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Mapping of modern pyroclastic deposits with ground penetrating radar: experimental, theoretical and field.. Rust, Alison C. 1998-12-31

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M A P P I N G O F M O D E R N P Y R O C L A S T I C DEPOSITS W I T H GROUND PENETRATING RADAR: EXPERIMENTAL, T H E O R E T I C A L AND FIELD RESULTS by A L I S O N C. RUST B . S c , The University of Toronto, 1996  A THESIS S U B M I T T E D IN P A R T I A L F U L F I L L M E N T OF THE REQUIREMENTS FOR T H E D E G R E E OF M A S T E R OF S C I E N C E in T H E F A C U L T Y OF G R A D U A T E STUDIES G E O L O G I C A L SCIENCE DIVISION D E P A R T M E N T OF E A R T H A N D O C E A N SCIENCES  We accept this thesis as conforming to the required standard  T H E U N I V E R S I T Y OF BRITISH C O L U M B I A August, 1998 © A l i s o n C . Rust, 1998  In presenting this thesis in partial fulfilment of the  requirements for an advanced  degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department  or  by his or  her  representatives.  It  is  understood  that  copying or  publication of this thesis for financial gain shall not be allowed without my written permission.  Department The University of British Columbia Vancouver, Canada  DE-6 (2/88)  11  Abstract This thesis explores the utility of ground-penetrating radar (GPR) i n mapping and characterizing young pyroclastic deposits. In particular, laboratory measurements examine the relationship between porosity and dielectric constant of volcanic rocks. Simulations and field studies demonstrate how G P R data can be used to both image, and quantify, relative porosity variations in pyroclastic deposits. The laboratory results (Chapter 2) indicate a strong and definite relationship between total porosity and dielectric constant of dry, felsic to intermediate volcanic rocks. The trend formed by these data is remarkably tight and coherent, especially considering the samples derive from five deposits and two volcanoes. Chapter 3 models the propagation of a radar wave through a welded pyroclastic flow deposit of variable porosity using the porosity-dielectric constant relationship from Chapter 2. Although porosity changes are gradational, the deposit generates reflections. Distinctive signals correspond to portions with essentially constant porosity or areas where porosity changes with depth at a moderate rate. G P R data were collected on sections of pyroclastic fall and welded and unwelded pyroclastic flow deposits i n Central Oregon (Chapter 4). Airfall and pyroclastic flow deposits can be distinguished on the basis of their distinct geophysical character. For example, the same characteristic signals for regions of changing porosity with depth and regions of constant porosity, which were recognized i n the modeling (Chapter 3), are seen i n the G P R data. The results indicate that G P R can be used to map the intensity of welding and separate zones of uniform welding from zones of variable welding. Velocity analysis of common midpoint ( C M P ) surveys is shown to aid in mapping facies variations, as well as,  Ill  converting travel times into depths in radargrams. GPR is also found to be useful in delimiting deposit thicknesses and geometries away from exposure.  Table of Contents Abstract  ii  List of Tables  vi  List of Figures  vii  Preface  x  Acknowledgments  xi  1. Introduction  1  2. Dielectric constant as a predictor of porosity in dry volcanic rocks 2.1 Introduction 2.2 Previous studies 2.3 Selection of sample suites 2.4 Measurement of porosity and density 2.5 Measurement of AT' 2.6 Relationship between <& and K' 2.7 Relationship between p and K' 2.8 Applications and limitations of results for G P R  4 4 5 13 14 21 27 34 36  3. Detection and mapping of welding in pyroclastic flows with G P R : Forward modeling results 3.1 Introduction 3.2 Subsurface model profiles 3.3 Critical layer thickness (L ) 3.4 Forward Modeling Results 3.5 Applicability to field G P R studies 3.6 Conclusion  39 39 40 44 47 53 58  4. Methods for mapping and characterizing pyroclastic flow and fall deposits with G P R 4.1 Introduction 4.2 Field sites 4.3 Calibration of characteristic signals in radargrams 4.4 Velocity analysis 4.5 Columbia Southern Canal: mapping deposit geometries 4.6 Summary and conclusions  60 60 61 63 75 87 98  T  c  5. Conclusion  100  References  103  Appendix I Measurement of density and porosity in volcanic rocks  114  Appendix II Scale of heterogeneity of pyroclastic deposits and applicability of gradational porosity profile models  122  Appendix III Inversion for porosity i n the presence of water  126  vi  List of tables  Table 2.1 Table 2.2  Details of 24 previous studies which reported dielectric constant measurements on igneous samples  6  Experimentally measured values of density, porosity and dielectric constant for samples of volcanic rock  17  Table 2.3  Parameters to model lines describing dielectric constant-porosity data  32  Table 4.1  Collection parameters and processing for radargrams  64  L i s t of Figures Figure 2.1  Plot of K'vs. p for data from Shmulevich et al. (1971) and model curves derived from Ulaby et al. (1990) and Olhoeft and Strangway (1975), respectively  8  Figure 2.2  Published values of i C a n d <& for volcanic rocks  11  Figure 2.3  Comparison of values of measured porosity, determined as connected porosity calculated from E q . (2.5), and total porosity calculated from E q . (2.6) : '. ,  18  T  Figure 2.4  Values of 0 „„(a) and <3>7 (b) are plotted against  Figure 2.5  Measured values of iT'plotted as a function of frequency  Figure 2.6  Plots of inversus $  Figure 2.7  Comparison of new data (porosity values represent total porosity) and  C()  20  p  T  :  25  26  results from other sources  28  Figure 2.8  Plots of ^'versus p  29  Figure 3.1  B u l k density  T  (p ) T  versus depth profiles for a basaltic ignimbrite at Playa  de Tasarte, Gran Canada (after Freunt and Schmincke, 1995)  41  Schematic demonstration of steps i n conversion from continuous porosity (O) profile to discretized profile of dielectric constant (K')  43  Figure 3.3  Discretized profile of K' using 1 cm thick layers  45  Figure 3.4  Simulations for profile a (Fig. 3.1-3.3) at a variety o f frequencies (f) and layer thicknesses (L)  46  Figure 3.2  Figure 3.5 Figure 3.6 Figure 3.7  Synthetic traces resulting from modeling a 25 M H z electromagnetic wave propagating through the two (a and b) Playa de Tasarte sections  49  Synthetic traces (0-150 ns) resulting from modeling 25, 35, 50, 100 and 200 M H z waves passing through the two Playa de Tasarte sections  50  Results (150 to 300 ns) of simulations for variety of frequencies  51  K'  profiles of Figure 3.3 at a  viii  Figure 3.8  R a w G P R data with minimal processing  54  Figure 3.9  Comparison of model and field G P R traces: a) synthetic trace for Playa de Tasarte, profile b (welded to base); b) average of 31 G P R traces from positions 10 to 40 m of Figure 3.8a  56  Location of two field sites near Bend, Oregon. A ) Cascade Pumice Company pits. B ) Site along the Columbia Southern Canal  62  Figure 4.1 Figure 4.2  Locations of surveys at the Cascade Pumice Company pits. Black arrows mark midpoints of common midpoint ( C M P ) surveys  65  Figure 4.3  Radargrams from the Cascade Pumice pits  66  Figure 4.4  Photographs of G P R lines at Cascade Pumice Company pits  68  Figure 4.5  Migrated version of 50 M H z , line 1 radargram (Fig. 5.4a)  72  Figure 4.6  50 M H z common midpoint survey C M P 1 (Fig. 4.2)  76  Figure 4.7  Results o f five C M P surveys plotted as root mean squared velocity vs. time  77  Figure 4.8  Plots showing velocity analysis results for five C M P surveys  79  Figure 4.9  Plot of velocity versus height above Tumalo Tuff/Bend Pumice boundary  80  Figure 4.10 Plot of velocity i n lowermost interval velocity for Tumalo T u f f (V-n-) vs. Bend Pumice velocity ( V )  83  travel time (center column). The depths scales for each survey derive from C M P analyses (Fig. 4.8,4.9)  85  BP  Figure 4.11 The first 10 m of surveys 1 and 4 are displayed with common two-way Figure 4.12 Comparison of depth to Tumalo Tuff/Bend Pumice boundary calculated from C M P velocity analysis (Fig. 4.9) and depth measured with a tape measure  86  Figure 4.13 V i e w of Columbia Southern Canal site, looking upstream  88  Figure 4.14 Location of G P R surveys at the Columbia Southern Canal site  89  Figure 4.15 50 M H z surveys at the Columbia Southern Canal without topographic correction  90  Figure 4.16 100 M H z radargrams at Columbia Southern Canal trending approximately north-west  91  Figure 4.17 100 M H z radargrams at Columbia Southern Canal trending approximately north-east  92  Figure 4.18 Four views of 100 M H z radargrams fenced together....  93  Figure 4.19 Photographs from Colombia Southern Canal site, a) Exposure on south-east sideof canal across from survey point C (Fig. 4.14). A l l deposits show little or no welding on this exposure, b) Layer of cobbles in strongly welded Shevlin Park flow marking the boundary of the phases of the flow  95  Figure 4.20 a) Migrated radargram for survey F-P (100 M H z ) using a constant velocity of 0.1 m/ns. b) Interpreted stratigraphy for a)  97  Figure A2.1Three processed versions of the radargram of Figure 3.8. a) Migrated data assuming constant velocity of 0.09 m/ns. Note the removal o f hyperbolic events seen in F i g . 3.8. b) Each trace is the mean of ten adjacent traces in Fig.3.8. c) Each trace is the average of ten adjacent traces of the migrated radargram (a) 124  Figure A 3 . 1 Dielectric constant vs. depth data for two C M P surveys at Cascade Pumice Company pits (Chapter 4). Shaded region indicates range of values predicted for dry, intermediate to felsic volcanic rocks according to laboratory experiments  128  x  Preface  This thesis comprises slightly modified versions of three papers (Chapters 2, 3 and 4) which are submitted to refereed journals or are i n preparation for publication. Chapter 2 was submitted to the Journal of Volcanology and Geothermal Research. Chapter 3 and 4 are i n preparation for submission to the Journal of Volcanology and Geothermal Research, and Bulletin of Volcanology, respectively. M y supervisor, Dr. J. K . Russell is a co-author on all three papers, while Dr. R. J. Knight is third author for the Chapter 2 paper. A l l data collection (lab and field), data processing, analysis and interpretation was performed by me. Dr. Russell supervised and financed the project, and provided text revisions. D r . Knight contributed analytical supervision and text revisions for Chapter 2.  xi  Acknowledgments  Financial support for this research derives from an N S E R C P G S A scholarship ( A . C . Rust) for September 1996 to September 1998, and N S E R C Research Grant #OGP0820 (J. K . Russell). I especially thank Rosemary Knight and members of the Rock Physics lab group, Paulette, K e v i n and Christina for their assistance and helpful suggestions. I am grateful to Steve Cardimona for the use of his program which models E M wave propagation (Chapter 3). This chapter also benefitted from comments by Guy Cross. I thank Britt H i l l for suggesting interesting field sites, and Larry Chitwood and family for their consummate generosity and the logistical support they provided in Oregon. Finally, I appreciate K e l l y ' s never-ending enthusiasm and thank h i m for being an insightful igneous petrologist just crazy enough to try geophysics.  1  Chapter 1 Overview  Ground-penetrating radar (GPR), used i n conjunction with conventional field techniques, offers an effective means of mapping the distribution and architecture of Modern volcanic deposits. There are several challenges associated with conventional mapping which G P R allows us to overcome. Firstly, the youthful, undissected landscapes associated with many Modern volcanic edifices offer little exposure of the 3 dimension (depth). Secondly, rd  volcanic stratigraphy is notoriously complex in terms of facies variations. Thirdly, the distribution of volcanic deposits can be heavily influenced by paleo-topography, making the stratigraphic correlation of specific units complicated. The fact that many young volcanic deposits are relatively thin and electrically resistive makes it very likely that G P R can probe the entire thickness of these deposits. O n this basis G P R promises to be useful i n mapping deposit boundaries as well as characterizing the internal structures of volcanic units. A theme, central to this research, is the use of G P R to obtain information about spatial variations i n the porosity of volcanic deposits. Volcanic successions can show large variations i n porosity that relate directly to volcanic processes. Porosity variation relates to the type of deposit (e.g., pyroclastic deposits vs. lava flows), to stratigraphic position within an individual unit (e.g., flow top vs. flow interior), and to lateral facies changes (e.g., proximal vs. distal lava flows). G P R has the potential to map porosity i n the subsurface; this information can i n turn, be used to identify deposit types and facies changes within units. The thesis comprises three papers (Chapters 2, 3 and 4 ) , as described below, followed  2 by a summary of principal conclusions (Chapter 5) and three appendices which provide additional discussion on peripheral topics. The chapters progress from laboratory work examining the effect of porosity on radar velocity in volcanic rocks (Chapter 2), to forward modeling of radar propagating through a welded pyroclastic flow (Chapter 3), and finally to G P R field work on pyroclastic deposits (Chapter 4). Chapter 2 is a laboratory study which examines the relationship between dielectric constant (K') and porosity (O) of dry volcanic rocks. Dielectric constant is the primary physical property controlling the velocity of radar through low loss material and K' values can be extracted from G P R data by acquiring estimates of radar velocities from common midpoint surveys. However, an understanding of the dielectric properties of volcanic rocks is required to convert K' values into material properties (i.e., porosity). Previous investigations of the dielectric constants of volcanic rocks have primarily focused on the influence of frequency, temperature and bulk density on K'. Chapter 2 reviews results from the literature, presents new data, and then explores the relationship between K', porosity and bulk density for a suite of 34 samples of diverse volcanic origin, composition, and vesicularity. A n empirical model is presented that relates rock porosity to dielectric constant of non-basaltic volcanic rocks. Chapter 2 shows that there is a strong correlation between the degree of vesicularity of volcanic rocks and their dielectric properties. Chapter 3 investigates the potential and the limitations of using G P R to delineate and trace welded portions of pyroclastic flows using a program by Steven Cardimona which models electromagnetic wave propagation through layered media. Input K' profiles are calculated from porosity profiles of a pyroclastic flow using the empirical ^'-porosity  relationship developed i n Chapter 2. Two approaches to detecting and mapping welding are considered: i) identification of characteristic signals or textures in radargrams for distinct welding facies; ii) tracing of strong, continuous reflections produced by rapid porosity changes bordering welded zones. Furthermore, I test ideas derived from this modeling against a case study comprising G P R data collected at a well exposed, welded pyroclastic flow. Appendix II discusses the effect of the scale of heterogeneity of pyroclastic deposits on the interpretation of radargrams using the modeling results of Chapter 3. Chapter 4 uses G P R field data collected on pyroclastic rocks near Bend, Oregon to demonstrate methods of characterizing and mapping pyroclastic deposits with G P R . The surveys show that valuable volcanological information is attainable from G P R studies. Surveys from a pumice quarry allow the comparison of radar signals to exposed stratigraphy; on this basis characteristic radar signals for individual units and facies are identified. Data from common midpoint ( C M P ) surveys are analyzed to determine relative porosity patterns in a welded pyrolclastic flow. A second field site, 3 k m to the south-west, tests the utility of G P R i n mapping deposit geometries away from exposed stratigraphy.  The use of G P R i n  volcanology is i n its infancy and an important contribution of this chapter is the demonstration of the quality of data that can be obtained and the type of information of interest to volcanologists that can be deduced with G P R surveys.  4  Chapter 2 Porosity as a predictor of dielectric constant of dry volcanic rocks  2.1 Introduction Ground penetrating radar (GPR) is a high resolution, near-surface, geophysical technique that provides a means of imaging geological structures and materials i n the subsurface. Young volcanic deposits are ideal candidates for G P R surveys because they are electrically resistive, and commonly form thin surficial deposits within 50m of the earth's surface. O f specific interest i n my research is the use of G P R to obtain information about the spatial variability in the porosity of young volcanic deposits. Such a technique would be a powerful tool i n volcanological studies because volcanic rocks are commonly vesicular and can show large variations in porosity that relate to volcanic processes. Properties of subsurface materials can be extracted from G P R data by obtaining estimates of radar velocities. This is done using common midpoint surveys, which employ an acquisition geometry that makes it possible to determine the velocity with which an electromagnetic wave travels through a region o f the subsurface. The dielectric constant (JC) of the material i n the region can be calculated from the velocity. However, the conversion o f K' into material properties, such as porosity, requires an understanding of the relationship between the property and the dielectric constant. Knowledge of the factors contributing to K' of volcanic deposits also impacts our ability to predict what aspects of volcanic deposits can best be imaged with G P R . The relationship between the measured dielectric properties and the porosity o f  5 volcanic rocks is affected by numerous factors such as mineralogy, water content, and phase geometries, thus making the accurate interpretation of porosity from G P R data a challenging research problem. In this study I begin to address this issue by investigating the dependence of K' on porosity for dry volcanic rocks. Measurements of K' are presented for several compositions o f volcanic rocks over a range of porosities, and a model is presented that relates porosity to dielectric constant. While further research is required to incorporate the effect o f other factors on dielectric properties, this model is a first step towards assessing the way i n which G P R data can be used to both image, and quantify, porosity variation i n young volcanic deposits.  2.2 Previous Studies Table 2.1 summarizes the results of 24 papers reporting dielectric constant measurements o f igneous rocks and includes information on samples, methodology and additional physical properties. The dielectric properties of igneous rocks, and volcanic rocks in particular, have been shown to be sensitive to frequency and temperature (e.g., SaintAmant and Strangway, 1970; Chung et al., 1970), water saturation (Roberts and L i n , 1997), mineralogy (e.g., Hansen et a l , 1973), fabric (Tuck and Stacey, 1977; Hawton and Borradaile, 1988), and bulk density (e.g., Olhoeft and Strangway, 1975). B u l k density is strongly affected by porosity changes but, to date, there has been no comprehensive study directly examining the porosity-dielectric constant relationship in volcanic rocks.  6  2  S  I"  S  3  |  a.  e.  «  s  8  —  H  c/i  — t/i  S * E. E.  £  w  S. •3  *  Crt  w  K  ?  ?n '  o  fPO  -  8  o 2.  EJ Si.  S I  O  >  a EL  3  ic anc nic rock: ic anc nic rock: ic anc uto nic rock:  W  "H. -a_ o 1  a EL  3 & jj B.  8  B  §  fc>  i  11  3!  •g £.  • —  S ?  o o X  2  o  3 3 re  •? •8  a. s > D. C  cr o  Q.  - •  3 3  I  o  3 + 8  w g.  S  8  3  D- ft OQ  a-  ! >3  Ii: a  E  a.  * s. a -=!  I*  1.1  I  i 3  .-1 J-i I 3  3  O."  •5'  if 8.  7  Density & K' Measurements of density and K' have been made on rocks and their corresponding powders (Campbell and Ulrichs, 1969; Troitsky and Shmulevich, 1973; Frisnillo et al., 1975),  on suites of solid and/or naturally unconsolidated volcanic rocks (Chung et al., 1970;  Gold et al., 1971 and 1973), on solid rocks (Bondarenko, 1971; Shmulevich et al., 1971) and on unconsolidated material (Gold et al., 1970; Adams et a l , 1996). The most comprehensive study in terms of the range of density and the range of chemical compositions of volcanic rock samples is by Shmulevich et al. (1971). They measured the dielectric properties of 89 acid to ultrabasic igneous rocks (68 volcanic, 21 intrusive) at a frequency of 500 MHz. The bulk density (p ) of volcanic samples ranged from r  0.54  to 2.90 g/cm . Rather than compare p and K' directly, Shmulevich et al. (1971) plotted 3  7  K' and the Krotikov parameter (a), against S i 0 content. The Krotikov parameter is defined 2  as:  a=V^ -l/p 7  (2- ) 1  T  Troitsky and Shmulevich (1973) found the Krotikov parameter to be practically invariant for lower density igneous rocks ( p < 2 g/cm ), and for all acidic rocks, regardless of density. 3  r  This study and others (e.g., Campbell and Ulrichs, 1969; Adams et al., 1996) indicate a trend of increasing K' with decreasing S i 0 content of volcanic rocks. 2  Using the values of a and p reported by Shmulevich et al. (1971), I have recalculated r  values of K'. Figure 2.1 is a plot comparing the values of K' and o (Shmulevich et al., 1971) T  against model curves of Ulaby et al. (1990) and Olhoeft and Strangway (1975). Ulaby et al. (1990)  fit experimental data from 80 rocks of diverse origin (volcanic, plutonic,  8  35 30 25  o volcanic A intrusive - - • U l a b y et al., 1990 Olhoeft and Strangway, 1975  o  20  AD  K'  15  6>  10  P  T  (g/cm ) J  F i g u r e 2.1 Plot of K'vs. p for data from Shmulevich et al. (1971). The model curves K' = \.96 and K' = l.93 derived from Ulaby et al. (1990) and Olhoeft and Strangway (1975), respectively. T  Pr  Pr  9 clastic, carbonate and "other") to: £'=(1.96±0.14)  (2.2)  Pr  Their dielectric data were collected at frequencies from 0.5 to 18 G H z . K' was found to be independent of frequency and they attributed 50% of the variance i n the data to variations i n sample density. Olhoeft and Strangway (1975) compiled and fit density measurements (92 solid and unconsolidated lunar rocks) to values of K' measured at frequencies greater than 0.1 M H z . Their model curve (Eq. 2.3) is very similar to that of Ulaby et al. (1990):  ^'=(1.93±0.17)  (2-3)  p/  The K' predicted by the models of Ulaby et al. (1990) and Olhoeft and Strangway (1975) are consistently lower than the majority o f Shmulevich et al. (1971) data. Although intended to predict dielectric constants as a function of p over the complete range of r  densities, the model curves fit the lower density data best up to values of 2.0 g/cm . The 3  variance i n measured values of K' increases markedly at higher values of bulk density (e.g., > 2 g/cm) which suggests that some factor other than density also affects dielectric constant of igneous rocks (Fig. 2.1). Nevertheless, density appears to be a good predictor o f dielectric constant for volcanic rocks o f low to moderate density.  Porosity & K' There are few published data relating dielectric constant directly to porosity (<&) for volcanic rocks. Five studies by Campbell and Ulrichs (1969), Chung et al. (1970), G o l d et al. (1970), Adams et al. (1996) and Russell and Stasiuk (1997) provide a total o f 28 ( $ , K')  10 points (Fig. 2.2). Data from Roberts and L i n (1997) and Drury (1978) are omitted because the samples were saturated with fresh or sea water (Table 2.1). Measurements o f K' were made at a variety of frequencies, and compositions o f samples, states of consolidation and methods of measuring porosity all varied. Campbell and Ulrichs (1969) and G o l d et al. (1970) used powdered samples and porosity was calculated assuming that the rock from which the powder originated was not porous (i.e., p T{rock)  Ps(rock)  Ps(powder)  ): (2.4)  Thus, the reported values of porosity represent minima; the extent to which they are l o w depends on the actual porosity of the original rocks. The four data points from G o l d et al. (1970) derive from a single powdered lunar rock compacted to various porosities. The eleven data points from Campbell and Ulrichs (1969) represent crushed rocks of different composition: obsidians (2), trachyte, phonolite, and basalt (7). A l l powders were compacted to a porosity o f 40%. One objective of this study (Campbell and Ulrichs, 1969) was to compare the electrical properties of powdered material to those o f the corresponding rock. They found that the difference i n K' between rock types was much smaller where measured on powdered rocks (all at 40% porosity) relative to measurements on the solid rock equivalents. The relevant samples of Adams et a l , (1996) consist of six natural volcanic ashes o f variable composition (basalt (2), andesite, dacite (2), and rhyolite) and two powdered basalt samples. K' measurements were made from 4 to 19 G H z . Porosity and density values  11  12  •  10  • • o  8 K'  C h u n g et al., 1970 Russell and Stasiuk, 1997 Campbell and Ulrichs, 1969  A  A d a m s e t a l . , 1996  •  Gold et al., 1970  6 4 A  2 0  0  0.2  0.4  ai  0.6  0.8  Figure 2.2 Published values of K'and $ for volcanic rocks. Legend includes sources.  12 themselves are not reported but rather the fractional volumes are listed. Fractional volume is defined as p  lps,  T(powder)  however, Adams et a l , (1996) do not state how the solid densities  were determined. Fractional volume is equivalent to 1  and the relationship between <& and  K' was indirectly explored by testing the validity o f various mixing formulas i n relating the dielectric constants of porous powders to the dielectric constants of their solid rock equivalents. Russell and Stasiuk (1997) measured dielectric constants o f four volcanic rocks (basalt lava, dacite pumice, dense obsidian breccia, and dacite lava). They argued that sample porosity is primarily responsible for variations in K', implying that chemical composition, modal mineralogy, proportion o f glass, and grain size have only secondary effects. Measurements were made on multiple sub-samples o f each o f the four hand-samples. Two o f the rock types (basalt and pumice) showed significant variance i n K'. Although there was not always a clear relationship between porosity (determined with a helium pycnometer) and dielectric constant in sub-sample suites, a direct correlation was found between the relative variance i n sample porosity and the variation in dielectric properties between disks taken from the same hand-sample. The data point from Chung et al. (1970) is from a lunar rock o f unusual chemistry (Kanamori et al., 1970) with low silica (37 w t . % S i 0 ) and very high titanium content (12 2  w t . % T i 0 ) . Porosity was calculated by examining the pore to rock ratio on the surface of the 2  cylindrical sample. They assumed that this two-dimensional porosity was representative o f the three-dimensional porosity (void volume over total volume) of the rock.  13 Effect of ilmenite on K' Chung et al. (1970) attributed the higher dielectric constants of their lunar samples, relative to terrestrial basalts, to a greater ilmenite ( F e T i 0 ) content. Similarly, Hansen et al. 3  (1973) found a positive correlation between dielectric constant and ilmenite content o f some basalts. These findings are plausible as ilmenite has a dielectric constant o f 30 - 80 (Parkhomenko, 1967; Nelson et al., 1989) compared to, for example, plagioclase, pyroxene and olivine which have dielectric constants between 4 and 11 (Keller, 1989; Nelson et al., 1989). However, neither Hansen et al. (1973) nor Chung et al. (1970) took into account relative porosities or densities of the samples. In fact, porosity data were reported for only one of the three samples examined by Chung et al. (1970). Olhoeft and Strangway (1975) compiled about ninety measurements for lunar rocks and soils and found no correspondence between K' and ( T i 0 + FeO) content when K' was normalized for constant bulk density (Eq. 2  2.3). This result, however, does not necessarily negate ilmenite as one of the principal controls on dielectric properties o f igneous rocks, because density also increases with increasing ilmenite content. A better understanding of the role of ilmenite would be gained by comparing rock compositions and modal mineralogies to values of K' normalized for porosity rather than density. The effects o f other semiconducting oxides commonly occurring i n volcanic rocks (magnetite and titanomagnetite) should also be considered.  2.3 Selection of Sample Suites The central aim of this study is to explore the relationship between the porosity (or vesicularity) o f volcanic rocks and their dielectric properties. I also elected to sample a  14 variety of compositions of volcanic rocks in order to test for compositional controls on K'. Compositionally the study suite spans dacite to basalt. Specifically, it comprises: i) dacite (~ 68 wt. % S i 0 ) lava and pumice collected from lava flow, airfall and pyroclastic f l o w 2  deposits, Mount Meager, B . C . (Stasiuk et al., 1996); ii) dacite (~ 60-62 wt. % S i 0 ) lavas 2  from the R i n g Creek lava flow, Garibaldi Volcanic Complex, (Sivertz, 1976; Brooks and Friele, 1992); iii) basalt (~ 55 wt. % S i 0 ) from a Cheakamus Valley lava flow (Green, 1977; 2  Higman, 1990), and iv) pahoehoe basalt (~ 50 wt. % S i 0 ) lava from Mauna U l u volcano 2  (Swanson, 1973). Hand samples were chosen i n the field with the aim of maximizing the variance in vesicularity of samples from each deposit. This sampling scheme produced suites of rocks of similar composition and mineralogy with a spectrum of porosities (and bulk densities). Each hand-sample was cored, producing 5 cm diameter right cylinders. B u l k density (p ) was r  calculated using measurements of weight, diameter and height. Redundant samples (rocks with equal bulk densities from the same deposit) were excluded from further procedures. From each core, a 0.5 cm thick disk was prepared. In several instances the cores showed large-scale textural heterogeneity, i n which case multiple disks were prepared. For example, all five Mauna U l u disks (each of which has a different porosity) derive from a single core. A l l disks were cleaned, dried in an oven at 105°C . Samples equilibrated with the room atmosphere for at least two days before physical properties were measured.  2.4 Measurement of porosity and density In general, earlier studies of dielectric properties of volcanic rocks report values of  15  bulk density (p ) and not porosity. I have also measured p , which depends both on porosity 7  r  and rock composition, in order to integrate my results with a larger data set from the literature. Density measurements are also used to cross-check primary porosity measurements, by identifying samples with low apparent porosity due to unconnected pores.  Methods  Porosity (<£) was measured in two distinct ways. Firstly, porosity is calculated from measurements of volume: <D = - ^ - ^ v  (2.5)  T  where V is the total volume of the disk and V is the solid volume, excluding pores. r  s  Operationally, V is calculated geometrically on the basis of caliper measurements of height r  and diameter of the sample disks. V , on the other hand, is measured with a helium s  pycnometer, a technique based on the ideal gas law. If there are unconnected pores not accessed by the helium, then V is overestimated as it includes the unconnected pore volume. s  Therefore, this method of measurement yields the "connected porosity" (Q> onn)- T h C  e  connected porosity is equal to "total porosity" (<J>) only if all pores are connected. r  The second way of determining $ addresses the possibility that a fraction of the pores is not penetrated by helium during the pycnometer experiment. <& as opposed to <& , is r  Coim  calculated from: $  PS^PT  (  2  Ps  where p - is the bulk density of the disk, and p is the density of the solid phase. The bulk 7  s  6  )  16 density is determined by dividing the mass o f the disks by their volumes based on calliper measurements. The density o f the solid phase, p is the void-free density o f the sample disk. s  This measurement is made by crushing a portion o f the hand-sample to 200 mesh and calculating the solid density from the mass o f the powder and the He-pycnometer measured volume o f the same sample o f powder. Based on replicate measurements, the precision (Is) associated with measurements o f p , p , $ „ „ and $ are all less than 1%. s  T  c  n  7  Results Measured values o f bulk density, connected and total porosity are listed in Table 2.2. Figure 2.3 is a comparison o f the results o f the two methods used to measure porosity. For porosities lower than 0.5 there is excellent agreement between <& and <& , values. Sample r  PF1 represents a single notable exception (<& „„=0.33, 0 Co  7  Com  =0.40). For porosities above 0.5,  the measured total porosity is significantly greater than the connected porosity for many samples.  The deviation (<& -<& „„„) can be as large as 0.11. This indicates that there are 7  c  unconnected pores i n several disks and direct measurements using the helium pycnometer on solid samples may result in apparent porosities significantly lower than true porosities. In fact up to 17% o f the pore space can be unconnected (e.g., sample PF1). A l l samples showing differences in porosity values >0.01 are from the Mount Meager suite o f dacites. In thin section, these rocks are glassy and show a bimodal distribution o f vesicles comprising large (mostly macroscopic), well-connected pores and small (< 0.25 mm), more poorly connected vesicles within the glassy matrix. In contrast, the M a u n a U l u basalts have porosities greater than 0.52 yet have virtually identical values o f 0  7  and <& „„. Co  Table 2.2  Experimentally measured values of bulk density (p ), connected r  porosity (<& „„), total porosity(<& ) and dielectric constant (K') for samples o f Co  7  volcanic rocks. Dielectric constants are reported for a frequency o f 10 M H z . Small letters indicate multiple disks from the same hand-sample. location  sample  Pr  Mount Meager  PMla  1.083  0.528  0.575  3.411  PMlb  1.086  0.529  0.573  3.429  P M 2a  0.937  0.543  0.623  3.073  PM2b  0.807  0.589  0.675  2.795  PM3  0.534  0.752  0.789  2.478  PM5  0.710  0.675  0.715  2.689  PM6  0.514  0.697  0.796  2.505  PM8  0.688  0.691  0.723  2.703  PM9  0.732  0.609  0.706  2.722  PM10  0.603  0.651  0.758  2.498  Ring Creek  Mauna Ulu  Cheakamus  K'  PF1  1.505  0.332  0.398  4.362  MM1  2.377  0.075  0.083  6.074  MM2  2.241  0.129  0.138  6.080  MM3  2.142  0.175  0.180  5.341  MM4  1.257  0.486  0.501  3.847  MM5  1.454  0.408  0.417  4.366  MB1  2.403  0.038  0.042  18.353  RC1  2.320  0.122  0.130  6.372  RC2  2.492  0.077  0.083  6.678  RC3  2.419  0.093  0.099  6.493  RC5  2.080  0.212  0.214  5.738  RC6  1.788  0.318  0.313  5.161  RC9  2.376  0.108  0.115  6.606  RC10  2.207  0.164  0.165  5.984  RC11  2.236  0.158  0.164  6.022  ULUa  1.370  0.554  0.557  5.183  ULUb  1.349  0.564  0.564  4.979  ULUc  1.476  0.522  0.523  5.573  ULUd  1.274  0.589  0.588  4.866  ULUe  1.317  0.571  0.574  4.668  CB5a  2.712  0.094  0.103  8.322  CB5b  2.732  0.088  0.096  8.203  CB7a  2.181  0.265  0.272  11.633  CB7b  2.272  0.233  0.241  13.472  18  Figure 2.3 Comparison of values of measured porosity, determined as connected porosity calculated from Eq. (2.5), and total porosity calculated from Eq. (2.6). See text for details.  19 The implication is that all porosity is connected and in thin sections the samples of basalt show pores that are macroscopic and well-connected. Because both connected and unconnected pores should affect values of K', all subsequent references to sample porosities refer to total porosities as determined by E q . (2.6). Figures 2.4a and 2.4b serve to illustrate, i n another way, the importance of measuring <E> over Q> 7  . For each rock suite of variable vesicularity and constant matrix, there should  Conn  be a simple linear relationship between porosity and bulk density (Eq. 2.6). Values of <& plotted against p, should produce a linear trend with y-intercept (<&) of 1 and x-intercept (p ) 7  of p , the true density of the solid with no porosity. Different volcanic rock suites w i l l have s  different x-intercepts because they have intrinsically different compositions and hence densities. Figure 2.4 develops this concept using values of <£ „„ (Fig. 2.4a) versus <& (Fig. Co  7  2.4b). The data show significantly more scatter in Figure 2.4a. In particular, plotted as <& o»n> C  the samples of dacite from Mount Meager are inconsistent with a straight line model suggesting different rock compositions. However when the same data are plotted as <I? they 7  fit a line of the form of E q . (2.6). Note that although the Ring Creek suite forms a clear trend, it does not extrapolate to a y-intercept (<3>) of 1 (corresponding to 100% air when the r  rock has no mass) with either set of porosity values. This indicates a small but systematic variation i n solid density likely due to a correlation between mineralogy (e.g., % glass) and porosity.  20  P  (g/cm ) 3  r  F i g u r e 2.4 Values of <E> „„ (a) and $ (b) are plotted against p . values of solid density of 3.10 g/cm and 2.52 g/cm (see text). Co  r  3  T  3  Fits to data extrapolate to  21  2.5 Measurement of K' Capacitance data were collected with an H P 4 1 9 2 A impedance analyzer using modified methods of R. Knight and co-workers in the Rock Physics Laboratory at The University of British Columbia (e.g., Knight and Nur, 1987; Knight and Abad, 1995). To make capacitance measurements, the dielectric material (rock) is placed between two parallel conductive plates (electrodes). Capacitance is a measure o f the charge polarization that occurs i n the sample between the plates. Dielectric constant (K ) is the ratio o f the 1  capacitance with the dielectric material between the plates to the capacitance with a vacuum between the plates. Dielectric constant is calculated from capacitance (C) by:  where A and d are the area and the separation of the electrodes, respectively, and 8» is the permittivity o f free space (8.554 x 10" F/m). Sample disks are approximately 5 cm i n 12  diameter and 0.5 cm thick. Dielectric constant data were collected at 25 frequencies over the interval 10 k H z to 10 M H z .  Experimental  Procedure  The standard procedure i n the Rock Physics Laboratory at The University o f British Columbia is to form electrodes (capacitors) by sputtering gold on the top and bottom faces of the sample disks. This method could not be used in the present study because many o f the samples are extremely porous (up to 80% pores) and/or contain large pores. G o l d sputtering o f the samples would have resulted in electrodes which deviated significantly from ideal  22 parallel plates. The surface area of gold on a pumice sample, for example, would be much greater than the area calculated from the diameter of the disk. A l s o , the distance separating the electrodes would not be constant and in some cases would be substantially less than the height of the disk measured with callipers. Lastly, a few samples have pore networks which directly connect the upper and lower surfaces of the sample discs. Sputtering such samples may form a "gold path" connecting the upper and lower electrodes rendering dielectric constant measurement impossible. Several electrode configurations were tested on five samples having variable porosity, as well as on a non-porous material of known dielectric constant ( S T Y C A S T H i K ;  K'=6).  The different electrode forms included: •  0.85 m m thick copper disks  •  0.025 m m thick silver foil  •  silver paint on copper disks or silver foil  •  saline electrolyte-aqueous polymer gel (generally used to attach electrodes to skin) on copper disks or silver foil  Where wet silver paint or gel was used to couple the copper disks or silver foil to the sample, it was applied to the metal rather than the rock to ensure an even distribution of paint and minimize the amount of conductive material entering pores. Prior to all measurements, the impedance analyzer was tested on a platinum-sputtered S T Y C A S T H i K  (K'=15)  disk with  the same dimensions as the sample suite. Once placed in the sample holder and attached to the impedance analyzer, differences between repeated capacitance readings were insignificant for all electrode configurations tested.  23 The dielectric constant at low frequencies (below 10-100 k H z ) was found to be extremely sensitive to the electrode configuration; however, at higher frequencies most methods converged to the same values of K'. Electrodes comprising copper disks or silver foil without A g paint or gel as adhesive consistently produced the lowest values of K'. This is attributed to air gaps due to poor contact between the sample and the electrodes. When A g paint was added (between sample and metal) higher dielectric constants were observed and using saline gel rather than A g paint produced still higher values. Electrode configurations involving gel were rejected because measured values of K' for S T Y C A S T H i K were always significantly higher than the reference value (K'=6). In the end all data were collected using copper disks coupled to the sample with silver paint. I chose this method because: the procedure generated consistent, reproducible results, the copper discs are easier to handle than foil and the method reproduced the accepted value for the S T Y C A S T H i K (A!"'=6) standard to within 4% over the entire.range of frequencies measured (10kHz to 10 M H z ) . I also measured dielectric constant of four volcanic samples using silver foil in place of the copper disks; these two electrode configurations agree to within 1.4% at 10 M H z . Although all samples were cored with the same bit, average disk diameters varied from - 4 8 m m to 50.5 m m due to drill movement and contrasts i n rock competency. Three pairs of copper disks of different diameters were made. The electrodes for each sample used the largest pair of copper disks whose diameter did not exceed that of the sample. The area used in E q . (2.7) is the area of the copper disk rather than the sample area. The entire circular surfaces of six of the low porosity samples ( M M 1 , M B 1 , R C 2 , R C 9 , C B 5 a , and C B 5 b ) were  24 coated with silver paint (no copper disks) and the entire area of the sample used i n E q . (2.7). In general, the dielectric constant determined using copper disks and silver paint is higher at lower frequencies and lower at higher frequencies than for silver paint alone (over the entire surface) but the deviation is less than 3% at 10 M H z except for a single outlier ( M B 1 , - 8 % difference).  K'-Frequency  dependence  K' is a measure of polarizability and different polarization mechanisms dominate at different frequencies. The dominant mechanism at G P R frequencies is dipole polarization; at lower frequencies interfacial polarization (Maxwell-Wagner effect) can be important. The latter mechanism occurs i n heterogeneous materials and is caused by charge accumulations along interfaces when an electric field is applied (Howell and Licastro, 1961). The measured values of dielectric constant for all samples are shown as a function of frequency in Figure 2.5. Samples have higher dielectric constants at lower frequencies and/ decrease to a near-constant K' value at frequencies above 0.1-1 M H z . Notable exceptions are M B 1 (a glassy clast from a "Merapi-style" breccia), C B 7 a and C B 7 b (scoria from the base of a basalt lava flow), and to a lesser degree all Mauna U l u samples (Fig. 2.5b). Samples M B 1 and CB7a,b have significantly higher dielectric constants than other samples from the same deposits (Fig. 2.5 and 2.6a). Furthermore, for these samples, the measured values of K' do not level off at higher frequencies suggesting that the high values of K' reflect interfacial polarization, although this mechanism usually contributes little to K' i n dry rocks. The Mount Meager outlier ( M B 1 ) has the same mineralogy as the rest of the Mount Meager suite  25  K  frequency (Hz) 12 —  10  -  Cheakamus basalt Mauna Ulu basalt Mount Meager & Ring Creek  8H K'  1 2x10  ' 6  I 4x10  I 6  6x10  I 6  8x10  6  1x10  7  frequency (Hz)  F i g u r e 2.5 Measured values of ^'plotted as a function of frequency, a) Sample M B 1 , C B 7 a and C B 7 b show greater frequency dependence and significantly higher dielectric constants than the rest o f the sample set. Data points (filled circles) are shown for these three samples; ^'measurements were made at the same 25 frequencies for all samples, b) Samples with lower values o f K'(<\0) are plotted against a non-logarithmic frequency scale.  26  20 • o D •  • »MB1  15 -  Mount Meager Ring Creek M a u n a Ulu Cheakamus Eq. (2.11): TP, K'.=7.54  •  K' 10  Eq. (2.9):cc=0.96,  K.=6.97  Eq. ( 2 : 9 ) : a = 0 . 4 9 ,  K',=14.95  •  air  a  i i 0.2  .  .  .  i 0.4  0.6  ,  ,  0.8  - 0.5 is  - B L 2 _  !  o  o  o  4 ^  • o  -0.5  0.4  0.2  Eq. (2.11): TP, K',=7.54 Eq. (2.9): a = 0 . 9 6 , K',=6.97  0.6  0.8  -1  99%  7.5  K'  s  7  6.5  0.5  •  E q . (2.9): ot=0.96, K',=6.97  •  Linear, K',=6.93  •  Eq. (2.11): TP, K',=7.54  0.6  0.7  0.8  0.9  1.1  1.2  1.3  a  F i g u r e 2.6 Plots of ^'versus O . a) Experimental data from this study and fitted curves: E q . (2.11) (TP, A* =7.54) fitted to M M - R C data; best fit of E q . (2.9) to the M M - R C data (K =6.97, a=0.96) (i.e., E q . 2.13); best fit of E q . (2.9) to the Mauna U l u suite (K= 14.95, a=0.49). b) Plot of residuals for the two curves (Eq. 2.9 and 2.11) fitted to the M M - R C data set. c) Confidence limits for two parameter fit (Eq. 2.9) to M M - R C data set show the T P model (a=0.5) to be outside the region of three standard deviations of uncertainly on the fit parameters. The linear model (volume average), however is within one standard deviation. The shaded region represents physically unrealistic solutions for the dipolar dielectric constant o f a heterogeneous mixture.  27 but it is unique in that its pore spaces are almost exclusively i n the form of cracks. It could be that the cracks host a thin (~10A) layer of adsorbed water, the presence of which has been shown to increase dielectric constant (Knight and Endres, 1990). A similar argument does not hold for the Cheakamus samples as the porosity is mainly in the form of primary vesicles.  2.6 Relationship between <& and K' Comparisons of dielectric constant with porosity (Fig. 2.6a, 2.7) and bulk density (Fig. 2.8) are made with the highest frequency data (10 M H z ) . The suite with the most complete porosity spectrum is from Mount Meager. The data (excluding M B 1 ) form a smooth and definite pattern in K-$> space of increasing dielectric constant with decreasing T  porosity. The trend for R i n g Creek data is approximately equivalent to that formed by the more felsic Mount Meager samples and, thus, the two suites are modeled as a single data set. The M a u n a U l u basalt samples show a similar pattern but define a distinct trend relative to the Mount Meager-Ring Creek samples and are therefore treated separately. There are not enough Cheakamus basalt samples to form a coherent trend and these data were not modeled. Because the Mount Meager and R i n g Creek suites span the greatest porosity, further discussion concentrates on this combined data set (excluding the outlier, sample M B 1 ) , henceforth referred to as the M M - R C data set. A simple approach to modeling dielectric constant of a heterogeneous material is to calculate the total dielectric constant (K^) from the volume fraction (6,) and dielectric constant (K) of each of the i components using a model of the form: (K;r=Y, ( ,*r Q  i  K  (-) 2  8  28  20  15  K'  10 -  •  •  •  These data  •  Russell and Stasiuk, 1997  o  Campbell and Ulrichs, 1969  •  Chung et al., 1970  A  Adams e t a l . , 1996  •  Gold e t a l . , 1970  0  Figure 2.7 Comparison of new data (porosity values represent total porosity) and results from other sources (porosity values are not necessarily total porosity). Arrows attached to vertical lines indicate that porosities are minima but there is no significance to the arrow lengths. See text for details and explanations of labels. Model curves plotted are identical to those in Fig. 2.6.  29  K'  25 20  • o • •  Basalts (present study) Other Volcanic Rocks (present study) Basalts (Shmulevich et al., 1971) Other Volcanic Rocks (Shmulevich et al., 1971)  MB1  15  K' 10 5 0 p  r  (g/cm ) J  Figure 2.8 Plots of K'versus p . a) Experimental data from this study shown against two T  models fitted to the M M - R C data: E q . (2.14) is the best straight line through theoretical value for air, and E q . (2.17) is the best fit curve of the form used by Ulaby et al. (1990) and Olhoeft and Strangway (1975) (Fig. 2.1). b) Comparison of data from this paper to data of Shmulevich et al. (1971). Volcanic data are grouped as basalts and other volcanics. Heavy dashed line is model derived from Ulaby et al. (1990) data, also plotted in F i g . 2.1.  30 where K* is the complex dielectric constant and a is a geometrical factor. This is known as the Lichtenecker-Rother (1931) equation. The theoretical lower and upper limits o f dipolar dielectric constant for a heterogeneous mixture occur where the components are arranged i n series (<x=-l) and in parallel (a=l), respectively. When the components are non-conducting, as is assumed for the air and the solid in the samples used i n this study, K* can be approximated by K'to yield:  (AJ.) =E B  W  "  ( -9) 2  A commonly used model o f this type is the time propagation (TP) model (Wharton et al., 1980):  ^  = £  6  ,  ^  (2.10)  In principle, one could build up the effective dielectric constant o f a rock by taking into account the constituent minerals, glass, and air. Here I consider each sample as a mixture o f air (K' =\) and a non-porous solid with a fixed dielectric constant K' , the expanded form o f ai  s  T P is: ^  = <V(l-$ )^ r  (2.11)  The general least squared-residuals best fit of E q . (2.11) for the M M - R C data set gives K' = s  7.54 (Table 2.3). This curve is plotted in Figure 2.6a. T P fits the M M - R C data well (Table 2.3); however, a plot o f residuals (Fig. 2.6b) shows a systematic distribution. Part o f this deviation from the model, particularly the large  31 residuals at high porosities, could be due to pore size and shape variation as T P does not take into account the geometry of the components. Alternatively, I have fit the data to E q . (2.9) solving for both K' and a by minimization of the x function: 2  x =£  [K' (K'(r,a))f r  2  (2.12)  2  (Press et al., 1986) where o is the mean uncertainty on the measured values of K. t  The  optimal solution, a=0.96, and K' =6.91: s  (^)  0 9 6  = $ + 6.97  0 9 6  (l-$)  (2.13)  fits the data very well (Table 2.3, F i g . 2.6a). Furthermore the residuals associated with this model show that the two parameter model is substantially better than the T P model for describing these data (Fig. 2.6b). Figure 2.6c shows the Is, 2s, and 3s (or 68, 95, 99%) confidence limits on the model solutions and demonstrates clearly that a T P model (cc=0.5) lies outside the reasonable solution space. The a value for M M - R C data (0.96) is very close to the theoretical upper limit (a =1) which is strictly linear. A linear model constrained to pass through the theoretical value for air, has the fitted parameter K=  6.93 (Table 2.3) and  corresponds, in principle, to an arrangement of columns of rock and air perpendicular to the electrodes. Clearly, this is not an accurate description of the pore geometry of the entire M M - R C sample set. However, the Mount Meager pumice pores can be larger than, or o f similar dimensions to, the thickness of the sample disks (0.5 cm), and the samples may be approaching a parallel arrangement at high porosities. The presence of such pores could explain why T P does not model these data as well as other data sets.  Table 2.3 Parameters to model lines describing AT'-porosity data. Data set  Model  MM-RC  T P : E q . (2.11)  MM-RC  a  R  7.543  0.5*  0.979  Two-parameter fit: Eq.(2.9), (2.13)  6.965  0.965  0.985  MM-RC  Linear, through (0,1)  6.927  1*  0.984  Mauna U l u  T P : E q . (2.11)  14.768  0.5*  0.833  Mauna U l u  Two-parameter fit: Eq.(2.9)  14.955  0.488  0.833  *fixedvalue required by model  1  33 The Mauna U l u basalt data were fit by least-squared residuals to the same models as the M M - R C data set (Table 2.3). T P (Eq. 2.11) gives K' =14.77 suggesting that the solid s  phase of the Mauna U l u suite has a dielectric constant approximately double that o f the Mount Meager and Ring Creek suites. The two-parameter fit (Eq. 2.9) has optimal values K' =14.95, a = 0.49 which is essentially the same as T P (a=0.5) and is also plotted i n Figure s  2.6a.  Comparison with previous results Figure 2.7 combines information from Figures 2.2 and 2.6a by superimposing the new K'-$  data on previous results. The data of Russell and Stasiuk (1997), labeled A through D ,  clearly agree with the data presented here, although Russell and Stasiuk (1997) used goldsputtered surfaces as electrodes and only measured connected porosity. In particular, two samples o f porous intermediate volcanic rocks ( A and B) lie on the trend formed by Mount Meager and Ring Creek samples. Point D represents a sample of basalt from the same outcrop as sampled in this study (e.g. Cheakamus). It plots relatively close to correlative samples in this study. These results indicate that the copper disks with silver paint electrodes give similar results to gold sputtering at low and moderate porosities. Point C is equivalent to the outlier M B 1 o f the present study but unlike M B 1, its porosity is not dominated by to cracks. The large gap i n K' between samples C and M B 1 is consistent with the abnormally high value for M B 1 being related to its pore geometry. The data from Campbell and Ulrichs (1969), G o l d et al. (1970) and Adams et al. (1996) deviate from the trends defined by my data. There are several possible explanations  for this disparity. Firstly, there are significant differences i n rock composition. Secondly, the three previous studies measured K' on samples of powdered rock or natural ashes and, thus, the pore geometries would be substantially different from those found i n the Mount Meager pumice samples. Thirdly, the porosities reported by Campbell and Ulrichs (1969) and G o l d et al. (1970) are minima because it was assumed that the rocks from which the powders were crushed were non-porous. Finally, the data derived from the three previous studies were collected at much higher frequencies (450 M H z to 19 G H z versus 10 M H z for the present study).  2.7 Relationship between p and K' T  Plots of K' vs. total porosity (Fig. 2.6a) and K' vs. bulk density (Fig. 2.8a) are approximately mirror images of each other. This is not surprising as, for small variation i n p , there is a simple relationship between porosity and bulk density (Eq. 2.6).  The basalts  s  (Cheakamus and Ulu) have higher dielectric constants than the more acidic rocks (Mount Meager and R i n g Creek) of similar porosity but the basalts also have higher p values (Fig. s  2.4, Table 2.2). B u l k density is dependent on both <E> and p , and plotting K' vs. bulk density s  rather than porosity brings the data for basalt samples closer to the trend defined by M M - R C samples (Fig. 2.8a). However, the M M - R C and U l u trends are still distinct i n (p , K') space T  and only the M M - R C data set is modeled. The M M - R C trend is remarkably linear (Fig. 2.8a). The best fit of a straight line constrained to pass through (0,1) is:  35 K'=2.26p +l  (7? =0.990)  (2.14)  2  T  Although the straight line fit is entirely empirical, it has two attributes: a) it describes all o f these data well (excluding M B 1 and basalts), and b) it offers a very simple model for making rapid estimates o f K for non-basaltic, dry, volcanic rocks based on a single measurement: p . r  For the purposes o f comparison, the M M - R C data were also fitted with a curve o f the form used by Olhoeft and Strangway (1975) and Ulaby et al. (1990). Fits by Olhoeft and Strangway (1975) and Ulaby et al. (1990) relating K' to p data, are based on a logarithmic r  addition formula (Lichtenecker and Rother, 1931):  \o (K' ) = g  T  £e  1  logfjq)  i  (2.15)  Treating the system as a mixture o f air and non-porous rock, (Eq. 2.15) simplifies to: Pr  ,  V  _ v^r)  _ ,P,  (2-16)  r  Assuming p is constant, K' can be related to p as was done by Ulaby et al. (1990) and s  T  Olhoeft and Strangway (1975) (Fig. 2.1). The resulting fit for the M M - R C data is: K'=2.22 T  (2-17)  p  This curve is plotted in Figure 2.8a. The solution predicts higher K' for a given p than the T  models o f Ulaby et al. (1990) and Olhoeft and Strangway (1975) (Eq. 2.2 and 2.3); however, the best fit to my experimental data is the linear model (Eq. 2.14).  36 Comparison with previous results Figure 2.8b compares the (K', p ) data from this paper to data for 68 volcanic rocks T  measured by Shmulevich et al. (1971) (e.g., F i g . 2.1). Plotted as K' vs. p , the present study T  shows higher K' for a given bulk density than most of the volcanic samples measured by Shmulevich et al. (1971) (Fig. 2.8b). This is particularly true at low bulk densities (high porosities). Part of this disparity is due to the difference in measurement frequency (500 M H z vs. 10 M H z ) . The scaling problem of large pores compared to sample thickness may also be contributing to the higher K' of the new experimental data at high porosities. The Shmulevich et al. (1971) data show a large spectrum of dielectric constants for basaltic rocks; indeed most of the dispersion in the K'-p  r  trend is due to basaltic samples  (Fig. 2.8b). The number of basalts in the present sample set is limited. Although the Mauna U l u samples show a clear trend of increasing dielectric constant with decreasing porosity, the span o f porosities is too small to model accurately. The Cheakamus basalts would not fit any air-rock mixing laws as the more porous samples (CB7a,b) from the base of the flow have much higher dielectric constants than the massive flow samples (CB5a,b). Perhaps the higher and more varied modal abundances of Fe,Ti oxides (magnetite, ilmenite, titanomagnetite) in basalts is responsible for the greater variance. Excluding all basalt samples, the results of this study parallel those of Shmulevich et al. (1971) and produce a single trend which can relate porosity or density to dielectric constant (Fig. 2.8b).  2.8 Applications and limitations of results for G P R One of the attributes of this study is that I have established a clear relationship  37 between O and K' for dry, non-basaltic volcanic rocks over a wide range of porosities. The results indicate that inverse modeling techniques could be applied to ground penetrating radar (GPR) velocity data to derive estimates of porosities or map changes in porosity of dry volcanic deposits. One possible application is to map zones of welding i n partially welded pyroclastic flows. The welded zones are composed of the same material as unwelded tops and bases but have lower porosity because slower cooling rates i n the middle of the deposit provide sufficient time for hot clasts to flatten and thereby reduce porosity. If the change in porosity is gradational, a single, strong continuous reflection may not be generated (e.g., defining some critical porosity). However, by using C M P analysis, changes in velocity with depth could be determined and converted into a porosity profile. Some caution should be taken in applying laboratory results directly to the interpretation of G P R data. Three main reasons are that: 1) the highest frequency used i n these laboratory measurements is 10 M H z and this is significantly below conventional G P R frequencies for geological applications (e.g., 50-200 M H z ) , 2) there may be a problem in upscaling laboratory dielectric measurements on rock samples to the scale of deposits due to spatial heterogeneity (Chan and Knight, 1997), and most importantly, 3) in nature, the pore space may be partially saturated with water which could drastically alter the dielectric properties of a deposit because of the large contrast between K[  mter  (80) an&K'  ajr  (1).  Although G P R has been used in geological studies since the 1960s, its application to problems associated with volcanic deposits is in its infancy. G P R w i l l never replace traditional stratigraphic mapping but rather should complement it by extending observations of physical properties, distributions, thicknesses and internal structures to areas which lack  38  exposure. In order to realize the full potential of GPR, a better understanding of the factors that contribute to the dielectric constant of volcanic rocks is paramount. The development of an empirical model relating porosity and dielectric constant of dry, non-basaltic volcanic rocks is an important step. Further work incorporating such factors such as mineralogy (e.g., ilmenite mode), pore and mineral geometries, and water content are required to enhance the simple models presented here.  39  Chapter 3 Detection and mapping of welding in pyroclastic flows with GPR: Forward modeling results  3.1 Introduction Porosity, or vesicularity, is a first order, primary physical property of volcanic deposits.  Porosity variation relates to the type of deposit (e.g., pyroclastic deposits vs. lava  flows), to stratigraphic position within an individual unit (e.g., flow top vs. flow interior), and to lateral facies changes (e.g., proximal vs. distal lava flows). Chapter 2 showed a strong correlation between the degree of vesicularity of volcanic rocks and their dielectric properties. Specifically I used laboratory measurements on dry, non-basaltic samples of volcanic material to develop the following relationship between porosity (<P) and dielectric constant (£"): (iC)  0 9 6  =0> + 6 . 9 7  0 9 6  (l-$)  (3.1)  These results have import for the potential of G P R as an aid to volcanological studies as K' is the primary physical property controlling the velocity of radar through l o w loss material:  V =  c  (3.2)  Indeed, these laboratory results, i n conjunction with E q . 3.2, suggest that there is great potential to constrain the actual or relative porosities of volcanic deposits using G P R . Specifically, radar data from the field elucidate variations in dielectric properties of deposits; in volcanic rocks these variations in K' can commonly be related to differences i n porosity.  40 Pyroclastic flow deposits represent an obvious target for this type of survey because welding of pyroclastic flows can cause substantial variations i n porosity. Pumice clasts and shards within hot, thick pyroclastic flows collapse, flatten and anneal under the weight of overlying material, causing substantial porosity reduction i n the interiors of the deposits (Fig. 3.1). For example, the porosity of the Battleship Rock ash-flow tuff ranges from 70% at the top and base of the unit, to 24% i n the interior of the deposit (Ross and Smith, 1961). The process of welding can produce considerably lower porosities (e.g., 3.4%; Marshall, 1935 in Ross and Smith, 1961). These changes in porosity suggest substantive changes in the dielectric properties of the deposit and, therefore, should be mappable with G P R . In this paper I investigate the potential and the limitations of using G P R to delineate and trace welded portions of pyroclastic flows. This is accomplished with numerical modeling of electromagnetic wave propagation through two subsurface K' models that derive from porosity profiles of a pyroclastic flow. Furthermore, I use a case study comprising G P R data collected at a well exposed, welded pyroclastic flow in central Oregon to test ideas derived from my model results. Two possible approaches to detecting and mapping welding are considered: i) identification of characteristic signals or textures in radargrams for unwelded to strongly welded facies; ii) tracing of strong, continuous reflections produced by rapid porosity changes bordering welded zones.  3.2 Subsurface model profiles I have used data of Freunt and Schmincke (1995) to construct model profiles of welded pyroclastic deposits. Their study of a welded basaltic ignimbrite on Gran Canada  T  1.5  2.5  3.5  0  i=  6  Q_  0)  Q  8  10  12  F i g u r e 3.1 B u l k density (p ) versus depth profiles for a basaltic ignimbrite at Playa de Tasarte, Gran Canaria (after Freunt and Schmincke, 1995): a) profile over cold ground shows unwelded base (thin line and solid symbols); b) profile over hot ground shows welding to base (heavy line and open squares). 7  produced bulk density (p ) profiles which are well constrained by abundant measurements of r  p and classic in shape. I chose two of these profiles (Fig. 3.1) for my forward modeling. r  The profiles differ only at the base: one section showed the ignimbrite to be unwelded at the base, whereas, the other section was welded to the very base of the deposit. Although the shapes of the Playa de Tasarte profiles are ideal for my modeling, the unusual composition (basalt) of the pyroclastic flow is less than ideal. The empirical relationship between 0 and K' established by Chapter 2 (Eq. 2.13, Eq. 3.1) is applicable only to intermediate to felsic volcanic rocks. Basaltic tephra have different dielectric properties. Thus, although I have used the <& profiles of the Gran Canaria deposit (calculated from p  T  data) I have treated the deposit as dacitic i n composition in the calculation of K' profiles. In short, these results are for a dacitic flow with the porosity distribution of the basaltic Gran Canaria deposit. The porosity profiles (e.g., F i g . 3.2a) were constructed from the p profiles T  by  assuming a fractional porosity (<5) of 0.05 (i.e., 5%) for the most densely welded part of the flow (p = 2.98 g/cm ). Using these p , <3> values and assuming that the solid (void-free) 3  T  r  density (p ) does not change with depth, the solid density is calculated from: s  <D=-^^ Ps  (3.3)  K n o w i n g p , each published bulk density value (Fig. 3.1) is then converted to $ by Eq. (3.3). s  Figure 3.2a shows the porosity versus depth data that are interpolated by a curve constrained to pass through the calculated data.  43  F i g u r e 3.2 Schematic demonstration of steps in conversion from continuous porosity (<&) profile to discretized profile of dielectric constant (K')\ a) Solid line denotes curve fitted to data to create a continuous profile of <& based on actual data points (squares) in Figure 3.1a (see text); b) <& profile is divided into layers of equal thickness (e.g., L = 50 cm) and solid circles show <E> values at the center of each layer interpolated from curve i n 2a; c) Layered <I> profile: each layer assigned the interpolated <E> value from 2b. d) Layered K' profile constructed by converting  to K' values with E q . (3.1).  44 I have approximated the continuous porosity profile by a series of homogeneous layers. This discretization involves dividing the profile into layers of constant thickness and assigning each layer the porosity corresponding to the depth at the center of the layer. This is illustrated in Figure 3.2 b,c where the continuous profile is divided into 27, 50 cm-thick layers. This layered porosity profile (Fig. 3.2c) is then converted into a layered K' profile using E q . (3.1). The resulting variations in K' are shown in Figure 3.2d. Figure 3.3 comprises K' profiles for layers 1 cm thick, with a 10 m thick layer of K'—l added to the base of the ignimbrite. This layer represents a uniform, homogeneous substrate.  3.3 C r i t i c a l l a y e r t h i c k n e s s ( L ) c  I have modeled actual gradational changes i n porosity (and K') of the welded pyroclastic flow by a series of homogeneous layers. It is essential that the layers are sufficiently thin to ensure that the radar wave interacts with the actual K' profile and not an artificial profile generated by the discretization process. Schematic, zero-phase Ricker source wavelets are shown in Figure 3.3c with wavelengths (A.) scaled to the axes of Figure 3.3a,b to allow comparison between the range of wavelengths used in the simulations and the thickness of discrete layers. Where a "high" frequency if), small wavelength pulse is propagated through a subsurface model with "large" layer thickness (L), each layer is resolved and a reflection is produced at each interface. For example, in a simulation through profile a (Fig. 3.1-3.3) with L=100 cm and7^200 M H z (upper left corner, F i g . 3.4), a reflection (trough-crest-trough or crest-trough-crest) forms at every interface with zones of zero amplitude between these reflections. A s X/L is increased either by a decrease i n layer  45  F i g u r e 3.3 Discretized profile of K' using 1 cm thick layers. Profiles are the K' equivalents of the p profiles in F i g . 3.1 overlying a 10 m thick layer of K'-l, and include: a) ignimbrite with unwelded base, b) ignimbrite with welded base. Inset is enlargement of top of profile showing actual discretized form of curve, and c) scaled wavelengths (A) of the 25 M H z and 200 M H z source wavelets through a material with K - 6 (X scaled to depth axes of a and b). T  47 thickness or frequency, reflections derived from the top and base of each layer begin to overlap and the layers cannot be resolved (Fig. 3.4). For a g i v e n / a n d K', there w i l l be some critical layer thickness (L ) such that further c  decreases i n L do not produce significant changes in the resulting synthetic traces. In order to model gradations in porosity with homogeneous layers, it is crucial that L<L . A n C  accepted criterion for vertical resolution is about L=A/4 (Yilmaz, 1987). Therefore L <fa'4is a minimum requirement for subsurface models. I have used 1 cm layers for the simulations presented in this paper (Fig. 3.5-3.7) which, for the range of frequencies (25 to 200 M H z ) and dielectric constant values (4<K'<7) used, falls i n the interval A/57 (f=25 M H z ; K'=7) to A/600 (f=200 M H z ; K'=4). Figure 3.4 shows that for a given frequency, amplitudes converge as L is decreased. Results for L = l cm and L=5 cm are practically identical, corroborating the notion that 1 cm layers adequately model the gradational changes i n physical properties of the pyroclastic flows modeled.  3.4 F o r w a r d M o d e l i n g Results I have modeled the propagation of electromagnetic waves through the profiles shown in Figure 3.3 using a program developed by Steven Cardimona of the University of MissouriRolla. This program is based on wave propagation matrices (Ursin, 1983) and uses the propagator calculation method of Kennett and Kerry (1979). The simulations are run for 1 cm thick layers at five frequencies: 25, 35, 50, 100 and 200 M H z . A l l layers are given a magnetic permeability o f 1 and conductivity of zero. Dacitic ignimbrites are, i n fact, resistive but have non-zero conductivity. Setting conductivity to zero removes the imaginary  48  part of the complex dielectric constant and avoids the need to gain results to compensate for signal attenuation. Figure 3.5 shows the synthetic traces resulting from the propagation of a 25 M H z wave of amplitude 1.0 through the two Playa de Tasarte profiles (a and b of F i g . 3.3).  The  traces show three distinct patterns: i) the first 115 ns exhibit abundant, relatively l o w amplitude reflections; ii) from 115 to 175 ns, the amplitude is essentially zero; iii) from 175 or 190 ns to 260 ns there are one or more strong reflections. B e l o w 260 ns, the waveform has virtually no amplitude due to the thick homogeneous layer of K'=l  added to the base of the  ignimbrite profiles. The three divisions of the synthetic trace correspond to: i) a zone of moderate increase in degree of welding (decrease in O and K'\ increase in p with depth); ii) T  a zone of dense welding with relatively constant physical and electrical properties; iii) the base of the flow preceded in profile a by a sharp decrease i n degree of welding (increase i n $ and K'\ decrease i n p with depth). The lowermost reflection (crest-trough-crest) is T  approximately centered at the basal contact of the pyroclastic flow, marked by the top of the stippled region. The results for the two profiles (a and b) are coincident except for the last division (iii). This is because the K' profiles (Fig. 3.3) are identical except at the base of the flow. The three divisions of the 25 M H z traces (Fig. 3.5) are also seen in the higher frequency simulations although the two way travel times for the division boundaries shift: somewhat. In all cases, there is a middle section (ii) of near-zero amplitude. Patterns and variations with changing frequency for the top (i) and basal (iii) sections are explored i n Figures 3.6 and 3.7  49  Amplitude -0.1  o.o  0.1  300  F i g u r e 3.5 Synthetic traces resulting from modeling propagation of 25 M H z electromagnetic wave through the two (a and b) Playa de Tasarte sections (Fig. 3.3). The traces are divided into three sections: i) zone of abundant crests and troughs; ii) zone of zero amplitude signal; iii) simple, distinct reflection(s) marking the base of the flow. The two geological sections have coincident results down to 150 ns. The profile with the unwelded base (a) shows a higher amplitude reflection at the base of the flow (-220 ns) and an extra trough (-200 ns). Depths are calculated from input K' profiles using an effective medium theory found to give accurate average velocities for X/L<1 (Chan and Knight, 1997). Differences in K' near the base of the flow result in a slight disparity between the travel time corresponding to a depth of 15 m for profile a (15a) and profile b (15 b). The top of the stippled region indicates a depth of 13.38 m, the boundary of the pyroclastic flow and the K'=7 substrate as calculated from profile a K values. The equivalent region for profile b begins 1.69 ns earlier.  50  Amplitude -0.01  0  0.01  200 MHz  150  F i g u r e 3.6 Synthetic traces (0-150 ns) resulting from modeling 25, 35, 50, 100 and 200 M H z waves passing through the two Playa de Tasarte sections (Fig. 3.3). A s degree o f welding increases, reflection crests and troughs are produced (0 to -100 ns); no reflections are apparent i n the densely welded zone (below -100 ns).  51  Amplitude  Amplitude 0.15  0.00  -0.15 150  0.00  .  J  co  (i)  CO cID  -0.15 150 C  E ,  CD  >  CD CO  7*  200  (ii)  CD  >  P  o 5  i-250 o  I  25 MHz 300  35 MHz 300 Amplitude  Amplitude -0.15  0.15  0.00  (iv)  cto CD  E  0.15  0.00  -0.15 150  0.15  200  "53 > CD  i-250 i o  100 MHz 300  300  Amplitude  Amplitude -0.15 "55"  c  0.00  0.15  (v)  CD  I 200  (  1— -*—'  200 MHz 300  (vi)  CD  ID > CD  250 -  o 5  ID  •I 210  _  CD > CD i—  200  0.15  0.00  -0.15  c5o 220 o .5 230  3  b  f  200 MHz  F i g u r e 3.7 Results (150 to 300 ns) of simulations for K' profiles of F i g . 3.3 at a variety of frequencies. In each case, the thin trace corresponds to profile a (unwelded base) and the thick trace to profile b (densely welded base). The box in panel (v) is stretched vertically in panel (vi) because of the smaller wavelength of the 200 M H z transmitted pulse.  52 respectively. Figure 3.6 shows the first 150 ns of the simulations for both profiles at frequencies of 25, 35, 50, 100 and 200 M H z . A s degree of welding increases, reflections are produced (0 to - 1 0 0 ns); i n the densely welded zone no reflections are apparent (below -100 ns). Amplitudes decrease with increasing frequency and there are shifts in the position o f peak amplitudes. In principle, each E M frequency is capable of delineating the zones of increasing welding and densest welding based on distinctive amplitude patterns. In practice, however, noise w i l l suppress all small amplitude reflections and, in particular, w i l l affect high frequency (lower amplitude) responses. Noise can be related to scattering, instrumental or cultural sources. If noise is truly random then averaging of repeated measurements w i l l improve the signal to noise ratio. Figure 3.7 shows the synthetic traces for the two Playa de Tasarte profiles from 150 to 300 ns. The results from profile b (densely welded at base) are simpler than for profile a which shows a rapid change i n degree of welding just above the base of the flow (Fig. 3.3). A t all frequencies, the synthetic trace for profile b consists of a crest, a trough and a crest with the trough centered in the 220-230 ns interval. The crest-trough-crest pattern is the shape of the propagating wave (Fig. 3.3c) and this reflection marks the actual base of the flow. The trace produced by profile a also ends with a crest-trough-crest pattern centered at about 220-230 ns (Fig. 3.7). However, the reflection has a greater amplitude which is a consequence of the larger contrast in K' of the unwelded base of the ignimbrite and the underlying layer of K'=7.  The rapid, gradational change in K' just above the base of the flow  53 results in an extra trough immediately preceding the final crest-trough-crest reflection for the 25, 35, and 50 M H z simulations (Fig. 3.7 i , i i , iii). A n enlargement of the 200 M H z panel (Fig. 3.7 vi) clearly shows a reflected pulse (trough-crest-trough) before the reflection from the basal contact of the flow. It is possible to see both reflections in the 200 M H z trace because of the small wavelength of the high frequency wave.  3.5 A p p l i c a b i l i t y to field GPR  studies  The relevance of these modeling results to the interpretation of real ground penetrating radar (GPR) data is tested below using data from a welded pyroclastic flow (Tumalo Tuff; H i l l , 1985) near Tumalo, central Oregon (Fig. 3.8). The data were collected every 0.5 m using a P u l s e E K K O 100 G P R system with 1000 V transmitter and 50 M H z antennas separated by 2.5 m. Each trace of the radargram is the result of stacking (averaging) 64 traces collected consecutively without moving the apparatus. The 89.5 m long survey (Fig. 3.8) was run parallel to a vertical wall of a quarry pit operated by the Cascade Pumice Company. This allowed comparison of outcrop observations and radar results. The top of the exposure is an erosional surface and comprises partially welded pyroclastic flow; the rock is solid, shows some alignment of pumice clasts, but lacks eutaxitic texture. The degree of welding decreases with depth and the base is unconsolidated and completely unwelded. A t the base of the flow is a 0.5 m ash layer. This is underlain by an airfall deposit (Bend Pumice) identical in mineralogy and chemical composition (rhyodacite) to the pyroclastic flow ( H i l l , 1985). The water table i n the Tumalo area is about 185 m below surface (Sceva, 1968; Caldwell and Truini, 1997) and the  54  Position (m) air and i waves  F i g u r e 3.8 R a w G P R data with minimal processing (see text). The Tumalo Tuff and Bend Pumice are co-eruptive welded pyroclastic flow and airfall deposits, respectively. Because velocity varies with depth, the time/depth relationship is not linear. However, the time axis is scaled so that a depth scale would be approximately equal to the lateral position scale (i.e., no vertical exaggeration).  55 deposits are relatively dry but there is still some moisture i n the ground. M y approach is to interpret the corresponding radargram, i n part, by comparison to the signal patterns generated for my model sections. Figure 3.8 shows the complete radargram with standard minimal processing: "dewow" to remove low frequency instrumental noise and S E C (spreading and exponential compensation) gain. The strong reflection at about 370 ns represents the base of the pyroclastic flow and the horizontal reflections from 370 down to 500 ns correspond to the underlying stratified, airfall deposit. The pyroclastic flow itself generates abundant reflections in the upper two thirds with very little response from the lower third of the flow. Numerous hyperbolic events (concave down) occur with apices i n the middle and upper portions of the deposit. These hyperbolas are caused by diffraction sources of contrasting fC compared to surrounding material. The diffraction hyperbolas are interpreted to originate from relatively large lithic or pumice clasts of unusual porosity compared to the surrounding matrix. These hyperbolas represent sharp, small scale discontinuities caused by clasts i n the pyroclastic flow. They can be "removed" by migrating or averaging the section (see Appendix II). The model simulations presented in this paper (e.g., F i g . 3.5) represent baseline responses caused solely by changes in welding. Figure 3.9 compares a spatially averaged G P R trace derived from Figure 3.8 (average of 31 traces from position 10 to 40m) to a simulation for profile b of the Playa de Tasarte ignimbrite. Spatially averaged data were used (see Appendix II) to remove the effects of erratic clasts and steeply dipping reflectors, thus exposing the desired baseline pattern. The simulation and field traces (Fig. 3.9) show similar amplitude patterns, including: i ) a n upper zone of crests and troughs; ii) a middle zone  56  F i g u r e 3.9 Comparison of model and field G P R traces: a) synthetic trace for Playa de Tasarte, profile b (welded to base); b) average of 31 G P R traces from positions 10 to 40 m of F i g . 3.8a. The stippled region marks the direct air and ground waves. A n S E C gain was applied i n b) using an attenuation of 0.5 dB/m. c) Schematic, interpretive porosity profile of pyroclastic flow consistent with G P R trace amplitude patterns of b).  57  lacking reflections, and iii) a strong reflection at the base of the flow. The similarity i n traces, however, is not the consequence of similar porosity profiles: the Playa de Tasarte flow (profile b) is densely welded at the base whereas the Oregon flow is unwelded at the base. Rather, the resemblance arises because zone (i) corresponds i n both cases to gradational changes i n porosity with depth while zone (ii) corresponds to a relatively constant porosity. These data demonstrate how regions of constant porosity and regions of changing porosity with depth can be effectively identified with G P R . The striking similarity of the model and field traces (Fig. 3 . 9 ) despite very different porosity profiles, reveals the ambiguity of the characteristic radar signals recognized i n my modeling: " A r e zones of near-zero amplitude unwelded or strongly welded regions? D o zones o f abundant crests and troughs represent increase or decrease i n welding with depth?" These ambiguities can be rectified with analysis of velocity versus depth using i n situ velocity estimates from common midpoint G P R surveys or from fitting diffraction hyperbolas. For example, i f velocity decreases/increases with depth, portions of traces that show abundant low amplitude crests and troughs can be identified as defining zones of increasing/decreasing degree of welding with depth. A velocity profile for the data in Figure 3 . 8 , has been derived from a central midpoint survey and shows that velocity increases with depth within the pyroclastic flow. Thus the upper zone, comprising abundant reflections, is interpreted as a zone of decreasing degree of welding with depth while the lower portion lacking reflections, is interpreted as a zone of relatively homogeneous, unwelded pyroclastic material. Figure 3 . 9 c is a possible relative porosity profile deduced from the radargram data. This interpretation, based on G P R data, is  58 also consistent with the welding pattern seen in outcrop.  3.6 C o n c l u s i o n Reflections of radar energy occur in response to spatial variations i n electrical properties, which in the case of welded pyroclastic flow units can be related to porosity and degree of welding. These forward modeling results indicate that moderate, gradational changes i n welding generate radar responses with low amplitude crests and troughs but no distinct, reflected wavelets. Densely welded areas with little change i n porosity produce sections of zero amplitude. A similar signal is generated by zones of unwelded flow of uniform porosity as demonstrated by the Tumalo Tuff G P R data (Fig. 3.8). A n extremely high rate of change in porosity with depth can produce a distinct reflection (Fig. 3.7 vi) but i f the sharp change occurs very near the base of the flow it can only be resolved by high frequency pulses. Ground penetrating radar (GPR) can be used to map welding in pyroclastic flows by identifying characteristic signals indicative of zones with strong changes i n the degree of welding and zones in which the degree of welding is constant. This is substantiated both by modeling results and, empirically, by case study. Simulations indicate that where porosity increases or decreases at an extremely high rate with depth then a distinct reflection could be used to delimit welded zones. The ability to map zones of welding i n volcanic stratigraphy with G P R is particularly useful because young volcanic deposits frequently lack extensive vertical exposure and can show rapid facies changes both vertically and laterally. The characterization of the degree of welding is also of interest for the evaluation of suitability for  nuclear waste disposal.  60  Chapter 4 Mapping and characterization of pyroclastic flow and fall deposits with GPR  4.1 Introduction In recent years, ground penetrating radar (GPR) has been used increasingly for imaging the shallow subsurface, however, it has rarely been applied to studies of volcanic deposits (e.g., L o w e , 1985; Russell and Stasiuk, 1997; Russell and Stasiuk 1998). Modern volcanic deposits are ideal candidates for G P R surveys because they possess properties which facilitate the probing of their entire depth; they are commonly electrically resistive and form relatively thin, surficial deposits. Furthermore, G P R can address a number of challenges posed by conventional mapping of volcanic stratigraphy. Firstly, the undissected landscapes associated with many Modern volcanic edifices offer little vertical exposure. Secondly, the stratigraphic correlation of specific units is frequently hindered by complex facies variations or by deposit distributions strongly influenced by paleotopography. In this chapter, I demonstrate the utility of G P R in the study of pyroclastic deposits. I use two sets of G P R data collected near Bend, central Oregon to illustrate the effectiveness of G P R in delineating and characterizing pyroclastic units and facies with G P R . The two case studies demonstrate strategies to discriminate between deposit types (e.g., airfall versus pyroclastic flow), and facies (e.g., welded versus unwelded pyroclastic flow), and to map deposit geometries. A l l data were collected using a P u l s e E K K O 100 G P R system with 1000 V transmitter  61 and 50 M H z and 100 M H z antennas. Two types of surveys were conducted: reflection surveys with constant antenna separation and common midpoint ( C M P ) surveys where antenna separation is increased about a central point. The first study consists of data collected at a pumice quarry which exposes a welded pyroclastic flow and an airfall of the same rhyodacite eruption. Geophysical survey results are directly compared to vertical outcrops in pit walls for the purpose of correlating distinctive radar signals to the actual pyroclastic deposits. This process of calibrating the radar signal against visible stratigraphy allows the user to determine which units are mappable with G P R . Subsequently, these units may be identified i n radargrams generated for locations where there is little or no exposure. Analysis of a series of C M P surveys at the pumice quarry illustrates a more quantitative method of mapping lateral and vertical changes in velocity; these changes in velocity reflect changes in relative porosities due to differential welding. The second field area provides limited vertical exposure of welded to unwelded andesitic pyroclastic flow and unwelded rhyodacite pyroclastic flow deposits exposed i n the steep banks of a canal. G P R signals are calibrated against stratigraphic exposures and G P R is then used to delineate deposit geometries away from the exposure.  4.2 F i e l d sites The locations of the two field sites near Bend, Oregon are shown i n Figure 4.1. The Cascade Pumice Company pits, are located 2 k m west of the town of Tumalo. The quarried material is pumice from an 0.4 M a ( H i l l and Taylor, 1990) rhyodacite airfall deposit called the Bend Pumice. The pumice is overlain by the Tumalo Tuff, a welded pyroclastic f l o w  F i g u r e 4.1 Location of two field sites near Bend, Oregon, A ) Cascade Pumice Company pits. B ) Site along the Columbia Southern Canal.  63 deposit ( H i l l , 1985; H i l l and Taylor, 1990). It is identical i n composition and mineralogy to the Bend Pumice. This flow is welded and varies from unconsolidated and unwelded to solid, welded rock; however, eutaxitic texture has not developed. A t the base of the f l o w is an ash layer, about 0.5 m thick. This ash and the immediately overlying pyroclastic f l o w are completely unwelded at the quarry. A l l lines were run parallel to pit walls to facilitate comparison of geophysical data and stratigraphy. The Southern Canal site, about 10 k m northwest of Bend is a wooded area along the Columbia Southern Canal (Fig. 4.1). Where possible, G P R lines follow jeep and horse trails; however, surveys were also run where no trail exists. T w o Quaternary pyroclastic f l o w deposits are exposed in the walls of the canal. The youngest, the Shevlin Park flow, is andesitic ( H i l l and Taylor, 1990). This deposit is variably welded and ranges from strongly welded with eutaxitic texture to unconsolidated and unwelded. Underlying the Shevlin Park flow is the Tumalo Tuff, the same pyroclastic flow as at the Cascasde Pumice pits; however it is completely unwelded at this locality.  4.3 Calibration of characteristic signals in radargrams The Cascade Pumice Company pits provide excellent vertical exposure which makes it possible to match radar signal patterns with stratigraphy. In this section, I identify characteristic signals for pyroclastic flow (Tumalo Tuff) and fall (Bend Pumice) deposits and for welded facies of the pyroclastic flow deposit. Figure 4.2 shows the survey locations at this site. Collection parameters and processing for all radargrams are listed i n Table 4.1.  64  a X a  3 3  H  •a  3  T3 o  o o 3  3  •  §  rn 7 V-Ti 0 7>  00 GO CO o o O O O TJ TJ  O  >  O  1  3  fD O e w  |— T J  c_  5' 5'  o O  1  7s  CD CO CD —  TJ  TJ T J T J T J  ^  one3"  ct> CD  Ol Ol Ol Ol Ol Ol O O O O O O O Ol O O O O O O O O O O O O O O  O O  8§  . - i . . . . . r 0 r 0 r 0 r 0 M „ M M M M M M ;„ ; ;„ O l 0 1 0 1 0 1 0 1 0 1 0 1 a  ,  o  l  n  o  l  u  ,  m  0  <  1  3. M M 111 i n b i ^ C T 0 1 CD 0  1  u  1  < 0 5  0 0  Z3.  Ol  1  V O 0  O  K O.  O Ol  o o p p p cn cn cn cn cn  1  o  !• 2o o r+  5° 3 3. a*o"  OQ "1 O  3  "§ >  3  =; 3 JS- CD  §  i  CD T3 cn N" CD  CD  3 *3 ,.  M M M M M M ro M oo oo oo oo oo oo oo oo oo 0 0 W  a> O)  4^ * v  00 0) o  W  > 00 00 00 00 00>00 > 00 CO 00 00 00 00 CO 0) O m m m m m mo O m m m m m m m O O O O O O O o O o o O O O O O 3' , , i Q) Q) Q) Q) Q) Q) 0) <<<<<<  O O O O O O T3 T3 T3 T3 T3 T3  < <  3fcT2j  (5"D  i-t  o o  I—»-  P  Cu  •5  CO o  1/1  C  CD  _ 0)  1 §  erg O  X N  cn CD  o 5 £L T5  CD o  3 CD  CD CD  3 > 3 CD  * a.  o <7 o o' 13  if  H  ft  3  CTQ  CD  Ooo  3  H  —\  °  o 3, S»3 co a. ° -• 3 3-  CQ' c  n  MP  52  CD  3 Rp 5. hH  n  4*. 4*. 4^ CD CD CO CO CO 0) CT 0)  D-  H4  B  0)  —^  eft)  Q- a  cn Ol cn £D  —^  ighi  ^ ll  00  5" a. " o 3 GO P» o OQ •a P5 o  4^ 4^ 4^ 4^ 4^ 4*. 4*. 4*.  4^  o o  CD w cn 3' CQ  CD  i-S  Cu  Figure 4.2 Aerial photograph indicating locations of surveys at the Cascade Pumice Company pits. Black arrows mark centers of common midpoint ( C M P ) surveys.  66  East  Position (m)  West air and j waves  East  Position (m)  West  F i g u r e 4.3 Radargrams from the Cascade Pumice pits. See Table 4.1 for collection and processing details. Survey locations are indicated in F i g . 4.2 and field photographs of survey sites i n F i g . 4.4. a) 50 M H z , common offset along survey line 1. b) 100 M H z common offset survey along survey line 1. Depth axis corresponds to a constant velocity of 0.08 m/ns. c) 50 M H z , common offset survey up a ramp through pyroclastic deposits (line 2). White arrows mark an above ground reflection off a pit wall. The locations of midpoints of C M P surveys 1 and 2 are indicated in a) and c) respectively. The C M P surveys were run along the survey lines of the common offset surveys.  67 Figure 4.3 a,b are radargrams from an 89.5 m long G P R survey (line 1, F i g . 4.2), run on horizontal ground (Figure 4.4a). A t this location, the erosional top of the Tumalo T u f f is welded and consists of solid rock with some alignment of pumice clasts. The degree of welding decreases with depth and the base is unconsolidated and completely unwelded. The strong reflection at about 370 ns represents the base of the pyroclastic f l o w and results from reflections off the upper and lower interfaces of a 0.5 m ash layer at the base of the flow. (Figure 4.4b). The pyroclastic flow itself generates abundant reflections and diffraction hyperbolas (concave down) with apices i n the upper two thirds with very little response from the lower third of the flow. The horizontal reflections from 370 down to 500 ns i n the 50 M H z survey (Fig. 4.3a) correspond to the underlying airfall deposit. The 100 M H z system does not penetrate to a sufficient depth to image below the Tumalo Tuff/Bend Pumice boundary. However, the higher frequency, smaller wavelength radar has greater resolution and therefore allows more closely spaced reflections to be distinguished (Fig. 4.3b). A comparison of outcrop-scale observations and radargrams leads to the development of characteristic radar signals for elements within the stratigraphic section: 1) The welded pyroclastic flow is characterized by abundant reflections and diffraction hyperbolas. 2) The less welded to unwelded zone shows essentially no response. 3) The base of the pyroclastic flow is marked by a strong, laterally continuous reflection. 4) The pyroclastic fall generates horizontal reflections parallel to its upper and lower boundaries. Figure 4.3c shows results of another G P R survey at the Cascade Pumice pits, collected along a ramp from the top of the airfall deposit up through the unwelded and then welded Tumalo T u f f (Figure 4.4c). This survey confirms the interpreted pyroclastic  68  Figure 4.4 Field photographs of G P R lines at Cascade Pumice Company pits, a) Survey line 1 (Fig. 4.2). Vertical arrow marks start of survey, b) Pit wall exposed along line 1. The degree of welding i n the Tumalo Tuff decreases with depth, c) Start of survey line 2 (Fig. 4.2) which continues to the right, up the ramp. The Bend Pumice underlies the white ash layer which marks the base of the Tumalo Tuff.  69 flow/airfall boundary reflection of Figure 4.3a because this reflector begins near surface at the start of line 2. More importantly, this radargram allows examination of signals from the airfall and the lower portion of the flow at very shallow depths where the signal energy is strongest. Near surface, the airfall deposit is marked by abundant reflections parallel to the top and base of the unit and the number of identifiable internal reflections decreases with depth (Fig. 4.3c). O f primary significance is the lack of reflections i n the lower, unwelded or poorly welded portion of the pyroclastic flow, even where the deposit is i n direct contact with the G P R antennas (positions 7 to 24 m, F i g . 4.3c). This observation confirms that the l o w amplitude response from the basal portion seen i n F i g 4.3a is caused by relatively uniform electrical properties and is not due to energy dissipation from earlier reflections or uncompensated signal attenuation. The ground surface-parallel reflection i n this l o w amplitude zone from 24 to 48 m positions, at about 150 ns two-way travel time in Figure 4.3c is interpreted to be an above ground reflection off a pit wall. This origin was corroborated by common midpoint ( C M P ) survey velocity analysis (see Velocity analysis, page 75).  Origins of characteristic signals observed The airfall and pyroclastic flow deposits at the Cascade Pumice site are characterized by different signal textures i n radargrams despite nearly identical mineralogy and chemistry ( H i l l , 1984). This indicates that the Tumalo Tuff, a pyroclastic flow, and the Bend Pumice, an airfall deposit, have distinctive physical properties which affect propagating radar waves. Possible causes for the patterns seen in the radargrams of the Cascade Pumice pits (fig. 4.3) are discussed below.  70 Pyroclastic  flow  M u c h of the character of the signals i n the pyroclastic flow can be attributed to variations in porosity. Using computer simulations of radar waves through welded pyroclastic f l o w profiles (Chapter 2), I demonstrated that the response generated by gradational changes i n porosity depends on the rate of change of porosity with depth. A moderate change in degree of welding generates abundant crests and troughs, a relatively constant porosity results in a flat, zero amplitude response and a discrete jump or extremely high rate of change i n degree of welding (abrupt at scale of radar wavelength) can produce a strong, distinct reflection. Based on these results, I interpret the characteristic signals of the pyroclastic flow in Figure 4.3a to indicate a zone with a moderate rate of change i n porosity with depth (upper two thirds of flow), overlying a zone with relatively constant porosity (lower third) with a strong reflection caused by a sudden change i n electrical properties marking the base of the flow. The degree of welding does in fact decrease with depth i n both the upper two thirds and the lower third of the deposit but the rate of change is apparently considerably lower towards the base of the flow. Another characteristic which separates the upper portion (2/3's) of the radargram from the lower third o f the deposit is that the upper portion generates abundant point diffraction hyperbolas. These are notably absent in the lower third of the flow. Considering the lack of eutaxitic texture, I interpret the diffraction sources in the upper portion to be large pumice clasts whose electrical properties contrast with the surrounding, less porous, welded matrix. In the lower, less welded portion of the flow, point diffraction sources are lacking because the matrix and pumice clasts have more similar porosities. However, the clast size and porosity distribution of the rocks have not been studied i n detail and the diffraction hyperbola pattern  71 could be related to the primary concentrations of relatively large pumice or lithic clasts. The hyperbolas are not internal structures of the deposit because migration of the data removes the tails of the hyperbolas (Fig. 4.5). While diffraction hyperbolas are seen i n other radargrams at the Cascade Pumice site, the line 1 (Fig 4.2) radargrams (Fig. 4.3a,b) have by far the densest hyperbola population. The simplest explanation is that there is a concentration of larger clasts near survey line 1. In addition to hyperbolic events, the upper portion of the pyroclastic f l o w is characterized by numerous, parallel, westward dipping reflectors which are apparent i n both the raw and migrated (Fig 4.5) versions of F i g . 4.3a,b. Such dipping reflectors are not seen i n the perpendicular survey, collected 200 m to the east (Fig. 4.3b). The origin of this geophysical anisotropy is not clear. N o corresponding bedform was evident i n outcrop but the slope at survey line 1 (Fig. 2) is not conducive to such observations (Fig 4.4a). These reflectors could be related to emplacement processes, possibly accentuated by welding. Further work exploring this geophysical anisotropy would be worthwhile as it is a potential indicator of flow direction.  Airfall The strong, continuous reflection marking the Tumalo Tuff/Bend Pumice boundary indicates a sudden change in velocity between the two deposits. Given the common mineralogy of these two deposits ( H i l l , 1984), this velocity contrast must be related to a change in grain size and sorting. The parallel reflections below the pyroclastic flow/airfall boundary reflection of Figures 4.3 and 4.5 are interpreted to be the result of internal stratification. Stratification is commonly seen in fall deposits and may be produced by  F i g u r e 4.5 Migrated version of 50 M H z , line 1 radargram (Fig. 5.4a). A constant velocity of 0.08 m/ns was assumed.  73 changes in discharge rates, temporary blocks of the conduit, changes i n lithic content, instabilities i n the column, compositional zoning, vent widening, or changes i n wind direction and speed (e.g., Cas and Wright, 1988). H i l l (1984) attributes vertical grain size variations i n the Bend Pumice to fluctuations in the diameter of the vent.  General application of characteristic signals The calibration of radar patterns against stratigraphic exposures is a key concept to extending G P R from areas with outcrop to areas which lack exposure. A t the most basic level, it is possible to map deposits and facies by tracing characteristic signals in radargrams, without understanding the physical properties responsible for the radar signals. However, to apply the concept of characteristic radar signals generally, and to be able to deduce physical or volcanological information from distinctive radar patterns, an understanding of the origins of the characteristic signals is required. The expected radar signal for a pyroclastic fall deposit is either i) a lack of reflections due to high degree of sorting, homogeneous properties and small grain size compared to the radar wavelength (e.g., Russell and Stasiuk, 1998), or ii) reflections parallel to the paleotopography caused by internal stratification (e.g., F i g . 4.3, 4.5). Diffraction hyperbolas formed by large lithics, pumice clasts or charred wood could also be observed, especially proximal to the vent where clasts are larger (e.g., Russell and Stasiuk, 1997). The signals generated by pyroclastic flow deposits are considerably more complex and variable. A t the Cascade Pumice pits alone, diffraction hyperbolas, dipping reflections, flat reflections and areas lacking reflections are all observed. If properties are homogeneous,  74 as for an unwelded, lithic poor, fine-grained deposit, then no reflections are produced. Bedforms, joints, and moderate to high rates of change of porosity with depth could generate reflections, and large clasts can form hyperbolic diffraction patterns. The correlation between hyperbola abundance and degree of welding seen i n Figure 4.3a is not expected to be a universal correlation. For instance, a completely unwelded flow could contain a large number of lithic blocks producing hyperbolic events. A l s o , i f an ignimbrite is extremely densely welded with eutaxitic texture (e.g., vitrophyre) then there would be no contrast i n the porosity of the pumice clasts and the matrix. This uniform, low porosity medium would not be a likely source of diffraction hyperbolas. A single deposit can generate radargrams with a variety of appearances due to the depth of the deposit, properties of overlying material, and variations i n cultural noise. This is illustrated by the signal texture produced by the airfall deposit (Bend Pumice) at the Cascade Pumice Company pits. The character of the Bend Pumice varies i n the two radargrams presented and is most noticeable in Figure 4.3c. It is implausible that the internal stratification of the pyroclastic fall deposit changes so drastically over such a short distance. In general, the deeper the airfall deposit, the less detailed is the stratification seen i n the radargrams. This can be attributed to loss of signal energy from earlier reflections and attenuation, and a reduction in peak frequency with depth. In Figure 4.3c, these effects are aggravated by a cultural noise source. The signal to noise ratio worsens systematically towards the right (south) end of the Figure 4.3c radargram. This is because at the north end of the survey (base of ramp), the G P R receiver is shielded from the noise source by the rock of the ramp and pit walls. A t the top of the ramp (positions >63m, F i g 4.3c), there is nothing  75 to the shield the receiver.  4.4 Velocity analysis C o m m o n midpoint ( C M P ) surveys provide data on subsurface radar velocity which are essential for converting two-way travel times into reflector depths. A further application of velocity analysis is determining spatial variations in dielectric constant which can be converted to physical properties. Therefore, there is the potential to use vertical and lateral changes i n velocity derived from C M P surveys to infer spatial variations i n relative degree of welding.  C M P surveys and velocity calculations A C M P survey involves the progressive increase i n separation of the transmitter and receiver from a central point. Arrows i n Figure 4.2 mark the C M P survey locations at the Cascade Pumice Company pits. The midpoints for two of these C M P surveys are also marked on the radargrams of Figure 4.3. Figure 4.6 gives an example of a C M P survey collected. The results of velocity analysis on the five C M P surveys are found i n Figures 4.7 to 4.9. Each reflector corresponds to a hyperbola on the C M P profile, the shape of which depends on the velocity of the radar wave through the material above the reflector. Hyperbolas are converted to ( V  rms  , time) data points (Fig. 4.7). The V  r m s  is neither the  instantaneous nor the average velocity but rather is the root mean squared velocity, defined by:  Figure 4.6 50 MHz common midpoint survey CMP1 (Fig 4.2). See Table 4.1 for details.  77  Root mean squared velocity (m/ns) 0 £  0.06  0.08  0.07  100  i 6 I-  400 500  • CMP1 XCMP2 OCMP3A • CMP3B  9+  X X  •  200 300  0.12  -+>—  •  .1  0.11  0.10  0.09  •  +  + +  X  x  o  +  o  +  o  o o  + CMP4  600  F i g u r e 4.7 Results of five C M P surveys plotted as root mean squared velocity vs. time. Velocities at time=0 represent velocities along ground surface between the antennas and do not involve reflection. Other data derive from fitting hyperbolas to reflections i n C M P radargrams (e.g., F i g . 4.6).  78  ]v\t )dt 0  {  (4.1)  o  0 Examining the results for all five C M P surveys (Fig 4.7, 4.8), two general patterns are evident: 1) within the Tumalo Tuff, V  r m s  increases with depth; 2) within the Bend Pumice,  is relatively constant. Based on these observations, for each C M P survey, I fit the V ^ -  time data for the two deposits separately. The Tumalo Tuff data are fit by least squared residuals (in velocity) with 1 or 2 st  nd  order polynomials, whereas, the Bend Pumice data are fit  with lines of constant velocity (Fig. 4.8). Velocities are re-sampled along polynomial fits, keeping the original two-way travel times (Fig. 4.8). Each re-sampled velocity is within 5% of the original  data.  I expect the overall velocity pattern to be gradational due to gradational changes i n porosity associated with welding. However, I model the system with a stack of homogeneous (constant velocity) layers; one between each pair of reflections fitted. The resampled  Vnns  data are converted into interval velocities (V ) using D i x ' s equation (Dix, int  1955): (4.2)  where V,„, is the velocity through a particular layer and V , and V  2  denote rms velocities for  the regions between the ground surface and the top and the base of the layer respectively (Fig. 4.8). Figure 4.9 plots interval velocities against height above the Tumalo Tuff/Bend Pumice boundary. Interval thicknesses are calculated from V  int  and travel time data.  79  0.11  0.10  0.06  0.08 100  200  300  400  100  200  300  200  100  400  200  0.11  •  Bend Pumice constant velocity fit (rms and interval velocities)  interval velocity — n  — 200  300  Two way travel time (ns)  400  rms velocity  Tumalo Tuff  100  300  Two way travel time (ns)  Two way travel time (ns)  0.08  300  Two way travel time (ns)  Two way travel time (ns)  0.09  100  500  400  polynomial fit to rms velocity data rms velocity derived from polynomial fit and re-sampling interval velocity derived from polynomial fit and re-sampling  F i g u r e 4.8 Plots showing velocity analysis results for five C M P surveys. Dark circles are same data as presented in F i g . 4.7. In each plot, the Tumalo T u f f data are fit to the 1 or 2 order polynomial curves. V data are re-sampled along the polynomial curve, keeping the same two-way travel times. Interval velocities are calculated for both the original (circles) and re-sampled (squares) data. The results of the latter are considerably less erratic Velocities in the Bend Pumice are averaged to give a constant V and V . st  r m s  r m s  int  nd  80  20  O  Ground surface velocity  18 CD CO CO _Q  o  16 14  CMP1 CMP2  ®  CMP3A '•  CMP3B  12  CO  10  h-  8  > O _Q CO  6  E  Bend Pumice velocity  :  CMP4  4 "(D  -1  2 0 0.06  1 - 2 4  0.08  0.1  3A—3B^  0.12  0.14  Velocity (m/ns)  Figure 4.9 Plot of velocity versus height above Tumalo Tuff/Bend Pumice boundary. Lines are interval velocity data derived from polynomial fit and re-sampling (Fig. 4.8). Open circles mark velocities of direct ground waves at surface of surveys. Grey circles indicate Bend Pumice velocities from F i g . 4.8.  81  Interpretation of velocity patterns I attribute decreases in velocity to decreases in porosity due to welding, and therefore use relative velocity patterns to determine relative changes in degree of welding. The increase i n velocity with depth through the Tumalo Tuff (Fig. 4.7-4.9) is interpreted as a decrease in degree of welding with depth as observed in pit walls. The relatively constant velocity through the unwelded Bend Pumice suggests fairly constant porosity with depth. The velocity analyses of all five C M P surveys indicate a lower velocity i n the Bend Pumice than i n the unwelded base of the overlying pyroclastic flow. If the assumption that velocity changes are primarily related to porosity differences is true, the relative velocities imply that the pyroclastic fall deposit has a lower porosity than the base of the pyroclastic flow deposit. This is an unexpected result because fall deposits are generally better sorted than flow deposits. However, the lower velocity in the Bend Pumice is confirmed by the polarity o f the reflection associated with the Tumalo Tuff/Bend Pumice boundary. In Figure 4.3a, the direct air wave is positive-negative-positive (white-black-white), whereas, the reflection at about 360 ns is negative-positive-negative. This polarity reversal indicates a lower velocity below the reflection surface (e.g., Reynolds, 1997). A comparison of the four velocity profiles suggests a decrease in degree of welding laterally from survey 1 to 2 to 4. This is i n fact confirmed by outcrop observations. Site 4 shows the least degree of welding and C M P analysis reveals a relatively constant velocity profile. The analyses of C M P surveys 3 A and 3B show substantially higher velocities than the other three surveys. This suggests much higher porosities than for other survey locations but this is not corroborated by field observations.  82 Variations i n velocity of the Bend Pumice provide clues to the origins of lateral velocity variation i n the Tumalo Tuff. The Bend Pumice is a pyroclastic fall deposit and the bulk physical properties of the unit are not expected to significantly vary laterally on the scale of this set of surveys. However, the average velocity in the Bend Pumice varies from 0.084 to 0.116 m/ns (Fig 4.10). Considering the deposition process of pyroclastic falls, the cause of this velocity diversity is likely post-depositional. One possible contributor is differences in the original thickness of Tumalo Tuff overlying the fall deposit. Increased thickness would cause greater compaction and lower porosities. The thickness of pyroclastic flows can be severely effected by changes in paleotopography, however, the Tumalo Tuff/Bend Pumice boundary is relatively flat. Therefore, it is unlikely that there were dramatic differences i n the original thickness of the Tumalo T u f f at surveys 1, 2 and 4 compared to surveys 3 A and 3B which lie between surveys 2 and 4 (Fig. 4.2). A second, more plausible origin for the lateral variation in Bend Pumice velocity is a difference i n degree of water saturation between survey lines. Water has a much higher K than air or volcanic rock. Thus small changes in water concentration and geometry of the water phase can have a large effect on velocity (Appendix 3). Water content variation may be natural but in this case some of the variation between surveys could be caused by evaporation off pit walls. The wall surfaces are completely dry and the proximity of surveys to walls and the azimuth of the walls could affect water content. There is a direct relationship between the velocity in the Bend Pumice and the velocity in the lowermost interval velocity of the Tumalo T u f f (Fig. 4.10). Given that a perfectly dry airfall deposit would be expected to have a constant lateral velocity, I conclude  0.08  0.1  0.12  0.14  Bend Pumice velocity (m/ns)  F i g u r e 4.10 Plot of velocity i n lowermost interval velocity for Tumalo T u f f (Vn) Pumice velocity ( V ) (Fig. 4.8, 4.9). Line of best fit is = 1.253V -0.019. BP  BP  vs.  84 from the correlation seen in F i g 4.10, that water equally affects the velocities of the Bend Pumice and the base of the Tumalo Tuff. Therefore a direct comparison of interval velocities from survey to survey w i l l not necessarily give accurate lateral porosity variation. There is the possibility, however, of normalizing the Tumalo Tuff data using the Bend Pumice velocities. Further research on the effect of water on velocities is required to normalize effectively.  D e p t h conversion A common application of C M P survey results is converting reflection times to depths. The lateral velocity variation at the Cascade Pumice pits means that a single travel time-depth conversion w i l l not be applicable to all radargrams at the site. For example, the travel time to the Tumalo Tuff/Bend Pumice boundary i n C M P 4 is less than for C M P 1 although the boundary is further below the ground surface in C M P 4 than C M P 1 . surveys and depth scales of lines 1 and 4 determined from V  int  Figure 4.11 compares  data.  Using interval velocity and travel time data, total thicknesses of the Tumalo T u f f are calculated (Fig. 4.9). Figure 4.12 compares the calculated depths to the Tumalo T u f f boundary to those measured on outcrops with a tape measure. The results show the C M P derived depths are accurate to within approximately 15%. Figure 4.11 also indicates that the C M P velocity analysis and conversion into interval velocities give reasonable results and that the significantly greater velocities calculated for survey line 3 are real.  85  Figure 4.11 The first 10 m of surveys 1 and 3 (Fig. 4.2) are displayed with common twoway travel time (center column). The depths scales for each survey derive from C M P analyses (Fig. 4.8, 4.9).  86  10  12  14  16  18  20  Depth measured (m)  F i g u r e 4.12 Comparison of depth to Tumalo Tuff/Bend Pumice boundary calculated from C M P velocity analysis (Fig. 4.9) and depth measured with a tape measure. Dashed lines envelope areas where calculated depths are within 10% and 20% of measured depths.  87  4.5 Columbia Southern Canal: mapping deposit geometries A t the Columbia Southern Canal, we move away from the control of a quarry site. I used steep stream bank exposures (Fig. 4.13) to calibrate the radargrams with volcanic stratigraphy. I include data from this site primarily to demonstrate the use of G P R in mapping deposit geometries away from exposures. In addition, I apply ideas developed in the Cascade Pumice case study to elucidate information of volcanological interest from the radargrams. Figure 4.14 indicates the positions of the surveys i n map view. Initial surveys employed 50 M H z antennas with a relatively large step size (1 m) to cover the area quickly. These radargrams are presented without topographic correction i n Figure 4.15. U s i n g these data, I chose a portion of the area covered by 50 M H z surveys, to examine i n further detail withlOO M H z antennas. The 100 M H z radargrams are presented i n Figures 4.16 and 4.17 with topographic correction assuming a constant velocity of 0.1 m/ns based on C M P survey analyses. To aid the visualization of deposit geometries four views with the sections fenced together are also included (Fig 4.18).  Deposit boundaries The reflection corresponding to the Shevlin Park/Tumalo interface is identified by comparison of radargrams to field exposures. A t point O (Fig. 4.16), the contact is 8.7 m below the G P R survey and at point L (Fig. 4.17), the top of the Tumalo T u f f is at a depth of 10.5 m with 0.6 m of reworked material, including vesicular basalt cobbles, at the base of the Shevlin Park flow. Using these two calibration points, the contact is traced to other  88  F i g u r e 4.13 V i e w of Columbia Southern Canal site, looking upstream. Most exposed rock is the Shevlin Park flow. Outcrops of the Tumalo Tuff (TT) are visible in foreground. The Black line marks survey H - L (Fig. 4.14).  91 Cu  Cu  cn  n  H  ro o —• re Mr* e 82. c 4-  O  o P  a ^+ oo  OQ  3* i n 0  s  a r.  Co  Cu  O C  N  Two-way travel time (ns)  Two-way travel time (ns)  1-1 Cu , ft) CTQ  r-f  5'  H  S3  O" cn  cn  ao  3  Cu.  4: Cu  G  cn  5'  a  EL  CD  o c  cr Cn  re  rs  —  Cu  g  c 13  o o EL c« o  o n  BO  I< g S" M  ro  Cu  03 p3  0  o  —1  1 -a C u  o  53  B9 tn  B  c u  ••  ©  B  3  cn  o 13 —  ro  I  o ro cn P ro  Depth (m)  X  . o a" ro *< U >  2  5  cn  E  3 n  •a ^ 0  he]  ro O ro .3 ft O  6 ro  Depth (m)  92 cr  p o  a. o o  o p  in »n  <: c  ~ p  3 »  P  Two-way travel time (ns)  Two-way travel time (ns)  M  3 o §•§ H  EL  c o  N >-i  gp  P  fare  n  c  » l 5'  Depth (m)  P  & o  °a CD  a  CI  3  o  §  a r O  p  3  «*  f CD r-t-  <" p  CD  & 3 ^  P C u CD •  o  tJ  o  8 s  3 ft fa O i  CD  P  & s  o o to p  ~  T3  o 3  5 o  ^£ O  O  p  p  CD ro  Depth (m)  93  F i g u r e 4.18 Four views of 100 M H z radargrams fenced together. R a w data ( A G C gain) on left; interpreted stratigraphy on right. See F i g . 4.14 for orientations of surveys and Figs. 4.16 and 4.17 for dimensions.  94 radargrams. In northwest trending surveys (radargrams H-I, J-K, N - M , and O-P, F i g . 4.16), the base of the andesitic flow (Shevlin Park) dips at about 15° N W ; whereas, i n most surveys trending approximately northeast, (radargrams E-F, H-I, F-P, P-G, F i g . 4.17), the base of the flow is practically horizontal. This geometry likely delimits the edge of a channeled flow, the result of paleotopography and scouring of the loose Tumalo T u f f during emplacement of the Shevlin Park flow. The Shevlin Park/Tumalo Tuff boundary is frequently characterized by apices of hyperbolic events (eg., surveys H-L, H-P, F i g 4.17) which are likely generated by a concentration of non-juvenile clasts at the base of the younger, Shevlin Park flow. The base of the Tumalo T u f f is not exposed i n outcrops along these G P R surveys. O n the other side of the canal, across from survey point C (Fig. 4.14), the Bend Pumice appears to underlie the Tumalo Tuff (Fig. 4.19 a); however, I was not able to get close enough to positively identify the deposit. The 13 m long, strong, continuous reflection at 450-500 ns i n radargram M - N (Fig. 4.16, 4.18) probably marks the base of the flow. This reflector is also recognized i n surveys H - L a n d F-P (Figs. 4.17, 4.18), and to a lesser extent surveys F-O, and O-P (Fig. 4.18). The reflector is not pervasive because its depth is close to the limits of penetration of the system. In all sections, regardless of the apparent dip of the basal contact of the Shevlin Park flow, the base of the Tumalo Tuff is horizontal or slightly dipping to the north-east.  Internal structures of pyroclastic flows There is a definite and continuous reflection within the Shevlin Park f l o w that approximately parallels the flow base with some thickening of the lower portion as the  96 channel deepens. This horizon is interpreted to be the boundary between two phases of the andesitic pyroclastic flow. In the upstream (southwest) portion of the 50 M H z survey, near point B (Fig. 4.14) this reflection coincides with a cobbly layer in a densely welded portion of the andesitic flow (Fig 4.19 b). The two phases were emplaced in relatively close succession because they form a single cooling unit. The presence of two phases is also evident is the unwelded/poorly welded flow seen i n Figure 4.19 a. The contact between the phases is not always so apparent, particularly in densely welded sections. Base-parallel reflections are present in both phases of the andesitic flow and are particularly abundant in the upper phase (e.g., H-I, J-K, N-M, and H-L, Figs. 4.16, 4.17). These may be caused by emplacement or welding processes and could be related to bedforms, rheomorphism, or clast geometries and orientations. A particularly strong and continuous reflection is found 50 ns below the interpreted boundary of the two Shevlin Park phases (Fig 4.15, 4.18). Diffraction hyperbolas, mostly i n the upper phase, cross this fabric (e.g., surveys H-I, J-K, F i g 4.16). Radargram F-P shows a particularly high density of hyperbolic events. A s with the hyperbolic events at the Cascade Pumice Company site, these are interpreted to be formed by diffraction at relatively large clasts within the flow. Migration of this radargram (Fig. 4.20) removes these hyperbolas and clarifies unit boundaries. The signal amplitude decreases with depth within the Shevlin Park flow (excluding the phase boundary reflection) despite there being sufficient energy to produce a relatively strong reflection at the base of the flow. This pattern indicates that the lower phase is more homogeneous than the later phase. The general lack of reflections produced by the Tumalo T u f f at the Southern Canal  97  0 5 10  e  15  CL  a 20 25 30  10 m  Shevlin Park (b)  15  10  Shevlin Park (a)  15  Q.  CD  Q  -20  Tumalo Tuff 25  Bend Pumice (?)  •30  10 m Figure 4.20 a) Radargram of migrated data for survey F-P (100 MHz) using a constant velocity of 0.1 m/ns. b) Interpreted stratigraphy for a).  98  site is consistent with a massive, homogeneous deposit. A l l exposures near the surveys show no evidence of welding in the rhyodacite flow. The low amplitude response of the Tumalo T u f f is therefore interpreted to result from a lack of welding (i.e., constant, high porosity) through the entire depth of the deposit. The signal is similar to the lower, unwelded portion of the Tumalo T u f f at the Cascade Pumice pits (Fig 4.3).  4.6 Summary and conclusions The results of two case studies demonstrate G P R to be capable of mapping unit boundaries, distinguishing between airfall and pyroclastic flow deposits and recognizing welded facies of a pyroclastic flow. A t the Cascade Pumice quarry, it was possible to compare geophysical signals to vertical outcrops. I used data from this site to recognize the signals produced by different deposits and facies and understand the origin of these characteristic signals. A t the Cascade Pumice pits, the pyroclastic fall deposit is identified by continuous, parallel reflectors created by internal stratification. A t both the Cascade Pumice and Southern Canal sites, the unwelded Tumalo Tuff, rhyodacite pyroclastic f l o w produces an essentially zero amplitude response due to its homogeneous character compared to the scale of the radar wavelength. The welded material at the Cascade Pumice pits produces a much more complex signal with abundant reflections and hyperbolic events. Hyperbolic events are created by the contrast i n porosity between relatively large clasts and the welded matrix. In one radargram (Fig. 4.3a) there are dipping reflectors, possibly indicative of f l o w direction but their origin is not clear. C M P surveys were used to evaluate velocity variation with depth. A series of C M P  99  surveys, collected at the Cascade Pumice pits, demonstrate that G P R data can be applied to interpreting and quantifying spatial porosity variations. However, the amount of moisture i n the ground has a strong effect on velocity. I advocate the interpretation of these data i n terms of relative porosities from which welding patterns can be identified. A combination of velocity profiles and the recognition of characteristic signals for different welding facies, together provide confident geological interpretations of welding patterns. In addition to the recognition of characteristic signals, criteria used in traditional mapping can also be applied to the identification of deposit types with G P R . For instance, an airfall deposit may be recognized by its high degree of sorting, high porosity, mantling of paleotopography and the reduction of thickness and grain size away from the source. Theoretically, all of this information can be deduced from G P R surveys. Crude estimates of grain size and degree of sorting information could be gained by running a series of G P R surveys at different frequencies and looking at the density of diffraction hyberbolas as a function of radar wavelength. G P R w i l l never replace traditional mapping but rather it should be used as a supplementary tool providing data where conventional methods are not adequate due to lack of vertical exposure.  100  Chapter 5 Conclusion  This thesis examines the relationship between porosity and dielectric constant of volcanic rocks through laboratory measurements, and explores the utility of G P R i n mapping and characterizing young pyroclastic deposits. In particular, simulations and field studies demonstrate how G P R data can be used to both image, and quantify, porosity variations i n pyroclastic deposits. It is evident that G P R is an effective tool for mapping paleotopography, defining major unit boundaries and internal structures, and tracing facies variations (e.g., welding). Furthermore, the nature of unexposed units may be identified based on their geometry and characteristic radar signals. There are numerous applications of G P R i n mapping volcanic stratigraphy including the estimation of eruption volumes, airfall isopach maps, correlation of units, and mapping of complicated geometries and facies changes. O n a more applied level, G P R also offers an alternative to drilling at potential pumice quarry sites to assess the extent of pumice deposits and the thickness and character of overburden. M y research demonstrates the utility of G P R to basic volcanology; however, there remain a number of areas requiring further research. A model relating porosity to dielectric constant of intermediate-felsic rocks was developed in Chapter 2. The trend formed by these data is remarkably tight and coherent especially considering the samples derive from five deposits and two volcanoes; however, no such relationship was found for basalt samples. Perhaps the higher and more variable concentration of F e - T i oxide minerals i n basalts causes the data dispersion. The effect of the modes and the geometries of these minerals also needs  101 to be investigated experimentally. A l s o , there is a single conspicuous outlier i n the intermediate-felsic sample suite (sample M B 1 ) with significantly higher dielectric constant than predicted by the trend formed by other samples i n O-K' or p-K' space. What makes this sample distinct is that it has the lowest porosity of the intermediate-felsic set of rocks and the pore space is dominated by cracks in the glass rather than vesicles. Further work is required to evaluate whether pore geometry and ambient moisture are responsible for the outlier and to determine whether this phenomenon is important at G P R survey frequencies. A n additional factor, not addressed by experiment (Chapter 2), is the effect of partially saturating the pore space with water. Due to the contrasting electrical properties of water compared to air and volcanic rocks at G P R frequencies, this is an important consideration. In fact, water appears to affect G P R velocities at the Cascade Pumice pits near Bend, Oregon, where the water table is more than 150 m below the depths of the surveys (Chapter 4). Therefore, there are few locations where it can be assumed that deposits are absolutely dry and velocity data can be converted to porosity data using the empirical relation developed i n Chapter 2. Laboratory studies treating intermediate-felsic volcanic rocks as ternary systems consisting of rock, air and water are a logical extension of the work of Chapter 2. However, even with an understanding of the dielectric properties of variable saturated volcanic rocks, evaluating absolute porosity information of G P R data would still not be a trivial task because water saturation levels must be assumed. For this reason, I advocate interpretations based on relative rather than absolute velocity (porosity) patterns. A n interesting and poorly understood feature of the field G P R data collected is a set of strong, parallel, dipping reflectors observed only i n one radargram (line 1). O f particular  102 interest is the genetic origin of these signals. The structure may indicate primary f l o w direction and thus G P R would be an important volcanological tool, especially considering the bedform is not readily visible in outcrops. Surveys in other areas would determine whether the dipping reflectors are a common feature in pyroclastic flows. Comparison of survey results i n well-exposed areas with flow direction indicators such as imbricated clasts would aid i n discerning whether the dipping reflectors are in fact related to flow direction.  103  References  Adams, R. J., Perger, W . F., Rose, W . I. and Kostinski, A . , 1996. Measurements o f the complex dielectric constant o f volcanic ash from 4 to 19 G H z . J. Geophys. Res., 1: 8175-8185.  Bondarenko, A . T., 1971. 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Geophys., Tulsa, O K , United States.  Appendix I Measurement of density and porosity in volcanic rocks  115 Several properties unique to volcanic rocks obviate the standard procedures for measuring density and porosity; volcanic rocks tend to have lower permeabilities than sedimentary rocks of the same porosity (Klug and Cashman, 1996), can be less dense than water, can contain anomalously large pores, and can have porosities as high as 98% (Robertson and Peck, 1974). The purpose of this appendix is to describe the problems associated with established techniques and give a rationale for the methods used i n the present project. Note that although not repeatedly stated, all papers referenced i n this appendix deal with volcanic rocks.  Density Density is mass per unit volume and an obvious approach to determining bulk density (p ), defined as the density of the whole rock including pores, is to measure mass (actually r  weight) and volume directly:  w t  P =^~  (Al.l)  T  T  Determination of sample weight (wt  rocyt  ) is straightforward and uses dry samples. There are  three techniques commonly employed to determine bulk volume CV ): T  i) measure volume of liquid displaced by the sample (Carey and Sigurdsson, 1987; Gardner etal., 1991), ii) calculate sample volume from the weight of liquid displaced by the sample (e.g., water or mercury pycnometer) (Manger, 1965; Gardner et al., 1996), and iii) calculate volume from dimensions o f carefully machines samples (Robertson and Peck, 1974; Witham and Sparks, 1986; Walker, 1989; Gardner et a l , 1996).  116 The first two methods require modification for porous rocks because fluids can enter pores thereby causing low estimates of sample volume. In the past, this problem has been addressed by blocking pores with a thin film of silicon-based aerosol spray (Houghton and W i l s o n , 1989) or with wax (Carey and Sigurdsson, 1987) or wrapping the sample with a sheet o f wax, plastic or latex (Gardner et al., 1991; Sahagian et al., 1989; Houghton and W i l s o n , 1989). N o such modifications are required for the technique o f machining samples into regular geometries.  Furthermore, samples are not contaminated (e.g., by sealants) and,  thus the sample can be used subsequently for other measurements (e.g., porosity and dielectric constant). The apparatus for direct measurement o f mass and volume are simple and such techniques are commonly used in studies where the porosity o f samples need not be measured directly and highly accurate estimates of density are not required. A n example is the calculation of pumice or lithic clast densities for Plinean column height determination (e.g., Carey and Sigurdsson, 1987). Densities are commonly determined using hydrostatic methods. Samples are dried and weighed in air (yvt  rock  ,„ „,>) then weighed suspended i n water (wt „ rocki  water)-  Density ( p ) is  calculated from: „  p =—  "water  rock in air  rock in air  ——  rock in water  , .  1  ~  N  (Al.2)  Depending on the porosity and permeability of the sample, equation (A2) w i l l give bulk density(p ), solid density ( p the density of the solid, void-free portion) or an apparent T  s  density i n between these two end-values. The standard method to determine the bulk density of porous samples is to saturate the sample with water and quickly weigh it in air after wiping  117 off excess water from the surface (Robertson and Peck, 1974; Cas and Wright, 1988). In this way, the weight o f the water in the pores can be determined and bulk density (p ) calculated r  using the following formula: o  Pr = —  dry rock in air  x  "water  —  wt, , . .-N,  dry rock in air  "  saturated rock in water  —  ( -) A1  saturated rock in air  3  Volcanic rocks, however commonly have vesicles which are too large for water to be retained when the saturated sample is removed from water (Robertson and Peck, 1974; Witham and Sparks, 1986). In order to measure the bulk density of such rocks by hydrostatic methods, the samples must be rendered impermeable to water. This can be done using some of the techniques listed above in the discussion of direct volume measurements. In the case of wrapping the sample with a sheet of wax, the formula for bulk density is (after Houghton and Wilson, 1989): P  _  PT  ,  "water  " dry rock in air  ~  x  wt.  , . .  dry rock in air  " wax sheet in water  T  -  f \'I  T  I  A1  A\  -T)  wax-coated rock in water  A n additional problem, unique to volcanic rocks, is that samples which are less dense than water w i l l float giving the false result that the samples have the same bulk density as water. A less dense fluid could be used, but the simplest solution is to ballast the sample with a metal weight and the negative effective weight of the sample i n water calculated by subtracting the ballast weight (Houghton and Wilson, 1989).  Porosity Porosity (<&) can also be determined by hydrostatic methods. The relevant formula  118 (after Cas and Wright, 1988) is: if.  saturated rock in air  <P =  saturated rock in air  dry rock in air  • , . ,  _  (A1.5)  N  saturated rock in water  However, the porosity given by equation (A1.5) can only be considered a minimum porosity as it does not include unconnected pores. Although the amount of water absorbed by a sample can be maximized by placing the sample i n a container, from which air is evacuated and then flooded with de-aerated water which is left under pressure for days (Cas and Wright, 1988; Robertson and Peck, 1974), one cannot be sure that all pores are filled. Hydrostatic or other methods which involve contact with water may not be feasible for rocks which contain zeolites. Soeder et al. (1991) found that porosity measurements of zeolitic tuffs from Y u c c a Mountain were as much as 8% higher when water was used rather than other liquids or gas. This is not an insurmountable problem for hydrostatic bulk density measurements where the sample can be coated with wax or some other material which is impermeable to water. However, such coating techniques are not feasible for hydrostatic porosity measurements because the weight of the water in the pores is required to calculate porosity. Porosity can also be expressed as a function of bulk and solid (void-free) densities ( p and p respectively): s  Q^PSZPT  (  A  1  6  )  Techniques to measure p have already been discussed and the only additional information T  required is p . Porosity is sometimes calculated from the relation i n equation (A1.6) using s  chemistry and proportions of glass and minerals to estimate solid density (Sahagian et al.,  T  119 1989; Gardner et al., 1991; 1996). Determining the solid density o f a porous rock by hydrostatic methods requires completely filling all pores with liquid. Even where possible to do so, it is difficult to ensure complete filling of all pores. In some experiments involving crushed rock it is assumed that the rock from which the powder was made was not porous and the porosity of the crushed rock and air mixture is determined by substituting solid density (in equation A 6 ) with the bulk density o f the original rock (eg., Campbell and Ulrichs, 1969). K l u g and Cashman (1996) and Russell and Stasiuk (1997) calculated the solid volume of vesicular samples with a helium pycnometer (or helium porosimeter), a technique based on the ideal gas law. Although rocks should be at least as permeable to helium gas as to water, the question as to whether or not there are unconnected pores which are not filled with gas remains. The apparatus has been extensively used on sedimentary material but sedimentary rocks generally have higher and more regular permeabilities than lavas of the same porosity ( K l u g and Cashman, 1996). Another approach to determining solid density (which i n turn is used to calculate porosity) is to measure the density of a representative powdered sample. The assumption is that i f the sample is crushed fine enough, all pores w i l l be accessible to fluid. A helium pycnometer is an ideal apparatus to measure the volume of the powdered material ( K . Cashman, personal communication). In determining the porosity of welded lapilli tuff, Manger (1965) used a water pycnometer and de-aerated the crushed rock by boiling the water-powder mixture in the pycnometer flask for ten minutes. Note that the term pycnometer is used i n this appendix both for the helium pycnometer and water pycnometer,  120 the apparatus and theory behind these two techniques are different. The water (or other liquid) pycnometer is a specially designed flask used to measure the weight o f fluid displaced by the sample. The helium (or other gas) pycnometer is based on the ideal gas law P V = n R T ; n (number of moles of gas), R (gas constant) and T (temperature) are kept constant while the volume of the chamber which contains the sample and helium is changed. Using the difference in pressure for the different chamber volumes, the volume o f the sample is calculated. Direct measurements of porosity are sometimes done visually or by digitally processing images of thin sections (e.g., Dorn, 1995) or hand sample surfaces (Kanamori et al., 1970), assuming that the porosity in three dimensions is the same as i n two dimensions. Walker (1989) took this approach one step further and measured porosity i n one dimension: he drew lines across sawn surfaces and found the porosity by dividing the length o f line crossing vesicles over the total length of the line. N o comparison between the results o f these quick methods and more sophisticated ones was located for volcanic rocks.  Selection of procedures for present study The laboratory study (Chapter 2) includes the measurements of bulk density and porosity for cylindrical disks of volcanic rocks. Porosity and density measurement methods were chosen such that: 1) they were applicable to sample set with large range i n porosity; 2) they were applicable to samples with individual pores as large as 5 m m i n diameter; and 3) they did not contaminate samples thus affecting subsequent capacitance measurements. Due to the high porosity o f many samples, determining bulk volumes by fluid displacement is not  121 feasible because fluids can enter pores thereby causing low estimates o f sample volume. Materials such as silicon spray and wax cannot be used to plug pores due to sample contamination. Hydrostatic methods to determine porosity or bulk density are not practical because many samples have vesicles which are too large for the pores to remain saturated when the sample is removed from water. The methods implemented i n this study (Chapter 2) fit the three requirements listed above and do not involve water or sealing vesicles. The procedures entail: 1) weighing samples, 2) measuring disk diameters and heights to calculate bulk volume, and 3) using a He-pycnometer to determine solid volumes of disks and powders from the same handsamples. Further details on the methodologies are listed in Chapter 2 (pages 15-16).  122  Appendix II Scale of heterogeneity of pyroclastic deposits and applicability of gradational porosity profile models  123 Chapter 3 simulates the interactions between a radar wave and subsurface models of K', that contain gradations in porosity. A logical question is whether the actual scale of heterogeneity of pyroclastic deposits can be adequately modeled by a gradational subsurface model. Profiles such as those used i n this study may be practical for fine-grained, lithic-poor deposits, but in many cases deposits contain variations in physical properties that cannot realistically be modeled as gradational. For example, a deposit may show an overall gradational porosity profile at one scale (e.g., F i g . 3.2a), yet, on a finer scale (e.g., decimeters) the presence of large pumice blocks or lithic clasts could impart sharp (nongradational) deviations from the background $ and K' profiles. Such clasts could generate reflections of strong amplitude or act as point diffractors and obscure the general patterns seen i n the simulations (e.g., F i g . 3.5). W e illustrate the problem presented by sharp, small-scale discontinuities and a method to overcome it with the G P R survey of a welded pyroclastic flow (Fig. 3.8). A s discussed i n the main text, the middle and upper portions of the deposit generate abundant reflections and numerous hyperbolic events (concave down). The diffraction hyperbolas are interpreted to originate from relatively large lithic or pumice clasts. In order to apply the results of our model simulations, we must remove the "noise" from erratic clasts to uncover the baseline response caused solely by changes in welding. Diffraction hyperbolas can be collapsed into their point sources by migration (Fig. A2.1a). Migration removes the tails of diffraction hyperbolas but there remain diffraction sources as well as westward dipping reflections of unknown origin (Fig A2.1a). To eliminate the entire effect of erratic clasts and steeply dipping reflectors, we have averaged groups of 10 adjacent traces of the Figure 8  124  Figure A2.1 Three processed versions of the radargram of F i g . 3.8. A l l radargrams are gained with an S E C gain with start value of 10, gain max of 120 and attenuation of 3 d B / m . A gain factor of 0.25 was applied to migrated data to compensate for higher amplitudes produced by the migration process, a) Migrated data assuming constant velocity o f 0.09 m/ns. Note the removal of hyperbolic events seen in F i g . 3.8. b) Each trace is the mean of 10 adjacent traces in Fig.3.8. c) Each trace is the average of 10 adjacent traces of the migrated radargram (a).  125 radargram (Fig. A2.1b). Each trace shown i n Figure A2.1b is, therefore, the spatial average of traces over a lateral distance of five meters. A s long as the clasts are distributed randomly and not concentrated in thin horizons, this process removes the "noise" imparted by clasts as well as steeply dipping reflectors. The resulting radargram (Fig. A2.1b) shows subhorizontal reflections i n the middle and upper portions of the pyroclastic flow with very little response below this until the base of the flow. Migration followed by averaging of groups of 10 adjacent traces (Fig. A2.1c) gives a similar result to simple averaging (A2.1b). Short reflections in Figure A l a such as the six meter-long reflection centered at (40 m , 260 ns) could have formed by smearing of a clast response and, therefore, may not actually represent the desired baseline pattern. However, many of the upper zone reflections are continuous over a distance of more than 10 m and are too long to be the result of smearing individual clast reflections by 5m spatial averaging. Note that this averaging technique w i l l not uncover a baseline pattern as desired in the presence of sub-horizontal bedforms.  Appendix III Effect of water on radar velocities  127 The velocity data of Chapter 4 derive from C M P surveys collected i n the BendTumalo area, Central Oregon. This region is dry and the water table is about 185 m below surface (Sceva, 1968; Caldwell and Truini, 1997) which is many times the depths imaged by the G P R surveys. Most precipitation occurs in the winter and these surveys were conducted in July and August during the hot, dry, summer season. However, even i n August there remains residual moisture in the ground. While the pit walls are dry, material dug out less than a meter into the wall is darker-coloured indicating the presence moisture. There are no visible drops or pockets of water filling spaces suggesting there are thin films of water adsorbed on the surfaces. Because the deposits are highly porous, there is a relatively large surface area to bulk volume ratio and a significant amount of water could be retained by the rocks. A comparison of calculated interval velocities (Chapter 4) with laboratory measurements on dry volcanic rocks (Chapter 2) indicates that the velocities observed at the Cascade Pumice site are too slow to correspond to completely dry deposits. For a low-loss medium, velocity (V) is related to dielectric constant by:  c  V =  (A3.1)  (e.g., Davis and Annan, 1989). Using E q . (A3.1), the velocity profiles from surveys C M P 1 and C M P 3 B (Fig.4.8) are converted to a K' profile (Fig. A3.1). F r o m experiments on rocks which were dry except for air-derived moisture (Chapter 2), the K' of intermediate to felsic volcanic rocks is related to porosity by: (K')  096  = $ + 6.51(1-$)  (A3.2)  128  K 0  Q.  CD  Q  Figure A3.1  10  15  20  water (K'=80)  Dielectric constant vs. depth data for two C M P surveys at Cascade Pumice  Company pits (Chapter 4). The shaded region indicates the range of values predicted for dry, intermediate to felsic volcanic rocks according to laboratory experiments (Eq. 2.13, Chapter 2).  129 where O is the fractional porosity of the rock ( 0 < ® < 1). The maximum dielectric constant possible according to E q . (A3.2) is 6.97 which corresponds to no pore space (0=0). Figure A3.1 shows dielectric constant values substantially exceeding this maximum. This discrepancy is attributed to the presence of water (K'  water  = 80) which has a much higher  dielectric constant than air (1) or intermediate volcanic rocks (-6.5). Volcanic deposits are found i n all climates from wet tropics, dry deserts to permafrost regions. In interpreting velocity analysis results one must be aware of the potential effect of water on velocity patterns. For example, in Chapter 4,1 attributed increases i n velocity with depth to increasing porosity (decreasing degree of welding) towards the base of the Tumalo Tuff, a nearly dry, welded pyroclastic flow. This interpreted relative porosity profile is i n agreement with outcrop-scale observations. However, i f water saturations are very high, then a decrease i n degree of welding with depth would be expected to cause a decrease i n velocity rather than increase as observed in these data. This is because air i n the pores is replaced by water and V  w a t e r  «V  r o c k  <V  a i r  (e.g.,  K\ ^>K' ^K'^. a  m  Because moisture content tends to increase with depth i n the vadose zone, radar C M P results typically show a decrease i n velocity with depth (Reynolds, 1997). The fact that I see an increase i n velocity within the Tumalo T u f f (Chapter 4) despite the presence of moisture substantiates the notion that porosity increases with depth and that water saturations are not very high at this site. I advocate the use of relative velocity (porosity) rather than absolute velocities i n the interpretation of volcanic sections and the identification of deposit type or facies within a deposit. Extra caution is required when interpreting profiles where velocity decreases with depth, as this could simply be a moisture content effect. E v e n basic  130  knowledge such as precipitation patterns and approximate water table depths in the area may be sufficient to discriminate between hydrological and volcanological origins of relative velocity profiles.  

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