Visualizing and Quantifying Uncertainty in Cut-off Grade Selection

Abstract

AbstractModern mine planning techniques are advancing at an incredible rate, and mining companies are progressively more interested in quantifying the uncertainty in their business plans. However, for many decision makers and other stakeholders, the leap from tried-and-true deterministic techniques to stochastic methods will be challenging to understand and accept due to the complexity of the work involved. At the 2019 SME Annual Conference, the author introduced a multifaceted model to embrace uncertainty in mine planning (Roos 2019), and at APCOM 2023, the author brought forth some modern data visualization techniques that can be leveraged to achieve this goal (Roos 2023). The purpose of this model is to fill the gap in embracing uncertainty by recommending improvements in visualization and communication techniques to ensure that all mining operations can take steps toward embracing uncertainty quantification. This paper presents a case study leveraging this model to adapt the cut-off grade selection process for an underground gold mine to one that utilizes grade uncertainty and provides the appropriate decision makers with the information they need to embrace the uncertainty in their business plan. The methods presented in this paper do not produce a finite solution to the cut-off grade selection process, but instead provide additional information that can be used in understanding the impact of geological uncertainty on the results of a deterministic study. In this study, the visualization techniques presented here have been useful in identifying areas of the deposit with a higher risk of achieving the estimated grade and also areas where there may be an opportunity to develop future stopes with additional geological information.