| 基于实数编码的遗传神经网络水淹层综合判别 |
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| 引用本文： | 寇峰,王树明,刘艳,李小琳,阎伟林. 基于实数编码的遗传神经网络水淹层综合判别[J]. 吉林大学学报(信息科学版), 2001, 0(Z1) |
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| 作者姓名： | 寇峰 王树明 刘艳 李小琳 阎伟林 |
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| 作者单位： | 吉林大学计算机科学与技术学院 吉林长春130026(寇峰，王树明，刘艳，李小琳)，大庆石油管理局勘探开发研究院 黑龙江大庆163400(阎伟林) |
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| 摘 要： | 为解决油层水淹后 ,使用一般测井解释方法很难识别水淹层的问题 ,提出了一种基于实数编码的遗传 BP ( Back Propagation)神经网络进行水淹等级综合判别的方法。在此基础上建立的神经网络经反复训练验证 ,性能稳定、学习收敛速度快 ,同时有很强的记忆能力、推广能力和适应性。对大庆长垣 7口井的资料处理表明 ,准确率达到 87%以上 ,取得了很好的效果。
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| 关 键 词： | 神经网络 自适应算法 编码 水淹层 BP算法 遗传算法 |
Automation distinguishing oil from water bearing reservoirs based on real coding genetic neural network |
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| KOU Feng ,WANG Shu ming ,LIU Yan ,LI Xiao lin ,YAN Wei lin. Automation distinguishing oil from water bearing reservoirs based on real coding genetic neural network[J]. Journal of Jilin University:Information Sci Ed, 2001, 0(Z1) |
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| Authors: | KOU Feng WANG Shu ming LIU Yan LI Xiao lin YAN Wei lin |
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| Affiliation: | KOU Feng 1,WANG Shu ming 1,LIU Yan 1,LI Xiao lin 1,YAN Wei lin 2 |
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| Abstract: | To solve difficult problem of that to identify the flooded formation with the conventional interpretation methods, a new method of automation distinguishing oil bearing reservoirs from water bearing reservoirs based on real coding genetic and BP algorithm and neural network technology is given. With many times train, the result proved: the network keeps properties of being stable; fast learning rate converged; awfully memorable, generalized and adaptive abilities. Testing on 7 wells of Changyuan of Daqing oil field, the accuracy reach 87%,the result is nice. |
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| Keywords: | Neural networks Adaptive algorithms Coding Water bearing reservoirs BP algorithm Genetic algorithm |
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