Sparsity Promoting Least Squares Migration for Laterally Inhomogeneous Media

The aim of this correspondence is to introduce a sparsity promoting least squares migration method using a generalized F-K migration operator that can compensate for lateral velocity change. In addition with help of sparse regularization the method finds a non-smooth model that has a higher resolution compared to a typical least squares migration algorithm and reduces the artifacts. The efficiency of the method is tested on synthetic seismic data.