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Geostatistical Integration of Geophysical, Well Bore and Outcrop Data for Flow Modeling of a Deltaic Reservoir Analogue

Significant world oil and gas reserves occur in deltaic reservoirs. Characterization of deltaic reservoirs requires understanding sedimentary and diagenetic heterogeneity at the submeter scale in three dimensions. However, deltaic facies architecture is complex and poorly understood. Moreover, precipitation of extensive calcite cement during diagenesis can modify the depositional permeability of sandstone reservoir and affect fluid flow. Heterogeneity contributes to trapping a significant portion of mobile oil in deltaic reservoirs analogous of Cretaceous Frontier Formation, Powder River Basin, Wyoming.
This dissertation focuses on 3D characterization of an ancient deltaic lobe. The Turonian Wall Creek Member in central Wyoming has been selected for the present study, which integrates outcrop digitized image analysis, 2D and 3D interpreted ground penetrating radar surveys, outcrop gamma ray measurements, well logs, permeameter logs and transects, and other data for 3D reservoir characterization and flow modeling. Well log data are used to predict the geological facies using beta-Bayes method and classic multivariate statistic methods, and predictions are compared with the outcrop description. Geostatistical models are constructed for the size, orientation, and shape of the concretions using interpreted GPR, well, and outcrop data. The spatial continuity of concretions is quantified using photomosaic derived variogram analysis.
Relationships among GRP attributes, well data, and outcrop data are investigated, including calcite concretion occurrence and permeability measurements from outcrop. A combination of truncated Gaussian simulation and Bayes rule predicts 3D concretion distributions. Comparisons between 2D flow simulations based on outcrop observations and an ensemble of geostatistical models indicates that the proposed approach can reproduce essential aspects of flow behavior in this system.
Experimental design, analysis of variance, and flow simulations examine the effects of geological variability on breakthrough time, sweep efficiency and upscaled permeability. The proposed geostatistical and statistical methods can improve prediction of flow behavior even if conditioning data are sparse and radar data are noisy. The derived geostatistical models of stratigraphy, facies and diagenesis are appropriate for analogous deltaic reservoirs. Furthermore, the results can guide data acquisition, improve performance prediction, and help to upscale models.

Identiferoai:union.ndltd.org:LSU/oai:etd.lsu.edu:etd-07032005-090208
Date06 July 2005
CreatorsTang, Hong
ContributorsAnuj Gupta, Christopher White, Julius Langlinais, Frank T-C. Tsai, John Wrenn
PublisherLSU
Source SetsLouisiana State University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lsu.edu/docs/available/etd-07032005-090208/
Rightsunrestricted, I hereby certify that, if appropriate, I have obtained and attached herein a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to LSU or its agents the non-exclusive license to archive and make accessible, under the conditions specified below and in appropriate University policies, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.

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