TY - JOUR
TI - Intelligent identification method for stick-slip vibration based on downhole data
AU - Liu Wei
AU - Pan Tao
AU - Fang Chao
AU - Li Qi-Feng
AU - Zhou Chao
AU - Li Xing-Cai
AU - Zhu Zhao-Peng
AU - Zhu Lin
AU - Wang Chao-Chen
JN - Thermal Science
PY - 2025
VL - 29
IS - 2
SP - 1521
EP - 1526
PT - Article
AB - The stick-slip vibration problem in downhole drilling has become prominent,  seriously affecting production efficiency and equipment safety. Therefore,  this study proposes an intelligent stick-slip vibration recognition method  based on downhole data. Utilizing downhole data aims to address the issues  of strong subjectivity and low accuracy in traditional stick-slip vibration  monitoring. First, time-domain pre­processing of the raw vibration signals  is conducted, including outlier removal, and noise reduction filtering.  Then, time-frequency analysis is performed using Fourier Transform to  extract deep features from the data. A stick-slip vibration classifica­tion  evaluation system is constructed using the stick-slip index method. Finally,  an intelligent stick-slip vibration recognition model is established based  on the long short-term memory algorithm, integrating frequency-domain and  time-domain features as input features to achieve accurate monitoring of  stick-slip vibration levels. Measured data from an oilfield in China were  selected for comparison. The results show that the model achieves an  accuracy of 85.8%, effectively identifying stick-slip vibrations and  demonstrating good application potential in the field.