Efficient and accurate edge-preserving smoothing for 3D hexagonally sampled seismic data

The automatic detection of geological features such as faults and channels is a challenging problem in today's seismic exploration industry. Edge detection filters are generally applied to locate features. It is desirable to reduce noise in the data before edge detection. The application of smoothing or low-pass filters results in noise suppression, but this causes edge blurring as well. Edge-preserving smoothing is a technique that results in simultaneous edge preservation and noise suppression. Until now, edge-preserving smoothing has been carried out on rectangular sampled seismic data. In this paper, an attempt has been made to detect edges by applying edge-preserving smoothing as a pre-processing step in the hexagonally sampled seismic-data spatial domain. A hexagonal approach is an efficient method of sampling and has greater symmetry than a rectangular approach. Here, spiral architecture has been employed to handle the hexagonally sampled seismic data. A comparison of edge-preserving smoothing on both rectangular and hexagonally sampled seismic data is carried out. The data used were provided by Saudi Aramco. It is shown that hexagonal processing results in well-defined edges with fewer computations.