Geometallurgical characterization is increasingly used in the mining industry to model ore types, predict process performance and identify potential recovery issues ahead of time. However, most geometallurgical assessments are based on bench- or laboratory-scale analyses of relatively sparse samples, leaving most of the orebody characteristics known only by inference until the rocks are actually mined. In this pilot study, we test drone- and tripod-based hyperspectral imaging for mapping mineralogy across mine highwalls, dumps and leach pads. The results show that hyperspectral imaging can successfully map the types and distribution patterns of key minerals (especially carbonates, sulfates, clays, other phyllosilicates) and other important features (such as lixiviant ponding on leach pads), bringing geometallurgy into the field to provide crucial inputs to process decisions.
Mining, Metallurgy & Exploration (2021) 38:799–818, https://doi.org/10.1007/s42461-021-00404-z