Application of Fuzzy Decision Trees to Reservoir Recognition

Abstract

This chapter reports a real application of fuzzy decision tree to a reservoir recognition in the logging area for oilfield exploration. Reservoir fluid recognition is an important but difficult task in providing a comprehensive explanation for logging. A good recognition method can provide reliable evidence for building a standard of explanation in a region. Since there is much vagueness in the reservoir fluid recognition and there are considerable differences of geological structure in different regions, it is very difficult to establish a uniform mathematical model to recognize the reservoir. The commonly used methods for reservoir recognition include empirical formula, synthetic evaluation, fuzzy clustering, etc. Unfortunately, these methods fail to meet many applications’ requirements. For example, the empirical formula and synthetic evaluation methods could not handle fuzzy or vague data while the fuzzy clustering could not give a good recognition of oil-water layer. By applying the fuzzy decision tree induction method to the problem of reservoir recognition in an oilfield of northern China, we find the recognition results encouraging.