A sequence-based method for dynamic reliability assessment of MPD systems

A sequence-based method for dynamic reliability assessment of MPD systems

Zhu, Jingyu (China University of Petroleum (East China))
Chen, Guoming (China University of Petroleum (East China))
Khan, Faisal (Memorial University of Newfoundland)
Yang, M. (TU Delft Safety and Security Science)
Li, Xinhong (Xi'an University of Architecture and Technology)
Meng, Xiangkun (Dalian Maritime University)
He, Rui (China University of Petroleum (East China))

2021

Managed Pressure Drilling (MPD) system is widely used in the deepwater drilling operation. Reliability assessment plays a critical role in the MPD system in the management of drilling operation risk and the prevention of blowouts. However, the reliability assessment of the MPD system is challenged due to its sequential operations and multiple processes. Consequently, the present work proposes a sequence-based dynamic reliability assessment method, which focuses on the dynamic modeling of sequential operations for the MPD system by integrating GO-FLOW and dynamic Bayesian Network (DBN). GO-FLOW models are firstly used to define the time interaction between multiple phases for complex systems. A sequence-based mapping method is also proposed for the DBN to construct the reliability model of the MPD system throughout the entire drilling cycle. In the end, the case study analyzed by the proposed framework indicates that the reliability of the MPD system decreases with increasing drilling depth, and the reliability of “tripping in” is highest among four different phases, while the “drilling process” is the lowest. The method provides an important technique that can be implemented with online condition monitoring tools to assess and monitor the reliability of the MPD operation in real-time.

Deepwater drilling
Dynamic bayesian network
GO-FLOW method
MPD system
Reliability assessment

http://resolver.tudelft.nl/uuid:fbc14986-0614-4c96-b27a-4e02a3d6bfa1

https://doi.org/10.1016/j.psep.2020.12.015

2021-06-15

0957-5820

Process Safety and Environmental Protection, 146, 927-942

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2021 Jingyu Zhu, Guoming Chen, Faisal Khan, M. Yang, Xinhong Li, Xiangkun Meng, Rui He