Slope-tomography preconditioned by an image guided smoothing filter

Stereotomography is a distinctive tomographic method. Nonlinear slope tomography, a variation of stereotomography, which is regarded as another robust solution for velocity model building. In this abstract, a revised slope tomography preconditioned by an image guided smoothing filter is presented thus the resolution of the slope tomography is significantly improved. Compared with the classic non-linear slope tomography, we revise the classic slope tomography work-flow by (1) inserting a pre-stack depth migrated (PSDM) based on a limited number of small offsets sections and (2) use slope (or horizontal slowness) observed at the surface as the only data component. The reason to add a PSDM in the classical work-flow is that we believe extracting preconditioner based on the depth image from the real data will be a more stable approach. The reason to use slope as the only data component is that we believe after a kinematic re-migration to re-modeling the ray-path in the updated model, the slope residual in the updated model is also precisely predicted. Thus performing a slope tomography is a more natural choice. The synthetic and real data examples demonstrated the correctness of the inversion algorithm and the robustness of the revised work-flow.