The use of Continuous Wavelet Transform for Ground Roll attenuation

In seismic reflection land data, Ground-Roll (GR) constitutes an high amplitude and low frequency noise that obliterates the reflected events decreasing the quality of the seimograms and, as a consequence, of the final stack section. Many processing methods are adopted to reduce the GR noise but the dispersive nature of the surface waves makes it difficult to design an optimal window for classical 1D filtering approaches based on short time Fourier Transform or for 2D approaches based on singular value decomposition. Also, 2D methods such as the f-k filtering can generate artifacts or can give poor results if the surface waves are aliased or if the traces are not regularly spaced. An additional difficulty is that the characteristics of the surface waves change depending on the near surface properties so that their features can vary drastically along the seismic line. This, requires to adapt the parameters of the processing operators according to the changing characteristics of the GR. Actual and more sophisticated methods consist in the estimation of the surface waves followed by adaptive subtraction but they are computationally expensive and time consuming. Source and/or receiver array design still remains the less invasive approach to reduce the surface waves noise and, for near surface survey, Tognarelli and Stucchi (2016) proposed an acquisition scheme that permits to perform different array simulations in the processing lab. Arrays are not able to remove the GR, they are effective to partially reduce the GR and at improving the signal window. In the last years, the continuous wavelet transform (CWT) (Daubechies, 1990,1992) has been used in a wide range of geophysical and geological disciplines such as seismic, oceanography, and climatology (Torrence and Compo, 1998, Lau and Weng,1995, Deighan and Watts,1997, Sinha et al., 2005, Farge, 1992, Sadowsky, 1996), but also in other contexts like image processing, music and medicine fields (Mallat, 2009). In general, the CWT analysis can be applied successfully to all time or spatial series that represent a non-stationary process, with the aim of investigating the spectral components and how they change over time and/or space. In this work, the CWT is used to analyse the shot gathers from a near surface seismic land survey and an intuitive filtering procedure, applied in the wavelet domain and aimed at attenuating the GR, is presented. The improvement of the data quality is shown and discussed for the shot gathers and finally for the stack section.