Permeability Estimation of Rock Reservoir Based on PCA and Elman Neural Networks

被引：0

作者：

Shi, Ying ^{[1
]}

Jian, Shaoyong ^{[2
]}

机构：

[1] Coll Wuhan Technol & Business Univ, Dept Publ Basic Course, Wuhan 430065, Hubei, Peoples R China

[2] Xinyu Univ, Coll Math & Comp Sci, Xinyu 338000, Jiangxi, Peoples R China

来源：

3RD INTERNATIONAL CONFERENCE ON ENERGY EQUIPMENT SCIENCE AND ENGINEERING (ICEESE 2017) | 2018年 / 128卷

关键词：

D O I：

10.1088/1755-1315/128/1/012001

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

an intelligent method which based on fuzzy neural networks with PCA algorithm, is proposed to estimate the permeability of rock reservoir. First, the dimensionality reduction process is utilized for these parameters by principal component analysis method. Further, the mapping relationship between rock slice characteristic parameters and permeability had been found through fuzzy neural networks. The estimation validity and reliability for this method were tested with practical data from Yan'an region in Ordos Basin. The result showed that the average relative errors of permeability estimation for this method is 6.25%, and this method had the better convergence speed and more accuracy than other. Therefore, by using the cheap rock slice related information, the permeability of rock reservoir can be estimated efficiently and accurately, and it is of high reliability, practicability and application prospect.

引用

页数：5

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