Abstract
Methods for segmenting stacked seismic data into zones of common signal character based on texture analysis are described. Their performance is demonstrated on a line of seismic data from the Gulf of Mexico that had been manually segmented. Two segmentation methods are described. The first is a template matching scheme that matches previously selected data templates with a block of pixels. The second uses statistics determined by examining the run-length of seismic reflection events. The run-length method is extended, through a decision process called the RESOLVER, to incorporate heuristic rules to influence the segmentation. A comparison is made between the automatic segmentations of the section and a manual interpretation.
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