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dc.contributor.authorRamos, Geraldo A. R.
dc.contributor.authorAkanji, Lateef
dc.date.accessioned2018-01-03T09:20:06Z
dc.date.available2018-01-03T09:20:06Z
dc.date.issued2017-12-19
dc.identifier.citationRamos , G A R & Akanji , L 2017 , ' Application of artificial intelligence for technical screening of enhanced oil recovery methods ' Journal of Oil, Gas and Petrochemical Sciences , vol. 1 , no. 1 , 00002 , pp. 1-12 .en
dc.identifier.otherPURE: 113773072
dc.identifier.otherPURE UUID: bd27c6f4-4bd6-4217-bf6e-01d6286804f2
dc.identifier.urihttp://hdl.handle.net/2164/9846
dc.identifier.urihttp://ologyjournals.com/jogps/volume_issues?issueId=7&volumeId=5en
dc.descriptionAcknowledgment This study is sponsored by the Angolan National Oil Company (Sonangol EP) and the authors are grateful for their support and the permission to use data and publish this manuscript.en
dc.format.extent12en
dc.language.isoeng
dc.relation.ispartofJournal of Oil, Gas and Petrochemical Sciencesen
dc.rightsCopyright© 2017 Ramos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. https://creativecommons.org/licenses/by-sa/4.0/legalcodeen
dc.subjectEnhanced Oil Recovery (EOR)en
dc.subjectneuro-fuzzyen
dc.subjectartificial intelligenceen
dc.subjectreservoir screeningen
dc.subjectneural networken
dc.subjectTA Engineering (General). Civil engineering (General)en
dc.subject.lccTAen
dc.titleApplication of artificial intelligence for technical screening of enhanced oil recovery methodsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen, Engineeringen
dc.contributor.institutionUniversity of Aberdeen, Aberdeen Institute of Energyen
dc.contributor.institutionUniversity of Aberdeen, Engineeringen
dc.description.statusPeer revieweden
dc.description.versionPublisher PDFen


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