Operational Risk Assessment of Ship to Shore Petroleum Transfer Using Fuzzy Rule-Based Bayesian Networks

Ayman F. Alghanmi, Department of Supply Chain Management and Maritime Business, Faculty of Maritime Studies, King Abdulaziz University, Jeddah, Saudi ArabiaFollow

Abstract

Petroleum ports represent critical infrastructure in global energy supply chains, where operational risks during ship-to-shore transfer operations can lead to catastrophic consequences including environmental damage and human casualties. Despite rigorous safety protocols, these facilities remain vulnerable to operational hazards in dynamic maritime environments. This research aimed to develop and apply a hybrid Fuzzy Rule-Based Bayesian Reasoning (FRBBR) model to identify, evaluate, and prioritize operational hazards during crude oil transfer operations at petroleum port berths, with a case study conducted in Saudi Arabia, addressing the challenge of risk assessment where historical data is limited.
The research employed a mixed-methods approach combining WHAT-IF and Cause-Effect techniques for hazard identification with Bayesian Network analysis for probability assessment and Fuzzy Rule-Based inference for consequence evaluation. Data collection involved semi-structured interviews with 42 industry experts selected through purposive sampling from the petroleum transportation sector from different parts of the world. The FRBBR model integrated probabilistic causal analysis with fuzzy linguistic variables using trapezoidal membership functions and Mamdani inference. Model validation was conducted through case studies at two petroleum port facilities not included in the initial data collection.

The analysis identified 18 critical hazard events, with fire/explosion during transfer operations classified as the highest risk despite its relatively low probability (0.019) due to its severe consequences (0.90). Five additional hazards received high-risk classifications, including leaks from loading arms/hoses and failure of emergency shutdown systems. Procedural non-compliance and operator error emerged as the most influential causal factors across high-priority hazards, with average influence indices of 0.60.
The FRBBR model demonstrated effectiveness in assessing operational risks in petroleum ports under uncertainty, enabling targeted allocation of safety resources. The findings support enhanced operational safety practices and contribute to operational safety practices in petroleum ports around the world, including supporting Saudi Arabia's strategic positioning in global maritime transportation networks.
Priority interventions include competency-based training and compliance assurance for transfer procedures, routine verification of emergency shutdown and control systems, deployment of leak-detection and pressure-surge protection on loading arms and lines, and operational limits triggered by weather and sea conditions to mitigate unsafe vessel movement and tank overflow.

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Recommended Citation

Alghanmi, Ayman F. (2026) "Operational Risk Assessment of Ship to Shore Petroleum Transfer Using Fuzzy Rule-Based Bayesian Networks," Journal of King Abdulaziz University: Marine Science: Vol. 36: No. 1, Article 2.
DOI: https://doi.org/10.64064/1658-4325.1024