A wave‐equation migration velocity analysis approach based on the finite‐frequency sensitivity kernel

Abstract

Based on the finite-frequency sensitivity theory, we present a migration velocity analysis method. The finite-frequency sensitivity kernel is used to link the observed residual moveout and the velocity perturbations in the migration velocity model. The new approach is a wave-equation based method which naturally incorporates the wave phenomena and is best teamed with the wave-equation based migration for velocity analysis. This paper is targeted to solve some important issues in using this approach in velocity updating process, e.g., the calculation and storage of huge amount of sensitivity kernels, the partition and interpolation of velocity model and the iteration process. Numerical examples are used to demonstrate the updating process.

On the gradient artifacts in migration velocity analysis based on differential semblance optimization

“…Compared with ray based tomography, wave equation MVA is band limited, stable when the geological structure is complicated, and potentially can provide better resolution (Sava and Biondi, 2004). Wave-equation based MVA has been widely studied and several approaches and variants have been proposed (Shen et al, 2003(Shen et al, , 2005Sava and Biondi, 2004;Albertin et al, 2006;Fliedner et al, 2007;Xie and Yang 2008;, Fei and Williamson, 2009, Yang and Sava, 2009, He et al, 2009). Among the different approaches, DSO-MVA is appealing because it does not require picking, and the objective function has been shown theoretically to be convex.…”

Velocity tomography based on turning waves and finite-frequency sensitivity kernels

“…Several techniques can be used to reduce the storage space. Here, following Xie and Yang (2008b), we first partition the integral in equation 2into the summation of integrals in small rectangular cells…”