Seismic Data Analysis Based on Fuzzy Clustering

Seismic data contain a large amount of geological information, clustering analysis is an effective method to analyze seismic data; it has already become a valid analytical tool for lithology prediction and reservoir characterization; unsupervised fuzzy clustering based on fuzzy c-means algorithm is a very important technology in seismic data analysis, it is capable of creating useful character mappings of the data by reducing a large number of attributes down to one that can be visualized on a map; this kind of method can look for the center of each cluster and membership grades which belong to corresponding cluster; model test and actual application have shown the validity of this method