Assessing geologic model uncertainty - a case study comparing methods
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
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=S2448-167X2019000500643 |
Resumo: | Abstract Evaluating mineral resources requires the prior delimitation of geologically homogeneous stationary domains. The knowledge about the ore genesis and geological processes involved are translated into three dimensional models, essential for planning the production and decision-making. The mineral industry usually considers grade uncertainty for resource evaluation; however, uncertainty related to the geological boundaries are often neglected. This uncertainty, related to the location of the boundary between distinct geological domains can be one of the major sources of uncertainty in a mineral project, and should be assessed due to its potential impact on the ore tonnage, and consequently, on enterprise profitability. This study aims at presenting three different methodologies capable of generating multiple geomodel realizations and thus, assessing uncertainty. A real dataset with high geological complexity is used to illustrate the methodology. The results are compared to a deterministic model used as a reference scenario. |
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REM - International Engineering Journal |
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Assessing geologic model uncertainty - a case study comparing methodsgeological modelmultipoint geostatisticsimplicit modelinguncertaintyAbstract Evaluating mineral resources requires the prior delimitation of geologically homogeneous stationary domains. The knowledge about the ore genesis and geological processes involved are translated into three dimensional models, essential for planning the production and decision-making. The mineral industry usually considers grade uncertainty for resource evaluation; however, uncertainty related to the geological boundaries are often neglected. This uncertainty, related to the location of the boundary between distinct geological domains can be one of the major sources of uncertainty in a mineral project, and should be assessed due to its potential impact on the ore tonnage, and consequently, on enterprise profitability. This study aims at presenting three different methodologies capable of generating multiple geomodel realizations and thus, assessing uncertainty. A real dataset with high geological complexity is used to illustrate the methodology. The results are compared to a deterministic model used as a reference scenario.Fundação Gorceix2019-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2019000500643REM - International Engineering Journal v.72 n.4 2019reponame:REM - International Engineering Journalinstname:Fundação Gorceix (FG)instacron:FG10.1590/0370-44672019720037info:eu-repo/semantics/openAccessAmarante,Flavio Azevedo NevesRolo,Roberto MentzingenCosta,João Felipe Coimbra Leiteeng2019-09-13T00:00:00Zoai:scielo:S2448-167X2019000500643Revistahttps://www.rem.com.br/?lang=pt-brPRIhttps://old.scielo.br/oai/scielo-oai.php||editor@rem.com.br2448-167X2448-167Xopendoar:2019-09-13T00:00REM - International Engineering Journal - Fundação Gorceix (FG)false |
dc.title.none.fl_str_mv |
Assessing geologic model uncertainty - a case study comparing methods |
title |
Assessing geologic model uncertainty - a case study comparing methods |
spellingShingle |
Assessing geologic model uncertainty - a case study comparing methods Amarante,Flavio Azevedo Neves geological model multipoint geostatistics implicit modeling uncertainty |
title_short |
Assessing geologic model uncertainty - a case study comparing methods |
title_full |
Assessing geologic model uncertainty - a case study comparing methods |
title_fullStr |
Assessing geologic model uncertainty - a case study comparing methods |
title_full_unstemmed |
Assessing geologic model uncertainty - a case study comparing methods |
title_sort |
Assessing geologic model uncertainty - a case study comparing methods |
author |
Amarante,Flavio Azevedo Neves |
author_facet |
Amarante,Flavio Azevedo Neves Rolo,Roberto Mentzingen Costa,João Felipe Coimbra Leite |
author_role |
author |
author2 |
Rolo,Roberto Mentzingen Costa,João Felipe Coimbra Leite |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Amarante,Flavio Azevedo Neves Rolo,Roberto Mentzingen Costa,João Felipe Coimbra Leite |
dc.subject.por.fl_str_mv |
geological model multipoint geostatistics implicit modeling uncertainty |
topic |
geological model multipoint geostatistics implicit modeling uncertainty |
description |
Abstract Evaluating mineral resources requires the prior delimitation of geologically homogeneous stationary domains. The knowledge about the ore genesis and geological processes involved are translated into three dimensional models, essential for planning the production and decision-making. The mineral industry usually considers grade uncertainty for resource evaluation; however, uncertainty related to the geological boundaries are often neglected. This uncertainty, related to the location of the boundary between distinct geological domains can be one of the major sources of uncertainty in a mineral project, and should be assessed due to its potential impact on the ore tonnage, and consequently, on enterprise profitability. This study aims at presenting three different methodologies capable of generating multiple geomodel realizations and thus, assessing uncertainty. A real dataset with high geological complexity is used to illustrate the methodology. The results are compared to a deterministic model used as a reference scenario. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10-01 |
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=S2448-167X2019000500643 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2019000500643 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0370-44672019720037 |
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.72 n.4 2019 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 |
_version_ |
1754734691432267776 |