Eliminating above-surface diffractions from ground-penetrating radar data using iterative Stolt migration

Above-surface diffractions (ASDs) received by unshielded ground-penetrating radar (GPR) antennas are known to contaminate subsurface reflections and diffractions. Existing ASD-removal methods either leave relatively strong residual ASDs within subsurface reflections or attenuate them excessively. We have developed an iterative migration-based ASD-removal method to address this issue that separates ASDs from subsurface reflections via surgical mute. First, we isolate ASDs within the GPR profile using an optimal window function, generated using the focal center of ASDs within the migrated domain. The remainder signifies the zeroth-order separation of subsurface reflections. Second, we perform Stolt migration on the isolated ASDs using the speed of light in air. Then, we mute out the regions dominated by ASDs from the migration results, characterized by highly focused ASDs that are well separated from the majority of subsurface reflections. Following that, we demigrate the separated ASDs and subsurface reflections back to the unmigrated domain using the speed of light in air. Next, we combine the demigrated subsurface reflections with the zeroth-order subsurface reflections, thereby completing the first iteration of the separation process. The entire aforementioned process is then repeated twice on the residual data to obtain further residual subsurface reflections from ASDs, using a lower velocity and a higher velocity in sequence. Our method is verified to suppress ASDs more effectively than existing approaches by retaining a greater proportion of subsurface reflections, and its residual error is negligible. It is robust with respect to energy levels, window widths of ASDs, and clustered ASDs.