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LMS Adaptive Filtering of Drilling Tool Vibration Signal

Authors :
Gao Yi
Sun Tao
He Yan
Kang Si-Min
Wang Yue-long
Source :
Journal of Physics: Conference Series. 1237:042018
Publication Year :
2019
Publisher :
IOP Publishing, 2019.

Abstract

As the dynamic measurement of attitude parameter of the steerable drilling tool under vibration may be not accurate, the Least Mean Square (LMS) adaptive filtering algorithm is adopted to filter the influence of drilling tool vibration on the attitude measurement in this paper. The simulation results show that the measurement error of inclination angle after LMS adaptive filtering can be less than 0.1°, and the measurement error of tool face angle is less than 6°, which could effectively improve the attitude measurement accuracy of vertical steerable drilling tools; the results of inverse analysis on actual drilling data show that the actual measurement error of inclination angle after LMS adaptive filtering is about 3°, which is much smaller than that before filtering. It shows that LMS adaptive filtering can effectively filter the vibration signal of drilling tools and greatly improve the dynamic measurement accuracy of the tool attitude.

Details

ISSN :
17426596 and 17426588
Volume :
1237
Database :
OpenAIRE
Journal :
Journal of Physics: Conference Series
Accession number :
edsair.doi...........448dd165ceb8268563f83a1b1e236d84