Experts' opinion-based Bayesian Inference for the Coverage Factor in BOP Reliability

The blowout preventer is an important system for safety assurance in well drilling operations. Therefore, the efficient management of its reliability is an essential issue for risk prevention. In the present paper one considers a dynamic Bayesian network for reliability modeling, approaching correct...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Revista IEEE América Latina 2020-12, Vol.18 (12), p.2029-2036
Hauptverfasser: de Almada Garcia, Pauli Adriano, de Carvalho Duim, Fernanda Abizethe, da Cruz Saldanha, Pedro Luiz, Couto Jacinto, Carlos Magno, Alves Lima, Gilson Brito
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 2036
container_issue 12
container_start_page 2029
container_title Revista IEEE América Latina
container_volume 18
creator de Almada Garcia, Pauli Adriano
de Carvalho Duim, Fernanda Abizethe
da Cruz Saldanha, Pedro Luiz
Couto Jacinto, Carlos Magno
Alves Lima, Gilson Brito
description The blowout preventer is an important system for safety assurance in well drilling operations. Therefore, the efficient management of its reliability is an essential issue for risk prevention. In the present paper one considers a dynamic Bayesian network for reliability modeling, approaching corrective maintenance and an imperfect coverage factor, combining with a hierarchical Bayesian inference. Traditionally, the coverage factor in this kind of analysis for well safety is based on belief values. Considering that, we will approach it through a Bayesian analysis for the experts’ opinion. Thus, the present paper presents a fully Bayesian approach for blowout preventer reliability analysis, combining experts’ opinions in a dynamic Bayesian net modeling. In the end, is possible to compare results with and without imperfect coverage factor, and with belief values. The obtained results for a hypothetical case show the importance of considering the estimates’ uncertainties in the context of reliability management of drilling operations.
doi_str_mv 10.1109/TLA.2020.9400429
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_journals_2513390471</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9400429</ieee_id><sourcerecordid>2513390471</sourcerecordid><originalsourceid>FETCH-LOGICAL-c174t-c9b5b45b6f7063f37fdd28adb940b11f81b6e17aa530754c45ea39de266335143</originalsourceid><addsrcrecordid>eNpNkM1LAzEQxYMoWKt3wUvAg6et-dzdHNvSqlCoSD2HZHeiKTW7Jlux_71bWsXTDDPvzWN-CF1TMqKUqPvVYjxihJGREoQIpk7QgEpRZkQpdvqvP0cXKa0J4WVe8gFazb5biF26w03rg29CZk2CGk_MDpI3AT8FBxFCBdg1EXfvgKfNF0TzBnhuqq6f-YAny2f8AhtvrN_4bneJzpzZJLg61iF6nc9W08dssXx4mo4XWUUL0WWVstIKaXNXkJw7Xri6ZqWpbf-CpdSV1OZAC2MkJ4UUlZBguKqB5Tnnkgo-RLeHu21sPreQOr1utjH0kZpJyrkioqC9ihxUVWxSiuB0G_2HiTtNid6z0z07vWenj-x6y83B4gHgT_67_QFkpGkz</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2513390471</pqid></control><display><type>article</type><title>Experts' opinion-based Bayesian Inference for the Coverage Factor in BOP Reliability</title><source>IEEE Electronic Library (IEL)</source><creator>de Almada Garcia, Pauli Adriano ; de Carvalho Duim, Fernanda Abizethe ; da Cruz Saldanha, Pedro Luiz ; Couto Jacinto, Carlos Magno ; Alves Lima, Gilson Brito</creator><creatorcontrib>de Almada Garcia, Pauli Adriano ; de Carvalho Duim, Fernanda Abizethe ; da Cruz Saldanha, Pedro Luiz ; Couto Jacinto, Carlos Magno ; Alves Lima, Gilson Brito</creatorcontrib><description>The blowout preventer is an important system for safety assurance in well drilling operations. Therefore, the efficient management of its reliability is an essential issue for risk prevention. In the present paper one considers a dynamic Bayesian network for reliability modeling, approaching corrective maintenance and an imperfect coverage factor, combining with a hierarchical Bayesian inference. Traditionally, the coverage factor in this kind of analysis for well safety is based on belief values. Considering that, we will approach it through a Bayesian analysis for the experts’ opinion. Thus, the present paper presents a fully Bayesian approach for blowout preventer reliability analysis, combining experts’ opinions in a dynamic Bayesian net modeling. In the end, is possible to compare results with and without imperfect coverage factor, and with belief values. The obtained results for a hypothetical case show the importance of considering the estimates’ uncertainties in the context of reliability management of drilling operations.</description><identifier>ISSN: 1548-0992</identifier><identifier>EISSN: 1548-0992</identifier><identifier>DOI: 10.1109/TLA.2020.9400429</identifier><language>eng</language><publisher>Los Alamitos: IEEE</publisher><subject>Bayes methods ; Bayesian analysis ; Blowout preventer reliability ; Coverage factor ; Expert´s Opinion ; IEEE transactions ; Markov processes ; Model testing ; Modelling ; Network reliability ; Reliability ; Reliability analysis ; Reliability aspects ; Safety ; Statistical inference ; Tornadoes ; Uncertainty ; Well drilling</subject><ispartof>Revista IEEE América Latina, 2020-12, Vol.18 (12), p.2029-2036</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0001-7617-0960 ; 0000-0002-7897-5217 ; 0000-0002-4672-1431 ; 0000-0002-3934-4332 ; 0000-0001-6741-2403</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9400429$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9400429$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>de Almada Garcia, Pauli Adriano</creatorcontrib><creatorcontrib>de Carvalho Duim, Fernanda Abizethe</creatorcontrib><creatorcontrib>da Cruz Saldanha, Pedro Luiz</creatorcontrib><creatorcontrib>Couto Jacinto, Carlos Magno</creatorcontrib><creatorcontrib>Alves Lima, Gilson Brito</creatorcontrib><title>Experts' opinion-based Bayesian Inference for the Coverage Factor in BOP Reliability</title><title>Revista IEEE América Latina</title><addtitle>T-LA</addtitle><description>The blowout preventer is an important system for safety assurance in well drilling operations. Therefore, the efficient management of its reliability is an essential issue for risk prevention. In the present paper one considers a dynamic Bayesian network for reliability modeling, approaching corrective maintenance and an imperfect coverage factor, combining with a hierarchical Bayesian inference. Traditionally, the coverage factor in this kind of analysis for well safety is based on belief values. Considering that, we will approach it through a Bayesian analysis for the experts’ opinion. Thus, the present paper presents a fully Bayesian approach for blowout preventer reliability analysis, combining experts’ opinions in a dynamic Bayesian net modeling. In the end, is possible to compare results with and without imperfect coverage factor, and with belief values. The obtained results for a hypothetical case show the importance of considering the estimates’ uncertainties in the context of reliability management of drilling operations.</description><subject>Bayes methods</subject><subject>Bayesian analysis</subject><subject>Blowout preventer reliability</subject><subject>Coverage factor</subject><subject>Expert´s Opinion</subject><subject>IEEE transactions</subject><subject>Markov processes</subject><subject>Model testing</subject><subject>Modelling</subject><subject>Network reliability</subject><subject>Reliability</subject><subject>Reliability analysis</subject><subject>Reliability aspects</subject><subject>Safety</subject><subject>Statistical inference</subject><subject>Tornadoes</subject><subject>Uncertainty</subject><subject>Well drilling</subject><issn>1548-0992</issn><issn>1548-0992</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkM1LAzEQxYMoWKt3wUvAg6et-dzdHNvSqlCoSD2HZHeiKTW7Jlux_71bWsXTDDPvzWN-CF1TMqKUqPvVYjxihJGREoQIpk7QgEpRZkQpdvqvP0cXKa0J4WVe8gFazb5biF26w03rg29CZk2CGk_MDpI3AT8FBxFCBdg1EXfvgKfNF0TzBnhuqq6f-YAny2f8AhtvrN_4bneJzpzZJLg61iF6nc9W08dssXx4mo4XWUUL0WWVstIKaXNXkJw7Xri6ZqWpbf-CpdSV1OZAC2MkJ4UUlZBguKqB5Tnnkgo-RLeHu21sPreQOr1utjH0kZpJyrkioqC9ihxUVWxSiuB0G_2HiTtNid6z0z07vWenj-x6y83B4gHgT_67_QFkpGkz</recordid><startdate>20201201</startdate><enddate>20201201</enddate><creator>de Almada Garcia, Pauli Adriano</creator><creator>de Carvalho Duim, Fernanda Abizethe</creator><creator>da Cruz Saldanha, Pedro Luiz</creator><creator>Couto Jacinto, Carlos Magno</creator><creator>Alves Lima, Gilson Brito</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-7617-0960</orcidid><orcidid>https://orcid.org/0000-0002-7897-5217</orcidid><orcidid>https://orcid.org/0000-0002-4672-1431</orcidid><orcidid>https://orcid.org/0000-0002-3934-4332</orcidid><orcidid>https://orcid.org/0000-0001-6741-2403</orcidid></search><sort><creationdate>20201201</creationdate><title>Experts' opinion-based Bayesian Inference for the Coverage Factor in BOP Reliability</title><author>de Almada Garcia, Pauli Adriano ; de Carvalho Duim, Fernanda Abizethe ; da Cruz Saldanha, Pedro Luiz ; Couto Jacinto, Carlos Magno ; Alves Lima, Gilson Brito</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c174t-c9b5b45b6f7063f37fdd28adb940b11f81b6e17aa530754c45ea39de266335143</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Bayes methods</topic><topic>Bayesian analysis</topic><topic>Blowout preventer reliability</topic><topic>Coverage factor</topic><topic>Expert´s Opinion</topic><topic>IEEE transactions</topic><topic>Markov processes</topic><topic>Model testing</topic><topic>Modelling</topic><topic>Network reliability</topic><topic>Reliability</topic><topic>Reliability analysis</topic><topic>Reliability aspects</topic><topic>Safety</topic><topic>Statistical inference</topic><topic>Tornadoes</topic><topic>Uncertainty</topic><topic>Well drilling</topic><toplevel>online_resources</toplevel><creatorcontrib>de Almada Garcia, Pauli Adriano</creatorcontrib><creatorcontrib>de Carvalho Duim, Fernanda Abizethe</creatorcontrib><creatorcontrib>da Cruz Saldanha, Pedro Luiz</creatorcontrib><creatorcontrib>Couto Jacinto, Carlos Magno</creatorcontrib><creatorcontrib>Alves Lima, Gilson Brito</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Revista IEEE América Latina</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>de Almada Garcia, Pauli Adriano</au><au>de Carvalho Duim, Fernanda Abizethe</au><au>da Cruz Saldanha, Pedro Luiz</au><au>Couto Jacinto, Carlos Magno</au><au>Alves Lima, Gilson Brito</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Experts' opinion-based Bayesian Inference for the Coverage Factor in BOP Reliability</atitle><jtitle>Revista IEEE América Latina</jtitle><stitle>T-LA</stitle><date>2020-12-01</date><risdate>2020</risdate><volume>18</volume><issue>12</issue><spage>2029</spage><epage>2036</epage><pages>2029-2036</pages><issn>1548-0992</issn><eissn>1548-0992</eissn><abstract>The blowout preventer is an important system for safety assurance in well drilling operations. Therefore, the efficient management of its reliability is an essential issue for risk prevention. In the present paper one considers a dynamic Bayesian network for reliability modeling, approaching corrective maintenance and an imperfect coverage factor, combining with a hierarchical Bayesian inference. Traditionally, the coverage factor in this kind of analysis for well safety is based on belief values. Considering that, we will approach it through a Bayesian analysis for the experts’ opinion. Thus, the present paper presents a fully Bayesian approach for blowout preventer reliability analysis, combining experts’ opinions in a dynamic Bayesian net modeling. In the end, is possible to compare results with and without imperfect coverage factor, and with belief values. The obtained results for a hypothetical case show the importance of considering the estimates’ uncertainties in the context of reliability management of drilling operations.</abstract><cop>Los Alamitos</cop><pub>IEEE</pub><doi>10.1109/TLA.2020.9400429</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-7617-0960</orcidid><orcidid>https://orcid.org/0000-0002-7897-5217</orcidid><orcidid>https://orcid.org/0000-0002-4672-1431</orcidid><orcidid>https://orcid.org/0000-0002-3934-4332</orcidid><orcidid>https://orcid.org/0000-0001-6741-2403</orcidid></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1548-0992
ispartof Revista IEEE América Latina, 2020-12, Vol.18 (12), p.2029-2036
issn 1548-0992
1548-0992
language eng
recordid cdi_proquest_journals_2513390471
source IEEE Electronic Library (IEL)
subjects Bayes methods
Bayesian analysis
Blowout preventer reliability
Coverage factor
Expert´s Opinion
IEEE transactions
Markov processes
Model testing
Modelling
Network reliability
Reliability
Reliability analysis
Reliability aspects
Safety
Statistical inference
Tornadoes
Uncertainty
Well drilling
title Experts' opinion-based Bayesian Inference for the Coverage Factor in BOP Reliability
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T14%3A52%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Experts'%20opinion-based%20Bayesian%20Inference%20for%20the%20Coverage%20Factor%20in%20BOP%20Reliability&rft.jtitle=Revista%20IEEE%20Am%C3%A9rica%20Latina&rft.au=de%20Almada%20Garcia,%20Pauli%20Adriano&rft.date=2020-12-01&rft.volume=18&rft.issue=12&rft.spage=2029&rft.epage=2036&rft.pages=2029-2036&rft.issn=1548-0992&rft.eissn=1548-0992&rft_id=info:doi/10.1109/TLA.2020.9400429&rft_dat=%3Cproquest_RIE%3E2513390471%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2513390471&rft_id=info:pmid/&rft_ieee_id=9400429&rfr_iscdi=true