Transdimensional multimode surface-wave dispersion inversion of seismic data recorded on trench-deployed distributed acoustic sensing fiber

PreviousNext No AccessFirst International Meeting for Applied Geoscience & Energy Expanded AbstractsTransdimensional multimode surface-wave dispersion inversion of seismic data recorded on trench-deployed distributed acoustic sensing fiberAuthors: Luping QuJan DettmerKristopher A. InnanenKevin HallMarie MacquetDonald LawtonLuping QuUniversity of CalgarySearch for more papers by this author, Jan DettmerUniversity of CalgarySearch for more papers by this author, Kristopher A. InnanenUniversity of CalgarySearch for more papers by this author, Kevin HallUniversity of CalgarySearch for more papers by this author, Marie MacquetUniversity of Calgary and CMCSearch for more papers by this author, and Donald LawtonUniversity of Calgary and CMCSearch for more papers by this authorhttps://doi.org/10.1190/segam2021-3594236.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractSurface-deployed distributed acoustic sensing (DAS) fiber has the potential to provide high quality fiberoptic seismic data for estimating near-surface velocity profiles using surface-wave dispersion (SWD) inversion methods. Because of the challenges of robust, multimode curve picking, most SWD inversion approaches only utilize the fundamental mode. However, putting this generally leads to damaging trade-offs in the resulting inferred models. We observe that surface DAS data, with its wide frequency range, makes multimodal dispersion curve picking much more straightforward, opening up as a practical possibility of using these higher modes to enhance resolution in shallow and deeper regions of the near surface simultaneously. In this study, a SWD approach based on three important ingredients is set out. First, we make use of DAS data with its benefits; second, we incorporate multiple modes of data in the inversion; and third we carry out the near surface model determination through a trans-dimensional inversion procedure, in which model size is included as an unknown. Parallel tempering with twenty chains is employed to speed up the convergence. Data errors are estimated through a non-parametric iterative process. Synthetic testing suggests that multimode surface wave inversion not only provides additional constraints on the structure, but also improves the noise estimation. Our method is further applied to the active source DAS dataset acquired at the Containment and Monitoring Institute Field Research Station in Newell County, Alberta, Canada. The results are consistent with the regional lithology background.Keywords: dispersion, surface wave, fiber-optic sensors, nonlinear, near surfacePermalink: https://doi.org/10.1190/segam2021-3594236.1FiguresReferencesRelatedDetails First International Meeting for Applied Geoscience & Energy Expanded AbstractsISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2021 Pages: 3561 publication data© 2021 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 01 Sep 2021 CITATION INFORMATION Luping Qu, Jan Dettmer, Kristopher A. Innanen, Kevin Hall, Marie Macquet, and Donald Lawton, (2021), "Transdimensional multimode surface-wave dispersion inversion of seismic data recorded on trench-deployed distributed acoustic sensing fiber," SEG Technical Program Expanded Abstracts : 1896-1900. https://doi.org/10.1190/segam2021-3594236.1 Plain-Language Summary Keywordsdispersionsurface wavefiber-optic sensorsnonlinearnear surfacePDF DownloadLoading ...