Fusion Based Classification Method And Its Application

Abstract

Summary Classification algorithms have many applications both in exploration and production seismology. Many classification algorithms have been reported in the literature, such as, seismic facies identification, lithology/fluid prediction, etc. However, improper choice of an algorithm and parameters for a specific problem will create incorrect classification results. Here, we elaborate on some of these issues. Further, we propose combing multiple classifiers with DempsterShafer theory (DS) to increase the accuracy of the classification. The philosophy of our approach is that different classifiers may offer complementary information about the patterns to be classified, combining classifiers in an efficient way can achieve better classification results than any single classifier. The effectiveness of this method is demonstrated with a synthetic data test.