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![The mechanisms of Cu-porphyry formation (Harris and Golding, 2002; Richards, 2003; Sillitoe, 2010),
theories of location (Tosdal and Richards, 2001), prediction and identification of type mineral assemblages
(Lowell, 1970; Titley, 1982, 1993; Hedenquist at al., 1998; Seedorf et al., 2005; Halley et al., 2015), relative
size and footprint (both vertically and horizontally) of alteration (Sillitoe, 2000,2010; Kerrich, 2000), grade
in relation to size, age, lithology, location and fluid geochemistry (Singer, 1995; Cooke et al., 2005) have all
been profoundly studied in the last 40+ years
“But more fundamentally, however, we require better and more detailed documentation of geologic
relationships in porphyry Cu systems worldwide, at all scales from the thin section to the entire system,
and with greater emphasis on the regional to district scale…[we] must further emphasize the relative
timing of intrusion, brecciation, alteration and mineralization events…this geologic detail [will] hopefully
further clarify the localization and evolutionary histories of porphyry Cu systems as well as the
fundamental controls on large size and high hypogene grade.” (Sillitoe, 2010)
There are three goals:
1. To expand current resource (less risk and highest reward/margins)
2. To optimize current mine process (increasing margins by mining better ore)
3. Greenfield discovery including potential new districts (high risk – low success) ;
Porphyry Alteration](https://image.slidesharecdn.com/pdac2016martinicareywitterfinal-160412183137/75/PDAC-2016-presentation-by-Martini-Carey-Witter-2-2048.jpg)
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PDAC 2016 presentation by Martini, Carey, & Witter
- 1. HYPERSPECTRAL CORE IMAGING FOR CHARACTERIZATIONOF CU- AU PORPHYRY 7 MARCH 2016 Brigette A. Martini, PhD & Ronell Carey, PhD Corescan Jeff Witter, PhD Mira Geosciences Presented at PDAC 2016
- 2. The mechanisms ofCu-porphyry formation (Harris and Golding, 2002; Richards, 2003; Sillitoe, 2010), theories of location (Tosdal and Richards, 2001), prediction and identification of type mineral assemblages (Lowell, 1970; Titley, 1982, 1993; Hedenquist at al., 1998; Seedorf et al., 2005; Halley et al., 2015), relative size and footprint (both vertically and horizontally) of alteration (Sillitoe, 2000,2010; Kerrich, 2000), grade in relation to size, age, lithology, location and fluid geochemistry (Singer, 1995; Cooke et al., 2005) have all been profoundly studied in the last 40+ years “But more fundamentally, however, we require better and more detailed documentation of geologic relationships in porphyry Cu systems worldwide, at all scales from the thin section to the entire system, and with greater emphasis on the regional to district scale…[we] must further emphasize the relative timing of intrusion, brecciation, alteration and mineralization events…this geologic detail [will] hopefully further clarify the localization and evolutionary histories of porphyry Cu systems as well as the fundamental controls on large size and high hypogene grade.” (Sillitoe, 2010) There are three goals: 1. To expand current resource (less risk and highest reward/margins) 2. To optimize current mine process (increasing margins by mining better ore) 3. Greenfield discovery including potential new districts (high risk – low success) ; Porphyry Alteration
- 3. Porphyry alteration variablesfrom hyperspectral imaging -Assemblage identification -subtypes Cu-Mo, Cu-Au -Textures (veined, pervasive, porphyritic) -Paragenesis, vein selvages, cross- cutting, overprints -Sharpness of alteration boundaries -Scaling from fine resolution (cm’s) through to borehole scale (m’s) through to entire deposit scales (km’s)
- 4. Diagnostic spectral absorptionfeatures: VNIR & SWIR 500 1000 1500 2000 2500 Fe3+ Fe3+ Fe2+ Unbound H2O CO3 Unbound H2O MgOH AlOH (Mg,Fe)OH (Al,Fe)OH, (Al,Mg)OH CO3 CO3 (Al,Fe)OH Cu NH4 AlOHOH Mn Cr Ni 500nm 1000nm 1500nm 2000nm 2500nm
- 5. Mobile, Automated, Hyperspectral CoreLogging HCI-3 System Specifications Spectrometers 3 (VNIR, SWIR-A, SWIR-B) Spectral range 450nm - 2500nm Spectral resolution ~4nm Scan modes 0.5mm square pixels Spectral calibration Detailed full width scan Reconnaissance profile scan Radiometric calibration Spectralon reflectance standard, dark current RGB image resolution 50 µm Height profile resolution 20 µm Core tray sizes Up to 0.6m x 1.5m (WxL) Scan rates 200m to 1000m per day depending on operational constraints
- 6. Porphyry alteration: Typicalassemblages Sodic-Calcic • Albite/oligoclase • Actinolite • Magnetite • Diopside • Epidote • Garnet Modified from Sillitoe, 2010
- 7. Porphyry alteration: Typicalassemblages Sodic-Calcic • Albite/oligoclase • Actinolite • Magnetite • Diopside • Epidote • Garnet Magnetite Cu-Au Low Mineral match High Magnetite
- 8. Porphyry alteration: Typicalassemblages Potassic • Biotite • K-spar • Actinolite • Epidote • Sericite • Albite • Carbonate • Tourmaline • Magnetite Modified from Sillitoe, 2010
- 9. Porphyry alteration: Typicalassemblages Potassic • Biotite • K-spar • Actinolite • Epidote • Sericite • Albite • Carbonate • Tourmaline • Magnetite ~2325nm ~2250nm ~1380nm ~2390nm Biotite Biotite Actinolite Mont. Sericite K-spar Cu-Au
- 10. Porphyry alteration: Typicalassemblages Propylitic • Chlorite • Epidote • Albite • Carbonate Modified from Sillitoe, 2010
- 11. Porphyry alteration: Typicalassemblages Propylitic • Chlorite • Epidote • Albite • Carbonate Chlorite ChloriteChem Epidote Calcite Plag. Cu-Au
- 12. Porphyry alteration: Typicalassemblages Chlorite-Sericite • Chlorite • Sericite/Illite • Hematite • Martite, Specularite • Carbonate • Epidote • Smectite Modified from Sillitoe, 2010
- 13. Porphyry alteration: Typicalassemblages Chlorite-Sericite • Chlorite • Sericite/Illite • Hematite • Martite, Specularite • Carbonate • Epidote • Smectite Cu-Au Sericite Chem. Sericite Xtal. Chlorite Chem. Classification Photography
- 14. Porphyry alteration: Typicalassemblages Sericite (Phyllic) • Sericite • Quartz Modified from Sillitoe, 2010
- 15. Porphyry alteration: Typicalassemblages Sericite (Phyllic) • Sericite • Quartz Sericite Ser.Chem. Ser.Xtal. ~2200nm Sericite composition 10nm shift ~2210nm ~2200nm Sericite crystallinity ~2200nm ~2200nm High crystallinity Low crystallinity Cu-Mo
- 16. Porphyry alteration: Typicalassemblages Advanced Argillic • Kaolinite • Alunite • Pyrophyllite • Diaspore • Dickite • Jarosite • Topaz • Quartz • Vuggy Silica Modified from Sillitoe, 2010
- 17. Porphyry alteration: Typicalassemblages Advanced Argillic • Kaolinite • Alunite • Pyrophyllite • Diaspore • Dickite • Jarosite • Topaz • Quartz • Vuggy Silica AluniteGypsumKaol.Aspec.Seric. Alunite Pyrophyllite Kaolinite Classification Cu-AuCu-Mo
- 18. Porphyry: Sulfides Bornite Py/CpyMoly Sericite Py/Cpy Calcite Silica Bornite Moly • It is possible to map sulfides in the VNIR-SWIR spectral range • However, unlike typical alteration mineralogy spectra, sulfide signatures are not unique and ambiguity between sulfides can be a problem • Massive sulfide has higher accuracy than finely disseminated sulfides Pyrite Spectral Signature
- 19. Assemblage – Alterationsimilarity across deposits (Cu-Mo) Sericite Sericite (Hi Xtal) Kaolinite Sulfide Sericite + Chlorite Chlorite Montmorillinite Phlogopite Carbonate Photo Class Sericite Ser. Wave Kaolinite Class Sericite Ser. Wave Kaolinite Porphyry A Porphyry B
- 20. Porphyry alteration variablesfrom hyperspectral imaging -Assemblage identification -subtypes Cu-Mo, Cu-Au -Textures (veined, pervasive, porphyritic) -Paragenesis, vein selvages, cross- cutting, overprints -Sharpness of alteration boundaries -Scaling from fine resolution (cm’s) through to borehole scale (m’s) through to entire deposit scales (km’s)
- 21. Core Photography Classification Map AspectralPhlogopite Sericite Kaolinite TexturalMapping: Pervasive v. Veined Low match Mineral match High match
- 22. Textural Mapping: Pervasivev. Veined Photo Class Ser. Wave Kaolinite Alunite Gypsum Sericite Sericite (Hi Xtal) Kaolinite Alunite Gypsum Tourmaline Low match Mineral match High match ~17m
- 23. Texture: Primary Porphyritic Core Photography KaoliniteMontmorillinite Aspectral
- 24. Porphyry alteration variablesfrom hyperspectral imaging Classification Map Sulfide Gypsum Sericite Chlorite + Clay -Assemblage identification -subtypes Cu-Mo, Cu-Au -Textures (veined, pervasive, porphyritic) -Paragenesis, vein selvages, cross- cutting, overprints -Sharpness of alteration boundaries -Scaling from fine resolution (cm’s) through to borehole scale (m’s) through to entire deposit scales (km’s) Cu-Mo(Au)
- 25. Paragenesis: Vein/Assemblage Low match Mineralmatch High match Photo Class Sericite Kaolinite Alunite Gypsum Carbonate Atacam. Cu-Mo
- 26. Paragenesis: Cross-Cutting Relationships Lowmatch Mineral match High match 2212 nmMuscovite2196 nm White mica composition index (~2200 nm position) Increase in Na (Paragonite) Increase in K/Al (Muscovite) 2196 nm 2212 nm Fe substitution (Phengite) 2185 nm 2225 nm Porphyry A Photo Class Phlog. Kaolinite Chlorite Sericite Ser. Wav. Cu-Mo
- 27. Vein Halos Low match Mineralmatch High match Photo Class Sericite Ser. Wav. Kaolinite 2212 nmMuscovite2196 nm White mica composition index (~2200 nm position) Increase in Na (Paragonite) Increase in K/Al (Muscovite) 2196 nm 2212 nm Fe substitution (Phengite) 2185 nm 2225 nm Porphyry A Cu-Mo
- 28. Vein/Fracture Halos Photo Class Sericite Ser. Wav. Gypsum Lowmatch Mineral match High match 2212 nmMuscovite2196 nm White mica composition index (~2200 nm position) Increase in Na (Paragonite) Increase in K/Al (Muscovite) 2196 nm 2212 nm Fe substitution (Phengite) 2185 nm 2225 nm Porphyry A Cu-Mo
- 29. Vein/Fracture Halos PHOTOGRAPHY CLASSMAP WHITE MICA WM CHEM. WM XTAL. Cu-Mo
- 30. Porphyry alteration variablesfrom hyperspectral imaging -Assemblage identification -subtypes Cu-Mo, Cu-Au -Textures (veined, pervasive, porphyritic) -Paragenesis, vein selvages, cross- cutting, overprints -Sharpness of alteration boundaries -Scaling from fine resolution (cm’s) through to borehole scale (m’s) through to entire deposit scales (km’s) Copper canyon Photo Class Asp.Ser. Ser. Wav. Chl. Cu-Au
- 31. Sharpness of AlterationBoundaries Photo Class Gyp.Kaol. Tourm.Ser. Ser. Wav. Mont. Chl. Sericite Sericite (Hi Xtal) Kaolinite Alunite Gypsum Tourmaline Low match Mineral match High match Cu-Mo
- 32. Sharpness of AlterationBoundaries Class Sericite Sericite (Hi Xtal) Kaolinite Alunite Gypsum Tourmaline Low match Mineral match High match Biotite/Phlogopite Cu-Au ~992m
- 33. Sharpness of AlterationBoundaries Photo Class Sericite Sericite (Hi Xtal) Kaolinite Alunite Gypsum Tourmaline Cu-Au ~1148m
- 34. Porphyry alteration variablesfrom hyperspectral imaging -Assemblage identification -subtypes Cu-Mo, Cu-Au -Textures (veined, pervasive, porphyritic) -Paragenesis, vein selvages, cross- cutting, overprints -Sharpness of alteration boundaries -Scaling from fine resolution (cm’s) through to borehole scale (m’s) through to entire deposit scales (km’s)
- 35. Borehole-scale Alteration Domains:Cu-Au Class Chlorite Sericite Kaolinite Alunite Gypsum Tourmaline Low match Mineral match High match Phlogopite Sericite ~992m
- 36. Borehole-scale Alteration Domains:Cu-Mo Class Chlorite Sericite Low match Mineral match High match Phlogopite ~833m
- 37. <<WHITE MICA (PHENGITE), HIGHXTAL WHITE MICA PHLOGOPITE + CHLORITE (FE-RICH) + = HIGHER CU-GRADE Borehole-Scale Alteration Domains ~169m
- 38. Borehole-scale Alteration Domains:Cu-Mo Photo Class Kaol. ChloriteAlunite Ser. Wav. Phlog. Mont. Argillic Lithocap Potassic CoreOverprint Low match Mineral match High match ~561m
- 39. Borehole-scale Alteration Domains-> Deposit Scale Photo Class AluniteMont. Low match Mineral match High match Export to downhole mineral % logs for database and 3D modeling ~561m
- 40. Assemblage ID: MineralPoint Logs Consistent, high resolution mineral point logs reveal basic (and sometimes subtle) mineral assemblages Alunite Atacamite GypsumAsp. (Sericite) Argillic
- 41. Assemblage ID: MineralPoint Logs Consistent, high resolution mineral point logs reveal basic (and sometimes subtle) mineral assemblages Chlorite Mont.Phlog (Sericite)Asp. Potassic
- 42. Deposit-Scale Alteration Domains:Alunite Alteration % point data brought into simple 3D models (e.g. Gocad) • Point data represents % of minerals counted downhole, in specific depth intervals • This model was created with 1m interval data which represents ~200,000 pixels/signatures per meter of core • Color of model spheres relates to purity or ‘goodness’ of fit to verified mineral spectral signatures • Size of model spheres also relates directly to purity of the identified mineral Cu-Mo
- 43. Deposit-Scale Alteration Domains:Aspectral • Aspectral refers to measured signatures that lack spectral absorption features • They are related to either non-included, crystalline quartz OR un-altered feldspars • Spatial mapping of this class is accurate – though identification can be ambiguous • In this porphyry, most of the aspectral class relates to quartz (confirmed from previous traditional logging)
- 44. Deposit-Scale Alteration Domains:Atacamite
- 45. Deposit-Scale Alteration Domains:Carbonate • While the chemistry of carbonates is possible to measure (e.g. dolomite v. calcite, ankerite, siderite, etc.), it is often useful to lump the carbonate classes in order to study gross patterns in alteration • Further delineations such as crystallinity are also possible
- 46.
- 47. Deposit-Scale Alteration Domains:Chrysocolla
- 48.
- 49. Deposit-Scale Alteration Domains:Kaolinite
- 50. Deposit-Scale Alteration Domains:Montmorillinite
- 51. Deposit-Scale Alteration Domains:Phlogopite • Discrimination between phlogopite and biotite is generally possible – though in some cases difficult • In general, the higher the iron content (as measured directly from the spectral signatures) and the less water detected – the more biotitic the rock is
- 52.
- 53. Deposit-Scale Alteration Domains:Sericite Chemistry 2212 nmMuscovite2196 nm White mica composition index (~2200 nm position) Increase in Na (Paragonite) Increase in K/Al (Muscovite) 2196 nm 2212 nm Fe substitution (Phengite) 2185 nm 2225 nm Porphyry A
- 54. Deposit-Scale Alteration Domains:Tourmaline • Distinction between tourmaline varietals is possible – though frequently of lesser importance • Typically, tourmaline is lumped into a single class
- 55. Deposit-Scale Alteration Domains:RQD • RQD data is derived using a laser profiling system with 15 micron vertical resolution • Though very consistent and accurate, automated RQD data should be considered carefully based on age and condition of core • Core that is old and/or been moved frequently may report different RQD values than those derived directly after drilling • On-site deployment of automated core-logging during drilling solves this issue
- 56. Deposit-Scale Alteration: Alunite≈ QS Potassic - Bi Quartz-Sericite (QS) • Alteration ‘cylinders’ derived from traditional core-logging data identified by on-site geologists • Hyperspectral alteration (alunite) correlates to QS code
- 57. Deposit-Scale Alteration: Phlogopite≈ KB Potassic – Bi (KB) Quartz-Sericite (QS) • Hyperspectral alteration (phlogopite) correlates to KB code
- 58. Deposit-Scale Alteration: Montmorillinite≈ KB Potassic – Bi (KB) Quartz-Sericite (QS) • Hyperspectral alteration (montmorillinite) correlates to KB code
- 59. Deposit-Scale Alteration Domains:Alun+Kaol (+Gyp) Alunite+Kaolinite (Gypsum) • We can start to create initial assemblage classifications and model these relationships in 3D
- 60. Deposit-Scale Alteration Domains:Phlog+Chl+Mont Alunite+Kaolinite (Gypsum) Phlogopite+Chlorite Montmorillinite
- 61. Deposit-Scale Alteration Domains:Argillic Alunite • Minerals thought to correlate to particular alteration domains are modeled in 3D space
- 62. Deposit-Scale Alteration Domains:Alunite – Mont. Alunite Montmorillinite • Such modeling shows presence of (late-stage?) montmorillinite overprint at depth
- 63. Deposit-Scale Alteration Domains:+Phlogopite Alunite Montmorillinite Phlogopite • Montmorillinite co-located with Phlogopite (Potassic) domain
- 64. Cu-Au Porphyry: Borehole-scaleAlteration Class Epidote ChloriteActin. SericitePhlog. Kaol.Chl+Clay Chl Wav. Ser. Wav. Mont. ~1148m
- 65. Cu-Au Porphyry: Borehole-scaleAlteration Class Epidote ChloriteActinolite SericitePhlog. Kaolinite Mont. ~995m
- 66. Deposit-Scale Alteration Domains Montmorillinite Phlogopite %Cu •Similar modeling in a Cu-Au porphyry highlights the more expected alteration domains as well as expected correlation of Cu with the Potassic (represented by phlogopite)
- 67. “From Microns toKilometers” Spectral Signatures (“microns”) Core-scale “meters” Core-hole scale “kilometers”