Low-frequency ambient Distributed Acoustic Sensing (DAS): Useful for subsurface investigation?
Seg Technical Program Expanded Abstracts(2019)
Abstract
PreviousNext No AccessSEG Technical Program Expanded Abstracts 2019Low-frequency ambient Distributed Acoustic Sensing (DAS): Useful for subsurface investigation?Authors: Jeffrey ShraggeJihyun YangNader A IssaMichael RoelensMichael DentithSascha SchediwyJeffrey ShraggeColorado School of MinesSearch for more papers by this author, Jihyun YangColorado School of MinesSearch for more papers by this author, Nader A IssaTerra15 Pty LtdSearch for more papers by this author, Michael RoelensTerra15 Pty LtdSearch for more papers by this author, Michael DentithUniversity of Western AustraliaSearch for more papers by this author, and Sascha SchediwyUniversity of Western AustraliaSearch for more papers by this authorhttps://doi.org/10.1190/segam2019-3216479.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractDistributed Acoustic Sensing (DAS) is a rapidly growing novel sensing method for seismic data acquisition. DAS arrays are particularly well-suited for dense recording of low-frequency ambient surface waves on long (>5 km) linear sections of deployed optical fiber cable. Applying multi-channel analysis of surface waves (MASW) to ambient wavefield DAS recordings characterized by a large number of sensing points and long recording times may enable 1D characterization of the S-wave velocity profile to depths of 750 m or greater. We present a low-frequency ambient wavefield investigation using a DAS dataset acquired on an array deployed in suburban Perth, Australia. We extract storm-induced swell noise from the nearby Indian Ocean in a low-frequency band (0.1–1.8 Hz) and generate virtual shot gathers by applying cross-correlation and deconvolution seismic interferometric analyses. The resulting gathers are transformed into dispersion images through two different methods: phase shift and high-resolution linear Radon transform. To recover the near-surface S-wave velocity model, we first pick and then invert the recovered 1D Rayleigh-wave dispersion curves using a particle-swarm optimization algorithm. Inversion results show that low-frequency ambient-wavefield DAS data can constrain the Vs model to 750 m depth, which helps validate the potential of DAS technology as a tool for large-scale surface-wave investigation.Presentation Date: Monday, September 16, 2019Session Start Time: 1:50 PMPresentation Time: 3:30 PMLocation: 221CPresentation Type: OralKeywords: fiber-optic sensors, passive acquisition, rayleigh wave, surface wave, inversionPermalink: https://doi.org/10.1190/segam2019-3216479.1FiguresReferencesRelatedDetailsCited byAmbient seismic noise in an urban environment: case study using downhole distributed acoustic sensors at the Curtin University campus in Perth, Western Australia24 January 2022 | Exploration Geophysics, Vol. 53, No. 6Downhole Monitoring Using Distributed Acoustic Sensing: Fundamentals and Two Decades Deployment in Oil and Gas Industries21 March 2022A Literature Review10 December 2021Well-scale demonstration of distributed pressure sensing using fiber-optic DAS and DTS14 June 2021 | Scientific Reports, Vol. 11, No. 1Sensing Shallow Structure and Traffic Noise with Fiber-optic Internet Cables in an Urban Area19 November 2021 | Surveys in Geophysics, Vol. 42, No. 6Rayleigh Wave Dispersion Spectrum Inversion Across Scales19 October 2021 | Surveys in Geophysics, Vol. 42, No. 6Surface-wave dispersion spectrum inversion method applied to Love and Rayleigh waves recorded by distributed acoustic sensingZhenghong Song, Xiangfang Zeng, and Clifford H. Thurber4 January 2021 | GEOPHYSICS, Vol. 86, No. 1Near-surface seismic properties characterizations with a roadside distributed acoustic sensing (DAS) arraySiyuan Yuan, Ariel Lellouch, Bob Clapp, and Biondo Biondi30 September 2020Near-surface characterization using a roadside distributed acoustic sensing arraySiyuan Yuan, Ariel Lellouch, Robert G. Clapp, and Biondo Biondi1 September 2020 | The Leading Edge, Vol. 39, No. 9Wave-equation dispersion spectrum inversion for near-surface characterization using fibre-optics acquisition1 May 2020 | Geophysical Journal International, Vol. 222, No. 2 SEG Technical Program Expanded Abstracts 2019ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2019 Pages: 5407 publication data© 2019 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 10 Aug 2019 CITATION INFORMATION Jeffrey Shragge, Jihyun Yang, Nader A Issa, Michael Roelens, Michael Dentith, and Sascha Schediwy, (2019), "Low-frequency ambient Distributed Acoustic Sensing (DAS): Useful for subsurface investigation?," SEG Technical Program Expanded Abstracts : 963-967. https://doi.org/10.1190/segam2019-3216479.1 Plain-Language Summary Keywordsfiber-optic sensorspassive acquisitionrayleigh wavesurface waveinversionPDF DownloadLoading ...
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acoustic sensing,subsurface investigation,low-frequency
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