Geostatistical Modelling of Geometalurgical Variables Through Turning Bands Approach

Abstract

Geometallurgical variables have a significant impact in downstream activities of mining projects. Reliable 3D spatial modelling of these variables play an important role in mine planning and mineral processing, in which it can maximize overall viability of the project. This interdisciplinary paradigm involves geology, geostatistics, mineral processing and metallurgy, needs enhanced techniques to model these variables. In some circumstances, these geometallurgical responses demonstrate a good intrinsic correlation that motivates one to use co-estimation or cosimulation approaches. The latter allows to reproduce that dependency characteristic in the final model. Among others, total and soluble copper grades as two important geometallurgical variables in copper deposits show some complex interrelationship characteristics. The reason is that the total copper grade in the material processed by heap leaching is not in complete agreement with the expected recovered grade and one can see a significant variation in different oxide minerals. In such cases, the current approaches of probabilistic modelling such as independent simulation gives poor results. In this paper, turning band simulation methodology in combination with minimum/maximum autocorrelation factor (MAF) used to reproduce this kind of behaviour and compare with those results obtained from conventional co-simulation approach.