文章基本信息

标题：Thickness, porosity, and permeability prediction: comparative studies and application of the geostatistical modeling in an Oil field
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作者：Shan Zhao ; Yang Zhou ; Mengyuan Wang 等
期刊名称：Environmental Systems Research
电子版ISSN：2193-2697
出版年度：2014
卷号：3
期号：1
页码：7-1-7-24
DOI：10.1186/2193-2697-3-7
语种：English
出版社：Springer
摘要：AbstractBackgroundIn this study, we applied the geostatistical modeling to analyze an oil field. The reservoir properties, thickness, porosity and permeability, were studied. Data analysis tools, such as histogram, scatter plot, variogram and cross variogram modeling, were employed to capture the interpretable spatial structure and provide the desired input parameters for further estimation. SK (simple kriging), OK (ordinary kriging), Sgism (Sequential Gaussian Simulation), SC (simple cokriging), OC (ordinary cokriging) and MM2 (Markov model 2) methods were applied to estimate reservoir properties. Estimation difference maps were generated to compare the results of each method, providing more straightforward realizations in a visual way.ResultsFor thickness, results indicated that anisotropic variogram could provide better interpretations for the spatial relationships than isotropic variogram. Both SK and OK could provide better estimates. In comparison to the conventional estimation techniques, the simulation method could well reflect the reservoir’s intrinsical characteristics in terms of the associated extreme values. OOIP (Original Oil In Place) was calculated later with the parameters attained before, including thickness and porosity. Estimation difference maps showed that there was no obvious difference in SK vs. OK and SC vs. OC for the study of permeability. However, OC was slightly different from OK, and there were significant discrepancies between the estimates of OC and MM2 at the unsampled locations. In addition, OC estimates were closest to the sample data of permeability with the minimum variance.ConclusionsGeostatistical modeling is an effective way for thickness, porosity, and permeability prediction.
关键词：KeywordsEnGeostatisticsVariogramKrigingThicknessPorosityPermeability