Automatic source localization of diffracted seismic noise in shallow water

Abstract

We evaluated an automatic source localization approach for diffracted seismic noise (DSN) attenuation based on apex recognition. The potential DSNs in each shot gather were first detected by identifying their apexes. Then, the positions of these detected apexes were used to calculate the source locations of their corresponding DSNs. After that, according to the distribution of the source locations obtained in all shot gathers in one seismic line, we removed some false detected DSNs and further improved the source location estimates of the remaining ones. By assuming that the source location of one DSN is fixed or slowly changed during the seismic data acquisition, for a truly existing DSN, its multiple source location estimates, which are obtained from different streamers in multiple shot gathers, should focus. Therefore, a clustering algorithm was applied to obtain the source location estimates of the final selected DSNs and remove the false recognized DSNs at the same time. To verify the source localization results obtained, we suppressed these DSNs by flattening them along their trajectories and extracting them by multichannel filters, similar to other existing methodologies. A real 3D marine data example demonstrated that the proposed method obtains some promising results for attenuation of the DSNs.