Vertical seismic profiling using distributed acoustic sensing in a hydrofrac treatment well

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2014Vertical seismic profiling using distributed acoustic sensing in a hydrofrac treatment wellAuthors: Sudhish K. Bakku*Michael FehlerPeter WillsJeff MestayerAlbena MateevaJorge LopezSudhish K. Bakku*MITSearch for more papers by this author, Michael FehlerMITSearch for more papers by this author, Peter WillsShellSearch for more papers by this author, Jeff MestayerShellSearch for more papers by this author, Albena MateevaShellSearch for more papers by this author, and Jorge LopezShellSearch for more papers by this authorhttps://doi.org/10.1190/segam2014-1559.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Distributed Acoustic Sensing (DAS) is a Fiber Optic (FO) cable based technology which is gaining importance for VSP surveys, especially for time-lapse monitoring of reservoirs. DAS offers distinct advantages over geophones but it also poses unique challenges, including receiver depth uncertainty and low signal-to-noise ratio. Here, we present an analysis of a DAS VSP acquired for monitoring purposes in a treatment well while a multi-stage hydraulic fracture treatment was ongoing in the same well. We describe the pre-processing needed before further time-lapse analysis of the VSP. We focus on two key steps - depth calibration and noise removal. Large spike noise, most likely from the DAS acquisition system, appears to be a major source of noise in the raw DAS data, but can be removed with careful processing. Other sources of noise include temperature fluctuations in the well and optical noise. We show that excellent quality VSP data can be obtained in a hydrofrac treatment well. Keywords: VSP, distributed systems, noise, processing, fracture stimulationPermalink: https://doi.org/10.1190/segam2014-1559.1FiguresReferencesRelatedDetailsCited ByExperimental study of temperature change effect on distributed acoustic sensing continuous measurementsEvgenii Sidenko, Konstantin Tertyshnikov, Maxim Lebedev, and Roman Pevzner11 March 2022 | GEOPHYSICS, Vol. 87, No. 3Coupled Noise Reduction in Distributed Acoustic Sensing Seismic Data Based on Convolutional Neural NetworkIEEE Geoscience and Remote Sensing Letters, Vol. 19Introduction to Distributed Acoustic Sensing (DAS) Applications for Characterization of Near‐Surface Processes10 December 2021Denoising Analysis and Processing Methods of Distributed Acoustic Sensing (DAS) Vertical Seismic Profiling (VSP) Data10 December 2021A Literature Review10 December 2021Cable reverberations during wireline distributed acoustic sensing measurements: their nature and methods for elimination16 May 2021 | Geophysical Prospecting, Vol. 69, No. 5Fibre Optic Methods of Prospecting: A Comprehensive and Modern Branch of Geophysics9 March 2021 | Surveys in Geophysics, Vol. 42, No. 3Seismic Applications of Downhole DAS21 April 2021 | Sensors, Vol. 21, No. 9Modeling and interpretation of scattered waves in interstage distributed acoustic sensing vertical seismic profiling surveyAleksei Titov, Gary Binder, Youfang Liu, Ge Jin, James Simmons, Ali Tura, David Monk, Grant Byerley, and Mike Yates2 March 2021 | GEOPHYSICS, Vol. 86, No. 2Distributed Acoustic Sensing Vertical Seismic Profile Data Denoiser Based on Convolutional Neural NetworkIEEE Transactions on Geoscience and Remote SensingFracture properties estimation using distributed acoustic sensing recording of guided waves in unconventional reservoirsAriel Lellouch, Mark A. 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