Seismic image enhancement by double-weighted stacking

Normal-moveout velocity analysis using semblance spectrum and common-midpoint stacking after normal-moveout correction are two indispensable procedures in seismic reflection data processing, especially for random noise attenuation, velocity model estimation, and imaging quality enhancement. During this process, weighting functions have been frequently used to improve the resolution of semblance and the performance of stacking. In this paper, the interactive relationship between semblance and stacking allows a new method of double-weighted stacking to be created. This method applies the same local-similarity-weighting function to the calculation of both semblance and stacking, aiming to enhance the final stacked image sections. The synthetic and field data numerical experiments have demonstrated that our new approach enhances the signal-to-noise ratio and the reflection-event continuity compared with conventional processing flows