Decision-Making Technology of Well Candidates Selection in In-depth Profile Control Based on Projection Pursuit Clustering Model

Abstract

Due to the long-term waterflooding, thief zone is widely developed in the mature field. As a result, the oil production drops and the water cut rises sharply. As an effective technology to extend the economic life of mature fields, in-depth profile control can fully exploit the remaining oil and improve oil recovery. The decision-making of well selection is key to in-depth profile control measures in the oilfield. In order to solve this problem, we build several indicator sets to measure the need of in-depth profile control for the well candidates. Then we propose a projection pursuit clustering model for well candidates and use the gravitational search algorithm to find the optimal projection direction. Finally, the coefficient for decision-making is obtained based on the optimal projection direction and the technology of well candidates selection in in-depth profile control is established. We apply this method to Bei 301 block of Hailar and the prediction results are compared with the fuzzy synthesis decision-making method. The result shows that the well candidates in Bei 301 block of Hailar are divided into two categories according to their own characteristics in the projection pursuit process, that is, four wells need to take in-depth profile control measures in the nine well candidates. In the previous research, decision-making of well selection in in-depth profile control is almost based on fuzzy synthetic decision-making. In that method, the weight of indicators is determined artificially, featuring subjective nature. However, the method used for decision-making in this paper is based on the feature of well candidates and relatively objective compared with the previous method. The program execution time for these two methods shows that the one proposed in this study is more efficient and accurate. The method adopted in this study solves the artificial weighting problem in the current well selection decision-making and makes the result more objective, which can provide better guidance for the decision-making of well selection in in-depth profile control and extend the economic life of mature fields.