Synthetic high-resolution ore deposit model and mine plan

dc.contributor.authorAltinpinar, Mehmet
dc.contributor.authorSari, Yuksel Asli
dc.contributor.authorOrtiz, Julian M.
dc.date.accessioned2020-10-29T20:37:42Z
dc.date.available2020-10-29T20:37:42Z
dc.date.issued2020
dc.description.abstractDecision making in the mining value chain is hindered by the variability of the rock properties and the uncertainty associated with their estimation in the blocks mined and processed. In addition to the grades of the elements and metals of interest, the presence of deleterious materials, and the geometallurgical properties of the rock have a significant impact on the economic performance of mining projects. Researchers are faced with the challenge that there are very limited opportunities for benchmarking methods, considering that this type of information is proprietary from mining companies and seldom shared for research purposes. In this study, we discuss the methodology to build a realistic block model, which contains grades as well as mineralogical and geometallurgical properties, for benchmarking purposes. This model is used to simulate mining decisions through the mine value chain. For this, a high-resolution model is created, and samples are extracted from this model to allow for comparison of estimation and planning decisions with the actual performance as the model provides access to the ground truth. This synthetic block model is built at a high resolution and blocks are then averaged to different supports to learn about the impact of selectivity and to assess dilution, grade control, mine planning, and processing strategies. This model also serves to demonstrate the use of advanced planning techniques and could also be used to test artificial intelligence tools in prediction, forecasting and decision making.en
dc.identifier.citationAltinpinar M, Sari YA, Ortiz JM (2020) Synthetic high-resolution ore deposit model and mine plan, paper 2020-09. Preprint.en
dc.identifier.urihttp://hdl.handle.net/1974/28547
dc.language.isoenen
dc.publisherQueen's Universityen
dc.relationQueen's University Research Initiation Granten
dc.relationMitacs Accelerateen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleSynthetic high-resolution ore deposit model and mine planen
dc.typepreprinten
oaire.awardNumberRGPIN-2017-04200en
oaire.awardNumberRGPAS-2017-507956en
oaire.awardNumberFR37072-IT14674en
project.funder.identifierhttp://dx.doi.org/10.13039/501100003321en
project.funder.identifierhttp://dx.doi.org//10.13039/501100000038en
project.funder.identifierhttp://dx.doi.org/10.13039/501100004489en
project.funder.nameQueen's Universityen
project.funder.nameNSERCen
project.funder.nameMitacsen
project.funder.nameSRK Consulting Canadaen
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