Elastic least-squares reverse time migration

Handle URI:
http://hdl.handle.net/10754/623002
Title:
Elastic least-squares reverse time migration
Authors:
Feng, Zongcai; Schuster, Gerard T. ( 0000-0001-7532-1587 )
Abstract:
We use elastic least-squares reverse time migration (LSRTM) to invert for the reflectivity images of P- and S-wave impedances. Elastic LSRTMsolves the linearized elastic-wave equations for forward modeling and the adjoint equations for backpropagating the residual wavefield at each iteration. Numerical tests on synthetic data and field data reveal the advantages of elastic LSRTM over elastic reverse time migration (RTM) and acoustic LSRTM. For our examples, the elastic LSRTM images have better resolution and amplitude balancing, fewer artifacts, and less crosstalk compared with the elastic RTM images. The images are also better focused and have better reflector continuity for steeply dipping events compared to the acoustic LSRTM images. Similar to conventional leastsquares migration, elastic LSRTM also requires an accurate estimation of the P- and S-wave migration velocity models. However, the problem remains that, when there are moderate errors in the velocity model and strong multiples, LSRTMwill produce migration noise stronger than that seen in the RTM images.
KAUST Department:
Earth Science and Engineering Program
Citation:
Feng Z, Schuster GT (2017) Elastic least-squares reverse time migration. GEOPHYSICS 82: S143–S157. Available: http://dx.doi.org/10.1190/GEO2016-0254.1.
Publisher:
Society of Exploration Geophysicists
Journal:
GEOPHYSICS
Issue Date:
8-Mar-2017
DOI:
10.1190/GEO2016-0254.1
Type:
Article
ISSN:
0016-8033; 1942-2156
Sponsors:
This research is supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling Consortium for their financial support. Z. Feng would also like to thank G. Dutta and B. Guo for their help. The computation resource provided by the KAUST Supercomputing Laboratory is greatly appreciated. We are very grateful to Jerry Harris and Robert Langan for the use of the crosswell data set.
Additional Links:
http://library.seg.org/doi/abs/10.1190/geo2016-0254.1
Appears in Collections:
Articles; Earth Science and Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorFeng, Zongcaien
dc.contributor.authorSchuster, Gerard T.en
dc.date.accessioned2017-03-15T07:15:27Z-
dc.date.available2017-03-15T07:15:27Z-
dc.date.issued2017-03-08en
dc.identifier.citationFeng Z, Schuster GT (2017) Elastic least-squares reverse time migration. GEOPHYSICS 82: S143–S157. Available: http://dx.doi.org/10.1190/GEO2016-0254.1.en
dc.identifier.issn0016-8033en
dc.identifier.issn1942-2156en
dc.identifier.doi10.1190/GEO2016-0254.1en
dc.identifier.urihttp://hdl.handle.net/10754/623002-
dc.description.abstractWe use elastic least-squares reverse time migration (LSRTM) to invert for the reflectivity images of P- and S-wave impedances. Elastic LSRTMsolves the linearized elastic-wave equations for forward modeling and the adjoint equations for backpropagating the residual wavefield at each iteration. Numerical tests on synthetic data and field data reveal the advantages of elastic LSRTM over elastic reverse time migration (RTM) and acoustic LSRTM. For our examples, the elastic LSRTM images have better resolution and amplitude balancing, fewer artifacts, and less crosstalk compared with the elastic RTM images. The images are also better focused and have better reflector continuity for steeply dipping events compared to the acoustic LSRTM images. Similar to conventional leastsquares migration, elastic LSRTM also requires an accurate estimation of the P- and S-wave migration velocity models. However, the problem remains that, when there are moderate errors in the velocity model and strong multiples, LSRTMwill produce migration noise stronger than that seen in the RTM images.en
dc.description.sponsorshipThis research is supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling Consortium for their financial support. Z. Feng would also like to thank G. Dutta and B. Guo for their help. The computation resource provided by the KAUST Supercomputing Laboratory is greatly appreciated. We are very grateful to Jerry Harris and Robert Langan for the use of the crosswell data set.en
dc.publisherSociety of Exploration Geophysicistsen
dc.relation.urlhttp://library.seg.org/doi/abs/10.1190/geo2016-0254.1en
dc.rightsArchived with thanks to GEOPHYSICSen
dc.titleElastic least-squares reverse time migrationen
dc.typeArticleen
dc.contributor.departmentEarth Science and Engineering Programen
dc.identifier.journalGEOPHYSICSen
dc.eprint.versionPublisher's Version/PDFen
kaust.authorFeng, Zongcaien
kaust.authorSchuster, Gerard T.en
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