中国石油大学学报（自然科学版）2016，Vol.40Issue(2)：70-75,6.DOI:10.3969/j.issn.1673-5005.2016.02.008
一基于时域统计特征的井眼碰撞识别方法
A borehole collision recognition method based on the time statistical characteristics
摘要
Abstract
During well drilling, special time-domain features of drilling bit vibration signals will be produced when drilling at cement sheath and casing, which are different with that when drilling through rock formations. A new method for the recogni-tion of borehole collision was proposed by analyzing the vibration signals produced when the drill bit collided with the cement sheath and casing of nearby wells. Firstly, the dispersion and shape distribution characteristics of the vibration signals were extracted, then the principal component analysis( PCA) was conducted to obtain the principal features of the signals. Finally a support vector machine ( SVM) was trained with sampled signals to establish a model, which could be used to identify the borehole collision automatically by distinguishing the principal features of different vibration signals. This method has been effectively verified through real drilling data analysis from offshore cluster wells.关键词
井眼碰撞/时域特征/主成分分析法/支持向量机Key words
borehole collision/time-domain feature/principal component analysis/support vector machine分类
能源科技引用本文复制引用
刘刚,张家林,刘闯,刘华亮,于长广..一基于时域统计特征的井眼碰撞识别方法[J].中国石油大学学报（自然科学版）,2016,40(2):70-75,6.基金项目
“十二五”国家科技重大专项(2011ZX05057-002-006,2011ZX05024-002-010) （2011ZX05057-002-006,2011ZX05024-002-010）
山东省自然科学基金项目(ZR2014EEQ021) （ZR2014EEQ021）
中央高校基本科研业务费专项(14CX02167A) （14CX02167A）
