MINERALS Applications in Exploration: Copper

Corescan® Logging in Copper Porphyry

High precision, accurate hyperspectral core imaging data is used to identify and map suites of porphyry mineralogy, both primary and secondary alteration.

Mineral maps: n reveal paragentic relationships and other textures (eg. pervasive vs. veined) n act as proxy for hydrothermal fluid temperature and chemistry characterisation n reveal specific indicator minerals and/or assemblages associated with Cu-Mo (Au,Ag) mineralisation

Scanning measurements are performed with the Corescan HCI-3 system which operates from 450-2500nm at a spectral resolution of ~4nm. The 500 µm hyperspectral spatial resolution results in ~150,000 pixels per meter of imaged core. Spatially co-registered photography (50 µm) and laser profiles (20 µm) complete the suite of collected imagery.

Corescan system components are housed within a ruggedized, mobile shipping sea container for remote, on-site or centralized, bureau scanning.

0.05mm RGB Digital Imagery

Mineral Classification Map

Sericite Chemistry Map Copper Basin, AZ - Porphyry Exploration 100 100

Corescan data from the Copper Basin Cu-Mo90 porphyry prospect in central90 Arizona is used to identify eleven (11) separate mineral species throughout seven (7) separate boreholes. An additional eight (8) sub-species (changing mica chemistry and 80 80 crystallinity) are also identified. Located in the Laramide-aged porphyry district of Arizona (near both Jerome and Bagdad), this system has 1km of vertical extent and 1.5km702 of exposed alteration and7 0mineralisation. Proterozoic granites cut by younger ~ ~ SER_2195 SER_2195 Laramide quartz-diorite stocks and dikes which60 are in-turn cut by younger 6stockworks0 and breccias are altered to typical porphySER_2201 ry SER_2201 SER_2212 SER_2212 assemblages: propylitic, phyllic, argillic and potassic.50 50 FE_CHL FE_CHL MG_CHL MG_CHL 40 40 Reflectance % Of particular importance in porphyry exploration is the logging and identificationReflectance % of mica species including white micas PHLOG_HI_FE PHLOG_HI_FE PHLOG_LO_FE PHLOG_LO_FE (paragonite, muscovite, phengite), biotite/phlogopite30 and chlorite (chamosite,30 clinochlore). Mica chemistry and degree of

crystallinity is measured and logged by hyperspectral20 Corescan imaging and20 aids in ore-vectoring. White Mica Chemistry 2200nm position Relative mineral abundance Sulfide Silica-Clay Mix ~ Carbonate White Mica (Hi Xtal) 10 10 Sericite-Chlorite Mix White Mica (Lo Xtal) 2185nm 2196nm 2212nm 2225nm Low abundance High abundance Chlorite Kaolinite Increase in Na Increase in K/Al Fe substitution Jarosite Montmorillinite (Paragonite)0 (Muscovite) (Phengite) 0 Phlogopite Aspectral 448 848 1244848 1648848 20142848 24146848nm 2048 2448 nm Gypsum

100 60 60 30 30

90

PHLOGOPITE PHLOGOPITE 80 50 50 25 25

70 SER_2195 60 SER_2201 SER_2212 40 40 20 20 50 FE_CHL MG_CHL 40 Reflectance % PHLOG_HI_FE 2212 PHLOG_LO_FE 30 2212 30 15 15 30 BIOTITE BIOTITE 17 nm 17 nm 20 Reflectance % total shift Reflectance % Reflectance % total shift Reflectance %

Offset Reflectance Offset Reflectance 20 20 10 10 10 2201 2201 0 448 848 1248 1648 2048 2448 nm

10 10 5 5 60 30 2195 2195 Left: Spectral signatures from typical mica species extracted from single PHLOGOPITE pixels Middle: Close-up of absorption50 feature in white mica25 due to Al-OH; 0 0 0 0 longward shift due to decreasing Al Right: Spectral signatures2000 of22 0both0 2400 nm 2000 2100 21242000 2180 2220400 2nm260 2300 2100 12002140 14020180 12620200 22168000 nm2300 1200 1400 1600 1800 nm phlogopite and biotite showing40 increasing iron 20

30 15 2212 BIOTITE 17 nm Reflectance % total shift Reflectance %

Offset Reflectance 20 10 2201

10 5 White Mica Chemistry 2200nm position Relative mineral abundance 2195 Sulfide Silica-Clay Mix ~ Carbonate White Mica (Hi Xtal)

0 0 Sericite-Chlorite Mix White Mica (Lo Xtal) 2185nm 2196nm 2212nm 2225nm Low abundance High abundance 2000 2200 2400 nm 2100 2140 2180 2220 2260 2300 1200 1400 1600 1800 nm Chlorite Kaolinite Increase in Na Increase in K/Al Fe substitution Jarosite Montmorillinite (Paragonite) (Muscovite) (Phengite) Phlogopite Aspectral Gypsum

White Mica Chemistry 2200nm position Relative mineral abundance Sulfide Silica-Clay Mix ~ Carbonate White Mica (Hi Xtal) 2185nm 2196nm 2212nm 2225nm e Sericite-Chlorite Mix White Mica (Lo Xtal) Low abundance High abundance e

y Chlorite Kaolinite Increase in Na Increase in K/Al Fe substitution

Jarosite e Montmorillinite (Paragonite) (Muscovite) (Phengite) Phlogopite Aspectral Gypsum bundan c y (ppm) bundan c y (50um) bundan c ss a e A ica Chemist r ica A White Mica Chemistry 2200nm position Relative mineral abundance

ap h Sulfide Silica-Clay Mix ~ r e A

Carbonate White Mica (Hi Xtal) i t e M e M o g Sericite-Chlorite Mix White Mica (Lo Xtal) 2185nm 2196nm 2212nm 2225nm Low abundance High abundance hi t hi t

Chlorite Kaolinite opper A ho t hlogopi t Increase in Na Increase in K/Al Fe substitution W W Mineral Classification Map Chlo r C P Jarosite Montmorillinite P (Paragonite) (Muscovite) (Phengite) Phlogopite Aspectral Gypsum Spectral scanning of approximately 70 m of cut core maps the spatial distribution of typical porphyry alteration and Data courtesy of : reveals potential assemblages related to copper mineralisation. In combination with lithological control, the assemblage defined by Chlorite+Phlogopite+Fe-rich, High-Crystallinity White Mica (Phengite) appears to correlate with increased copper grade. Such relationships help to define ore zones and direct future drilling. Mineral Classification Map with type-porphyry assemblage

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