Abstract:
Abstract： The traditional method of predicting open flow potential is calculated through gas test operation， which has long operation cycle and large capital investment. However， in the early stage of gas exploration and development， a large number of parameters obtained from logging can effectively reflect the advantages and disadvantages of reservoir properties. In this paper， a relationship model between logging parameters and open flow potential is established. First， K-means clustering analysis method is used to analyze and select， preprocess and transform logging parameters. Then， the improved ID3 algorithm is used to design the open flow potential prediction method， to construct the open flow potential decision tree and form the open flow potential decision scheme for the target interval of a single well. The experiment results show that this method can effectively predict open flow potential and single well productivity by using logging parameters. Through omitting the gas test operation， we can speed up the gas field production schedule， reduce the development cost， and improve the economic benefits of gas field development.

Key words: Key words： K-means, open flow potential, cluster analysis, decision tree, ID3