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Whole rock geochemical analysis of drill core is crucial for rock classification and understanding the evolution of a geological province. This becomes even more important when access to fresh rock samples is hindered by considerable overburden, such as in the case of the basement to the Eucla Basin sediments in Australia. A partial least squares (PLS) regression method was trialled to model geochemical indices, commonly applied for classification of igneous rocks, from hyperspectral visible-near infrared (VNIR; 350 to 1200 nm), shortwave infrared (SWIR; 1200 to 2500 nm) and thermal infrared (TIR; 6000 to 14,500 nm) reflectance spectra of three drill cores intersecting the basement of the Eucla Basin. Modelling of the Mg# (Mg/Mg + Fe) achieved a high correlation between the calculated and predicted values (i.e. R2 > 0.9) at an RMSE of about 10 %. The 2200 to 2400 nm wavelength region of the SWIR was key in modelling the Mg#, with amphibole and chlorite-related absorption features overlapping with the most important input bands in the PLS model. Modelling of the silicon, calcium, iron, magnesium index (SCFM; SiO 2 /(SiO 2 + CaO + FeO + MgO)) required the TIR wavelength range, where diagnostic spectral signatures of silicates are located. PLS-based modelling of the SCFM achieved even a high correlation (i.e. R2 > 0.8) when the model was developed for one drill core but applied to another drill core that intersects the same lithologies. The third geochemical index trialled was the aluminium saturation index (ASI; Al 2 O 3 /(Na 2 O + K 2 O + CaO), producing high correlation between calculated and predicted ASI when using either, the VNIR-SWIR and the TIR wavelength ranges as input. Our study demonstrates how PLS regression can utilise hyperspectral data to determine geochemical indices, without the cost of full geochemical analysis of every sample in a wide array of rock types. The higher spatial resolution of the modelled geochemistry and the extrapolation of the modelling results to intervals that haven't been sampled for geochemistry supports stratigraphic correlation between drill cores. Furthermore, the combined analysis of geochemical and hyperspectrally-derived mineralogy helps mapping the intensity of weathering of basement as well as mineralogical and physicochemical gradients potentially related to hydrothermal systems. • PLS-based modelling of geochemical indices from hyperspectral reflectance spectra • Correlations between calculated and modelled Mg#, SCFM and ASI are significant. • RMSE of modelled geochemical index values about 10 % on average • Comparison of input bands with reflectance spectra reveals causative relationships. • Modelling results can be used for stratigraphic correlations between drill cores. [ABSTRACT FROM AUTHOR]

Patterns in white mica (muscovite, paragonite, and phengite) Al-Si chemistry (Tschermak substitution) were examined for the Archean Kanowna Belle and Sunrise Dam gold deposits in the Eastern Goldfields of Western Australia, using short-wave infrared (SWIR) spectrometry of drill core samples. Both of these deposits represent greenschist-facies, structurally controlled, >10-Moz gold systems with broadly similar host rocks and superimposed metasomatic hydrothermal alteration halos that extend for up to 3 km from the economic zone. However, zonation toward gold mineralization at Kanowna Belle is associated with increasingly longer wavelength white mica, whereas Sunrise Dam comprises the opposite pattern. The study also found that gold mineralization at Kanowna Belle is associated with quartz, chalcopyrite, and pyrite with negative δ34S values and a relative lack of carbonate, chlorite, and paragonite (Na-rich white mica), whereas gold mineralization at Sunrise Dam is associated with paragonite as well as carbonate, Fe-rich chlorite and pyrite with positive Tschermak34S values and a relative lack of quartz and chalcopyrite. Thermodynamic numerical modeling revealed that these contrasting patterns in white mica Tschermakite substitution (and associated alteration mineralogy) can be explained by two different types of ore fluids, namely (1) oxidized, alkaline, and silica-rich at Kanowna Belle; and (2) reduced, acid, Fe-rich and silica-poor at Sunrise Dam, though the sources of these contrasting fluids are less clear. Importantly for explorers, spectral measurement (using drill core, field, airborne, and potentially satellite hyperspectral SWIR data) of gradients (especially within a given geologic unit) in white mica absorption wavelength (Tschermak substitution) represents a potential vectoring tool for the discovery of new Archean hydrothermal gold systems. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging is a powerful tool for mineral mapping and increasingly used in poorly-accessible areas. It only requires a limited amount of validation sample points, but can fail to discriminate spectrally-similar features. In this manuscript, we show that we improve the identification of interesting targets by including geomorphological data in the spectral mapping scheme. We jointly use geomorphic and spectral features to locate gossanous ironstone ridges as an indicator for possible Pb-Zn-Ag-mineralization and provide an application around Mount Isa and George Fisher/Hilton mine, Queensland, Australia. We combine hyperspectral HyMap data using mixture tuned matched filtering with topographical indices, such as maximum curvature and the topographical position index. As it is often the case with structurally-controlled mineralization, the amount of training sites is limited, and supervised classification methods cannot be implemented. Therefore, we implement expert knowledge in a decision tree to take advantage of the relationship between mineralization, alteration and structure. Optimized rock sampling and spectral measurements provided data for validation. We are able to map sets of gossanous ridges with a minimum of validation points, not only within the Mount Isa mining area itself, but also outside the commonly-accepted host rocks. The ridges are parallel to north-south trending geomorphological features and probably associated with the Paroo fault zone. Similarities between the ridges were confirmed by field observations, spectral measurements and a qualitative rock sample analysis. We identified new mineralized ridges that we could subsequently attribute to a poorly-known and sub-economic deposit known as the Mount Novit Pb-Zn-deposit. [ABSTRACT FROM AUTHOR]