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Application of Self-organizing Neural Network to Logging Reservoir Evaluation

Ren Pei-gang1a,1b,XIA Cun-yin1a,1b,LI Yuan1a,1b,XU Bo-wen2,YIN Ling-ling2(1a.Faculty of Earth Resources;1b.Key Laboratory of Tectonics and Petroleum Resources of Ministry of Education,China University of Geosciences Wuhan 430074,China;2.Faculty of Exploration Technologies for Oil and Resources,Yangtze University,Hubei Jingzhou 434023,China)  
The BP neural network model and forecasting has certain limitation,for it is known as a priori knowledge of certain conditions.This paper puts forward a self-organizing neural network for logging reservoir evaluation.With its self-learning ability,this network has the space for calssification of the input of events and activities in these areas selectively.The lithology identification and fluid property identification by using the self-organizing neural network and real data processing results show that the core with self-organizing neural network has higher practicability in identifying lithology and fluid property.
【Fund】: 国家自然科学基金项目(40872077)
【CateGory Index】: P631.84
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