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dc.contributor.authorDutta, Gaurav
dc.contributor.authorGiboli, Matteo
dc.contributor.authorAgut, Cyril
dc.contributor.authorWilliamson, Paul
dc.contributor.authorSchuster, Gerard T.
dc.date.accessioned2017-03-15T07:15:27Z
dc.date.available2017-03-15T07:15:27Z
dc.date.issued2017-03-08
dc.identifier.citationDutta G, Giboli M, Agut C, Williamson P, Schuster GT (2017) Least-squares reverse time migration with local Radon-based preconditioning. GEOPHYSICS 82: S75–S84. Available: http://dx.doi.org/10.1190/GEO2016-0117.1.
dc.identifier.issn0016-8033
dc.identifier.issn1942-2156
dc.identifier.doi10.1190/GEO2016-0117.1
dc.identifier.urihttp://hdl.handle.net/10754/623005
dc.description.abstractLeast-squares migration (LSM) can produce images with better balanced amplitudes and fewer artifacts than standard migration. The conventional objective function used for LSM minimizes the L2-norm of the data residual between the predicted and the observed data. However, for field-data applications in which the recorded data are noisy and undersampled, the conventional formulation of LSM fails to provide the desired uplift in the quality of the inverted image. We have developed a leastsquares reverse time migration (LSRTM) method using local Radon-based preconditioning to overcome the low signal-tonoise ratio (S/N) problem of noisy or severely undersampled data. A high-resolution local Radon transform of the reflectivity is used, and sparseness constraints are imposed on the inverted reflectivity in the local Radon domain. The sparseness constraint is that the inverted reflectivity is sparse in the Radon domain and each location of the subsurface is represented by a limited number of geologic dips. The forward and the inverse mapping of the reflectivity to the local Radon domain and vice versa is done through 3D Fourier-based discrete Radon transform operators. The weights for the preconditioning are chosen to be varying locally based on the relative amplitudes of the local dips or assigned using quantile measures. Numerical tests on synthetic and field data validate the effectiveness of our approach in producing images with good S/N and fewer aliasing artifacts when compared with standard RTM or standard LSRTM.
dc.description.sponsorshipG. Dutta would like to thank King Abdullah University of Science and Technology (KAUST) for funding his graduate studies. The authors are grateful to TOTAL E&P France for permission to publish this work. We also thank the associate editor K. Innanen and the three anonymous reviewers for their helpful comments and suggestions. The plots for this paper have been prepared using the Madagascar open-source software package.
dc.publisherSociety of Exploration Geophysicists
dc.relation.urlhttp://library.seg.org/doi/abs/10.1190/geo2016-0117.1
dc.rightsArchived with thanks to GEOPHYSICS
dc.titleLeast-squares reverse time migration with local Radon-based preconditioning
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.journalGEOPHYSICS
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionTOTAL Exploration and Production, CSTJF, Pau, , France
kaust.personDutta, Gaurav
kaust.personSchuster, Gerard T.
refterms.dateFOA2018-06-13T14:07:15Z
dc.date.published-online2017-03-08
dc.date.published-print2017-03


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