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Production Performance Appraisal Rating for Reservoir Management Units Based on Fuzzy Clustering
Author(s) -
Anqi Li,
Yan-Rong Chang,
Xinhai Kong
Publication year - 2012
Publication title -
advances in fuzzy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 19
eISSN - 1687-711X
pISSN - 1687-7101
DOI - 10.1155/2012/134068
Subject(s) - delicacy , production (economics) , computer science , topsis , fuzzy logic , operations research , euclidean distance , performance appraisal , task (project management) , data mining , mathematics , artificial intelligence , engineering , economics , systems engineering , geology , paleontology , macroeconomics , management
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

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