Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization

Detalhes bibliográficos
Autor(a) principal: Afonseca,Bruno de Deus
Data de Publicação: 2021
Outros Autores: Costa,João Felipe Coimbra Leite
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=S2448-167X2021000200199
Resumo: Abstract Non-linear geostatistical methods are known to deal appropriately with the geological and geometrical complexity of gold deposits. This article reports the results related to an investigation to improve the gold content estimate based on restricted ore modeling to honor the structural aspects that control the mineralization. The grade domains are defined by using structural measurements to guide the indicator kriging (IK) estimator. Relevant grade intervals are chosen as indicators. Kriging the indicators provides a measure of the grade uncertainty at the sample support. The probability indicator modeling relies on thresholding the estimates which are represented by cumulative distribution functions (cdf) at the unsampled locations. The implicit concept of probability means that the chance of an estimated node belonging to a given grade domain is as big as the estimated IK value. The geological consistency of IK models requires a proper definition of some key parameters: The probability thresholds and indicator variogram models must honor the structural features and stationarity conditions of grade intervals. The geological representativeness of these models depends heavily on thresholding the estimates. For instance, extremely permissive estimates may produce overrepresented ore domains. The decision of the optimal indicator probability for defining the ore boundaries is made by iterative comparison. Several thresholds were applied to kriged maps and the results reconciled to the most sampled areas until achieving reasonable geological adherence. The mineralization continuity often varies according to local structural features and so dynamic anisotropy is used to control the variogram direction and search ellipse to consider the significant scale trend and small-scale fold geometries. A case study based on a real gold deposit dataset was performed and the method was discussed. The IK models can define precisely the mineralization bounds in the most detailed areas. However, the results presented some limitations on reproducing the geological expectation in regions of wide drilling spacing. The lack of information in some areas led to an excessive number of small sub-zones. The method allows a faster and efficient modeling of structurally complex geometries and provides an uncertainty assessment which may be useful to support exploratory and short-term decisions.
id FG-1_319e9a87b330b4740f516ac2d420cfb1
oai_identifier_str oai:scielo:S2448-167X2021000200199
network_acronym_str FG-1
network_name_str REM - International Engineering Journal
repository_id_str
spelling Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralizationstructural geologygeological modellingIndicator KriginggeostatisticsAbstract Non-linear geostatistical methods are known to deal appropriately with the geological and geometrical complexity of gold deposits. This article reports the results related to an investigation to improve the gold content estimate based on restricted ore modeling to honor the structural aspects that control the mineralization. The grade domains are defined by using structural measurements to guide the indicator kriging (IK) estimator. Relevant grade intervals are chosen as indicators. Kriging the indicators provides a measure of the grade uncertainty at the sample support. The probability indicator modeling relies on thresholding the estimates which are represented by cumulative distribution functions (cdf) at the unsampled locations. The implicit concept of probability means that the chance of an estimated node belonging to a given grade domain is as big as the estimated IK value. The geological consistency of IK models requires a proper definition of some key parameters: The probability thresholds and indicator variogram models must honor the structural features and stationarity conditions of grade intervals. The geological representativeness of these models depends heavily on thresholding the estimates. For instance, extremely permissive estimates may produce overrepresented ore domains. The decision of the optimal indicator probability for defining the ore boundaries is made by iterative comparison. Several thresholds were applied to kriged maps and the results reconciled to the most sampled areas until achieving reasonable geological adherence. The mineralization continuity often varies according to local structural features and so dynamic anisotropy is used to control the variogram direction and search ellipse to consider the significant scale trend and small-scale fold geometries. A case study based on a real gold deposit dataset was performed and the method was discussed. The IK models can define precisely the mineralization bounds in the most detailed areas. However, the results presented some limitations on reproducing the geological expectation in regions of wide drilling spacing. The lack of information in some areas led to an excessive number of small sub-zones. The method allows a faster and efficient modeling of structurally complex geometries and provides an uncertainty assessment which may be useful to support exploratory and short-term decisions.Fundação Gorceix2021-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2021000200199REM - International Engineering Journal v.74 n.2 2021reponame:REM - International Engineering Journalinstname:Fundação Gorceix (FG)instacron:FG10.1590/0370-44672020740034info:eu-repo/semantics/openAccessAfonseca,Bruno de DeusCosta,João Felipe Coimbra Leiteeng2021-03-25T00:00:00Zoai:scielo:S2448-167X2021000200199Revistahttps://www.rem.com.br/?lang=pt-brPRIhttps://old.scielo.br/oai/scielo-oai.php||editor@rem.com.br2448-167X2448-167Xopendoar:2021-03-25T00:00REM - International Engineering Journal - Fundação Gorceix (FG)false
dc.title.none.fl_str_mv Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization
title Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization
spellingShingle Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization
Afonseca,Bruno de Deus
structural geology
geological modelling
Indicator Kriging
geostatistics
title_short Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization
title_full Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization
title_fullStr Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization
title_full_unstemmed Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization
title_sort Dynamic anisotropy and non-linear geostatistics supporting short term modelling of structurally complex gold mineralization
author Afonseca,Bruno de Deus
author_facet Afonseca,Bruno de Deus
Costa,João Felipe Coimbra Leite
author_role author
author2 Costa,João Felipe Coimbra Leite
author2_role author
dc.contributor.author.fl_str_mv Afonseca,Bruno de Deus
Costa,João Felipe Coimbra Leite
dc.subject.por.fl_str_mv structural geology
geological modelling
Indicator Kriging
geostatistics
topic structural geology
geological modelling
Indicator Kriging
geostatistics
description Abstract Non-linear geostatistical methods are known to deal appropriately with the geological and geometrical complexity of gold deposits. This article reports the results related to an investigation to improve the gold content estimate based on restricted ore modeling to honor the structural aspects that control the mineralization. The grade domains are defined by using structural measurements to guide the indicator kriging (IK) estimator. Relevant grade intervals are chosen as indicators. Kriging the indicators provides a measure of the grade uncertainty at the sample support. The probability indicator modeling relies on thresholding the estimates which are represented by cumulative distribution functions (cdf) at the unsampled locations. The implicit concept of probability means that the chance of an estimated node belonging to a given grade domain is as big as the estimated IK value. The geological consistency of IK models requires a proper definition of some key parameters: The probability thresholds and indicator variogram models must honor the structural features and stationarity conditions of grade intervals. The geological representativeness of these models depends heavily on thresholding the estimates. For instance, extremely permissive estimates may produce overrepresented ore domains. The decision of the optimal indicator probability for defining the ore boundaries is made by iterative comparison. Several thresholds were applied to kriged maps and the results reconciled to the most sampled areas until achieving reasonable geological adherence. The mineralization continuity often varies according to local structural features and so dynamic anisotropy is used to control the variogram direction and search ellipse to consider the significant scale trend and small-scale fold geometries. A case study based on a real gold deposit dataset was performed and the method was discussed. The IK models can define precisely the mineralization bounds in the most detailed areas. However, the results presented some limitations on reproducing the geological expectation in regions of wide drilling spacing. The lack of information in some areas led to an excessive number of small sub-zones. The method allows a faster and efficient modeling of structurally complex geometries and provides an uncertainty assessment which may be useful to support exploratory and short-term decisions.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-01
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=S2448-167X2021000200199
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2021000200199
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0370-44672020740034
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.74 n.2 2021
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_ 1754734691878961152