Towards resilient urban gas networks: a predictive and multi-level risk control framework empowered by smart technologies

This study investigates operation and maintenance strategies, along with risk prevention mechanisms, for urban medium and low-pressure oil and gas intelligent pipeline networks. Through a systematic analysis of domestic and international advancements in gas pipeline management, a comprehensive framework is proposed to improve network reliability and operational safety. A multi-source monitoring architecture integrating aerial, terrestrial, and subsurface data is constructed, and a machine learning-based predictive maintenance system is introduced. In addition, a hierarchical risk prevention and control system is developed, incorporating components such as risk evaluation, intelligent fault diagnosis, safety assurance, and emergency response mechanisms. The proposed approach is validated through a case study of the China–Russia East-Route Natural Gas Pipeline Project, which demonstrates notable enhancements in anomaly detection precision, efficiency of risk mitigation responses, and overall system resilience. The study further evaluates existing limitations and outlines potential directions for future research. This work provides both theoretical foundations and practical methodologies for achieving intelligent and secure management of urban oil and gas distribution infrastructures, thereby supporting the evolution of smart energy systems.