Impact of Geological Uncertainty at Different Stages of the Open-Pit Mine Production Planning Process
This work addresses the long-term open-pit mine production planning. The solution for this problem indicates how and when the ore reserves will be extracted in order to maximize the value of the mining business, generating a promise that commits the mine production over time. Usually, due to the complexity of the problem, the planning process is divided into stages, generating three related problems that are sequentially solved to obtain a tentative production plan, that is: (i) determination of the final pit, which consists of delimiting the subregion of the mine where the extraction will be carried out; (ii) pushbacks selection, that corresponds to a partition of the final pit that allows to guide the sequence of extraction and to control the design; and finally, (iii) temporary production scheduling, which defines when the different zones will be extracted and which of them will be processed.
One of the disadvantages of the traditional methodology is the geological uncertainty is not taken into account, despite the great impact it can have on the production objectives. In this work we show some approaches to incorporate the uncertainty by means of conditional simulations to different stages of production planning, evaluating their impact. The results show that, on one hand, it is possible to increase the expected value of the business, and on the other hand, to reduce the risk of failure to meet production targets, allowing to generate more robust plans. In the case study presented, the results show that it is possible to obtain a discounted expected value increase of 2% and an uncertainty total cost decrease of 69% with respect to the usual methodology, which does not consider the geological uncertainty. Therefore, better decisions could be made in the long-term open pit mine production planning.
KeywordsOpen-pit mine production scheduling Geological uncertainty Stochastic mixed integer programming Conditional simulation
Enrique Jélvez and Nelson Morales were supported by CONICYT/PIA Project AFB180004 – Advanced Mining Technology Center – Universidad de Chile.
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