Management of offshore structures under microbiologically influenced corrosion (MIC)

Offshore systems suffer from excessive corrosion damage in the marine environment because of the dynamic operational and environmental contributing factors. Such situations enhance the serious integrity and safety concerns, systems degradation, and associated risks, especially in harsh environmental conditions. The microbiologically influenced corrosion as an essential corrosion category has considerable characteristic complexity because of the interactions between the bacteria and the corrosion contributing factors. The microbial corrosion and the interconnected system safety management plan are impacted by the stochastic behavior of microbial metabolism and operational parameters. To have a robust and reliable corrosion management plan in offshore systems, the dynamic microbial corrosion features, as well as the corresponding risk factors, must be taken into account. The present thesis proposes a dynamics-based approach for risk-based safety and integrity management of marine and offshore systems that suffer from microbial corrosion. First of all, a literature review is presented for the identification of microbial corrosion shortages, challenges, and requirements in the risk-based decision-making framework. The study is focused on the four tasks, including characteristics, mechanisms, modeling, and management of microbial corrosion. Secondly, a new probabilistic model is proposed to estimate the corrosion rate of a subsea pipeline by assessing the failure time and probability. The microbial corrosion monitoring and management activities are achieved using the Continuous Bayesian Network technique with the integration of Hierarchical Bayesian Analysis. The analysis outcomes indicate that the interdependencies between the contributing factors of microbial corrosion could raise the rate of corrosion and reduce the failure time of engineered corroded systems. Thirdly, new reliability is proposed to assess the optimum maintenance strategy time-interval for a subsea system impacted by multiple microbial corrosion defects. The different probabilistic models, including the non-homogeneous Markov processes, non-homogeneous Poisson, and homogeneous gamma, are utilized to model the maximum and average pit depth and multiple defects generations. The results show the influence of multiple microbial corrosion defects on the subsea pipeline considering several scenarios and recommend the optimal intervention time and management practices. Finally, a novel risk-based safety and integrity management framework is recommended to evaluate the subsea pipeline's failure. A multi-objective functional optimization methodology is developed to minimize the operational risk associated with microbial corrosion. The research results highlight an actual safety and integrity management plan consistent with the industrial practices. An innovative and dynamic Bayesian Network-based approach is proposed to assess the subsea system's resilience under MIC as a function of time. The subsea system is designed with sufficient resilience to maintain its performance under the time-varying interdependent stochastic conditions. The proposed methodology assists decision-makers in considering the resilience of the system design and operation. The present thesis investigates the mechanisms of microbial corrosion and explores the dynamic risk-based methodologies for several operating scenarios to manage the safety and integrity of marine and offshore systems.