Structure-oriented Gaussian filter for seismic detail preserving smoothing

This paper presents a structure-oriented Gaussian (SOG) filter for reducing noise in 3D reflection seismic data while preserving relevant details such as structural and stratigraphic discontinuities and lateral heterogeneity. The Gaussian kernel is anisotropically constructed based on two confidence measures, both of which take into account the regularity of the local seismic structures. So that, the filter shape is well adjusted according to different local geological features. Then, the anisotropic Gaussian is steered by local orientations of the geological features (layers) provided by the Gradient Structure Tensor. The potential of our approach is presented through a comparative experiment with seismic fault preserving diffusion (SFPD) filter on synthetic blocks and an application to real 3D seismic data.