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• W2517232604 abstract "PreviousNext No AccessSEG Technical Program Expanded Abstracts 2016Full-waveform inversion using smoothing kernelsAuthors: Zhiguang XueNick AlgerSergey FomelZhiguang XueUniversity of Texas—AustinSearch for more papers by this author, Nick AlgerUniversity of Texas—AustinSearch for more papers by this author, and Sergey FomelUniversity of Texas—AustinSearch for more papers by this authorhttps://doi.org/10.1190/segam2016-13948739.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract We introduce smoothing kernels into the FWI (full waveform inversion) objective function to mitigate the cycle skipping problem. This approach resembles the commonly used frequency continuation technique, wherein low frequencies are inverted for first, followed by progressively higher and higher frequencies. However, FWI with smoothing kernels does not require the existence of very low frequency components in seismic data. Its implementation is straightforward based on the conventional least-squares FWI. It successively minimizes a sequence of modified least-squares objective functions which measure smoothed data residuals. The smoothing strength at each stage of the inversion is different: it begins with strong smoothing and ends with no smoothing, at which point the inversion converges to the solution of the original (unsmoothed) problem. We propose three alternative optimization strategies for inverting for velocity models using smoothing kernels: successive smoothing relaxation, smoothing path continuation, and homotopy continuation. Numerical examples demonstrate that FWI using smoothing kernels can effectively overcome the cycle skipping problem, and is capable of producing highly accurate velocity models even in salt-affected environments and in the absence of ultra low frequencies. Presentation Date: Thursday, October 20, 2016 Start Time: 9:20:00 AM Location: 162/164 Presentation Type: ORAL Keywords: continuation, subsalt, velocity, full-waveform inversion, optimizationPermalink: https://doi.org/10.1190/segam2016-13948739.1FiguresReferencesRelatedDetailsCited byA Hybrid Optimization Framework for Seismic Full Waveform Inversion14 August 2022 | Journal of Geophysical Research: Solid Earth, Vol. 127, No. 8A variational approach for picking optimal surfaces from semblance-like panelsLuke Decker and Sergey Fomel11 April 2022 | GEOPHYSICS, Vol. 87, No. 3Full waveform inversion based on the non-parametric estimate of the probability distribution of the residuals27 October 2021 | Geophysical Journal International, Vol. 229, No. 1A continuation approach for avoiding local minima in seismic velocity pickingLuke Decker and Sergey Fomel1 September 2021A hybrid optimization method for full-waveform inversionZeyu Zhao and Mrinal K. Sen1 September 2021A gradient-based Markov chain Monte Carlo method for full-waveform inversion and uncertainty analysisZeyu Zhao and Mrinal K. Sen16 December 2020 | GEOPHYSICS, Vol. 86, No. 1Full waveform inversion of combined towed streamer and limited OBS seismic data: a theoretical study11 June 2018 | Marine Geophysical Research, Vol. 40, No. 3A multi-scale full waveform inversion method - staging wavenumber components and layer-strippingZeyu Zhao and Mrinal K. Sen10 August 2019Flux-corrected transport for full-waveform inversion25 February 2019 | Geophysical Journal International, Vol. 217, No. 3The Interpolation of Sparse Geophysical Data27 September 2018 | Surveys in Geophysics, Vol. 40, No. 1Elastic full-waveform inversion by b-spline projectionPeng Shen, Uwe Albertin, Lin Zhang, and Ling Duan27 August 2018Signal-Preserving Erratic Noise Attenuation via Iterative Robust Sparsity-Promoting FilterIEEE Transactions on Geoscience and Remote Sensing, Vol. 56, No. 6Adaptive stabilization for Q-compensated reverse time migrationYufeng Wang, Hui Zhou, Hanming Chen, and Yangkang Chen14 November 2017 | GEOPHYSICS, Vol. 83, No. 1Automated time-window selection based on machine learning for full-waveform inversionYangkang Chen, Judith Hill, Wenjie Lei, Matthieu Lefebvre, Jeroen Tromp, Ebru Bozdag, and Dimitri Komatitsch17 August 2017Fast building initial velocity modeling using encoding multiscale multishot full-waveform inversionYundong Guo, Jianping Huang, Chao Cui, and Zhenchun Li17 August 2017Fast double plane wave full-waveform inversion using the scattering-integral method in frequency domainZeyu Zhao and Mrinal Sen17 August 2017Full-Waveform Inversion I Complete Session17 August 2017Full-Waveform Inversion II Complete Session17 August 2017 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 Zhiguang Xue, Nick Alger, and Sergey Fomel, (2016), Full-waveform inversion using smoothing kernels, SEG Technical Program Expanded Abstracts : 1358-1363. https://doi.org/10.1190/segam2016-13948739.1 Plain-Language Summary Keywordscontinuationsubsaltvelocityfull-waveform inversionoptimizationPDF DownloadLoading ..." @default.
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