Resilience Assessment of Drilling Risers in Extreme Marine Environments

Authors

  • Huawei Wang
  • Chuan Wang
  • Guangtao Chen

DOI:

https://doi.org/10.62051/ijmee.v7n3.13

Keywords:

Drilling Riser, Resilience, Performance Quantification, Dynamic Bayesian Networks

Abstract

Resilience, as a comprehensive evaluation concept, assesses the overall post-event response capability of a system, providing theoretical foundations and decision support for system design optimization and disaster emergency management. Extreme marine environments characterized by violent winds, strong currents, and large waves significantly increase the failure probability of deepwater drilling riser systems. These extreme loads induce excessive stress, fatigue, and fracture, heightening the risk of structural failure. This paper proposes a resilience assessment method for drilling risers under extreme sea conditions. The method first employs high-precision hydrodynamic simulation to fit and process acquired time-varying load data, deriving riser failure probabilities. It then quantifies degradation processes using a dynamic Bayesian network model. Subsequently, a dynamic recovery process encompassing fault diagnosis, resource allocation, and maintenance models is established. Two metrics—failure rate and recovery capability—are selected as single-stage resilience indicators for each process, with resilience calculated using the area method. Using a drilling riser in the South China Sea as a case study, the proposed resilience framework demonstrates validity and applicability. Results confirm the method effectively quantifies riser performance degradation and recovery capacity, providing critical guidance for engineering design and operational management.

References

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Published

26-12-2025

Issue

Section

Articles

How to Cite

Wang, H., Wang, C., & Chen, G. (2025). Resilience Assessment of Drilling Risers in Extreme Marine Environments. International Journal of Mechanical and Electrical Engineering, 7(3), 128-139. https://doi.org/10.62051/ijmee.v7n3.13