Casing life prediction using Borda and support vector machine methods

• Published in: Petroleum science 2010-09, Vol.7 (3), p.416-421
• Main Authors: Xu, Zhiqian, Yan, Xiangzhen, Yang, Xiujuan
• Format: Article
• Language: English
• Subjects: Borda法; Earth and Environmental Science; Earth Sciences; Economics and Management; Energy Policy; Industrial and Production Engineering; Industrial Chemistry/Chemical Engineering; Mineral Resources; SVM模型; 剩余寿命预测; 失效模式; 套管损坏; 寿命预测模型; 支持向量机方法; 风险因素
• ISSN: 1672-5107; 1995-8226
• DOI: 10.1007/s12182-010-0087-8

Eight casing failure modes and 32 risk factors in oil and gas wells are given in this paper. According to the quantitative analysis of the influence degree and occurrence probability of risk factors, the Borda counts for failure modes are obtained with the Borda method. The risk indexes of failure modes are derived from the Borda matrix. Based on the support vector machine （SVM）, a casing life prediction model is established. In the prediction model, eight risk indexes are defined as input vectors and casing life is defined as the output vector. The ideal model parameters are determined with the training set from 19 wells with casing failure. The casing life prediction software is developed with the SVM model as a predictor. The residual life of 60 wells with casing failure is predicted with the software, and then compared with the actual casing life. The comparison results show that the casing life prediction software with the SVM model has high accuracy.