Best practices for characterising mine wastes towards a mineral recovery assessment: a concept

In response to the growing strategic and economic interest in sourcing minerals from mining residues, the industry is increasingly developing practices to optimise mineral recovery. Some of the challenges lies in characterising the spatial and volumetric distribution of the waste components and upscaling geochemical and mineralogical data from microscopic to deposit-scale observations. This work introduces a conceptual framework for the geochemical and mineralogical characterisation of mine wastes that can support the successful recovery of residual and secondary ores. The basis of this framework is a combination of laboratory analyses, in-the-field surveys and remote sensing techniques integrated through machine learning and artificial intelligence techniques. The output of this framework is a toolbox that provides a holistic overview of the components inside a waste deposit and their distribution that generates information about the presence of recoverable ore.