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BP神经网络识别塔北低阻油气层
引用本文:贺铎华.BP神经网络识别塔北低阻油气层[J].物探与化探,2002,26(2):122-125.
作者姓名:贺铎华
作者单位:中国石油化工集团新星公司,西北石油局工程技术中心,新疆,乌鲁木齐,830011
摘    要:简要介绍了塔北低阻油气层岩性剖面、低阻油气层地球物理测井曲线特征,分析了塔北地区低阻油气储层成因,重点论述BP人工神经网络识别油气层、油水同层、水层和干层的方法原理。识别实例表明,BP人工神经网络识别低阻油(气)、水层的结果与实际相符,明显地提高了测井的解释精度。

关 键 词:塔北地区  低阻油气层  BP人工神经网络  测井解释
文章编号:1000-8918(2002)02-0122-04
收稿时间:2001-05-18

THE APPLICATION OF BP NEURAL NETWORK TO RECOGNITION OF THE TABEI LOW RESISTIVITY OIL AND GAS LAYERS
HE Duo?hua.THE APPLICATION OF BP NEURAL NETWORK TO RECOGNITION OF THE TABEI LOW RESISTIVITY OIL AND GAS LAYERS[J].Geophysical and Geochemical Exploration,2002,26(2):122-125.
Authors:HE Duo?hua
Institution:Engineering and Technical Center, Northwest Bureau of Petroleum, New Star Company of China Petroleum and Chemical Industry Corporation, Urumchi 830011, China
Abstract:This paper describes in brief the lithologic profiles and the geophysical logging curves of the low resistivity oil and gas layers in Tabei area, analyzes the origin of the low resistivity oil and gas reservoirs in that area, and deals emphatically with the principle of applying the neural network to recognizing oil and gas layers, oil-water layers, water layers and dry layers. The recognition of low resistivity oil (gas) layers and water layers is consistent with the real conditions, thus obviously improving the interpretation precision of logging data.
Keywords:Tabei area  low resistivity oil and gas layer  BP artificial neural network  interpretation of logging data  
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