Analysis on the Fracturing Result of Reservoir by Artificial Neural Network: A Case Study of the C2 Reservoir in SA Wellblock, Jingan Oilfeld <?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" /><o:p></o:p>

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Analysis on the Fracturing Result of Reservoir by Artificial Neural Network: A Case Study of the C₂ Reservoir in SA Wellblock, Jingan Oilfeld

详细信息

责任者：Li Xinming (No.3 Oil Extraction Plant ; Changqing Oilfield Branch ; PetroChina ; Yinchuan 750001 ; China)
刊名：Geology and Resources
出版年：2009
卷期：18(3)
关键词：BP神经网络系统 ; BP neural network system ; 压裂 ; fracturing
页码：p.217-221
图表：3 illus., 2 tables, 5 refs.
分类号：1900
issnNo：ISSN1671-1947
isbnNo：CN21-1458/P

摘要

The fracture parameters are obtained through the well test data from a small number of wells. With the existing parameters as samples, the artificial neural network system is set up. The input parameters that influence the outcome of fracturing, such as the formation thickness, porosity, clay content, working stress and sand displacement, are selected. The ability to fracture conductivity and fracture half-length is the output parameters. With training by BP neural networks, the fracturing parameters of the whole wells are inferred, resulting in the fracturing distribution of the reservoir.

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