Assessing geologic model uncertainty - a case study comparing methods
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 min...
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doaj-52983347ae78436aa4d64a7f045c52972020-11-25T01:25:34ZengFundação GorceixREM: International Engineering Journal2448-167X72464365310.1590/0370-44672019720037S2448-167X2019000500643Assessing geologic model uncertainty - a case study comparing methodsFlavio Azevedo Neves AmaranteRoberto Mentzingen RoloJoão Felipe Coimbra Leite CostaAbstract 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.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2019000500643&lng=en&tlng=engeological modelmultipoint geostatisticsimplicit modelinguncertainty |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Flavio Azevedo Neves Amarante Roberto Mentzingen Rolo João Felipe Coimbra Leite Costa |
spellingShingle |
Flavio Azevedo Neves Amarante Roberto Mentzingen Rolo João Felipe Coimbra Leite Costa Assessing geologic model uncertainty - a case study comparing methods REM: International Engineering Journal geological model multipoint geostatistics implicit modeling uncertainty |
author_facet |
Flavio Azevedo Neves Amarante Roberto Mentzingen Rolo João Felipe Coimbra Leite Costa |
author_sort |
Flavio Azevedo Neves Amarante |
title |
Assessing geologic model uncertainty - a case study comparing methods |
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 |
publisher |
Fundação Gorceix |
series |
REM: International Engineering Journal |
issn |
2448-167X |
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. |
topic |
geological model multipoint geostatistics implicit modeling uncertainty |
url |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2019000500643&lng=en&tlng=en |
work_keys_str_mv |
AT flavioazevedonevesamarante assessinggeologicmodeluncertaintyacasestudycomparingmethods AT robertomentzingenrolo assessinggeologicmodeluncertaintyacasestudycomparingmethods AT joaofelipecoimbraleitecosta assessinggeologicmodeluncertaintyacasestudycomparingmethods |
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