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China Ocean Engineering

, Volume 33, Issue 1, pp 14–25 | Cite as

Failure Statistics Analysis Based on Bayesian Theory: A Study of FPSO Internal Turret Leakage

  • Ji-chuan Kang
  • Lang Wang
  • Ming-xin LiEmail author
  • Li-ping Sun
  • Peng Jin
Article
  • 3 Downloads

Abstract

The load and corrosion caused by the harsh marine environment lead to the severe degradation of offshore equipment and to their compromised security and reliability. In the quantitative risk analysis, the failure models are difficult to establish through traditional statistical methods. Hence, the calculation of the occurrence probability of small sample events is often met with great uncertainty. In this study, the Bayesian statistical method is implemented to analyze the oil and gas leakages of FPSO internal turret, which is a typical small sample risk but could lead to severe losses. According to the corresponding failure mechanism, two Bayesian statistical models using the Weibull distribution and logarithmic normal distribution as the population distribution are established, and the posterior distribution of the corresponding parameters is calculated. The optimal Bayesian statistical model is determined according to the Bayesian information criterion and Akaike criterion. On the basis of the determined optimal model, the corresponding reliability index is solved to provide basic data for the subsequent risk assessments of FPSO systems.

Key words

risk analysis Bayesian theory FPSO internal turret system Markov chain Monte Carlo 

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Copyright information

© Chinese Ocean Engineering Society and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Ji-chuan Kang
    • 1
    • 2
  • Lang Wang
    • 3
  • Ming-xin Li
    • 1
    Email author
  • Li-ping Sun
    • 1
  • Peng Jin
    • 1
  1. 1.College of Shipbuilding EngineeringHarbin Engineering UniversityHarbinChina
  2. 2.Center for Marine Technology and EngineeringUniversity of LisbonLisbonPortugal
  3. 3.Yantai CIMC Raffles Offshore LimitedYantaiChina

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