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- W4291743752 abstract "PreviousNext No AccessSecond International Meeting for Applied Geoscience & EnergyGeostatistical reservoir modeling using computational stratigraphy models on non-Cartesian gridsAuthors: Lewis LiTao SunJulio De La ColinaLewis Li Chevron Technical CenterSearch for more papers by this author, Tao Sun Chevron Technical CenterSearch for more papers by this author, and Julio De La Colina Chevron Technical CenterSearch for more papers by this authorhttps://doi.org/10.1190/image2022-3751585.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract We present a new geostatistical methodology of building reservoir models using process-based models as training data. The reservoir models are built in the depositional time-domain (k-layer) which allows for the construction of non-Cartesian grids that can readily capture thin flow baffles and barriers. These fine-scale heterogeneities, while volumetrically insignificant, can have a large impact on fluid flow. We perform flow diagnostics to evaluate and compare models built with our methodology to a set of reservoir models built using conventional techniques. This demonstrates the improved ability of the proposed models to capture fine-scale heterogeneities as well as the significance of their impact on fluid behavior and reservoir predictivity. Keywords: multipoint geostatistics, process-based modeling, computational stratigraphy, flow diagnostics, non-Cartesian griddingPermalink: https://doi.org/10.1190/image2022-3751585.1FiguresReferencesRelatedDetails Second International Meeting for Applied Geoscience & EnergyISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2022 Pages: 3694 publication data© 2022 Published in electronic format with permission by the Society of Exploration Geophysicists and the American Association of Petroleum GeologistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 15 Aug 2022 CITATION INFORMATION Lewis Li, Tao Sun, and Julio De La Colina, (2022), Geostatistical reservoir modeling using computational stratigraphy models on non-Cartesian grids, SEG Technical Program Expanded Abstracts : 1467-1471. https://doi.org/10.1190/image2022-3751585.1 Plain-Language Summary Keywordsmultipoint geostatisticsprocess-based modelingcomputational stratigraphyflow diagnosticsnon-Cartesian griddingPDF DownloadLoading ..." @default.
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- W4291743752 title "Geostatistical reservoir modeling using computational stratigraphy models on non-Cartesian grids" @default.
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