Evaluation of rock characterization tests as geometallurgical predictors of bond work index at the Tasiast Mine, Mauritania. (1st January 2022)

• Record Type: Journal Article
• Authors: Bhuiyan, Mahadi; Esmaeili, Kamran; Ordóñez-Calderón, Juan C.
• Is Part Of: Minerals engineering. Volume 175(2022)
• Publication Date: 2022-01-01
• Subjects: Rock characterization -- Geometallurgy -- Data analytics -- Bond work index -- Portable XRF -- Equotip leeb hardness -- Point load strength test -- Ultrasonic pulse velocity; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Mines and mineral resources; Periodicals; Electronic journals; 622
• DOI: 10.1016/j.mineng.2021.107293
• Languages: English
• ISSNs: 0892-6875

Abstract

Highlights: A practical geometallurgical testing program was proposed for prediction of rock comminution behaviour based on rock characterization tests at Tasiast mine. Drill core samples from the mine were tested to measure physical, mechanical, geochemical, mineralogical, and textural rock properties. Geometallurgical associations were established between the measured rock properties and the rock grindability index using unsupervised data analytics techniques. A multi-linear regression approach was applied to assess the prediction of rock comminution index based on rock characterization tests. 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.