Incorporation of geological uncertainty in pit optimization with geostatistics simulation

Detalhes bibliográficos
Autor(a) principal: Souza,Rafael Alvarenga
Data de Publicação: 2017
Outros Autores: Cabral,Ivo Eyer
Tipo de documento: Artigo
Idioma: eng
Título da fonte: REM - International Engineering Journal
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2017000300325
Resumo: Abstract Risk mapping processes in mine planning and ore recovery are constantly used in the mining industry to increase decision making certainty based on the available information. However, it is not possible to predict the risk behavior in all of the project's boundary conditions and small variations in some of these conditions can cause a great impact on its financial return. Among the countless uncertainties existing in a mining project (operational, costs, market change), many authors define the geological uncertainty as the most critical one, capable of influencing the success of the project. Measurement and evaluation of the geological uncertainty of a mine planning project is crucial because the calculated risk can be translated into a financial risk of the project. This article presents a possible way to consider the geological uncertainty in the pit optimization step by using sequential Gaussian simulation. The results obtained from the case study on a copper deposit results in a simple procedure with significant increase in reliability for the project.
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spelling Incorporation of geological uncertainty in pit optimization with geostatistics simulationrisksgeological uncertaintysequential Gaussian simulationmine planningpit optimizationAbstract Risk mapping processes in mine planning and ore recovery are constantly used in the mining industry to increase decision making certainty based on the available information. However, it is not possible to predict the risk behavior in all of the project's boundary conditions and small variations in some of these conditions can cause a great impact on its financial return. Among the countless uncertainties existing in a mining project (operational, costs, market change), many authors define the geological uncertainty as the most critical one, capable of influencing the success of the project. Measurement and evaluation of the geological uncertainty of a mine planning project is crucial because the calculated risk can be translated into a financial risk of the project. This article presents a possible way to consider the geological uncertainty in the pit optimization step by using sequential Gaussian simulation. The results obtained from the case study on a copper deposit results in a simple procedure with significant increase in reliability for the project.Fundação Gorceix2017-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2017000300325REM - International Engineering Journal v.70 n.3 2017reponame:REM - International Engineering Journalinstname:Fundação Gorceix (FG)instacron:FG10.1590/0370-44672016700134info:eu-repo/semantics/openAccessSouza,Rafael AlvarengaCabral,Ivo Eyereng2017-07-21T00:00:00Zoai:scielo:S2448-167X2017000300325Revistahttps://www.rem.com.br/?lang=pt-brPRIhttps://old.scielo.br/oai/scielo-oai.php||editor@rem.com.br2448-167X2448-167Xopendoar:2017-07-21T00:00REM - International Engineering Journal - Fundação Gorceix (FG)false
dc.title.none.fl_str_mv Incorporation of geological uncertainty in pit optimization with geostatistics simulation
title Incorporation of geological uncertainty in pit optimization with geostatistics simulation
spellingShingle Incorporation of geological uncertainty in pit optimization with geostatistics simulation
Souza,Rafael Alvarenga
risks
geological uncertainty
sequential Gaussian simulation
mine planning
pit optimization
title_short Incorporation of geological uncertainty in pit optimization with geostatistics simulation
title_full Incorporation of geological uncertainty in pit optimization with geostatistics simulation
title_fullStr Incorporation of geological uncertainty in pit optimization with geostatistics simulation
title_full_unstemmed Incorporation of geological uncertainty in pit optimization with geostatistics simulation
title_sort Incorporation of geological uncertainty in pit optimization with geostatistics simulation
author Souza,Rafael Alvarenga
author_facet Souza,Rafael Alvarenga
Cabral,Ivo Eyer
author_role author
author2 Cabral,Ivo Eyer
author2_role author
dc.contributor.author.fl_str_mv Souza,Rafael Alvarenga
Cabral,Ivo Eyer
dc.subject.por.fl_str_mv risks
geological uncertainty
sequential Gaussian simulation
mine planning
pit optimization
topic risks
geological uncertainty
sequential Gaussian simulation
mine planning
pit optimization
description Abstract Risk mapping processes in mine planning and ore recovery are constantly used in the mining industry to increase decision making certainty based on the available information. However, it is not possible to predict the risk behavior in all of the project's boundary conditions and small variations in some of these conditions can cause a great impact on its financial return. Among the countless uncertainties existing in a mining project (operational, costs, market change), many authors define the geological uncertainty as the most critical one, capable of influencing the success of the project. Measurement and evaluation of the geological uncertainty of a mine planning project is crucial because the calculated risk can be translated into a financial risk of the project. This article presents a possible way to consider the geological uncertainty in the pit optimization step by using sequential Gaussian simulation. The results obtained from the case study on a copper deposit results in a simple procedure with significant increase in reliability for the project.
publishDate 2017
dc.date.none.fl_str_mv 2017-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2017000300325
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2017000300325
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0370-44672016700134
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Fundação Gorceix
publisher.none.fl_str_mv Fundação Gorceix
dc.source.none.fl_str_mv REM - International Engineering Journal v.70 n.3 2017
reponame:REM - International Engineering Journal
instname:Fundação Gorceix (FG)
instacron:FG
instname_str Fundação Gorceix (FG)
instacron_str FG
institution FG
reponame_str REM - International Engineering Journal
collection REM - International Engineering Journal
repository.name.fl_str_mv REM - International Engineering Journal - Fundação Gorceix (FG)
repository.mail.fl_str_mv ||editor@rem.com.br
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