FUSION BASED CLASSIFICATION METHOD AND ITS APPLICATION

Classification algorithms have many applications both in exploration and production seismology. Many classification algorithms have been reported in the literature. However, for facies identification, lithology/fluid prediction etc, improper choice of an algorithm and parameters for a specific problem will create incorrect classification results. Here, we elaborate on some of these issues and propose a new method based on combining multiple classifiers with Dempster-Shafer theory (DS) that increases the accuracy of classification. The philosophy of our approach is that different classifiers offer complementary information about the patterns to be classified. Thus combining classifiers in an efficient way can achieve better classification results than a single classifier alone can. The effectiveness of this method is demonstrated with a real well log data from North Sea.