Automatic fault surface detection by using 3D Hough transform

Abstract

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2014Automatic fault surface detection by using 3D Hough transformAuthors: Zhen Wang*Ghassan AlRegibZhen Wang*Georgia Institute of TechnologySearch for more papers by this author and Ghassan AlRegibGeorgia Institute of TechnologySearch for more papers by this authorhttps://doi.org/10.1190/segam2014-1590.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Detection of faults plays an important role in the characterization of reservoir regions. In this paper, we propose an automatic fault surface detection method using 3D Hough transform to improve the interpretation efficiency. We first highlight the likely fault points in seismic data by thresholding the corresponding discontinuity volumes. Then, we apply 3D Hough transform to detect the likely fault planes in seismic volumes. After filtering out the noisy planes, we apply the weighted plane fitting method to extract the smooth fault surfaces from the remaining fault planes. Experimental results show that the proposed method has the capability of detecting fault surfaces in real seismic data with high accuracy and fewer human interventions. Keywords: 3D, faults, interpretation, seismicPermalink: https://doi.org/10.1190/segam2014-1590.1FiguresReferencesRelatedDetailsCited ByFault surface extraction from a global perspectiveCheng Zhou, Ruoshui Zhou, Xianglin Zhan, Hanpeng Cai, Xingmiao Yao, and Guangmin Hu13 July 2022 | GEOPHYSICS, Vol. 87, No. 5Seismic horizon extraction with dynamic programmingShangsheng Yan and Xinming Wu11 February 2021 | GEOPHYSICS, Vol. 86, No. 2Pseudo-probabilistic identification of fracture network in seismic clouds driven by source parameters5 October 2020 | Geophysical Journal International, Vol. 223, No. 3Improving seismic fault detection by super-attribute-based classificationHaibin Di, Mohammod Amir Shafiq, Zhen Wang, and Ghassan AlRegib7 August 2019 | Interpretation, Vol. 7, No. 3Semi‐automatic fault/fracture interpretation based on seismic geometry analysis13 March 2019 | Geophysical Prospecting, Vol. 67, No. 5Patch-level MLP classification for improved fault detectionHaibin Di, Muhammad Shafiq, and Ghassan AlRegib27 August 2018Why using CNN for seismic interpretation? An investigationHaibin Di, Zhen Wang, and Ghassan AlRegib27 August 2018Successful leveraging of image processing and machine learning in seismic structural interpretation: A reviewZhen Wang, Haibin Di, Muhammad Amir Shafiq, Yazeed Alaudah, and Ghassan AlRegib6 June 2018 | The Leading Edge, Vol. 37, No. 6Subsurface Structure Analysis Using Computational Interpretation and Learning: A Visual Signal Processing PerspectiveIEEE Signal Processing Magazine, Vol. 35, No. 2Methods to enhance seismic faults and construct fault surfacesComputers & Geosciences, Vol. 107Interactive Fault Extraction in 3-D Seismic Data Using the Hough Transform and Tracking VectorsIEEE Transactions on Computational Imaging, Vol. 3, No. 1Fault enhancement and visualization with 3D log-Gabor filter arrayYingwei Yu1 September 2016Fault detection using color blending and color transformations SEG Technical Program Expanded Abstracts 2014ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2014 Pages: 5183 publication data© 2014 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 05 Aug 2014 CITATION INFORMATION ZhenWang* and GhassanAlRegib, (2014), "Automatic fault surface detection by using 3D Hough transform," SEG Technical Program Expanded Abstracts : 1439-1444. https://doi.org/10.1190/segam2014-1590.1 Plain-Language Summary Keywords3DfaultsinterpretationseismicPDF DownloadLoading ...