Early Warning Technology in Drilling Muds Lost Circulation Anomaly Based on Data Analysis

2nd International Symposium on Resource Exploration and Environmental Science

生态环境科学

Luan, Yongle^1

Daqing Oilfield Production Engineering and Research Institute, Daqing Oilfield Company Ltd, PetroChina, Daqing, Heilongjiang

163453, China^1

关键词: Classification algorithm;    Complex structure;    Drilling engineering;    Early Warning System;    Inflection points;    Kernel principal component analyses (KPCA);    Nonlinear process;    Outlier elimination;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/170/2/022047/pdf
DOI  :  10.1088/1755-1315/170/2/022047

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

To change the complex structure and the changeable working conditions of Daqing oil drilling engineering, as well as the phenomenon of misreporting for the drilling muds lost circulation warning system, in view of the early warning system of the drilling engineering in Daqing oilfield, the drilling well lost circulation fault detection method with multimode kernel principal component analysis (KPCA) based on data was proposed. First, the outlier elimination algorithmwas described in detail.The experiment verified the reliability of the adaptive determination of the length of the sliding window by using the inflection point of the elimination rate as the standard. Then, in view of the early warning system of oil drilling engineering, a new threshold classification algorithm, which can correctly classify each working condition in drilling, was proposed. Because the study object was nonlinear process, the fault detection method based on single KPCA was extended to multiple KPCA model fault detection methods which can be applied to oil drilling process. The research showed that the multimode KPCA drilling muds lost circulation detection method achieved accurate and sensitive fault detection for Daqing oilfield. It is concluded that the new fault detection method proposed in this paper can make the drilling lost circulation anomaly early warning system detect faults used in Daqing oilfield more accurately and efficiently, so as to avoid misreporting.