Early warning of deep-water drilling influx based on machine learning
Document Type
Conference Proceeding
Publication Date
1-1-2023
Abstract
During deep-water drilling, the pressure window between pore pressure and leakage pressure is narrow, leading to frequent gas kick incidents. Loss of control can lead to severe gas kick or well blowout, resulting in incalculable losses. Therefore, the early detection of gas kick to allow for efficient well control strategies has been a focus of research in recent years. This paper presents a machine learning-based approach and research framework for early warning of gas kick during deep-water drilling. This approach is also applicable to handle other complex downhole incidents.
Publication Source (Journal or Book title)
Proceedings of the International Offshore and Polar Engineering Conference
First Page
22
Last Page
29
Recommended Citation
Yin, Q., Song, Z., Chen, K., Zhou, X., Tyagi, M., & Li, L. (2023). Early warning of deep-water drilling influx based on machine learning. Proceedings of the International Offshore and Polar Engineering Conference, 22-29. Retrieved from https://repository.lsu.edu/petroleum_engineering_pubs/662