Ore-waste discrimination with adaptive sampling strategy

Abstract

Grade control and short-term planning determine the performance of a mining project. Improving this decision, by collecting the most informative samples (data) may have significant financial impact on the project. In this paper, a method to select sampling locations is proposed in an advanced drilling grid for short-term planning and grade control in order to improve the correct assessment (ore-waste discrimination) of blocks. The sampling strategy is based on a regularized maximization of the conditional entropy of the field, functional that formally combines global characterization of the field with the principle of maximizing information extraction for ore-waste discrimination. This sampling strategy is applied to three real cases, where dense blast-hole data is available for validation from several benches. Remarkably, results show relevant and systematic improvement with respect to the standard regular grid strategy, where for deeper benches in the field the gains in ore-waste discrimination are more prominent.