Safety evaluation of casing string based on BP artificial neural network

被引:0
|
作者
Yan, Yifei [1 ]
Yang, Xiujuan [2 ]
Kong, Chao [1 ]
Zhou, Xiaoqi [3 ]
Shao, Bing [1 ]
机构
[1] China Univ Petr, Coll Mech & Elect Engn, Qingdao 266580, Shandong, Peoples R China
[2] China Univ Petr, Coll Pipeline & Civil Engn, Qingdao 266580, Shandong, Peoples R China
[3] Sinopec, Petr Engn Technol Res Inst Zhongyuan Oilfield, Beijing 457001, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
WELLS;
D O I
10.1088/1757-899X/383/1/012003
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the traditional safety assessment of casing string, some influencing factors are ignored for modelling convenience, which makes the casing string safety assessment effect of oil and gas well not very ideal. For complexity and randomness of casing load and its properties parameters in complex well conditions, BP artificial neural network is created in MATLAB based on the analysis of the influencing factors of casing string security. Casing string section whose safety assessment is more mature is taken as a sample to train the BP neural network. The trained network is applied to make case assessment. At the same time, GUI interface is applied to implement the visualization. The results show that safety evaluation of the casing string can be achieved by using BP neural network. The accuracy of the casing string network safety evaluation is high. It will realize the visualization of safety evaluation and provide more accurate and effective reference for the design of casing string.
引用
收藏
页数:5
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