Ground‐roll suppression from deep crustal seismic reflection data using a wavelet‐based approach: A case study from western Canada
Seismic reflection data sets recorded on land are often contaminated by coherent ground‐roll noise generated by the propagation of dispersive waves along the free surface. For crustal‐scale investigations, this ground‐roll contamination can be particularly harmful as the higher amplitude, low‐frequency noise overwhelms low‐frequency signals coming from deep reflectors. Consequently, conventional ground‐roll suppression techniques which rely on frequency separation of ground roll from signal become ineffective for crustal studies. This paper presents the successful use of a new 2D wavelet method based on frame theory (physical wavelet frame denoising) in removing ground roll from a deep 3D reflection data set intended for the study of upper crustal Precambrian mafic sills in southwestern Alberta, Canada.