Least-squares migration of multisource data with a deblurring filter

Handle URI:
http://hdl.handle.net/10754/561868
Title:
Least-squares migration of multisource data with a deblurring filter
Authors:
Dai, Wei; Wang, Xin; Schuster, Gerard T. ( 0000-0001-7532-1587 )
Abstract:
Least-squares migration (LSM) has been shown to be able to produce high-quality migration images, but its computational cost is considered to be too high for practical imaging. We have developed a multisource least-squares migration algorithm (MLSM) to increase the computational efficiency by using the blended sources processing technique. To expedite convergence, a multisource deblurring filter is used as a preconditioner to reduce the data residual. This MLSM algorithm is applicable with Kirchhoff migration, wave-equation migration, or reverse time migration, and the gain in computational efficiency depends on the choice of migration method. Numerical results with Kirchhoff LSM on the 2D SEG/EAGE salt model show that an accurate image is obtained by migrating a supergather of 320 phase-encoded shots. When the encoding functions are the same for every iteration, the input/output cost of MLSM is reduced by 320 times. Empirical results show that the crosstalk noise introduced by blended sources is more effectively reduced when the encoding functions are changed at every iteration. The analysis of signal-to-noise ratio (S/N) suggests that not too many iterations are needed to enhance the S/N to an acceptable level. Therefore, when implemented with wave-equation migration or reverse time migration methods, the MLSM algorithm can be more efficient than the conventional migration method. © 2011 Society of Exploration Geophysicists.
KAUST Department:
Physical Sciences and Engineering (PSE) Division; Earth Science and Engineering Program; Earth Sciences and Engineering Program; Environmental Science and Engineering Program
Publisher:
Society of Exploration Geophysicists
Journal:
Geophysics
Issue Date:
Sep-2011
DOI:
10.1190/geo2010-0159.1
Type:
Article
ISSN:
00168033
Sponsors:
We are grateful to King Abdullah University of Science and Technology and the sponsors of the 2009 University of Utah Tomography and Modeling/Migration (UTAM) Consortium for their financial support. We also thank the associate editor and three anonymous reviewers for their constructive comments.
Appears in Collections:
Articles; Environmental Science and Engineering Program; Physical Sciences and Engineering (PSE) Division; Earth Science and Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorDai, Weien
dc.contributor.authorWang, Xinen
dc.contributor.authorSchuster, Gerard T.en
dc.date.accessioned2015-08-03T09:32:53Zen
dc.date.available2015-08-03T09:32:53Zen
dc.date.issued2011-09en
dc.identifier.issn00168033en
dc.identifier.doi10.1190/geo2010-0159.1en
dc.identifier.urihttp://hdl.handle.net/10754/561868en
dc.description.abstractLeast-squares migration (LSM) has been shown to be able to produce high-quality migration images, but its computational cost is considered to be too high for practical imaging. We have developed a multisource least-squares migration algorithm (MLSM) to increase the computational efficiency by using the blended sources processing technique. To expedite convergence, a multisource deblurring filter is used as a preconditioner to reduce the data residual. This MLSM algorithm is applicable with Kirchhoff migration, wave-equation migration, or reverse time migration, and the gain in computational efficiency depends on the choice of migration method. Numerical results with Kirchhoff LSM on the 2D SEG/EAGE salt model show that an accurate image is obtained by migrating a supergather of 320 phase-encoded shots. When the encoding functions are the same for every iteration, the input/output cost of MLSM is reduced by 320 times. Empirical results show that the crosstalk noise introduced by blended sources is more effectively reduced when the encoding functions are changed at every iteration. The analysis of signal-to-noise ratio (S/N) suggests that not too many iterations are needed to enhance the S/N to an acceptable level. Therefore, when implemented with wave-equation migration or reverse time migration methods, the MLSM algorithm can be more efficient than the conventional migration method. © 2011 Society of Exploration Geophysicists.en
dc.description.sponsorshipWe are grateful to King Abdullah University of Science and Technology and the sponsors of the 2009 University of Utah Tomography and Modeling/Migration (UTAM) Consortium for their financial support. We also thank the associate editor and three anonymous reviewers for their constructive comments.en
dc.publisherSociety of Exploration Geophysicistsen
dc.subjectLeast squaresen
dc.subjectMigrationen
dc.titleLeast-squares migration of multisource data with a deblurring filteren
dc.typeArticleen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.contributor.departmentEarth Science and Engineering Programen
dc.contributor.departmentEarth Sciences and Engineering Programen
dc.contributor.departmentEnvironmental Science and Engineering Programen
dc.identifier.journalGeophysicsen
dc.contributor.institutionUniversity of Utah, Department of Geology and Geophysics, Salt Lake City, UT, United Statesen
kaust.authorDai, Weien
kaust.authorSchuster, Gerard T.en
kaust.authorWang, Xinen
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