Risk assessment for reservoir development under uncertainty
Autor(a) principal: | |
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Data de Publicação: | 2004 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782004000200014 |
Resumo: | Decision analysis applied to petroleum field development is always strongly related to risk due to the uncertainties present in the process. Methodologies to quantify the impact of uncertainties are still not well established due to the amount of variables that have to be considered. The complete analysis usually depends on geological, economical and technological uncertainties that have different degrees of impact in the recovery process and may affect the decision process at different levels depending on the problem, reservoir characteristics, recovery mechanism and stage of field development. This paper shows several details of a methodology that can be applied to complex and simple reservoirs in a reasonable amount of time, discussing especially the influence of the model used to predict recovery, choice of production strategies to be used in the process, number of attributes and type of information necessary to obtain reliable results. A discussion of data integration among geology, reservoir engineering and economic analysis also is presented in order to reduce the amount of information necessary and time for the process. Some results are presented to show the advantages of automation and parallel computing to reduce the total time of the procedure where reservoir simulation is necessary for reservoir performance prediction. |
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Risk assessment for reservoir development under uncertaintyPetroleumreservoir engineeringuncertaintyriskDecision analysis applied to petroleum field development is always strongly related to risk due to the uncertainties present in the process. Methodologies to quantify the impact of uncertainties are still not well established due to the amount of variables that have to be considered. The complete analysis usually depends on geological, economical and technological uncertainties that have different degrees of impact in the recovery process and may affect the decision process at different levels depending on the problem, reservoir characteristics, recovery mechanism and stage of field development. This paper shows several details of a methodology that can be applied to complex and simple reservoirs in a reasonable amount of time, discussing especially the influence of the model used to predict recovery, choice of production strategies to be used in the process, number of attributes and type of information necessary to obtain reliable results. A discussion of data integration among geology, reservoir engineering and economic analysis also is presented in order to reduce the amount of information necessary and time for the process. Some results are presented to show the advantages of automation and parallel computing to reduce the total time of the procedure where reservoir simulation is necessary for reservoir performance prediction.Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM2004-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782004000200014Journal of the Brazilian Society of Mechanical Sciences and Engineering v.26 n.2 2004reponame:Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)instname:Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)instacron:ABCM10.1590/S1678-58782004000200014info:eu-repo/semantics/openAccessSchiozer,D. J.Ligero,E. L.Santos,J. A. M.eng2004-08-12T00:00:00Zoai:scielo:S1678-58782004000200014Revistahttps://www.scielo.br/j/jbsmse/https://old.scielo.br/oai/scielo-oai.php||abcm@abcm.org.br1806-36911678-5878opendoar:2004-08-12T00:00Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) - Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)false |
dc.title.none.fl_str_mv |
Risk assessment for reservoir development under uncertainty |
title |
Risk assessment for reservoir development under uncertainty |
spellingShingle |
Risk assessment for reservoir development under uncertainty Schiozer,D. J. Petroleum reservoir engineering uncertainty risk |
title_short |
Risk assessment for reservoir development under uncertainty |
title_full |
Risk assessment for reservoir development under uncertainty |
title_fullStr |
Risk assessment for reservoir development under uncertainty |
title_full_unstemmed |
Risk assessment for reservoir development under uncertainty |
title_sort |
Risk assessment for reservoir development under uncertainty |
author |
Schiozer,D. J. |
author_facet |
Schiozer,D. J. Ligero,E. L. Santos,J. A. M. |
author_role |
author |
author2 |
Ligero,E. L. Santos,J. A. M. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Schiozer,D. J. Ligero,E. L. Santos,J. A. M. |
dc.subject.por.fl_str_mv |
Petroleum reservoir engineering uncertainty risk |
topic |
Petroleum reservoir engineering uncertainty risk |
description |
Decision analysis applied to petroleum field development is always strongly related to risk due to the uncertainties present in the process. Methodologies to quantify the impact of uncertainties are still not well established due to the amount of variables that have to be considered. The complete analysis usually depends on geological, economical and technological uncertainties that have different degrees of impact in the recovery process and may affect the decision process at different levels depending on the problem, reservoir characteristics, recovery mechanism and stage of field development. This paper shows several details of a methodology that can be applied to complex and simple reservoirs in a reasonable amount of time, discussing especially the influence of the model used to predict recovery, choice of production strategies to be used in the process, number of attributes and type of information necessary to obtain reliable results. A discussion of data integration among geology, reservoir engineering and economic analysis also is presented in order to reduce the amount of information necessary and time for the process. Some results are presented to show the advantages of automation and parallel computing to reduce the total time of the procedure where reservoir simulation is necessary for reservoir performance prediction. |
publishDate |
2004 |
dc.date.none.fl_str_mv |
2004-06-01 |
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=S1678-58782004000200014 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782004000200014 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1678-58782004000200014 |
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 |
Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM |
dc.source.none.fl_str_mv |
Journal of the Brazilian Society of Mechanical Sciences and Engineering v.26 n.2 2004 reponame:Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) instname:Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM) instacron:ABCM |
instname_str |
Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM) |
instacron_str |
ABCM |
institution |
ABCM |
reponame_str |
Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) |
collection |
Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) |
repository.name.fl_str_mv |
Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) - Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM) |
repository.mail.fl_str_mv |
||abcm@abcm.org.br |
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1754734680138055680 |