F-xy domain morphological filtering for 3D seismic erratic noise suppression

Seismic signal is always contaminated by coherent and incoherent noise. Conventional incoherent noise suppression methods use the statistical difference between the signal and incoherent noise to distinguish between them. These methods are effective for random noise but are limited or even invalid for erratic noise because the latter far from satisfies the statistical assumption behind the conventional techniques. The presented study proposes a novel mathematical morphology based technique for attenuating both erratic and random noise. In this technique, 2-D mathematical morphological filtering (MMF) is implemented in each frequency slice of the 3-D seismic data cube (f-xy domain) to detect the morphological scale difference between the signal and noise. The proposed technique is compared with state-of-the-art low-rank/sparse representation based techniques by using both synthetic and real data sets. The various examples demonstrate that the proposed f-xy domain 2-D MMF method can preserve more useful signal and suppress more incoherent noise (erratic and random noise) than the low-rank and sparse representations based methods.