The petroleum industry in the United States relies heavily on facilities in hurricane-prone regions, such as the Gulf Coast. Past hurricanes have demonstrated the vulnerability of petroleum supply chains to these extreme events; however, models are lacking for hurricane performance assessment of petroleum supply chain infrastructure. In this study, a probabilistic framework is presented for the performance assessment of oil supply chain infrastructure (OSCI) subjected to hurricane events, spanning from a methodological definition to implementation to opportunities and needs. The framework leverages Bayesian networks for probabilistic analysis of connectivity and flow within the oil supply chain, alongside fragility functions for physical damage and functionality assessment of supply chain components. A literature survey is conducted to identify the tools enabling the proposed framework. Application of the method for probabilistic assessment of tightly interrelated oil supply chains subjected to hurricane events is demonstrated with a representative OSCI comprised of platforms, ports, pipelines, refineries, storage facilities, power, and transportation infrastructure. In addition to investigating the impact of alternative levels of hazard exposure and the effectiveness of different mitigation actions, the framework affords the potential for Bayesian updating as new data come online regarding the component performance or product availability/flow. The proposed framework can provide a foundation to support risk mitigation and resilience enhancement efforts in the petroleum industry.
Supply Chain Risk Management Capabilities Center