Multiples attenuation using trace randomization and empirical mode decomposition

Seg Technical Program Expanded Abstracts(2016)

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PreviousNext No AccessSEG Technical Program Expanded Abstracts 2016Multiples attenuation using trace randomization and empirical mode decompositionAuthors: Wei ChenYangkang ChenJianyong XieShaohuan ZuYizhuo ZhangWei ChenYangtze UniversitySearch for more papers by this author, Yangkang ChenUniversity of Texas–AustinSearch for more papers by this author, Jianyong XieChina University of Petroleum–BeijingSearch for more papers by this author, Shaohuan ZuChina University of Petroleum–BeijingSearch for more papers by this author, and Yizhuo ZhangCNOOC Research InstituteSearch for more papers by this authorhttps://doi.org/10.1190/segam2016-13771915.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract We propose a new approach for removing multiples based on trace randomization and empirical mode decomposition (EMD). We first flatten the primary reflections in common CMP gather using the picked NMO velocities that correspond to the primaries and then randomly permutate all the traces. Next, we removed the spatially distributed random spikes that correspond to the multiples using the EMD based smoothing approach that is implemented in the f − x domain. The trace randomization approach can make the spatially coherent multiples random along the space direction and can decrease the coherency of near-offset multiples. The EMD based smoothing method is superior to median filter and prediction error filter in that it can help preserve the flattened signals better, without the need of exact flattening, and can preserve the amplitude variation much better. In addition, EMD is a fully adaptive algorithm and the parameterization for EMD based smoothing can be very convenient. Presentation Date: Monday, October 17, 2016 Start Time: 2:15:00 PM Location: 142 Presentation Type: ORAL Keywords: internal multiples, signal processingPermalink: https://doi.org/10.1190/segam2016-13771915.1FiguresReferencesRelatedDetailsCited byPreserving signal during random noise attenuation through migration enhancement and local orthogonalizationChao Li and Jinhai Zhang1 August 2022 | GEOPHYSICS, Vol. 87, No. 5A Robust Random Noise Suppression Method for Seismic Data Using Sparse Low-Rank Estimation in the Time-Frequency DomainIEEE Access, Vol. 8Least-Squares Gaussian Beam Transform for Seismic Noise AttenuationIEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 11Dictionary learning based on dip patch selection training for random noise attenuationShaohuan Zu, Hui Zhou, Rushan Wu, Maocai Jiang, and Yangkang Chen12 March 2019 | GEOPHYSICS, Vol. 84, No. 3 SEG Technical Program Expanded Abstracts 2016ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2016 Pages: 5654 publication data© 2016 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 01 Sep 2016 CITATION INFORMATION Wei Chen, Yangkang Chen, Jianyong Xie, Shaohuan Zu, and Yizhuo Zhang, (2016), "Multiples attenuation using trace randomization and empirical mode decomposition," SEG Technical Program Expanded Abstracts : 4498-4502. https://doi.org/10.1190/segam2016-13771915.1 Plain-Language Summary Keywordsinternal multiplessignal processingPDF DownloadLoading ...
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trace randomization,mode
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