Multicomponent DAS sensing: Time-series strain-rate tensor estimation from fiber data

PreviousNext No AccessFirst International Meeting for Applied Geoscience & Energy Expanded AbstractsMulticomponent DAS sensing: Time-series strain-rate tensor estimation from fiber dataAuthors: Kevin W. HallKristopher A. InnanenDonald C. LawtonKevin W. HallUniversity of CalgarySearch for more papers by this author, Kristopher A. InnanenUniversity of CalgarySearch for more papers by this author, and Donald C. LawtonUniversity of Calgary and Carbon Management Canada (CMC)Search for more papers by this authorhttps://doi.org/10.1190/segam2021-3583573.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractWe constructed an experimental directional DAS sensor (DDS) at CMC’s Containment and Monitoring Institute Field Research Station (CaMI.FRS) in 2018. The sensor (initially described by Innanen et al. (2019), consists of two buried 10x10 m squares of straight and helically wound fiber, with the second square rotated forty-five degrees relative to the first. For validation purposes, three component geophones were planted on the surface just outside of the corners of the DDS, and data from four vibe points were acquired. In recent work (Hall et al., 2020), the horizontal components of the geophone data were converted to directional strain-rate traces and visually compared to fiber strain-rate traces. We concluded that the strain-rate traces were faithfully expressing projections of the time derivative of the strain tensor onto the fiber intervals in the DDS.We then set about to determine 3 components of horizontal strain rate tensor in field coordinates, using the DAS measurements and the geometry of the DDS. The result is to our knowledge one of the first ever examples of the sensing of multicomponent DAS data: a set of three traces representing the time evolution of the three independent lateral components of the strain carried by seismic waves (primarily ground roll in this case).Both straight and helically wound fibre are included in the DDS. The resulting estimated tensors are almost identical for both fiber types after trace scaling. The amplitudes of the strain-rate tensors estimated for validation purposes by differencing the geophone data are higher than seen for the fiber results in some cases. We interpret the difference as being caused primarily by differences in geophone and the fiber locations.Keywords: DAS (distributed acoustic sensors), multicomponent, tensor, surface wave, estimationPermalink: https://doi.org/10.1190/segam2021-3583573.1FiguresReferencesRelatedDetails 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 Kevin W. Hall, Kristopher A. Innanen, and Donald C. Lawton, (2021), "Multicomponent DAS sensing: Time-series strain-rate tensor estimation from fiber data," SEG Technical Program Expanded Abstracts : 442-446. https://doi.org/10.1190/segam2021-3583573.1 Plain-Language Summary KeywordsDAS (distributed acoustic sensors)multicomponenttensorsurface waveestimationPDF DownloadLoading ...