the P-d curves (left) and a video microscope image of the residual indentation (right). 241 A.4 Incomplete Loading and Spring Compliance Issues Another indentation error came in the form of incomplete loading and spring compliance issues. Despite residual indentations and similar surface conditions, maximum indentation load was not achieved in some indentation measurements. Figure A.6 displays inaccurate and incomplete indentation curves for measurements 11, 25, 26, and 26 of sample RM1-A, well C-004-F/094-G-08. Measurement 16, displayed in black, exemplifies correct indentation curves as a reference. In conjunction, Figure A.7 displays video microscope images of residual indentations of these five measurements. Upon inspection, measurements 26 and 27 suggest that surface roughness may factor into the resulting erroneous curves; however, in the same sample, most indentation measurements performed in similar locations of low topography produced complete indentations (i.e. Figure A.6). Measurements 11 and 25 recorded erroneous and dissimilar load-displacement curves, despite being visually similar to the completed indentation 16 and other measurements (i.e. Figure A.7). The technical fix on this issue was never concluded, nor was appropriate support provided by the instrument manufacturer. In some instances, indentation measurements would fail part-way through an indentation, freeze following an indentation, or end the indentation test list prematurely. Despite these technical errors, work was done to minimize the effects of this error on indentation results through data filtering. 242 Figure A.6: Load-displacement (top), load (middle), and displacement (bottom) curves for indentation measurements 11, 16, 25, 26, and 27 of sample RM1-A. 243 Figure A.7: video microscope images of indentation measurements 11, 16, 25, 26, and 27 of sample RM1-A, well C-004-G/094-G-08. Residual indentations can be seen in the middle of the red dotted triangle. In the specific case of incomplete loading – in test lists that were completed and with curves that were recorded – erroneous indentation curves are suspected to be related to the automatic calculation of spring compliance by the indentation software. Updated user manuals for the newest iteration of the NHT2, the NHT3 suggest spring compliance warnings may be the results of an inaccurate ADO, raised local sample topography, an approach speed which was too high, contact detection in air, or improper mounting of the indenter. Potential solutions include 244 remounting the indenter tip, verifying the local sample bump is less than 20 µm, re-performing the ADO at default, and adjusting approach parameters. The software post-data collection solution displayed in Figure A.8 – a spring compliance correction – was not possible with present indentation software. Despite stating in the manual that the spring compliance correction is both applicable and possible with the NHT2 instrument, the author was advised by the manufacturer technical support that because spring compliance was calculated automatically and couldn’t be changed. Figure A.9 shows an example of where a manual spring compliance could be employed. 245 Figure A.8: Theoretical spring compliance correction to change the approach phase slope of the load curve (modified from A Indentation Software Manual, p.118). 246 Figure A.9: Contact point correction window in indentation software, displaying non-rectilinear load curve approach slope due to spring compliance error. In summary, the main fix for spring compliance and load issues came in the form of data filtering and prevention. Erroneous curves were filtered from data sets, excluded even from datasets designated as ‘unfiltered’. Adjusting indentation parameters, ensuring frequent ADO measurements where topographic changes were evident, and the reset and recalibration of hardware was performed to minimize issues with loading and spring compliance. 247 A.5 Unfiltered versus Filtered Data Comparison and the Effects of Contact Stiffness Threshold on Indentation Results. Out of 25 indentations performed on quartz, 64% of standard, 52% of CSS, and 28% of LSS indentations were filtered (Table 2.1). Data filtering only significantly influenced indentation results for standard indentation measurements, changing mean EIT from an unfiltered 86.9 ± 8.2 GPa to a filtered 79.6 ± 4.1 GPa. For standard indentation measurements on quartz, with a contact stiffness threshold of 500 µN/µm, data filtering is suggested. On 4 mesh size dolomite, 60% of 124 standard measurements with a contact stiffness threshold of 500 µN/µm were filtered; at 1000 µN/µm, 11% of 93 measurements were filtered (Figure A.10; Table A.3). Unfiltered and filtered mean indentation moduli values (i.e. 91.4 ± 13.2 GPa unfiltered versus 88.4 ± 10.4 GPa filtered) are similar with 95% confidence, and results are within the 87 to 142 GPa literature Young’s modulus of dolomite (Bakri and Zaoui, 2011). At each stiffness threshold, mean unfiltered and filtered results are repeatable. For standard indentation measurements in dolomite samples, contact stiffness threshold should be selected at 1000 µN/µm to minimize erroneous P-h curves and limit the need for data filtration. 248 Figure A.10: Unfiltered and filtered indentation modulus data for standard indentations on >4 mesh sized dolomite. Sample Measurement Parameters Contact Stiffness Threshold (µN/µm) Unfiltered Mean EIT (GPa) Filtered Mean EIT (GPa) Dolomite Sample Size 4 mesh (4760 µm) Fm 100 mN 1000 94.2 ± 15.4 (N = 93) 91.2 ± 11.1 (N = 83) 500 91.4 ± 13.2 (N = 124) 88.4 ± 10.4 (N = 49) Table A.3: Measurement parameters and unfiltered and filtered indentation results for indentations on 4 mesh sized dolomite. 249 For Set 1 shale samples, indentation results outline the influence of data filtration (Figure A.11 and Table A.4) and contact stiffness threshold (Figure A.13 and Table A.5). In the 12 samples tested with standard indentation (Pmax = 200 mN; stiffness threshold = 1000µN/µm), 11 – 60% of measurements were filtered. A strong linear correlation (R2 = 0.98) was observed, suggesting similar mean results between unfiltered and filtered measurements. Mean EIT values differed by -0.1 to 10.3 GPa after filtering, with 7G-3, 7G-4, and 7G-10 demonstrating the greatest increase of 8.8 – 10.3 GPa. Six samples (7G-3, 7G-4, 7G-9, 7G-10, 7G-11, and 7G-12) have mean unfiltered and filtered mean EIT that are not repeatable within 95% confidence intervals, suggesting influence of filtering on mean indentation results. Filtration is suggested for standard measurements in shale samples to minimize the influence of erroneous curves on indentation results. Indentation results comparing data filtration and contact stiffness threshold in shale samples from well 01-20-063-08W6 are plotted in Figure A.13 and summarized in Table A.5. The 4 samples show differences of -6.1 to 3.7 GPa between unfiltered and filtered mean indentation modulus. At a contact stiffness threshold of 500µN/µm, between 39 – 69% of indentation measurements were filtered, versus 8 – 17% filtration at 1000 µN/µm. Mean EIT for unfiltered versus filtered measurements are similar within 95% confidence intervals, with the exception of sample #19 T3 tested at 500 uN/um stiffness threshold where means differ significantly (73.3 ± 18.6 GPa unfiltered versus 67.2 ± 11.2 GPa filtered). 250 Figure A.11: Unfiltered (left) and filtered (right) colour-paired EIT results for standard measurements on samples of Set 1 Montney Formation shales.251 Sample Unfiltered EIT (GPa) Filtered EIT (GPa) 7G-1 62.5 ± 11.7 (N=75) 63.1 ± 11.9 (N=67) 7G-2 64.6 ±16.2 (N=299) 65.1 ± 10.8 (N=245) 7G-3 51.2 ± 14.0 (N=213) 56.2 ± 10.6 (N=86) 7G-4 36.1 ± 13.2 (N=381) 39.5 ±10.8 (N=232) 7G-6 58.9 ± 14.1 (N=193) 59.4 ±10.7 (N=155) 7G-7 52.3 ± 15.7 (N=352) 54.0 ±12.6 (N=266) 7G-8 61.5 ± 11.0 (N=144) 61.4 ± 11.0 (N=126) 7G-9 48.7 ± 13.0 (N=326) 52.3 ± 10.9 (N=229) 7G-10 38.9 ± 11.2 (N=352) 43.4 ± 9.8 (N=197) 7G-11 51.0 ± 12.5 (N=385) 53.7 ± 10.4 (N=288) 7G-12 49.4 ± 11.3 (N=491) 51.3 ± 10.4 (N=405) 7G-15 58.1 ± 14.8 (N=149) 58.1 ± 11.6 (N=113) Table A.4: Unfiltered versus filtered standard indentation measurement results for Set 1 shale samples. 252 Figure A.12: Unfiltered versus filtered mean EIT for standard measurements on Set 1 Montney Formation shales. 253 Figure A.13: Indentation modulus results for unfiltered (top) and filtered (bottom) measurements at 500 µN/µm and 1000 µN/µm contact stiffness threshold for shale samples of well 01-20-063-08W6. Colours indicate stiffness threshold pairs and samples (i.e. dark red indicates sample #1 at 1000 µN/µm stiffness threshold; light red indicates sample #1 at 500 µN/µm). 254 Sample Measurement Parameters Contact Stiffness Threshold (µN/µm) Unfiltered Mean EIT (GPa) Filtered Mean EIT (GPa) #1 – CSS CSS Fm 100 mN 1000 63.1 ± 23.7 (N = 96) 59.8 ± 14.5 (N = 84) 500 51.2 ± 14.9 (N = 98) 54.9 ± 12.6 (N = 50) #4 Standard Fm 200 mN 1000 63.6 ± 12.0 (N = 100) 63.7 ± 9.2 (N = 90) 500 69.2 ± 19.6 (N = 139) 66.8 ± 10.1 (N = 43) #4 – CSS CSS Fm 100 mN 1000 65.8 ± 12.4 (N = 99) 66.3 ± 11.3 (N = 82) 500 65.4 ± 16.2 (N = 136) 66.7 ± 11.0 (N = 83) #19 – Test 3 Standard Fm 200 mN 1000 67.6 ± 10.4 (N = 99) 67.0 ± 9.8 (N = 91) 500 73.3 ± 18.6 (N = 99) 67.2 ± 11.2 (N =40) Table A.5: Comparing contact stiffness threshold in unfiltered and filtered indentation results of well 01-20-063-08W6 shale samples. Subsequent instrumented indentation testing on dolomite, calcite, quartz, and Montney Formation shales is suggested to be performed at contact stiffness threshold of 1000 µN/µm and filtered to minimize the effects of erroneous P-h curves on mean indentation results. 255 Appendix B - Repeatability of Mean Indentation Results for Standard and CSS Measurement Types in Shale Drill Cuttings Drill cuttings samples from the Montney Formation were tested with standard and CSS indentation measurements (Figure B.1 to Figure B.7). A good linear correlation (R2 = 0.79) is observed for mean EIT results from the two measurement types, plotting within a similar trend as core chip samples (Figure B.1). Repeatability of mean EIT results tested relatively poor, with only 8 of 21 standard to CSS comparisons demonstrating repeatable results. Mean results from standard measurements measured relatively lower mean EIT than CSS measurements, likely due to differing maximum indentation loads possible with each measurement type. Standard measurements with Pmax of 200 mN would indent to a greater mean maximum displacement than CSS measurements that are only capable of indentations at Pmax of 100 mN. A greater load and larger displacement would result in a larger indentation area, encompassing more components of a composite material in the indentation area and measuring a relatively stiff, more composite material response. Mean indentation results for a given sample and measurement type should be compared to other samples tested with the same measurement type, when possible. 256 Figure B.1: Mean EIT for Standard and CSS measurements on core chip and drill cuttings subsamples. Combined core chips and drill cuttings correlation is R2 = 0.91. 257 Figure B.2: Standard and CSS indentation results for drill cuttings of shallow sampling depth, well C-004. 258 Figure B.3: Standard and CSS indentation results for drill cuttings of moderate sampling depth, well C-004. 259 Figure B.4: Standard and CSS indentation results for drill cuttings of deep sampling depth, well C-004. 260 Figure B.5: Standard and CSS indentation results for drill cuttings of shallow sampling depth, well A01-32. 261 Figure B.6: Standard and CSS indentation results for drill cuttings of moderate and deep sampling depths, well A01-32.262 Figure B.7: EIT results for standard and CSS measurements on core chips and drill cuttings, plotted as colour pairs (i.e. darkest yellow = DC-1780m standard [left] and CSS [right]).263 Appendix C - Indentation Results, Geomechanical Depth Profiles, and Mineralogy of A01-32-083-25W6, Separated by Sampling Depth Interval Figure C.1: Indentation results for first sampling depth interval (2310 – 2345 m) samples of well A01-32-083-25W6. 264 Figure C.2: Geomechanical-depth profile for first sampling depth interval (2310 – 2345 m) samples of well A01-32-083-25W6.265 Figure C.3: XRD mineralogy versus geomechanical moduli for first sampling depth interval (2310 – 2345 m) samples of well A01-32-083-25W6. 266 Figure C.4: Indentation results for second sampling depth interval (2455 – 2465 m) samples of well A01-32-083-25W6. 267 Figure C.5: Geomechanical-depth profiles for second sampling depth interval (2455 – 2465 m) samples of well A01-32-083-25W6. 268 Figure C.6: XRD mineralogy versus geomechanical moduli for second sampling depth interval (2455 – 2465 m) samples of well A01-32-083-25W6. 269 Figure C.7: Indentation results for the third sampling depth intveral (2524 – 2542 m) samples of well A01-32-083-25W6. 270 Figure C.8: Geomechanical-depth profile for the third sampling depth interval (2524 – 2542 m) samples of well A01-32-083-25W6. 271 Figure C.9: XRD mineralogy versus geomechanical moduli for the third sampling depth interval (2524 – 2542 m) samples of well A01-32-083-25W6.
Thesis/Dissertation
eng
Geological Sciences
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Utility of instrumented indentation for the optimization of horizontal wellbore completions with examples from the Montney formation of Alberta and British Columbia
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