Nonparallelism attributes and data adaptive Kuwahara image processing

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2019Nonparallelism attributes and data adaptive Kuwahara image processingAuthors: Jie QiKurt MarfurtJie QiThe University of OklahomaSearch for more papers by this author and Kurt MarfurtThe University of OklahomaSearch for more papers by this authorhttps://doi.org/10.1190/segam2019-3216022.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractTo map the properties of seismic facies, we introduce 3D nonparallelism attributes that highlight lateral variation of parallelism of reflectors and their energy. The nonparallelism attributes provide quantitative measures of reflector dips by extracting statistical components of the 3D seismic amplitude volume. Many seismic attributes computed by a fixed window, exhibit a "salt and pepper" classification, which is more often seen on karst collapse features, salt dome, and mass transport complex facies. In our workflow, we also propose a 3D structure-oriented adaptive Kuwahara filtering technique to precondition seismic attributes for subsequent machine learning classification. The new adaptive Kuwahara filtering method is more efficient than the original 3D Kuwahara filtering to increase facies discrimination of seismic attributes. We validate the statistic measure of reflector dips and statistic measure of seismic spectrum to map karst collapse facies.Presentation Date: Tuesday, September 17, 2019Session Start Time: 8:30 AMPresentation Time: 8:30 AMLocation: 221BPresentation Type: OralKeywords: seismic attributes, machine learning, carbonatePermalink: https://doi.org/10.1190/segam2019-3216022.1FiguresReferencesRelatedDetailsCited byQuantifying the sensitivity of seismic facies classification to seismic attribute selection: An explainable machine-learning studyDavid Lubo-Robles, Deepak Devegowda, Vikram Jayaram, Heather Bedle, Kurt J. Marfurt, and Matthew J. Pranter19 May 2022 | Interpretation, Vol. 10, No. 3Study on the parameterization response of probabilistic neural networks for seismic facies classification in the Gulf of MexicoDiana Salazar Florez and Heather Bedle27 October 2021 | Interpretation, Vol. 10, No. 1Exhaustive probabilistic neural network for attribute selection and supervised seismic facies classificationDavid Lubo-Robles, Thang Ha, Sivaramakrishnan Lakshmivarahan, Kurt J. Marfurt, and Matthew J. Pranter7 April 2021 | Interpretation, Vol. 9, No. 2 SEG Technical Program Expanded Abstracts 2019ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2019 Pages: 5407 publication data© 2019 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 10 Aug 2019 CITATION INFORMATION Jie Qi and Kurt Marfurt, (2019), "Nonparallelism attributes and data adaptive Kuwahara image processing," SEG Technical Program Expanded Abstracts : 1858-1862. https://doi.org/10.1190/segam2019-3216022.1 Plain-Language Summary Keywordsseismic attributesmachine learningcarbonatePDF DownloadLoading ...