Enhancing Static Interpretations Using Histogram Equalisation and Edge Detection

Abstract In this paper, we introduce a workflow to improve stratigraphic and lithologic interpretations by improving static analyses of seismic data using a histogram equalization technique. In particular, we demonstrate the use of histogram equalization followed by edge detection to enhance geological features such as faults, fractures, and channels. Post-stack and migrated seismic data are often subjected to automatic gain control (AGC) to increase the visibility of low-strength reflections. Unfortunately, AGC can mask stratigraphic details by drastically changing relative amplitude levels and by producing low-amplitude "shadow zones" near strong reflectors and near unconformity terminations. Histogram equalization (HE) was originally developed for image processing but serves a useful purpose for seismic analysis. Unlike AGC, histogram equalization preserves subtle stratigraphic features and does not create "shadow-zones" beneath strong reflectors. Histogram equalization enhances the sharpness of stratigraphic features, thereby allowing edge detection algorithms to more effectively highlight discontinuities in the amplitude level even if the change is small.