High-order residual moveout correction with global optimization in local time windows

Abstract

Residual moveout (RMO) correction is significant for optimizing the common image gathers (CIGs) and migration stacked sections, which is a vital step in seismic data processing. The conventional RMO correction methods flatten the migrated gathers by inverse normal moveout and then pick up the velocity parameters, which require high labor of manual picking with low efficiency. The existing high-order RMO correction methods by scanning technology need a bispectral picking process. To address these issues, we propose a novel high-order RMO correction method based on a crosscorrelation-based objective function with global optimization in local time windows. The selected time windows covering the reflected events in the stacked section are used for parameter estimation. Then the very fast simulated annealing (VFSA) algorithm is used to simultaneously invert the two effective parameters (migration velocity and anellipticity anisotropic parameter) with the local CIGs in the time window, which has relatively high computational efficiency. The Hess model example test results show that the proposed method can effectively deal with the RMO problem in the case of anisotropic media, and the developed high-order RMO correction based on anisotropic assumption significantly improved the imaging performance compared to the conventional isotropic RMO correction methods, especially for steep structures. The application to a real 3D land data set further confirms the effectiveness and practicability of the proposed method.