A novel wavelet extraction method from seismic data without well information

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2020A novel wavelet extraction method from seismic data without well informationAuthors: Yi ShenKui BaoMarianne VissingaJie ShenOlga RodinaYi ShenShell International Exploration and ProductionSearch for more papers by this author, Kui BaoShell International Exploration and ProductionSearch for more papers by this author, Marianne VissingaShell International Exploration and ProductionSearch for more papers by this author, Jie ShenShell International Exploration and ProductionSearch for more papers by this author, and Olga RodinaShell International Exploration and ProductionSearch for more papers by this authorhttps://doi.org/10.1190/segam2020-3427201.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractThe common practice to extract a wavelet for seismic quantitative interpretation (e.g., impedance inversion) requires well information. In our study, we proposed to use bi-directional deconvolution to estimate the wavelet directly from seismic data in such a way that well information is no longer a requirement. This method has the following two features. First, this method is not limited to the type of the wavelet phase by decomposing a wavelet into a minimum-phase part and a maximum-phase part. Meanwhile, this method still guarantees a stable inversion. Second, this method uses hybrid norm to preserve the sparseness and spikiness of the earth reflectivity. We have verified this method through a synthetic data test. This test was followed by a demonstration on onshore field data and offshore field data. In these field tests, we benchmarked our results with the wavelet derived from a well tie. The comparison showed a high similarity in the amplitude spectra and phase spectra of the derived wavelets. Furthermore, the offshore example showed that this method is useful for areas where there is no well penetration. The impedance inversion using our estimated wavelet from no-well area is better detuned and has more details, when compared with a conventional well-based quantitative interpretation.Presentation Date: Wednesday, October 14, 2020Session Start Time: 1:50 PMPresentation Time: 2:40 PMLocation: 360DPresentation Type: OralKeywords: deconvolution, signal processing, wavelet, impedance, interpretationPermalink: https://doi.org/10.1190/segam2020-3427201.1FiguresReferencesRelatedDetailsCited byMachine Learning–Based Digital Integration of Geotechnical and Ultrahigh–Frequency Geophysical Data for Offshore Site CharacterizationsJournal of Geotechnical and Geoenvironmental Engineering, Vol. 147, No. 12 SEG Technical Program Expanded Abstracts 2020ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2020 Pages: 3887 publication data© 2020 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 30 Sep 2020 CITATION INFORMATION Yi Shen, Kui Bao, Marianne Vissinga, Jie Shen, and Olga Rodina, (2020), "A novel wavelet extraction method from seismic data without well information," SEG Technical Program Expanded Abstracts : 2241-2245. https://doi.org/10.1190/segam2020-3427201.1 Plain-Language Summary Keywordsdeconvolutionsignal processingwaveletimpedanceinterpretationPDF DownloadLoading ...