Least-squares reverse time migration with radon preconditioning

Handle URI:
http://hdl.handle.net/10754/625273
Title:
Least-squares reverse time migration with radon preconditioning
Authors:
Dutta, Gaurav ( 0000-0002-2024-1683 ) ; Agut, Cyril; Giboli, Matteo; Williamson, Paul
Abstract:
We present a least-squares reverse time migration (LSRTM) method using Radon preconditioning to regularize noisy or severely undersampled data. A high resolution local radon transform is used as a change of basis for the reflectivity and sparseness constraints are applied to the inverted reflectivity in the transform domain. This reflects the prior that for each location of the subsurface the number of geological dips is limited. The forward and the adjoint mapping of the reflectivity to the local Radon domain and back are done through 3D Fourier-based discrete Radon transform operators. The sparseness is enforced by applying weights to the Radon domain components which either vary with the amplitudes of the local dips or are thresholded at given quantiles. Numerical tests on synthetic and field data validate the effectiveness of the proposed approach in producing images with improved SNR and reduced aliasing artifacts when compared with standard RTM or LSRTM.
KAUST Department:
King Abdullah University of Science and Technology, , Saudi Arabia
Citation:
Dutta G, Agut C, Giboli M, Williamson P (2016) Least-squares reverse time migration with radon preconditioning. SEG Technical Program Expanded Abstracts 2016. Available: http://dx.doi.org/10.1190/segam2016-13943593.1.
Publisher:
Society of Exploration Geophysicists
Journal:
SEG Technical Program Expanded Abstracts 2016
Conference/Event name:
SEG International Exposition and 86th Annual Meeting, SEG 2016
Issue Date:
6-Sep-2016
DOI:
10.1190/segam2016-13943593.1
Type:
Conference Paper
Additional Links:
http://library.seg.org/doi/10.1190/segam2016-13943593.1
Appears in Collections:
Conference Papers

Full metadata record

DC FieldValue Language
dc.contributor.authorDutta, Gauraven
dc.contributor.authorAgut, Cyrilen
dc.contributor.authorGiboli, Matteoen
dc.contributor.authorWilliamson, Paulen
dc.date.accessioned2017-07-27T11:21:47Z-
dc.date.available2017-07-27T11:21:47Z-
dc.date.issued2016-09-06en
dc.identifier.citationDutta G, Agut C, Giboli M, Williamson P (2016) Least-squares reverse time migration with radon preconditioning. SEG Technical Program Expanded Abstracts 2016. Available: http://dx.doi.org/10.1190/segam2016-13943593.1.en
dc.identifier.doi10.1190/segam2016-13943593.1en
dc.identifier.urihttp://hdl.handle.net/10754/625273-
dc.description.abstractWe present a least-squares reverse time migration (LSRTM) method using Radon preconditioning to regularize noisy or severely undersampled data. A high resolution local radon transform is used as a change of basis for the reflectivity and sparseness constraints are applied to the inverted reflectivity in the transform domain. This reflects the prior that for each location of the subsurface the number of geological dips is limited. The forward and the adjoint mapping of the reflectivity to the local Radon domain and back are done through 3D Fourier-based discrete Radon transform operators. The sparseness is enforced by applying weights to the Radon domain components which either vary with the amplitudes of the local dips or are thresholded at given quantiles. Numerical tests on synthetic and field data validate the effectiveness of the proposed approach in producing images with improved SNR and reduced aliasing artifacts when compared with standard RTM or LSRTM.en
dc.publisherSociety of Exploration Geophysicistsen
dc.relation.urlhttp://library.seg.org/doi/10.1190/segam2016-13943593.1en
dc.rightsArchived with thanks to SEG Technical Program Expanded Abstracts 2016en
dc.subjectleast-squares migrationen
dc.subjectRadonen
dc.subjectwave equationen
dc.subjectdepth migrationen
dc.subjectimagingen
dc.titleLeast-squares reverse time migration with radon preconditioningen
dc.typeConference Paperen
dc.contributor.departmentKing Abdullah University of Science and Technology, , Saudi Arabiaen
dc.identifier.journalSEG Technical Program Expanded Abstracts 2016en
dc.conference.date2011-10-16 to 2011-10-21en
dc.conference.nameSEG International Exposition and 86th Annual Meeting, SEG 2016en
dc.conference.locationDallas, TX, USAen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionTOTAL SA, , Franceen
kaust.authorDutta, Gauraven
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