KAUST DepartmentEarth Science and Engineering Program
Physical Sciences and Engineering (PSE) Division
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AbstractWe propose sparse least-squares reverse time migration (LSRTM) using seislets as a basis for the reflectivity distribution. This basis is used along with a dip-constrained preconditioner that emphasizes image updates only along prominent dips during the iterations. These dips can be estimated from the standard migration image or from the gradient using plane-wave destruction filters or structural tensors. Numerical tests on synthetic datasets demonstrate the benefits of this method for mitigation of aliasing artifacts and crosstalk noise in multisource least-squares migration.
CitationGaurav Dutta and Gerard T. Schuster (2015) Sparse least-squares reverse time migration using seislets. SEG Technical Program Expanded Abstracts 2015: pp. 4232-4237. doi: 10.1190/segam2015-5869595.1
PublisherSociety of Exploration Geophysicists