Swell Noise Suppression by Wiener Prediction Filter

Abstract The conventional method to remove swell noise from raw seismic data is band–pass filtering (BPF). It ideally removes whole low frequency band of the spectral content, which results in a total loss of the amplitudes concerning the low frequency reflections from deeper reflectors, and hence lower resolution in the deeper reflection events. The procedure described here attenuates swell noise from seismic data while preserving the reflection amplitudes at low frequency band. The proposed Wiener prediction filter (WPF) method is used to estimate the swell noise embedded in the raw marine seismic data and then the estimated noise is subtracted from shots by a trace–by–trace basis. It is observed that the deeper reflections have significantly higher amplitudes and show better trace–by–trace consistency in the final migration sections obtained by the WPF application. The WPF method removes most of the swell noise and may be an alternative filtering technique to the conventional BPF method. It can be used with high resolution marine seismic data which may have weaker reflection amplitudes from deeper reflectors. It also improves the lateral continuity of the events which may be useful for auto–picking tools such as automatic event tracking. We propose that the method can effectively be used to remove any type of coherent noise providing that a suitable noise model can be determined from the data itself.