Intelligent Evaluation Model for Cementing Quality Based on GA-SVM and Application

被引:2
|
作者
Liu, Jingcheng [1 ,2 ]
Zeng, Shunpeng [1 ]
Yuan, Zhigang [2 ]
机构
[1] Chongqing Univ Sci & Technol, Coll Petr Engn, Chongqing 401331, Peoples R China
[2] Chongqing Univ, Minist Educ, Key Lab Exploitat Southestern Resources & Environ, Chongqing 400030, Peoples R China
关键词
genetic algorithm; SVM; well cementing quality; intelligent evaluation; NETWORKS;
D O I
10.4028/www.scientific.net/AMM.121-126.2730
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The cementing quality is directly related to the normal operation of the gas well, therefore, the evaluation of cementing quality is key to the correctly use the gas well as well as to take measures to protect the gas well. In this paper, four first wave amplitudes at the same depth point when using the borehole compensated sonic logger with double transceiver technique to carry out the acoustic amplitude log operation are served as the discriminant factors to evaluate the cementing quality. Taking the engineering actual measured data as the learning samples and using the particle swarm optimization to optimize the parameters of support vector machine, this paper established the intelligent evaluation model for cementing quality based on genetic algorithm (GA) and support vector machine (SVM). The model employs the excellent characteristic of SVM which has high speed of solving and could describe nonlinear relation as well as the characteristic of GA which has global optimization. Through test of engineering samples, the research result showed that this model has fast astringency and high precision, providing a new method and approach for the fast and accurate evaluation of the well cementing quality.
引用
收藏
页码:2730 / +
页数:2
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