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A Hybrid Approach for Joint Simulation of Geometallurgical Variables with Inequality Constraint

Department of Mining Engineering, School of Mining and Geosciences, Nazarbayev University, Astana 010000, Kazakhstan
Mining Engineering and Metallurgical Engineering, WA School of Mines, Faculty of Science and Engineering Curtin University, Bentley WA 6102, Australia
Author to whom correspondence should be addressed.
Minerals 2019, 9(1), 24;
Received: 14 September 2018 / Revised: 10 December 2018 / Accepted: 10 December 2018 / Published: 4 January 2019
(This article belongs to the Special Issue Geometallurgy)
Geometallurgical variables have a significant impact on downstream activities of mining projects. Reliable 3D spatial modelling of these variables plays an important role in mine planning and mineral processing, in which it can improve the overall viability of the mining projects. This interdisciplinary paradigm involves geology, geostatistics, mineral processing and metallurgy that creates a need for enhanced techniques of modelling. In some circumstances, the geometallurgical responses demonstrate a decent intrinsic correlation that motivates one to use co-estimation or co-simulation approaches rather than independent estimation or simulation. The latter approach allows us to reproduce that dependency characteristic in the final model. In this paper, two problems have been addressed, one is concerning the inequality constraint that might exist among geometallurgical variables, and the second is dealing with difficulty in variogram analysis. To alleviate the first problem, the variables can be converted to new variables free of inequality constraint. The second problem can also be solved by taking into account the minimum/maximum autocorrelation factors (MAF) transformation technique which allows defining a hybrid approach of joint simulation rather than conventional method of co-simulation. A case study was carried out for the total and acid soluble copper grades obtained from an oxide copper deposit. Firstly, these two geometallurgical variables are transferred to the new variables without inequality constraint and then MAF analysis is used for joint simulation and modelling. After back transformation of the results, they are compared with traditional approaches of co-simulation, for which they showed that the MAF methodology is able to reproduce the spatial correlation between the variables without loss of generality while the inequality constraint is honored. The results are then post processed to support probabilistic domaining of geometallurgical zones. View Full-Text
Keywords: MAF; Geometallurgy; joint simulation; inequality constraint MAF; Geometallurgy; joint simulation; inequality constraint
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MDPI and ACS Style

Abildin, Y.; Madani, N.; Topal, E. A Hybrid Approach for Joint Simulation of Geometallurgical Variables with Inequality Constraint. Minerals 2019, 9, 24.

AMA Style

Abildin Y, Madani N, Topal E. A Hybrid Approach for Joint Simulation of Geometallurgical Variables with Inequality Constraint. Minerals. 2019; 9(1):24.

Chicago/Turabian Style

Abildin, Yerniyaz, Nasser Madani, and Erkan Topal. 2019. "A Hybrid Approach for Joint Simulation of Geometallurgical Variables with Inequality Constraint" Minerals 9, no. 1: 24.

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