TY - JOUR
T1 - Sparse least-squares reverse time migration using seislets
AU - Dutta, Gaurav
AU - Schuster, Gerard T.
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2015/8/19
Y1 - 2015/8/19
N2 - We 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.
AB - We 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.
UR - http://hdl.handle.net/10754/593141
UR - http://library.seg.org/doi/10.1190/segam2015-5869595.1
UR - http://www.scopus.com/inward/record.url?scp=85011647492&partnerID=8YFLogxK
U2 - 10.1190/segam2015-5869595.1
DO - 10.1190/segam2015-5869595.1
M3 - Article
SN - 1949-4645
VL - 34
SP - 4232
EP - 4237
JO - SEG Technical Program Expanded Abstracts 2015
JF - SEG Technical Program Expanded Abstracts 2015
ER -