Ground-roll noise suppression in land surface seismic data using a wavenumber-adaptive bandpass filter

Land surface seismic data contain strong and coherent ground-roll noise. It is impossible to use such noise-corrupted data for waveform fitting-based imaging and inversion. We design a novel wavenumber-adaptive bandpass filter to suppress this noise without hurting the signal. This filter adaptively exploits both characteristics of the lower frequency and the smaller velocity of the ground-roll noise than those of the signal. Consequently, this filter can effectively differentiate the ground-roll noise from the signal. We validate this new method using surface seismic data acquired at two geothermal sites. Our results demonstrate that our wavenumber-adaptive bandpass filtering method successfully suppress the strong and coherent ground-roll noise in land seismic data. This leads to improved subsurface images obtained by reverse-time migration (RTM). This novel filter enables us to use the processed seismic data for waveform fitting-based imaging (least-squares reverse-time migration) and full-waveform inversion.