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dc.contributor.authorMøyner, Olav
dc.contributor.authorKrogstad, Stein
dc.contributor.authorLie, Knut-Andreas
dc.date.accessioned2017-12-20T07:46:18Z
dc.date.available2017-12-20T07:46:18Z
dc.date.created2014-09-26T17:14:03Z
dc.date.issued2014
dc.identifier.citationSPE Journal. 2014, 20 (2), 306-323.nb_NO
dc.identifier.issn1086-055X
dc.identifier.urihttp://hdl.handle.net/11250/2473111
dc.description.abstractFlow diagnostics, as referred to herein, are computational tools derived from controlled numerical flow experiments that yield quantitative information regarding the flow behavior of a reservoir model in settings much simpler than would be encountered in the actual field. In contrast to output from traditional reservoir simulators, flow-diagnostic measures can be obtained within seconds. The methodology can be used to evaluate, rank, and/or compare realizations or strategies, and the computational speed makes it ideal for interactive visualization output. We also consider application of flow diagnostics as proxies in optimization of reservoir-management work flows. In particular, by use of finite-volume discretizations for pressure, time of flight (TOF), and stationary tracers, we efficiently compute general Lorenz coefficients (and variants) that are shown to correlate well with simulated recovery. For efficient optimization, we develop an adjoint code for gradient computations of the considered flow-diagnostic measures. We present several numerical examples, including optimization of rates, well placements, and drilling sequences for two- and three-phase synthetic and real field models. Overall, optimizing the diagnostic measures implies substantial improvement in simulation-based objectives.nb_NO
dc.language.isoengnb_NO
dc.titleThe application of flow diagnostics for reservoir managementnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionsubmittedVersionnb_NO
dc.subject.nsiVDP::Anvendt matematikk: 413nb_NO
dc.subject.nsiVDP::Applied mathematics: 413nb_NO
dc.source.pagenumber306-323nb_NO
dc.source.volume20nb_NO
dc.source.journalSPE Journalnb_NO
dc.source.issue2nb_NO
dc.identifier.doi10.2118/171557-PA
dc.identifier.cristin1158751
dc.relation.projectNorges forskningsråd: 215665nb_NO
dc.relation.projectAndre: Chevron Energy Technology Companynb_NO
dc.relation.projectNorges teknisk-naturvitenskapelige universitet: Center for Integrated Operations in the Petroleum Industrynb_NO
cristin.unitcode7401,90,11,0
cristin.unitnameAnvendt matematikk
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode2


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