Research Method of Fuzzy Neural Network of Reservoir Heterogeneity

Li Guorong, H. Jingjing, Liao Tai-ping, Lin Zhicheng, Z. Furong
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Abstract

For analysis of the reservoir, due to complexity of the reservoir heterogeneity, the relationship between the logging response value and the non-homogenous reservoir is complex and fuzzy. The use of fuzzy clustering method of neural network combines the adaptivity and the fault tolerance of the neural network organic manner with the fuzzy comprehensive discrimination in the human thinking simulation of fuzzy logic, so as to recognize the reservoir heterogeneity through multi-factor fuzzy comprehensive judgment and reasoning. This method has been used to treat the data about the 135 wells in Xujiahe Group in central Sichuan, and has shown good results, with a coincidence rate as high as 87.6%. The result demonstrates that this method enjoys good adaptivity against the problem of automatic recognition of the reservoir heterogeneity, and could improve the precision of automatic recognition of the reservoir heterogeneity.
储层非均质性模糊神经网络研究方法
在储层分析中,由于储层非均质性的复杂性,测井响应值与非均质储层之间的关系是复杂和模糊的。利用神经网络的模糊聚类方法,将神经网络有机方式的自适应性和容错性与人类思维模拟模糊逻辑中的模糊综合判别相结合,通过多因素模糊综合判断和推理来识别储层非均质性。将该方法应用于川中地区须家河组135口井的数据处理,取得了较好的效果,符合率高达87.6%。结果表明,该方法对储层非均质性自动识别问题具有较好的适应性,可以提高储层非均质性自动识别的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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