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dc.contributor.advisorSrinivasan, Sanjayen
dc.creatorBhowmik, Sayantanen
dc.date.accessioned2012-08-20T15:32:49Zen
dc.date.available2012-08-20T15:32:49Zen
dc.date.issued2012-05en
dc.date.submittedMay 2012en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2012-05-5787en
dc.descriptiontexten
dc.description.abstractDuring the operation of a geological carbon storage project, verifying that the CO₂ plume remains within the permitted zone is of particular interest both to regulators and to operators. However, the cost of many monitoring technologies, such as time-lapse seismic, limits their application. For adequate predictions of plume migration, proper representation of heterogeneous permeability fields is imperative. Previous work has shown that injection data (pressures, rates) from wells might provide a means of characterizing complex permeability fields in saline aquifers. Thus, given that injection data are readily available and inexpensive, they might provide an inexpensive alternative for monitoring; combined with a flow model like the one developed in this work, these data could even be used for predicting plume migration. These predictions of plume migration pathways can then be compared to field observations like time-lapse seismic or satellite measurements of surface-deformation, to ensure the containment of the injected CO₂ within the storage area. In this work, two novel methods for creating heterogeneous permeability fields constrained by injection data are demonstrated. The first method is an implementation of a probabilistic history matching algorithm to create models of the aquifer for predicting the movement of the CO₂ plume. The geologic property of interest, for example hydraulic conductivity, is updated conditioned to geological information and injection pressures. The resultant aquifer model which is geologically consistent can be used to reliably predict the movement of the CO₂ plume in the subsurface. The second method is a model selection algorithm that refines an initial suite of subsurface models representing the prior uncertainty to create a posterior set of subsurface models that reflect injection performance consistent with that observed. Such posterior models can be used to represent uncertainty in the future migration of the CO₂ plume. The applicability of both methods is demonstrated using a field data set from central Algeria.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectCO2 sequestrationen
dc.subjectHistory matchingen
dc.subjectModel selectionen
dc.subjectUncertainty estimationen
dc.titlePredicting the migration of CO₂ plume in saline aquifers using probabilistic history matching approachesen
dc.date.updated2012-08-20T15:32:58Zen
dc.identifier.slug2152/ETD-UT-2012-05-5787en
dc.contributor.committeeMemberBryant, Steven L.en
dc.description.departmentPetroleum and Geosystems Engineeringen
dc.type.genrethesisen
thesis.degree.departmentPetroleum and Geosystems Engineeringen
thesis.degree.disciplinePetroleum Engineeringen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Engineeringen


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