Intelligent Evaluation Model for Cementing Quality Based on PSO-SVM and Application
- 作者：LIU Jing-chengWANG Hong-tuZENG Shun-pengYUAN Zhi-gang
- 会议时间：2011-11-01
- 关键词：PSO ; SVM ; well cementing quality ; intelligent evaluation
- 作者单位：LIU Jing-cheng(Key Laboratory for Exploitation of Southwestern Resources & Environmental Disaster Control Engineering, Ministry of Education,Chongqing University,Chongqing,China,400030 ;College of Petroleum Engineering, Chongqing University of Science and Technology, Chongqing, China, 401331)WANG Hong-tu,YUAN Zhi-gang(Key Laboratory for Exploitation of Southwestern Resources & Environmental Disaster Control Engineering, Ministry of Education,Chongqing University,Chongqing,China,400030)ZENG Shun-peng(College of Petroleum Engineering, Chongqing University of Science and Technology, Chongqing, China, 401331)
- 母体文献：2011全国特殊气藏开发技术研讨会论文集
- 会议名称：2011全国特殊气藏开发技术研讨会
- 会议地点：重庆
- 主办单位：重庆市科学技术协会
- 语种：chi
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 particle swarm optimization (PSO) 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 PSO 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.