Imaging strategies using surface-related multiples for incomplete seismic data

Abstract

Seismic surveys are often restricted due to finite number of receivers as well as missing near and far offsets, thus affecting the illumination of subsurface. Surface-related multiples are known to carry valuable information, making them indispensable for dealing with these cases of finite illumination. As the use of surface-related multiples is gaining prominence in imaging methods, it has become crucial to find the best way of exploiting information from them. Usually, these imaging methods image surface-related multiples by re-injecting the total data as a downgoing wavefield, hence banking heavily on a dense receiver configuration making it sensitive to missing data. In this paper we discuss different imaging strategies using surface-related multiples in case of missing offset data. To overcome the effect of incomplete receiver data, we also suggest an addition to the current migration methods that involves a non-linear inversion approach, where all surface multiples are built from the original source field. This method gives better results compared to the linear inversion methods and mitigate the effect of incomplete data substantially.