A hybrid joint‐inversion scheme

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2011A hybrid joint‐inversion schemeAuthors: Charlie JingJames J. CarazzoneChris DiCaprioGarrett LeahyAnoop A. MullurRebecca L. SaltzerJan SchmedesVijay P. SinghCharlie JingExxonMobil Upstream Research CompanySearch for more papers by this author, James J. CarazzoneExxonMobil Upstream Research CompanySearch for more papers by this author, Chris DiCaprioExxonMobil Upstream Research CompanySearch for more papers by this author, Garrett LeahyExxonMobil Upstream Research CompanySearch for more papers by this author, Anoop A. MullurExxonMobil Upstream Research CompanySearch for more papers by this author, Rebecca L. SaltzerExxonMobil Upstream Research CompanySearch for more papers by this author, Jan SchmedesExxonMobil Upstream Research CompanySearch for more papers by this author, and Vijay P. SinghExxonMobil Upstream Research CompanySearch for more papers by this authorhttps://doi.org/10.1190/1.3627751 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract As the search for hydrocarbons becomes more challenging, geophysical data of different types beyond seismic reflection are sometimes acquired for exploration. Multiple data types, which are sensitive to different physical properties, can be used to reduce uncertainty in predicting the existence or absence of hydrocarbons. Joint inversion of multiple geophysical data types for subsurface physical properties is an attractive tool for hydrocarbon detection. However, there are challenges in performing the joint inversion of multiple data types simultaneously due to factors such as differences in spatial resolution and sensitivity to different rock properties. In this paper, we describe a hybrid joint inversion method. It inverts low‐resolution data types for rock‐property models on a coarse scale, and these models are subsequently used as model constraints in the inversion of high‐resolution data. This inversion method benefits from the information contained in different data types but with an increased computational efficiency. The methodology and the value of joint inversion for hydrocarbon detection are demonstrated with synthetic data examples.Permalink: https://doi.org/10.1190/1.3627751FiguresReferencesRelatedDetailsCited ByCooperative joint inversion of 3D seismic and magnetotelluric data: With application in a mineral provinceEric M. Takam Takougang, Brett Harris, Anton Kepic, and Cuong V. A. Le26 May 2015 | GEOPHYSICS, Vol. 80, No. 4 SEG Technical Program Expanded Abstracts 2011ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2011 Pages: 4424 Publisher:Society of Exploration Geophysicists HistoryPublished: 08 Aug 2011 CITATION INFORMATION Charlie Jing, James J. Carazzone, Chris DiCaprio, Garrett Leahy, Anoop A. Mullur, Rebecca L. Saltzer, Jan Schmedes, and Vijay P. Singh, (2011), "A hybrid joint‐inversion scheme," SEG Technical Program Expanded Abstracts : 2689-2693. https://doi.org/10.1190/1.3627751 Plain-Language Summary PDF DownloadLoading ...