Ore variability can be understood as the natural variation in the physical, chemical, and geometallurgical characteristics of a particular mineral deposit. Mine scheduling, in turn, can be described as an effort to define the optimal sequence of mining operations that will result in maximum profits. In the case under discussion, the mineral deposit in question contains multiple elements that have to be extracted at once. It is crucial to understand these concepts, since any spatial uncertainty inevitably determines the economic feasibility of the project.
As a matter of fact, the variation of ore has tremendous implications for mine scheduling due to the uncertainties that occur. Namely, if the mine scheduling model relies solely on an average geological situation, the actual spatial continuity of materials cannot be properly considered. This leads to a failure in the operation of processing lines and creates numerous deviations. The problem further intensifies the farther one proceeds along the process, resulting in a lower net present value of the project as a whole.
It becomes exceedingly difficult to cope with all of these variations in a multiple element deposit. The existence of several economic elements implies that the mining process should take account of their grades, recoverability, and metallurgy altogether. Since most of the processes are not linear, any changes in grades and contaminants’ levels can significantly change recoveries of other elements. Traditional optimization methods that are based on a consideration of single elements cannot be applied to such cases.
Modern stochastic approaches have been developed to solve the problems arising from these peculiarities. Conventional scheduling approaches optimize each component separately, disregarding the interactions between mining stages. Modern computing power allows including all factors that affect processes, such as uncertainty of supply, in a unified model with synergistic effects taken into consideration.
At present, simultaneous stochastic optimization remains one of the main instruments employed to cope with ore variability in such complicated settings (Goodfellow & Dimitrakopoulos, 2017). This powerful method relies on geostatistical simulations and enables the creation of several possible realizations of the multi-element deposit, thus accounting for spatial uncertainty and connectivity (de Carvalho & Dimitrakopoulos, 2019). The use of the said stochastic models allows one to assess blending strategies, processing streams, and destinations simultaneously through a single uncertainty-based optimization model (Kumar & Dimitrakopoulos, 2019).
Proper handling of ore variability within multi-element deposits plays a key role in maximizing resource recovery rates and earning money. Using advanced techniques, such as simultaneous stochastic optimization, helps mining facilities eliminate any technical risks and guarantee a high probability of satisfying all kinds of production requirements. Utilizing geostatistical simulations and scheduling approaches will help mine operators to convert a serious operational issue into an asset.
References
de Carvalho, J. P., & Dimitrakopoulos, R. (2019). Effects of high-order simulations on the simultaneous stochastic optimization of mining complexes. Minerals, 9(4), 210. https://doi.org/10.3390/min9040210
Goodfellow, R., & Dimitrakopoulos, R. (2017). Simultaneous stochastic optimization of mining complexes and mineral value chains. Mathematical Geosciences, 49, 341–360. https://doi.org/10.1007/s11004-017-9680-3
Kumar, A., & Dimitrakopoulos, R. (2019). Application of simultaneous stochastic optimization with geometallurgical decisions at a copper–gold mining complex. Mining Technology, 128(2), 88–105. https://doi.org/10.1080/25726668.2019.1575053
