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dc.contributor.authorBellout, Mathias Rodrigez
dc.contributor.authorCiaurri, David Echeverria
dc.contributor.authorDurlofsky, Louis J.
dc.contributor.authorFoss, Bjarne Anton
dc.contributor.authorKleppe, Jon
dc.date.accessioned2019-08-07T13:32:01Z
dc.date.available2019-08-07T13:32:01Z
dc.date.created2011-11-09T19:34:25Z
dc.date.issued2012
dc.identifier.citationComputational Geosciences. 2012, 16 (4), 1061-1079.nb_NO
dc.identifier.issn1420-0597
dc.identifier.urihttp://hdl.handle.net/11250/2607485
dc.description.abstractWell placement and control optimization in oil field development are commonly performed in a sequential manner. In this work, we propose a joint approach that embeds well control optimization within the search for optimum well placement configurations. We solve for well placement using derivative-free methods based on pattern search. Control optimization is solved by sequential quadratic programming using gradients efficiently computed through adjoints. Joint optimization yields a significant increase, of up to 20% in net present value, when compared to reasonable sequential approaches. The joint approach does, however, require about an order of magnitude increase in the number of objective function evaluations compared to sequential procedures. This increase is somewhat mitigated by the parallel implementation of some of the pattern-search algorithms used in this work. Two pattern-search algorithms using eight and 20 computing cores yield speedup factors of 4.1 and 6.4, respectively. A third pattern-search procedure based on a serial evaluation of the objective function is less efficient in terms of clock time, but the optimized cost function value obtained with this scheme is marginally better.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringer Verlagnb_NO
dc.titleJoint Optimization of Oil Well Placement and Controlsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber1061-1079nb_NO
dc.source.volume16nb_NO
dc.source.journalComputational Geosciencesnb_NO
dc.source.issue4nb_NO
dc.identifier.doi10.1007/s10596-012-9303-5
dc.identifier.cristin851671
dc.description.localcodeThis is a post-peer-review, pre-copyedit version of an article published in [Computational Geosciences]. The final authenticated version is available online at: https://doi.org/10.1007/s10596-012-9303-5nb_NO
cristin.unitcode194,64,90,0
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for geovitenskap og petroleum
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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