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dc.contributor.authorAllen, Rebecca
dc.contributor.authorNilsen, Halvor Møll
dc.contributor.authorAndersen, Odd
dc.contributor.authorLie, Knut-Andreas
dc.date.accessioned2017-10-26T07:38:36Z
dc.date.available2017-10-26T07:38:36Z
dc.date.created2017-03-04T17:34:57Z
dc.date.issued2017
dc.identifier.citationComputational Geosciences. 2017, pp 20nb_NO
dc.identifier.issn1420-0597
dc.identifier.urihttp://hdl.handle.net/11250/2462252
dc.description.abstractLarge-scale storage of CO2 in saline aquifers is considered an essential technology to mitigate CO2 emissions. Storage potential has mainly been estimated based on volumetrics or detailed simulations for specific injection scenarios. In practice, achievable storage capacity will depend on engineering, economical, and political restrictions and be limited by the length of the injection period, costs associated with potential CO2 leakage, pressure management, etc. We show how achievable storage volumes can be estimated and maximized using adjoint-based optimization and a hierarchy of simulation methods. In particular, vertical equilibrium models provide the simplest possible description of the flow dynamics during the injection and early post-injection period, while percolation type methods provide effective means for forecasting the long-term fate of CO2 during the later migration stages. We investigate the storage volumes that can be achieved for several formations found along the Norwegian Continental Shelf by optimizing well placement and injection rates, and using production wells for pressure management when necessary. Optimal strategies are obtained under various objectives and simple but realistic constraints, namely: penalization of CO2 leakage, minimization of well cost, and restriction of pressure buildup.
dc.language.isoengnb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleOn obtaining optimal well rates and placement for CO2 storagenb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersion
dc.source.pagenumber20nb_NO
dc.source.journalComputational Geosciencesnb_NO
dc.identifier.doi10.1007/s10596-017-9631-6
dc.identifier.cristin1455745
dc.relation.projectNorges forskningsråd: 243729nb_NO
cristin.unitcode7401,90,11,0
cristin.unitnameAnvendt matematikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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