Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control

Detalhes bibliográficos
Autor(a) principal: Silva,Victor Miguel
Data de Publicação: 2016
Outros Autores: Costa,Joao 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=S2448-167X2016000400491
Resumo: Abstract Data quality control programs used in the mineral industry normally define tolerance limits based on values considered as good practice or those that have previously been applied to similar deposits, although the precision and accuracy of estimates depend on a combination of geological characteristics, estimation parameters, sample spacing and data quality. This study investigates how the sample quality limits affect the estimates results. The proposed methodology is based on a series of metrics used to compare the impact on the estimates using a synthetic database with an increasing amount of error added to the original sample grades or positions, emulating different levels of precision. The proposed approach results lead to tolerance limits for the grades similar to those recommended in literature. The influence of the positional uncertainty on model estimates is at a minimum, because of the accuracy of current surveying methods that have a deviation in the order of millimeters, so its impact can be considered negligible.
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spelling Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality controlgeostatisticsdata uncertaintysensitivity analysissampling errorQA/QCAbstract Data quality control programs used in the mineral industry normally define tolerance limits based on values considered as good practice or those that have previously been applied to similar deposits, although the precision and accuracy of estimates depend on a combination of geological characteristics, estimation parameters, sample spacing and data quality. This study investigates how the sample quality limits affect the estimates results. The proposed methodology is based on a series of metrics used to compare the impact on the estimates using a synthetic database with an increasing amount of error added to the original sample grades or positions, emulating different levels of precision. The proposed approach results lead to tolerance limits for the grades similar to those recommended in literature. The influence of the positional uncertainty on model estimates is at a minimum, because of the accuracy of current surveying methods that have a deviation in the order of millimeters, so its impact can be considered negligible.Fundação Gorceix2016-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2016000400491REM - International Engineering Journal v.69 n.4 2016reponame:REM - International Engineering Journalinstname:Fundação Gorceix (FG)instacron:FG10.1590/0370-44672015690159info:eu-repo/semantics/openAccessSilva,Victor MiguelCosta,Joao Felipe Coimbra Leiteeng2016-10-17T00:00:00Zoai:scielo:S2448-167X2016000400491Revistahttps://www.rem.com.br/?lang=pt-brPRIhttps://old.scielo.br/oai/scielo-oai.php||editor@rem.com.br2448-167X2448-167Xopendoar:2016-10-17T00:00REM - International Engineering Journal - Fundação Gorceix (FG)false
dc.title.none.fl_str_mv Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
title Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
spellingShingle Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
Silva,Victor Miguel
geostatistics
data uncertainty
sensitivity analysis
sampling error
QA/QC
title_short Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
title_full Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
title_fullStr Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
title_full_unstemmed Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
title_sort Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
author Silva,Victor Miguel
author_facet Silva,Victor Miguel
Costa,Joao Felipe Coimbra Leite
author_role author
author2 Costa,Joao Felipe Coimbra Leite
author2_role author
dc.contributor.author.fl_str_mv Silva,Victor Miguel
Costa,Joao Felipe Coimbra Leite
dc.subject.por.fl_str_mv geostatistics
data uncertainty
sensitivity analysis
sampling error
QA/QC
topic geostatistics
data uncertainty
sensitivity analysis
sampling error
QA/QC
description Abstract Data quality control programs used in the mineral industry normally define tolerance limits based on values considered as good practice or those that have previously been applied to similar deposits, although the precision and accuracy of estimates depend on a combination of geological characteristics, estimation parameters, sample spacing and data quality. This study investigates how the sample quality limits affect the estimates results. The proposed methodology is based on a series of metrics used to compare the impact on the estimates using a synthetic database with an increasing amount of error added to the original sample grades or positions, emulating different levels of precision. The proposed approach results lead to tolerance limits for the grades similar to those recommended in literature. The influence of the positional uncertainty on model estimates is at a minimum, because of the accuracy of current surveying methods that have a deviation in the order of millimeters, so its impact can be considered negligible.
publishDate 2016
dc.date.none.fl_str_mv 2016-12-01
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=S2448-167X2016000400491
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2016000400491
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0370-44672015690159
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.69 n.4 2016
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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