Two-step velocity inversion using trans-dimensional tomography and elastic FWI

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2020Two-step velocity inversion using trans-dimensional tomography and elastic FWIAuthors: Reetam BiswasAdrien F. ArnulfMrinal K. SenDebanjan DattaZeyu ZhaoPankaj K. MishraPiyoosh JaysavalReetam BiswasUniversity of Texas at Austin, and BPSearch for more papers by this author, Adrien F. ArnulfUniversity of Texas at AustinSearch for more papers by this author, Mrinal K. SenUniversity of Texas at AustinSearch for more papers by this author, Debanjan DattaUniversity of Texas at Austin, and Shell International Exploration and ProductionSearch for more papers by this author, Zeyu ZhaoUniversity of Texas at AustinSearch for more papers by this author, Pankaj K. MishraUniversity of Texas at AustinSearch for more papers by this author, and Piyoosh JaysavalUniversity of Texas at Austin, and Pacific Northwest National LaboratorySearch for more papers by this authorhttps://doi.org/10.1190/segam2020-3407268.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractFull Waveform Inversion (FWI) has become a powerful tool to generate high-resolution subsurface velocity models. FWI attempts to solve a non-linear and non-unique inverse problem, and is traditionally based on a local optimization technique. As a result, it can easily get stuck in a local minimum. To mitigate this deleterious effect, FWI requires a good starting model, which should be close enough to the optimal model to properly converge to the global minimum. Here, we investigate a two-step approach for solving this problem. In the first step, we generate a starting model for FWI, that includes the low-wavenumber information, from first-arrival traveltime tomography of downward extrapolated streamer data. We solve the tomography problem using a trans-dimensional approach, based on a Bayesian framework. The number of model parameters is treated as a variable, similar to the P-wave velocity information. We use an adaptive cloud of nuclei points and Voronoi cells to represent our 2D velocity model. We use Reversible Jump Markov Chain Monte Carlo (RJMCMC) to sample models from a variable dimensional model space and obtain an optimum starting model for local elastic FWI. We also estimate uncertainty in our tomography derived model. We solve for the Eikonal equation using a shortest path method for ray tracing in tomography and we solve the elastic wave equation using a time-domain finite-difference method in FWI. To compute the gradient we used the adjoint method. We demonstrate our algorithm on a real 2-D seismic streamer dataset from Axial Seamount, which is the most volcanically active site of the northeastern Pacific. We ran 17 Markov chains with different starting number of nuclei and convergence for all chains was attained in about 1000 iterations. Marginal posterior density plots of velocity models demonstrate uncertainty in the obtained starting velocity models. We then ran a local FWI using the combined result from all chains.Presentation Date: Tuesday, October 13, 2020Session Start Time: 1:50 PMPresentation Time: 2:40 PMLocation: 362APresentation Type: OralKeywords: tomography, traveltime, inversion, full-waveform inversion, elasticPermalink: https://doi.org/10.1190/segam2020-3407268.1FiguresReferencesRelatedDetailsCited bySeismic inversion for density using a transdimensional approachReetam Biswas, Dhananjay Kumar, and Mrinal K. Sen1 August 2022 | The Leading Edge, Vol. 41, No. 8Seismic velocity inversion based on CNN-LSTM fusion deep neural network2 May 2022 | Applied Geophysics, Vol. 18, No. 4Deep learning for velocity model building with common-image gather volumes22 September 2021 | Geophysical Journal International, Vol. 228, No. 2 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 Reetam Biswas, Adrien F. Arnulf, Mrinal K. Sen, Debanjan Datta, Zeyu Zhao, Pankaj K. Mishra, and Piyoosh Jaysaval, (2020), "Two-step velocity inversion using trans-dimensional tomography and elastic FWI," SEG Technical Program Expanded Abstracts : 3628-3633. https://doi.org/10.1190/segam2020-3407268.1 Plain-Language Summary Keywordstomographytraveltimeinversionfull-waveform inversionelasticPDF DownloadLoading ...