Vertical transversely isotropic elastic least-squares reverse time migration based on elastic wavefield vector decomposition

Anisotropic elastic reverse time migration (RTM) is a prom-ising technique for imaging complex oil and gas reservoirs. However, the migrated images often suffer from low spatial res-olution, migration artifacts, wave-mode crosstalk, and unbal-anced amplitude response. Conventional vertical transversely isotropic elastic least-squares reverse time migration (VTI-elas-tic LSRTM) defines stiffness parameter perturbations as elastic images, which have different physical meanings from VTI-elas-tic RTM images. We have developed a VTI-elastic LSRTM method based on elastic wavefield vector decomposition that is a natural extension of VTI-elastic RTM. More specifically, our method applies least-squares inversion to VTI-elastic RTM and defines the compressional-and shear-wave reflectiv-ity as elastic images (PP, PS, SP, and SS images). When com-puting the elastic images, we decompose the elastic wavefields into compressional and shear wavefields and cross-correlate the corresponding wave modes. We derive the reverse time demi-gration operator by taking the adjoint of the RTM operator. Us-ing the migration and demigration operators, we formulate the VTI-elastic LSRTM as a linear inverse problem with the least -squares criterion. The conjugate gradient method is used to solve the optimization problem. Three numerical examples are presented to test the feasibility of our method. The VTI-elas-tic LSRTM images have higher resolution, fewer migration ar-tifacts and wave-mode crosstalk, and improved amplitude response when compared with VTI-elastic RTM images.