Local Directional and Uncoherent Seismic Noise Filtering with Oversampled Filter Banks

Seismic data are subject to different kinds of unwanted perturbations. These random or organised noises, which can be acquisition or processing related for instance, may disturb geophysical interpretations and thwart attempts at automated processing methods. Since the relative features (e.g. amplitude, spectrum) of the signals of interest and the noises may vary locally, signal and noise separation is obtained by a local data-driven filtering with two or three-dimensional oversampled complex filter banks. Filter banks in general decompose the noisy data onto frequency bands and directions on restricted subregions (sub-images or sub-volumes), acting like a local FK with improved properties. The transforms studied in this work present sub-regions smooth overlapping, to avoid tiling effects while allowing signal reconstruction from the transformed domain. The proposed methodology uses limited redundancy filtering that both yield enhanced noise robustness (due to oversampling) and tractable 2D or 3D processing, since they are optimized to limit the redundancy cost. Coupling those redundant transforms with a processing method designed to detect and compute locally dominant directions, and to remove unwanted directions and random noise, leads to good visual results. Tests were performed on 2D and 3D seismic data.