publications

2020

1. Risk Analysis of a Large Copper Mining Complex under Joint Geological and Equipment Uncertainty

   Luiz Resende Silva, and Roussos Dimitrakopoulos

   Apr 2020

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   Conventionally optimized production schedules of mining complexes do not account for the different sources of uncertainty. The current work performs a risk analysis over such a production schedule incorporating the joint uncertainty in supply and equipment performance. This quantification of risk due to geological uncertainty and variability is assessed in the study through the use of geological simulations, where a series of orebody models are stochastically simulated conditionally to the available copper grade. Historical mining and processing production data provide the input for generating Monte Carlo simulations for equipment productions. The current risk analysis is performed for a 10-year life of mine deterministically optimized production schedule of a large copper mining complex. Such a mining complex comprises two deposits, two stockpiles, five crushers, three mills, two leach pads, a waste dump and several different mining equipment types and models. The schedule’s response under the different joint uncertainty scenarios is measured, and the impact on metal production and cumulative discounted cash flows are compared to initial forecasts, assessing the risk in meeting these initial predictions. Results show the financial impact of not accounting for geological or equipment uncertainty and substantial differences between the planned forecasts and the schedule’s responses.

2. Application of Simultaneous Stochastic Optimization at Large Copper Mining Complex with Geological and Equipment Uncertainty

   Luiz Resende Silva, and Roussos Dimitrakopoulos

   Jun 2020

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   The simultaneous stochastic optimization of mining complexes aims to optimize the different components in a single optimization model under grade, material type and, in the present work, equipment production uncertainty, capitalizing on the synergies between the various components and the quantified variability and uncertainty of the materials mined, to meet production targets and capacities better. The uncertainty and variability associated with the different material sources are incorporated in the optimization model using stochastic simulations, also employed to quantify the uncertainty related to equipment production, generated conditional to historical mining and processing production data collected from different equipment in the mining complex. The current work presents an application to integrate uncertainty and decisions about mining capacities dictated by the available mining equipment (e.g. trucks and shovels) and crushers’ production capacities in the simultaneous stochastic optimization model. The application of the approach at a large copper mining complex composed of two deposits, three stockpiles, five crushers, three mills, two leach pads, a waste dump and several different mining equipment types and models indicates that the stochastic schedule has higher chances of meeting the production targets and capacities while achieving a substantial increase in the net present value (NPV) of the mining complex when compared to the conventional plan.