Mine Planning with Variable Price Input: A Case of Using Mine Planning Software

Document Type

Article

Publication Date

1-1-2025

Abstract

The success of a mining project heavily dependent on the accuracy of input parameters used during the mine planning process, particularly commodity price that determines the proportion of ore and waste in the deposit. Conventional mine planning tools typically employ the Lerchs-Grossman (LG) algorithm, which takes fixed commodity price as input to generate ultimate pit limit and pushbacks. This article used an enhanced approach to incorporate commodity prices volatility into the LG algorithm. Initially, gold prices were predicted using the Autoregressive Distributed Lag (ARDL) which was deemed suitable for the chosen commodity from the previous studies. These prices were then integrated into the LG mine planning algorithm on an annual basis to estimate the impact of price volatility on net present value (NPV) when commodity prices are under both upward and downward price trends. Finally, a comparison was made between constant price and variable price approaches using NPV. The results showed that the constant price model underestimated the NPV by approximately 35%, whereas the ARDL-based forecast led to a 27% overestimation relative to the actual price. Conversely, during periods of price decline, the deterministic price model overestimated NPV by nearly 30%, while the ARDL approach yielded an underestimation of only 4%. The results confirm that incorporating price volatility into the mine planning software that employing LG mine planning algorithm is possible and also yields NPV estimates that more close to reality compared to those derived from a constant price assumption.

Publication Title

Mining Metallurgy and Exploration

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