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dc.contributor.authorHuang, Yunsong
dc.contributor.authorDutta, Gaurav
dc.contributor.authorDai, Wei
dc.contributor.authorWang, Xin
dc.contributor.authorSchuster, Gerard T.
dc.contributor.authorYu, Jianhua
dc.date.accessioned2015-03-17T13:45:50Z
dc.date.available2015-03-17T13:45:50Z
dc.date.issued2014-09
dc.identifier.citationMaking the most out of least-squares migration 2014, 33 (9):954 The Leading Edge
dc.identifier.issn1070-485X
dc.identifier.issn1938-3789
dc.identifier.doi10.1190/tle33090954.1
dc.identifier.urihttp://hdl.handle.net/10754/346780
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.
dc.publisherSociety of Exploration Geophysicists
dc.relation.urlhttp://library.seg.org/doi/abs/10.1190/tle33090954.1
dc.rightsArchived with thanks to The Leading Edge
dc.titleMaking the most out of least-squares migration
dc.typeArticle
dc.contributor.departmentCenter for Subsurface Imaging and Fluid Modeling
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalThe Leading Edge
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionBP, Houston, Texas Area
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personHuang, Yunsong
kaust.personDai, Wei
kaust.personSchuster, Gerard T.
kaust.personDutta, Gaurav
kaust.personWang, Xin
refterms.dateFOA2018-06-14T07:30:01Z


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