THERMAL SCIENCE

International Scientific Journal

INTELLIGENT IDENTIFICATION METHOD FOR STICK-SLIP VIBRATION BASED ON DOWNHOLE DATA

ABSTRACT
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.
KEYWORDS
PAPER SUBMITTED: 2024-10-31
PAPER REVISED: 2024-11-28
PAPER ACCEPTED: 2024-12-05
PUBLISHED ONLINE: 2025-06-01
DOI REFERENCE: https://doi.org/10.2298/TSCI2502521L
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2025, VOLUME 29, ISSUE Issue 2, PAGES [1521 - 1526]
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2025 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence