A simulated simultaneous source experiment in shallow waters and the impact of randomization schemes (2013)

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2013A simulated simultaneous source experiment in shallow waters and the impact of randomization schemesAuthors: Rolf BaardmanRoald van BorselenRolf BaardmanPGS and Roald van BorselenPGShttps://doi.org/10.1190/segam2013-1199.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract In simultaneous source acquisition, seismic data can be recorded with a temporal overlap between the shots. Better sampled data in terms of source spacing, azimuth and/or offset distributions can be obtained in a much more efficient way. These potential benefits can only be realized if the recorded data, with interfering energy from multiple sources, can be handled properly. Common practice is to apply randomized time-delays to the sources during the acquisition of the data. As a result of using randomized firing schemes, coherency measures can be utilized to actively separate the recorded data over the individual sources. In this paper an inversion-based source separation method is utilized to a shallow water data set which may have specific challenges compared to deeper water applications. We will focus a bit more on the randomized firing schemes. It is shown that optimizing these firing schemes, introducing "pseudo randomization", instead of using random time-delays, can benefit the performance of the source separation. The separation method is illustrated using a controlled simultaneous source experiment where a shallow water field data set is used to mimic simultaneous recorded data where two sources were located with only a small cross line distance between them (simultaneous FLIP/FLOP acquisition). Results demonstrate that it is advised to utilize "pseudo randomization" of the firing delay-times. The controlled shallow water field data example shows that good separation results are obtained. Permalink: https://doi.org/10.1190/segam2013-1199.1FiguresReferencesRelatedDetailsCited byAcquisition/Processing: Machine learning-based deblending: Dispersed source array data exampleRolf H. Baardman and Rob F. Hegge1 October 2021 | The Leading Edge, Vol. 40, No. 10Machine-learning-based data recovery and its contribution to seismic acquisition: Simultaneous application of deblending, trace reconstruction, and low-frequency extrapolationShotaro Nakayama and Gerrit Blacquière23 February 2021 | GEOPHYSICS, Vol. 86, No. 2References4 February 2021Iterative deblending for simultaneous source data using the deep neural networkShaohuan Zu, Junxing Cao, Shan Qu, and Yangkang Chen30 January 2020 | GEOPHYSICS, Vol. 85, No. 2Machine learning approaches for use in deblendingRolf H. Baardman and Rob F. Hegge2 March 2020 | The Leading Edge, Vol. 39, No. 3Automated survey design for blended acquisition with irregular spatial sampling via the integration of a metaheuristic and deep learningShotaro Nakayama, Gerrit Blacquière, and Tomohide Ishiyama31 May 2019 | GEOPHYSICS, Vol. 84, No. 4Blended‐acquisition design of irregular geometries towards faster, cheaper, safer and better seismic surveying25 October 2018 | Geophysical Prospecting, Vol. 67, No. 6Blended-acquisition design with irregular geometries for wide-azimuth samplingShotaro Nakayama, Gerrit Blacquière, Tomohide Ishiyama, and Satoshi Ishikawa27 August 2018Fast dual-domain reduced-rank algorithm for 3D deblending via randomized QR decompositionJinkun Cheng and Mauricio D. Sacchi29 January 2016 | GEOPHYSICS, Vol. 81, No. 1Shot scheduling in simultaneous shootingRay Abma*5 August 2014SI attenuation as part of simultaneous source acquisition: GOM field data exerciseR. H. Baardman, Jack Kinkead*, Ruth Loyd, and Roald G. van Borselen5 August 2014 SEG Technical Program Expanded Abstracts 2013ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2013 Pages: 5258 Publisher:Society of Exploration Geophysicists HistoryPublished Online: 19 Aug 2013 CITATION INFORMATION Rolf Baardman and Roald van Borselen, (2013), "A simulated simultaneous source experiment in shallow waters and the impact of randomization schemes," SEG Technical Program Expanded Abstracts : 4382-4386. https://doi.org/10.1190/segam2013-1199.1 Plain-Language Summary PDF DownloadLoading ...