Accidental leakage from oil–gas storage tanks can lead to the formation of liquid pools. These pools can result in vapor cloud explosions (VCEs) if combustible vapors encounter ignition energy. Conducting accurate and comprehensive consequence analyses of such explosions is crucial for quantitative risk assessments (QRAs) in industrial safety. In this study, a methodology based on the SLAB-TNO model to calculate the overpressure resulting from a VCE is presented. Based on this method, the consequences of the VCE accident considering the gas cloud concentration diffusion are studied. The probit model is employed to evaluate casualty probabilities under varying environmental and operational conditions. The effects of key parameters, including gas diffusion time, wind speed, lower flammability limit (LFL), and environment temperature, on casualty diffusion are systematically investigated. The results indicate that when the diffusion time is less than 100 s, the VCE consequences are significantly more severe due to the rapid spread of the gas cloud. Furthermore, increasing wind speed accelerates gas dispersion, reducing the spatial extent of casualty isopleths. The LFL is shown to have a direct impact on both the mass and diffusion of the flammable gas cloud, with higher LFL values shifting the explosion’s epicenter upward. The environmental temperature promotes gas diffusion in the core area and increases the mass of the combustible gas cloud. These findings provide critical insights for improving the safety protocols in oil and gas storage facilities and can serve as a valuable reference for consequence assessment and emergency response planning in similar industrial scenarios.

Ensuring the safety of oil tank farms is essential to maintaining energy security and minimizing the impact of potential accidents. This paper develops a quantitative regional risk model designed to assess both individual and societal risks in oil tank farms, with particular attention to energy-related risks such as leaks, fires, and explosions. The model integrates factors like day–night operational variations, weather conditions, and risk superposition to provide a comprehensive and accurate evaluation of regional risks. By considering the cumulative effects of multiple hazards, including those tied to energy dynamics, and the stability and validity of the model are researched through Monte Carlo simulations and case application. The results show that the model enhances the reliability of traditional risk assessment methods, making it more applicable to oil tank farm safety concerns. Furthermore, this study introduces a practical tool that simplifies the risk assessment process, allowing operators and decision-makers to evaluate risks without requiring in-depth technical expertise. The methodology improves the ability to safeguard oil tank farms, ensuring the stability of energy supply chains and contributing to broader energy security efforts. This study provides a valuable method for researchers and engineers seeking to enhance regional risk calculation efficiency, with a specific focus on energy risks.