During the drilling process, the non-linear contacts between the bit and the bottom hole, the drill string and the borehole wall can cause the bit’s stick-slip vibration, which will shorten the life of the bit and even endanger the safety of the drill string. The severity of stick-slip vibration of a bit can be identified by the rotary speed of a bit, the triaxial accelerations of the drill string, the wellhead torque and other parameters measured by the measuring while drilling (MWD) tools in the downhole and devices on the surface. To evaluate the level of stick-slip vibration, this paper proposes a risk assessment method of sick-slip vibration based on backpropagation neural network (BPNN). According to the time and frequency domain analysis of the data collected from simulation, the feature parameters of the time and frequency domains of signals are extracted, and then the kernel principal component analysis (KPCA) is applied to reduce dimensions. Consequently, the feature vectors can be obtained, which become the input parameters of the BPNN. Based on BPNN algorithm, the stick-slip vibration of the bit is determined, and the classification of stick-slip vibration strength is carried out. The results show that this method can effectively identify the severity of stick-slip vibration of a bit. Therefore, this method is valid to evaluate the stick-slip vibration of a bit, which will help drillers adjust the drilling parameters practically according to the severity of vibration, so as to reduce the risks of stick-slip vibration during drilling and improve the efficiency and safety of drilling operation.
Skip Nav Destination
ASME 2018 Pressure Vessels and Piping Conference
July 15–20, 2018
Prague, Czech Republic
Conference Sponsors:
- Pressure Vessels and Piping Division
ISBN:
978-0-7918-5170-8
PROCEEDINGS PAPER
Research on Risk Assessment Method of Stick-Slip Vibration of the Bit Based on BP Neural Network Algorithm
Chong Chen,
Chong Chen
China University of Petroleum, Beijing, China
Search for other works by this author on:
Shimin Zhang,
Shimin Zhang
China University of Petroleum, Beijing, China
Search for other works by this author on:
Hang Zhang,
Hang Zhang
China University of Petroleum, Beijing, China
Search for other works by this author on:
Xiaojun Li,
Xiaojun Li
CNPC Xibu Drilling Engineering Company Limited, Urumchi, China
Search for other works by this author on:
Zichen He
Zichen He
China University of Petroleum, Beijing, China
Search for other works by this author on:
Chong Chen
China University of Petroleum, Beijing, China
Shimin Zhang
China University of Petroleum, Beijing, China
Hang Zhang
China University of Petroleum, Beijing, China
Xiaojun Li
CNPC Xibu Drilling Engineering Company Limited, Urumchi, China
Zichen He
China University of Petroleum, Beijing, China
Paper No:
PVP2018-84144, V007T07A026; 6 pages
Published Online:
October 26, 2018
Citation
Chen, C, Zhang, S, Zhang, H, Li, X, & He, Z. "Research on Risk Assessment Method of Stick-Slip Vibration of the Bit Based on BP Neural Network Algorithm." Proceedings of the ASME 2018 Pressure Vessels and Piping Conference. Volume 7: Operations, Applications, and Components. Prague, Czech Republic. July 15–20, 2018. V007T07A026. ASME. https://doi.org/10.1115/PVP2018-84144
Download citation file:
17
Views
0
Citations
Related Proceedings Papers
Related Articles
Torsional Vibrations and Nonlinear Dynamic Characteristics of Drill Strings and Stick-Slip Reduction Mechanism
J. Comput. Nonlinear Dynam (August,2019)
Dynamic Measurement of Spatial Attitude at Bottom Rotating Drillstring: Simulation, Experimental, and Field Test
J. Energy Resour. Technol (March,2016)
Stick-Slip and Bit-Bounce of Deep-Hole Drillstrings
J. Energy Resour. Technol (June,2000)
Related Chapters
A Novel Approach for LFC and AVR of an Autonomous Power Generating System
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)
Covariance Regularization for Supervised Learning in High Dimensions
Intelligent Engineering Systems through Artificial Neural Networks, Volume 20
Applied Drilling Mechanics
Mechanics of Drillstrings and Marine Risers