Grandite-based resource characterization of the skarn-hosted Cu-Zn-Mo deposit of Antamina, Peru

Field and drill core hyperspectral sensing technologies are cost-effective tools for identifying footprints of hydrothermal mineral systems, vectoring towards potential ore bodies and differentiating domains in ore deposits. Hyperspectral visible-near, shortwave and thermal infrared data were collected from drill core and chip samples from the Cu-Zn-Mo deposit of Antamina, Peru, to map the relative abundance and chemical composition of major gangue minerals, such as garnet and quartz. This study focuses on grandite-series garnets (i.e. grossular to andradite), which show distinct variations with regard to their relative abundance and chemical composition across the Antamina deposit. Reflectance spectra were calibrated with quantitative mineralogy derived from scanning electron microscopy and X-ray diffraction-derived mineralogy. This allowed the modal abundances of garnet and quartz to be modelled using a partial least squares approach, achieving regression coefficients of up to 0.887 and 0.891, respectively. The accuracy of the modelled modal mineral abundance depended on the method of external calibration, and the mineral assemblage associated with the mineral of interest. Comparing the hyperspectral data with major sulfide mineralogy, whole-rock geochemistry, electron probe microanalysis and Fourier-transform infrared microscopy allowed the identification of five ore clusters at Antamina, including high Cu ± Zn-Mo; Zn + Cu ± Mo and Zn ± Cu in the exoskarn and Mo ± Cu-Zn and high Mo ± Cu-Zn in the endoskarn. The garnet species comprise mainly grossular ± andradite in the endoskarn and andradite in the exoskarn. Different garnet compositions are associated with different sulfide mineral assemblages, making Antamina an ideal candidate for evaluating hyperspectral sensing for rapid and reliable mineral characterisation of skarn deposits. Vector minerals typical of skarn deposits (e.g. garnet, vesuvianite) were determined using this approach, indicating its potential for effectively characterising skarn deposits worldwide.