Fast antialiasing Fourier inversion for 5D seismic data regularization

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2017Fast antialiasing Fourier inversion for 5D seismic data regularizationAuthors: Hao YangJinsong LiLideng GanShufang MaHao YangRIPED, PetroChinaSearch for more papers by this author, Jinsong LiRIPED, PetroChinaSearch for more papers by this author, Lideng GanRIPED, PetroChinaSearch for more papers by this author, and Shufang MaCNOOCSearch for more papers by this authorhttps://doi.org/10.1190/segam2017-17623715.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Fourier-based seismic data reconstruction algorithm has several significant advantages such as the improvement of efficiency by using FFT or Non-uniform Fast Fourier Transform (NFFT) and the regularization feature in some of the algorithms which avoids the geometry errors caused by binning the input seismic traces into a regular spatial grid. However, in some cases, only when spatial aliasing problem is overcome properly can the algorithm play its powerful role. In order to address the aliasing problem, an additional constraint item which characterizes the spatial continuity of the inversion result is put into the conventional optimization formula. The weight matrix in the constraint item can be approximately degenerated as a diagonal matrix which makes nearly an equal computational complexity to that of conventional optimization formula but almost no difference for the function of anti-aliasing. A 1D synthetic data is used to illustrate the basic principle of the method. A 2D synthetic data example demonstrates that the algorithm performs well on spatial aliasing data. The algorithm is also tested on a 5D real data in which the relative regular but aliasing dimension of receiver lines is successfully interpolated. Presentation Date: Wednesday, September 27, 2017 Start Time: 4:45 PM Location: 360A Presentation Type: ORAL Keywords: Fourier, interpolation, 5D reconstructionPermalink: https://doi.org/10.1190/segam2017-17623715.1FiguresReferencesRelatedDetailsCited byDeep-seismic-prior-based reconstruction of seismic data using convolutional neural networksQun Liu, Lihua Fu, and Meng Zhang18 February 2021 | GEOPHYSICS, Vol. 86, No. 2 SEG Technical Program Expanded Abstracts 2017ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2017 Pages: 6093 publication data© 2017 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 17 Aug 2017 CITATION INFORMATION Hao Yang, Jinsong Li, Lideng Gan, and Shufang Ma, (2017), "Fast antialiasing Fourier inversion for 5D seismic data regularization," SEG Technical Program Expanded Abstracts : 4317-4321. https://doi.org/10.1190/segam2017-17623715.1 Plain-Language Summary KeywordsFourierinterpolation5D reconstructionPDF DownloadLoading ...