GeoMind: an Intelligent Earth Model Building Tool

PreviousNext No AccessSecond International Meeting for Applied Geoscience & EnergyGeoMind: An intelligent earth model building toolAuthors: Saleh Al SalehEwenet GashawbezaMustafa MarzooqHussam BanajaHusain Al ShakhsJianwu JiaoSaleh Al SalehSaudi AramcoSearch for more papers by this author, Ewenet GashawbezaSaudi AramcoSearch for more papers by this author, Mustafa MarzooqSaudi AramcoSearch for more papers by this author, Hussam BanajaSaudi AramcoSearch for more papers by this author, Husain Al ShakhsSaudi AramcoSearch for more papers by this author, and Jianwu JiaoSaudi AramcoSearch for more papers by this authorhttps://doi.org/10.1190/image2022-3747928.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractSeeing the geology of the subsurface with accuracy and resolution remains a big challenge for seismic imaging. We present the GeoMind, an approach that can predict velocity models directly from the raw seismic data. Geologists use their prior information about an area, wells, and outcrops, to build high-resolution 3D geological models. A deep learning algorithm then generates scenarios nonstop of such models. We use an elastic modeling program to simulate the seismic response of each model. This continuous process keeps enhancing the prediction accuracy of GeoMind utilizing Dammam-7, one of the top ten supercomputers in the world. Applications of this method on synthetic and real data show a promising approach to obtain subsurface information.Keywords: deep learning, geological modeling, seismic simulation, model predictions, supercomputingPermalink: https://doi.org/10.1190/image2022-3747928.1FiguresReferencesRelatedDetails 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 Saleh Al Saleh, Ewenet Gashawbeza, Mustafa Marzooq, Hussam Banaja, Husain Al Shakhs, and Jianwu Jiao, (2022), "GeoMind: An intelligent earth model building tool," SEG Technical Program Expanded Abstracts : 2368-2371. https://doi.org/10.1190/image2022-3747928.1 Plain-Language Summary Keywordsdeep learninggeological modelingseismic simulationmodel predictionssupercomputingPDF DownloadLoading ...