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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Main Authors: Flavio Azevedo Neves Amarante, Roberto Mentzingen Rolo, João Felipe Coimbra Leite Costa
Format: Article
Language:English
Published: Fundação Gorceix
Series:REM: International Engineering Journal
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2019000500643&lng=en&tlng=en
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spelling 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
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