Attenuation of random noise using advanced adaptive filters in post-stack seismic imaging

The main objective of this work is to propose a method based on adaptive filtering to reduce the random noise from post-stack seismic data. The random noise can be reduced from seismic data by stacking the traces in multiple coverage, filtering during processing or using arrays of geophones during data acquisition. Recently, several filters have been used in image processing to resolve or compensate the deficiencies of conventional filtering such as the Adaptive Median Filter and 2D Adaptive Wiener Filter. Therefore, Adaptive Median filtering has been applied widely in image processing as an advanced method compared to standard median filtering. In this study, we present a combination of the Adaptive Median Filter, 2D Adaptive Wiener Filter, and Adaptive Local Noise Reduction Filter applied to post-stacked synthetic and real seismic data. The different comparisons of resulting seismic sections and their power spectrum show that both the proposed methods of filtering improve seismic imaging of the faulted structures better than other used filters.