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dc.contributor.authorNilsen, Halvor Møll
dc.contributor.authorLie, Knut-Andreas
dc.contributor.authorAndersen, Odd
dc.date.accessioned2016-11-04T09:15:31Z
dc.date.accessioned2016-11-15T12:24:27Z
dc.date.available2016-11-04T09:15:31Z
dc.date.available2016-11-15T12:24:27Z
dc.date.issued2015
dc.identifier.citationComputational Geosciences 2015, Published ahead of printnb_NO
dc.identifier.issn1573-1499
dc.identifier.urihttp://hdl.handle.net/11250/2420981
dc.description-nb_NO
dc.description.abstractModeling geological carbon storage represents a new and substantial challenge for the subsurface geosciences. To increase understanding and make good engineering decisions, containment processes and large-scale storage operations must be simulated in a thousand-year perspective. Large differences in spatial and temporal scales makes it prohibitively expensive to compute the fate of injected CO2 using traditional 3D simulators. Instead, accurate forecast can be computed using simplified models that are adapted to the specific setting of the buoyancy-driven migration of the light fluid phase. This paper presents a family of vertically integrated models for studying the combined large-scale and long-term effects of structural, residual, and solubility trapping of CO2. The models are based on an assumption of a sharp interface separating CO2 and brine and can provide a detailed inventory of the injected CO2 volumes over periods of thousands of years within reasonable computational time. To be compatible with simulation tools used in industry, the models are formulated in a black-oil framework. The models are implemented in MRST-co2lab, which is an open community software developed especially to study and optimize large-scale, long-term geological storage of CO2. The resulting simulators are fully implicit and handle input from standard geomodeling tools.nb_NO
dc.language.isoengnb_NO
dc.titleRobust simulation of sharp-interface models for fast estimation of CO2 trapping capacity in large-scale aquifer systemsnb_NO
dc.typeJournal articlenb_NO
dc.date.updated2016-11-04T09:15:31Z
dc.identifier.doi10.1007/s10596-015-9549-9
dc.identifier.cristin1291693


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