Automatic velocity picking with convolutional neural networks

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2018Automatic velocity picking with convolutional neural networksAuthors: Yue MaXu JiTong W. FeiYi LuoYue MaAramco Research Center – Beijing, Aramco AsiaSearch for more papers by this author, Xu JiEXPEC Advanced Research Center, Saudi AramcoSearch for more papers by this author, Tong W. FeiEXPEC Advanced Research Center, Saudi AramcoSearch for more papers by this author, and Yi LuoEXPEC Advanced Research Center, Saudi AramcoSearch for more papers by this authorhttps://doi.org/10.1190/segam2018-2987088.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractWe developed an automatic velocity picking methodology based on convolutional neural networks (ConvNets). The proposed method formalizes the picking problem into a ConvNet regression model to map the NMO-corrected seismic gather to the velocity error estimates. We also propose a data preprocessing technique to normalize the shallow and deep reflections of a CMP gather into the same moveout shape, which is a key ingredient for successful training. A synthetic example shows the feasibility and effectiveness of the proposed method.Presentation Date: Wednesday, October 17, 2018Start Time: 1:50:00 PMLocation: 204B (Anaheim Convention Center)Presentation Type: OralKeywords: velocity analysis, machine learning, stackingPermalink: https://doi.org/10.1190/segam2018-2987088.1FiguresReferencesRelatedDetailsCited byAutomatic velocity picking with restricted weighted k-means clustering using prior information16 January 2023 | Frontiers in Earth Science, Vol. 10Intelligent velocity picking and uncertainty analysis based on the Gaussian mixture model14 July 2022 | Acta Geophysica, Vol. 70, No. 6Estimation of anisotropic parameters from semblance picking using dynamic programmingHong Liang, Houzhu (James) Zhang, Dongliang Zhang, Hongwei Liu, and Xu Ji15 August 2022An automatic velocity picking method based on object detectionCe Bian, Weifeng Geng, Ping Yang, Pengyuan Sun, Guiren Xue, and Haikun Lin15 August 2022Automatic migration velocity analysis via deep learningChao Ding and Jianwei Ma7 June 2022 | GEOPHYSICS, Vol. 87, No. 4Seismic velocity modeling in the digital transformation era: a review of the role of machine learning28 September 2021 | Journal of Petroleum Exploration and Production Technology, Vol. 12, No. 1BiInNet: Bilateral Inversion Network for Real-Time Velocity AnalysisIEEE Transactions on Geoscience and Remote Sensing, Vol. 60Automatic Velocity Picking Using a Multi-Information Fusion Deep Semantic Segmentation NetworkIEEE Transactions on Geoscience and Remote Sensing, Vol. 60A Velocity Spectrum Picking Method Based on Detection Fine Tuning Depth Recognition TechnologyAutomatic Velocity Analysis Using a Hybrid Regression Approach With Convolutional Neural NetworksIEEE Transactions on Geoscience and Remote Sensing, Vol. 59, No. 5Automatic velocity picking from semblances with a new deep-learning regression strategy: Comparison with a classification approachWenlong Wang, George A. McMechan, Jianwei Ma, and Fei Xie5 February 2021 | GEOPHYSICS, Vol. 86, No. 2Automate seismic velocity model building through machine learningJiangchuan Huang, Jun Cao, Guang Chen, and Yu Zhang30 September 2020Estimating normal moveout velocity using the recurrent neural networkReetam Biswas, Anthony Vassiliou, Rodney Stromberg, and Mrinal K. Sen20 September 2019 | Interpretation, Vol. 7, No. 4Deep learning guiding first-arrival traveltime tomographyZiang Li, Xiaofeng Jia, and Jie Zhang10 August 2019Automatic velocity picking based on deep learningHao Zhang, Peimin Zhu, Yuan Gu, and Xiaozhang Li10 August 2019 SEG Technical Program Expanded Abstracts 2018ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2018 Pages: 5520 publication data© 2018 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 27 Aug 2018 CITATION INFORMATION Yue Ma, Xu Ji, Tong W. Fei, and Yi Luo, (2018), "Automatic velocity picking with convolutional neural networks," SEG Technical Program Expanded Abstracts : 2066-2070. https://doi.org/10.1190/segam2018-2987088.1 Plain-Language Summary Keywordsvelocity analysismachine learningstackingPDF DownloadLoading ...