Plane-wave least-squares reverse time migration for rugged topography

Abstract

We present a method based on least-squares reverse time migration with plane-wave encoding (P-LSRTM) for rugged topography. Instead of modifying the wave field before migration, we modify the plane-wave encoding function and fill constant velocity to the area above rugged topography in the model so that P-LSRTM can be directly performed from rugged surface in the way same to shot domain reverse time migration. In order to improve efficiency and reduce I/O (input/output) cost, the dynamic encoding strategy and hybrid encoding strategy are implemented. Numerical test on SEG rugged topography model show that P-LSRTM can suppress migration artifacts in the migration image, and compensate amplitude in the middle-deep part efficiently. Without data correction, P-LSRTM can produce a satisfying image of near-surface if we could get an accurate near-surface velocity model. Moreover, the pre-stack P-LSRTM is more robust than conventional RTM in the presence of migration velocity errors.

Regularized least-squares migration of simultaneous-source seismic data with adaptive singular spectrum analysis

“…Least-squares migration (LSM) is able to suppress the migration artifacts and produce high-quality images (Nemeth et al 1999 ; Tang and Biondi 2009 ; Dai and Schuster 2013 ; Li et al 2014 , 2015a ; Liu and Li 2015 ; Huang et al 2013 , 2015a ). However, the computational cost of LSM is high as it is solved by gradient-based optimization schemes (Huang et al 2015b ; Huang and Zhou 2015 ; Li et al 2016a ). The computational efficiency and imaging quality can be improved by incorporating some sort of regularization into the LSM (Wang et al 2009 ; Liu et al 2013 ; Wang 2013 ; Li et al 2015b ; Lu et al 2015 ).…”