Simulation of Synthetic Exploration and Geometallurgical Database of Porphyry Copper Deposits for Educational Purposes
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Original Paper
Simulation of Synthetic Exploration and Geometallurgical Database of Porphyry Copper Deposits for Educational Purposes Mauricio Garrido ,1,5 Exequiel Sepu´lveda ,2,3 Julia´n Ortiz ,4 and Brian Townley1 Received 23 December 2019; accepted 29 April 2020
The access to real geometallurgical data is very limited in practice, making it difficult for practitioners, researchers and students to test methods, models and reproduce results in the field of geometallurgy. The aim of this work is to propose a methodology to simulate geometallurgical data with geostatistical tools preserving the coherent relationship among primary attributes, such as grades and geological attributes, with mineralogy and some response attributes, for example, grindability, throughput, kinetic flotation performance and recovery. The methodology is based in three main components: (1) definition of spatial relationship between geometallurgical units, (2) cosimulation of regionalized variables with geometallurgical coherence and (3) simulation of georeferenced drill holes based on geometrical and operational constraints. The simulated geometallurgical drill holes generated look very realistic, and they are consistent with the input statistics, coherent in terms of geology and mineralogy and produce realistic processing metallurgical performance responses. These simulations can be used for several purposes, for example, benchmarking geometallurgical modeling methods and mine planning optimization solvers, or performing risk assessment under different blending schemes. Generated datasets are available in a public repository. KEY WORDS: Geometallurgy, Geostatistics, Synthetic database, Uncertainty.
INTRODUCTION At present, access to large mining exploration and/or geometallurgical databases from industry, for academic and/or educational purposes, is difficult, and this due to confidentiality restrictions and/or 1
Department of Geology, Universidad de Chile, Santiago, Chile. School of Civil, Environmental and Mining Engineering, The University of Adelaide, Adelaide, Australia. 3 School of Mining Engineering, Universidad de Talca, Talca, Chile. 4 The Robert M. Buchan Department of Mining, QueenÕs University, Kingston, ON, Canada. 5 To whom correspondence should be addressed; e-mail: [email protected] 2
budget limitations. Development of realistic synthetic geometallurgical databases as proposed in this paper may allow an alternative to such problem and may also offer a robust tool for the purposes of benchmarking exploration and/or geometallurgical modeling, mine planning methods or reserves estimations (Garrido et al. 2019). Geometallurgy has become an important field in mining engineering because of its benefits on the ore quality on mine planning, plant performance, lower costs and product quality. To incorporate these benefits into the mining value chain, key metallurgical responses and proxy variables need to be incorporated into the block model, which is the main input to solve many optimization problems in
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