Deghosting for variable depth streamer based on super-Gaussianity

Summary It is well known that seismic signal is of super-Gaussian distributions, i.e., sparse signal. In this paper, we present a super-Gaussianity based deghosting method (SGDG) for variable depth streamer in time-space domain. In our method, the ghosts received by variable depth streamer are modeled by two time-space variant parameters, one is the sea surface reflection coefficient, and the other is the time-shift between the upgoing wave and its ghost. In SGDG method, these two parameters are estimated in time-space domain by a 2D scanning method, which is based on maximization of super-Gaussianity of the deghosting outputs. According to the estimated parameters, the selected deghosting outputs are merged together to obtain the final result. Applications of the proposed method on the synthetic and real seismic data give some promising results.