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http://dx.doi.org/10.7842/kigas.2020.24.1.66

Analysis of Technical Trend for Drilling ROP Optimization with Artificial Intelligent  

Jung, Ji-hun (IHK)
Han, Dong-kwon (Dept. of Energy and Mineral Resources Engineering, Dong-A University)
Kim, Sang-ho (Dept. of Energy and Mineral Resources Engineering, Dong-A University)
Yoo, In-hang (IHK)
Kwon, Sun-il (Dept. of Energy and Mineral Resources Engineering, Dong-A University)
Publication Information
Journal of the Korean Institute of Gas / v.24, no.1, 2020 , pp. 66-75 More about this Journal
Abstract
Drilling operation is the most important and costly essential work in oil and gas exploration and development. Therefore, the studies about rate of penetration have been carried out continuously to improve drilling efficiency. In recent years, data-driven models have been developed by various researchers to overcome disadvantages of traditional mathematical models. For the data-driven models, selecting proper algorithms and parameters is very important. In addition, data-driven models should be retrained in real-time during continuous drilling operations in order to improve the model performance. In this paper, the latest studies are investigated to provide information about algorithms, drilling parameters and model retraining intervals that used in drilling optimization.
Keywords
Drilling optimization; Drilling parameter; Rate of penetration; Real time drilling optimization;
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