Abstract
PreviousNext No AccessSEG Technical Program Expanded Abstracts 20072D stationary‐wavelet transform‐based acquisition footprint suppressionAuthors: Milos CvetkovicScott FalconerKurt J. MarfurtSergio Chávez‐PérezMilos CvetkovicUniversity of HoustonSearch for more papers by this author, Scott FalconerUniversity of HoustonSearch for more papers by this author, Kurt J. MarfurtUniversity of HoustonSearch for more papers by this author, and Sergio Chávez‐PérezInstituto Mexicano del PetróleoSearch for more papers by this authorhttps://doi.org/10.1190/1.2793005 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Acquisition of seismic data over a large 3D survey acquired in Mexico is constrained by both cultural and ecological limitations, resulting in strong acquisition footprint that contaminates the target turbidite reservoir of interest. Due to the acquisition obstacles, the source and receiver grid is quite irregular, such that we cannot suppress acquisition footprint through simple kx‐ky filtering of time slices. In this survey, the most vexing components of acquisition footprint are due to leakage of backscattered ground roll into the migration‐stack and migration artifacts. 2D Wavelet Transforms provide a spatially varying filter that better adapts to the irregular acquisition geometry. We find that 2D Stationary Wavelet Transform (2D SWT) based filters applied to seismic time slices allow us to suppress both acquisition footprint and random noise., while preserving geologic discontinuities of interest. We decompose each seismic time slice into five levels of wavelet components that represent progressively coarser details. In the shallow section, acquisition footprint is strong and geologic structure is weak. We therefore examine successive levels (or panels) to determine where the acquisition footprint lies. Once identified, we suppress these components in the data reconstruction. We find that 2D SWT filtering on time slices allows us to suppress backscattered ground roll, as well as migration artifacts that leak through the seismic processing. We evaluate the efficacy of this processing through the use of geometric attribute imaging of the turbidite system.Permalink: https://doi.org/10.1190/1.2793005FiguresReferencesRelatedDetailsCited ByStatistics-Guided Residual Dictionary Learning for Footprint Noise RemovalIEEE Transactions on Geoscience and Remote Sensing, Vol. 60Target-oriented model-based seismic footprint analysis and mitigationC. Payson Todd, James Simmons, and Ali Tura26 June 2020 | Interpretation, Vol. 8, No. 4Acquisition footprint suppression of towed streamer 4D seismic dataZou Zhen*, Cao Sheng, Zhang Libin, He Weisheng, and Ling Yun19 August 2015Preconditioning seismic data with 5D interpolation for computing geometric attributesSatinder Chopra and Kurt J. Marfurt2 December 2013 | The Leading Edge, Vol. 32, No. 12Comparison of some algorithms for acquisition footprint suppression and their effect on attribute analysisMilos Cvetkovic, Nebojsa Pralica, Scott Falconer, Kurt J. Marfurt, and Sergio Chávez‐Pérez15 December 2008Attribute‐driven footprint suppressionScott Falconer and Kurt J. Marfurt15 December 2008 SEG Technical Program Expanded Abstracts 2007ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2007 Pages: 3124 publication data© 2007 Copyright © 2007 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 14 Sep 2007 CITATION INFORMATION Milos Cvetkovic, Scott Falconer, Kurt J. Marfurt, and Sergio Chávez‐Pérez, (2007), "2D stationary‐wavelet transform‐based acquisition footprint suppression," SEG Technical Program Expanded Abstracts : 2590-2594. https://doi.org/10.1190/1.2793005 Plain-Language Summary PDF DownloadLoading ...
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