The role of mineralogy in predictive geometallurgy
DOI:
https://doi.org/10.17159/Abstract
Since geometallurgy emerged as a discipline focused on managing ore variability and reducing risk across the mining value chain, mineralogy has played a central role. Here, mineralogy is expressed through the mineral composition triad and mineral texture, the former, which articulates the relationship between mineral and elemental grades. Inspection of the geometallurgy literature shows that predictive geometallurgical modelling can be divided into the traditional approach, the proxies and the mineralogical approach, although an emerging fourth hybrid approach is also recognised. To evaluate these approaches, we pose the theory statement that mineralogy is the ‘blueprint’ encapsulating all the primary properties of the rock, including the signatures of the ore-forming and any subsequent alteration processes. Should predictive geometallurgical modelling fail to demonstrate the relationship between the mineralogy and the response variable, an assessment of the sampling and measurement of both primary and response variables is required. This calls for ensuring greater articulation of geometallurgical measurement confidence within the industry, but also highlights that, despite years of research in mineral processing and metallurgy, there is still more research to be done. Data-driven modelling and machine learning offer significant opportunities for predictive geometallurgy, especially where non-additive relationships occur. However, for industry adoption, these models must remain explainable and interpretable, with mechanisms that practitioners can understand and trust.
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Copyright (c) 2026 Megan Becker
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