A Cut-Off of Liberated and Selected Ore Minerals Optimisation Based on the Geometallurgy Concept

An improvement to cut-off grade optimisation theory based on geometallurgy has been completed. The improvement fundamentally consisted of taking into account mineralogical and textural characteristics instead of grades. These characteristics are related to the spatial variability of mineral abundance, association, particle size and liberation properties. Additionally, the improve- ment considered the spatial variability of mineral processing liberation and selectivity properties associated with mineralogy and texture. The enhanced optimisation enables estimation of the economic value of mining operations based on an optimum cut-off policy attributed to liberated and selected ore minerals.The enhanced optimisation was developed as an essential component of a joint cut-and-fill mining and mineral processing methodology based on mixed integer mathematical programming. The formulation considers static and dynamic modifying factors that vary over the projected life of mining. The objective function of the mathematical formulation consists of maximising the realistic expected economic value of concentrates or products of liberated and selected ore minerals, whilst minimises liberated and selected gangue minerals. The optimal solution is obtained when the objective function is subject to geological, mining, processing, marketing, smelting, refining, environmental and financial constraints. The methodology accesses geometallurgical multivariate resource models, which integrate the spatial variability of mineralogical and textural characteristics and mineral processing liberation and selectivity properties.The geometallurgical process concurrently optimises stope geometries, ore reserves, mining sequences, and mining and mineral processing production based on the enhanced cut-off of liberated and selected ore minerals. In addition, the process considers additive and non-additive transfer functions associated to mutually exclusive geometallurgical spatial domains. The transfer functions also take into consideration the blending of mineralogical and textural characteristics with mineral processing liberation and selectivity properties.This contribution presents an example of cut-off grade optimisation via mineralogical and textural characteristic, and liberation and selectivity processing parameter optimisation for a spatially variable orebody.