Artificial intelligence method for predicting the maximum stress of an off-center casing under non-uniform ground stress with support vector machine  

作　　者：DI QinFeng WU ZhiHao CHEN Tao CHEN Feng WANG WenChang QIN GuangXu CHEN Wei 

机构地区：[1]Shanghai Institute of Applied Mathematics and Mechanics,School of Mechanics and Engineering Science,Shanghai University,Shanghai 200444,China [2]School of Computer Engineering and Science,Shanghai University,Shanghai 200444,China [3]School of Mechatronics Engineering and Automaton,Shanghai University,Shanghai 200444,China

出　　处：《Science China(Technological Sciences)》2020年第12期2553-2561,共9页中国科学（技术科学英文版）

基　　金：This work was supported by the National Natural Science Foundation of China(Grant Nos.U1663205,51704191 and 51804194);the Shanghai Leading Academic Discipline Project(Grant No.S30106);the Shanghai Municipal Education Commission(Peak Discipline Construction Program);the Shanghai Sailing Program(Grant No.17YF1428000)。

摘　　要：The situation of an off-center casing under non-uniform ground stress can occur in the process of drilling a salt-gypsum formation,and the related casing stress calculation has not yet been solved analytically. In addition,the experimental equipment in many cases cannot meet the actual conditions and the experimental cost is very high. These comprehensive factors cause the existing casing design to not meet the actual conditions and cause casing deformation,affecting the drilling operation in Tarim oil field. The finite element method is the only effective method to solve this problem at present,but the re-modelling process is time-consuming because of the changes in the parameters,such as the cement properties,casing centrality,and the casing size. In this article,an artificial intelligence method based on support vector machine(SVM) to predict the maximum stress of an offcenter casing under non-uniform ground stress has been proposed. After a program based on a radial basis function(RBF)-support vector regression(SVR)(ε-SVR) model was established and validated,we constructed a data sample with a capacity of 120 by using the finite element method,which could meet the demand of the nine-factor ε-SVR model to predict the maximum stress of the casing. The results showed that the artificial intelligence prediction method proposed in this manuscript had satisfactory prediction accuracy and could be effectively used to predict the maximum stress of an off-center casing under complex downhole conditions.

关 键 词：support vector machine maximum stress off-center casing non-uniform ground stress oil and gas wells 

分 类 号：TE24[石油与天然气工程—油气井工程] TP18[自动化与计算机技术—控制理论与控制工程]