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HYPERSPECTRAL CORE
IMAGING FOR
CHARACTERIZATION OF CU-
AU PORPHYRY
7 MARCH 2016
Brigette A. Martini, PhD & Ronell Carey, PhD
Corescan
Jeff Witter, PhD
Mira Geosciences
Presented at PDAC 2016
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
Porphyry alteration variables from 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)
Diagnostic spectral absorption features: 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
Mobile, Automated,
Hyperspectral Core Logging
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
Porphyry alteration: Typical assemblages
Sodic-Calcic
• Albite/oligoclase
• Actinolite
• Magnetite
• Diopside
• Epidote
• Garnet
Modified from Sillitoe, 2010
Porphyry alteration: Typical assemblages
Sodic-Calcic
• Albite/oligoclase
• Actinolite
• Magnetite
• Diopside
• Epidote
• Garnet
Magnetite
Cu-Au
Low
Mineral match
High
Magnetite
Porphyry alteration: Typical assemblages
Potassic
• Biotite
• K-spar
• Actinolite
• Epidote
• Sericite
• Albite
• Carbonate
• Tourmaline
• Magnetite
Modified from Sillitoe, 2010
Porphyry alteration: Typical assemblages
Potassic
• Biotite
• K-spar
• Actinolite
• Epidote
• Sericite
• Albite
• Carbonate
• Tourmaline
• Magnetite
~2325nm
~2250nm
~1380nm
~2390nm
Biotite
Biotite
Actinolite
Mont.
Sericite
K-spar
Cu-Au
Porphyry alteration: Typical assemblages
Propylitic
• Chlorite
• Epidote
• Albite
• Carbonate
Modified from Sillitoe, 2010
Porphyry alteration: Typical assemblages
Propylitic
• Chlorite
• Epidote
• Albite
• Carbonate
Chlorite
ChloriteChem
Epidote
Calcite
Plag.
Cu-Au
Porphyry alteration: Typical assemblages
Chlorite-Sericite
• Chlorite
• Sericite/Illite
• Hematite
• Martite, Specularite
• Carbonate
• Epidote
• Smectite
Modified from Sillitoe, 2010
Porphyry alteration: Typical assemblages
Chlorite-Sericite
• Chlorite
• Sericite/Illite
• Hematite
• Martite, Specularite
• Carbonate
• Epidote
• Smectite
Cu-Au
Sericite Chem.
Sericite Xtal.
Chlorite Chem.
Classification
Photography
Porphyry alteration: Typical assemblages
Sericite (Phyllic)
• Sericite
• Quartz
Modified from Sillitoe, 2010
Porphyry alteration: Typical assemblages
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
Porphyry alteration: Typical assemblages
Advanced Argillic
• Kaolinite
• Alunite
• Pyrophyllite
• Diaspore
• Dickite
• Jarosite
• Topaz
• Quartz
• Vuggy Silica
Modified from Sillitoe, 2010
Porphyry alteration: Typical assemblages
Advanced Argillic
• Kaolinite
• Alunite
• Pyrophyllite
• Diaspore
• Dickite
• Jarosite
• Topaz
• Quartz
• Vuggy Silica
AluniteGypsumKaol.Aspec.Seric.
Alunite
Pyrophyllite
Kaolinite
Classification
Cu-AuCu-Mo
Porphyry: Sulfides
Bornite Py/Cpy Moly
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
Assemblage – Alteration similarity 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
Porphyry alteration variables from 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)
Core
Photography
Classification
Map
AspectralPhlogopite Sericite Kaolinite
Textural Mapping: Pervasive v. Veined
Low match
Mineral match
High match
Textural Mapping: Pervasive v. Veined
Photo Class Ser. Wave Kaolinite Alunite Gypsum Sericite
Sericite (Hi Xtal)
Kaolinite
Alunite
Gypsum
Tourmaline
Low match
Mineral match
High match
~17m
Texture: Primary Porphyritic
Core
Photography
Kaolinite Montmorillinite Aspectral
Porphyry alteration variables from 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)
Paragenesis: Vein/Assemblage
Low match
Mineral match
High match
Photo Class Sericite Kaolinite Alunite Gypsum Carbonate Atacam.
Cu-Mo
Paragenesis: Cross-Cutting Relationships
Low match
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
Vein Halos
Low match
Mineral match
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
Vein/Fracture Halos
Photo
Class
Sericite
Ser. Wav.
Gypsum
Low match
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
Vein/Fracture Halos
PHOTOGRAPHY CLASS MAP WHITE MICA WM CHEM. WM XTAL.
Cu-Mo
Porphyry alteration variables from 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
Sharpness of Alteration Boundaries
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
Sharpness of Alteration Boundaries
Class
Sericite
Sericite (Hi Xtal)
Kaolinite
Alunite
Gypsum
Tourmaline
Low match
Mineral match
High match
Biotite/Phlogopite
Cu-Au
~992m
Sharpness of Alteration Boundaries
Photo Class
Sericite
Sericite (Hi Xtal)
Kaolinite
Alunite
Gypsum
Tourmaline
Cu-Au
~1148m
Porphyry alteration variables from 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)
Borehole-scale Alteration Domains: Cu-Au
Class Chlorite Sericite
Kaolinite
Alunite
Gypsum
Tourmaline
Low
match
Mineral match
High
match
Phlogopite
Sericite
~992m
Borehole-scale Alteration Domains: Cu-Mo
Class Chlorite Sericite
Low
match
Mineral match
High
match
Phlogopite
~833m
<<WHITE MICA (PHENGITE),
HIGH XTAL WHITE MICA
PHLOGOPITE
+ CHLORITE (FE-RICH)
+ =
HIGHER CU-GRADE
Borehole-Scale Alteration Domains
~169m
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
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
Assemblage ID: Mineral Point Logs
Consistent, high resolution mineral point logs reveal basic (and sometimes subtle) mineral assemblages
Alunite Atacamite GypsumAsp. (Sericite)
Argillic
Assemblage ID: Mineral Point Logs
Consistent, high resolution mineral point logs reveal basic (and sometimes subtle) mineral assemblages
Chlorite Mont.Phlog (Sericite)Asp.
Potassic
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
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)
Deposit-Scale Alteration Domains: Atacamite
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
Deposit-Scale Alteration Domains: Chlorite
Deposit-Scale Alteration Domains: Chrysocolla
Deposit-Scale Alteration Domains: Gypsum
Deposit-Scale Alteration Domains: Kaolinite
Deposit-Scale Alteration Domains: Montmorillinite
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
Deposit-Scale Alteration Domains: Sericite
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
Deposit-Scale Alteration Domains: Tourmaline
• Distinction between
tourmaline varietals is
possible – though
frequently of lesser
importance
• Typically, tourmaline is
lumped into a single class
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
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
Deposit-Scale Alteration: Phlogopite ≈ KB
Potassic – Bi (KB) Quartz-Sericite (QS)
• Hyperspectral alteration
(phlogopite) correlates to
KB code
Deposit-Scale Alteration: Montmorillinite ≈ KB
Potassic – Bi (KB) Quartz-Sericite (QS)
• Hyperspectral alteration
(montmorillinite) correlates
to KB code
Deposit-Scale Alteration Domains: Alun+Kaol (+Gyp)
Alunite+Kaolinite
(Gypsum)
• We can start to create initial
assemblage classifications and
model these relationships in 3D
Deposit-Scale Alteration Domains: Phlog+Chl+Mont
Alunite+Kaolinite
(Gypsum)
Phlogopite+Chlorite
Montmorillinite
Deposit-Scale Alteration Domains: Argillic
Alunite
• Minerals thought to correlate to
particular alteration domains
are modeled in 3D space
Deposit-Scale Alteration Domains: Alunite – Mont.
Alunite
Montmorillinite
• Such modeling shows presence
of (late-stage?) montmorillinite
overprint at depth
Deposit-Scale Alteration Domains: +Phlogopite
Alunite
Montmorillinite
Phlogopite
• Montmorillinite co-located with
Phlogopite (Potassic) domain
Cu-Au Porphyry: Borehole-scale Alteration
Class Epidote ChloriteActin. SericitePhlog. Kaol.Chl+Clay Chl Wav. Ser. Wav. Mont.
~1148m
Cu-Au Porphyry: Borehole-scale Alteration
Class Epidote ChloriteActinolite SericitePhlog. Kaolinite Mont.
~995m
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)
“From Microns to Kilometers”
Spectral
Signatures
(“microns”)
Core-scale
“meters”
Core-hole
scale
“kilometers”

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PDAC 2016 presentation by Martini, Carey, & Witter

  • 1. HYPERSPECTRAL CORE IMAGING FOR CHARACTERIZATION OF 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 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
  • 3. Porphyry alteration variables from 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 absorption features: 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 Core Logging 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: Typical assemblages Sodic-Calcic • Albite/oligoclase • Actinolite • Magnetite • Diopside • Epidote • Garnet Modified from Sillitoe, 2010
  • 7. Porphyry alteration: Typical assemblages Sodic-Calcic • Albite/oligoclase • Actinolite • Magnetite • Diopside • Epidote • Garnet Magnetite Cu-Au Low Mineral match High Magnetite
  • 8. Porphyry alteration: Typical assemblages Potassic • Biotite • K-spar • Actinolite • Epidote • Sericite • Albite • Carbonate • Tourmaline • Magnetite Modified from Sillitoe, 2010
  • 9. Porphyry alteration: Typical assemblages 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: Typical assemblages Propylitic • Chlorite • Epidote • Albite • Carbonate Modified from Sillitoe, 2010
  • 11. Porphyry alteration: Typical assemblages Propylitic • Chlorite • Epidote • Albite • Carbonate Chlorite ChloriteChem Epidote Calcite Plag. Cu-Au
  • 12. Porphyry alteration: Typical assemblages Chlorite-Sericite • Chlorite • Sericite/Illite • Hematite • Martite, Specularite • Carbonate • Epidote • Smectite Modified from Sillitoe, 2010
  • 13. Porphyry alteration: Typical assemblages Chlorite-Sericite • Chlorite • Sericite/Illite • Hematite • Martite, Specularite • Carbonate • Epidote • Smectite Cu-Au Sericite Chem. Sericite Xtal. Chlorite Chem. Classification Photography
  • 14. Porphyry alteration: Typical assemblages Sericite (Phyllic) • Sericite • Quartz Modified from Sillitoe, 2010
  • 15. Porphyry alteration: Typical assemblages 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: Typical assemblages Advanced Argillic • Kaolinite • Alunite • Pyrophyllite • Diaspore • Dickite • Jarosite • Topaz • Quartz • Vuggy Silica Modified from Sillitoe, 2010
  • 17. Porphyry alteration: Typical assemblages 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/Cpy Moly 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 – Alteration similarity 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 variables from 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 Textural Mapping: Pervasive v. Veined Low match Mineral match High match
  • 22. Textural Mapping: Pervasive v. Veined Photo Class Ser. Wave Kaolinite Alunite Gypsum Sericite Sericite (Hi Xtal) Kaolinite Alunite Gypsum Tourmaline Low match Mineral match High match ~17m
  • 24. Porphyry alteration variables from 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 Mineral match High match Photo Class Sericite Kaolinite Alunite Gypsum Carbonate Atacam. Cu-Mo
  • 26. Paragenesis: Cross-Cutting Relationships Low match 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 Mineral match 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 Low match 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 CLASS MAP WHITE MICA WM CHEM. WM XTAL. Cu-Mo
  • 30. Porphyry alteration variables from 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 Alteration Boundaries 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 Alteration Boundaries Class Sericite Sericite (Hi Xtal) Kaolinite Alunite Gypsum Tourmaline Low match Mineral match High match Biotite/Phlogopite Cu-Au ~992m
  • 33. Sharpness of Alteration Boundaries Photo Class Sericite Sericite (Hi Xtal) Kaolinite Alunite Gypsum Tourmaline Cu-Au ~1148m
  • 34. Porphyry alteration variables from 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), HIGH XTAL 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: Mineral Point Logs Consistent, high resolution mineral point logs reveal basic (and sometimes subtle) mineral assemblages Alunite Atacamite GypsumAsp. (Sericite) Argillic
  • 41. Assemblage ID: Mineral Point 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)
  • 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
  • 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
  • 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-scale Alteration Class Epidote ChloriteActin. SericitePhlog. Kaol.Chl+Clay Chl Wav. Ser. Wav. Mont. ~1148m
  • 65. Cu-Au Porphyry: Borehole-scale Alteration 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 to Kilometers” Spectral Signatures (“microns”) Core-scale “meters” Core-hole scale “kilometers”