Production phase and ultimate pit limit design under commodity price uncertainty

Abstract

Open pit mine design optimization under uncertainty is one of the most critical and challenging tasks in the mine planning process. This paper describes the implementation of a minimum cut network flow algorithm for the optimal production phase and ultimate pit limit design under commodity price or market uncertainty. A new smoothing splines algorithm with sequential Gaussian simulation generates multiple commodity price scenarios, and a computationally efficient stochastic framework accommodates the joint representation and processing of the mining block economic values that result from these commodity price scenarios. A case study at an existing iron mining operation demonstrates the performance of the proposed method, and a comparison with conventional deterministic approach shows a higher cumulative metal production coupled with a 48% increase in the net present value (NPV) of the operation.