PREDICTION OF DRILL STRING VIBRATIONS USING MACHINE LEARNING TOOLS
Kudaibergenov A.K. Kudaibergenov A.K. Tileuberdi T.B.
21 June 2025al-Farabi Kazakh State National University
KazNU Bulletin. Mathematics, Mechanics, Computer Science Series
2025#126Issue 2151 - 163 pp.
The objective of this work is to apply machine learning algorithms for the analysis of dynamic vibrations of drill strings. As part of the research, a mathematical model describing the vibrations of the drill string was developed; a finite difference scheme was implemented, and numerical modeling was carried out using the three-point sweep method. Based on the data obtained from the numerical solution, a machine learning model was created. The numerical modeling was implemented using C++, while data collection and the construction of the machine learning model were performed using the Python programming language. As a result, a predictive model was obtained, capable of accurately forecasting the dynamic vibrations of the drill string and determining optimal parameters, thereby improving the efficiency and safety of drilling operations.
drill string , linear regression , machine learning , random forest , vibrations
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Department of Mathematical and Computer Modeling, Al-Farabi Kazakh National University, Almaty, Kazakhstan
Department of Mathematical and Computer Modeling
10 лет помогаем публиковать статьи Международный издатель
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