Using Histogram Equalization and Edge Detection to Enhance Stratigraphic

Abstract

Abstract In this paper we introduce a workflow to improve stratigraphie and lithologie interpretations. 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 is 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 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. The effect of histogram equalization followed by edge detection is demonstrated using 128-fold 3D seismic land data (Figure 1). Using this data we analyze the ability to map a fluvial channel of noticeable thickness. The channel is the result of Hirnantain (Late Ordovician) glaciations subjected to a local tectonic uplift. A time slice of histogram equalized data shows the channel boundary more clearly than the AGC-processed version. Figure 1 E-W line extracted from 3D seismic data shows the channel system.