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Surface lithogeochemistry of the Relincho porphyry copper-molybdenum deposit, Atacama region, Chile Greenlaw, Lauren 2014

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Surface	  Lithogeochemistry	  of	  the	  Relincho	  Porphyry	  Copper-­‐Molybdenum	  Deposit,	  Atacama	  Region,	  Chile	  	  	  by	  	  Lauren	  Greenlaw	  	  B.Sc.	  Eng.,	  Queen’s	  University	  at	  Kingston,	  2004	  	  	  A	  THESIS	  SUBMITTED	  IN	  PARTIAL	  FULFILLMENT	  OF	  	  THE	  REQUIREMENTS	  FOR	  THE	  DEGREE	  OF	  	  MASTER	  OF	  SCIENCE	  	  in	  	  THE	  COLLEGE	  OF	  GRADUATE	  AND	  POSTDOCTORAL	  STUDIES	  	  (Geological	  Sciences)	  	  THE	  UNIVERSITY	  OF	  BRITISH	  COLUMBIA	  (Vancouver)	  	  October	  2014 	  	  ©Lauren	  Greenlaw	  2014	  	  	  	   ii	  	   Abstract	  Porphyry	  copper	  deposits	  (PCDs)	  typically	  have	  large	  alteration	  haloes	  that	  extend	  several	  kilometers	  from	  economic	  mineralization	  providing	  a	  geochemical	  footprint	  potentially	  an	  order	  of	  magnitude	  larger	  than	  the	  deposit.	  The	  Paleocene	  (64±2	  Ma)	  Los	  Morteros	  batholith	  comprises	  four	  granodiorite	  units	  and	  hosts	  four	  syn-­‐mineralization	  porphyry	  units.	  These	  units	  are	  interpreted	  as	  the	  product	  of	  four	  magmatic	  differentiation	  cycles	  with	  three	  magmatic	  recharges.	  Alteration	  assemblages	  observed	  within	  the	  system	  include	  potassic,	  propylitic	  and	  phyllic,	  with	  intensities	  varying	  between	  weak	  to	  moderate	  for	  potassic	  and	  phyllic	  alteration,	  and	  weak	  to	  strong	  for	  propylitic.	  	  	   Lithogeochemical	  characterization	  and	  quantification	  of	  alteration	  is	  an	  important	  exploration	  tool	  that	  has	  the	  potential	  to	  lead	  to	  exploration	  success.	  Two	  hundred	  and	  ninety-­‐six	  surface	  rock	  samples	  were	  collected	  in	  a	  grid	  covering	  65	  km2	  centered	  over	  the	  Relincho	  PCD	  in	  the	  Atacama	  region,	  Chile	  to	  assess	  the	  suitability	  of	  surface	  rock	  lithogeochemistry	  as	  a	  medium	  for	  lithological	  and	  alteration	  characterization.	  Aqua	  regia	  ICP-­‐MS,	  pressed	  pellet	  XRF,	  and	  fusion-­‐ICP	  results,	  combined	  with	  shortwave	  infrared	  (SWIR)	  spectra,	  alkali	  feldspar	  staining,	  petrography	  and	  field	  observations	  were	  used	  to	  classify	  lithological	  units	  and	  identify	  and	  quantify	  alteration.	  	  	   Data	  evaluation	  and	  modeling	  is	  completed	  through	  the	  use	  of	  exploratory	  data	  analysis,	  simple	  mass	  balances	  and	  molar	  element	  ratios	  (MER)	  complimented	  by	  hand	  and	  thin-­‐section	  observations	  and	  SWIR	  analyses.	  Gain-­‐loss	  variations	  are	  consistent	  with	  spatial	  element	  distributions	  indicating:	  the	  addition	  of	  SiO2,	  K2O,	  Ag,	  Cu	  and	  Mo	  and	  loss	  of	  CaO,	  Na2O	  during	  potassic	  alteration;	  and	  the	  addition	  of	  Na2O	  and	  loss	  of	  SiO2	  during	  propyltic	  alteration.	  Wavelengths	  of	  SWIR	  chlorite	  features	  indicate	  that	  chlorite	  is	  more	  Fe-­‐rich	  proximal	  to	  mineralization	  and	  Mg-­‐rich	  distally.	  	  Simple	  and	  molar	  element	  ratios	  are	  used	  as	  proxies	  for	  the	  potassic,	  propylitic	  and	  phyllic	  alteration	  assemblages.	  From	  these	  ratios,	  alteration	  indices	  are	  calculated.	  The	  potassic	  index	  (K2O/Th)	  and	  propylitic-­‐phyllic	  index	  ((18Ca	  +	  14Na	  +	  25K)/(2Si	  +	  7Al	  +	  4(Fe	  +	  Mg))	  identify	  and	  quantify	  potassic,	  phyllic	  and	  propylitic	  alteration.	  Alteration	  	   iii	  thresholds	  derived	  from	  probability	  plots	  indicate	  that	  these	  indices	  would	  identify	  the	  Relincho	  deposit	  as	  a	  potential	  PCD	  exploration	  target	  at	  a	  sample	  spacing	  of	  up	  to	  2000	  m.	  	  	   	  	   iv	  Preface	  This	  thesis	  was	  sponsored	  by	  Teck	  Resources	  Limited	  and	  its	  subsidiaries	  (Teck).	  The	  author	  and	  Mike	  Richard,	  formerly	  of	  Teck,	  identified	  the	  research	  scope	  and	  project	  area.	  The	  author,	  her	  supervisor	  (Dr.	  Craig	  Hart)	  and	  Paul	  Johnston	  of	  Teck	  Resources	  Limited	  identified	  the	  research	  objectives	  and	  strategy	  of	  the	  research.	  The	  thesis	  committee	  consists	  of	  Dr.	  Craig	  Hart,	  Dr.	  Peter	  Winterburn	  and	  Dr.	  James	  Scoates.	  Additional	  contributors	  include	  Dr.	  Paul	  Johnston,	  Dr.	  Liz	  Stock,	  Dr.	  Claire	  Chamberlain,	  Dr.	  Iain	  Dalrymple	  and	  Stephen	  Cook,	  all	  of	  Teck;	  Brian	  McNulty	  of	  MDRU;	  and	  Dr.	  Cliff	  Stanley	  of	  Acadia.	  This	  thesis	  is	  based	  on	  the	  analytical	  results	  of	  fieldwork	  performed	  by	  the	  author.	  All	  sample	  descriptions	  and	  data	  interrogation	  results	  are	  the	  responsibility	  of	  the	  author	  unless	  otherwise	  noted.	  Samples	  were	  selected	  by	  the	  author	  for	  thin	  sections,	  alkali-­‐feldspar	  staining,	  scanning	  electron	  microscope	  analysis,	  microprobe	  analysis,	  short-­‐wave	  infrared	  analysis,	  and	  mineral	  quantification	  by	  Rietveld	  refinement,	  x-­‐ray	  diffraction	  analysis,	  quantitative	  evaluation	  of	  minerals	  by	  scanning	  electron	  microscopy	  analysis	  and	  mineral	  liberation	  analysis.	  	   	  	   v	  Table	  of	  Contents	  	  ABSTRACT	  ..................................................................................................................................	  ii	  PREFACE	  ....................................................................................................................................	  iv	  TABLE	  OF	  CONTENTS	  ..............................................................................................................	  v	  LIST	  OF	  TABLES	  .......................................................................................................................	  ix	  LIST	  OF	  FIGURES	  ......................................................................................................................	  x	  LIST	  OF	  TERMS	  AND	  ACRONYMS	  ......................................................................................	  xii	  ACKNOWLEDGEMENTS	  ......................................................................................................	  xiii	  DEDICATION	  ...........................................................................................................................	  xiv	  	  CHAPTER	  1:	  INTRODUCTION:	  PROJECT	  SETTING	  AND	  OBJECTIVES	  ......	  …………...1	  1.1	   Introduction	  ..............................................................................................................................................	  1	  1.2	   Project	  Setting	  ..........................................................................................................................................	  5	  1.3	   Historical	  Exploration	  ...........................................................................................................................	  7	  1.4	   Regional	  Geology	  ...................................................................................................................................	  10	  1.5	   Research	  Objectives	  and	  Approach	  ................................................................................................	  12	  1.6	   Thesis	  Overview	  ....................................................................................................................................	  13	  	  CHAPTER	  2:	  METHODOLOGY	  AND	  DATA	  QUALITY	  ASSESSMENT	  ........................	  14	  2.1	   Introduction	  ............................................................................................................................................	  14	  2.2	   Field	  Methods	  .........................................................................................................................................	  14	  2.3	   Hand	  Samples:	  Shortwave	  Infrared,	  Petrography	  and	  Quantitative	  Mineralogy	  ...........	  17	  2.4	   Laboratory	  Methods	  .............................................................................................................................	  18	  2.5	   Data	  Quality	  Assessment	  ....................................................................................................................	  19	  2.6	   Data	  Analysis	  Methodologies	  ............................................................................................................	  23	  2.6.1	   Probability	  Plots	  ...........................................................................................................................................	  23	  2.6.2	   Tukey	  Plots	  ......................................................................................................................................................	  23	  2.6.3	   Ranked	  Variable	  Plots	  ................................................................................................................................	  24	  2.6.4	   Bivariate	  Analysis	  .........................................................................................................................................	  24	  	  2.7	   Elemental	  Gains	  and	  Losses	  ..............................................................................................................	  24	  2.8	   Molar	  Element	  Ratios	  ..........................................................................................................................	  26	  	  	   vi	  CHAPTER	  3:	  CHARACTERIZATION	  AND	  EVOLUTION	  OF	  THE	  LITHOLOGICAL	  UNITS	  IN	  A	  CALC-­‐ALKALIC	  PORPHYRY:	  A	  CASE	  STUDY	  OF	  THE	  RELINCHO	  CU-­‐MO	  PORPHYRY,	  ATACAMA,	  CHILE	  ...................................................................................................................	  30	  3.1	   Introduction	  ............................................................................................................................................	  30	  3.2	   Geological	  Setting	  ..................................................................................................................................	  31	  3.3	   Lithological	  Units	  ..................................................................................................................................	  31	  3.3.1	   Andesite	  ............................................................................................................................................................	  33	  3.3.2	   Granodiorite	  Units	  .......................................................................................................................................	  33	  3.3.3	   Porphyry	  Units	  ...............................................................................................................................................	  37	  3.3.4	   Hydrothermal	  Breccia	  ................................................................................................................................	  39	  3.3.5	   Post-­‐Mineralization	  Dikes	  ........................................................................................................................	  39	  	  3.4	   Alteration	  .................................................................................................................................................	  42	  3.4.1	   Potassic	  Alteration	  .......................................................................................................................................	  44	  3.4.2	   Propylitic	  Alteration	  ...................................................................................................................................	  44	  3.4.3	   Phyllic	  Alteration	  ..........................................................................................................................................	  44	  	  3.5	   Geochemistry	  of	  Lithological	  Units	  .................................................................................................................	  45	  3.5.1	   Granodiorite	  Units	  .......................................................................................................................................	  45	  3.5.2	   Porphyry	  Units	  ...............................................................................................................................................	  55	  3.5.3	   Magma	  Differentiation	  and	  Fertility	  Plots	  ........................................................................................	  55	  	  3.6	   Elemental	  Variability	  Attributed	  to	  Alteration	  .......................................................................................	  59	  3.6.1	   Spatial	  Element	  Variability	  ......................................................................................................................	  61	  3.6.2	   Bivariate	  Analyses	  ........................................................................................................................................	  70	  3.6.3	   Probability	  Plots	  ...........................................................................................................................................	  70	  3.6.4	   Elemental	  Gains	  and	  Losses	  .....................................................................................................................	  76	  	  3.7	   Interpretations	  of	  Magmatic	  Evolution,	  Fertility	  and	  Alteration	  Fluids	  .................................	  79	  3.7.1	   Magmatic	  Evolution	  and	  Fertility	  .........................................................................................................	  79	  3.7.2	   Alteration	  Fluids	  ...........................................................................................................................................	  81	  	  3.8	   Exploration	  Implications	  of	  Interpretations	  .............................................................................................	  85	  	  CHAPTER	  4:	  RECOGNIZING	  HYDROTHERMAL	  ALTERATION	  IN	  A	  FELSIC	  ENVIRONMENT:	  A	  CASE	  STUDY	  OF	  THE	  RELINCHO	  CU-­‐MO	  PORPHYRY,	  ATACAMA,	  CHILE	  ................................................................................................................................................................................................	  87	  4.1	   Introduction	  ............................................................................................................................................	  87	  4.2	   Local	  Geology	  and	  Alteration	  ............................................................................................................	  88	  4.2.1	   Lithological	  Units	  .........................................................................................................................................	  88	  4.2.2	   Alteration	  .........................................................................................................................................................	  88	  	  4.3	   Results	  	  ..............................................................................................................................................................................	  89	  	   vii	  4.3.1	   Staining,	  Field	  and	  Petrographic	  Observations	  ..............................................................................	  89	  4.3.2	   Shortwave	  Infrared	  Results	  .....................................................................................................................	  90	  4.3.3	   Molar	  Element	  Ratios	  .................................................................................................................................	  90	  	  4.4	   Interpretation	  of	  Alteration	  Processes	  .........................................................................................................	  96	  4.4.1	   Identification	  of	  Alteration	  Using	  Shortwave	  Infrared	  ................................................................	  96	  4.4.2	   Identification	  of	  Alteration	  Using	  Lithogeochemistry	  ..................................................................	  98	  4.4.3	   Alteration	  Indices	  and	  Quantification	  ...............................................................................................	  100	  4.4.4	   Comments	  on	  Sample	  Spacing	  for	  Regional	  Exploration	  .........................................................	  101	  4.4.5	   Using	  Alteration	  Indices	  as	  a	  Vector	  to	  Mineralization	  .............................................................	  103	  4.4.6	   Comments	  on	  Alteration	  Indices	  ..........................................................................................................	  106	  	  4.5	   Exploration	  Implications	  of	  Interpretations	  ...........................................................................................	  106	  	  CHAPTER	  5:	  CONCLUSIONS	  AND	  IMPLICATIONS	  FOR	  EXPLORATION	  .....................	  108	  5.1	   Summary	  of	  Research	  Results	  ..........................................................................................................................	  108	  5.1.1	   Rock	  Fertility	  Assessment	  .......................................................................................................................	  108	  5.1.2	   Alteration	  Characterization	  ..................................................................................................................	  108	  5.1.3	   Quantifying	  Alteration	  Intensity	  on	  a	  Regional	  Scale	  ................................................................	  109	  	  5.2	   Comparison	  of	  Methodologies	  .........................................................................................................................	  109	  5.2.1	   Gain-­‐Loss	  versus	  Molar	  Element	  Ratios	  ...........................................................................................	  109	  5.2.2	   Spatial	  Elemental	  Variability	  versus	  Molar	  Element	  Ratios	  ...................................................	  110	  5.2.3	   Simple	  Element	  Ratios	  versus	  Molar	  Element	  Ratios	  .................................................................	  110	  	  5.3	   Research	  Shortcomings	  ...................................................................................................................	  111	  5.4	   Research	  Implications	  for	  Exploration	  ......................................................................................................	  111	  5.5	   Recommended	  Exploration	  Methodologies	  for	  Porphyry	  Cu-­‐Mo	  Exploration	  .............	  112	  5.6	   Suggested	  Future	  Work	  .......................................................................................................................................	  114	  	  REFERENCES	  	  .........................................................................................................................	  115	  	  APPENDIX	  A:	  QUANTITATIVE	  MINERALOGY:	  A	  COMPARISON	  OF	  MINERAL	  LIBERATION,	  RIETVELD	  REFINEMENT,	  X-­‐RAY	  DIFFRACTION,	  QUANTITATIVE	  EVALUATION	  OF	  MINERALS	  BY	  SCANNING	  ELECTRON	  MICROSCOPY	  AND	  WHOLE	  ROCK	  ANALYSES	  	  .................................................................................................................	  122	  	   See	  Supplementary	  Materials	  and	  Errata	  Collection	  	  APPENDIX	  B:	  SAMPLE	  DESCRIPTIONS	  AND	  PHOTOGRAPHS	  ................................	  235	  See	  Supplementary	  Materials	  and	  Errata	  Collection	  	  APPENDIX	  C:	  THIN	  SECTION	  PHOTOGRAPHS	  ............................................................	  525	  See	  Supplementary	  Materials	  and	  Errata	  Collection	  	  	   viii	  	  APPENDIX	  D:	  TERRASPEC	  RESULTS	  .............................................................................................................	  582	  See	  Supplementary	  Materials	  and	  Errata	  Collection	  	  APPENDIX	  E:	  ANALYTICAL	  RESULTS	  ............................................................................	  594	  See	  Supplementary	  Materials	  and	  Errata	  Collection	  	  APPENDIX	  F:	  DATA	  QUALITY	  ASSESSMENT	  ...............................................................	  607	  See	  Supplementary	  Materials	  and	  Errata	  Collection	  	  APPENDIX	  G:	  ELECTRON	  MICROPROBE	  RESULTS	  ....................................................	  712	  See	  Supplementary	  Materials	  and	  Errata	  Collection	  	  APPENDIX	  H:	  SCANNING	  ELECTRON	  MICROSCOPE	  RESULTS	  ...............................	  722	  See	  Supplementary	  Materials	  and	  Errata	  Collection	  	   	  	   	  	   ix	  List	  of	  Tables	  Table	  1:	  Summary	  of	  certified	  values	  for	  reference	  materials	  ............................................	  22	  Table	  2:	  Summary	  of	  granodiorite	  unit	  properties	  ..................................................................	  35	  Table	  3:	  Summary	  of	  porphyry	  unit	  properties	  ...........................................................................................	  38	  Table	  4:	  Summary	  of	  Tukey	  diagram	  observations	  ..................................................................................	  47	  Table	  5:	  Summary	  statistics	  for	  selected	  major	  oxides,	  heavy	  rare	  earth	  elements	  and	  trace	  metals	  for	  the	  porphyry	  and	  granodiorite	  units	  	  ............................................	  52	  Table	  6:	  Alteration	  gains	  and	  losses	  at	  Relincho	  and	  porphyry	  deposits	  with	  similar	  characteristics	  ..........................................................................................................................................................	  78	  Table	  7:	  Summary	  of	  alteration	  reactions	  between	  primary	  and	  alteration	  minerals	  at	  the	  Relincho	  deposit	  ................................................................................................................................	  84	  Table	  8:	  Summary	  of	  effective	  tools	  for	  the	  characterization	  of	  lithological	  units	  and	  alteration	  assemblages	  ............................................................................................................................	  113	  	  	  	   	  	   x	  List	  of	  Figures	  Figure	  1:	  Global	  map	  of	  porphyry	  belts	  ............................................................................................	  2	  Figure	  2:	  Schematic	  cross-­‐section	  of	  porphyry	  formation	  in	  a	  subduction	  zone	  ...........	  3	  Figure	  3:	  Location	  of	  the	  Relincho	  deposit	  .....................................................................................	  6	  Figure	  4:	  Sample	  location	  map	  .............................................................................................................	  8	  Figure	  5:	  Photographs	  of	  the	  project	  area	  .......................................................................................	  9	  Figure	  6:	  Regional	  geology	  of	  the	  project	  area	  ...........................................................................	  11	  Figure	  7:	  Sample	  survey	  .......................................................................................................................	  16	  Figure	  8:	  Plots	  of	  mean	  versus	  mean	  percentage	  difference	  for	  selected	  analyte	  duplicates	  .................................................................................................................................	  21	  Figure	  9:	  Compositional	  matrix	  reduced	  to	  x	  and	  y	  vectors	  representative	  of	  the	  null	  vector	  for	  customized	  Pearce	  element	  ratio	  plot	  ....................................................	  29	  Figure	  10:	  Schematic	  geological	  map	  of	  the	  project	  area	  ......................................................	  32	  Figure	  11:	  Photographs	  of	  the	  Cerrillos	  Formation	  andesite	  ..............................................	  34	  Figure	  12:	  Summary	  of	  the	  compositions	  of	  the	  granodiorite	  and	  porphyry	  units	  ...	  36	  Figure	  13:	  Pictures	  of	  the	  contact	  breccia	  ....................................................................................	  40	  Figure	  14:	  Pictures	  of	  post	  mineralization	  dykes	  .....................................................................	  41	  Figure	  15:	  Spatial	  extent	  of	  weak	  alteration,	  with	  example	  photographs	  of	  alteration	  assemblages	  ............................................................................................................................	  43	  Figure	  16:	  Tukey	  diagrams	  by	  lithology	  .......................................................................................	  48	  Figure	  17:	  Major	  oxide	  and	  immobile	  element	  diagrams	  for	  granodiorite	  units	  ........	  53	  Figure	  18:	  Radiometric	  diagrams	  distinguishing	  GRD1a	  from	  the	  GRD2,	  GRD3	  and	  GRD1b	  units	  ............................................................................................................................	  54	  Figure	  19:	  Major	  oxide	  and	  immobile	  element	  diagrams	  for	  the	  porphyry	  units	  ......	  56	  Figure	  20:	  N-­‐MORB	  normalized	  rare	  earth	  element	  diagrams	  of	  the	  granodiorite	  and	  porphyry	  units	  ......................................................................................................................	  	  57	  Figure	  21:	  Magmatic	  evolution	  diagrams	  for	  the	  porphyry	  and	  granodiorite	  units	  ..	  58	  Figure	  22:	  Hornblende	  fractionation	  diagrams	  .........................................................................	  60	  Figure	  23:	  Spatial	  Elemental	  Variability	  Plots	  ............................................................................	  62	  Figure	  24:	  Bivariate	  Plots	  by	  Lithology	  .........................................................................................	  71	  	   xi	  Figure	  25:	  Population	  breaks	  based	  on	  probability	  plots	  .....................................................	  74	  Figure	  26:	  Spatial	  expression	  of	  alteration	  populations	  with	  alteration	  footprints	  ..	  75	  Figure	  27:	  Elemental	  variability	  due	  to	  hydrothermal	  alteration	  .....................................	  77	  Figure	  28:	  Shortwave	  infrared	  patterns	  indicative	  of	  potassic	  alteration	  .....................	  83	  Figure	  29:	  Shortwave	  infrared	  patterns	  indicative	  of	  propylitic	  alteration	  ..................	  91	  Figure	  30:	  General	  element	  ratio	  plots	  of	  feldspar-­‐space	  .....................................................	  93	  Figure	  31:	  Conserved	  element	  plots	  by	  differentiation	  cycle	  ..............................................	  94	  Figure	  32:	  Pearce	  element	  ratio	  plots	  with	  spatial	  context	  ..................................................	  95	  Figure	  33:	  Alteration	  indices	  and	  quantification	  .....................................................................	  102	  Figure	  34:	  Alteration	  indices	  at	  1000	  m	  and	  2000	  m	  sample	  spacing	  ...........................	  104	  Figure	  35:	  Transects	  of	  alteration	  indices	  and	  Cu	  concentrations	  over	  the	  porphyry	  corridor	  ...................................................................................................................................	  105	  	  	   	  	   xii	  List	  of	  Terms	  and	  Acronyms	  Term	  or	  Acronym	   Definition	  2bt	   Secondary	  biotite	  2CNK	   (2Ca	  +	  Na	  +	  K)	  apa	   Apatite	  bt	   Biotite	  Customized	  PER	  Refers	  to	  the	  customized	  Pearce	  element	  ratio	  diagram:	  (2Si+7Al+4(Fe+Mg))/Ti	  vs	  (18Ca+14Na+25K)/Ti	  Propylitic-­‐phyllic	  index	  	  Refers	  to	  the	  customized	  molar	  ratio:	  [(18Ca+14Na+25K)/(2Si+7Al+4(Fe+Mg))]	  Feldspar	  space	  PER	  Refers	  to	  the	  Pearce	  elemen	  ratio	  diagram:	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  Al/Ti	  vs	  (2Ca+Na+K)/Ti	  GER	   General	  element	  ratio	  hem	   Hematite	  HFSE	   High	  field	  strength	  element	  HREE	   Heavy	  rare	  earth	  element	  ICP-­‐MS	   Inductively	  coupled	  plasma	  mass	  spectrometry	  ICP-­‐OES	   Inductively	  coupled	  plasma	  optical	  emission	  spectrometry	  LREE	   Light	  rare	  earth	  elements	  mag	   Magnetite	  MER	   Molar	  element	  ratio	  	  MLA	   Mineral	  liberation	  analysis	  PCD	   Porphyry	  copper	  deposits	  PER	   Pearce	  element	  ratio	  Porphyry	  corridor	  Outline	  of	  the	  multiple	  mineralized	  porphry	  centers,	  as	  seen	  in	  Figure	  4	  Potassic	  index	   K2O/Th	  Project	  area	   The	  area	  covered	  by	  the	  sampling	  grid	  PTS	   Polished	  thin	  section	  QEMSCAN	  Quantitative	  evaluation	  of	  minerals	  by	  scanning	  electron	  microscopy	  REE	   Rare	  earth	  elements	  Relincho	  Property	   The	  area	  depicted	  by	  the	  property	  boundary	  in	  Figure	  2	  	  RR	   Rietveld	  refinement	  SWIR	   Shortwave	  infrared,	  in	  this	  case	  Terraspec	  XRD	   X-­‐ray	  Diffraction	  XRF	   X-­‐ray	  fluorescence	  	  	  	   xiii	  Acknowledgements	  The	  author	  would	  like	  to	  thank	  her	  supervisor,	  Dr.	  Craig	  Hart,	  and	  her	  committee	  members	  Dr.	  Peter	  Winterburn	  and	  Dr.	  James	  Scoates	  for	  their	  contributions.	  The	  author	  would	  like	  to	  thank	  Teck	  Resources	  Limited	  for	  the	  opportunity	  to	  complete	  this	  thesis	  and	  for	  their	  financial	  support.	  Thank	  you	  to	  Acme	  Analytical	  Laboratories	  for	  their	  high	  quality	  analyses.	  The	  author	  would	  also	  like	  to	  thank	  Dr.	  Cliff	  Stanley,	  Dr.	  Liz	  Stock,	  Stephen	  Cook,	  Dr.	  Paul	  Johnston,	  Dr.	  Iain	  Dalrymple,	  Dr.	  Claire	  Chamberlain	  and	  Luis	  Nuehe	  for	  their	  considerable	  contributions.	  Thanks	  to	  all	  the	  others	  who	  helped	  out	  including,	  but	  not	  limited	  to	  Tansy	  O’Connor	  Parsons,	  Pim	  VanGeffen,	  Murray	  Allen,	  Thomas	  Bissig	  and	  Farhad	  Bouzari.	  And	  a	  special	  thanks	  to	  my	  peeps:	  Brian	  McNulty,	  Irene	  Del	  Real,	  Esther	  Bordet,	  Erin	  Looby,	  Erin	  O’Brien,	  Jeannie-­‐kins,	  Victoria	  Sterritt,	  Gayle	  Febbo,	  Alfonso	  Luis	  Rodriguez	  Madrid,	  Sara	  Jenkins	  Newkirk,	  Aimée	  Campeau,	  Rupa	  Mukherjee,	  Madeleine	  Corriveau,	  Stanislawa	  Hickey,	  Allison	  Brand,	  Tucker,	  Lindsay	  McCleneghan,	  Jess	  Norris,	  my	  SnB	  group,	  Birgit	  Woods,	  Karen	  Furlong,	  Sarah	  Gordon	  and	  of	  course	  my	  family:	  the	  Greenlaws,	  Watsons,	  Wickmans	  and	  Takaichis	  for	  weddings,	  fondues,	  jam	  sessions,	  dog-­‐sitting,	  wine	  nights,	  roadtrips	  and	  overall	  awesomeness	  over	  the	  past	  few	  years.	  Of	  course-­‐	  a	  big	  thanks	  to	  my	  partner	  in	  crime,	  Mike	  Takaichi,	  for	  being	  so	  supportive	  in	  every	  way:	  I	  could	  not	  have	  done	  this	  without	  you.	  	  	   	  	   xiv	              To Michael: I love you dearly.  I am so excited to be sharing my life with you.    	  	  	  	  	  Chapter	  1:	  Introduction:	  Project	  Setting	  and	  Objectives	  	  1.1 Introduction	  	   Porphyry	  copper	  deposits	  (PCDs)	  account	  for	  nearly	  three-­‐quarters	  of	  the	  world’s	  supply	  of	  Cu	  (Sillitoe	  2010).	  Generally	  large-­‐tonnage	  and	  low-­‐grade,	  they	  are	  associated	  with	  convergent	  plate	  margins,	  frequently	  occurring	  in	  orogen-­‐parallel	  belts	  with	  other	  PCDs	  of	  a	  similar	  age	  (Seedorff	  2005;	  Singer	  et	  al.	  2005;	  Corbett	  2009;	  Sillitoe	  2010)	  (Figure	  1).	  Chile	  is	  well	  endowed	  with	  PCDs	  with	  a	  total	  resource,	  including	  production,	  of	  approximately	  360	  million	  tonnes	  of	  fine	  Cu	  identified	  in	  over	  50	  PCDs	  and	  prospects	  (Camus	  &	  Dilles	  2001).	  As	  the	  world’s	  largest	  Cu	  producer,	  Chile	  annually	  exports	  approximately	  33	  %	  of	  the	  global	  supply	  of	  refined	  Cu,	  or	  5.43	  million	  tonnes	  (Mt),	  amounting	  to	  approximately	  US$	  42.7	  billion,	  or	  13.2	  %	  of	  Chile’s	  gross	  domestic	  product,	  representing	  53	  %	  of	  the	  nation’s	  exports	  in	  2011	  (BN	  Americas	  2013).	  	  	   A	  porphyry	  deposit	  comprises	  porphyritic	  textured	  intrusive	  bodies,	  in	  which	  phenocrysts,	  generally	  feldspar	  and	  quartz,	  occur	  in	  a	  fine-­‐grained	  to	  aphanitic	  groundmass.	  These	  intrusive	  bodies	  are	  associated	  spatially,	  temporally	  and	  genetically	  with	  mineralization	  (Seedorff	  et	  al.	  2005).	  Porphyry	  deposits	  form	  when	  increasing	  temperature	  due	  to	  the	  earth’s	  thermal	  gradient	  dehydrates	  a	  subducting	  oceanic	  plate,	  releasing	  the	  less	  dense	  volatiles	  into	  the	  overlying	  mantle	  and	  causing	  partial	  melting	  (Richards	  2003).	  The	  resulting	  hydrous	  basalt	  undergoes	  melting,	  assimilation,	  storage	  and	  homogenization	  (MASH)	  to	  produce	  a	  more	  silica-­‐rich	  magma	  through	  magma	  differentiation	  by	  crystal	  fractionation	  (Hildreth	  &	  Moorbath	  1988).	  Heat	  produced	  by	  the	  MASH	  zone	  causes	  further	  melting	  and	  assimilation	  of	  the	  surrounding	  rocks,	  facilitating	  the	  enrichment	  of	  volatiles	  and	  incompatible	  elements.	  Convection	  of	  this	  hydrated,	  evolving	  magma	  to	  hotter	  regions	  results	  in	  further	  partial	  melting	  of	  surrounding	  rocks	  (Figure	  2;	  Richards	  2003).	  The	  less	  dense,	  more	  evolved	  magmas	  rise	  with	  the	  volatiles	  to	  upper	  crustal	  levels	  where	  fractionation	  and	  interaction	  with	  crustal	  material	  occurs	  (Richards	  2003).	  	  1BoliviaArgentinaPacic OceanPeruSantiago •CarmenEl SalvadorLa EscondidaSierra GordaMarte-LoboRefugioLoicaAndacolloDomeykoEl TenienteRio Blanco -   Los BroncesLos Pellambres -  El PachonGalenosaAntucoya SpenceChuquicamataQuebrada BlancaCollahuasiEl AbraCerro ColoradoRelincho0 km 300200100N22oE26oE30oE34oE18oEUpper Oligocene - MioceneUpper Miocene - PlioceneCretaceousPaleocene - Lower EoceneUpper EoceneFigure 3.1a:  Location of global porphyry belts, location data from USGS.  Figure 3.1b:  Porphyry deposits in northern Chile.  There are ve porphyry belts of distinct age sub parallel to the Andes, younging to the east.  The Relincho deposit is located at the southern extent of the Paleocene-Lower Eocene belt. Modied from Vry et al., 2010C PMOECPMOE150oW 30oW60oW90oW120oW 150oE30oE 60oE 90oE 120oE0o30oN60oN90oN30oS60oS0o Figure 1: Approximate location of global porphyry deposit belts, strongly coincident with subduction zones.  The black box over Chile indicates the outline of the map in Figure 2.  (Modified from Singer et al., 2005).21400 oC1000oC600oC1000 oCC600oCAsthenosphereSea LevelOceanic Mantle LithosphereMantle LithosphereOceanic Crust0 km100 km200 kmVolcanic ArcPartial Melting of hydrated mantleMASH ZoneDehydration of Oceanic CrustBatholith Figure 2: A schematic cross section of subduction arc showing dehydration of the subducting slab transfering volatiles causing partial melting of asthenosphere above. Magma pools at the astheno-sphere-lithosphere boundary causing further partial melting in the mash zone. Magmas rise to form batholiths. (Modified from Winter, J.D., 2001)3	  	  	  	   Magma	  pooled	  in	  the	  upper	  crust	  continues	  to	  fractionate	  and	  can	  produce	  a	  bubbly,	  buoyant	  mixture	  of	  evolved	  magma	  and	  contained	  volatiles.	  Following	  existing	  large,	  crustal-­‐scale	  structures,	  this	  magma	  intrudes	  upward	  as	  dykes	  and	  plugs,	  some	  of	  which	  have	  a	  porphyritic	  texture.	  The	  volatile	  and	  incompatible	  element	  enriched	  fluids	  are	  released	  as	  they	  rise	  and	  cool	  typically	  at	  a	  depth	  of	  approximately	  5-­‐10	  km	  (Richards	  2011b).	  These	  fluids	  flow	  along	  fractures	  and	  permeate	  the	  host	  rock,	  depositing	  hypogene	  mineralization	  in	  the	  form	  of	  disseminated	  sulphides	  and	  stockwork	  veins	  (and	  native	  Au	  in	  the	  case	  of	  Au	  porphyry	  deposits),	  causing	  hydrothermal	  alteration	  of	  the	  host	  rock	  (Sillitoe	  2010;	  Seedorff	  et	  al.	  2005).	  	  	   The	  dominant	  metal	  assemblage	  categorizes	  a	  porphyry	  deposits	  e.g.	  porphyry	  Cu-­‐Mo	  deposit.	  The	  subducting	  slab	  is	  theorized	  to	  be	  the	  source	  of	  fluid-­‐mobile	  elements	  including	  U,	  Pb,	  As,	  Sb,	  K,	  Sr,	  Ca,	  Cl,	  B,	  S	  and	  possibly	  Cu,	  Au	  and	  platinum	  group	  elements	  (PGEs)	  (Richards	  2011b).	  Relatively	  high	  oxidation	  states,	  fO2	  ≥	  FMQ	  +2,	  in	  the	  mantle	  above	  the	  descending	  slab	  force	  S	  to	  be	  incorporated	  in	  the	  magma	  as	  sulphate,	  allowing	  sulphide-­‐compatible	  elements	  (e.g.	  Cu	  and	  Mo)	  to	  be	  incorporated	  into	  the	  evolving	  melts	  and	  not	  bound	  as	  sulphides	  and	  potentially	  lost	  by	  sulphide	  segregation	  and	  settling	  (Richards	  2011b,	  Pirajno	  2009).	  Though	  it	  is	  unclear	  whether	  the	  source	  of	  Mo	  is	  mantle,	  crustal	  or	  both,	  it	  is	  in	  the	  MASH	  zone	  that	  Mo	  is	  likely	  introduced	  from	  the	  assimilation	  of	  Mo-­‐bearing	  crustal	  material	  (Richards	  2011a).	  	  	   Hydrothermal	  alteration	  forms	  mineralogically	  distinct	  zones	  around	  the	  porphyritic	  intrusions	  that	  are	  controlled	  by	  increasing	  acidity	  and	  sulfidation	  state,	  and	  decreasing	  temperature	  of	  the	  hydrothermal	  fluids	  (Sillitoe	  2010).	  The	  general	  spatial	  progression	  is	  from	  potassic,	  proximal	  to	  mineralization,	  through	  phyllic	  to	  propylitic	  alteration	  (Lowell	  &	  Guilbert	  1970).	  Alteration	  related	  mineralogical	  changes	  are	  seen	  up	  to	  several	  kilometres	  away	  from	  porphyry	  related	  mineralization	  (Sillitoe	  2010).	  Alteration	  significantly	  modifies	  the	  geochemistry	  of	  the	  host	  rocks	  making	  PCDs	  highly	  prospective	  targets	  for	  geochemical	  exploration	  (Sillitoe	  1995).	  Ultimately	  the	  alteration	  ceases	  to	  have	  obvious,	  visible	  mineralogical	  effects	  and	  becomes	  cryptic,	  though	  is	  commonly	  still	  geochemically	  identifiable	  (e.g.	  Urqueta	  et	  al.	  2009;	  Djouka-­‐Fonkwe	  et	  al.	  2012).	  4	  	  	  	   Lithogeochemistry	  of	  drill	  core	  material	  is	  recognized	  as	  a	  useful	  tool	  for	  exploration,	  fertility	  studies	  and	  characterization	  of	  various	  deposit	  types	  including	  PCDs	  worldwide	  (Stanley	  &	  Lang	  1995;	  Ulrich	  &	  Heinrich	  2002;	  Shen	  et	  al.	  2009;	  Loucks	  2014,etc.).	  Exploration	  using	  surface	  rock	  lithogeochemistry	  for	  PCDs,	  however,	  is	  not	  well	  documented	  in	  literature.	  The	  principal	  exception	  being	  the	  work	  by	  Urqueta	  et	  al.,	  2009	  on	  the	  Collahuasi	  region	  of	  Chile,	  which	  successfully	  identified	  potassic,	  sericitic	  and	  argillic	  alteration	  through	  the	  use	  of	  molar	  element	  ratios	  (MERs)	  and	  relatively	  quantified	  alteration	  using	  indices	  derived	  from	  MERs.	  	  	   The	  Relincho	  PCD	  in	  the	  Atacama	  region	  of	  Chile	  provides	  a	  unique	  opportunity	  to	  characterize	  the	  alteration	  assemblages	  and	  lithological	  units	  associated	  with	  mineralization	  using	  surface	  rock	  lithogeochemistry.	  Relincho	  is	  geologically	  well	  characterized	  (Cintis	  &	  Boivin	  2003;	  Camus	  2007;	  Teck	  Resouces	  Limited	  2007;	  Stanley	  &	  Johnston	  2011;	  Johnston	  et	  al.	  2012),	  yet	  the	  project	  area	  is	  not	  affected	  by	  large-­‐scale	  mining	  operations	  or	  development.	  In	  addition,	  the	  deposit	  is	  unconcealed	  by	  overlying	  cover	  and	  has	  excellent	  outcrop	  exposure,	  thus	  giving	  full	  2D	  access	  by	  foot	  or	  truck,	  making	  it	  an	  excellent	  candidate	  for	  surface	  rock	  lithogeochemical	  characterization.	  The	  results	  of	  this	  study	  will	  determine	  the	  feasibility	  of	  using	  surface	  rock	  samples	  as	  a	  regional	  lithogeochemical	  exploration	  tool.	  	  1.2 Project	  Setting	  	   The	  Relincho	  PCD	  (S	  28.515°,	  W	  70.312°)	  is	  of	  Paleocene	  age	  and	  located	  approximately	  45	  km	  east-­‐northeast	  of	  Vallenar	  in	  the	  Atacama	  region	  of	  Chile	  (Figure	  3;	  Teck	  Resouces	  Limited	  2007).	  Situated	  at	  the	  southern	  extent	  of	  a	  belt	  of	  Paleocene	  PCDs	  trending	  from	  southern	  Peru	  to	  central	  Chile,	  it	  is	  one	  of	  five	  such	  distinctly	  aged	  belts	  occurring	  parallel	  to	  and	  contained	  by	  the	  Andes	  (Figure	  3;	  Vry	  et	  al.	  2010).	  These	  belts	  formed	  as	  a	  result	  of	  the	  eastern	  migration	  of	  plutonism	  caused	  by	  contractional	  tectonism	  in	  the	  Andes	  spanning	  from	  the	  mid	  Cretaceous	  to	  Recent	  (Camus	  &	  Dilles	  2001).	  	  	  5 0 km 300200100N22oE26oE30oE18oE34oEUpper Oligocene- MioceneUpper Miocene- PlioceneCretaceousPaleocene-Lower EoceneUpper EoceneBoliviaArgentinaPacic OceanPeruSantiago •CarmenEl SalvadorLa EscondidaSierra GordaMarte-LoboRefugioLoicaAndacolloDomeykoEl TenienteRio Blanco -   Los BroncesLos Pellambres -  El PachonGalenosaAntucoya SpenceChuquicamataQuebrada BlancaCollahuasiEl AbraCerro ColoradoRelincho30oS60oS0o150oW 30oW60oW90oW120oW 0oFigure 3: The Relincho Paleocene Cu-Mo porphyry deposit is located approximately 630 km northeast of Santiago at the southern end of a belt of Paleocene aged PCDs, which spans from southern Peru to central Chile. Five such distinctly aged PCD belts occur sub-parallel to the Andes, and young eastward (modified from Vry et al., 2010).6	  	  	  	   The	  property	  encompassing	  the	  Relincho	  PCD	  covers	  approximately	  195	  km2	  with	  elevations	  varying	  between	  1500	  and	  3000	  m	  above	  mean	  sea	  level	  (Figure	  4).	  The	  term	  “project	  area”	  refers	  to	  the	  area	  covered	  by	  samples	  in	  Figure	  4,	  which	  is	  centered	  over	  the	  Relincho	  PCD.	  The	  project	  area	  is	  located	  in	  a	  transitional	  desert,	  sparsely	  covered	  by	  sagebrush	  and	  wildflowers,	  with	  small	  trees	  limited	  to	  streambeds	  (Figure	  5).	  Topographically	  the	  project	  area	  comprises	  small	  hills,	  intermitted	  by	  semi-­‐dry	  streambeds,	  populated	  by	  wild	  donkeys	  and	  guanaco.	  As	  there	  is	  little	  in	  the	  way	  of	  vegetation,	  most	  of	  the	  property	  is	  accessible	  by	  truck,	  even	  areas	  without	  roads,	  allowing	  for	  excellent	  accessibility.	  	  	   Blocky,	  generally	  small	  outcrops	  (one	  to	  six	  square	  metres)	  and	  angular	  boulders	  cover	  the	  hillsides.	  Host	  granodiorite	  and	  syn-­‐mineralization	  porphyry	  units	  outcrop	  at	  surface.	  Minimal	  supergene	  transport	  of	  Cu	  and	  dominantly	  physical	  weathering	  (as	  opposed	  to	  chemical)	  are	  the	  result	  of	  a	  lack	  of	  precipitation.	  Weathered	  rinds	  are	  thin	  to	  non-­‐existent	  and	  do	  not	  impact	  lithogeochemical	  results.	  Although	  there	  is	  minimal	  supergene	  transport	  of	  Cu,	  areas	  with	  surface	  exposure	  of	  sulphides	  have	  suffered	  oxidation	  to	  secondary	  copper	  minerals	  such	  as	  glassy	  limonite,	  malachite	  and	  azurite.	  	  	  1.3 Historical	  Exploration	  	   Artisanal	  mining	  operations,	  currently	  still	  active,	  date	  back	  to	  the	  early	  1900s,	  with	  large-­‐scale	  exploration	  starting	  in	  the	  early	  1970s.	  More	  recently	  the	  Outokumpu	  company	  diamond	  drilled	  and	  sampled	  35,000	  m	  between	  1993	  and	  1997,	  reporting	  a	  resource	  estimate	  of	  112.2	  Mt	  at	  0.66	  %	  Cu	  and	  286	  ppm	  Mo	  in	  1995	  (Cintis	  &	  Boivin	  2003).	  Little	  exploration	  took	  place	  over	  the	  following	  decade	  as	  the	  property	  changed	  hands	  several	  times.	  The	  property	  was	  purchased	  in	  2000	  by	  Placer	  Dome;	  followed	  by	  Andes	  Pacific	  in	  2002;	  optioned	  in	  2003	  by	  Lumina	  Copper	  Corp.;	  and	  finally	  transferred	  in	  2006	  to	  their	  subsidiary,	  Global	  Copper	  Corp.	  (Cintis	  &	  Boivin	  2003).	  	  	  7 Figure 4: Areal photograph showing sample locations, the porphyry corridor, and the Relincho property out-line. Sample spacing is 250 m proximal to the porphyry corridor and 500 m distally.  Thirty-four re-gional samples were taken at random spacing to assess background. The sample grid covers about 65 km2. Contacts between Los Morteros granodiorite batholith and andesite of the Cerrillos Formation are approximated by white lines.8a bedcFigure 5: Photographs of the project area depicting the flora, fauna and outcrops.The lack of veg-etation allows for easy vehicle access to outcrops. a. A photograph taken south of the project area looking northwest, with the Relincho camp visible in the lower left corner. b. Relincho camp, looking northeast. c. An example of a typical outcrop (sample Q-07), with the hammerhead pointing to the north. d. Wild donkeys native to the area. e. Guanaco native to the area.9From	  2006	  to	  2008	  Global	  Copper	  Corp.	  ran	  drilling	  programs	  to	  extend	  resources.	  Drilling	  continued	  into	  2008,	  when	  Teck	  Cominco	  (now	  Teck	  Resources	  Limited)	  acquired	  Global	  Copper	  Corp.,	  whose	  principal	  asset	  was	  the	  Relincho	  property.	  Since	  2008,	  Relincho	  has	  undergone	  metallurgical	  studies,	  additional	  diamond	  drilling	  and	  further	  exploration.	  A	  feasibility	  report	  completed	  in	  the	  last	  quarter	  of	  2013	  reports	  1,239.1	  Mt	  at	  0.37	  %	  Cu,	  0.017	  %	  Mo	  Proven	  and	  Probable	  Mineral	  Reserves,	  and	  397.0	  Mt	  at	  0.33	  %	  Cu,	  0.011	  %	  Mo	  Measured	  and	  Indicated	  Mineral	  Resources	  (Teck	  Resources	  Limited	  2014).	  	  	  1.4	   Regional	  Geology	  Situated	  on	  the	  same	  Paleocene-­‐Lower	  Eocene	  aged	  belt	  as	  the	  Carmen	  and	  Spence	  deposits,	  the	  Relincho	  PCD	  is	  hosted	  in	  Paleocene	  aged	  rocks,	  surrounded	  by	  Cretaceous	  volcanic	  units.	  Andesite	  of	  the	  Cerrillos	  Formation,	  into	  which	  the	  host	  granodiorite	  and	  mineralized	  porphyry	  units	  are	  intruded,	  formed	  during	  an	  extensional	  episode	  in	  the	  Early	  to	  Late	  Cretaceous	  (Camus	  2007).	  The	  Cerrillos	  Formation	  consists	  of	  two	  units:	  a	  lower	  unit	  comprised	  of	  pyroclastic	  and	  sedimentary	  deposits	  and	  the	  upper	  unit	  comprised	  of	  andesitic	  to	  rhyolitic	  lavas	  (Camus	  2007;	  Figure	  6).	  Unconformably	  overlying	  the	  Cerrillos	  Formation	  are	  volcaniclastic	  breccias,	  conglomerates	  and	  sandstones	  of	  the	  Hornitos	  Formation	  (Reynaldo,	  et	  al.,	  2002),	  K-­‐Ar	  dating	  on	  biotite	  indicates	  an	  age	  of	  72.1	  ±	  1.2	  Ma	  (Moscoso	  et	  al.	  2010a).	  Extensional	  episodes	  in	  the	  Jurassic	  to	  Early	  Cretaceous	  formed	  a	  system	  of	  north-­‐northwest	  striking	  basin-­‐range	  faults	  (Reynaldo	  et	  al.	  2002).	  These	  faults	  provided	  feeding	  structures	  for	  the	  emplacement	  of	  the	  Paleocene	  granodiorite	  of	  the	  Los	  Morteros	  batholith	  into	  both	  the	  Cerrillos	  and	  Hornitos	  Formations	  (Camus	  &	  Dilles	  2001;	  Camus	  2007).	  K-­‐Ar	  dating	  on	  biotite	  of	  the	  Los	  Morteros	  batholith	  shows	  an	  age	  of	  61.1	  –	  64.9	  ±	  2.9	  Ma	  near	  the	  Relincho	  deposit	  (Moscoso	  et	  al.	  2010a).	  The	  Los	  Morteros	  batholith	  outcrops	  over	  hundreds	  of	  square	  kilometres	  and	  hosts	  over	  a	  dozen	  known	  deposits	  (Moscoso	  et	  al.	  2010b).	  	  	  1068400006850000380000370000 390000Surface SedimentsEocene IntrusivesPaleocene Intrusives (Los Morteros)Cretaceous IntrusivesCretaceous Volcanics (Cerrillos Formation)Cretaceous Volcanics (Hornitos Formation)Triassic-Jurassic VolcanicsPaleozoic IntrusivesRelincho Deposit Figure 6: Regional geology of the area surrounding the Relincho deposit. Lithological units have been grouped by age for simplification. (Modified from Moscoso et al., 2010b)11	  	  On	  the	  project	  scale,	  the	  Los	  Morteros	  granodiorite	  dominates	  with	  the	  andesite	  of	  the	  Cerrillos	  Formation	  surrounding	  the	  project	  area	  (Figure	  4).	  The	  four	  Paleocene	  porphyry	  units,	  also	  of	  the	  Los	  Morteros	  batholith,	  are	  associated	  with	  hydrothermal	  alteration	  and	  sulphide	  mineralization	  (Figure	  4).	  Porphyry	  units	  are	  concentrated	  along	  a	  seven	  km	  long,	  northwest-­‐southeast	  trending	  series	  of	  porphyry	  centers,	  hereon	  referred	  to	  as	  the	  “porphyry	  corridor”	  (Figure	  4).	  Hydrothermal	  breccias	  often	  mark	  the	  contacts	  between	  the	  granodiorite	  and	  porphyry	  units.	  Barren,	  post	  mineralization,	  dacite	  dikes	  intrude	  all	  preceding	  units.	  	  Potassic,	  propylitic	  and	  phyllic	  alteration	  at	  Relincho	  are	  defined	  by	  the	  following	  assemblages,	  with	  key	  minerals	  indicated	  in	  bold:	  Potassic	  Assemblage:	  	   secondary	  biotite	  +	  K-­‐feldspar	  +	  magnetite	  ±	  glassy	  limonite	  (from	  chalcopyrite)	  Propylitic	  Assemblage:	  	   epidote	  +	  chlorite	  +	  hematite	  ±	  albite	  ±	  calcite	  ±	  pyrite	  Phyllic	  Assemblage:	  	   	   chlorite	  +	  muscovite	  +	  quartz	  ±	  calcite	  ±	  hematite.	  	  	  1.5 Research	  Objectives	  and	  Approach	  The	  objectives	  of	  this	  thesis	  are:	  • To	  characterize	  the	  lithological	  units	  using	  surface	  rock	  lithogeochemistry	  • To	  characterize	  alteration	  assemblages	  using	  surface	  rock	  lithogeochemistry	  • To	  quantify	  alteration	  using	  alteration	  indices	  identified	  through	  alteration	  characterization	  • To	  identify	  key	  lithogeochemical	  indicators	  for	  recognizing	  areas	  of	  potential	  PCD	  mineralization	  • To	  determine	  appropriate	  regional	  and	  follow	  up	  scale	  sample	  spacing	  strategies	  for	  identifying	  areas	  of	  potential	  PCD	  mineralization	  • To	  propose	  appropriate	  analytical	  methodologies	  for	  PCD	  exploration	  	  These	  objectives	  are	  achieved	  by	  first	  completing	  a	  two-­‐month	  sampling	  survey	  centered	  over	  known	  mineralization	  (Figure	  4)	  with	  the	  assistance	  of	  Luis	  Nuehe,	  an	  12	  	  employee	  of	  Teck	  Resources	  Limited.	  The	  survey	  covers	  65	  km2	  comprising	  an	  inner	  square	  grid	  with	  sample	  spacing	  of	  250	  m,	  surrounded	  by	  an	  outer	  grid	  with	  a	  sample	  spacing	  of	  500	  m.	  An	  additional	  34	  samples	  were	  taken	  regionally	  to	  assess	  background	  concentrations.	  Hand	  specimens	  were	  cut	  from	  each	  sample	  in	  the	  field	  and	  retained	  for	  petrography	  and	  alkali	  feldspar	  staining.	  Samples	  weighing	  approximately	  five	  kg	  were	  submitted	  for	  preparation	  and	  analysis	  at	  Acme	  Analytical	  Laboratories	  Limited	  (Acme)	  in	  Vancouver.	  Lithogeochemical	  results	  are	  interpreted	  using	  exploratory	  data	  analysis	  techniques	  such	  as	  probability,	  Tukey,	  ranked	  variable,	  univariate	  and	  bivariate	  methods;	  elemental	  gains	  and	  loss	  determinations;	  fertility	  assessment;	  and	  MER	  diagrams	  to	  determine	  the	  viability	  and	  suitability	  of	  surface	  rock	  lithogeochemistry	  as	  a	  regional	  scale	  exploration	  tool.	  Successful	  methods	  for	  using	  regional	  scale,	  surface	  lithogeochemistry	  for	  PCD	  exploration	  are	  summarized	  in	  the	  conclusions	  section	  for	  future	  exploration	  applications.	  Field,	  analytical	  and	  interpretive	  methodologies	  are	  summarized	  in	  chapter	  two.	  	  It	  is	  important	  to	  note	  that	  geological	  mapping	  is	  not	  an	  objective	  of	  this	  thesis.	  A	  separate	  mapping	  program	  was	  initiated	  by	  Teck	  Resources	  Limited	  to	  achieve	  this	  goal.	  Point	  sample	  data	  has	  been	  collected	  and	  interpreted	  with	  few	  observations	  of	  contact	  relationships	  between	  lithological	  units.	  This	  data	  has	  been	  used	  to	  produce	  a	  schematic	  map	  of	  the	  project	  scale	  geology	  presented	  in	  Chapter	  two.	  	  	  1.6 	  Thesis	  Overview	  	  This	  thesis	  is	  divided	  into	  five	  chapters:	  (1)	  an	  introduction	  to	  the	  project	  setting,	  objectives,	  and	  regional	  geology;	  (2)	  descriptions	  of	  field	  and	  analytical	  methodologies,	  including	  a	  summary	  of	  the	  data	  quality	  assessment;	  (3)	  descriptions	  and	  discussions	  of	  the	  physical	  and	  chemical	  characteristics	  of	  the	  lithological	  units	  and	  alteration	  assemblages,	  including	  an	  interpreted	  magmatic	  evolution	  model	  and	  regional	  exploration	  applications;	  (4)	  descriptions	  and	  discussions	  of	  the	  geochemical	  attributes	  of	  the	  alteration	  assemblages,	  alteration	  indices	  and	  their	  regional	  exploration	  applications;	  and	  (5)	  a	  summary	  of	  the	  conclusions	  of	  chapters	  three	  and	  four	  and	  a	  discussion	  regarding	  suggested	  follow-­‐up	  work	  and	  potential	  exploration	  applications.	  13	  	  Chapter	  2:	  Methodology	  and	  Data	  Quality	  Assessment	  2.1 Introduction	  The	  purpose	  of	  this	  study	  is	  to	  use	  regional	  surface	  lithogeochemistry	  to	  characterize	  lithological	  units	  and	  alteration	  assemblages	  for	  applications	  in	  PCD	  exploration.	  As	  such	  a	  sample	  of	  each	  lithological	  unit	  present	  at	  267	  sites	  was	  collected	  for	  lithogeochemical	  characterization.	  In	  total	  291	  samples	  were	  collected	  over	  a	  65	  km2	  area.	  This	  section	  describes	  the	  field	  methods,	  petrography,	  analyses,	  data	  quality	  assessment	  procedures	  and	  interpretive	  methods	  involved	  in	  this	  characterization	  study.	  A	  comparison	  of	  the	  mineral	  quantification	  methods:	  mineral	  liberation	  analysis	  (MLA);	  Rietveld	  refinement;	  X-­‐ray	  diffraction	  (XRD);	  quantitative	  evaluation	  of	  minerals	  by	  scanning	  electron	  microscopy	  (QEMSCAN);	  and	  whole	  rock	  data	  tabulated	  using	  the	  MINSQ	  spreadsheet	  (Herrmann	  &	  Berry	  2002)	  was	  completed	  as	  a	  separate	  study	  using	  a	  subset	  of	  ten	  granodiorite	  samples.	  Appendix	  A	  presents	  the	  report	  and	  results	  from	  this	  comparison.	  	  2.2 Field	  Methods	  Sampling	  was	  completed	  over	  a	  two-­‐month	  field	  season	  beginning	  in	  January	  of	  2012.	  Centered	  over	  the	  porphyry	  corridor,	  sampling	  covers	  approximately	  65	  km2	  and	  consists	  of	  an	  inner	  grid	  with	  sample	  spacing	  of	  250	  m	  covering	  approximately	  10	  km2	  along	  the	  strike	  of	  the	  porphyry	  corridor,	  an	  outer	  grid	  with	  sample	  spacing	  of	  500	  m	  covering	  an	  additional	  25	  km2,	  and	  regional	  sampling	  taken	  based	  on	  accessibility	  covering	  an	  additional	  30	  km2	  (Figure	  4).	  Regional	  samples	  were	  taken	  in	  an	  attempt	  to	  ascertain	  background	  values.	  Every	  effort	  was	  made	  to	  obtain	  unaltered	  samples	  of	  each	  lithology,	  but	  the	  large	  footprint	  of	  the	  hydrothermal	  system	  made	  establishing	  a	  confident	  background	  baseline	  challenging.	  	  All	  sample	  location	  information	  was	  collected,	  and	  is	  displayed	  in	  this	  thesis	  using	  the	  projection	  PSAD56,	  UTM	  zone	  19S.	  Samples	  were	  collected	  in	  a	  grid	  pattern,	  14	  	  where	  each	  square	  is	  one	  square	  km	  organized	  alphabetically,	  then	  numerically,	  such	  that	  the	  sample	  name	  is	  representative	  of	  the	  sample	  location,	  e.g.	  LEG-­‐A-­‐04	  is	  from	  the	  northwest	  corner	  of	  the	  sample	  area	  (grid	  A),	  and	  the	  northeast	  corner	  of	  grid	  A	  (Figure	  7).	  Samples	  with	  double	  letters	  are	  from	  the	  small	  sample	  grid	  at	  the	  southeast	  end	  of	  the	  porphyry	  corridor;	  samples	  prefixed	  with	  a	  Z	  are	  regional	  samples.	  	  Only	  outcrops	  were	  sampled	  in	  this	  survey.	  Outcrops	  were	  described	  in	  the	  field,	  noting	  location,	  lithology,	  alteration	  minerals,	  oxidation,	  veins,	  associated	  alteration	  haloes	  and	  contact	  relationships.	  A	  photograph	  was	  taken	  at	  each	  sample	  site.	  An	  in-­‐situ	  outcrop	  sample,	  on	  average	  about	  six	  kg,	  was	  taken	  at	  each	  sample	  site.	  In	  cases	  where	  more	  than	  one	  lithology	  was	  identified	  at	  an	  outcrop,	  a	  sample	  representing	  each	  lithology	  was	  collected.	  Ten	  magnetic	  susceptibility	  measurements	  were	  taken	  using	  a	  KT-­‐9	  Kappameter	  for	  each	  sample	  on	  the	  outcrop	  with	  the	  maximum,	  minimum	  and	  average	  values	  recorded.	  The	  magnetic	  susceptibility	  values	  are	  assessed	  to	  determine	  if	  certain	  ranges	  are	  characteristic	  of	  a	  lithology	  or	  alteration	  assemblage.	  Each	  sample	  was	  tested	  for	  the	  presence	  of	  carbonates	  using	  10	  %	  hydrochloric	  acid.	  The	  intensity	  of	  the	  reaction	  to	  acid	  was	  recorded	  on	  a	  scale	  of	  one	  (least	  reactive)	  to	  three	  (most	  reactive)	  and	  prefixed	  as	  a	  reaction	  within	  the	  rock	  (R)	  or	  vein	  (V).	  This	  information	  is	  presented	  in	  Appendix	  B.	  Care	  was	  taken	  to	  obtain	  representative	  samples	  of	  each	  outcrop.	  Any	  weathered	  portion	  of	  a	  sample	  was	  removed	  as	  much	  as	  possible	  in	  the	  field	  using	  a	  hammer	  to	  reduce	  the	  lithogeochemical	  impact	  of	  chemical	  weathering.	  Large	  (>	  3	  cm)	  veins	  were	  avoided	  when	  sampling	  to	  ensure	  that	  analytical	  results	  are	  representative	  of	  the	  host	  rock,	  and	  not	  diluted	  or	  biased	  by	  the	  composition	  of	  veins.	  Using	  a	  rock	  saw,	  each	  sample	  was	  cut	  into	  two	  parts:	  1. A	  representative	  hand	  specimen,	  approximately	  10	  x	  15	  x	  3	  cm3	  preserving	  the	  fresh	  and	  weathered	  surfaces	  for	  mineralogical	  observations,	  photographs,	  alkali	  feldspar	  staining,	  TerraSpec®	  work	  and	  polished	  thin	  sections;	  2. Sample	  material	  submitted	  for	  geochemical	  analyses,	  approximately	  five	  kg	  once	  the	  hand	  specimen	  has	  been	  removed.	  	   	  15AJIHGFEDCBRQPONMLKTSAAFAEAHADACAGABA0     1     2kmN Figure 7: Map showing the one square kilometer grid pattern of the sampling survey.  Each sample is named according to the location of the sampled outcrop, for instance LEG-I-08 would be from the center of the I square.  All regional samples contain the prex Z.16	  	  	  2.3 Hand	  Samples:	  Shortwave	  Infrared,	  Petrography	  and	  Quantitative	  Mineralogy	  	  Hand	  samples	  were	  described	  in	  detail	  using	  a	  binocular	  microscope	  (Appendix	  B).	  Polished	  thin	  sections	  (PTS)	  from	  Vancouver	  Petrographics	  of	  56	  hand	  samples,	  selected	  based	  on	  lithology,	  alteration	  type/intensity,	  mineralization	  and	  texture,	  were	  photographed	  and	  described	  in	  detail	  (Appendix	  C).	  Vancouver	  Petrographics	  completed	  alkali	  feldspar	  staining	  on	  268	  samples	  by	  etching	  polished	  samples	  with	  hydrofluoric	  acid,	  and	  then	  dipping	  the	  sample	  in	  sodium	  cobaltinitrite,	  which	  stains	  K-­‐bearing	  minerals,	  such	  as	  K-­‐feldspar,	  yellow.	  Pictures	  of	  the	  stained	  samples	  are	  presented	  in	  Appendix	  B.	  Electron	  microprobe	  (EMP)	  (Appendix	  D)	  and	  scanning	  electron	  microscope	  (SEM)	  (Appendix	  E)	  work	  completed	  by	  the	  author	  at	  the	  University	  of	  British	  Columbia	  focused	  on	  characterizing	  feldspars,	  hornblende	  and	  biotite	  (primary	  and	  secondary)	  and	  also	  served	  to	  confirm	  petrographic	  observations.	  The	  56	  samples	  selected	  for	  PTS	  were	  submitted	  for	  XRD	  analysis	  at	  Acme	  in	  Vancouver;	  these	  results	  are	  found	  in	  Appendix	  A	  with	  the	  quantification	  method	  comparison.	  Hand	  specimens	  were	  analyzed	  by	  shortwave	  infrared	  (SWIR)	  using	  a	  model	  TSP	  350-­‐2500	  TerraSpec©	  instrument	  at	  the	  University	  of	  British	  Columbia.	  TerraSpec©	  spectra	  were	  processed	  using	  The	  Spectral	  Geologist©	  (TSG)	  software	  from	  AusSpec	  International	  Inc.	  Mineral	  speciation	  is	  based	  on	  best	  fit	  with	  a	  spectral	  library	  provided	  by	  the	  SpecMin®	  software.	  These	  mineral	  identifications	  were	  crosschecked	  manually	  by	  visual	  spectra	  comparison,	  rejecting	  any	  spectra	  identified	  as	  aspectral,	  null,	  wood	  or	  Teflon.	  In	  addition	  to	  mineral	  identification,	  the	  width,	  depth	  and	  wavelength	  of	  features	  occurring	  at	  1930±	  30	  nm,	  2205	  ±	  25	  nm,	  2254	  ±	  14	  nm,	  and	  2330	  ±	  30	  nm	  were	  extracted	  to	  investigate	  the	  properties	  of:	  water	  chemically	  bound	  in	  clay	  minerals	  (1900);	  white	  micas	  (2200	  nm);	  and	  chlorite	  (2250	  nm,	  2350	  nm)	  (Halley	  2008).	  Identified	  minerals	  and	  exported	  wavelength	  information	  is	  presented	  in	  Appendix	  F.	  For	  Terraspec©	  work	  a	  white	  polytetrafluoroethylene	  (Teflon)	  tile	  was	  measured	  every	  20th	  sample	  as	  an	  absolute	  reflectance	  reference	  for	  calibration.	  	  	  17	  	  2.4 Laboratory	  Methods	  After	  weathered	  portions	  and	  a	  representative	  hand	  sample	  were	  removed,	  approximately	  five	  kg	  of	  sample	  material	  remained	  for	  preparation	  and	  analysis	  at	  Acme.	  Samples	  were	  jaw	  crushed	  at	  the	  facility	  in	  Copiapo,	  Chile	  to	  nominally	  80	  %	  passing	  a	  2	  mm	  screen.	  All	  crushed	  material	  was	  sent	  to	  the	  Vancouver	  facility	  where	  a	  500	  g	  riffle	  split	  was	  disk	  mill	  pulverized	  by	  a	  labtechs	  LM2	  in	  a	  1000	  cc	  capacity,	  high	  C	  steel	  composition	  bowl,	  to	  nominally	  85	  %	  passing	  0.075	  mm.	  	  Samples	  were	  analyzed	  for:	  	  1. Major	  oxides	  by	  a	  lithium	  metaborate/tetraborate	  fusion,	  dilute	  HNO3	  digestion	  of	  the	  fusion	  prill	  and	  inductively	  coupled	  plasma	  optical	  emission	  spectrometer	  (ICP-­‐OES)	  finish	  on	  a	  0.2	  g	  sample	  split	  (Acme	  package	  4A)	  2. Trace	  elements	  by	  lithium	  metaborate/tetraborate	  fusion,	  dilute	  HNO3	  digestion	  of	  the	  fusion	  prill,	  with	  an	  inductively	  coupled	  plasma	  mass	  spectrometer	  (ICP-­‐MS)	  finish	  on	  a	  0.2	  g	  sample	  split	  (Acme	  package	  4B)	  3. Trace	  elements	  by	  pressed	  pellet	  X-­‐ray	  fluorescence	  (XRF)	  on	  a	  7.5	  g	  sample	  split	  (Acme	  package	  2X)	  4. Total	  carbon	  and	  sulphur	  by	  combustion	  furnace	  infrared	  C-­‐S	  analysis	  (Leco)	  on	  a	  1	  g	  sample	  split	  (Acme	  package	  4A)	  5. Ultratrace-­‐level	  analysis	  on	  53	  elements	  by	  Acme’s	  “aqua	  regia”	  (a	  solution	  of	  equal	  parts	  HCl,	  HNO3	  and	  H2O)	  digest	  with	  ICP-­‐MS	  finish	  on	  a	  30g	  sample	  split	  (Acme	  package	  1F30)	  6. Samples	  exceeding	  1000	  ppm	  Cu	  were	  submitted	  for	  Cu	  and	  Mo	  assays	  by	  4-­‐acid	  (HClO4,	  HNO3,	  HF	  and	  HCl)	  digestion	  with	  an	  Atomic	  Absorption	  finish	  at	  Acme	  Analytical	  Laboratories	  in	  Santiago,	  Chile	  (Acme	  package	  8TD).	  	  	  Analytical	  results	  and	  package	  descriptions	  are	  shown	  in	  Appendix	  G.	  	  18	  	  2.5 Data	  Quality	  Assessment	  All	  data	  quality	  plots	  are	  found	  in	  Appendix	  H,	  along	  with	  a	  summary	  of	  the	  data	  quality	  assessment.	  	  Field	  duplicates,	  preparation	  duplicates,	  preparation	  blanks	  and	  certified	  reference	  materials	  (CRMs)	  were	  inserted	  at	  a	  rate	  of	  at	  least	  one	  in	  20	  samples,	  as	  per	  the	  data	  quality	  protocol	  of	  Teck	  Resources	  Limited.	  The	  author	  took	  field	  duplicates	  as	  independent	  samples	  from	  the	  same	  outcrop.	  Analytical	  results	  for	  the	  duplicates,	  blanks	  and	  CRMs	  along	  with	  a	  summary	  of	  the	  data	  quality	  assessment	  are	  found	  in	  Appendix	  H.	  	  An	  Acme	  employee	  inserted	  the	  preparation	  duplicates,	  preparation	  blanks	  and	  CRMs	  at	  the	  instruction	  of	  the	  author.	  Preparation	  duplicates	  were	  taken	  during	  riffle	  splitting	  after	  crushing	  and	  prior	  to	  pulverization.	  Preparation	  blanks	  (G1)	  comprise	  barren	  granite	  inserted	  by	  an	  Acme	  employee	  prior	  to	  crushing.	  Five	  different	  CRMs	  were	  inserted	  at	  the	  weighing	  stage:	  ST-­‐1;	  ST-­‐2;	  52C;	  GSP-­‐2;	  and	  SY-­‐4.	  	  In	  general	  the	  preparation	  duplicates	  show	  better	  reproducibility	  than	  the	  field	  duplicates	  with	  reproducibility	  improving	  as	  concentration	  increases.	  Analytical	  results	  for	  all	  duplicate	  pairs	  are	  separated	  into	  ‘parent’	  and	  ‘daughter’	  samples	  which	  are	  plotted	  against	  each	  other	  with	  ±	  10,	  20	  and	  30	  %	  error	  lines	  indicated	  to	  assess	  natural	  variability	  and	  to	  identify	  any	  contamination	  or	  sample	  mix-­‐up	  in	  the	  lab.	  As	  per	  the	  protocol	  of	  Teck	  Resources	  Limited,	  field	  duplicates	  are	  expected	  to	  have	  90	  %	  of	  pairs	  fall	  within	  30	  %	  of	  each	  other	  at	  values	  greater	  than	  ten	  times	  detection	  limit,	  and	  preparation	  duplicates	  are	  expected	  to	  have	  90	  %	  of	  pairs	  fall	  within	  20	  %	  of	  each	  other	  for	  values	  greater	  than	  ten	  times	  detection	  limit.	  Based	  on	  these	  criteria	  the	  field	  duplicates	  show	  high	  natural	  variability	  (>	  10	  %	  of	  pairs	  plotting	  outside	  of	  ±	  30	  %)	  for	  U,	  Pb,	  Zn,	  Cu,	  Mo,	  Ag,	  As,	  Au,	  Cd,	  Sb,	  and	  Li.	  Preparation	  duplicates	  show	  a	  lack	  of	  reproducibility	  (>	  10	  %	  of	  pairs	  plotting	  outside	  of	  ±	  20	  %)	  for	  Au,	  Mo,	  and	  Cd.	  Elements	  such	  as	  Ag,	  Au	  and	  Mo	  commonly	  exhibit	  high	  natural	  variability	  because	  of	  the	  nugget	  effect.	  These	  elements	  tend	  to	  occur	  in	  concentrated	  nuggets	  that	  are	  non-­‐uniformly	  disseminated	  resulting	  in	  poor	  analytical	  reproducibility.	  	  19	  	  To	  express	  the	  variability	  and	  bias	  visually,	  SiO2,	  Al2O3,	  K2O,	  TiO2,	  Cu	  and	  Au	  are	  plotted	  on	  a	  mean	  versus	  mean	  percentage	  difference	  (MPD)	  diagram	  with	  ±	  20	  %	  and	  ±	  30	  %	  limits	  plotted	  (Figure	  8).	  These	  plots	  indicate	  no	  obvious	  bias	  in	  the	  data,	  and	  emphasize	  the	  variability	  in	  Cu	  and	  Mo	  seen	  in	  the	  parent	  versus	  daughter	  duplicate	  plots	  in	  Appendix	  H.	  In	  practice	  no	  bias	  would	  be	  expected	  as	  the	  samples	  are	  analyzed	  at	  the	  same	  time,	  in	  the	  same	  batch	  with	  the	  same	  method.	  Some	  analytes	  are	  too	  close	  to	  or	  at	  the	  detection	  limits	  of	  the	  analytical	  techniques	  used	  to	  comment	  on	  natural	  variability	  or	  reproducibility,	  such	  as	  Sn,	  Ta,	  S,	  B,	  Hg,	  Se,	  Te,	  Re,	  Pd,	  and	  Pt;	  these	  elements	  are	  excluded	  from	  this	  study.	  As	  per	  the	  protocols	  of	  Teck	  Resources	  Limited,	  blank	  sample	  (G1)	  concentrations	  are	  plotted	  with	  a	  line	  representing	  ten	  times	  the	  detection	  limit	  for	  each	  analyte	  (Appendix	  H),	  though	  this	  “blank”	  is	  a	  natural	  material,	  subject	  to	  natural	  variability.	  The	  G1	  results	  are	  examined	  for	  any	  obvious	  outliers	  that	  could	  indicate	  carryover	  during	  preparation.	  Any	  erratic	  results	  for	  a	  sample	  have	  been	  investigated	  for	  consistent	  behavior	  between	  analytes	  and	  deemed	  a	  product	  of	  natural	  variability.	  If	  contamination	  were	  the	  source	  of	  an	  erratic	  result,	  it	  would	  be	  apparent	  in	  more	  than	  one	  analyte.	  Five	  reference	  materials	  were	  inserted	  to	  assess	  data	  quality.	  Reference	  materials	  ST-­‐1	  and	  ST-­‐2	  are	  certified	  by	  and	  internal	  to	  Teck.	  They	  are	  weakly	  mineralized	  granodiorite	  from	  the	  Relincho	  property.	  Material	  52C	  is	  ore	  and	  waste	  rock	  from	  an	  Au	  -­‐	  Cu	  ±	  Mo	  porphyry	  in	  central	  western	  Australia	  commercially	  produced	  by	  OREAS.	  The	  USGS	  manufactured	  GSP-­‐2	  is	  a	  granodiorite	  from	  Silver	  Plume,	  Colorado.	  Diorite	  gneiss	  was	  used	  by	  CANMET	  to	  manufacture	  SY-­‐4.	  Certified	  values	  for	  reference	  materials	  are	  summarized	  in	  Table	  1.	  All	  CRM	  analyses	  are	  plotted	  with	  the	  published	  certified	  values	  and	  accepted	  range	  of	  variation	  determined	  as	  three	  times	  the	  published	  standard	  deviation	  around	  the	  certified	  value	  and	  presented	  in	  Appendix	  H.	  Where	  values	  are	  not	  reported,	  published	  accepted	  means	  are	  used.	  Where	  no	  accepted	  values	  are	  given,	  analytical	  results	  are	  plotted	  without	  control	  limits.	  Plots	  are	  examined	  for	  results	  lying	  outside	  of	  the	  acceptance	  criteria,	  taking	  into	  account	  any	  discrepancy	  between	  the	  analytical	  method	  for	  the	  certified	  values	  and	  those	  used	  for	  the	  study	  sample	  results.	  Special	  20-50.0 -40.0 -30.0 -20.0 -10.0 0.0 10.0 20.0 30.0 40.0 50.0 0.0 2.0 4.0 6.0 8.0 10.0 MPD	  K2O	  %	  (mean)	  K2O_4A Dups pct  K2O_4A4B_Field K2O_4A4B_Prep x=y +/-30% +/-20% -50.0 -40.0 -30.0 -20.0 -10.0 0.0 10.0 20.0 30.0 40.0 50.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 MPD	  TiO2	  %	  (mean)	  TiO2_4A Dups pct  TiO2_4A4B_Field TiO2_4A4B_Prep x=y +/-30% +/-20% -50.0 -40.0 -30.0 -20.0 -10.0 0.0 10.0 20.0 30.0 40.0 50.0 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0 900.0 MPD	  Cu	  ppm	  (mean)	  Cu_1F Dups ppm Cu_1F30_Field Cu_1F30_Prep x=y +/-30% +/-20% -50.0 -40.0 -30.0 -20.0 -10.0 0.0 10.0 20.0 30.0 40.0 50.0 0.0 2.0 4.0 6.0 8.0 10.0 MPD	  Mo	  ppm	  (mean)	  Mo_1F Dups ppm Mo_1F30_Field Mo_1F30_Prep x=y +/-30% +/-20% -50.0 -40.0 -30.0 -20.0 -10.0 0.0 10.0 20.0 30.0 40.0 50.0 50.0 55.0 60.0 65.0 70.0 75.0 MPD	  SiO2	  %	  (mean)	  SiO2_4A Dups pct  SiO2_4A4B_Field SiO2_4A4B_Prep x=y +/-30% +/-20 % -50.0 -40.0 -30.0 -20.0 -10.0 0.0 10.0 20.0 30.0 40.0 50.0 10.0 12.0 14.0 16.0 18.0 20.0 MPD	  Al2O3	  %	  (mean)	  Al2O3_4A Dups pct  Al2O3_4A4B_Field Al2O3_4A4B_Prep x=y +/-30% +/-20%  Figure 8: Duplicate pairs plotted as the mean versus the mean percentage difference (MPD) calculated as 100*(Original-Duplicate)/mean. Field duplicates are plotted as blue dots, and prep duplicates as green diamonds. 21Reference MaterialCu (ppm)Mo (ppm)Au (ppb)Al2O3 (wt %)TiO2 (wt %)SiO2 (wt %)Na2O (wt %)CaO (wt %)GSP-2 43  -  - 14.9 0.66 66.6 2.78 2.10OREAS 52C 3440 267 346 15.3 0.64 59.7 3.47 3.45ST-1 180 13  -  -  -  -  -  - ST-2 760 40  -  -  -  -  -  - SY-4 7  -  - 20.69 0.287 49.9 7.10 8.05Table 1:  Summary of certified values for reference materials used for analysis.  Plots of the reference material results are found in Appendix H.Reference MaterialCu (ppm)Mo (ppm)Au (ppb)Al2O3 (wt %)TiO2 (wt %)SiO2 (wt %)Na2O (wt %)CaO (wt %)GSP-2 43  -  - 14.9 0.66 66.6 2.78 2.10OREAS 52C 3440 267 346 15.3 0.64 59.7 3.47 3.45ST-1 180 13  -  -  -  -  -  - ST-2 760 40  -  -  -  -  -  - SY-4 7  -  - 20.69 0.287 49.9 7.10 8.0522	  	  attention	  is	  paid	  to	  the	  principle	  analytes	  used	  in	  this	  study,	  such	  as	  Cu,	  Mo,	  Au,	  CaO,	  Na2O,	  K2O,	  TiO2,	  Al2O3,	  etc.	  Consistent	  low	  biases	  (for	  instance	  Fe,	  Mn,	  Pb	  and	  Cd	  for	  GSP-­‐2)	  are	  considered	  an	  analytical	  artifact	  due	  to	  minor	  methodological	  differences	  between	  analytical	  techniques	  used	  in	  certification	  and	  those	  used	  in	  this	  survey.	  These	  samples	  were	  not	  submitted	  for	  re-­‐analysis,	  as	  re-­‐analysis	  by	  the	  same	  methodology	  would	  not	  correct	  for	  analytical	  method	  bias.	  In	  general	  the	  results	  for	  ST-­‐1,	  ST-­‐2,	  52C	  and	  GSP-­‐2	  were	  consistent	  with	  certified	  results,	  with	  the	  exception	  of	  analytical	  biases.	  	  SY-­‐4	  is	  only	  provided	  with	  a	  95	  %	  confidence	  interval,	  which	  is	  both	  inappropriate	  and	  incorrect	  to	  use	  for	  determination	  of	  acceptance	  criteria.	  Instead	  of	  using	  the	  confidence	  interval,	  values	  that	  are	  ±	  5	  %	  of	  the	  reported	  mean	  are	  used.	  Failures	  for	  Ba,	  Cs,	  Hf,	  Th,	  Ta,	  Sr,	  La,	  Zr,	  Pr,	  Nd,	  Y,	  Ce,	  Sm,	  Gd,	  Lu,	  Cu,	  Zn,	  Ni,	  Be,	  Li,	  Co,	  Zn,	  and	  Ni	  are	  due:	  to	  incomparable	  analytical	  methods	  (e.g.	  Cu,	  Pb,	  Zn,	  Ni,	  etc.);	  detection	  limit	  proximity	  (e.g.	  U);	  and	  excessively	  tight	  control	  limits	  (e.g.	  Nb,	  Zr,	  etc.).	  No	  significant	  data	  quality	  issues	  have	  been	  identified	  and	  this	  data	  has	  been	  deemed	  fit	  for	  purpose	  based	  on	  typical	  exploration	  data	  quality	  assessment	  procedures	  and	  parameters	  as	  defined	  by	  Teck	  Resources	  Limited.	  	  	  2.6 Data	  Analysis	  Methodologies	  2.6.1 Probability	  Plots	  Data	  consisting	  of	  continuous	  variables,	  for	  example	  elemental	  concentrations	  and	  magnetic	  susceptibility	  values,	  have	  been	  assessed	  for	  multiple	  populations	  using	  probability	  plots,	  after	  assessing	  for	  normal	  distribution	  (Sinclair	  1976).	  By	  plotting	  concentration	  on	  the	  y-­‐axis,	  and	  units	  of	  normal	  probability	  on	  the	  x-­‐axis,	  representative	  of	  the	  probability	  that	  a	  value	  will	  lie	  below	  the	  corresponding	  concentration,	  probability	  plots	  effectively	  shows	  the	  distribution	  of	  a	  population.	  Inflection	  points	  on	  a	  probability	  plot	  are	  indicative	  of	  a	  mixing	  of	  multiple	  populations	  (Sinclair	  1976).	  2.6.2 Tukey	  Plots	  Tukey	  plots	  are	  used	  in	  chapter	  three	  for	  assessing	  and	  summarizing	  overall	  23	  	  compositional	  differences	  between	  lithological	  units.	  The	  plot	  boxes	  represents	  the	  “interquartile	  range”	  defined	  as	  the	  50	  %	  of	  data	  that	  lies	  between	  the	  first	  and	  third	  quartile	  (interquartile	  =	  Q3-­‐Q1)	  of	  ranked	  data.	  Whiskers	  extend	  to	  the	  fifth	  and	  95th	  percentiles.	  Outliers,	  displayed	  as	  hollow	  circles,	  fall	  outside	  of	  the	  fifth	  and	  95th	  percentile.	  The	  mean	  is	  represented	  by	  a	  solid	  black	  dot,	  and	  the	  median	  a	  black	  line.	  Some	  elements	  are	  shown	  on	  a	  logarithmic	  scale	  (log)	  to	  better	  illustrate	  the	  range	  of	  the	  natural	  variability.	  Analytes	  such	  as	  Sn,	  Ta,	  S,	  B,	  Hg,	  Se,	  Te,	  Re,	  Pd,	  and	  Pt	  have	  been	  omitted	  from	  the	  Tukey	  plots,	  because	  their	  concentrations	  are	  too	  close	  to	  detection	  limit.	  La,	  Eu,	  Yb	  and	  Ce	  are	  plotted	  to	  represent	  the	  behavior	  of	  REEs.	  Population	  size	  for	  each	  lithology	  is	  indicated	  in	  the	  legend	  of	  the	  plots.	  2.6.3 Ranked	  Variable	  Plots	  Ranked	  variable	  plots,	  produced	  by	  the	  ioGAS	  software,	  are	  used	  in	  chapter	  three	  to	  visualize	  spatial	  compositional	  variations	  of	  GRD1a	  due	  to	  alteration	  processes.	  Each	  point	  is	  assigned	  colour	  and	  size	  representative	  of	  an	  equal	  portion	  of	  the	  sample	  population.	  Most	  analytes	  are	  plotted	  with	  10	  bins	  (i.e.	  10	  dots	  of	  a	  distinct	  colour	  and	  size).	  Analytes	  with	  a	  tighter	  concentration	  range,	  or	  samples	  close	  to	  detection	  limit	  contain	  fewer	  bins.	  Point	  size	  increases	  with	  increased	  concentration,	  colours	  are	  scaled	  on	  a	  cold	  (blue)	  to	  hot	  (red/pink)	  spectrum.	  	  2.6.4 Bivariate	  Analysis	  Plots	  of	  analyte	  versus	  analyte	  are	  used	  to	  assess	  correlations	  and	  differences	  between	  elements	  to	  aid	  in	  the	  characterization	  of	  the	  alteration	  assemblages	  and	  lithological	  units.	  This	  evaluation	  focusses	  on	  common	  geochemical	  associations	  (e.g.	  K-­‐Rb,	  Ca-­‐Sr,	  K-­‐Tl,	  Zn-­‐Cd,	  Ca-­‐Eu,	  etc.),	  and	  relationships	  between	  ore	  and	  trace	  metals	  (e.g.	  Cu	  and	  Mo	  with	  the	  key	  traces	  As,	  Au,	  Ag,	  K,	  etc.).	  Samples	  in	  these	  plots	  are	  identified	  by	  lithology.	  	  2.7 Elemental	  Gains	  and	  Losses	  A	  comparison	  of	  fresh	  and	  altered	  whole	  rock	  compositions	  indicates	  which	  elements	  are	  gained	  and	  lost	  during	  the	  alteration	  process.	  In	  order	  to	  quantify	  24	  	  elemental	  variability,	  volume	  or	  mass	  changes	  resulting	  from	  hydrothermal	  alteration	  must	  be	  accounted	  for	  (Gresens	  1967;	  Grant	  1986;	  Appleyard	  1980;	  MacLean	  &	  Barrett	  1993).	  Using	  immobile	  element	  ratios	  as	  a	  proxy	  for	  mass	  and	  volume	  change,	  gains	  and	  losses	  are	  calculated	  using	  the	  formula:	  	  ∆?   =   ? ™? ™∗ ?? − ??	   (1)	  	  Where	  ΔX	  is	  the	  mass	  change	  of	  the	  mobile	  analyte	  in	  g/100	  g,	  (for	  concentrations	  in	  %)	  XAi/XBi	  is	  the	  ratio	  of	  the	  fresh	  (A)	  and	  altered	  (B)	  immobile	  analyte	  and	  X	  is	  the	  concentration	  of	  the	  mobile	  element	  for	  the	  fresh	  (A)	  and	  altered	  (B)	  samples	  (Warren	  et	  al.	  2007).	  This	  equation	  is	  the	  mathematical	  equivalent	  to	  the	  equation	  put	  forth	  by	  Grant	  (1986),	  though	  by	  using	  immobile	  element	  ratios	  it	  is	  not	  necessary	  to	  know	  the	  fresh	  and	  altered	  rock	  densities	  (Warren	  et	  al.	  2007).	  Ti	  is	  used	  as	  the	  immobile	  element	  (Hezarkhani	  2011).	  Elemental	  gains	  and	  losses	  induced	  by	  hydrothermal	  alteration	  have	  been	  determined	  for	  GRD1a	  using	  end	  members,	  selected	  based	  on	  observations	  and	  MER	  diagrams,	  to	  represent	  unaltered	  (fresh)	  rocks	  and	  those	  that	  display	  potassic,	  phyllic	  and	  propylitic	  alteration.	  Hand	  sample	  observations	  and	  a	  combination	  of	  element	  ratio	  plots	  identify	  samples:	  	  G-­‐07a:	  as	  fresh,	  as	  it	  plots	  on	  the	  line	  connecting	  (1,1)	  and	  (1,0),	  at	  the	  known	  composition	  of	  fresh	  plagioclase	  (around	  An45)	  on	  the	  plots	  (2Ca	  +	  Na	  +	  K)/Al	  versus	  2Ca/Al	  and	  Na/Al;	  plots	  on	  the	  fresh	  line	  of	  Al/Ti	  versus	  (2Ca	  +	  Na	  +	  K)/Ti;	  and	  appears	  fresh	  in	  hand	  sample	  	  H-­‐05:	   	  as	  representative	  of	  potassic	  alteration,	  plotting	  with	  low	  Ca	  and	  Na	  and	  high	  K	  on	  the	  plots	  (2Ca	  +	  Na	  +	  K)/Al	  versus	  2Ca/Al,	  Na/Al	  and	  K/Al,	  consistent	  with	  K-­‐feldspar	  alteration	  of	  plagioclase;	  and	  confirmed	  by	  feldspar	  staining	  and	  hand	  sample	  observations	  	  	  	  25	  	  G-­‐03:	   	  as	  representative	  of	  propylitic	  alteration,	  as	  it	  plots	  the	  farthest	  from	  the	  x	  =	  y	  control	  line,	  and	  closest	  to	  the	  epidote	  control	  line	  on	  the	  Al/Ti	  versus	  (2Ca	  +	  Na	  +	  K)/Ti;	  and	  confirmed	  by	  hand	  sample	  observations	  	  O-­‐04:	   	  as	  representative	  of	  phyllic	  alteration;	  plotting	  with	  both	  low	  Ca	  and	  high	  K	  on	  the	  (2Ca	  +	  Na	  +	  K)/Al	  versus	  2Ca/Al	  and	  K/Al,	  indicative	  of	  calcic	  zones	  of	  plagioclase	  altering	  to	  muscovite;	  and	  confirmed	  by	  thin	  section	  observations.	  	  Photographs	  and	  descriptions	  of	  the	  selected	  samples	  are	  found	  in	  Appendix	  B	  and	  C.	  2.8 Molar	  Element	  Ratios	  Pearce	  and	  general	  element	  ratio	  (PER	  and	  GER)	  plots	  are	  used	  in	  chapter	  four	  to	  interpret	  alteration	  processes.	  Molar	  element	  ratio	  (MERs)	  is	  the	  collective	  term	  that	  encompasses	  both	  PER	  and	  GER.	  Molar	  combinations,	  stoichiometrically	  representative	  of	  minerals	  of	  interest,	  are	  plotted	  as	  axes	  to	  show	  trends	  indicative	  of	  a	  process,	  such	  as	  alteration	  (Pearce	  1968).	  	  A	  GER	  uses	  a	  compositionally	  suitable	  denominator	  (e.g.	  Al	  for	  examining	  feldspar	  systematics)	  to	  assess	  chemical	  variation	  relative	  to	  mineral	  nodes.	  Element	  ratios	  are	  presented	  on	  each	  axis	  that	  represent	  a	  mineral	  or	  group	  of	  minerals.	  Feldspar	  space	  is	  commonly	  examined	  using	  (2Ca	  +	  Na	  +	  K),	  abbreviated	  as	  2CNK,	  on	  one	  axis,	  to	  accommodate	  for	  variability	  between	  feldspar	  end	  members	  anorthite,	  albite	  and	  orthoclase.	  The	  diagram	  2CNK/Al	  versus	  Na/Al	  has	  mineral	  nodes	  representing	  albite	  (1,1),	  muscovite	  (1/3,0)	  and	  anorthite/K-­‐feldspar	  (1,0).	  These	  mineral	  nodes	  are	  used	  to	  indicate	  both	  primary	  and	  alteration	  mineral	  composition.	  Mineral	  composition	  determines	  the	  node	  location.	  For	  example,	  albite	  with	  the	  end	  member	  composition	  NaAlSi3O8	  [((2*0	  +	  1	  +	  0)/1),	  (1/1)]	  plots	  as	  (1,1).	  Neither	  of	  the	  end	  members	  anorthite	  (CaAl2Si2O8)	  nor	  K-­‐feldspar	  (KAlSi3O8)	  contains	  any	  Na;	  therefore	  both	  plot	  as	  (1,0).	  	  A	  conserved	  element	  is	  used	  in	  the	  denominator	  for	  PERs,	  which	  allows	  for	  mineral	  control	  lines	  (as	  opposed	  to	  nodes	  as	  in	  GER)	  to	  be	  used	  for	  interpreting	  26processes	  such	  as	  alteration.	  In	  order	  to	  use	  PER	  diagrams	  there	  must	  be	  a	  failure	  to	  reject	  the	  cogenetic	  hypothesis	  (Russell	  &	  Stanley	  1990).	  The	  cogenetic	  hypothesis	  postulates	  that	  each	  rock	  unit,	  at	  some	  point,	  originated	  from	  a	  homogeneous	  system	  (Russell	  &	  Stanley	  1990).	  To	  reject	  the	  cogenetic	  hypothesis,	  two	  potentially	  conserved	  elements	  (or	  oxides)	  are	  plotted	  against	  one	  another,	  treating	  each	  lithology	  separately.	  If	  the	  two	  elements	  are	  conserved	  the	  best-­‐fit	  line	  will	  have	  a	  positive	  slope,	  pass	  through	  the	  origin,	  or	  cross	  the	  axis	  of	  the	  least	  conserved	  element,	  as	  well	  as	  intersect	  the	  analytical	  error	  ellipses	  (representing	  two	  standard	  deviations)	  of	  a	  statistically	  significant	  portion	  of	  samples	  (determined	  by	  population	  size,	  generally	  ~	  95	  %)	  (Stanley,	  unpublished).	  If	  the	  elements	  are	  not	  conserved	  the	  slope	  of	  the	  best	  fit	  line	  will	  be	  negative,	  zero	  or	  infinite;	  or	  will	  not	  intersect	  an	  appropriate	  portion	  of	  the	  error	  ellipses.	  The	  conservation	  of	  Zr	  and	  TiO2,	  both	  high	  field	  strength	  elements	  (HFSE)	  commonly	  determined	  as	  immobile	  elements	  for	  PER	  (e.g.	  Pearce	  1987;	  Whitbread	  &	  Moore	  2004;	  Urqueta	  et	  al.	  2009),	  have	  been	  tested	  for	  each	  lithology;	  TiO2	  is	  deemed	  more	  conserved	  than	  Zr	  and	  is	  used	  as	  the	  immobile	  element	  for	  PER	  assessment	  (Figure	  31).	  The	  PER	  diagrams	  are	  generally	  designed	  to	  have	  a	  specific	  mineral,	  or	  group	  of	  minerals	  of	  interest	  represented	  by	  the	  x	  =	  y	  (slope	  of	  the	  line	  -­‐	  m	  =	  1)	  control	  line	  (Stanley	  &	  Russell,	  1989).	  Control	  lines	  are	  calculated	  using	  mineral	  compositions	  in	  the	  same	  way	  as	  nodes	  in	  GER	  plots,	  and	  are	  two-­‐dimensional	  expressions	  of	  compositional	  planes	  into	  and	  out	  of	  the	  page	  representative	  of	  that	  mineral	  or	  groups	  of	  minerals.	  For	  example	  the	  plot	  Al/Ti	  versus	  2CNK/Ti	  isolates	  all	  feldspar	  variation	  along	  the	  x	  =	  y	  control	  line.	  This	  plot	  also	  displays	  control	  lines	  representing	  epidote	  (m	  =	  2),	  muscovite	  (m	  =	  1/3)	  and	  chlorite	  (m	  =	  0).	  Any	  chemical	  difference	  due	  to	  feldspar	  composition	  (e.g.	  albitic	  alteration,	  or	  igneous	  K-­‐feldspar)	  will	  be	  captured	  in	  the	  plane	  represented	  by	  the	  m	  =	  1	  line;	  chemical	  variability	  introduced	  by	  hydrothermal	  alteration	  to	  epidote	  (propylitic),	  muscovite	  (phyllic)	  or	  chlorite	  (propylitic	  and/or	  phyllic)	  will	  result	  in	  points	  plotting	  away	  from	  the	  feldspar	  control	  line,	  and	  towards	  their	  respective	  alteration	  mineral(s)	  control	  lines.	  One	  advantage	  of	  PER	  over	  GER	  is	  that	  PER	  diagrams	  can	  be	  customized	  to	  maximize	  the	  visualization	  of	  a	  particular	  alteration	  process	  by	  using	  a	  selection	  of	  27	  	  suitable	  minerals,	  for	  instance	  minerals	  representing	  the	  primary	  composition,	  for	  axes	  calculations.	  These	  axes	  are	  calculated	  by	  first	  expressing	  the	  mineral	  compositions	  in	  a	  matrix,	  then	  calculating	  the	  null	  vector	  for	  that	  matrix,	  usually	  using	  mathematical	  software	  such	  as	  MATLAB®	  (modified	  from	  Stanley	  &	  Russell	  1989)	  (Figure	  9).	  This	  null	  vector	  is	  broken	  into	  an	  x	  and	  y	  component	  that	  defines	  a	  plane	  in	  space	  representing	  the	  compositional	  variability	  introduced	  by	  the	  minerals.	  Using	  the	  identified	  x	  and	  y	  components	  as	  the	  axes,	  this	  plane	  becomes	  the	  line	  identified	  by	  x	  =	  y.	  	  28Figure 9: Compositional matrix of anorthite (An), pargasite (Hb), biotite (Bt), albite (Ab) and actinolite (Ac) reduced to x and y vectors representative of the null vector.  These  x and y vectors define a plane that is representative of compositional variability attribute to the primary mineral assemblage  Actino-lite, pargasite, anorthite and albite are used to accomodate for compositional variations in feldspars and hornblende.29	  	  Chapter	  3:	  Characterization	  and	  Evolution	  of	  the	  Lithological	  Units	  in	  a	  Calc-­‐Alkalic	  Porphyry:	  A	  Case	  Study	  of	  the	  Relincho	  Cu-­‐Mo	  Porphyry,	  Atacama,	  Chile	  3.1 Introduction	  	   Lithogeochemical	  sampling	  of	  surface	  rocks	  at	  a	  regional	  scale	  coupled	  with	  robust	  interpretation	  is	  used	  to	  characterize	  lithological	  units	  and	  alteration	  assemblages,	  as	  well	  as	  interpret	  potential	  magmatic	  evolution	  and	  source	  magma	  fertility.	  Mineralization	  at	  the	  Relincho	  PCD	  is	  hosted	  by	  Paleocene	  granodiorite	  of	  the	  Los	  Morteros	  batholith.	  Four	  Paleocene	  porphyritic	  units	  are	  spatially	  and	  genetically	  associated	  with	  Cu-­‐Mo	  mineralization.	  Geochemistry	  is	  used	  to	  identify	  distinguishing	  features	  of	  the	  porphyry	  and	  granodiorite	  units	  for	  characterization,	  to	  understand	  the	  magmatic	  evolution	  of	  the	  lithological	  units,	  and	  to	  characterize	  alteration	  assemblages.	  	  	   Characterization	  of	  the	  granodiorite	  and	  porphyry	  units	  using	  lithogeochemistry,	  petrography	  and	  field	  observations	  distinguishes	  four	  units	  of	  the	  granodiorite	  (GRD1a,	  GRD1b,	  GRD2	  and	  GRD3),	  and	  four	  syn-­‐mineralization	  porphyritic	  units	  (PQF1,	  PQF2,	  PFB,	  and	  PQB).	  An	  evolutionary	  model	  presented	  here	  suggests	  four	  magmatic	  differentiation	  cycles	  associated	  with	  three	  magma	  recharges	  resulting	  in	  an	  evolution	  from	  [GRD1b	  +	  GRD3]	  à	  GRD1a	  à	  [PQF1	  +	  PQF2	  +	  PFB	  +	  PQB]	  à	  GRD2.	  Compositional	  overlaps	  within	  the	  porphyritic	  units	  prohibit	  further	  distinctions.	  	   Results	  from	  the	  characterization	  are	  used	  for	  interpreting	  the	  magmatic	  fertility	  of	  the	  Los	  Morteros	  batholith.	  Magma	  fertility	  plots	  identify	  potentially	  Cu-­‐Mo	  fertile	  source	  magmas	  from	  infertile	  based	  on	  water	  content	  of	  the	  source	  magma.	  The	  GRD1a,	  GRD2	  and	  the	  porphyritic	  units	  are	  identified	  as	  potentially	  Cu-­‐Mo	  fertile	  and	  likely	  from	  a	  high	  magmatic	  water	  content	  magma	  source,	  whereas	  the	  (interpreted)	  early	  granodiorite	  units	  [GRD1b	  +	  GRD3]	  are	  infertile	  from	  a	  water-­‐poor	  source	  magma.	  	   Characterization	  of	  the	  alteration	  fluids	  is	  the	  initial	  step	  in	  understanding	  alteration	  processes	  and	  being	  able	  to	  relatively	  quantify	  alteration.	  Widespread,	  weak	  30to	  moderate	  intensity	  alteration	  associated	  with	  Cu-­‐mineralization	  grades	  outward	  from	  mineralization	  from	  potassic	  proximally	  to	  phyllic	  and	  propylitic	  distally.	  Elemental	  gains	  and	  losses	  for	  potassic,	  propylitic	  and	  phyllic	  alteration	  are	  used	  to	  determine	  fingerprint	  elements	  for	  each	  assemblage	  that	  can	  be	  used	  regionally	  for	  exploration.	  Population	  breaks	  in	  key	  alteration	  elements	  distinguish	  samples	  affected	  by	  alteration	  from	  those	  unaffected.	   	   3.2	  	  Geological	  Setting	  Early	  to	  Late	  Cretaceous	  andesite	  of	  the	  Cerrillos	  Formation	  host	  the	  Paleocene	  granodiorite	  of	  the	  Los	  Morteros	  batholith,	  which	  was	  emplaced	  via	  regional	  north-­‐south	  striking	  extensional	  faulting	  formed	  during	  the	  Jurassic-­‐Early	  Cretaceous	  period	  (Camus	  2007)	  (Figure	  4).	  This	  granodiorite	  hosts	  four	  Paleocene,	  syn-­‐mineralization	  porphyritic	  units,	  emplaced	  along	  a	  seven	  km	  long,	  northwest-­‐southeast	  striking	  series	  of	  mineralized	  porphyry	  centers,	  referred	  to	  as	  the	  porphyry	  corridor	  (Figure	  4).	  Hypogene	  mineralization	  consists	  of	  veinlet-­‐controlled	  and	  disseminated	  bornite,	  chalcopyrite,	  pyrite,	  and	  molybdenite.	  A	  2000	  m	  x	  500	  m	  surface	  exposure	  of	  mineralization	  is	  in	  the	  form	  of	  discontinuous	  copper	  oxide,	  oriented	  approximately	  northwest-­‐southeast	  along	  the	  porphyry	  corridor	  (Teck	  Resouces	  Limited	  2007).	  Mineralization	  is	  related	  to	  a	  large-­‐scale	  hydrothermal	  system	  that	  has	  an	  alteration	  surface	  expression	  of	  approximately	  60	  km2.	  	  3.3	  Lithological	  Units	  A	  project	  scale	  schematic	  geological	  map	  compiled	  from	  point	  data	  and	  regional	  geologic	  map	  are	  presented	  for	  general	  reference	  with	  the	  caveat	  that	  contacts	  between	  lithological	  units	  on	  the	  project	  scale	  map	  are	  approximated,	  being	  based	  on	  sample	  collection	  localities	  rather	  than	  detailed	  lithological	  boundary	  mapping	  (Figure	  6,	  Figure	  10).	  Descriptions	  are	  presented	  chronologically	  from	  oldest	  lithological	  unit	  to	  youngest.	  The	  andesite,	  granodiorite,	  porphyry,	  hydrothermal	  breccia	  and	  post-­‐mineralization	  intrusive	  units	  are	  described,	  though	  only	  the	  granodiorite	  and	  porphyry	  units	  are	  characterized	  geochemically	  as	  they	  are	  related	  to	  the	  magmatic	  source	  of	  mineralization	  and	  its	  alteration	  effects.	  	   	  	  31Figure 10: Schematic geological map of the project area based on point data showing approximate contacts. Porphyry corridor is used for spatial context, note the spatial restrictions for the lithological units, namely GRD1a outcropping largely adjacent to or north of the porphyry corridor.  GRD2, GRD3 and GRD1b outcrop predominantly to the south. Porphyry units are structurally controlled, outcrop-ping near the porphyry corridor, or perpindicular to it32	  	  3.3.1 Andesite	  The	  Early	  Cretaceous,	  Cerrillos	  Formation	  andesite	  was	  emplaced	  subaerially	  (Martínez	  et	  al.	  2013),	  with	  no	  flow	  structures	  observed	  in	  the	  project	  area.	  It	  is	  dark	  grey	  to	  brown,	  jointed	  to	  blocky,	  and	  resistant	  to	  weathering	  in	  outcrop,	  while	  appearing	  dark	  grey-­‐green	  and	  homogeneous	  in	  hand	  sample	  (Figure	  11a,	  b).	  The	  andesite	  is	  plagioclase-­‐phyric	  and	  crowded	  (60	  %	  plagioclase	  phenocrysts)	  with	  a	  fine-­‐grained	  groundmass	  and	  minor	  amounts	  of	  hornblende	  (less	  than	  5	  %).	  Plagioclase	  crystals	  are	  0.05	  –	  0.1	  cm	  long	  and	  sub-­‐angular	  (Figure	  11c,	  d).	  The	  Cerrillos	  Formation	  andesite	  hosts	  the	  granodiorite	  and	  outcrops	  in	  the	  north	  and	  northwest	  region	  of	  the	  project	  area	  (Figure	  4,	  Figure	  10).	  Weak	  propylitic	  alteration	  is	  present	  in	  some	  of	  the	  andesite	  outcrops.	  This	  unit	  has	  not	  been	  characterized	  in	  this	  study	  due	  to	  its	  small	  spatial	  footprint	  in	  the	  project	  area	  and	  hence	  poor	  sample	  representation.	  3.3.2 Granodiorite	  Units	  The	  granodiorite	  units	  outcrop	  throughout	  the	  project	  area.	  They	  are	  spatially	  constrained	  in	  that	  GRD2	  and	  GRD3	  predominantly	  outcrop	  to	  the	  south	  of	  the	  porphyry	  corridor	  (Figure	  10).	  In	  outcrop	  all	  granodiorite	  units	  appear	  similar:	  grey	  to	  pale	  brown-­‐pink,	  competent,	  resistant	  to	  weathering	  and	  blocky	  when	  jointed.	  	  Texture	  and	  mineralogy	  define	  three	  granodiorite	  units:	  GRD1,	  GRD2	  and	  GRD3	  (Table	  2	  and	  Figure	  12a).	  Mineralogically	  the	  three	  units	  are	  comprised	  of	  varying	  quantities	  of	  plagioclase,	  quartz,	  hornblende	  and	  biotite	  with	  trace	  amounts	  of	  apatite,	  titanite,	  ilmenite,	  zircon,	  magnetite	  and	  in	  the	  case	  of	  GRD2	  K-­‐feldspar,	  as	  summarized	  in	  Table	  2	  and	  Figure	  12a.	  In	  hand	  sample	  GRD1	  has	  a	  characteristic	  homogenous,	  medium	  grained,	  idiomorphic	  texture.	  GRD2	  is	  discernable	  by	  its	  hypidiomorphic	  texture,	  relative	  lack	  of	  mafic	  minerals	  and	  distinct	  pink	  colour	  due	  to	  the	  presence	  of	  igneous	  K-­‐feldspar.	  Unit	  GRD3	  has	  a	  relatively	  higher	  hornblende	  and	  biotite	  content	  than	  the	  other	  two	  units,	  and	  a	  distinguishing	  hypidiomorphic	  to	  sub-­‐porphyritic	  texture.	  Igneous	  K-­‐feldspar	  is	  only	  present	  in	  GRD2.	  	   	  3350 cm10 mmFigure 11: Pictures of the Cerrillos Formation andesite in a. outcrop, b. hand sample, c. polarized light thin section and d. cross-polarized light thin section.adcb34 	  Code	   Photograph	   Granular	  Fabric	  Protolith	  Composition	  Hand	  Sample	  Colour	   Lithology	  GRD1a	  n=97	  	  Idiomorphic,	  homogeneous	  Medium	  grained	  60-­‐75%	  plagioclase	  	  	  10-­‐15%	  quartz	  	  	  	  	  	  	  	  	  	  10-­‐15%	  hornblende	  	  	  5-­‐12%	  biotite	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  2-­‐5%	  magnetite	  	  	  	  	  	  	  	  	  	  	  trace	  apatite	  Zr	  <	  150	  ppm	  White-­‐grey	  Biotite-­‐hornblende	  quartz	  diorite	  GRD1b	  n=28	  	  Idiomorphic,	  homogeneous	  Medium	  grained	  60-­‐75%	  plagioclase	  	  10-­‐15%	  quartz	  	  	  	  	  	  	  	  	  	  10-­‐15%	  hornblende	  	  	  5-­‐12%	  biotite	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  2-­‐5%	  magnetite	  	  	  	  	  	  	  	  	  	  	  trace	  apatite	  Zr	  >	  150	  ppm	  White-­‐grey	  Biotite-­‐hornblende	  quartz	  diorite	  GRD2	  n=12	  	  Hypidiomorphic	  Fine-­‐medium	  grained	  20-­‐40%	  plagioclase	  	  15-­‐30%	  K-­‐feldspar	  	  	  35-­‐55%	  quartz	  	  	  	  	  	  	  	  	  	  	  	  	  0-­‐5%	  biotite	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  3-­‐12%	  hornblende	  Pink	  Hornblende	  granodiorite	  GRD3	  n=14	  	  Idiomorphic	  to	  sub-­‐porphyritic	  Fine-­‐medium	  grained	  45-­‐55%	  plagioclase	  	  	  	  5-­‐12%	  quartz	  	  	  	  	  	  	  	  	  	  	  	  	  20-­‐30%	  biotite	  	  	  	  	  	  	  	  	  	  10-­‐15%	  hornblende	  up	  to	  5%	  magnetite	  White-­‐grey	  Hornblende-­‐biotite	  quartz	  diorite	  Table 2: Summary of granodiorite unit properties.  Photographs are of the hand sample (top left), stained section (top right), polished thin section in polarized light (bottom left), and polished thin section in cross-polarized light (bottom right).  Each photograph is of the same area of the same sample, to the same scale.  Lithology classifications are based on quartz-alkali feldspar-plagioclase ternary classifications from Streckeisen, 1976  based on mineral composition from hand sample, thin section, feldspar staining and field observations.  Note that the yellow staining in the GRD1b and GRD3 samples are from K-feldspar alteration, not igneous K-feldspar.35a cbFigure 12: Compositional diagrams indicating variability of a. granodiorite units b. porphyry units, with ground mass depicted as solid co-lours and phenocrysts depicted as hatched, and c. the lithology of each unit, based on observed mineralogical compositions in accordance with  the quartz - alkali feldspar - plagioclase ternary diagram presented by Streckeisen (1976) .36The	  term	  “granodiorite”	  is	  used	  for	  consistency	  with	  current	  practices.	  Only	  GRD2	  is	  a	  granodiorite	  sensu	  stricto	  as	  it	  is	  the	  only	  unit	  that	  contains	  igneous	  K-­‐feldspar.	  Based	  on	  mineralogy	  the	  units	  are:	  biotite-­‐hornblende	  quartz-­‐diorite	  (GRD1);	  hornblende	  granodiorite	  (GRD2);	  and	  hornblende-­‐biotite	  quartz-­‐diorite	  (GRD3),	  in	  accordance	  with	  the	  quartz-­‐alkali	  feldspar-­‐plagioclase	  classification	  scheme	  presented	  by	  Streckeisen	  (1976)	  (Figure	  12c).	  All	  granodiorite	  units	  exhibit	  some	  Cu-­‐Mo	  mineralization,	  with	  GRD1	  and	  GRD3	  being	  the	  most	  mineralized	  and	  GRD2	  least.	  	  The	  granodiorite	  units	  have	  previously	  been	  identified	  in	  property	  scale	  maps	  as	  a	  single	  unit,	  however	  detailed	  observations	  made	  in	  this	  study	  have	  identified	  four	  distinct	  units.	  Geochemistry	  is	  used	  to	  further	  breakdown	  the	  GRD1	  unit	  into	  GRD1a	  and	  GRD1b,	  which	  are	  visually	  indistinguishable.	  Further	  discussion	  is	  found	  in	  the	  “Geochemistry	  of	  Lithological	  Units”	  section	  of	  this	  chapter.	  With	  no	  contacts	  observed	  in	  the	  field	  and	  no	  prior	  subdivision	  of	  the	  granodiorite	  recorded,	  the	  contact	  relationships	  and	  relative	  ages	  of	  these	  units	  are	  unknown.	  	  3.3.3	   Porphyry	  Units	  The	  porphyry	  units	  are	  isolated	  to	  outcropping	  within	  and	  near	  the	  porphyry	  corridor.	  Some	  offshoots	  to	  the	  north	  and	  south	  follow	  regional	  structures	  and	  are	  approximately	  perpendicular	  to	  the	  porphyry	  corridor	  (Figure	  10).	  The	  four	  porphyry	  units	  are	  all	  similar	  in	  appearance	  in	  outcrop.	  In	  outcrop	  the	  porphyry	  units	  are	  beige-­‐pink	  to	  light	  brown,	  massive,	  competent,	  resistant	  to	  weathering	  and	  blocky	  when	  jointed.	  	  In	  hand	  sample	  the	  four	  units	  are	  distinguishable	  by	  texture	  and	  subtle	  variations	  in	  feldspar,	  quartz,	  hornblende	  and	  biotite	  content,	  as	  summarized	  in	  Table	  3	  and	  Figure	  12b.	  PQF1	  is	  aphanitic	  groundmass	  supported	  with	  phenocrysts	  of	  plagioclase,	  rounded	  quartz	  eyes,	  hornblende	  and	  biotite.	  PQF2	  is	  distinguishable	  by	  the	  crowded	  phenocrysts	  of	  plagioclase,	  quartz	  eyes,	  hornblende	  and	  biotite,	  and	  the	  aphanitic	  groundmass.	  PFB	  has	  a	  distinct	  lack	  of	  quartz	  eyes,	  while	  containing	  crowded	  plagioclase,	  hornblende	  and	  biotite	  phenocrysts	  and	  a	  fine-­‐grained	  groundmass.	  PQB	  is	  aphanitic	  groundmass	  supported,	  containing	  plagioclase,	  sub-­‐rounded	  quartz	  eyes,	  hornblende	  and	  biotite	  phenocrysts.	  	  	  37	  CgSW	   KbgmgakMhb	   KbWfgRkqlml	  KkghWkmcWl	  FkgnfSeMll	  KkghWkmcWl	  Icmbgdgaq	  KLB	  f702	  	  12y326	  hbWfgRkqlms	  lhMklWdq	  RkgpSWSt	  	  0y,26	  lnPykgnfSWSs	  ,	  Re	  inMkmr	  WqWl	  -­‐zy126	  hdMacgRdMlW	  Ml	  zu2	  Re	  lnPyMfandMk	  mg	  lnPykgnfSWS	  RkqlmMdl	  0y26	  bgkfPdWfSW	  2y,z6	  PcgmcmW	  02y226	  MhbMfcmcR	  akgnfSeMll	  lnhhgkmWS	  	  226	  inMkmr	  126	  HyZWdSlhMk	  	  GgkfPdWfSWyPcgmcmW	  egfrgakMfcmW	  KDB	  f7-­‐4	  	  22y326	  hbWfgRkqlms	  RkgpSWSt	  	  zy06	  lnPyMfandMks	  zu-­‐	  Re	  inMkmr	  WqWl	  1zy226	  hdMacgRdMlW	  Ml	  ,Re	  lnPykgnfSWS	  MfS	  zu-­‐	  Re	  lnPyMfandMk	  RkqlmMdl	  0y36	  bgkfPdWfSW	  1y,z6	  PcgmcmW	  02y126	  ZcfWyakMcfWS	  akgnfSeMlls	  hbWfgRkqlm	  lnhhgkmWS	  	  226	  inMkmr	  126	  HyZWdSlhMk	  	  GgkfPdWfSWyPcgmcmW	  akMfgScgkcmW	  KLD-­‐	  f7,1	  	  3zy426	  hbWfgRkqlmls	  RkgpSWSt	  	  2y46	  kgnfSWSs	  zu2Re	  inMkmr	  WqWl	  12y226	  hdMacgRdMlW	  Ml	  ,Re	  dMmbl	  gk	  zu2Re	  lnPykgnfSWS	  RkqlmMdl	  0y26	  WnbWSkMd	  bgkfPdWfSW	  2y56	  WnbWSkMd	  PcgmcmW	  -­‐2y1z6	  MhbMfcmcR	  akgnfSeMlls	  hbWfgRkqlm	  lnhhgkmWS	  	  2-­‐6	  inMkmr	  106	  HyZWdSlhMk	  26	  ldcoWkl	  gZ	  PcgmcmW	  GgkfPdWfSWyPcgmcmW	  akMfgScgkcmW	  KLD,	  f70-­‐	  	  22y326	  hbWfgRkqlmls	  lhMklWdq	  RkgpSWSt	  	  2y,-­‐6	  kgnfSWS	  inMkmr	  WqWl	  -­‐2y126	  hdMacgRdMlW	  Ml	  zu2	  Re	  dMmbl	  gk	  zu-­‐2	  Re	  lnPykgnfSWS	  RkqlmMdl	  -­‐y26	  WnbWSkMd	  bgkfPdWfSWs	  0y46	  WnbWSkMd	  PcgmcmW	  02y126	  MhbMfcmcR	  akgnfSeMll	  lnhhgkmWSu	  	  206	  inMkmr	  116	  HyZWdSlhMk	  06	  PcgmcmW	  GgkfPdWfSWyPcgmcmW	  akMfgScgkcmW	  	  Table 3:  Summary of porphyry unit properties.  Photographs are of the hand sample (top left), stained section (top right), polished thin section in polarized light (bottom left), and polished thin section in cross-polarized light (bottom right).  Each photograph is of the same area of the same sample, to the same scale. Lithology classifications are based on quartz-alkali feldspar-plagioclase ternary classifications from Streckeisen, 1976  based on mineral composition from hand sample, thin section, feldspar staining and field observations.38	  	  All	  four	  porphyry	  units	  contain	  K-­‐feldspar	  and	  quartz	  in	  their	  groundmass.	  Mineralogically	  PQF1,	  PQF2	  and	  PFB	  are	  hornblende-­‐biotite	  granodiorite	  and	  the	  PQB	  is	  a	  hornblende-­‐biotite	  monzogranite,	  in	  accordance	  with	  the	  classification	  scheme	  presented	  by	  Streckeisen	  (1976)(Figure	  12c).	  All	  porphyry	  units	  show	  some	  Cu-­‐Mo	  mineralization,	  with	  PQF1	  being	  most	  strongly	  so,	  followed	  by	  PQF2,	  PFB	  and	  PQB.	  Observed	  crosscutting	  relationships	  and	  mineralization	  aid	  in	  determining	  the	  relative	  ages	  of	  the	  porphyry	  units.	  Based	  on	  cross	  cutting	  relationships,	  PQB	  is	  the	  youngest	  porphyry	  unit.	  Mapping	  and	  age	  dating	  by	  Teck	  Resources	  Limited	  indicate	  that	  PQF1	  is	  oldest,	  followed	  by	  PQF2,	  PFB	  and	  PQB.	  All	  four	  porphyry	  units	  are	  mineralized.	  3.3.4 Hydrothermal	  Breccia	  Hydrothermal	  breccia	  (BX)	  outcrops	  along	  the	  porphyry	  corridor	  (Figure	  10).	  It	  is	  a	  polymictic,	  matrix	  supported	  breccia	  with	  angular	  to	  sub-­‐angular	  granodiorite	  and/or	  porphyry	  clasts	  (0.5	  –	  3cm)	  depending	  on	  contact	  lithology,	  with	  a	  mafic	  rich	  matrix	  (Figure	  13).	  The	  breccia	  unit	  is	  generally	  isolated	  to	  the	  area	  directly	  adjacent	  to	  porphyry	  –	  granodiorite	  contacts	  and	  typically	  contains	  mineralization	  in	  the	  matrix	  and	  clasts.	  This	  unit	  has	  not	  been	  characterized	  in	  this	  study	  due	  to	  limited	  spatial	  coverage	  and	  polymictic	  nature	  making	  them	  poor	  candidates	  for	  lithogeochemical	  assessment.	  	  3.3.5 Post-­‐Mineralization	  Dikes	  Post-­‐mineralization	  dikes	  (PM)	  follow	  northeast-­‐southwest	  structures,	  outcropping	  as	  long,	  slender	  bodies	  (Figure	  10).	  They	  intrude	  the	  porphyry	  and	  granodiorite	  units	  in	  the	  project	  area.	  The	  dykes	  are	  dacitic	  with	  textures	  ranging	  from	  fine-­‐grained,	  idiomorphic	  to,	  more	  typically,	  porphyritic	  (Figure	  14).	  Porphyritic	  dikes	  are	  groundmass	  supported	  with	  15-­‐40%	  sub-­‐rounded	  plagioclase	  phenocrysts,	  7-­‐15%	  hornblende	  phenocrysts	  and	  1-­‐10%	  quartz	  eyes.	  This	  unit	  has	  not	  been	  characterized	  in	  this	  study	  due	  to	  poor	  spatial	  distribution	  and	  hence	  poor	  representation	  in	  the	  sample	  suite.	  Given	  that	  these	  dykes	  are	  post	  mineralization,	  lithogeochemical	  assessment	  of	  them	  would	  not	  add	  significant	  information	  as	  they	  post	  date	  alteration	  processes.	  3910 mm1 m10 mmFigure 13: Pictures of the hydrothermal breccia in a. outcrop, b. hand sample, c. stained section d. polarized light thin section and e. cross-polarized light thin section.abcdd401 m 4 cmFigure 14: Pictures of the post mineralization dikes in a. outcrop and b. hand sample.a. b.41	  	  3.4 Alteration	  Alteration	  assemblages	  exhibited	  in	  the	  project	  area	  are	  potassic,	  propylitic	  and	  phyllic	  defined	  as:	  	  Potassic	  Assemblage:	  	   secondary	  biotite	  +	  K-­‐feldspar	  +	  magnetite	  +	  ±	  glassy	  limonite	  (from	  chalcopyrite	  weathering	  at	  surface)	  	  Propylitic	  Assemblage:	  	   epidote	  +	  chlorite	  +	  hematite	  ±	  albite	  ±	  calcite	  ±	  pyrite	  	  Phyllic	  Assemblage:	  	   	   chlorite	  +	  muscovite	  +	  quartz	  ±	  calcite	  ±	  hematite.	  	  	  With	  key	  assemblage	  indicator	  minerals	  in	  bold.	  Potassic,	  propylitic	  and	  phyllic	  alteration	  affects	  all	  granodiorite	  and	  porphyry	  units,	  with	  the	  exception	  of	  PQB,	  which	  is	  not	  affected	  by	  potassic	  alteration.	  Late-­‐stage,	  widespread	  chlorite	  alteration	  affects	  the	  entire	  project	  area.	  Alteration	  intensities	  are	  described	  as:	  unaltered	  (<	  15%	  replacement	  of	  the	  primary	  mineralogy	  by	  the	  alteration	  mineralogy);	  weak	  (15%	  ≤	 replacement	  <	  30%);	  moderate	  (30%	  ≤	 replacement	  <	  60%);	  or	  strong	  (≥	  60%	  replacement).	  A	  schematic	  alteration	  map	  based	  on	  hand	  sample,	  field	  and	  thin	  section	  observations	  indicates	  the	  extent	  of	  weak	  alteration	  (Figure	  15).	  Alteration	  mineralogy	  shows	  an	  overall	  proximal	  to	  distal	  pattern	  of	  potassic	  (up	  to	  200	  m	  from	  the	  porphyry	  corridor)	  –	  phyllic	  (within	  100	  m	  of	  mineralization	  with	  structurally	  controlled	  outcrops	  distally)	  -­‐	  propylitic	  (up	  to	  2.5	  km	  from	  the	  porphyry	  corridor)	  alteration	  progressing	  outward	  from	  the	  porphyry	  corridor.	  Cu	  sulphide	  mineralization	  is	  spatially	  related	  to	  potassic	  alteration.	  Propylitic	  alteration	  has	  the	  largest	  footprint.	  Patterns	  of	  overprinting	  alteration	  minerals	  indicate	  that	  the	  potassic	  alteration	  occurred	  first,	  followed	  by	  propylitic	  and	  phyllic,	  consistent	  with	  conventional	  porphyry	  models	  (Lowell	  &	  Guilbert	  1970;	  Seedorff	  2005;	  Sillitoe	  2010).	  	   	  42dcbaFigure 15: Spatial extent of alteration assemblage and examples of minerals diagnostic of each as-semblage a. Spatial extent of weak alteration based on hand sample, petrography and field observa-tions. The potassic alteration occurs in the porphyry corridor or within 200 m, with some structurally controlled distal expressions. Phyllic alteration is observed within 100 m of the porphyry corridor with some structurally controlled distal expressions. Propylitic alteration is expressed up to 2.5 km away. b. Potassic assemblage is defined by the presence of secondary biotite and K-feldspar. Moderate K-feld-spar replacement of plagioclase, strong secondary biotite replacement of hornblende and K-feldspar haloes around glassy limonite veins is indicative of moderate intensity potassic alteration.  Thin section photographs shows biotite replacement of a hornblende site being overprinted by chlorite alteration indicating propylitic or phyllic alteration overprinting of the potassic. c. Propylitic alteration is charac-terized by the presence of chlorite and epidote. Photographs indicate strong alteration of plagioclase and hornblende by epidote. The presence of K-feldspar indicates propylitic overprinting of potassic alteration. d. Phyllic alteration is defined by muscovite and chlorite. Thin section photographs show weak muscovite alteration of calcic zones in plagioclase, and weak calcite alteration of feldspar.43	  	  3.4.1 Potassic	  Alteration	  	   Potassic	  alteration	  is	  generally	  constrained	  to	  in,	  or	  within	  200	  m	  of	  the	  porphyry	  corridor	  (Figure	  15a).	  Secondary	  biotite	  and	  K-­‐feldspar	  alteration	  are	  definitive	  of	  the	  assemblage	  (Figure	  15b).	  Secondary	  biotite	  alters	  biotite	  and	  hornblende.	  It	  is	  identified	  by	  its	  well-­‐developed	  shredded	  texture	  and	  distinct	  beer-­‐bottle-­‐brown	  colour.	  K-­‐feldspar	  alteration	  tends	  to	  be	  incipient	  and	  difficult	  to	  identify	  in	  the	  field.	  Potassic	  alteration	  is	  associated	  with	  disseminated	  Cu-­‐Mo	  mineralization	  in	  the	  form	  of	  chalcopyrite,	  molybdenite,	  and	  bornite,	  in	  addition	  to	  veins	  of	  chalcopyrite	  ±	  bornite	  ±	  molybdenite.	  Where	  oxidized,	  chalcopyrite	  has	  been	  changed	  to	  glassy	  limonite.	  	  3.4.2 Propylitic	  Alteration	  The	  propylitic	  alteration	  has	  the	  largest	  footprint	  of	  the	  alteration	  assemblages,	  extending	  up	  to	  2.5	  km	  away	  from	  the	  porphyry	  corridor	  (Figure	  15c).	  Epidote	  and	  chlorite	  are	  diagnostic	  of	  the	  propylitic	  assemblage.	  Alteration	  intensities	  vary	  from	  weak	  to	  strong.	  Strong	  propylitic	  alteration	  is	  defined	  by	  strong	  replacement	  of	  hornblende	  and	  moderate	  replacement	  of	  plagioclase	  by	  epidote	  (Figure	  15a).	  Albite	  replacement,	  where	  present,	  is	  weak	  and	  only	  apparent	  by	  an	  increased	  hardness	  of	  the	  plagioclase.	  Calcite,	  where	  present,	  replaces	  hornblende	  and/or	  plagioclase	  and/or	  is	  associated	  with	  veinlets.	  Pyrite	  has	  been	  largely	  destroyed	  by	  oxidation,	  though	  rusted	  pits	  are	  indicative	  of	  its	  existence.	  	  In	  places,	  propylitic	  alteration	  overprints	  potassic	  alteration.	  These	  cases	  show	  incongruent	  mineral	  associations,	  such	  as	  epidote	  in	  the	  same	  sample	  as	  incipient	  K-­‐feldspar	  alteration	  of	  plagioclase,	  or	  overprinting	  mineralogical	  textures	  such	  as	  chlorite	  overprinting	  secondary	  biotite.	  	  Incipient	  to	  pervasive	  chlorite	  replacement	  of	  hornblende	  and	  biotite	  is	  a	  product	  of	  phyllic,	  propylitic	  and	  late-­‐stage	  chlorite	  alteration.	  In	  order	  to	  differentiate	  between	  these	  alteration	  styles,	  epidote	  or	  muscovite	  must	  be	  identified	  in	  conjunction	  with	  chlorite	  to	  define	  alteration	  as	  part	  of	  either	  the	  phyllic	  or	  propylitic	  assemblage.	  3.4.3 Phyllic	  Alteration	  Phyllic	  alteration	  generally	  occurs	  within	  100	  m	  of	  the	  porphyry	  corridor	  with	  isolated,	  structurally	  controlled	  outcrops	  distally	  (Figure	  15a).	  It	  is	  defined	  by	  the	  44	  	  presence	  of	  chlorite	  and	  muscovite	  with	  sporadic	  carbonate	  (Figure	  15d).	  Muscovite	  alteration	  affects	  hornblende,	  biotite	  and	  calcic	  zones	  in	  plagioclase.	  The	  alteration	  of	  plagioclase	  by	  muscovite	  can	  resemble	  K-­‐feldspar	  alteration,	  as	  it	  tends	  to	  be	  pink,	  though	  it	  is	  much	  softer	  than	  K-­‐feldspar	  alteration.	  Quartz	  ±	  chlorite	  veins	  are	  also	  associated	  with	  phyllic	  alteration.	  The	  phyllic	  assemblage	  is	  not	  associated	  with	  supergene	  mobilization	  of	  mineralization,	  though	  it	  may	  contain	  pyrite,	  which	  has	  been	  oxidized	  and	  is	  now	  indicated	  by	  rusted	  vugs.	  Hematite	  is	  commonly	  associated	  with	  the	  phyllic	  assemblage	  and	  is	  interpreted	  to	  be	  a	  product	  of	  phyllic-­‐related	  magnetite	  destruction.	  Phyllic	  alteration	  locally	  overprints	  the	  potassic	  and/or	  propylitic	  assemblages.	  These	  cases	  show	  incongruent	  mineral	  associations,	  such	  as	  muscovite	  alteration	  of	  plagioclase	  adjacent	  to	  secondary	  biotite	  or	  epidote.	  Overprinting	  mineral	  textures,	  such	  as	  muscovite	  overprinting	  secondary	  biotite	  or	  chlorite,	  are	  also	  indicative	  of	  phyllic	  overprinting	  of	  potassic	  or	  propylitic	  alteration	  assemblages	  respectively.	  	  	  3.5 Geochemistry	  of	  Lithological	  Units	  Granodiorite	  units	  are	  distinctive	  geochemically	  from	  each	  other,	  though	  the	  porphyry	  units	  are	  much	  less	  so.	  Tukey,	  bivariate,	  univariate,	  immobile	  element,	  and	  REE	  plots	  along	  with	  radiometric	  imaging	  are	  used	  to	  differentiate	  and	  characterize	  the	  lithological	  units.	  Due	  to	  the	  incipient,	  widespread	  nature	  of	  alteration,	  most	  alteration	  is	  weak	  to	  moderate,	  and	  no	  samples	  are	  truly	  fresh.	  For	  the	  lithological	  characterization	  all	  sample	  results	  are	  used	  with	  no	  distinction	  between	  altered	  and	  fresh	  rocks.	  Summary	  statistics	  for	  diagnostic	  analytes	  are	  found	  in	  Table	  5.	  	  3.5.1 Granodiorite	  Units	  Field	  observations	  distinguish	  three	  granodiorite	  units:	  GRD1,	  GRD2	  and	  GRD3.	  Lithogeochemistry	  identifies	  two	  populations	  within	  the	  GRD1	  unit:	  GRD1a	  and	  GRD1b.	  GRD1b	  is	  visually	  indistinguishable	  from	  GRD1a,	  though	  chemically	  GRD1b	  is	  more	  similar	  to	  GRD3.	  The	  granodiorite	  units,	  therefore,	  are	  separated	  into	  three	  geochemically	  distinct	  groups:	  GRD1a,	  GRD2	  and	  [GRD1b	  +	  GRD3].	  	  45	  	  Tukey	  plots	  demonstrate	  the	  general	  compositional	  ranges	  between	  units	  (Table	  4,	  Figure	  16).	  These	  Tukey	  plots	  display	  10	  %	  of	  samples	  as	  outliers,	  with	  the	  number	  of	  outliers	  being	  directly	  proportional	  to	  population	  size.	  As	  GRD1a	  has	  the	  largest	  sample	  population,	  it	  also	  has	  the	  most	  outliers	  (10).	  Relative	  standard	  deviations	  (RSD)	  calculated	  for	  selected	  elements	  gives	  a	  better	  indication	  of	  compositional	  variance	  within	  a	  unit	  (Table	  5).	  	  GRD2	  and	  [GRD1b	  +	  GRD3]	  are	  the	  compositional	  end	  members	  of	  the	  granodiorite	  units.	  With	  respect	  to	  the	  other	  granodiorite	  units,	  GRD2	  has	  higher	  concentrations	  of	  K2O	  and	  SiO2	  due	  to	  the	  igneous	  K-­‐feldspar	  and	  elevated	  quartz	  content,	  not	  present	  in	  the	  other	  granodiorite	  units.	  [GRD1b	  +	  GRD3]	  shows	  elevated	  TiO2,	  Fe2O3,	  Cr2O3,	  MnO	  and	  MgO	  relative	  to	  the	  other	  granodiorite	  units,	  consistent	  with	  a	  higher	  mafic	  mineral	  content	  in	  [GRD1b	  +	  GRD3].	  GRD1a	  contains	  slightly	  more	  Na2O	  than	  the	  other	  granodiorite	  units,	  consistent	  with	  a	  more	  plagioclase	  dominant	  rock.	  All	  four	  units	  show	  some	  mineralization.	  Major	  oxide	  and	  immobile	  element	  plots	  show	  that	  GRD1a	  clusters	  tightly	  relative	  to	  other	  lithological	  units,	  generally	  between	  the	  compositions	  of	  [GRD1b	  +	  GRD3]	  and	  GRD2	  (Figure	  17).	  Generally	  speaking,	  GRD2	  is	  slightly	  depleted	  and	  GRD1b	  slightly	  enriched	  in	  the	  light	  rare	  earth	  elements	  (LREEs)	  relative	  to	  GRD1a	  and	  GRD3	  (Figure	  20).	  REEs	  normalized	  to	  mid-­‐ocean	  ridge	  basalt	  (N-­‐MORB)	  show	  lower	  heavy	  rare	  earth	  elements	  (HREEs)	  concentrations	  in	  GRD1a	  and	  GRD2	  relative	  to	  GRD1b	  +	  GRD3,	  consistent	  with	  hornblende	  fractionation	  in	  the	  source	  magma	  of	  GRD1a	  and	  GRD2	  (Davidson	  et	  al.	  2013).	  Negative	  Eu	  anomalies	  in	  [GRD1b	  +	  GRD3]	  and	  GRD2,	  but	  not	  in	  GRD1a	  (Figure	  20)	  are	  associated	  with	  plagioclase	  fractionation	  and	  removal	  from	  the	  source	  magma	  (Davidson	  et	  al.	  2013).	  	  Radiometric	  K-­‐eU-­‐eTh	  imaging	  proves	  a	  useful	  tool	  for	  discriminating	  between	  the	  granodiorite	  units.	  Consistent	  with	  K2O,	  Th	  and	  U	  variations	  in	  the	  geochemistry,	  the	  radiometric	  image	  shows	  a	  distinct	  boundary	  between	  the	  GRD1a	  in	  the	  north,	  a	  radiometric	  low,	  and	  GRD1b,	  GRD2,	  GRD3,	  and	  the	  porphyry	  units	  to	  the	  south,	  represented	  by	  a	  radiometric	  high	  (Figure	  18a	  and	  b).	  This	  is	  a	  product	  of	  the	  low	  K2O,	  Th	  and	  U	  concentrations	  in	  GRD1a	  relative	  to	  GRD1b,	  GRD2	  and	  GRD3	  (Figure	  18a).	  	  	   	  46Unit	   Elevated	   Depleted	  GRD2	   SiO2,	  K2O,	  U	  Fe2O3,	  MgO,	  MnO,	  Cr2O3,	  TiO2,	  Tl,	  Li,	  Ni,	  V,Zr,	  V,	  Sc,	  Rb,	  Zn,	  Ni,	  	  LREEs,	  HREEs	  GRD1a	   Li,	  Ga,Sr	   U,	  Th,	  Rb,	  Cs,	  Ta,	  As,	  HREEs,	  LREEs	  GRD3	  Fe2O3,	  MgO,	  MnO,	  Cr2O3,	  TiO2,	  Tl,	  Li,	  Ni,	  U,	  HREEs,	  Zr,	  Y,	  V,	  Sc,	  Hf	  SiO2	  GRD1b	  Fe2O3,	  MgO,	  MnO,	  Cr2O3,	  TiO2,	  Tl,	  Li,	  Ni,U,	  HREEs	  Eu,	  Zr,	  Y,	  V,	  Sc,	  Hf	  SiO2	  	  	   	  	   	  	  PQB	   MnO,	  P2O5,	  Zn,	  Pb,	  LREEs,	  HREEs	   Mo,	  Cu,	  Ag,	  As	  PFB	   SiO2,	  K2O,	  Ag,	  Mo,	  Cu,	  As,	  W,	  Rb,	  Re	  Al2O3,	  CaO,	  TiO2,	  Fe2O3,	  MgO,	  CaO,	  TiO2,	  P2O5,	  MnO,	  Zn,	  Ni,	  HREEs,	  LREEs,	  Tm,	  Y	  PQF2	   Pb,	  	  	  PQF1	   Al2O3,	  CaO,	  TiO2,	  Ni,	  Mn,	  Co,	  V,	  Sc	   SiO2,	  K2O,	  U,	  Ta,	  Th	  	  Table 4:  Summary of Tukey plot observations for distinguishing lithological units chemically.Higher Concentration Range Lower Concentration Range 47     GRD2(12)     PQB(35)     PFB(27)    PQF2(14)     PQF1(32)      GRD1a(97)      GRD3(14)    GRD1b(28)Figure 16: Tukey diagrams are arranged by lithology in the order of interpreted chronology to assess compositional differences between lithological units, and overall compositional trends with magmatic evolution.  Boxes represent the interquartile range defined as the 50% of the data lying between the first and third quartile. Outliers, shown as hollow circles are points beyond 1.5 * (Q3-Q1). Extreme outli-ers, hollow triangles, fall outside of 3.0 * (Q3-Q1). Whiskers extend to extreme values that are not outli-ers, i.e. fall within 1.5 * (Q3-Q1)).  The mean is indicated as the solid black dot, the median as a black line.  Some concentrations (Cu, Mo, Pb, Zn, Ag, Mn, Co, Bi, Mn, As, Au, Ce, Sb and Bi) are shown on a log scale to better represent the compositional spread.  Population sizes are indicated in  brackets next to the lithology above the plots.48    GRD2(12)     PQB(35)     PFB(27)    PQF2(14)     PQF1(32)      GRD1a(97)     GRD3(14)    GRD1b(28)Figure 16: Continued49    GRD2(12)     PQB(35)     PFB(27)    PQF2(14)     PQF1(32)      GRD1a(97)      GRD3(14)    GRD1b(28) Figure 16: Continued50    GRD2(12)     PQB(35)     PFB(27)    PQF2(14)     PQF1(32)      GRD1a(97)      GRD3(14)    GRD1b(28) Figure 16: Continued51SiO 2 wt%K 2 O wt%Al 2 O 3 wt%TiO 2 wt%Mo ppmCu   ppmEu ppmHo ppmYb ppmZr ppmTh ppmU ppmmin 59.8 0.26 13.85 0.28 0.12 1.55 0.52 0.14 0.34 97.3 2 0.6max 73.44 4.83 19.75 0.61 230 9930 1.03 0.46 1.37 161 22.3 4.1mean 65.70 2.08 16.93 0.46 4.93 538.79 0.76 0.24 0.60 122.65 4.99 1.25median 65.69 2.25 16.94 0.46 0.525 46.835 0.75 0.22 0.54 122.9 4 1.1stdev 1.62 0.85 0.65 0.05 23.92 1344.17 0.09 0.07 0.21 12.56 3.04 0.66RSD 2% 41% 4% 11% 485% 249% 11% 28% 35% 10% 61% 53%min 59.44 0.72 14.16 0.38 0.34 5.85 0.68 0.42 1.07 154.8 4.1 1.2max 69.64 4.6 17.46 0.77 10 5900 1.05 1.14 3.42 306.9 29.7 7.5mean 64.35 3.21 15.93 0.61 1.37 473.01 0.83 0.62 1.74 196.86 15.56 3.94median 63.59 3.25 15.93 0.61 0.81 92.82 0.82 0.6 1.6 190.9 15.4 3.6stdev 2.33 0.74 0.66 0.09 1.88 1132.16 0.09 0.15 0.53 32.68 4.61 1.25RSD 4% 23% 4% 15% 137% 239% 10% 24% 30% 17% 30% 32%min 60.49 1.04 12.35 0.1 0.44 2.32 0.19 0.1 0.31 53.5 3.6 0.8max 77.37 8.43 18.88 0.45 10.84 533.03 1.02 0.48 1.57 157.2 45.4 9.8mean 70.41 4.95 15.11 0.27 2.86 219.47 0.49 0.25 0.79 98.35 16.35 3.45median 72.2 5.22 14.44 0.21 1.32 207.08 0.41 0.22 0.59 92.9 14.7 3.1stdev 5.66 2.29 2.36 0.15 3.59 165.40 0.27 0.13 0.47 33.66 13.08 2.53RSD 8% 46% 16% 57% 126% 75% 54% 52% 60% 34% 80% 73%min 54.76 1.57 11.74 0.43 0.22 30.33 0.4 0.27 0.89 106.6 4.2 0.9max 69.43 4.49 18.09 0.93 290 15880 1.18 1.14 3.32 306.8 22.2 15.1mean 62.99 3.01 16.09 0.62 22.06 1423.39 0.83 0.54 1.54 177.24 12.53 3.87median 63.56 3.225 16.445 0.59 0.63 127.105 0.81 0.525 1.475 173.75 13.8 3.4stdev 4.77 1.07 1.71 0.14 77.15 4179.63 0.17 0.20 0.60 62.74 6.28 3.52RSD 8% 36% 11% 23% 350% 294% 21% 36% 39% 35% 50% 91%min 66.34 3.18 13.95 0.27 0.22 3.19 0.37 0.09 0.28 107.9 4.5 0.9max 72.2 5.55 16.56 0.44 10 2940 1.02 0.37 1.44 537 10.1 2.6mean 68.80 3.95 15.66 0.33 1.55 247.45 0.63 0.19 0.56 142.19 6.12 1.49median 68.675 3.935 15.705 0.33 0.5 32.47 0.625 0.19 0.525 129.45 6.05 1.4stdev 1.27 0.53 0.50 0.04 2.63 588.10 0.11 0.05 0.18 70.60 1.10 0.38RSD 2% 13% 3% 13% 170% 238% 18% 24% 32% 50% 18% 26%min 64.51 2.14 15.71 0.32 0.16 2.05 0.54 0.13 0.37 94.3 4 0.8max 68.63 4.27 17.56 0.46 30 3310 0.79 0.29 0.66 147.3 6.5 1.6mean 66.83 3.09 16.51 0.40 2.60 479.68 0.68 0.20 0.51 122.24 4.77 1.20median 66.53 2.98 16.51 0.41 0.69 172.9 0.68 0.2 0.52 121.9 4.6 1.2stdev 1.18 0.58 0.51 0.03 5.92 853.79 0.06 0.04 0.09 13.51 0.61 0.22RSD 2% 19% 3% 8% 227% 178% 9% 19% 17% 11% 13% 18%min 65.32 0.65 15.22 0.26 0.2 4.52 0.46 0.13 0.37 105.9 5 0.9max 70.07 5.75 16.4 0.4 10 2670 0.8 0.2 0.63 133.3 7 2.4mean 68.38 3.55 15.73 0.32 1.82 446.87 0.60 0.18 0.49 115.76 5.96 1.44median 68.735 3.545 15.765 0.32 0.91 188.96 0.575 0.175 0.49 114.2 6 1.4stdev 1.19 1.06 0.33 0.04 2.63 728.07 0.09 0.02 0.07 8.45 0.57 0.41RSD 2% 30% 2% 13% 144% 163% 15% 13% 14% 7% 10% 28%min 59.97 1.17 12.69 0.14 0.19 5.55 0.22 0.07 0.17 64.8 3.2 0.9max 73.81 8.11 17.58 0.42 110.95 6980 0.72 0.25 0.85 153.3 8.4 2.3mean 69.27 4.38 15.41 0.31 13.48 784.38 0.54 0.17 0.47 114.49 5.57 1.54median 69.41 4.235 15.515 0.315 6.835 332.595 0.555 0.17 0.48 118.35 5.5 1.6stdev 2.25 1.11 0.82 0.06 21.14 1338.40 0.13 0.04 0.13 18.92 1.15 0.38RSD 3% 25% 5% 18% 157% 171% 24% 22% 27% 17% 21% 24%PQB   n=35GRD1b  n=28GRD1a  n=97GRD2  n=12GRD3   n=14PQF1   n=32PQF2 n=14PFB   n=27Table 5: Summary statistics for major oxides, HREEs Cu and Mo for porphyry and granodiorite units.  Porphyry units have considerable compositional overlap, though some distinction can be made from the K2O, Zr, Th, and the HREE concentrations.  Granodiorite units are best distinguished using TiO2, Zr, K2O, U and Th.52adcbFigure 17: Major oxide and immobile element plots for granodiorite units. a. Zr v TiO2: GRD1a clusters tightly relative to other units. GRD2 contains the least Zr ans TiO2 of the granodiorite units, and GRD1b + GRD3 the most. b. K2O v TiO2: GRD1a clusters tightly relative to other units.  GRD2 shows increased K2O, consistent with igneous K-feldspar content. GRD3 + GRD1b have increased TiO2, consistent with a higher mafic component.  c. SiO2 v MgO: GRD1a clusters tightly between GRD2 and GRD1b + GRD3.  Relatively high SiO2 and low mafic content apparent in GRD2 points.  High MgO due to high mafic con-tent in  GRD1b + GRD3. d. K2O v Al2O3.  K2O content generally increases from GRD1a to GRD1b+GRD3 to GRD2.  High variability in Al2O3 in GRD 2 and GRD1b+GRD3.  Summary statistics for these analytes are found in Table 3.53a bU= 0.6 ppmU= 15.1 ppm0.712.0Figure 18: Radiometric analytes distinguish the GRD1a unit from the GRD2, GRD3 and GRD1b sub-units. a. Radiometric diagram of K2O (wt%) versus Th (ppm) with U (ppm) for size show a tight cluster of GRD1a points with low Th, K2O and U concentrations. Concentrations gradually increase in GRD3 and GRD1b, which have the highest U concentrations.  GRD2 has the highest Th and K2O concentrai-tons, but lower U than GRD1b and GRD3. b. Radiometric image draped over an airphoto, with points coloured by granodiorite sub-unit and sized using the formula , where the sample content is divided by the mean of the entire granodiorite population (i.e. the mean of GRD1a, GRD1b, GRD2 and GRD3 combined). This plot emphasizes the spatial relationships between the granodiorite sub-units and the effectiveness of using a radiometric image to predict lithology.54	  	  3.5.2 Porphyry	  Units	  The	  porphyry	  units	  generally	  lie	  within	  the	  compositional	  range	  defined	  by	  GRD1a	  and	  GRD2,	  and	  are	  least	  similar	  to	  the	  group	  [GRD1b	  +	  GRD3]	  (Figure	  17,	  Figure	  19	  and	  Table	  5).	  Major	  oxides	  SiO2,	  TiO2,	  Al2O3	  and	  K2O	  are	  useful	  for	  breaking	  out	  PFB	  and	  PQF1	  as	  compositional	  end	  members	  of	  the	  porphyry	  units,	  with	  PQF2	  and	  PQB	  falling	  between	  with	  considerable	  compositional	  overlap	  (Figure	  19).	  From	  major	  oxide	  compositions,	  PFB	  is	  most	  similar	  to	  GRD1a;	  and	  PQF1	  most	  similar	  to	  GRD2.	  PQB	  is	  distinguishable	  by	  its	  slightly	  elevated	  concentrations	  of	  P,	  Mn,	  Zn,	  Pb,	  Nb,	  Nd	  and	  Ta.	  	  All	  four	  porphyry	  units	  have	  similar	  REE	  concentrations,	  with	  PQB	  having	  a	  slightly	  higher	  concentrations	  of	  REE,	  and	  PFB	  slightly	  lower	  (Figure	  20).	  All	  porphyry	  units	  display	  the	  “spoon	  pattern”	  in	  normalized	  REEs,	  indicative	  of	  hornblende	  fractionation	  (Davidson	  et	  al.	  2013).	  No	  porphyry	  unit	  shows	  a	  negative	  Eu	  anomaly	  which	  would	  be	  indicative	  of	  plagioclase	  fractionation	  (Davidson	  et	  al.	  2013).	  In	  terms	  of	  REEs,	  the	  porphyry	  units	  are	  most	  similar	  to	  GRD1a.	  All	  porphyry	  units	  are	  mineralized,	  PQF1	  most	  strongly,	  followed	  by	  PQF2,	  PFB	  and	  PQB	  (Table	  5).	  3.5.3 Magma	  Differentiation	  and	  Fertility	  Plots	  Differentiation	  cycles	  and	  magmatic	  recharges	  can	  be	  interpreted	  from	  SiO2	  -­‐TiO2	  variations	  (Loucks	  2013).	  Ti	  is	  melt-­‐incompatible	  and	  decreases	  with	  fractionation	  in	  a	  melt,	  while	  Si	  increases	  with	  fractionation.	  Magmatic	  recharges	  introduce	  Ti	  and	  other	  compatible	  elements	  causing	  an	  increase	  in	  Ti	  by	  addition	  and	  decrease	  in	  Si	  by	  dilution	  (Rohrlach	  &	  Loucks	  2005).	  SiO2	  against	  TiO2	  and	  Zr	  are	  used	  to	  interpret	  magmatic	  differentiation	  cycles	  for	  the	  granodiorite	  and	  porphyry	  units	  (following	  the	  methods	  of	  Loucks	  2013).	  SiO2	  against	  TiO2	  shows	  tight	  clusters	  proceeding	  from	  low	  SiO2	  and	  high	  TiO2	  to	  high	  SiO2	  and	  low	  TiO2	  of	  the	  following	  groups:	  [GRD1b	  +	  GRD3],	  GRD1a,	  porphyry	  units,	  and	  GRD2	  (Figure	  21a).	  	  SiO2	  against	  Zr	  shows	  a	  similar	  progression	  from	  [GRD1b	  +	  GRD3],	  GRD1a,	  porphyry	  units,	  through	  GRD2.	  [GRD1b	  +	  GRD3]	  has	  the	  highest	  Zr	  content	  of	  the	  porphyry	  and	  granodiorite	  units,	  on	  average	  190	  ppm,	  and	  between	  50	  and	  70	  wt	  %	  SiO2.	  GRD1a	  and	  the	  porphyry	  units	  contain	  around	  120	  ppm	  Zr	  and	  60	  to	  72.5	  wt%	  SiO2.	  GRD2	  has	  the	  highest	  SiO2	  content,	  between	  70-­‐77.5	  wt%,	  and	  lowest	  Zr,	  on	  average	  98	  ppm.	   	  55adcb Figure 19:Major oxide and immobile element plots for porphyry units using the same scale as the granodiorite plots to indicate composition variation between the units. a. Zr v TiO2 show some distinc-tion between PQF1 and PFB, but much overlap between the PQF2 and PQB populations. b. K2O v TiO2  variability in K2O distinguishes PQF1 from PFB, but PQB and PQF2 overlap.  c. SiO2 v MgO  considerable compositional overlap, with PQF1 and PFB plotting as end members d. K2O v Al2O3 considerable com-positional overlap, with PQF1 and PFB plotting as end members.  Summary statistics for these analytes are found in Table 356Figure 20: N-MORB normalized REE plots of granodiorite and porphyry units. HREEs distinguish GRD1b and GRD3 from GRD2 and GRD1b. PQF1 is generally REE depleted, relative to PQF2, PFB and PQB. PQB has elevated LREEs relative to the other porphyry units, with the exception of Eu. Depleted HREE concentrations in GRD1a, GRD2 and the porphyry units are indicative of hornblende fraction-ation from a hydrous melt.  Negative Eu anomalies in GRD1b and GRD3 are indicative of plagioclase fractionation from an anhydrous melt. Normalization values from Sun & McDonough,1989. 57baFigure 21: The interpreted differentiation cycles are shown as numbered shaded areas, with num-bered grey arrows showing recharges. a. SiO2 v TiO2: between populations there is an increase in TiO2 and decrease in SiO2 concentrations caused by the influx of fresh magma containing TiO2, whichde-creases SiO2 content by dilution and increase in TiO2  by addition. b. SiO2 v Zr: GRD1b + GRD3 show increases in Zr concentration up to 65 wt% SiO2, after which Zr concentration drops, consistent with infertile magmas. Magmatic recharge, seen between each population, results in SiO2 depletion and a slight influx of Zr, which decreases with increasing SiO2 concentration.58	  	  	   Fertility,	  or	  the	  potential	  for	  a	  magma	  to	  generate	  porphyry	  style	  mineralization,	  in	  a	  porphyry	  system	  is	  dependent	  upon	  a	  high	  magmatic	  water	  content	  source	  magma	  (Castillo	  1999;	  Rohrlach	  &	  Loucks	  2005).	  Water	  rich-­‐source	  magmas	  can	  be	  distinguished	  based	  on	  the	  principle	  that	  hornblende	  preferentially	  partitions	  Y	  (and	  Mn)	  and	  plagioclase	  preferentially	  partitions	  Sr.	  A	  high	  magmatic	  water	  content	  magma	  fractionates	  hornblende	  in	  preference	  to	  plagioclase;	  therefore	  elevated	  Sr/Y	  ratios	  are	  indicative	  of	  mineral	  fractionation	  in	  high	  magmatic	  water	  content	  magmas	  (at	  the	  appropriate	  P	  and	  T	  conditions)	  (Rohrlach	  &	  Loucks	  2005;	  Loucks	  2013).	  Y	  against	  Sr/Y	  diagrams	  separate	  adakite-­‐like	  rocks	  derived	  from	  a	  high	  magmatic	  water	  content,	  potentially	  fertile	  magma	  source,	  from	  “normal”,	  infertile,	  island-­‐arc	  andesite-­‐dacite-­‐rhyolite	  rocks	  using	  a	  threshold	  derived	  from	  observations	  made	  on	  numerous	  other	  porphyry	  deposits	  of	  Sr/Y	  =	  30,	  (Richards	  &	  Kerrich	  2007).	  For	  the	  Relincho	  deposit,	  an	  asymptotic	  trend	  from	  a	  high	  Sr/Y	  and	  low	  Y,	  to	  low	  Sr/Y	  and	  high	  Y	  distinguishes	  the	  potentially	  fertile	  porphyry	  units,	  GRD1a	  and	  GRD2,	  from	  the	  infertile	  [GRD1b	  +	  GRD3]	  (Figure	  22).	  	  3.6 Elemental	  Variability	  Attributed	  to	  Alteration	  	  Alteration	  intensity	  at	  the	  Relincho	  deposit	  is	  weak	  to	  moderate	  and	  is	  represented	  by	  minor	  compositional	  changes	  in	  the	  host	  rock.	  Gain-­‐loss	  diagrams	  are	  calculated	  using	  one	  sample	  each	  to	  represent	  unaltered,	  potassic,	  propylitic	  and	  phyllic	  alteration	  composition,	  to	  summarize	  the	  materials	  transferred	  during	  alteration.	  Spatial	  plots	  of	  element	  variability	  in	  the	  GRD1a	  unit	  provide	  some	  insight	  as	  to	  the	  extent	  of	  element	  involvement	  in	  alteration.	  Bivariate	  analyses	  explore	  whether	  common	  elemental	  relationships	  exist.	  Probability	  plots	  are	  used	  to	  distinguish	  samples	  affected	  by	  alteration	  from	  those	  unaffected.	  The	  characterization	  of	  the	  alteration	  assemblages	  employs	  all	  of	  these	  results	  to	  determine	  how	  alteration	  can	  be	  identified	  on	  a	  regional	  scale	  and	  how	  it	  can	  be	  relatively	  quantification.	  	  	   	  59 55.0    57.5     60.0     62.5     65.0    67.5    70.0     72.5    75.0   77.5 SiO 2 (wt %)2502252001751501251007550250Sr/YAdakite-like2.    5.0   7.5   1 12.5   15.0   17.5  20.0  22.5  25.0  27.5  3 .0Y (ppm)171117Sr/YNormal andesite -   dacite-rhyoliteAdakite-likerocksGRD2PQBPFBPQF2PQF1GRD1aGRD3GRD1bFigure 22: Magma fertility is indicated by hornblende fractionation from a water-rich melt. Y v Sr/Y uses the threshold of Sr/Y=30 represent hornblende fractionation. Hornblende sequesters Y as it frac-tionates, the remaining hydrous melt depleted Y, Sr is sequestered by plagioclase. Points plotting in the “adakite-like rocks” field are interpreted as more fertile than those plotting in the “normal andesite-dacite-rhyolite” field. Field outlines modified from Richards and Kerrich, 2007.603.6.1	   Spatial	  Element	  Variability	  	  Ranked	  variable	  plots	  display	  equal	  sample	  populations	  as	  points	  of	  distinct	  colour	  and	  size,	  according	  to	  element	  concentration	  (Figure	  23).	  To	  reduce	  the	  chemical	  variability	  introduced	  by	  plotting	  multiple	  lithological	  units,	  only	  GRD1a	  has	  been	  plotted	  spatially.	  Relative	  highs	  and	  lows	  are	  summarized	  with	  spatial	  reference	  to	  the	  porphyry	  corridor	  as	  within,	  adjacent	  (up	  to	  500	  m	  outside	  of	  the	  porphyry	  corridor)	  and	  distal	  (more	  than	  500	  m	  outside	  of	  the	  porphyry	  corridor):	  	  	  Within	  	   High:	  	   SiO2,	  K2O,	  Cu,	  Mo,	  Au,	  Ag,	  Rb,	  W,	  Bi	  	   	   Low:	  	   CaO,	  Na2O,	  P2O5,	  Al2O3,	  MnO,	  Sr	  	  Adjacent	   High:	  	   CaO,	  MnO,	  Na2O,	  Sr,	  Sb,	  Ba,	  Fe2O3,	  Al2O3,	  As,	  Ce,	  La,	  P2O5	  	   	   Low:	  	   K2O,	  Cu,	  Au,	  Ba,	  Cd,	  Co,	  Ga,	  Mo,	  Ni,	  Pb,	  Rb	  	  Distal	   	   High:	  	   Na2O,	  Pb,	  Zn,	  Mn,	  Co,	  P2O5,	  Al2O3,	  Cr2O3,	  La	  	   	   Low:	  	   Al2O3,	  Cu,	  Mo,	  Ni,	  SiO2,	  Au,	  Cs,	  W,	  Li	  	  Elements	  are	  grouped	  by	  their	  Goldschmidt	  classification	  for	  interpretation,	  which	  categorizes	  elements	  by	  their	  geochemical	  affinity	  (Goldschmidt	  1937).	  Lithophile	  elements	  (e.g.	  Li,	  Na,	  Mg,	  K,	  Ca,	  Rb,	  Sr,	  Cs,	  Ba,	  V,	  Cr,	  Zr,	  Al,	  Si,	  P)	  combine	  readily	  with	  O	  and	  tend	  to	  be	  elevated	  adjacent	  to	  the	  porphyry	  corridor,	  with	  the	  exception	  of	  K,	  Si,	  V	  and	  Rb,	  which	  are	  elevated	  within	  the	  porphyry	  corridor,	  and	  low	  adjacent	  to	  it.	  Chalcophile	  elements	  (e.g.	  Cu,	  Mo,	  Zn,	  As,	  Ag,	  Cd,	  Sb,	  Pb,	  Bi)	  combine	  readily	  with	  S.	  Cu,	  Mo,	  Bi	  and	  Ag	  are	  elevated	  within	  the	  porphyry	  corridor,	  though	  some	  chalcophile	  elements	  are	  elevated	  adjacent	  (Sb	  and	  As)	  or	  distal	  (Zn	  and	  Pb)	  to	  the	  porphyry	  corridor.	  Siderophile	  elements	  (e.g.	  Mn,	  Fe,	  Co,	  Ni,	  Au)	  combine	  readily	  with	  iron.	  Au	  is	  elevated	  in	  the	  porphyry	  corridor,	  though	  low	  adjacent	  and	  distally.	  Adjacent	  to	  the	  porphyry	  corridor	  Mn	  and	  Ni	  are	  elevated,	  with	  elevated	  Mn	  continuing	  distally.	  	  	  	  61Figure 2: Spatial plots of elemental variability for GRD1a with the porphy-ry corridor. Points are sized and coloured according to concentration, with each uniquely sized-coloured point representative of an equal number of samples. 62Figure 2: Continued63Figure 2: Continued64Figure 2: Continued65Figure 2: Continued66Figure 2: Continued67Figure 2: Continued68Figure 2: Continued69	  	  3.6.2 Bivariate	  Analyses	  Bivariate	  plots	  have	  been	  focused	  on	  elements	  pairs	  that	  exhibit	  geochemically	  similar	  behavior	  (e.g.	  Al2O3	  –	  Ga,	  K2O	  –	  Rb,	  CaO	  –	  Sr	  and	  Zn	  –	  Cd);	  identify	  lithological	  units	  (e.g.	  major	  element	  oxides,	  Eu,	  Th	  and	  Rb)	  or	  are	  potentially	  associated	  with	  mineralization	  (e.g.	  Cu	  and	  Mo	  versus	  trace	  and	  precious	  metals)	  (Figure	  24).	  The	  porphyry	  and	  granodiorite	  units	  are	  distinguished	  by	  colour	  on	  the	  bivariate	  plots.	  Strong	  positive	  correlations	  are	  seen	  between	  Al2O3	  –	  Ga,	  K2O	  –	  Rb,	  K2O	  –	  Th,	  CaO	  –	  Eu,	  and	  CaO	  –	  Sr.	  Lithological	  units	  cluster	  in	  these	  diagrams	  emphasizing	  the	  end	  member	  compositions	  of	  [GRD1b	  +	  GRD3]	  and	  GRD2	  for	  the	  granodiorite	  units,	  and	  compositional	  end	  members	  PQF1	  and	  PFB	  for	  the	  porphyry	  units.	  There	  is	  a	  weak	  correlation	  between	  Zn	  –	  Pb	  and	  Zn	  –	  Cd	  in	  the	  sample	  plots,	  though	  spatially	  there	  is	  a	  strong	  correlation	  between	  Zn	  –	  Pb	  –	  Cd.	  There	  is	  no	  correlation	  between	  Cu	  and	  Au,	  As,	  Ni,	  Pb,	  though	  Cu	  shows	  weak	  correlations	  with	  Ag,	  Mo	  and	  K2O.	  Elevated	  Mo	  and	  Cu	  concentrations	  occurring	  predominantly	  in	  samples	  with	  over	  2	  wt	  %	  K2O.	  Mo	  does	  not	  correlate	  with	  Au,	  Zn,	  Ag	  or	  As.	  3.6.3 Probability	  Plots	  Concentration	  breaks	  determined	  from	  probability	  plots	  are	  more	  representative	  than	  arbitrary	  concentration	  breaks,	  as	  they	  are	  indicative	  of	  distinct	  populations	  with	  fundamental	  compositional	  differences	  that	  could	  be	  due	  to	  lithology,	  alteration	  or	  mineralization	  (Sinclair	  1976).	  Probability	  plots	  have	  been	  used	  to	  distinguish	  populations	  affected	  by	  alteration	  from	  those	  unaffected	  within	  the	  GRD1a	  unit	  (Figure	  25).	  To	  minimize	  populations	  introduced	  by	  mixing	  lithological	  units,	  only	  GRD1a	  has	  been	  plotted.	  Once	  populations	  have	  been	  identified,	  they	  are	  plotted	  spatially	  to	  determine	  if	  they	  are	  consistent	  with	  field	  and	  hand	  sample	  observations.	  As	  GRD1a	  outcrops	  predominantly	  to	  the	  north,	  the	  alteration	  population	  footprints	  interpreted	  from	  GRD1a	  samples	  are	  truncated	  near	  the	  porphyry	  corridor.	  Elevated	  populations	  of	  K2O/Th	  (>	  0.32)	  and	  Cu	  (>	  118	  ppm)	  have	  a	  similar	  spatial	  extent	  to	  that	  of	  potassic	  alteration	  (Figure	  26a).	  Low	  magnetic	  susceptibility	  (<	  10.1)	  values	  resemble	  the	  phyllic	  alteration	  footprint,	  indicating	  magnetite	  destruction,	  giving	  a	  magnetically	  depressed	  zone	  in	  the	  system	  (Figure	  26b).	  	  70 Figure 2: Bivariate plots by lithology71Figure 2: Continued 72Figure 2: Continued73 Figure 2: Population separation based on probability plots with isolated populations indicated by shaded areas  a. Probability plot of magnetic susceptibility in GRD1a samples showing a small popula-tion change around 10.1. a. Depleted magnetic susceptibility are associated with phyllic alteration. b. K2O/Th probability plot of GRD1a samples showing a population break around 0.36. c. Cu probability plot of GRD1a with a break distinguishing background from samples affected by hydothermal process-es around 112 ppm. d. Cu probability plot of all granodiorite and porphyry units showing a population break at 282 ppm.a. b.d.c.741 kmNPotassic AlterationK2O/Th > 0.32Cu > 112 ppmPorphyry CorridorGRD1a Sample1 kmNMS < 15.4Phyllic AlterationPorphyry CorridorGRD1a SampleFigure 2: a. Potassic alteration showing strong spatial correlation with elevated GRD1a K2O/Th, and Cu populations. b. Depleted magnetic susceptibility samples correlate with the outline of weak phyllic alteration in GRD1a. a.b.75	  	  3.6.4 Elemental	  Gains	  and	  Losses	  Gain-­‐loss	  diagrams	  summarize	  element	  transfer	  during	  alteration.	  This	  type	  of	  geochemical	  assessment	  is	  useful	  in	  identifying	  subtle	  changes	  in	  trace,	  generally	  mobile	  element	  chemistry,	  which	  can	  sometimes	  be	  cryptic	  and	  difficult	  to	  quantify	  with	  traditional	  methods,	  such	  as	  petrography.	  Altered	  and	  fresh	  samples	  are	  selected	  using	  a	  combination	  of	  hand	  sample	  observations	  and	  MER	  relationships	  to	  identify	  a	  representative	  sample	  of	  each	  alteration	  assemblage.	  Gains	  and	  losses	  are	  relative	  to	  volume	  change	  during	  alteration,	  which	  is	  approximated	  using	  immobile	  “element”	  ratios	  of	  the	  altered	  and	  fresh	  samples.	  TiO2	  is	  used	  as	  the	  immobile	  element	  to	  keep	  consistency	  with	  the	  PER	  interpretations.	  To	  minimize	  compositional	  variations	  due	  to	  lithology,	  only	  samples	  of	  GRD1a	  were	  used.	  	  Elemental	  gains	  and	  losses	  from	  alteration	  of	  GRD1a	  are	  presented	  in	  Figure	  27	  and	  summarized	  in	  Table	  6.	  The	  calculated	  gains	  and	  losses	  are	  summarized	  below	  with	  significant	  variations	  (>	  1	  g/100	  g	  for	  oxides	  and	  >	  10	  mg/100	  g	  for	  trace	  metals)	  indicated	  in	  bold:	  	  Potassic	  alteration	   Gains:	  SiO2,	  K2O,	  Zn,	  Ag,	  Cu,	  Al2O3,	  Fe2O3,	  MgO,	  Mo,	  Pb,	  Li	  	  Losses:	  CaO,	  Na2O	  	  	  Propylitic	  alteration	   Gains:	  K2O,	  Na2O,	  Mo,	  Pb,	  Li	  Losses:	  SiO2,	  Cu,	  Zn,	  Fe2O3,	  Al2O3,	  CaO,	  Ag,	  Li	  	  Phyllic	  alteration	  	   Gains:	  SiO2,	  K2O,	  Cu,	  Mo,	  Ag,	  Pb,	  Zn,	  Au,	  B	  	  Losses:	  Fe2O3,	  CaO,Al2O3,	  MgO,	  Na2O,	  Li	  	   	  The	  elemental	  variations	  associated	  with	  potassic,	  propylitic	  and	  phyllic	  alteration	  at	  the	  Relincho	  PCD	  are	  consistent	  with	  those	  observed	  at	  the	  trachydacite	  hosted	  Bajo	  de	  la	  Alumbrera	  porphyry	  deposit	  (Ulrich	  &	  Heinrich	  2002);	  the	  diorite-­‐granodiorite	  hosted	  Sungun	  porphyry	  deposit	  (Taylor	  &	  Fryer	  1980);	  and	  various	  granodiorite	  related	  porphyry	  deposits	  in	  Turkey	  (Hezarkhani	  2011)	  (Table	  6).	  	  	  	  	  	   	  76e(T# A)#T $Ko#T $ PpT DlT Sl #T M#T a #T % P3T D%#T $ P D am i3 Ap A C O(K%ou 52.4 18 10.1 4.23 9.18 3.12 0.99 0.2 0.16 0.01 0.41 60.5 1.77 39.8 185 0.5 1 8al(n6.62 0.66 0.17 0.08 -­‐1.4 -­‐1.1 3.34 -­‐0 0.02 0 0.3 402 1.24 12 182 0.01 0.05 5.37a%)((n-­‐1.6 -­‐0.2 -­‐0.2 -­‐0 -­‐0.1 0.26 0.22 -­‐0 -­‐0 -­‐0 0.21 -­‐25 2.29 -­‐19 -­‐19 -­‐0 -­‐0 5.19au))(n 3.99 -­‐0.2 -­‐1 -­‐0.9 -­‐2.5 -­‐0.7 1.5 -­‐0 -­‐0 0 40.6 1536 2.98 2.83 560 0.82 1.54 -­‐2.1p "!!	  p 2p "!!	  p	  ( 2-5 -3 -1 1 3 5 7 SiO2 Al2O3 Fe2O3 MgO CaO Na2O K2O P2O5 MnO Cr2O3 Ku)((	  K	  ATlCiiOD	   AeTaoPOmD	   AMoPPOD	  -3000 -2000 -1000 0 1000 2000 3000 4000 5000 6000 7000 Mo Cu Pb Zn Ag Au B Li SKu)((	  K	  Figure 2: Elemental gains and losses due to alteration of GRD1a are calculated using the formula , where ΔX is the mass change of the mobile analyte per 100 g,  XAi/XBi is the ratio of the median values of the fresh (A) and altered (B) immobile analyte and X is the median concentration of the mobile analyte for the fresh (A) and altered (B) populations (Warren et al. 2007).  TiO2 is used as the immobile analyte. a. gains and losses plots and b. summary of gains and losses. a.b.77Rn3vitDd1	  ln	  3d	  B3end	  #b3vit	  %	  Gnvvit"	  )'')$a2vt	  Qt vn	  #ad 3	  %	  E n"	  (+*'$Up	  Qt  	  #Gn!d2tdv"	  )'(($QdviPWNl f	  Hl Nf	  RZf	  AVf	  AYl Nmf	  FUl Nmf	  LVNf	  Eef	  Laf	  OTf	  KW	  Hl Nf	  PWNl f	  FUN	  cacf	  Gl Nf	  Eef	  Ae	  Hf	  PWf	  Eef	  OT Hl Nf	  PWNl f	  Ebl Nmf	  EeQ 3vviHl Nf	  MSl Nf	  Laf	  OTf	  KW	   RZf	  MW hMgAi hMgAiQt 33viPWNl f	  Hl Nf	  Eef	  Laf	  AVf	  OTf	  RZf	  Aef	  C	  hMgAi hMgAiPWNl f	  ESNf	  Ebl Nmf	  LZNf	  LVNf	  Eef	  MWRn3vitDd1	  ln	  3d	  B3end	  #b3vit	  %	  Gnvvit"	  )'')$a2vt	  Qt vn	  #ad 3	  %	  E n"	  (+*'$Up	  Qt  	  #Gn!d2tdv"	  )'(($Qdvi ESNf	  MSl N	   ESNf	  MSl N FUf	  LVf	  ESf	  MSf	  AYLZNf	  LVNf	  MS l Nf	  ESNf	  FUl NmQ 3vviPWNl f	  Eef	  RZf	  FUl Nmf	  AYl Nmf	  ESNf	  AVf	  KWPWNl f	  FUl Nmf	  Hl Nf	  MSl N hMgAi hMgAiQt 33viFU2Nmf	  ESNf	  AYl Nmf	  LVNf	  MS l Nf	  KWhMgAi hMgAi FUl Nmf	  RZf	  Hl NFdvPnTable 6:  Summary of elemental gains and losses due to hydrothermal alteration at Relincho as com-pared to equivalent alteration assemblages at other porphyry deposits. 78	  	  3.7 Interpretations	  of	  Magmatic	  Evolution,	  Fertility	  and	  Alteration	  Fluids	  Major	  oxides,	  trace	  elements,	  REEs	  and	  hand	  sample	  observations	  are	  used	  to	  distinguish	  four	  porphyry	  units	  and	  four	  granodiorite	  units.	  These	  eight	  units	  are	  interpreted	  as	  the	  products	  of	  four	  differentiation	  cycles	  with	  three	  magmatic	  recharges.	  Porphyry	  and	  granodiorite	  units	  are	  identified	  as	  being	  sourced	  from	  a	  hydrous	  magma	  and	  are	  therefore	  potentially	  fertile,	  with	  the	  exception	  of	  GRD1b	  and	  GRD3.	  	  Gain-­‐loss	  observations	  are	  consistent	  with	  spatial	  plots	  of	  elements,	  showing	  increased	  concentrations	  of	  K,	  Cu,	  Si,	  Au	  and	  Ag	  in	  the	  porphyry	  corridor,	  with	  typical	  metal	  zonation	  of	  increased	  Zn,	  Mn	  and	  Pb	  distally.	  Population	  breaks	  within	  K2O/Th,	  Cu	  and	  magnetic	  susceptibility	  identify	  the	  potassic	  (K2O/Th	  and	  Cu)	  and	  phyllic	  (magnetic	  susceptibility)	  alteration	  assemblages.	  3.7.1 Magmatic	  Evolution	  and	  Fertility	  Based	  on	  major	  oxide,	  REE,	  and	  trace	  element	  plots	  there	  are	  eight	  distinct	  lithological	  units:	  [GRD1b	  +	  GRD3],	  GRD2,	  GRD1a,	  PQF1,	  PQF2,	  PFB	  and	  PQB.	  [GRD1b	  +	  GRD3]	  and	  GRD2	  represent	  the	  compositional	  end	  members	  of	  the	  eight	  lithological	  units.	  Within	  the	  porphyry	  units	  PQF1	  and	  PFB	  define	  the	  end	  member	  compositions,	  with	  much	  compositional	  overlap	  between	  the	  porphyry	  units.	  Tight	  clustering	  of	  GRD1a	  oxide	  and	  HFSE	  compositions	  (Figure	  17	  and	  Figure	  18)	  is	  due	  to	  the	  homogeneous	  nature	  of	  the	  unit.	  Geochemical	  similarities	  between	  GRD1b	  and	  GRD3	  imply	  that	  they	  are	  the	  same	  unit	  with	  variable	  mafic	  content	  and	  texture,	  resulting	  in	  the	  physical	  similarity	  between	  GRD1b	  and	  GRD1a.	  An	  interpreted	  compositional	  progression	  from	  [GRD1b	  +	  GRD3],	  through	  [GRD1a	  and	  PFB],	  [PQF2	  and	  PQB],	  PQF1	  and	  GRD2	  is	  based	  on	  major	  oxide	  diagrams.	  The	  unit	  compositions	  trends	  from	  more	  primitive	  and	  mafic	  mineral	  rich	  (GRD1b	  +	  GRD3)	  through	  to	  more	  evolved,	  containing	  igneous	  K-­‐feldspar	  (GRD2)(Figure	  17	  and	  Figure	  19).	  	  Cu-­‐Mo	  fertility	  in	  PCDs	  is	  related	  to	  water	  content	  of	  the	  source	  magma	  (Rohrlach	  &	  Loucks	  2005).	  Multiple	  differentiation	  and	  recharge	  cycles	  are	  required	  to	  concentrate	  Cu,	  Mo	  and	  volatile	  components,	  including	  water	  (Rohrlach	  &	  Loucks	  2005).	  Influxes	  of	  fresh	  magma	  to	  the	  magma	  pooled	  in	  the	  upper	  crust	  introduce	  79	  	  additional	  water,	  volatiles	  and	  incompatible	  elements	  to	  the	  magma	  chamber,	  which	  accumulates	  in	  a	  cyclic	  manner	  (Rohrlach	  &	  Loucks	  2005).	  When	  the	  magma	  ascends	  to	  a	  critical	  P	  level	  the	  fluids	  are	  exsolved	  from	  the	  magma	  along	  with	  other	  volatiles,	  which,	  if	  in	  an	  oxidized	  state	  (i.e.	  S	  as	  SO42-­‐	  and	  not	  as	  S2-­‐),	  has	  the	  capacity	  to	  carry	  metals	  (Richards	  et	  al.	  2012).	  The	  reactions	  caused	  by	  these	  fluids	  interacting	  with	  the	  host	  rock	  and	  porphyry	  units	  result	  in	  the	  hydrothermal	  alteration	  and	  mineralization	  associated	  with	  PCDs	  (Winter	  2001).	  	  Four	  differentiation	  cycles	  with	  three	  magma	  recharges	  have	  been	  interpreted	  from	  SiO2	  versus	  TiO2	  and	  Zr	  plots.	  The	  interpreted	  evolution	  of	  the	  granodiorite	  and	  porphyry	  units	  is:	  [GRD1b	  +	  GRD3]à	  GRD1a	  à	  porphyry	  units	  à	  GRD2,	  where	  arrows	  represent	  magma	  recharges.	  TiO2	  concentrations	  are	  highest	  in	  [GRD1b	  +	  GRD3],	  which	  also	  has	  the	  lowest	  SiO2	  concentrations	  (Figure	  21a).	  The	  TiO2	  concentration	  in	  [GRD1b	  +	  GRD3]	  decreases	  as	  the	  SiO2	  concentration	  increases.	  An	  interpreted	  magmatic	  recharge	  causes	  GRD1a	  to	  repeat	  the	  pattern	  exhibited	  by	  [GRD1b	  +	  GRD3],	  but	  with	  a	  starting	  composition	  between	  the	  maximum	  and	  minimum	  TiO2	  and	  SiO2	  concentrations	  of	  [GRD1b	  +	  GRD3].	  A	  magma	  recharge	  between	  [GRD1b	  +	  GRD3]	  and	  GRD1a	  causes	  an	  increase	  in	  TiO2	  by	  addition	  of	  magma	  and	  a	  decrease	  in	  SiO2	  concentrations	  by	  dilution.	  Two	  more	  magma	  recharges	  are	  interpreted:	  between	  GRD1a	  and	  the	  porphyry	  units;	  and	  between	  the	  porphyry	  units	  and	  GRD2,	  as	  evidenced	  by	  the	  decrease	  in	  SiO2	  and	  increase	  in	  TiO2	  between	  the	  differentiation	  cycles	  (Figure	  21a).	  	  SiO2	  –	  Zr	  variations	  support	  these	  differentiation	  cycles	  by	  highlighting	  the	  same	  four	  distinct	  populations	  (Figure	  21b).	  Zr	  concentrations	  in	  [GRD1b	  +	  GRD3]	  on	  average	  are	  higher	  than	  those	  of	  the	  other	  granodiorite	  units,	  with	  SiO2	  concentrations	  between	  55	  and	  70	  wt	  %.	  The	  process	  of	  mixing	  the	  fractionated	  and	  unfractionated	  magmas	  gives	  rise	  to	  compositions	  with	  a	  SiO2	  content	  around	  65	  wt	  %	  but	  with	  low	  Zr,	  as	  in	  GRD1a,	  porphyry	  units,	  and	  GRD3.	  Zr	  concentrations	  decrease	  with	  increasing	  SiO2	  concentration	  in	  GRD1a.	  A	  recharge	  dilutes	  the	  SiO2	  concentration	  for	  the	  porphyry	  units,	  and	  again	  for	  GRD2.	  	  Strongly	  depleted	  HREEs	  with	  a	  spoon	  shaped	  pattern	  are	  indicative	  of	  hornblende	  fractionation	  and	  therefore	  of	  a	  hydrous	  melt	  (Richards	  &	  Kerrich	  2007).	  80	  	  The	  overall	  HREE	  content	  of	  a	  melt	  is	  reduced	  as	  a	  result	  of	  hornblende	  fractionating	  from	  a	  hydrous	  melt	  and	  sequestering	  the	  middle	  HREEs	  during	  crystallization	  (Richards	  &	  Kerrich	  2007)	  with,	  however	  an	  elevated	  tale	  in	  Yb-­‐Lu.	  Depleted	  HREE	  concentrations	  in	  GRD1a,	  PQF1,	  PQF2,	  PFB,	  PQB	  and	  GRD2	  produces	  the	  characteristic	  spoon	  shaped	  REE	  profile,	  indicating	  hornblende	  fractionation	  and	  therefore	  a	  high	  magmatic	  water	  content	  source	  magma	  with	  the	  potential	  for	  Cu	  fertility	  (Figure	  20).	  GRD1b,	  GRD3	  and	  GRD2	  show	  a	  negative	  Eu	  anomaly,	  consistent	  with	  plagioclase	  fractionation	  (Loucks,	  2013).	  The	  fractionation	  of	  hornblende	  also	  partitions	  Y	  during	  crystallization	  as	  plagioclase	  fractionation	  partitions	  Sr.	  A	  Y	  versus	  Sr/Y	  plot	  is	  used	  to	  assess	  a	  high	  magmatic	  water	  content	  magma	  signature	  at	  Relincho	  and	  in	  fact	  test	  for	  Cu	  fertility	  in	  the	  PCD	  environment	  (Castillo,	  1999,	  Rohrlach	  &	  Loucks	  2005)	  (Figure	  22).	  A	  threshold	  of	  Sr/Y=30	  on	  the	  Y	  versus	  Sr/Y	  plot	  identifies	  GRD1a,	  PQF1,	  PQF2,	  PFB,	  PQB	  and	  GRD2	  as	  originating	  from	  a	  high	  magmatic	  water	  content	  source	  magma	  and	  therefore	  potentially	  fertile,	  and	  [GRD1b	  +	  GRD3]	  as	  infertile	  (Rohrlach	  &	  Loucks	  2005).	  	  [GRD1b	  +	  GRD3]	  is	  also	  identified	  as	  being	  sourced	  from	  an	  infertile	  magma	  by	  SiO2	  versus	  Zr	  plots	  (Figure	  21b).	  In	  a	  Cu-­‐infertile	  magma	  Zr	  concentrations	  typically	  peak	  around	  65	  wt	  %	  SiO2,	  as	  in	  the	  [GRD1b	  +	  GRD3]	  (Rohrlach	  &	  Loucks	  2005;	  Loucks	  2013).	  A	  product	  of	  anhydrous	  fractionation,	  this	  implies	  a	  decreased	  likelihood	  of	  Cu-­‐Mo	  fertility	  in	  [GRD1b	  +	  GRD3]	  (Figure	  21b)(Rohrlach	  &	  Loucks	  2005;	  Loucks	  2013).	  The	  progression	  of	  [GRD1b	  +	  GRD3]	  à	  GRD1a	  à	  porphyry	  units	  à	  GRD2	  is	  supported	  by	  the	  hand	  sample	  observations	  of	  the	  mineral	  composition	  becoming	  more	  evolved.	  The	  mafic	  component,	  hornblende	  and	  biotite,	  decreases	  as	  igneous	  K-­‐feldspar	  content	  increases	  in	  the	  units,	  consistent	  with	  this	  proposed	  progression	  (Table	  2,	  Table	  3,	  and	  Figure	  12).	  	  3.7.2 Alteration	  Fluids	  	  Alteration	  in	  the	  project	  area	  is	  generally	  weak	  to	  moderate.	  Given	  the	  weak	  to	  moderate	  intensity	  of	  alteration,	  the	  tight	  clustering	  of	  the	  GRD1a	  results	  implies	  a	  low	  water	  to	  rock	  ratio,	  or	  low	  reactivity	  of	  the	  minerals	  during	  alteration	  resulting	  in	  limited	  metasomatism	  (Figure	  17	  and	  Figure	  18).	  81	  	  The	  spatial	  correlation	  between	  elevated	  Cu	  (>	  112	  ppm)	  in	  GRD1a	  and	  the	  extent	  of	  potassic	  alteration	  is	  supportive	  of	  a	  common	  source	  fluid,	  consistent	  with	  accepted	  porphyry	  models	  (Sillitoe	  2010,	  Seedorff	  et	  al.	  2005).	  Population	  breaks	  in	  magnetic	  susceptibility,	  K2O/Th	  and	  Cu	  within	  the	  GRD1a	  results	  identified	  using	  basic	  statistics	  correspond	  spatially	  with	  alteration	  assemblages	  (Figure	  25	  and	  Figure	  26).	  The	  influx	  of	  K	  during	  potassic	  alteration	  is	  evidenced	  by	  the	  correlation	  between	  the	  spatial	  expression	  of	  visible	  potassic	  alteration	  and	  elevated	  K2O/Th	  (>	  0.32)	  (Figure	  26).	  Correlations	  between	  elevated	  Cu	  (>	  118	  ppm)	  populations	  and	  the	  potassic	  extent	  is	  evident	  of	  mineralization	  being	  associated	  with	  potassic	  alteration,	  consistent	  with	  current	  porphyry	  models	  (Sillitoe	  2010,	  Seedorff	  et	  al.	  2005).Low	  magnetic	  susceptibility	  populations	  (<	  10.1)	  have	  a	  spatial	  correlation	  with	  phyllic	  alteration,	  implying	  that	  the	  phyllic	  alteration	  assemblage	  is	  magnetite-­‐destructive	  and	  potentially	  visible	  in	  geophysical	  surveys	  (Figure	  26).	  This	  is	  consistent	  with	  the	  oxygen	  rich	  environment	  created	  by	  phyllic	  alteration	  (Table	  7)	  driving	  the	  oxidation	  of	  magnetite,	  resulting	  in	  the	  presence	  of	  hematite	  in	  phyllic-­‐altered	  areas.	  	  Calculated	  gains	  and	  losses	  are	  consistent	  with	  alteration	  reactions	  known	  to	  take	  place,	  based	  on	  primary	  and	  alteration	  mineral	  compositions	  (Table	  7).	  Addition	  of	  SiO2	  and	  K2O,	  and	  loss	  of	  CaO	  and	  Na2O	  during	  potassic	  alteration	  is	  consistent	  with	  the	  alteration	  of	  anorthite	  to	  K-­‐feldspar	  and	  hornblende	  to	  secondary	  biotite	  (Table	  7).	  Gains	  in	  Cu,	  Mo	  and	  Ag	  are	  consistent	  with	  observed	  mineralization	  associated	  with	  potassic	  alteration.	  Propylitic	  alteration	  shows	  gains	  of	  Na,	  and	  K	  and	  losses	  of	  Si	  and	  Ca,	  consistent	  with	  alteration	  of	  plagioclase	  to	  albite,	  plagioclase	  to	  epidote,	  biotite	  to	  epidote	  and	  plagioclase	  to	  albite	  (Table	  7).	  Phyllic	  alteration	  shows	  a	  gain	  of	  Si	  and	  K	  and	  loss	  of	  Ca	  relative	  to	  fresh	  samples,	  consistent	  with	  calcic	  zones	  of	  plagioclase	  altering	  to	  muscovite	  (Table	  7).	  Phyllic	  related	  muscovite	  alteration	  of	  the	  mafic	  minerals	  biotite	  and	  hornblende	  result	  in	  a	  loss	  of	  both	  Fe	  and	  Mg	  (Table	  7).	  The	  gain	  in	  Cu,	  Mo,	  Au	  and	  Ag	  in	  the	  phyllic	  assemblage	  could	  be	  due	  to	  variability	  in	  the	  levels	  of	  hypogene	  mineralization	  in	  the	  sample	  used	  to	  represent	  phyllic	  alteration.	  Elevated	  Pb	  and	  Zn	  in	  the	  propylitic	  and	  phyllic	  zones	  are	  common	  in	  porphyry	  deposits	  (Lowell	  &	  Guilbert	  1970),	  however	  the	  gains	  and	  losses	  demonstrated	  by	  the	  samples	  are	  weak	  for	  Pb	  in	  particular.	  Despite	  this	  there	  are	  clear	  spatial	  indications	  of	  a	  Pb-­‐Zn	  halo	  821 kmN2207.5 < Wavelength < 22092207.5 > Wavelength > 2209Cu < 282 ppmCu > 282 ppmPotassic AlterationPorphyry Corridor2207.5 < Wavelength < 22092207.5 > Wavelength > 2209Cu < 282 ppmCu > 282 ppm2202.5           2205.0       2207.5    2210.0          2212.5     2215.0          2217.5Wavelength (nm)0.140.120.100.080.060.040.02Fe + Mg (Molar)NSample PointMontmorilloniteSiderite Potassic AlterationPorphyry CorridorSample SiteIllitePropylitic AlterationPorphyry Corridor1 kmNFigure 28: SWIR results showing samples with a. potassic alteration footprint with white mica features between 2207.5 to 2209 nm and elevated Cu concentrations, b. wavelength of white mica features versus molar (Fe + Mg) with elevated Cu concentrations, c. potassic alteration footprint with SpecMin identified montmerillonite and siderite and d. SpecMin identified illite with the propylitic alteration footprint.a. b.c. d.83AssemblageReplacement (Primary à Alteration)Reaction Additions LossesHb à2Bt Ca2(Mg,Fe) 4 Fe3+ (Si 7 Al)O 22 (OH) 2  + 2K +  + Al 3+  + 2(Mg,Fe) 2+  +  2H +    à         2K(Mg,Fe) 3 AlSi 3 O 10 (OH) 2 + 2Ca 2+  +Fe 3+  + Si 4+K + , (Fe,Mg) 2+ , H + ,Al3+ Ca2+ , Al 3+ , Fe3+ , Si 4+Anà Ks CaAl2Si2 O 8  + K+  + Si 4+   à                         KAlSi 3 O 8  + Ca 2+  + Al 3+K + , Si 4+ Ca2+ , Al 3+Hb à Cl Ca2(Mg,Fe) 4 Fe3+ (Si 7 Al)O 22 (OH) 2  + (Fe,Mg) 2+  + Al 3+  + 12H +   à            (Fe,Mg) 5Al2Si3 O 10 (OH) 8  + 2Ca 2+   + Fe 3+  + 4Si 4+  + 6OH - (Fe,Mg) 2+ , H + , Al 3+ Ca2+ , Fe3+ , OH - , Si 4+Hb à Ep Ca2(Mg,Fe) 4 Fe3+ (Si 6Al2 )O 22 (OH) 2  + 2Ca 2+  + 3Al 3+  + 2OH -   à                   2Ca2(Fe,Al) 3 (SiO 4 ) 3 (OH) + 4(Fe,Mg) 2+   + 2H +Ca2+ , Al 3+ , OH - H + , (Fe,Mg) 2+Bt à Cl 2K(Fe, Mg) 3 AlSi 3 O 10 (OH) 2 + 16H+ à                                                                                   (Fe,Mg) 5Al2Si3 O 10 (OH) 8  + 2K +  + (Fe,Mg) 2+  + 3Si 4+ + 6H 2 OH + K + , (Fe,Mg) 2+ , Si 4+Anà Ep 2CaAl2Si2O 8  + 7H+   à                                                                                                  Ca2 (Al) 3 (SiO 4 ) 3 (OH) + Al 3+  + Si 4+ +  3H 2 OH + Al3+ , Si 4+AnàAb CaAl2Si2 O 8  + Na+  + Si 4+  +   à                                                                                                      NaAlSi 3 O 8 + Al 3+  +  Ca 2+Na + , Si 4+ Al3+ , Ca2+Anà Mu 3CaAl 2Si2O 8  + 4H+  + 2K +  à                    2KAl 2(Si 3 Al)O 10 (OH) 2  + 3Ca 2+K + , H + Ca2+Hb à Cl Ca2(Mg,Fe) 4 Fe3+ (Si 7 Al)O 22 (OH) 2  + (Fe,Mg) 2+  + Al 3+  + 12H +   à            (Fe,Mg) 5Al2Si3 O 10 (OH) 8  + 2Ca 2+   + Fe 3+  + 4Si 4+  + 6OH - (Fe,Mg) 2+ , H + , Al 3+ Ca2+ , Fe3+ , OH - , Si 4+Bt à Cl 2K(Fe,Mg) 3 AlSi 3 O 10 (OH) 2 + 16H+ à                                                                                   (Fe,Mg) 5Al2Si3 O 10 (OH) 8  + 2K +  +(Fe,Mg) 2+  + 3Si 4+ + 6H 2 OH +K + , (Mg,Fe) 2+ , Si 4+ , H 2 OPotassicPhyllicPropyliticTable 7: Summary of primary and alteration mineral compositions and alteration reactions with gains and losses,  where HB=igneous horn -blende, BT= igneous Biotite, AN= anorthite (igneous feldspar), Alteration minerals: 2Bt=secondary biotite, KS= feldspar, EP= epidote, CL= chlorite, CA= calcite, AB= albite, MU= muscovite. Mineral compositions are simplied from compositions calculated from electron microprobe results.84	  	  around	  the	  porphyry.	  Gain-­‐loss	  results	  at	  Relincho	  for	  the	  potassic,	  propylitic	  and	  phyllic	  alteration	  assemblages	  are	  consistent	  with	  equivalent	  alteration	  assemblages	  at	  other	  porphyry	  deposits	  in	  similar	  host	  rocks	  (Ulrich	  &	  Heinrich	  2002;	  Hezarkhani	  2011;	  Taylor	  &	  Fryer	  1980)	  (Table	  6).	  The	  spatial	  element	  variability	  plots	  support	  the	  gain-­‐loss	  calculations.	  When	  lithological	  variability	  is	  limited	  by	  only	  reviewing	  variability	  in	  GRD1a	  plots,	  areas	  affected	  by	  potassic	  alteration	  and	  possibly	  propylitic	  alteration	  are	  clear.	  Relatively	  high	  concentrations	  of	  K2O,	  SiO2,	  Cu,	  Mo,	  Ag,	  and	  Au	  and	  relatively	  low	  concentrations	  of	  CaO	  and	  Na2O	  are	  consistent	  with	  gain-­‐loss	  calculations	  for	  potassic	  alteration.	  Relatively	  high	  concentrations	  Na2O	  adjacent	  to	  potassic	  alteration	  are	  consistent	  with	  propylitic	  alteration.	  Immediately	  adjacent	  to	  mineralization	  is	  elevated	  Mn,	  Zn	  and	  Pb,	  consistent	  gain-­‐loss	  results	  for	  the	  phyllic	  assemblage,	  and	  with	  metal	  zoning	  presented	  by	  Lowell	  &	  Guilbert	  (1970).	  	  	  3.8 Exploration	  Implications	  of	  Interpretations	  	  Two	  methods	  for	  using	  surface	  sample	  lithogeochemistry	  for	  regional	  exploration	  of	  porphyry	  deposits	  have	  been	  identified:	  	  	  1. Identifying	  prospective	  regions	  through	  the	  assessment	  of	  magma	  fertility	  by	  geochemical	  characterization	  of	  lithological	  units	  	  2. Understanding	  alteration	  assemblages	  and	  identifying	  prospective	  areas	  through	  the	  use	  of	  simple	  element	  concentration	  plots.	  	  The	  Relincho	  PCD	  is	  hosted	  in	  a	  set	  of	  four	  granodiorite	  (GRD1a,	  GRD1b,	  GRD2	  and	  GRD3)	  units	  previously	  undifferentiated.	  Mineralization	  is	  associated	  with	  four	  syn-­‐mineralization	  porphyry	  units:	  PQF1,	  PQF2,	  PFB	  and	  PQB.	  The	  interpreted	  magmatic	  evolution	  of	  this	  suite	  of	  rocks	  is:	  [GRD1b	  +	  GRD3]	  à	  GRD1a	  à	  [PQF1,	  PQF2,	  PFB	  and	  PQB]	  à	  GRD2	  based	  on	  mineralogy	  and	  relationships	  displayed	  in	  the	  SiO2	  versus	  TiO2	  and	  SiO2	  versus	  Zr	  diagrams.	  All	  porphyry	  and	  granodiorite	  units,	  with	  the	  exception	  of	  85	  	  GRD1b	  and	  GRD3	  are	  interpreted	  as	  sourced	  from	  a	  high	  magmatic	  water	  content	  magma,	  and	  therefore	  potentially	  Cu-­‐fertile.	  These	  diagrams	  can	  be	  used	  to	  determine	  whether	  or	  not	  a	  source	  magma	  had	  the	  potential	  to	  generate	  mineralization,	  given	  the	  appropriate	  metal	  content,	  and	  P-­‐T	  conditions	  of	  emplacement.	  This	  method	  can	  be	  used	  to	  quickly	  and	  relatively	  inexpensively	  identify	  regions	  of	  potential	  interest	  for	  follow-­‐up	  exploration,	  even	  in	  areas	  with	  limited	  background	  knowledge	  of	  the	  lithological	  units	  and	  alteration.	  Statistical	  population	  breaks	  in	  K2O/Th,	  Cu	  and	  magnetic	  susceptibility	  within	  the	  GRD1a	  unit	  show	  strong	  correlation	  with	  potassic	  and	  phyllic	  alteration	  respectively.	  Elevated	  K2O/Th	  and	  Cu	  populations	  show	  a	  strong	  spatial	  correlation	  with	  the	  potassic	  footprint,	  consistent	  with	  gain-­‐loss,	  bivariate	  and	  spatial	  concentration	  diagrams.	  This	  is	  a	  logical	  observation	  as	  Cu-­‐mineralization	  is	  commonly	  associated	  with	  potassic	  alteration	  in	  PCDs	  (Sillitoe	  2010).	  K2O/Th	  could	  be	  used	  on	  a	  regional	  scale	  to	  identify	  areas	  for	  PCD	  exploration.	  Low	  magnetic	  susceptibility	  populations	  are	  spatially	  consistent	  with	  the	  phyllic	  assemblage,	  indicative	  of	  magnetite	  destruction,	  consistent	  with	  hematite	  observed	  in	  phyllic-­‐altered	  samples.	  This	  magnetic	  susceptibility	  low	  could	  potentially	  be	  visible	  in	  regional	  geophysical	  surveys	  as	  well.	  These	  statistical	  population	  breaks	  emphasize	  regions	  for	  exploration	  follow-­‐up	  even	  with	  limited	  knowledge	  of	  the	  geological	  environment.	  Gain-­‐loss	  calculations	  assist	  in	  for	  regional	  exploration	  by	  identifying,	  which	  elements	  are	  associated	  with	  which	  alteration	  assemblage,	  and	  could	  be	  applied	  to	  identify	  areas	  of	  alteration.	  In	  the	  case	  of	  Relincho	  the	  chemical	  compositional	  change	  due	  to	  alteration	  is	  relatively	  insignificant	  making	  it	  difficult	  to	  apply	  the	  method	  without	  a	  thorough	  understanding	  of	  the	  local	  geology	  and	  alteration.	  To	  emphasize	  the	  effect	  of	  alteration,	  compositional	  end	  members	  identified	  using	  geochemistry	  and	  hand	  sample	  observations	  were	  used	  to	  represent	  the	  altered	  and	  unaltered	  compositions.	  Nevertheless,	  when	  the	  GRD1a	  geochemical	  results	  are	  reviewed	  spatially,	  typical	  high	  concentrations	  of	  K,	  Cu,	  Si,	  Mo	  and	  Au	  identify	  the	  area	  of	  mineralization	  and	  potassic	  alteration,	  showing	  classic	  distal	  elemental	  zonation	  such	  as	  elevated	  Zn	  and	  Pb	  around	  the	  deposit	  area.	  	   	  86	  	  Chapter	  4:	  Recognizing	  Hydrothermal	  Alteration	  in	  a	  Felsic	  Environment:	  A	  Case	  Study	  of	  the	  Relincho	  Cu-­‐Mo	  Porphyry,	  Atacama,	  Chile	  4.1 Introduction	  Alteration	  at	  the	  Relincho	  deposit	  is	  easily	  misidentified	  due	  to	  its	  weak	  intensity.	  Hand	  sample	  observations	  in	  combination	  with	  SWIR	  results	  and	  MERs	  applied	  to	  the	  porphyry	  and	  granodiorite	  samples	  identify	  key	  indicators	  for	  distinguishing	  alteration	  assemblages.	  Representative	  properties	  of	  the	  alteration	  assemblages	  are	  then	  used	  to	  calculate	  an	  alteration	  index	  for	  relative	  quantification	  of	  alteration	  intensity.	  SWIR	  results	  aid	  in	  the	  characterization	  of	  potassic	  and	  propylitic	  alteration,	  but	  are	  less	  useful	  for	  the	  identification	  of	  phyllic	  alteration.	  Interpretations	  of	  SWIR	  analyses	  indicate	  that	  montmorillonite	  and	  siderite	  may	  be	  part	  of	  the	  potassic	  assemblage,	  and	  illite	  part	  of	  the	  propylitic.	  The	  wavelengths	  of	  identified	  chlorite	  features	  indicate	  that	  chlorite	  proximal	  to	  the	  porphyry	  corridor	  is	  Fe-­‐rich,	  grading	  outwards	  to	  Mg-­‐rich.	  White	  mica	  features	  show	  that	  elevated	  Cu	  concentrations	  (>	  282	  ppm)	  in	  samples	  with	  white	  micas	  are	  consistent	  with	  features	  occurring	  between	  2207.5	  and	  2209	  nm.	  	  MERs,	  though	  ineffective	  for	  depicting	  potassic	  alteration	  at	  the	  Relincho	  deposit	  due	  to	  the	  chemical	  similarity	  between	  igneous	  and	  alteration	  minerals,	  depict	  even	  weak	  phyllic	  and	  propylitic	  alteration.	  GERs	  of	  feldspar	  space	  (2CNK/Al	  versus	  K/Al,	  2Ca/Al	  and	  Na/Al)	  show	  losses	  in	  Ca	  associated	  with	  gains	  in	  K,	  interpreted	  to	  be	  a	  product	  of	  phyllic	  alteration.	  Feldspar	  space	  PER	  diagrams	  of	  (Al/Ti	  versus	  2CNK/Ti)	  and	  customized	  PER	  diagrams	  ((2Si	  +	  7Al	  +	  4(Mg	  +	  Fe))/Ti	  versus	  (18Ca	  +	  14Na	  +	  25K)/Ti)	  effectively	  depict	  phyllic	  and	  propylitic	  alteration.	  Effective	  simple	  and	  Pearce	  element	  ratios	  are	  used	  to	  calculate	  alteration	  indices	  and	  relatively	  quantify	  alteration	  intensity.	  This	  alteration	  index	  is	  used	  to	  calculate	  the	  minimum	  sample	  population	  required	  for	  regional	  PCD	  exploration.	  	  874.2	  	  Local	  Geology	  and	  Alteration	  4.2.1	   	  Lithological	  Units	  Mineralization	  at	  the	  Relincho	  deposit	  is	  hosted	  in	  a	  Paleocene	  granodiorite	  of	  the	  Los	  Morteros	  batholith	  and	  associated	  with	  four	  Paleocene	  porphyritic	  intrusions	  (Figure	  10).	  Mineralogy,	  texture	  and	  geochemistry	  distinguish	  four	  granodiorite	  units:	  GRD1a,	  GRD1b,	  GRD2	  and	  GRD3	  (Table	  2,	  Figure	  12);	  and	  four	  porphyry	  units:	  PQF1,	  PQF2,	  PFB	  and	  PQB	  (Table	  3,	  Figure	  12).	  Relative	  emplacement	  timing	  of	  the	  granodiorite	  units	  was	  not	  observed	  or	  deduced	  in	  the	  field,	  though	  based	  on	  evidence	  presented	  in	  Chapter	  three,	  three	  episodes	  of	  magma	  recharge	  drove	  four	  differentiation	  cycles	  resulting	  in	  the	  following	  progression	  from	  oldest	  (1)	  to	  youngest	  (4):	  	  1-­‐	  GRD1b	  +	  GRD3	  2-­‐	  GRD1a	  3-­‐	  Porphyry	  units	  (mineralization	  event)	  4-­‐	  GRD2	  	  	   This	  evolutionary	  progression	  is	  supported	  by	  petrographic	  observations	  of	  the	  mafic	  mineral	  content	  decreasing	  and	  K-­‐	  feldspar	  content	  increasing	  from	  [GRD1b	  +	  GRD3]	  →	  GRD1a	  →	  porphyry	  units	  →	  GRD2	  (Figure	  12).	  It	  is	  important	  to	  note	  that	  only	  GRD2	  and	  the	  porphyry	  units	  contain	  igneous	  K-­‐feldspar	  (Figure	  12).	  	  4.2.2	   Alteration	  	  	   Alteration	  assemblages	  associated	  with	  mineralization	  are	  potassic,	  propylitic	  and	  phyllic	  with	  a	  late-­‐stage,	  post	  mineralization	  chlorite	  alteration	  affecting	  the	  entire	  project	  area	  (Figure	  15a).	  Mineralization	  is	  strongly	  associated	  with	  the	  potassic	  assemblage.	  Petrographic	  observations	  of	  overprinting	  mineral	  textures	  indicate	  that	  potassic	  alteration	  was	  followed	  by	  propylitic,	  then	  phyllic,	  consistent	  with	  general	  porphyry	  system	  models	  (Lowell	  &	  Guilbert	  1970;	  Seedorff	  2005).	  Alteration	  intensities	  are	  defined	  by	  the	  average	  replacement	  of	  primary	  minerals	  by	  alteration	  minerals	  as	  unaltered	  (<	  15	  %	  replacement	  of	  primary	  mineral	  by	  alteration	  mineral),	  weak	  (>15	  %	  88	  	  replacement	  <	  30	  %),	  moderate	  (30	  %	  <	  replacement	  <60	  %)	  and	  strong	  (60	  %	  <	  replacement).	  The	  spatial	  footprint	  of	  weak	  potassic,	  propylitic	  and	  phyllic	  alteration	  based	  on	  hand	  sample	  and	  thin	  section	  observations	  is	  shown	  in	  Figure	  15a.	  Alteration	  assemblages	  are	  defined	  by	  the	  presence	  of:	  	  	  Potassic:	  	   secondary	  biotite	  +	  incipient	  K-­‐feldspar	  +	  magnetite	  ±	  epidote	  ±	  glassy	  limonite	  (from	  chalcopyrite);	  	  Propylitic:	  	   epidote	  +	  chlorite	  +	  hematite	  ±	  albite	  ±	  calcite	  ±	  actinolite±pyrite;	  	  Phyllic:	  	   chlorite	  +muscovite	  +	  quartz	  	  ±	  calcite	  ±	  hematite.	  	  4.3 Results	  Petrographic	  observations,	  including	  alkali	  feldspar	  staining,	  are	  used	  to	  support	  SWIR	  results	  and	  MER	  interpretations	  to	  characterize	  the	  alteration	  assemblages.	  The	  results	  of	  this	  characterization	  are	  used	  to	  calculate	  alteration	  indices.	  4.3.1 	  Staining,	  Field	  and	  Petrographic	  Observations	  	  Based	  on	  field	  and	  petrographic	  observations,	  supported	  by	  rock	  staining	  for	  alkali	  feldspar,	  the	  spatial	  extents	  of	  weak	  alteration	  were	  established	  and	  presented	  in	  Figure	  15.	  Alkali	  feldspar	  staining	  supports	  hand	  sample	  and	  field	  observations	  of	  the	  incipient	  nature	  of	  K-­‐feldspar	  alteration	  of	  plagioclase	  and	  confirms	  the	  presence	  of	  igneous	  K-­‐feldspar	  in	  GRD2	  and	  the	  groundmass	  of	  the	  porphyry	  units	  as	  well	  as	  a	  lack	  of	  igneous	  K-­‐feldspar	  in	  GRD1a,	  GRD1b	  and	  GRD3.	  Field	  and	  petrographic	  observations	  also	  indicate	  that	  alteration	  intensity	  is	  generally	  weak	  to	  moderate	  in	  phyllic	  or	  potassic	  alteration,	  and	  weak	  to	  strong	  in	  propylitic	  alteration.	  Weak	  phyllic	  alteration	  is	  best	  observed	  with	  a	  microscope,	  which	  shows	  the	  incipient	  nature	  of	  the	  selective	  muscovite	  replacement	  of	  calcic	  zones	  within	  plagioclase	  (Figure	  15d).	  	  89	  	  4.3.2 	  Shortwave	  Infrared	  Results	  SWIR	  results	  are	  processed	  by	  the	  software	  SpecMin®	  which	  compares	  the	  SWIR	  spectra	  to	  a	  spectral	  library	  to	  identify	  minerals.	  SpecMin®	  effectively	  identified	  minerals	  and	  features	  associated	  with	  the	  potassic	  and	  propylitic	  assemblages	  that	  could	  be	  used	  for	  regional	  characterization.	  Montmorillonite	  and	  siderite	  are	  weakly	  spatially	  associated	  with	  the	  potassic	  footprint,	  though	  not	  positively	  identified	  in	  hand	  sample	  (Figure	  28).	  In	  samples	  that	  contain	  elevated	  Cu	  concentrations	  (Cu	  >	  282	  ppm	  for	  all	  porphyry	  and	  granodiorite	  units,	  Figure	  25)	  and	  SpecMin®	  identified	  white	  micas	  (illite,	  muscovite,	  phengite	  and	  montmorillonite),	  elevated	  Cu	  concentrations	  strongly	  correlate	  with	  white	  mica	  with	  features	  between	  2207.5	  to	  2209	  nm	  (Figure	  28b).	  SpecMin®	  chlorite	  with	  features	  in	  the	  range	  of	  2330	  ±	  30	  nm	  can	  be	  separated	  into	  three	  populations	  based	  on	  the	  wavelength	  location	  of	  features:	  2335	  to	  2343	  nm,	  2343.5	  to	  2345.5	  and	  2346	  to	  2352	  nm	  (Figure	  29b).	  Plotted	  spatially,	  chlorite	  with	  higher	  wavelength	  features	  is	  proximal	  to	  the	  porphyry	  corridor.	  Illite	  is	  weakly	  associated	  with	  propylitic	  alteration	  (Figure	  28c).	  4.3.3 Molar	  Element	  Ratios	  General	  and	  Pearce	  element	  ratios	  (GERs	  and	  PERs)	  are	  both	  molar	  element	  ratios	  (MERs)	  used	  to	  depict	  geochemical	  processes	  such	  as	  alteration	  (Stanley	  &	  Russell,	  1989).	  In	  the	  accompanying	  GER	  and	  PER	  figures,	  unaltered	  to	  weakly	  altered	  samples	  are	  shown	  as	  dark	  points,	  and	  moderately	  to	  strongly	  altered	  samples	  as	  light	  points	  (Figure	  30	  and	  Figure	  32).	  Feldspar	  composition	  is	  commonly	  examined	  using	  the	  molar	  sum	  of	  (2Ca	  +	  Na	  +	  K),	  summarized	  as	  2CNK.	  Mineral	  nodes	  (GER)	  and	  control	  lines	  (PER)	  are	  calculated	  from	  simple	  mineral	  compositions.	  Mineral	  nodes	  are	  two-­‐dimensional,	  whereas	  control	  lines	  are	  three-­‐dimensional	  expressions	  of	  compositional	  planes	  into	  and	  out	  of	  the	  page	  representative	  of	  a	  mineral	  or	  group	  of	  minerals.	  Alteration	  intensity	  is	  proportional	  to	  a	  sample’s	  position	  relative	  to	  unaltered	  composition	  and	  the	  alteration	  mineral	  node	  or	  control	  line.	  To	  simplify	  element	  ratio	  interpretation,	  end-­‐member	  compositions	  of	  common	  primary	  and	  alteration	  minerals	  at	  the	  Relincho	  deposit	  have	  been	  summarized	  in	  Table	  7.	  	  	   	  901 kmNFe-rich ChloriteIntermediate ChloriteMg-rich ChloritePorphyry Corridor1 kmNChloriteEpidotePSPQZMJUJc AlterationPorphyry CorridorGRD1a SampleFigure 29: TerraSpec results for chlorite and illite a. Probability plot of the wavelengths of chlorite features showing popultaion breaks by colour theoretically indicative of relative Fe and Mg concentra-tions, b. Spatial footprint of chlorite populations relative to the porphyry corridor showing the theo-retical composition changing outwardly from Fe-rich to Mg-rich c. SpecMin identified illite with the propyltiic alteration footprinta.b.c.91Test	  of	  the	  Cogenetic	  Hypothesis	  Pearce	  element	  ratios	  differ	  from	  GERs	  in	  that	  they	  use	  a	  conserved	  element	  in	  the	  denominator.	  In	  order	  to	  use	  a	  conserved	  element,	  the	  PER	  methodology	  requires	  a	  failure	  to	  reject	  the	  cogenetic	  hypothesis,	  which	  postulates	  that	  each	  rock	  unit,	  at	  some	  point,	  originated	  from	  a	  homogeneous	  system	  (Russell	  &	  Stanley	  1990).	  Two	  equally	  conserved	  elements	  plotted	  against	  each	  other	  yield	  a	  best-­‐fit	  line	  with	  a	  positive	  slope	  that	  intersects	  the	  origin,	  if	  equally	  conserved,	  or	  the	  best-­‐fit	  line	  will	  cross	  the	  axis	  of	  the	  less	  conserved	  element	  (Stanley	  &	  Madeisky,	  1995).	  The	  conservation	  of	  TiO2	  and	  Zr	  are	  tested	  for	  the	  four	  differentiation	  cycles	  identified	  in	  Chapter	  three	  (Figure	  31).	  There	  is	  a	  failure	  to	  reject	  the	  cogenetic	  hypothesis	  for	  GRD1a,	  GRD2,	  and	  the	  porphyry	  units,	  with	  indications	  that	  Ti	  is	  slightly	  more	  conserved	  than	  Zr	  in	  GRD2.	  For	  this	  reason	  Ti	  is	  used	  as	  the	  conserved	  element	  in	  the	  PER	  plots	  (Figure	  31b,	  c	  and	  d).	  There	  is	  a	  lack	  of	  conservation	  of	  Ti	  and	  Zr	  in	  units	  GRD1b	  and	  GRD3,	  resulting	  in	  a	  rejection	  of	  the	  cogenetic	  hypothesis	  (Figure	  31a).	  The	  failure	  to	  reject	  the	  cogenetic	  hypothesis	  allows	  the	  use	  of	  PERs	  for	  GRD1a,	  GRD2	  and	  the	  porphyry	  units,	  but	  not	  GRD1b	  and	  GRD3.	  	  Molar	  Element	  Ratio	  Observations	  Compositional	  variability	  in	  feldspar	  due	  to	  alteration	  and	  primary	  composition	  is	  depicted	  by	  the	  GER	  plots	  2CNK/Al	  versus	  2Ca/Al,	  Na/Al	  and	  K/Al	  (Figure	  30).	  These	  plots	  indicate	  muscovite,	  K-­‐feldspar,	  anorthite	  and	  albite	  nodes	  that	  can	  be	  used	  for	  interpretation	  of	  compositional	  variation	  due	  to	  alteration.	  Minimal	  fluctuation	  in	  Na	  concentration	  indicates	  that	  variability	  shown	  by	  2CNK	  is	  from	  loss	  of	  Ca	  and	  gain	  of	  K	  during	  alteration,	  and	  from	  differences	  in	  primary	  mineralogy	  between	  lithological	  	  units.	  	  Feldspar	  compositional	  variation	  is	  isolated	  in	  the	  plane	  represented	  by	  the	  m	  =	  1	  control	  line	  on	  the	  diagram	  2CNK/Ti	  versus	  Al/Ti,	  hereon	  referred	  to	  as	  the	  feldspar	  space	  PER,	  emphasizing	  the	  effect	  of	  epidote	  (propylitic),	  muscovite	  (phyllic)	  and	  chlorite	  (propylitic	  and/or	  phyllic)	  alteration	  (Figure	  32a).	  Unaltered	  samples	  lie	  approximately	  on	  the	  m	  =	  1	  line.	  Samples	  that	  have	  been	  phyllic	  altered	  plot	  below	  m	  =	  1,	  toward	  the	  92a. b. &&.&(.&*.&+.&,.'&.'(.&&. &(. &*. &+. &,. '&. '(.KMaAO	  ePSOMTi	  elCMmKMmDiaAO	  	  ePSOMTi	  56!0.56!-­‐.50!0.50!-­‐.560(!0.560(!-­‐.560'!0.560'!-­‐.17'9!0.17'9!-­‐.17'!0.17'!-­‐.17(!0.17(!-­‐.17)!0.17)!-­‐.3..4."' )&#.-­‐.2!89..4."'&#.-­‐.4."''#.Figure 30: General Element Ratio plots of feldspar space with dark points representing fresh to weakly altered samples and light points representing moderately to strongly altered samples.  The combina-tion of these two plots allows for the isolation of the source of the variability in the feldspar space. a. (2Ca+Na+K)/Al vs 2Ca/Al, shows a depletion in Ca due to an alteration process. b. (2Ca+Na+K)/Al vs K/Al), shows elevation of K due to alteration, also distinguishes the units with igneous K-feldspar (GRD2 and the porphyry units) and indicates that the loss of Ca from alteration coincides with a gain in K, due to muscovite alteration of plagioclase. c. (2Ca+Na+K)/Al vs Na/Al, shows little variability in the Na component indicating that alteration affects the calcic zones of plagioclase.c.93adcbFigure 31: Conserved element plots by differentiation cycle.  The mean value is indicated by the green dot, with analytical error indicated by the bars, the dashed line is the line of best fit.  Samples plotting outside of the line of best fit +/- the calculated error are plotted in red. a. GRD2 samples indicate that both Zr and TiO2 are conserved, failing to reject the cogenetic hypothesis, and indicates that TiO2 is more conserved than Zr as the line of best fit intercepts the Zr axis. b. GRD1a shows two outliers in a population of 97, which is statistically acceptable.  GRD1a fails to reject the cogenetic hypothesis and indicates that TiO2 and Zr are equally conserved. c. Porphyry units have three outliers in a population of 108, which is statistically acceptable. The porphyry units fail to reject the cogenetic hypothesis and indicate that TiO2 and Zr are equally conserved. d. GRD1b + GRD3 populations have eight outliers in a population of 42, which is not statistically acceptable, and a general best fit trend with a negative slope, thereby failing to reject the cogenetic hypothesis. 94adcb Figure 32: Pearce Element Ratio plots and associated spatial plots. PER plots show fresh samples as dark points and altered samples as light; shaded areas indicate point colours on the spatial plots.  Spa-tial plots show strongly altered samples as larger points, weakly altered as medium, and fresh as small black dots, with lithology indicated by the point shape. Alteration intensity is based on the distance a sample plots from the trend of the fresh samples on the PER plot. Spatial plots of the alteration identi-fied in the PER plots are consistent with hand sample and field alteration observations. GRD1b and GRD3 have not been plotted as those units failed the cogenetic hypothesis test. a. (2Ca+K+Na)/Ti vs Al/Ti with the m=1 control line isolating compositional variability introduced by feldspar. Samples plotting towards epidote, muscovite and chlorite control lines are indicative of propylitic, phyllic or both types of alteration, respectively. b. Spatial plot of propylitic and phyllic alteration, with intensity indicated by size. c. Customized PER plot of (2i+7Al+4(Fe+Mg))/Ti vs (18Ca+14Na+25K)/Ti that isolates variability due to anorthite, albite, actinolite, pargasite and biotite in the m=1 control line. Samples plotting near epidote, chlorite, muscovite and K-feldspar control lines indicate alteration. Igneous K-feldspar and lower mafic content results in GRD2 samples plotting to the upper right quandrant. The porphyry units plot between the GRD2 points and GRD1a on the m=1 control line because of the increased K-feldspar and diminished mafic content relative to GRD1a. Four chemically distinct sam-ples are labeled with photographs and the minerals which have affected their plotting space. Fresh samples plot close to the m=1 control line. A sample with quartz veins associated with muscovite and chlorite alteration result in a sample plotting towards the x-axis.  d. Spatial plot of propylitic and phyllic alteration, with intensity indicated by size, based on the proximity of a sample to an alteration mineral control line.95	  	  muscovite	  (m	  =	  1/3)	  and	  chlorite	  (m	  =	  0)	  control	  lines.	  Propylitic	  altered	  samples	  plot	  above	  the	  m	  =	  1	  line	  toward	  the	  epidote	  (m	  =	  2)	  control	  line.	  As	  epidote	  and	  chlorite	  lie	  	  on	  opposite	  sides	  of	  the	  m	  =	  1	  control	  line,	  the	  effect	  of	  propylitic	  alteration	  is	  understated	  by	  the	  chlorite	  content	  causing	  samples	  to	  plot	  towards	  m	  =	  0.	  The	  customized	  PER	  diagram	  has	  axes	  mathematically	  derived	  from	  simplified	  end	  member	  compositions	  of	  anorthite,	  pargasite,	  actinolite,	  albite	  and	  biotite	  (annite)	  (Figure	  9).	  The	  diagram	  [(2Si	  +	  7Al	  +	  4(Fe	  +	  Mg))/Ti	  versus	  (18Ca	  +	  14Na	  +	  25K)/Ti],	  hereon	  referred	  to	  as	  the	  customized	  PER,	  isolates	  the	  compositional	  variability	  of	  the	  primary	  mineralogy	  along	  the	  x=y	  plane,	  emphasizing	  the	  effect	  of	  potassic,	  propylitic	  and	  phyllic	  alteration	  (Figure	  32b).	  Samples	  that	  have	  been	  propylitic	  altered	  plot	  above	  the	  m	  =	  1	  line	  toward	  epidote	  (m	  =	  3/2),	  and	  phyllic	  altered	  plot	  below	  toward	  chlorite	  (m	  =	  0)	  and	  muscovite	  (m	  =	  25/27).	  Primary	  mineralogy	  controls	  the	  majority	  of	  samples	  plotting	  towards	  the	  K-­‐feldspar	  (m	  =	  25/13)	  line.	  Propylitic	  alteration	  is	  understated	  as	  epidote	  plots	  above	  the	  m	  =	  1	  control	  line	  and	  chlorite	  plots	  at	  m	  =	  0,	  similarly,	  phyllic	  alteration	  is	  over-­‐represented	  because	  of	  the	  bias	  introduced	  by	  the	  late	  stage	  chlorite	  alteration	  and	  chlorite	  associated	  with	  the	  propylitic	  assemblage.	  Hand	  sample	  observations	  should	  be	  made	  to	  ensure	  that	  points	  interpreted	  as	  propylitic	  altered	  are	  not	  the	  product	  of	  potassic	  alteration	  or	  primary	  K-­‐feldspar	  mineralogy,	  as	  the	  K-­‐feldspar	  line	  lies	  above	  the	  epidote	  line.	  	  4.4 	  Interpretation	  of	  Alteration	  Processes	  	  SWIR	  results	  in	  combination	  with	  MERs	  and	  simple	  element	  ratios	  from	  Chapter	  three	  are	  used	  to	  identify	  properties	  that	  can	  effectively	  distinguish	  alteration	  on	  a	  regional	  scale.	  Ratios	  that	  distinguish	  alteration	  are	  used	  to	  calculate	  an	  alteration	  index	  that	  relatively	  quantifies	  alteration.	  4.4.1 Identification	  of	  Alteration	  Using	  Shortwave	  Infrared	  Potassic	  Alteration	  	  SWIR	  results	  indicate	  mineralogical	  patterns	  associated	  with	  the	  potassic	  alteration.	  Elevated	  Cu	  populations	  in	  samples	  with	  SpecMin®	  identified	  white	  mica,	  show	  a	  correlation	  between	  elevated	  Cu	  and	  white	  micas	  with	  features	  ranging	  from	  96	  	  2207.5	  and	  2209	  nm	  (Figure	  28c).	  The	  relatively	  high	  wavelength	  for	  white	  micas	  has	  been	  attributed	  to	  Tschermak	  substitution	  of	  [(Al3+)vi	  +	  (Al3+)iv	  <-­‐>	  (Fe2+	  or	  Mg2+	  )vi	  +	  (Si4+)iv]	  in	  illite	  and	  muscovite	  (Cohen	  2012),	  though	  plots	  of	  molar	  Fe	  and	  Mg	  against	  wavelength	  of	  white	  mica	  features	  do	  not	  show	  a	  consistent	  pattern	  (Figure	  28d).	  SpecMin®	  identified	  montmorillonite	  and	  siderite	  in	  potassically	  altered	  samples.	  Neither	  montmorillonite	  nor	  siderite	  were	  identified	  in	  thin	  section	  or	  hand	  sample,	  though	  montmorillonite	  can	  be	  associated	  with	  potassic	  alteration	  (Franchini	  et	  al.	  2007)	  and	  siderite	  could	  either	  be	  associated	  with	  chalcopyrite	  or	  with	  an	  overprinting	  assemblage	  (Reynolds	  &	  Beane	  1985;	  Rose	  1970).	  	  Propylitic	  Alteration	  The	  spatial	  footprint	  of	  SpecMin®	  identified	  epidote,	  chlorite	  and	  illite	  are	  consistent	  with	  that	  of	  the	  propylitic	  assemblage.	  Epidote	  and	  chlorite	  identified	  by	  SpecMin®	  correspond	  spatially	  with	  the	  propylitic	  footprint,	  consistent	  with	  field	  observations	  (Figure	  29a).	  Illite	  also	  shows	  a	  correlation	  with	  the	  propylitic	  footprint	  (Figure	  29c).	  Illite	  and	  chlorite	  tend	  to	  interlayer,	  and	  though	  not	  identified	  in	  field	  or	  petrographic	  observations,	  illite	  is	  known	  to	  be	  associated	  with	  propylitic	  alteration	  (Franchini	  et	  al.	  2007;	  Allen	  et	  al.	  1996).	  Probability	  plots	  identify	  three	  populations	  based	  on	  the	  wavelength	  of	  features	  within	  the	  identified	  chlorite:	  2335	  to	  2343	  nm,	  2346	  to	  2352	  nm	  and	  2343.5	  to	  2345.5	  nm.	  Chlorite	  with	  features	  towards	  2320	  nm	  are	  theoretically	  more	  Fe-­‐rich	  than	  those	  with	  features	  toward	  2350	  nm	  (Halley	  2008).	  These	  populations	  have	  been	  interpreted	  as	  Fe-­‐rich,	  intermediate	  and	  Mg-­‐rich,	  respectively,	  though	  Fe	  and	  Mg	  fluctuations	  on	  this	  scale	  are	  not	  noticeable	  in	  geochemical	  results:	  EMP	  calculated	  chlorite	  compositions	  would	  confirm	  this	  pattern	  (Figure	  29a).	  Chlorite	  is	  Fe-­‐rich	  proximal	  to	  the	  porphyry	  corridor,	  transitioning	  through	  intermediate,	  and	  Mg-­‐rich	  distally,	  according	  to	  this	  interpretation	  (Figure	  29b).	  	  Phyllic	  Alteration	  	  The	  phyllic	  assemblage	  is	  not	  consistently	  represented	  by	  the	  SWIR	  results.	  SpecMin®	  software	  identified	  muscovite	  and	  chlorite,	  though	  they	  do	  not	  show	  spatial	  correlation	  with	  the	  phyllic	  alteration	  footprint.	  Feature	  properties	  such	  as	  wavelength	  97	  	  and	  depth	  for	  white	  micas	  and	  chlorite	  do	  not	  show	  any	  patterns	  that	  aid	  in	  the	  identification	  of	  phyllic	  alteration.	  	  	  4.4.2 Identification	  of	  Alteration	  Using	  Lithogeochemistry	  Potassic	  Alteration	  	  Potassic	  alteration	  in	  felsic	  host	  rocks	  is	  not	  well	  characterized	  by	  MER	  plots	  due	  to	  the	  compositional	  similarity	  between	  alteration	  mineralogy	  and	  primary	  mineralogy.	  Secondary	  biotite	  is	  well	  developed	  in	  potassic-­‐altered	  samples	  at	  Relincho,	  especially	  when	  replacing	  hornblende,	  though	  EMP	  results	  indicate	  that	  the	  compositional	  difference	  between	  primary	  and	  secondary	  biotite	  is	  minimal	  (Appendix	  D).	  K-­‐feldspar	  replacement	  of	  plagioclase	  is	  weak	  to	  moderate	  even	  in	  samples	  with	  strong	  potassic	  alteration.	  	  Primary	  mineralogy	  overshadows	  the	  K-­‐feldspar	  alteration	  trends	  in	  the	  PER	  and	  GER	  diagrams	  (Figure	  30	  and	  Figure	  32).	  Points	  trending	  towards	  the	  GER	  K-­‐feldspar	  nodes	  are	  predominantly	  from	  the	  GRD2	  and	  porphyry	  units	  representative	  of	  igneous	  K-­‐feldspar	  as	  opposed	  to	  alteration	  (Figure	  30a	  and	  b).	  In	  both	  PER	  diagrams	  the	  porphyry	  units	  plot	  high	  on	  the	  x	  =	  y	  line	  because	  of	  the	  relatively	  high	  K	  from	  igneous	  K-­‐feldspar	  and	  low	  Ti	  from	  lower	  mafic	  mineral	  content	  (Figure	  32a	  &	  b).	  Epidote	  confounds	  the	  identification	  of	  K-­‐feldspar	  alteration	  in	  the	  customized	  PER	  diagram	  by	  having	  a	  control	  line	  at	  m	  =	  3/2,	  on	  the	  same	  side	  of	  the	  x	  =	  y	  line	  as	  K-­‐feldspar	  (m	  =25/13).	  Epidote	  alteration	  is	  generally	  a	  stronger	  intensity	  than	  K-­‐feldspar	  alteration,	  and	  dominates	  on	  this	  diagram.	  Potassic	  alteration	  is	  commonly	  overprinted	  by	  propylitic	  or	  phyllic	  alteration,	  which	  further	  confuses	  interpretations	  of	  potassic	  alteration,	  muting	  the	  effects	  of	  K-­‐feldspar	  alteration	  by	  pulling	  samples	  toward	  the	  control	  lines	  of	  epidote	  (m	  =	  3/2),	  chlorite	  (m	  =	  0)	  and	  muscovite	  (m	  =	  25/27)	  (Figure	  32).	  The	  similarity	  of	  primary	  and	  alteration	  mineralogy	  in	  the	  granodiorite	  and	  porphyry	  units,	  combined	  with	  the	  alteration	  overprinting	  of	  the	  phyllic	  and	  propylitic	  assemblages	  makes	  interpretations	  and	  quantifications	  using	  MER	  diagrams	  difficult	  and	  inaccurate.	  	  98	  	  The	  simple	  element	  ratio	  of	  K2O/Th	  discussed	  in	  Chapter	  three	  is	  a	  better	  indicator	  of	  potassic	  alteration	  than	  either	  the	  SWIR	  interpretations	  or	  the	  MERs.	  It	  is	  simple,	  fast	  and	  effective.	  Alteration	  indices	  are	  calculated	  using	  K2O/Th	  for	  the	  relative	  quantification	  of	  alteration.	  	  Propylitic	  Alteration	  Feldspar	  space	  GER	  diagrams	  do	  not	  effectively	  represent	  propylitic	  alteration.	  Propylitic	  associated	  albite	  alteration,	  where	  present,	  is	  weak	  and	  does	  not	  produce	  significant	  geochemical	  variation.	  Albite	  alteration	  should	  result	  in	  a	  replacement	  of	  Ca	  by	  Na	  in	  plagioclase,	  which	  would	  be	  reflected	  by	  a	  loss	  of	  Ca	  and	  gain	  in	  Na	  in	  feldspar	  space	  GERs.	  Instead,	  Na	  concentration	  shows	  little	  variability,	  rendering	  the	  feldspar	  space	  GER	  diagrams	  ineffective	  at	  depicting	  propylitic	  alteration	  (Figure	  30c).	  	  Most	  effective	  for	  the	  interpretation	  of	  propylitic	  alteration	  are	  the	  feldspar	  space	  and	  customized	  PER	  diagrams	  (Figure	  32a	  and	  c).	  In	  both	  diagrams	  points	  plotting	  above	  the	  m=1	  line	  are	  indicative	  of	  epidote	  alteration,	  as	  confirmed	  by	  hand	  sample	  observations.	  The	  further	  a	  sample	  plots	  from	  the	  unaltered	  m	  =	  1	  composition,	  the	  more	  altered	  the	  sample	  is	  interpreted	  to	  be.	  The	  K-­‐feldspar	  control	  line	  on	  the	  customized	  PER	  diagram	  lies	  above	  the	  epidote	  control	  line	  and	  can	  mask	  epidote	  alteration.	  The	  chlorite	  control	  line	  (m	  =	  0)	  lies	  below	  the	  m	  =	  1	  control	  line	  resulting	  in	  a	  muted	  representation	  of	  propylitic	  alteration,	  as	  epidote	  lies	  above	  m	  =	  1	  and	  both	  are	  present	  in	  propylitic	  alteration	  (Figure	  32a	  and	  c).	  Hand	  sample	  and	  petrography	  observations	  are	  beneficial	  to	  confirm	  that	  epidote	  alteration	  as	  the	  cause	  of	  trends	  towards	  the	  epidote	  line.	  	  	  Phyllic	  Alteration	  Phyllic	  alteration	  is	  commonly	  so	  weak	  that	  it	  is	  only	  evident	  through	  microscope	  petrography	  by	  the	  incipient	  muscovite	  alteration	  of	  calcic	  zones	  of	  plagioclase,	  yet	  the	  GER	  and	  PER	  diagrams	  readily	  identify	  the	  process	  of	  phyllic	  alteration.	  Trends	  towards	  the	  K-­‐feldspar	  node	  on	  the	  GER	  diagram	  2CNK/Al	  versus	  K/Al	  suggest	  that	  a	  gain	  in	  K	  in	  plagioclase	  is	  due	  to	  K-­‐feldspar	  alteration	  (Figure	  30a).	  When	  compared	  to	  the	  99	  	  diagram	  2CNK/Al	  versus	  2Ca/Al,	  the	  loss	  of	  Ca	  and	  gain	  in	  K	  is	  shown	  to	  be	  consistent	  with	  muscovite	  alteration	  of	  the	  plagioclase,	  with	  trends	  towards	  K-­‐feldspar	  node	  controlled	  by	  primary	  mineralogy	  (Figure	  30b).	  Petrography	  and	  staining	  confirms	  that	  the	  gain	  of	  K	  and	  loss	  of	  Ca	  is	  due	  to	  the	  incipient,	  selective	  alteration	  of	  calcic	  zones	  in	  plagioclase	  to	  muscovite	  (Figure	  15c).	  	  The	  feldspar	  space	  and	  customized	  PER	  diagrams	  depict	  the	  effect	  of	  phyllic	  alteration	  by	  isolating	  the	  control	  lines	  for	  chlorite	  and	  muscovite	  to	  below	  the	  x	  =	  y	  control	  line	  (Figure	  32a	  and	  c).	  Unaltered	  samples	  plot	  along	  the	  m	  =	  1	  control	  line	  with	  points	  plotting	  closest	  to	  the	  chlorite	  control	  line	  (m	  =	  0)	  being	  the	  most	  phyllic	  altered.	  Chlorite	  is	  associated	  with	  both	  the	  phyllic	  and	  propylitic	  assemblages,	  as	  chlorite	  lies	  below	  the	  m	  =	  1	  control	  line	  and	  epidote	  above,	  this	  could	  lead	  to	  an	  over-­‐representation	  of	  phyllic	  altered	  samples,	  depending	  on	  the	  intensity	  of	  chlorite	  alteration	  versus	  epidote.	  	  4.4.3 Alteration	  Indices	  and	  Quantification	  Alteration	  intensity	  can	  be	  relatively	  quantified	  geochemically	  by	  using	  the	  lever	  rule	  on	  a	  MER	  diagram	  used	  to	  depict	  and	  constrain	  alteration	  processes,	  or	  by	  creating	  an	  alteration	  index.	  	  Alteration	  is	  relatively	  quantified	  by	  observing	  the	  distance	  between	  a	  fresh	  sample	  (or	  the	  x	  =	  y	  control	  line	  for	  PER	  diagrams)	  and	  altered	  samples.	  For	  phyllic	  and	  propylitic	  alteration	  this	  quantification	  is	  most	  easily	  performed	  using	  the	  feldspar	  space	  or	  customized	  PER	  diagrams	  (Figure	  32b	  and	  d).	  As	  the	  MER	  diagrams	  did	  not	  reflect	  potassic	  alteration,	  this	  method	  is	  not	  applicable	  to	  potassic	  alteration	  in	  this	  case.	  Alteration	  indices	  can	  be	  calculated	  using	  a	  proven	  effective	  ratio.	  On	  a	  regional	  scale	  at	  Relincho	  the	  simple	  ratio	  K2O/Th	  effectively	  represents	  potassic	  alteration,	  and	  the	  customized	  PER	  plot	  [(2Si	  +	  7Al	  +	  4(Fe	  +	  Mg))/Ti	  versus	  (18Ca	  +	  14Na	  +	  25K)/Ti]	  is	  effective	  for	  identifying	  propylitic	  and	  phyllic	  alteration.	  In	  order	  to	  quantify	  the	  alteration,	  populations	  of	  unaltered	  and	  altered	  samples	  are	  identified	  using	  probability	  plots	  of	  the	  ratios	  (18Ca	  +	  14Na	  +	  25K)/(2Si	  +	  7Al	  +	  4(Fe	  +	  Mg)),	  hereon	  referred	  to	  as	  the	  propylitic-­‐phyllic	  index,	  and	  K2O/Th,	  hereon	  referred	  to	  as	  the	  potassic	  index	  100	  	  (Figure	  33a	  and	  c).	  On	  a	  PER	  plot	  unaltered	  samples	  should	  lie	  on	  the	  line	  of	  m	  =	  1.	  According	  to	  the	  probability	  plot	  of	  the	  propylitic-­‐phyllic	  index	  unaltered	  samples	  lie	  between	  0.94	  and	  1.04	  (Figure	  33a).	  Samples	  below	  0.94	  are	  considered	  phyllic-­‐altered	  with	  P-­‐04	  identified	  as	  most	  altered	  as	  it	  has	  the	  lowest	  alteration	  index	  value.	  Samples	  above	  1.04	  are	  propylitic-­‐altered	  with	  A-­‐08	  identified	  as	  most	  altered	  as	  it	  has	  the	  highest	  alteration	  index	  value.	  Using	  these	  two	  samples	  with	  0.94	  and	  1.04	  to	  represent	  an	  unaltered	  baseline	  for	  phyllic	  and	  propylitic	  alteration	  respectively,	  alteration	  intensity	  is	  calculated	  using	  equation	  (2).	  The	  probability	  plot	  for	  the	  potassic	  index	  indicates	  the	  unaltered	  population	  at	  and	  below	  0.36,	  identifying	  H-­‐05	  as	  most	  potassically	  altered	  sample	  (Figure	  33c).	  Relative	  alteration	  quantification	  is	  calculated	  for	  each	  sample	  using	  the	  formula:	  	  ?????????	  	  	  	  	  	  	  	  	  (2)	  	  	  Where	  X	  is	  the	  sample	  value,	  XF	  is	  the	  value	  for	  the	  fresh	  sample	  and	  XA	  is	  the	  value	  for	  the	  most	  altered	  sample	  identified	  by	  the	  alteration	  index.	  This	  creates	  a	  quantification	  that	  ranges	  between	  fresh	  (0)	  and	  most	  altered	  (1).	  Spatial	  plots	  of	  the	  alteration	  indices	  show	  intensity	  as	  the	  size	  of	  the	  bubbles	  for	  the	  256	  granodiorite	  and	  porphyry	  samples	  over	  approximately	  35	  km2	  (Figure	  33b	  and	  d).	  The	  alteration	  indices	  identify	  potassic,	  propylitic	  and	  phyllic	  alteration	  and	  correctly	  indicate	  increasing	  alteration	  intensity	  with	  proximity	  to	  the	  porphyry	  corridor.	  	  4.4.4 Comments	  on	  Sample	  Spacing	  for	  Regional	  Exploration	  Sample	  spacing	  used	  for	  this	  survey,	  approximately	  250	  m	  over	  known	  mineralization,	  and	  500	  m	  adjacent	  to	  mineralization,	  was	  adequate	  for	  the	  purpose	  of	  using	  lithogeochemistry	  to	  identify	  potentially	  fertile	  environments,	  characterize	  lithological	  units	  and	  identify	  alteration	  indices.	  Using	  only	  the	  porphyry	  and	  granodiorite	  samples	  and	  de-­‐sampling	  the	  grid	  to	  a	  wider	  spacing	  allows	  for	  the	  assessment	  of	  the	  necessary	  sample	  spacing	  for	  target	  identification.	  Probability	  plots	  101 ............-­‐7110.-­‐4237105.6666.7666.8666.9666.666.666.666.666.666.666.6666.9666.97666. 99666. 9666.9666.9666.-­‐13220.Figure 33: Alteration indices calculated for propylitic-phyllic and potassic alteration of porphyry and granodiorite samples  a. Propylitic-phyllic index probability plot indicates that samples below 0.94 are phyllic-altered, and samples above 1.04 are propylitic-altered b. Spatial plot using the propylitic-phyllic alteration index for point size, c. Potassic index probability plots indicate a population break around 0.36, indicating samples above 0.36 are potassic-altered and d. Spatial plot using the potassic altera-tion index for point size.a. b.c. d.Propylitic-Phyllic Index Potassic Index102	  	  of	  the	  potassic	  and	  propylitic-­‐phyllic	  alteration	  indices	  for	  each	  sample	  spacing	  set	  determines	  if	  this	  new	  set	  of	  samples	  will	  identify	  populations	  representative	  of	  potassic,	  propylitic	  or	  phyllic	  alteration.	  	  	  Two	  examples	  of	  sample	  spacing	  are	  evaluated:	  a	  grid	  with	  1000	  m	  sample	  spacing	  for	  a	  total	  of	  32	  samples,	  and	  a	  grid	  with	  approximately	  2000	  m	  spacing	  with	  7	  samples	  (Figure	  34).	  Thresholds	  interpreted	  from	  the	  probability	  plot	  of	  the	  entire	  survey	  are	  applied	  to	  the	  new	  sample	  populations	  to	  identify	  alteration.	  Over	  an	  area	  of	  approximately	  35	  km2,	  the	  1000	  m	  spacing	  sampling	  grid	  identified	  15	  phyllic,	  two	  propylitic	  and	  26	  potassic	  altered	  samples,	  out	  of	  a	  sample	  set	  of	  32	  (Figure	  34a	  and	  b).	  Alteration	  indices	  identified	  five	  phyllic;	  one	  propylitic;	  and	  three	  potassic-­‐altered	  samples	  out	  of	  a	  sample	  set	  of	  seven,	  at	  2000	  m	  sample	  spacing	  (Figure	  34c	  and	  d).	  The	  Cu	  and	  Mo	  concentrations	  are	  high	  in	  four	  of	  the	  five	  most	  potassic	  altered	  samples	  in	  the	  1000	  m	  sample	  spacing,	  but	  are	  low	  in	  the	  potassic-­‐altered	  samples	  identified	  by	  the	  2000	  m	  spacing	  (Figure	  34).	  4.4.5 Using	  Alteration	  Indices	  as	  a	  Vector	  to	  Mineralization	  To	  examine	  the	  alteration	  indices	  as	  an	  indicator	  of	  distance	  to	  ore	  both	  alteration	  indices	  are	  plotted	  for	  three	  transects	  over	  the	  deposit	  with	  Cu	  concentrations	  and	  the	  porphyry	  corridor	  indicated	  (Figure	  35).	  There	  is	  little	  correlation	  between	  the	  alteration	  index	  and	  proximity	  to	  the	  porphyry	  corridor,	  nor	  is	  there	  much	  of	  a	  correlation	  between	  Cu	  concentration	  and	  the	  potassic	  indicator.	  The	  northern	  transect	  shows	  low,	  erratic	  potassic	  index	  values	  over	  the	  porphyry	  corridor	  consistent	  with	  low,	  erratic	  Cu	  concentrations,	  with	  a	  slight	  increase	  in	  potassic	  index	  values	  and	  Cu	  concentrations	  directly	  adjacent	  to	  the	  porphyry	  corridor.	  The	  propylitic-­‐phyllic	  index	  does	  not	  show	  any	  trend	  (Figure	  35b).	  The	  central	  transect	  shows	  relatively	  stable,	  high	  potassic	  index	  values	  over	  the	  porphyry	  corridor	  accompanied	  by	  highly	  erratic	  Cu	  concentrations,	  and	  relatively	  stable	  propylitic-­‐phyllic	  index	  values.	  The	  southern	  transect	  shows	  a	  weak	  correlation	  between	  elevated	  potassic	  index	  values	  and	  Cu	  concentration,	  and	  still	  no	  correlation	  with	  the	  propylitic-­‐phyllic	  alteration	  index.	  	   	  103............-­‐7110.-­‐4237105. ............ . . . . .5706621-­‐37.47.33603.1514303.84459.48 4.94373.260.737.170.48....... . . . . .-­‐7110.-­‐4237105.............  . . . . . .576630.-­‐4128.Figure 34: Potassic and propylitic-phyllic alteration indices for porphyry and granodiorite samples at 1000 m and 2000 m sample spacing. Concentrations of Cu (red) and Mo (blue) in ppm are indicated adjacent to the 5 most potassic altered samples on the spatial plots.  a. Propylitic-phyllic alteration indices at 1000 m sample spacing, b. Potassic alteration index at 1000 m sample spacing, c. Propylitic-phyllic alteration indices at 2000 m sample spacing,  and d. Potassic alteration index at 2000 m sample spacing, a. b.c. d.81.010.4343.571.297.590.38104.. .!.#... .!.#.... .!.#... .!.#." . ". ""!. "!.C)	  mme	  AapSnOuli	  KiPS2	  DOouiT	  e	  M	  8051.723.8965146651.723.-­‐..!..!..!..!. . !... .".$... .".$.# !. #  . ##  . #$. # !.C(	  3lla	  AToPmMpie	  KeOP)	  DMnpeS	  3a	  C	  8051.723.8965146651.723.-­‐... .".$... ."... .".$... .".$.#! #. #""%.C)	  mme	  AapSnOuli	  KiPS2	  DOouiT	  e	  M	  8051.723.8965146651.723.-­‐.a. b.c. d.1 kmNTransectsPorphyry CorridorGRD1a SampleNSCFigure 35: The propylitic-phyllic index ((18Ca+14Na+25K)/(2Si+7Al+4(Fe+Mg)), green) and potassic index (K2O/Th, pink) alteration indices plotted with Cu concentraitons (red) as transects across the porphyry corridor (grey box). Alteration index values are indicated on the left y-axis, Cu concentration values are on the right y-axis. a. Sample sites with porphyry corridor  and transects North (N), Centre (C) and South (S) indicated: , b. North transect showing a correlation between elevated Cu concentra-tions with elevated K2O/Th values and no correlation with the customized alteration index. The K2O/Th index seems to be higher adjacent to the porphyry corridor as opposed to within it. c. The centre tran-sect does not indicate any consistent pattern between the alteration indeces and Cu concentration, or proximity to the porphyry corridor. d. The south transect does not indicate any consistent pattern between the alteration indeces and Cu concentration, or proximity to the porphyry corridor.105	  	  	  The	  lack	  of	  correlation	  between	  the	  alteration	  indices,	  Cu	  concentration	  and	  proximity	  to	  the	  porphyry	  corridor	  is	  potentially	  a	  product	  of	  inconsistent	  flow	  patterns	  of	  the	  hydrothermal	  fluids.	  The	  inconsistent	  flow	  could	  be	  a	  product	  of	  variations	  in	  permeability	  between	  lithological	  units,	  surface	  area	  of	  primary	  minerals,	  or	  due	  to	  the	  presence	  of	  structures,	  which	  form	  fluid	  pathways.	  The	  permeability	  in	  units	  with	  porphyritic	  texture	  is	  higher	  than	  those	  with	  the	  idiomorphic	  texture	  due	  to	  the	  porous	  nature	  of	  the	  groundmass.	  Grain	  sizes	  in	  the	  porphyry	  units	  are	  smaller	  and	  therefore	  a	  higher	  surface	  area,	  allowing	  for	  increased	  alteration	  of	  the	  surface	  areas.	  Northeast-­‐southwest	  regional	  structures	  provide	  conduits	  for	  the	  alteration	  fluids	  resulting	  in	  uneven	  dispersal	  of	  alteration	  fluids.	  Though	  the	  alteration	  indices	  are	  not	  suitable	  for	  calculating	  the	  distance	  a	  sample	  is	  from	  mineralization,	  the	  transects	  show	  that	  alteration	  indices	  behave	  independently	  from	  Cu	  concentration.	  This	  implies	  that	  areas	  identified	  as	  prospective	  by	  alteration	  indices,	  would	  not	  be	  identified	  by	  elevated	  Cu	  concentrations.	  	  4.4.6 Comments	  on	  Alteration	  Indices	  The	  propylitic-­‐phyllic	  alteration	  index	  calculated	  for	  Relincho	  is	  similar	  to	  that	  calculated	  by	  Urqueta	  et	  al.	  (2009)	  for	  the	  Collahuasi	  epithermal	  cluster	  in	  Chile:	  (18Ca+13Na)/(2Si+7Al+4(Mg+Fe)).	  As	  at	  Relincho,	  the	  alteration	  indices	  identified	  propylitic	  alteration,	  but	  were	  unsuccessful	  as	  a	  tool	  for	  determining	  the	  distance	  to	  ore	  mineralization.	  4.5 Exploration	  Implications	  of	  Interpretations	  Lithogeochemistry	  of	  surface	  samples	  identifies	  potassic,	  propylitic	  and	  phyllic	  alteration	  at	  Relincho	  using	  SWIR,	  basic	  statistics	  and	  MER	  plots.	  Potassic	  alteration,	  though	  not	  evident	  in	  PER	  and	  GER	  plots	  due	  to	  the	  compositional	  similarity	  between	  primary	  mineralogy	  potassic	  alteration	  mineralogy,	  is	  consistent	  with	  elevated	  K2O/Th	  populations.	  Propylitic	  alteration	  is	  optimally	  characterized	  using	  a	  combination	  of	  PER	  plots,	  which	  identify	  epidote	  alteration.	  Weak	  phyllic	  alteration	  is	  characterized	  using	  a	  combination	  of	  PER	  and	  GER	  plots.	  Even	  weakly	  altered	  samples	  with	  incipient	  muscovite	  alteration	  of	  calcic	  zones	  in	  plagioclase	  are	  evident	  in	  the	  PER	  and	  GER	  plots.	  	  106	  	  The	  potassic	  (K2O/Th)	  and	  propylitic-­‐phyllic	  ((18Ca	  +	  14Na	  +	  25K)/(2Si	  +	  7Al	  +	  4(Fe	  +	  Mg)))	  alteration	  indices	  relatively	  quantify	  alteration	  intensity	  and	  determine	  necessary	  sample	  spacing.	  Using	  the	  Relincho	  deposit	  as	  a	  test,	  these	  indices	  could	  identify	  a	  blind	  target	  as	  an	  area	  for	  exploration	  follow-­‐up	  using	  a	  sample	  spacing	  of	  up	  to	  2000	  m.	  Sample	  spacing	  of	  2000	  m	  identifies	  potassic,	  propylitic	  and	  phyllic	  alteration	  even	  when	  Cu	  and	  Mo	  concentrations	  do	  not.	  Though	  the	  indices	  identify	  target	  areas,	  transects	  over	  the	  porphyry	  corridor	  indicate	  that	  the	  indices	  are	  not	  applicable	  for	  determining	  the	  distance	  to	  mineralization.	  This	  ability	  to	  identify	  alteration	  assemblages	  through	  basic	  statistics	  and	  lithogeochemistry	  means	  that	  alteration	  fluid	  pathways	  could	  be	  mapped	  regionally,	  and	  in	  3-­‐dimensional	  models.	  Because	  of	  the	  predictable	  pattern	  of	  porphyry	  alteration	  haloes	  (Lowell	  &	  Guilbert	  1970;	  Seedorff	  2005;	  Sillitoe	  2010),	  these	  population	  distinctions	  can	  be	  used	  to	  identify	  areas	  of	  interest	  for	  porphyry	  style	  mineralization,	  following	  alteration	  assemblages	  towards	  potassic	  alteration	  and	  potential	  mineralization.	  	  	  	   	  107	  	  Chapter	  5:	  Conclusions	  and	  Implications	  for	  Exploration	  5.1 Summary	  of	  Research	  Results	  Surface	  lithogeochemistry,	  in	  combination	  with	  petrography	  and	  SWIR,	  were	  successfully	  used	  to	  characterize	  the	  lithological	  units	  and	  alteration	  assemblages	  at	  the	  Relincho	  PCD.	  Three	  effective	  methods	  have	  been	  identified	  in	  this	  study:	  	  1. Rock	  fertility	  assessment	  for	  identifying	  regions	  of	  potential	  PCD	  mineralization;	  2. Potassic,	  propylitic	  and	  phyllic	  alteration	  assemblage	  characterization	  through	  spatial	  element	  distributions,	  and	  simple	  and	  molar	  element	  ratios;	  3. Quantifying	  alteration	  intensity	  on	  a	  regional	  scale	  through	  the	  application	  of	  alteration	  indices.	  	  5.1.1 Rock	  Fertility	  Assessment	  Four	  host	  granodiorite	  units	  and	  four	  porphyry	  units	  were	  distinguished	  based	  on	  mineralogy,	  texture	  and	  geochemistry.	  Magma	  evolution	  diagrams	  indicate	  that	  the	  granodiorite	  and	  porphyry	  units	  evolved	  in	  the	  following	  order:	  [GRD1b	  +	  GRD3]	  à	  GRD1a	  à	  [PQF1	  +	  PQF2	  +	  PFB	  +	  PQB]	  à	  GRD2.	  They	  are	  interpreted	  as	  the	  product	  of	  four	  differentiation	  cycles	  and	  three	  magma	  recharges	  (indicated	  by	  arrows),	  although	  evolution	  between	  the	  porphyry	  units	  is	  unclear.	  Fertility	  was	  assessed	  for	  each	  of	  these	  differentiation	  cycles.	  GRD1a,	  GRD2	  and	  the	  porphyry	  units	  are	  identified	  as	  potentially	  fertile	  and	  [GRD1b	  +	  GRD3]	  potentially	  infertile,	  on	  the	  basis	  of	  N-­‐MORB	  normalized	  REEs	  and	  Y	  versus	  Sr/Y	  properties,	  considered	  to	  be	  indicative	  of	  hornblende	  fractionation	  in	  high	  magmatic	  water	  content	  magmas.	  5.1.2 Alteration	  Characterization	  Lithogeochemistry	  of	  surface	  samples	  identifies	  potassic,	  propylitic	  and	  phyllic	  alteration	  using	  simple	  element	  ratios	  and	  MERs.	  The	  spatial	  footprint	  of	  elevated	  K2O/Th	  and	  Cu	  populations	  in	  the	  GRD1a	  unit	  serves	  as	  a	  proxy	  for	  potassic	  alteration.	  Propylitic	  and	  phyllic	  alteration	  are	  best	  characterized	  by	  the	  feldspar-­‐space	  (Al/Ti	  108	  	  versus	  (2Ca+K+Na)/Ti)	  and	  customized	  ((2Si	  +	  7Al	  +	  4(Fe	  +	  Mg))/Ti	  versus	  (18Ca	  +	  14Na	  +	  25K)/Ti)	  PER	  diagrams.	  The	  PER	  diagrams	  isolate	  propylitic	  alteration	  processes	  above	  the	  m	  =	  1	  line,	  and	  phyllic	  alteration	  processes	  below.	  Phyllic	  and	  propylitic	  alteration	  can	  be	  visually,	  relatively	  quantified	  by	  assessing	  the	  distance	  between	  a	  point’s	  position	  and	  the	  fresh	  composition	  control	  line	  (m	  =	  1)	  on	  these	  PER	  diagrams.	  	  5.1.3 Quantifying	  Alteration	  Intensity	  on	  a	  Regional	  Scale	  Alteration	  indices	  are	  calculated	  from	  simple	  and	  molar	  element	  ratios	  to	  quantify	  potassic,	  propylitic	  and	  phyllic	  alteration.	  Using	  K2O/Th	  as	  the	  potassic	  index	  and	  ((18Ca	  +	  14Na	  +	  25K)/(2Si	  +	  7Al	  +	  4(Fe	  +	  Mg))	  as	  the	  propylitic-­‐phyllic	  index,	  five	  phyllic,	  one	  propylitic	  and	  three	  potassic	  altered	  samples	  are	  identified	  at	  a	  sample	  spacing	  of	  2000	  m.	  5.2 Comparison	  of	  Methodologies	  	  5.2.1 Gain-­‐Loss	  versus	  Molar	  Element	  Ratios	  Gain-­‐loss	  variations	  provide	  detailed	  information	  about	  alteration	  processes,	  though	  they	  can	  easily	  be	  miscalculated	  when	  in-­‐depth	  knowledge	  of	  lithological	  units	  and	  alteration	  assemblages	  is	  lacking.	  It	  is	  imperative	  that	  gain-­‐loss	  calculations	  be	  done	  using	  the	  same	  rock	  type	  for	  both	  altered	  and	  unaltered	  compositions.	  This	  can	  be	  difficult	  when	  separating	  lithological	  units	  geochemically,	  especially	  when	  there	  is	  limited	  background	  geological	  knowledge.	  Distinguishing	  attributes	  (e.g.	  REE	  and	  HFSE	  concentrations)	  must	  be	  examined	  to	  ensure	  the	  same	  lithological	  units	  are	  being	  compared.	  At	  Relincho	  there	  are	  very	  few	  samples	  that	  are	  unaltered,	  with	  almost	  all	  samples	  having	  undergone,	  at	  least,	  chlorite	  alteration	  to	  some	  extent.	  Field	  observations	  as	  well	  as	  MERs	  were	  relied	  upon	  to	  find	  least-­‐altered	  and	  most-­‐altered	  compositions	  to	  be	  used	  for	  the	  gain-­‐loss	  calculations.	  Element	  variability	  is	  lost	  if	  the	  altered	  and	  fresh	  samples	  are	  not	  carefully	  selected.	  Weak	  alteration	  intensity	  and	  overlapping	  alteration	  assemblages	  at	  Relincho	  also	  complicated	  gain-­‐loss	  variation	  interpretations.	  The	  gain-­‐loss	  results	  showed	  illogical	  patterns	  when	  entire	  populations	  (i.e.	  all	  potassic	  altered	  GRD1a	  samples)	  were	  used	  for	  calculations.	  	  109	  	  Numerous	  lithological	  units	  can	  be	  plotted	  on	  MER	  diagrams	  simultaneously,	  as	  long	  as	  they	  are	  distinguishable	  on	  the	  plot.	  This,	  by	  default,	  increases	  the	  population	  represented	  by	  the	  diagram.	  MER	  diagrams	  indicate	  the	  process	  of	  alteration	  by	  showing	  a	  compositional	  trend	  from	  a	  primary	  mineral	  composition	  to	  an	  alteration	  mineral	  composition.	  Alteration	  intensity	  can	  be	  relatively	  quantified	  on	  an	  MER	  diagram	  by	  measuring	  the	  distance	  an	  altered	  point	  plots	  from	  the	  unaltered	  composition.	  Though	  gain-­‐loss	  diagrams	  can	  simultaneously	  express	  numerous	  analytes	  in	  one	  graph,	  they	  also	  require	  an	  in-­‐depth	  knowledge	  of	  the	  host	  lithology	  and	  alteration	  intensity	  and	  are	  labour	  intensive.	  MER	  diagrams	  do	  not	  require	  in-­‐depth	  background	  knowledge	  of	  the	  lithological	  units,	  beyond	  an	  understanding	  of	  what	  primary	  and	  alteration	  mineralogy	  is	  for	  the	  construction	  of	  the	  MER	  diagram.	  MER	  diagrams	  are	  more	  effective	  than	  gain-­‐loss	  diagrams	  at	  displaying	  the	  alteration	  processes	  and	  the	  variability	  in	  alteration	  intensity.	  The	  MERs	  are	  more	  easily	  applied	  to	  large	  datasets	  with	  multiple	  lithological	  units.	  5.2.2 Spatial	  Elemental	  Variability	  versus	  Molar	  Element	  Ratios	  Spatial	  element	  variability	  is	  an	  effective	  means	  of	  identifying	  a	  prospective	  area	  for	  PCD	  exploration,	  especially	  in	  conjunction	  with	  the	  gain-­‐loss	  variations.	  Spatial	  variability	  of	  trace	  metals	  such	  as	  Cu,	  Mo,	  Au,	  Pb	  and	  Zn	  show	  typical	  zonation	  of	  a	  PCD	  with	  Cu,	  Mo	  and	  Au	  elevated	  within	  the	  porphyry	  corridor	  and	  Zn	  and	  Pb	  elevated	  distally.	  The	  spatial	  variability	  indicates	  elemental	  trends	  but	  does	  not	  characterize	  an	  alteration	  process,	  or	  indicate	  alteration	  intensity	  as	  MER	  diagrams	  do.	  	  5.2.3 Simple	  Element	  Ratios	  versus	  Molar	  Element	  Ratios	  Simple	  and	  molar	  element	  ratios	  are	  both	  effective	  methods	  of	  quantifying	  alteration	  at	  the	  Relincho	  deposit.	  K2O/Th	  was	  superior	  to	  the	  MERs	  for	  displaying	  and	  quantifying	  potassic	  alteration,	  for	  this	  reason	  it	  was	  used	  as	  the	  potassic	  alteration	  index.	  MERs,	  however,	  were	  more	  effective	  and	  exhibiting	  and	  quantifying	  propylitic	  and	  phyllic	  alteration	  than	  simple	  ratios.	  	  	  	  110	  	  	  5.3 Research	  Shortcomings	  This	  study	  focuses	  on	  regional	  scale	  lithogeochemical	  characterization.	  Though	  successful	  on	  the	  regional	  scale,	  by	  its	  very	  nature	  it	  lacks	  local	  detail:	  • Sample	  spacing	  may	  have	  missed	  some	  important	  alteration	  indicators.	  Project	  geologists	  for	  Teck	  Resources	  Limited	  have	  reported	  strong	  potassic	  alteration	  proximal	  to	  mineralization,	  the	  extent	  of	  which	  was	  not	  observed	  in	  this	  sample	  set;	  • Lack	  of	  lithological	  contact	  or	  vein	  relationship	  information.	  The	  contact	  relationships	  between	  some	  lithological	  units,	  in	  particular	  the	  granodiorite	  units,	  is	  not	  fully	  explored	  by	  this	  study,	  nor	  are	  veins	  characterized;	  • Fresh	  samples	  were	  not	  obtained	  for	  most	  lithological	  units.	  Truly	  unaltered	  samples	  are	  nearly	  impossible	  to	  acquire	  over	  a	  hydrothermal	  system	  with	  an	  alteration	  footprint	  of	  60	  km2.	  This	  leads	  to	  a	  potential	  bias	  in	  alteration	  calculations;	  • A	  failure	  to	  uniquely	  characterize	  the	  porphyry	  units.	  The	  compositional	  overlap	  of	  the	  porphyry	  units	  would	  not	  allow	  for	  characterization;	  • Lack	  of	  characterization	  of	  ore	  mineralogy.	  Due	  to	  destruction	  by	  oxidation,	  ore	  mineral	  assemblages	  are	  not	  described	  in	  detail.	  	  5.4 Research	  Implications	  for	  Exploration	  From	  a	  regional	  exploration	  perspective	  the	  surface	  rock	  lithogeochemistry	  successfully	  identified	  areas	  of	  potential	  mineralization.	  Sample	  spacing	  of	  500	  m	  is	  adequate	  for	  future	  surveys	  designed	  to	  characterize	  lithological	  units	  and	  alteration	  assemblages,	  provided	  that	  adequate	  sample	  populations	  for	  each	  lithology	  are	  acquired.	  Alteration	  indices	  suggest	  that	  sample	  spacing	  up	  to	  2000	  m	  can	  be	  used	  for	  identifying	  areas	  of	  potential	  PCD	  fertility.	  Alteration	  indices	  for	  the	  potassic,	  propylitic	  and	  phyllic	  assemblages	  could	  have	  applications	  for	  mapping	  alteration	  fluid	  pathways	  regionally.	  The	  indices	  could	  also	  be	  applied	  to	  existing	  databases	  or	  as	  a	  prospecting	  tool	  for	  identifying	  potential	  regions	  111	  	  	  for	  porphyry	  style	  mineralization.	  Potassic	  and	  propylitic-­‐phyllic	  indices	  could	  be	  applied	  to	  granodiorite	  dominant	  regions	  using	  thresholds	  of	  K2O/Th	  >	  0.36	  for	  potassic	  alteration	  and	  ((18Ca	  +	  14Na	  +	  25K)/(2Si	  +	  7Al	  +	  4(Fe	  +	  Mg))	  <	  0.94	  for	  potassic,	  and	  ((18Ca	  +	  14Na	  +	  25K)/(2Si	  +	  7Al	  +	  4(Fe	  +	  Mg))	  >	  1.04	  for	  propylitic.	  	  5.5 Recommended	  Exploration	  Methodologies	  for	  Porphyry	  Cu-­‐Mo	  Exploration	  The	  most	  effective	  analytical	  methodologies	  were	  aqua	  regia,	  ICP-­‐MS	  and	  fusion	  ICP-­‐OES	  (Table	  8).	  These	  two	  analytical	  methods	  provide	  all	  the	  trace	  element,	  major	  oxide,	  HFSE	  and	  REE	  data	  necessary	  for	  an	  in-­‐depth	  lithogeochemical	  interpretation.	  Commercial	  XRD	  results	  were	  of	  limited	  value	  to	  the	  extent	  that	  they	  were	  not	  used	  in	  the	  interpretation.	  Fusion	  ICP-­‐OES	  trace	  element	  results	  proved	  to	  be	  of	  equal	  or	  better	  quality	  than	  the	  pressed	  pellet	  XRF	  results,	  with	  detection	  limits	  on	  average	  an	  order	  of	  magnitude	  lower.	  SWIR	  interpretations	  are	  complimentary	  to	  the	  dataset,	  but	  not	  necessary.	  	  Although	  proven	  as	  a	  useful	  tool	  for	  alteration	  mapping	  at	  many	  other	  deposits	  (e.g.	  SWIR	  interpretations	  at	  the	  Pebble	  PCD	  by	  Harraden	  et	  al.	  (2013))	  they	  were	  not	  particularly	  effective	  at	  the	  Relincho	  deposit,	  possibly	  due	  to	  weak	  alteration	  intensity.	  Interpretations	  were	  laborious	  and	  yielded	  results	  that	  were	  largely	  replaceable	  by	  hand	  sample	  observations	  or	  geochemistry.	  	  The	  most	  effective	  interpretive	  methodologies	  for	  PCD	  exploration	  at	  the	  Relincho	  deposit	  were	  rock	  fertility	  assessment,	  and	  simple	  and	  molar	  element	  ratio	  characterization	  of	  alteration	  assemblages	  (Table	  8).	  The	  assessment	  of	  GRD1a,	  GRD2	  and	  the	  porphyry	  units	  as	  potentially	  fertile	  would	  identify	  the	  area	  as	  a	  candidate	  for	  follow-­‐up	  geochemical	  investigation.	  Alteration	  indices	  produced	  from	  simple	  and	  molar	  element	  ratios,	  with	  population	  breaks	  determined	  from	  probability	  plots,	  quantified	  alteration	  and	  could	  be	  applied	  to	  regions	  of	  a	  similar	  geological	  setting	  for	  PCD	  exploration,	  or	  to	  map	  alteration	  intensity	  of	  known	  mineralization	  and	  map	  fluid	  pathways.	  Magmatic	  evolution	  and	  Tukey	  diagrams	  help	  to	  characterize	  lithological	  units,	  but	  are	  not	  necessary	  for	  regional	  exploration.	  Gain-­‐loss	  diagrams	  aid	  in	  characterizing	  alteration	  assemblages,	  but	  are	  potentially	  inaccurate	  when	  there	  is	  limited	  knowledge	  of	  the	  lithological	  host	  units.	  112 Method Purpose Necessary Complimentary NonessentialAqua	  Regia,	  ICPMS Trace	  metals,	  rare	  earth	  elements	  and	  precious	  metals xPressed	  pellet	  XRF Trace	  elements xFusion,	  ICP-­‐OES Major	  oxides	  and	  trace	  elements xSWIR Identification	  of	  alteration	  minerals xXRD Quantification	  of	  mineralogy xMethod Purpose Necessary Complimentary NonessentialFertility	  Assessment Identification	  of	  prospective	  regions	  through	  recognizing	  potentially	  fertile	  lithological	  units xMagmatic	  Evolution Characterization	  of	  lithological	  units xSimple	  Element	  Ratios Identification	  of	  prospective	  regions	  through	  recognizing	  elemental	  patterns xMolar	  Element	  Ratios Identification	  of	  prospective	  regions	  through	  recognizing	  alteration	  patterns xSpatial	  Element	  Variability Identification	  of	  prospective	  regions	  through	  recognizing	  elemental	  patterns xGain-­‐Loss	  Calculations Characterization	  of	  alteration	  assemblages xTukey	  Plots Characterization	  of	  lithological	  units xProbability	  plots Characterization	  of	  alteration	  assemblages xInterpretiveAnalyticalTable 8:Summary of effective analytical and interpretive tools for the characterization of lithological units and alteration assemblages113	  	  	  5.6 Suggested	  Future	  Work	  A	  thorough	  mapping	  program	  would	  glean	  much	  about	  the	  alteration	  fluids	  and	  lithological	  units.	  By	  examining	  the	  veins	  associated	  with	  each	  assemblage,	  more	  could	  be	  understood	  about	  alteration	  fluid	  timing	  and	  composition.	  Prior	  to	  this	  study	  the	  four	  granodiorite	  units	  had	  not	  been	  differentiated.	  Studies	  of	  the	  temporal	  relationships	  of	  the	  four	  granodiorite	  units	  could	  benefit	  property	  scale	  exploration.	  Fluid	  inclusion	  and	  isotope	  work	  could	  be	  considered	  for	  further	  characterization	  of	  the	  alteration	  fluids.	  Fluid	  inclusions	  can	  be	  used	  to	  determine	  relative	  temperature,	  pressure,	  salinity	  and	  gas	  composition	  of	  the	  different	  alteration	  fluids,	  allowing	  for	  a	  better	  understanding	  of	  alteration	  fluid	  composition	  and	  compositional	  evolution	  (Kamilli	  &	  Ohmoto	  1977;	  Arancibia	  &	  Clark	  1996;	  Ulrich	  et	  al.	  2001;	  etc.).	  Isotope	  work	  using	  C,	  H,	  O	  and	  S	  could	  be	  used	  to	  distinguish	  one	  alteration	  events	  (Ulrich	  et	  al.	  2001;	  Cohen	  2012;	  Djouka-­‐Fonkwe	  et	  al.	  2012;	  etc.).	  Sulphur	  isotopes	  could	  be	  used	  in	  the	  drill	  core,	  although	  not	  in	  surface	  samples	  as	  surficial	  processes	  have	  destroyed	  sulphides.	  The	  results	  of	  this	  study	  could	  be	  applied	  to	  an	  in-­‐depth	  characterization	  of	  alteration	  on	  a	  deposit	  scale	  using	  the	  existing,	  extensive	  database	  of	  drill	  core.	  Alteration	  indices	  derived	  from	  this	  study	  could	  be	  applied	  to	  drill	  core	  results	  to	  produce	  a	  three-­‐dimensional	  model	  of	  the	  alteration.	  Spatial	  elemental	  variability,	  probability	  diagrams,	  SWIR	  and	  MERs	  can	  be	  employed	  for	  the	  characterization	  of	  a	  variety	  of	  rock	  types	  and	  deposit	  styles.	  SWIR	  results	  are	  known	  to	  have	  many	  successful	  applications	  for	  alteration	  characterization,	  particularly	  at	  deposits	  with	  clays	  as	  alteration	  minerals	  (Cohen	  2012;	  Barker	  et	  al.	  2013;	  Harraden	  et	  al.	  2013;	  etc.).	  Probability	  plots	  distinguish	  between	  samples	  affected	  by	  a	  process,	  such	  as	  alteration	  or	  mineralization,	  from	  those	  unaffected,	  as	  such	  could	  be	  applied	  to	  any	  deposit	  style	  (Sinclair	  1976).	  Molar	  element	  ratio	  diagrams	  describe	  processes.	  By	  changing	  the	  minerals	  used	  to	  calculate	  the	  axes,	  MER	 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