Sensitivity-kernel-based tomographic migration velocity analysis using reverse time migration angle-image gathers

Abstract

Sensitivity-kernel-based tomographic migration velocity analysis (TMVA) provides a means to better update the migration velocity model in complex media. For actual seismic data with finite-frequency bandwidth, migration velocity updated from wave-equation-based tomography is more suitable and robust than ray-based tomography for images obtained from reverse time migration (RTM). Depth residuals in the RTM-extracted angle-image gathers offer a reliable source of velocity information. We have developed cost-effective means of calculating the angle-domain sensitivity kernel and incorporated it into the TMVA approach using RTM angle-image gathers. The angle-domain sensitivity kernels are used to convert the depth residuals from RTM angle-image gathers into velocity perturbations, which were then used to refine the velocity model. We derived an approximate analytical residual moveout function for measuring depth residuals of the RTM angle-image gather in isotropic media and also devised a workflow for sensitivity-kernel-based TMVA. The workflow maintains the simplicity of ray-based tomography by replacing the rays with the more accurate angle-domain sensitivity kernels. We determined the capability of this method in updating migration velocity with the 2D Sigsbee2 model and the 3D SEAM model. Our method significantly improved the quality of the migrated depth image and flattened the RTM angle-image gathers.