Reliability Assessment of Oil and Gas Pipeline Systems at Burst Limit State Under Active Corrosion

Civil infrastructures such as oil and gas transportation systems play a vital role in industrial and public energy distribution and consumption. A large number of existing oil and gas transportation pipelines in many cities in the USA are running at the end of their design life and are at risk. Failure in these systems can potentially cause adverse effects to the society, economy, and environment. Asset managers often need to prioritize the critical segments based on the risk of failure, available budget, and resources. In this paper, the fitness for service of oil and gas pipelines and network integrity are evaluated probabilistically using various burst pressure models to prioritize the riskiest segments to support asset management. The current state-of-the-art practice of burst failure models for pressurized metallic pipelines is compared using a physical probabilistic approach. Since metallic pipelines for oil and gas transportation are typically designed for a long lifespan and experience localized corrosion deterioration throughout their lifetime, a steady-state corrosion model was assumed for accounting for the effect of external corrosion deterioration on the burst pressure of pipelines. A Monte Carlo Simulation technique is utilized to generate the fragility curves of pipelines considering corrosion deterioration over time. Uncertainties involved in various parameters related to burst failure and fragility estimation are modelled based on the knowledge gained from past research. A comparative analysis is presented for various fragility models of pipelines. Also, system reliability was evaluated using a minimum cut sets approach. The proposed approach is illustrated for a simple hypothetical oil/gas transmission system. Outcomes of the study show a consistent trend of failure for various models over time. The results of the probabilistic models of burst failures are analyzed, and recommendations are provided to support asset management planning.