Vision for a Risk Adverse Integrated Geometallurgy Framework

"Best practice in the economic evaluation of mining projects and operations is based on the integration of geological, mining, metallurgical, environmental, marketing, economic and corporate information and strategies. Fundamentally, the economic evaluation takes into account mining, blending, stockpiling, processing, smelting, refining and marketing ore resources with grades estimated by geostatistical methodologies.Nevertheless, a realistic economic evaluation consists of a concurrent and integrated optimization process that maximizes the concentrates or products of liberated and selected ore minerals from mineral deposits. The optimum solution is obtained through a trade-off among mining, blending, stockpiling and processing ore reserves with distinct mineralogy and texture characteristics. The concurrent optimization determines both the practical mining sequence of ore reserves and the dynamic and robust mineral processing flowsheet design over the expected life of mining projects and operations.A combined risk-adverse and concurrent optimization process takes into account the spatial uncertainty of the mineralogy and texture characteristics of ore reserves. Additionally, a variety of mineral processing linear, non-linear, additive and non-additive parameters modeled spatially. The spatial uncertainty of these ore reserves characteristics and parameters has a direct impact in the expected mining sequence, mineral processing flowsheet design, concentrates or products quantity and quality, and economic value of mining projects and operations.Geometallurgical domain constrained stochastic geostatistical methodologies and multivariate mathematical models are applied for spatial uncertainty modeling of ore reserves characteristics and parameters. These mathematical models correlate the mineral processing liberation and selectivity responses of the mineralogy and textures within each geometallurgical domain. These models, in turn, are defined based on results of mineral processing and environmental testwork of unbiased and representative samples chosen for their variability. These samples are selected within mutually exclusive spatial geometallurgical uncertainty domains with similar mineralogical and textural characteristics in mineral deposits.Geometallurgical domains are defined by applying and combining multivariate statistical analysis and implicit modeling methodologies. These involve determining and constraining mineral processing liberation and selectivity properties explicitly contained in the extensive and integrated exploration drillhole database."