Effects of High-Order Simulations on the Simultaneous Stochastic Optimization of Mining Complexes
A mining complex is composed of mines, mineral processing streams, stockpiles, and waste facilities, which culminate with generated products that are delivered to customers. The supply uncertainty and variability of materials extracted from the mines, which flow through a mining complex to generate...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-03-01
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| Series: | Minerals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-163X/9/4/210 |
| _version_ | 1811303050865803264 |
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| author | Joao Pedro de Carvalho Roussos Dimitrakopoulos |
| author_facet | Joao Pedro de Carvalho Roussos Dimitrakopoulos |
| author_sort | Joao Pedro de Carvalho |
| collection | DOAJ |
| description | A mining complex is composed of mines, mineral processing streams, stockpiles, and waste facilities, which culminate with generated products that are delivered to customers. The supply uncertainty and variability of materials extracted from the mines, which flow through a mining complex to generate products, can be quantified through geostatistical simulations and can be used as inputs to the simultaneous optimization of mining complexes. A critical aspect to consider is that mineral deposits are characterized by spatially complex, non-Gaussian geological properties and multiple-point connectivity of high-grades, features that are not captured by conventional second-order simulation methods. This paper investigates the benefits of simultaneously optimizing a mining complex where the simulations of the mineral deposit are generated by a high-order, direct-block simulation approach. The optimized life-of-mine (LOM) production schedule is compared to a case in which the same setting is optimized by having the related simulations generated using a second-order simulation method. The comparison shows that the incorporation of simulations that reproduce the spatial connectivity of high-grades results in a more informed LOM production schedule. The sequence of extraction is driven by the spatial connectivity of high-grades, resulting in a mill throughput with better material quality and reduced waste extraction. Furthermore, the discounted cash-flow increases by more than 5% as compared to the case in which the second-order simulations are used. |
| first_indexed | 2024-04-13T07:39:47Z |
| format | Article |
| id | doaj.art-0388cb2aae2e4b5f9ef4fa2384878422 |
| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-04-13T07:39:47Z |
| publishDate | 2019-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-0388cb2aae2e4b5f9ef4fa23848784222022-12-22T02:55:56ZengMDPI AGMinerals2075-163X2019-03-019421010.3390/min9040210min9040210Effects of High-Order Simulations on the Simultaneous Stochastic Optimization of Mining ComplexesJoao Pedro de Carvalho0Roussos Dimitrakopoulos1COSMO—Stochastic Mine Planning Laboratory, Department of Mining and Materials Engineering, McGill University, Montreal, QC H3A 0E8, CanadaCOSMO—Stochastic Mine Planning Laboratory, Department of Mining and Materials Engineering, McGill University, Montreal, QC H3A 0E8, CanadaA mining complex is composed of mines, mineral processing streams, stockpiles, and waste facilities, which culminate with generated products that are delivered to customers. The supply uncertainty and variability of materials extracted from the mines, which flow through a mining complex to generate products, can be quantified through geostatistical simulations and can be used as inputs to the simultaneous optimization of mining complexes. A critical aspect to consider is that mineral deposits are characterized by spatially complex, non-Gaussian geological properties and multiple-point connectivity of high-grades, features that are not captured by conventional second-order simulation methods. This paper investigates the benefits of simultaneously optimizing a mining complex where the simulations of the mineral deposit are generated by a high-order, direct-block simulation approach. The optimized life-of-mine (LOM) production schedule is compared to a case in which the same setting is optimized by having the related simulations generated using a second-order simulation method. The comparison shows that the incorporation of simulations that reproduce the spatial connectivity of high-grades results in a more informed LOM production schedule. The sequence of extraction is driven by the spatial connectivity of high-grades, resulting in a mill throughput with better material quality and reduced waste extraction. Furthermore, the discounted cash-flow increases by more than 5% as compared to the case in which the second-order simulations are used.https://www.mdpi.com/2075-163X/9/4/210simultaneous optimization of mine complexeshigh-order simulationdirect block support simulationconnectivity of high-grades |
| spellingShingle | Joao Pedro de Carvalho Roussos Dimitrakopoulos Effects of High-Order Simulations on the Simultaneous Stochastic Optimization of Mining Complexes Minerals simultaneous optimization of mine complexes high-order simulation direct block support simulation connectivity of high-grades |
| title | Effects of High-Order Simulations on the Simultaneous Stochastic Optimization of Mining Complexes |
| title_full | Effects of High-Order Simulations on the Simultaneous Stochastic Optimization of Mining Complexes |
| title_fullStr | Effects of High-Order Simulations on the Simultaneous Stochastic Optimization of Mining Complexes |
| title_full_unstemmed | Effects of High-Order Simulations on the Simultaneous Stochastic Optimization of Mining Complexes |
| title_short | Effects of High-Order Simulations on the Simultaneous Stochastic Optimization of Mining Complexes |
| title_sort | effects of high order simulations on the simultaneous stochastic optimization of mining complexes |
| topic | simultaneous optimization of mine complexes high-order simulation direct block support simulation connectivity of high-grades |
| url | https://www.mdpi.com/2075-163X/9/4/210 |
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