PreviousNext No AccessSEG Technical Program Expanded Abstracts 2010Mixed‐phase wavelet extraction based on subspace methodAuthors: Peijie YangXing MuShuhui LiuPeijie YangGeological Scientific Research Institute of Shengli Oilfield, SINOPEC, ChinaSearch for more papers by this author, Xing MuGeological Scientific Research Institute of Shengli Oilfield, SINOPEC, ChinaSearch for more papers by this author, and Shuhui LiuGeological Scientific Research Institute of Shengli Oilfield, SINOPEC, ChinaSearch for more papers by this authorhttps://doi.org/10.1190/1.3513614 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Usually, statistical methods are needed to extract seismic wavelet while there is no well information available. However, statistical wavelets extraction methods are mostly based on high order statistics, which require reflectivities are non‐gauss white noise and its' computation speed is slow. Subspace decomposition mixed‐phase seismic wavelets extraction ignores the assumption, it's based on the orthogonality between a signal and a noise subspaces, and the reflectivities need not be made any assumption; so this method is totally different from high order statistics wavelets extraction. Tests on synthetic and real data show that subspace mixed‐phase wavelet extraction method can provides better wavelet estimation results and the computational complexity is lower, thus very attractive for real application.Permalink: https://doi.org/10.1190/1.3513614FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2010ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2010 Pages: 4453 publication data© 2010 Copyright © 2010 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 21 Oct 2010 CITATION INFORMATION Peijie Yang, Xing Mu, and Shuhui Liu, (2010), "Mixed‐phase wavelet extraction based on subspace method," SEG Technical Program Expanded Abstracts : 3679-3683. https://doi.org/10.1190/1.3513614 Plain-Language Summary PDF DownloadLoading ...
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