Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil

Detalhes bibliográficos
Autor(a) principal: Leal, Alessandra Brito
Data de Publicação: 2021
Outros Autores: Moura, Thiago Rafael da Silva
Tipo de documento: Artigo
Idioma: por
Título da fonte: Brazilian Applied Science Review
Texto Completo: https://ojs.brazilianjournals.com.br/ojs/index.php/BASR/article/view/26969
Resumo: We mine the set of data provided by the ANP (Agência Nacional do Petróleo e Gás - National Oil and Gas Agency), of petroleum production and distribution in Brazilian territory. We use modern data science techniques to collect, analyze, treat and model hydrocarbon production data from all production units operating in the period from February 2009 to 2020. We highlight the high production of hydrocarbons in the Brazilian territory related to the performance of Petrobras, responsible for about 95% of Brazilian production. We report the discovery of an apparent paradox: the Tupi field presents the highest daily production, however it is not the largest national producer, a position that belongs to the Marlim field, yet we present the data analytics techniques that we use to solve this paradox.
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spelling Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no BrasilData ScienceBusiness IntelligencePetroleum ProductionWe mine the set of data provided by the ANP (Agência Nacional do Petróleo e Gás - National Oil and Gas Agency), of petroleum production and distribution in Brazilian territory. We use modern data science techniques to collect, analyze, treat and model hydrocarbon production data from all production units operating in the period from February 2009 to 2020. We highlight the high production of hydrocarbons in the Brazilian territory related to the performance of Petrobras, responsible for about 95% of Brazilian production. We report the discovery of an apparent paradox: the Tupi field presents the highest daily production, however it is not the largest national producer, a position that belongs to the Marlim field, yet we present the data analytics techniques that we use to solve this paradox.Brazilian Journals Publicações de Periódicos e Editora Ltda.2021-03-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://ojs.brazilianjournals.com.br/ojs/index.php/BASR/article/view/2696910.34115/basrv5n2-015Brazilian Applied Science Review; Vol. 5 No. 2 (2021); 818-835Brazilian Applied Science Review; v. 5 n. 2 (2021); 818-8352595-36212595-362110.34115/basr.v5i2reponame:Brazilian Applied Science Reviewinstname:Brazilian Journals Publicações de Periódicos e Editora Ltdainstacron:FIEPporhttps://ojs.brazilianjournals.com.br/ojs/index.php/BASR/article/view/26969/21332Copyright (c) 2021 Brazilian Applied Science Reviewinfo:eu-repo/semantics/openAccessLeal, Alessandra BritoMoura, Thiago Rafael da Silva2021-04-28T16:37:23Zoai:ojs2.ojs.brazilianjournals.com.br:article/26969Revistahttps://www.brazilianjournals.com/index.php/BASRPRIhttps://ojs.brazilianjournals.com.br/ojs/index.php/BASR/oaibrazilianasr@yahoo.com || brazilianasr@yahoo.com2595-36212595-3621opendoar:2021-04-28T16:37:23Brazilian Applied Science Review - Brazilian Journals Publicações de Periódicos e Editora Ltdafalse
dc.title.none.fl_str_mv Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil
title Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil
spellingShingle Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil
Leal, Alessandra Brito
Data Science
Business Intelligence
Petroleum Production
title_short Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil
title_full Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil
title_fullStr Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil
title_full_unstemmed Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil
title_sort Data analytics applied to the analysis of petroleum production in Brazil / Análise de dados aplicada à análise da produção de petróleo no Brasil
author Leal, Alessandra Brito
author_facet Leal, Alessandra Brito
Moura, Thiago Rafael da Silva
author_role author
author2 Moura, Thiago Rafael da Silva
author2_role author
dc.contributor.author.fl_str_mv Leal, Alessandra Brito
Moura, Thiago Rafael da Silva
dc.subject.por.fl_str_mv Data Science
Business Intelligence
Petroleum Production
topic Data Science
Business Intelligence
Petroleum Production
description We mine the set of data provided by the ANP (Agência Nacional do Petróleo e Gás - National Oil and Gas Agency), of petroleum production and distribution in Brazilian territory. We use modern data science techniques to collect, analyze, treat and model hydrocarbon production data from all production units operating in the period from February 2009 to 2020. We highlight the high production of hydrocarbons in the Brazilian territory related to the performance of Petrobras, responsible for about 95% of Brazilian production. We report the discovery of an apparent paradox: the Tupi field presents the highest daily production, however it is not the largest national producer, a position that belongs to the Marlim field, yet we present the data analytics techniques that we use to solve this paradox.
publishDate 2021
dc.date.none.fl_str_mv 2021-03-24
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://ojs.brazilianjournals.com.br/ojs/index.php/BASR/article/view/26969
10.34115/basrv5n2-015
url https://ojs.brazilianjournals.com.br/ojs/index.php/BASR/article/view/26969
identifier_str_mv 10.34115/basrv5n2-015
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://ojs.brazilianjournals.com.br/ojs/index.php/BASR/article/view/26969/21332
dc.rights.driver.fl_str_mv Copyright (c) 2021 Brazilian Applied Science Review
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Brazilian Applied Science Review
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Brazilian Journals Publicações de Periódicos e Editora Ltda.
publisher.none.fl_str_mv Brazilian Journals Publicações de Periódicos e Editora Ltda.
dc.source.none.fl_str_mv Brazilian Applied Science Review; Vol. 5 No. 2 (2021); 818-835
Brazilian Applied Science Review; v. 5 n. 2 (2021); 818-835
2595-3621
2595-3621
10.34115/basr.v5i2
reponame:Brazilian Applied Science Review
instname:Brazilian Journals Publicações de Periódicos e Editora Ltda
instacron:FIEP
instname_str Brazilian Journals Publicações de Periódicos e Editora Ltda
instacron_str FIEP
institution FIEP
reponame_str Brazilian Applied Science Review
collection Brazilian Applied Science Review
repository.name.fl_str_mv Brazilian Applied Science Review - Brazilian Journals Publicações de Periódicos e Editora Ltda
repository.mail.fl_str_mv brazilianasr@yahoo.com || brazilianasr@yahoo.com
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