Geostatistical analysis of a geochemical dataset

Detalhes bibliográficos
Autor(a) principal: Paz-Ferreiro,Jorge
Data de Publicação: 2010
Outros Autores: Vázquez,Eva Vidal, Vieira,Sidney Rosa
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Bragantia
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500013
Resumo: The application of geostatistics to data obtained from geochemical prospecting process can provide useful information for evaluating mineralization potential. The objective of this study was to evaluate the spatial distribution of Au, As and Sb contents over a large area of the Coruña province, Spain. A geochemical survey was carried out from which a data set with 323 samples was collected. Macroelements and trace elements were determined by routine analytical techniques. The spatial variability was assessed using semivariogram and cross-semivariogram as well as indicator semivariogram analysis. Frequency distributions of the studied elements departed from normal, as indicated by skewness and kurtosis coefficients. Coefficients of variation ranked as follows: Sb < As < Au. Significant correlation coefficients between Au, Sb and As were found, even though the correlation values were low. Spherical models with nugget effects ranging from 50% (As) to 57.8% (Au) were fitted to the experimental semivariograms. Cross semivariograms of Au versus Sb and As showed smaller nugget variance than individual semivariograms. Indicator semivariograms were calculated taken mean, median, and different percentiles as threshold values. Ordinary kriging, cokriging, and indicator kriging were performed to generate geochemical maps. The method has succeeded in effectively extracting useful information, and improving the analysis of the metallogenic and ore-controlling factors, thereby playing an important role in qualitative and quantitative predictions.
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spelling Geostatistical analysis of a geochemical datasetgeochemical surveygeostatisticskrigingindicator krigingcokrigingThe application of geostatistics to data obtained from geochemical prospecting process can provide useful information for evaluating mineralization potential. The objective of this study was to evaluate the spatial distribution of Au, As and Sb contents over a large area of the Coruña province, Spain. A geochemical survey was carried out from which a data set with 323 samples was collected. Macroelements and trace elements were determined by routine analytical techniques. The spatial variability was assessed using semivariogram and cross-semivariogram as well as indicator semivariogram analysis. Frequency distributions of the studied elements departed from normal, as indicated by skewness and kurtosis coefficients. Coefficients of variation ranked as follows: Sb < As < Au. Significant correlation coefficients between Au, Sb and As were found, even though the correlation values were low. Spherical models with nugget effects ranging from 50% (As) to 57.8% (Au) were fitted to the experimental semivariograms. Cross semivariograms of Au versus Sb and As showed smaller nugget variance than individual semivariograms. Indicator semivariograms were calculated taken mean, median, and different percentiles as threshold values. Ordinary kriging, cokriging, and indicator kriging were performed to generate geochemical maps. The method has succeeded in effectively extracting useful information, and improving the analysis of the metallogenic and ore-controlling factors, thereby playing an important role in qualitative and quantitative predictions.Instituto Agronômico de Campinas2010-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500013Bragantia v.69 suppl.0 2010reponame:Bragantiainstname:Instituto Agronômico de Campinas (IAC)instacron:IAC10.1590/S0006-87052010000500013info:eu-repo/semantics/openAccessPaz-Ferreiro,JorgeVázquez,Eva VidalVieira,Sidney Rosaeng2011-02-14T00:00:00Zoai:scielo:S0006-87052010000500013Revistahttps://www.scielo.br/j/brag/https://old.scielo.br/oai/scielo-oai.phpbragantia@iac.sp.gov.br||bragantia@iac.sp.gov.br1678-44990006-8705opendoar:2011-02-14T00:00Bragantia - Instituto Agronômico de Campinas (IAC)false
dc.title.none.fl_str_mv Geostatistical analysis of a geochemical dataset
title Geostatistical analysis of a geochemical dataset
spellingShingle Geostatistical analysis of a geochemical dataset
Paz-Ferreiro,Jorge
geochemical survey
geostatistics
kriging
indicator kriging
cokriging
title_short Geostatistical analysis of a geochemical dataset
title_full Geostatistical analysis of a geochemical dataset
title_fullStr Geostatistical analysis of a geochemical dataset
title_full_unstemmed Geostatistical analysis of a geochemical dataset
title_sort Geostatistical analysis of a geochemical dataset
author Paz-Ferreiro,Jorge
author_facet Paz-Ferreiro,Jorge
Vázquez,Eva Vidal
Vieira,Sidney Rosa
author_role author
author2 Vázquez,Eva Vidal
Vieira,Sidney Rosa
author2_role author
author
dc.contributor.author.fl_str_mv Paz-Ferreiro,Jorge
Vázquez,Eva Vidal
Vieira,Sidney Rosa
dc.subject.por.fl_str_mv geochemical survey
geostatistics
kriging
indicator kriging
cokriging
topic geochemical survey
geostatistics
kriging
indicator kriging
cokriging
description The application of geostatistics to data obtained from geochemical prospecting process can provide useful information for evaluating mineralization potential. The objective of this study was to evaluate the spatial distribution of Au, As and Sb contents over a large area of the Coruña province, Spain. A geochemical survey was carried out from which a data set with 323 samples was collected. Macroelements and trace elements were determined by routine analytical techniques. The spatial variability was assessed using semivariogram and cross-semivariogram as well as indicator semivariogram analysis. Frequency distributions of the studied elements departed from normal, as indicated by skewness and kurtosis coefficients. Coefficients of variation ranked as follows: Sb < As < Au. Significant correlation coefficients between Au, Sb and As were found, even though the correlation values were low. Spherical models with nugget effects ranging from 50% (As) to 57.8% (Au) were fitted to the experimental semivariograms. Cross semivariograms of Au versus Sb and As showed smaller nugget variance than individual semivariograms. Indicator semivariograms were calculated taken mean, median, and different percentiles as threshold values. Ordinary kriging, cokriging, and indicator kriging were performed to generate geochemical maps. The method has succeeded in effectively extracting useful information, and improving the analysis of the metallogenic and ore-controlling factors, thereby playing an important role in qualitative and quantitative predictions.
publishDate 2010
dc.date.none.fl_str_mv 2010-01-01
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500013
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500013
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0006-87052010000500013
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Instituto Agronômico de Campinas
publisher.none.fl_str_mv Instituto Agronômico de Campinas
dc.source.none.fl_str_mv Bragantia v.69 suppl.0 2010
reponame:Bragantia
instname:Instituto Agronômico de Campinas (IAC)
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instname_str Instituto Agronômico de Campinas (IAC)
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repository.name.fl_str_mv Bragantia - Instituto Agronômico de Campinas (IAC)
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