Probabilistic framework-based history matching algorithm utilizing sub-domain delineation and software 'Pro-HMS'

dc.contributor.advisorBryant, Steven L.
dc.contributor.advisorSrinivasan, Sanjay
dc.creatorKim, Yonghwee, 1979-
dc.date.accessioned2017-04-05T21:12:54Z
dc.date.available2017-04-05T21:12:54Z
dc.date.issued2007-12
dc.description.abstractThe key idea presented in this thesis is the perturbation of the probability distribution describing the uncertainty in the permeability value within sub-domains of the reservoir using the dynamic information. Probability deformation parameters are defined and optimally established to minimize the deviation of the predicted production response from the observed or measured response. To implement the perturbation method in a parallel computational environment, sub-domains have to be established such that they are the most influential regions and least correlated. In that case the perturbations for establishing the deformation parameters can be done independently in the sub-domains. In contrast to current history matching algorithms that incur significant computational cost in optimizing permeability for each gridblock in the simulation model, our approach reduces the optimizing period by employing innovative method such as sub-domain delineation using principal component analysis (PCA) and a reduced parameter set in the form of deformation parameters that have to be optimized. Once the domains are delineated, a fully probabilistic approach to perturb permeability within the delineated zones is implemented. With this method the information inferred from dynamic data is merged with the prior geologic information. The described process of history matching is effective; however, it can be cumbersome because it combines aspects of stochastic reservoir modeling, flow simulation and iterative optimization. To speed up and enhance the efficiency of history matching process, and to render a streamlined process, an integrated software package Pro-HMS (Probabilistic History Matching Software) was developed. Various synthetic and real field data sets were processed with Pro-HMS, and they show reliable predictions for future reservoir performance.en_US
dc.description.departmentPetroleum and Geosystems Engineeringen_US
dc.format.mediumelectronicen_US
dc.identifierdoi:10.15781/T2SQ8QP3K
dc.identifier.urihttp://hdl.handle.net/2152/46342
dc.language.isoengen_US
dc.relation.ispartofUT Electronic Theses and Dissertationsen_US
dc.rightsCopyright © is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works.en_US
dc.rights.restrictionRestricteden_US
dc.subjectPro-HMS (Probabilistic History Matching Software)en_US
dc.subjectPerturbation of probability distributionen_US
dc.subjectPermeability valueen_US
dc.titleProbabilistic framework-based history matching algorithm utilizing sub-domain delineation and software 'Pro-HMS'en_US
dc.typeThesisen_US
dc.type.genreThesisen_US
thesis.degree.departmentPetroleum and Geosystems Engineeringen_US
thesis.degree.disciplinePetroleum and Geosystems Engineeringen_US
thesis.degree.grantorUniversity of Texas at Austinen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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