Production Performance Appraisal Rating for Reservoir Management Units Based on Fuzzy Clustering

Abstract

In view of the existing situation of oilfield development, one kind of method to evaluate the production performance of reservoir management units (RMUs) was presented in this paper. Among the commonly used indicators of oilfield development, select 12 indicators from the three aspects of production task, production technology, and reservoir development. According to the principle of fuzzy analytic hierarchy process (FAHP), this paper introduced one kind of new method to get the weights of indicators. By means of the method of TOPSIS, it is easy to obtain the rankings for all the RMUs through calculating the weighted Euclidean distance between each RMU and the positive or negative ideal RMU. Considering the gap between the differences in RMUs, the production performance appraisal ratings of RMUs are determined by fuzzy clustering. This evaluation method could constantly improve the management level of reservoir units and deepen the delicacy management of oilfield development.

Application of Data Mining in the Field of Human Resource Management: A Review

“…Clustering analysis [25] used fuzzy clustering methods to evaluate oilfield companies' reservoir management units (RMUs). [26] used information entropy with improved clustering algorithm to process high-dimensional data and consistent data in discrete manufacturing quality management systems.…”