Abstract

This paper presents a geometallurgical study for predicting ore grindability at Tasiast Gold Mine. Drill core samples of main gold-bearing lithologies were subjected to three phases of testing for characterization of physicomechanical, geochemical, mineralogical, and textural rock properties. In phase one, a set of physiomechanical and geochemical properties were measured using rapid and portable rock characterization tests. The measured properties include surface rebound hardness (Leeb hardness test), multi-element geochemistry (portable XRF test), acoustic wave velocity, and strength index (Point load test). In the second phase, the rock samples were subjected to more time-consuming and expensive micro-scale tests including mineralogical characterization by XRD and textural classification by petrographic analysis of thin sections. Finally in the third phase, the core samples were used for Bond ball mill work index (BWI) test to assess their grinding behaviour. Geometallurgical associations were identified between grindability and the geometallurgical test predictors using principal components analytics and K-means clustering. These associations were then used for fitting predictive models for BWI using multiple linear regression. Inferential tests were applied to evaluate how well micro-scale (phase 2) and drill core-scale (phase 1) properties can predict BWI behaviour, and how these predictions capture important geometallurgical relationships to BWI. The best BWI predictive model was considered by assessing statistical fit, testing speed, relative cost, and portability and amenability of the testing tool to the field. Accordingly, at the Tasiast mine multi-element geochemistry and lithological textural characteristics are the top two predictors of BWI.

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