Oil production prediction with neural network method

被引:0
作者
Liu, Haohan [1 ]
Li, Wei [1 ]
Zhang, Songlin [1 ]
机构
[1] Sichuan Coll Architectural Technol, Deyang 618000, Peoples R China
来源
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND SERVICE SYSTEM (CSSS) | 2014年 / 109卷
关键词
correlation degree analysis; neural network; prediction;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Many kinds of method can be used to predict oil production, and the neural network method is one of the most basic methods to predict oil production. In this study a modified neural network method is proposed to predict oil production in oil field. A fuzzy cluster analysis is introduced to determine the major influencing factors and obtain non-dimensional data; a proper kernel function of the neural network structure is chosen to establish the relational expression of site variables and fit the relational expression of weight. A new predicting method based on the cluster analysis is proposed to predict the oil production. Good predicting results are obtained by introducing this new method to the Cong-D block of certain block faulted oilfield of China.
引用
收藏
页码:143 / 145
页数:3
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