Show simple item record

dc.contributor.advisorFisher, W. L. (William Lawrence), 1932-en
dc.creatorChang, Linen
dc.date.accessioned2011-02-22T17:20:33Zen
dc.date.accessioned2011-02-22T17:21:06Zen
dc.date.available2011-02-22T17:20:33Zen
dc.date.available2011-02-22T17:21:06Zen
dc.date.issued2010-12en
dc.date.submittedDecember 2010en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2010-12-2252en
dc.descriptiontexten
dc.description.abstractThe primary controls on subsurface reservoir heterogeneities and fluid flow characteristics are sedimentary facies architecture and petrophysical rock fabric distribution in clastic reservoirs and in carbonate reservoirs, respectively. Facies models are critical and fundamental for summarizing facies and facies architecture in data-rich areas. Facies models also assist in predicting the spatial architectural trend of sedimentary facies in other areas where subsurface information is lacking. The method for transferring geological information from different facies models into digital data and then generating associated numerical models is called facies modeling or geological modeling. Facies modeling is also vital to reservoir simulation and reservoir characterization analysis. By extensively studying and reviewing the relevant research in the published literature, this report identifies and analyzes the best and most detailed geologic data that can be used in facies modeling, and the most current geostatistical and stochastic methods applicable to facies modeling. Through intensive study of recent literature, the author (1) summarizes the basic concepts and their applications to facies and facies models, and discusses a variety of numerical modeling methods, including geostatistics and stochastic facies modeling, such as variogram-based geostatistics modeling, object-based stochastic modeling, and multiple-point geostatistics modeling; and (2) recognizes that the most effective way to characterize reservoir is to integrate data from multiple sources, such as well data, outcrop data, modern analogs, and seismic interpretation. Detailed and more accurate parameters using in facies modeling, including grain size, grain type, grain sorting, sedimentary structures, and diagenesis, are gained through this multidisciplinary analysis. The report concludes that facies and facies models are scale dependent, and that attention should be paid to scale-related issues in order to choose appropriate methods and parameters to meet facies modeling requirements.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectFaciesen
dc.subjectFacies modelen
dc.subjectFacies modelingen
dc.subjectModel integrationen
dc.subjectReservoir simulationen
dc.titleIntegration of facies models in reservoir simulationen
dc.date.updated2011-02-22T17:21:06Zen
dc.contributor.committeeMemberSteel, Ronalden
dc.contributor.committeeMemberTorres-verdin, Carlosen
dc.description.departmentGeological Sciencesen
dc.type.genrethesisen
thesis.degree.departmentGeological Sciencesen
thesis.degree.disciplineGeological Sciencesen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Artsen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record