Adaptive f-k deghosting method based on non-Gaussianity

• The proposed method obtains the ghost parameters adaptively shot by shot.
• We use non-Gaussian criteria for ghost parameter estimation.
• We analyze the performance of different non-Gaussian criteria by experiments.

For conventional horizontal towed streamer data, the f-k deghosting method is widely used to remove receiver ghosts. In the traditional f-k deghosting method, the depth of the streamer and the sea surface reflection coefficient are two key ghost parameters. In general, for one seismic line, these two parameters are fixed for all shot gathers and given by the users. In practice, these two parameters often vary during acquisition because of the rough sea condition. This paper proposes an automatic method to adaptively obtain these two ghost parameters for every shot gather. Since the proposed method is based on the non-Gaussianity of the deghosting result, it is important to choose a proper non-Gaussian criterion to ensure high accuracy of the parameter estimation. We evaluate six non-Gaussian criteria by synthetic experiment. The conclusion of our experiment is expected to provide a reference for choosing the most appropriate criterion. We apply the proposed method on a 2D real field example. Experimental results show that the optimal parameters vary among shot gathers and validate effectiveness of the parameter estimation process. Moreover, despite that this method ignores the parameter variation within one shot, the adaptive deghosting results show improvements when compared with the deghosting results obtained by using constant parameters for the whole line.