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dc.contributor.authorAndersen, Odd
dc.contributor.authorNilsen, Halvor Møll
dc.contributor.authorGasda, Sarah
dc.date.accessioned2017-06-08T13:00:58Z
dc.date.available2017-06-08T13:00:58Z
dc.date.issued2016
dc.identifier.isbn978-94-6282-193-4
dc.identifier.urihttps://hdl.handle.net/1956/15945
dc.descriptionPresented at: ECMOR XV - 15th European conference on the mathematics of oil recovery, Amsterdam, Netherlands, 29 August-1 September 2016eng
dc.description.abstractWhen injecting CO2 or other fluids into a geological formation, pressure plays an important role both as a driver of flow and as a risk factor for mechanical integrity. The full effect of geomechanics on aquifer flow can only be captured using a coupled flow-geomechanics model. In order to solve this computationally expensive system, various strategies have been put forward over the years, with some of the best current methods based on sequential splitting. In this present work, we seek to approximate the full geomechanics effect on flow without the need of coupling with a geomechanics solver during simulation. We do this by means of precomputed pressure response functions. At grid model generation time, a geomechanics solver is used to compute the mechanical response of the aquifer for a set of pressure fields. The relevant information from these responses is then stored in a compact form and embedded with the grid model. We test the accuracy and computational performance of our approach on a simple 2D model and a more complex 3D model, and compare the results with those produced by a fully coupled approach as well as from as simple decoupled method based on Geertsma's uniaxial expansion coefficient.en_US
dc.language.isoengeng
dc.publisherEAGEen_US
dc.relation.ispartof<a href="http://hdl.handle.net/1956/15477" target="blank">Simplified models for numerical simulation of geological CO2 storage</a>en_US
dc.relation.ispartofECMOR XV - 15th European Conference on the Mathematics of Oil Recovery
dc.titleModelling Geomechanical Impact of CO2 Injection Using Precomputed Response Functionsen_US
dc.typeChapter
dc.typePeer reviewed
dc.description.versionpublishedVersionen_US
dc.source.articlenumbercp-494-00022
dc.identifier.doihttps://doi.org/10.3997/2214-4609.201601760
dc.identifier.cristin1388451


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