No abstract

The importance of mine planning is often underestimated. Nonetheless, it is essential in achieving high performance by identifying the potential value of mineral resources and providing an optimal, practical, and realistic strategy for extraction, which considers the greatest quantity of options, materials, and scenarios. Conventional mine planning is based on a mostly deterministic approach, ignoring part of the uncertainty presented in the input data, such as the mineralogical composition of the feed. This work develops a methodology to optimize the mineral recovery of the heap leaching phase by addressing the mineralogical variation of the feed, by alternating the mode of operation depending on the type of ore in the feed. The operational changes considered in the analysis include the leaching of oxide ores by adding only sulfuric acid (H2SO4) as reagent and adding chloride in the case of sulfide ores (secondary sulfides). The incorporation of uncertainty allows the creation of models that maximize the productivity, while confronting the geological uncertainty, as the extraction program progresses. The model seeks to increase the expected recovery from leaching, considering a set of equiprobable geological scenarios. The modeling and simulation of this productive phase is developed through a discrete event simulation (DES) framework. The results of the simulation indicate the potential to address the dynamics of feed variation through the implementation of alternating modes of operation.

Given the active growth of emerging technology industries, it has become essential to have large quantities of critical metals to meet the current demand. In the Chilean mining industry, there is a depletion of high-grade mineral ores, and there is hence a need to increase production levels in the copper industry and diversify its market by extracting other elements. One of the strategies is to foster the production of lithium batteries, but the manufacture requires reserves of cobalt (Co) and manganese (Mn). Currently, Co reserves are not being exploited in Chile, and Mn production is almost negligible. This is due to the apparent shortage of high-grade ores on the land surface of the country. Given this scenario, the seabed manganese nodules are presented as a good alternative due to their high average grades of Co and Mn, which in turn would allow the growth of strategic value-added industries including lithium battery production. Chile’s current environmental regulations prevent the exploitation of marine resources. However, given technological advances worldwide, both in collection mechanisms and extractive processes, in addition to the needs generated from the future strategic plans, leads us to think about a project to exploit manganese nodules locally.

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Strategic decisions to develop a mineral deposit are subject to geological uncertainty, due to the sparsity of drill core samples. The selection of metallurgical equipment is especially critical, since it restricts the processing options that are available to different ore blocks, even as the nature of the deposit is still highly uncertain. Current approaches for long-term mine planning are successful at addressing geological uncertainty, but do not adequately represent alternate modes of operation for the mineral processing plant, nor do they provide sufficient guidance for developing processing options. Nonetheless, recent developments in stochastic optimization and computer data structures have resulted in a framework that can integrate operational modes into strategic mine planning algorithms. A logical next step is to incorporate geometallurgical models that relate mineralogical features to plant performance, as described in this paper.