Uncertainty Analysis and Visualization of Open Pit Optimization Results by Considering Variation in Mineral Prices

Abstract

This study proposes a new method to quantitatively represent the uncertainty existing in open pit optimization results due to variations in mineral prices. After generating multiple mineral prices using Monte Carlo simulation with data on past mineral prices, a probability model that represents the uncertainty was developed by integrating multiple open pit optimization results derived from the mineral prices. The results of applying the proposed method to the copper-zinc deposits showed that significant uncertainty exists in open pit optimization results due to the variation in copper prices. In addition, the study was able to quantify the probability that each block that represents deposits is included within the open pit optimal boundary when copper and zinc prices increase or decrease from the current reference prices. Using these probabilities, reserves of the deposits were estimated as a function of confidence level. When confidence level was set at 90% or higher, reserve was estimated to be about 76,000 tonnes, and when confidence level was set at 50% or higher, reserve was estimated to be about 2,550,000 tonnes. This suggests that the proposed method also has a potential as a tool for classifying the estimation results of ore reserve based on confidence level.