基于改进神经网络的渗透率预测方法
网络出版日期: 2011-02-20
基金资助
受国家油气重大专项“剩余油分布综合预测与层系井网重组技术”项目(编号:2008ZX05010-003)资助
Permeability prediction method based on improved BP neural network
Online published: 2011-02-20
袁剑英 , 付锁堂 , 曹正林 , 阎存凤 , 张水昌 , 马达德 . 基于改进神经网络的渗透率预测方法[J]. 岩性油气藏, 2011 , 23(1) : 98 -102 . DOI: 10.3969/j.issn.1673-8926.2011.01.017
The traditional BP algorithmhas slowconvergence rate, and is easy to fall into local minimum. It is improved based on Kozeny-Carman equation and the study of Yang Zhengming, and a three-layer feedforward BP neural network model for permeability prediction is established bymeans ofMATLAB neural network toolbox. The simulation training of the improved neural network model is carried out. The result shows that the improved model has faster convergence rate and higher accuracy. The values predicted by the model are consistent with the laboratory test values, and the relative error is less than 10%, so it can completelymeet the accuracy demand ofwell site.
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