On Application Of The BP Artificial Neural Network Analysis In The Oilfield Exploitation—A Case Study of Chang 2 Reservoir of Sai-A Wellblock of Changqing Oilfield Company
The BP neural network analysis is a kind of method used to analyze, process and forecast the data and has become a hot subject for the research of management and the high technology in recent years. The artificial neural network was also established during the exploitation result evaluation and plan adjustment research of the Chang 2 Reservoir of Sai-A Wellblock of Changqing Oilfield Company, taking the fracture parameters of the existing 29 oil wells as the sample which are obtained through the analysis of the unsteady well testing data of the fractured formation of the 29 wells. It was trained with the formation parameters and operation parameters having a influence on the hydraulic fracturing parameters as the input parameters and the fracture conductivity and fracture half-length as the output parameters, through which the feature of the fracture distribution of the whole oil reservoir was obtained, providing a more visual way to evaluate the result of the fracturing measures and the basis for the exploitation adjustment.
artificial neural network well test analysis fracture
JIA Yuqing
School of Management, Henan University of Technology, Zhengzhou, P. R. China, 450001
国际会议
2010 International Conference on Management(2010管理国际大会)
上海
英文
845-850
2010-07-24（万方平台首次上网日期，不代表论文的发表时间）