Geomet: Modelling Metallurgical Parameters from Exploration and Resource Data

A growing problem facing geoscientists, metallurgists and process engineers is the lack of knowledge transfer between the exploration and production teams. This siloing is generally unintentional, as a typical project may change ownership several times over several decades before it reaches the feasibility and operation stages. Many exploration projects generate vast amounts of high-quality, quantitative data with great spatial resolution, but unfortunately these data are often ignored in subsequent deposit modelling. Instead, deposit models tend to rely on subjective, non-standardized, qualitative classification of geological materials (e.g. rock type, mineral abundance) and processes (e.g. alteration style and intensity), obtained through visual logging of drill core. When projects advance to feasibility studies, the required quantitative data are obtained through expensive metallurgical test work and detailed quantitative mineralogical analysis, such as QEMScan or qXRD. These detailed tests are generally only performed on a small number of large composite samples and the results are extrapolated throughout the deposit, inherently underrepresenting their true variability. Geochemical data obtained during all stages of the project provide comprehensive data coverage at much greater detail and spatial resolution, which allows for the estimation of key metallurgical performance parameters that are required for accurate deposit modelling and domaining.