Making the most out of least-squares migration

Handle URI:
http://hdl.handle.net/10754/346780
Title:
Making the most out of least-squares migration
Authors:
Huang, Yunsong; Dutta, Gaurav ( 0000-0002-2024-1683 ) ; Dai, Wei; Wang, Xin; Schuster, Gerard T. ( 0000-0001-7532-1587 ) ; Yu, Jianhua
Abstract:
Standard migration images can suffer from (1) migration artifacts caused by an undersampled acquisition geometry, (2) poor resolution resulting from a limited recording aperture, (3) ringing artifacts caused by ripples in the source wavelet, and (4) weak amplitudes resulting from geometric spreading, attenuation, and defocusing. These problems can be remedied in part by least-squares migration (LSM), also known as linearized seismic inversion or migration deconvolution (MD), which aims to linearly invert seismic data for the reflectivity distribution. Given a sufficiently accurate migration velocity model, LSM can mitigate many of the above problems and can produce more resolved migration images, sometimes with more than twice the spatial resolution of standard migration. However, LSM faces two challenges: The computational cost can be an order of magnitude higher than that of standard migration, and the resulting image quality can fail to improve for migration velocity errors of about 5% or more. It is possible to obtain the most from least-squares migration by reducing the cost and velocity sensitivity of LSM.
KAUST Department:
Earth Science and Engineering Program; Physical Sciences and Engineering (PSE) Division
Citation:
Making the most out of least-squares migration 2014, 33 (9):954 The Leading Edge
Publisher:
Society of Exploration Geophysicists
Journal:
The Leading Edge
Issue Date:
Sep-2014
DOI:
10.1190/tle33090954.1
Type:
Article
ISSN:
1070-485X; 1938-3789
Additional Links:
http://library.seg.org/doi/abs/10.1190/tle33090954.1
Appears in Collections:
Articles; Physical Sciences and Engineering (PSE) Division; Earth Science and Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorHuang, Yunsongen
dc.contributor.authorDutta, Gauraven
dc.contributor.authorDai, Weien
dc.contributor.authorWang, Xinen
dc.contributor.authorSchuster, Gerard T.en
dc.contributor.authorYu, Jianhuaen
dc.date.accessioned2015-03-17T13:45:50Zen
dc.date.available2015-03-17T13:45:50Zen
dc.date.issued2014-09en
dc.identifier.citationMaking the most out of least-squares migration 2014, 33 (9):954 The Leading Edgeen
dc.identifier.issn1070-485Xen
dc.identifier.issn1938-3789en
dc.identifier.doi10.1190/tle33090954.1en
dc.identifier.urihttp://hdl.handle.net/10754/346780en
dc.description.abstractStandard migration images can suffer from (1) migration artifacts caused by an undersampled acquisition geometry, (2) poor resolution resulting from a limited recording aperture, (3) ringing artifacts caused by ripples in the source wavelet, and (4) weak amplitudes resulting from geometric spreading, attenuation, and defocusing. These problems can be remedied in part by least-squares migration (LSM), also known as linearized seismic inversion or migration deconvolution (MD), which aims to linearly invert seismic data for the reflectivity distribution. Given a sufficiently accurate migration velocity model, LSM can mitigate many of the above problems and can produce more resolved migration images, sometimes with more than twice the spatial resolution of standard migration. However, LSM faces two challenges: The computational cost can be an order of magnitude higher than that of standard migration, and the resulting image quality can fail to improve for migration velocity errors of about 5% or more. It is possible to obtain the most from least-squares migration by reducing the cost and velocity sensitivity of LSM.en
dc.publisherSociety of Exploration Geophysicistsen
dc.relation.urlhttp://library.seg.org/doi/abs/10.1190/tle33090954.1en
dc.rightsArchived with thanks to The Leading Edgeen
dc.titleMaking the most out of least-squares migrationen
dc.typeArticleen
dc.contributor.departmentEarth Science and Engineering Programen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.identifier.journalThe Leading Edgeen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionBP, Houston, Texas Areaen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorHuang, Yunsongen
kaust.authorDai, Weien
kaust.authorSchuster, Gerard T.en
kaust.authorDutta, Gauraven
kaust.authorWang, Xinen
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