Globally, oil pipeline failures can lead to catastrophic human casualties, environmental damage, and economic losses, emphasizing the need for robust risk management. This study addresses these challenges through a case analysis of the Cheshmeh-Khosh–Ahvaz oil pipeline in southwestern Iran, integrating multiple methodologies within a dynamic risk assessment framework. The approach combines Fault Tree Analysis (FTA) and Failure Modes and Effects Analysis (FMEA) to identify and evaluate operational risks systematically, employs fuzzy logic to quantify uncertain linguistic data, and incorporates a Bayesian Network (BN) for real-time probability updating. The model is informed by field observations, expert interviews, and historical data, and Bayesian inference enables continuous updating of failure likelihoods as new information emerges. This multi-method approach quantifies uncertainty and dynamically reprioritizes risk factors, identifying improper pipeline routing as a dominant failure cause in the case study. Notably, while prior studies applied fuzzy FTA to subsea pipeline systems, this work is the first to implement a fuzzy-FTA–FMEA–BN methodology for a terrestrial pipeline, capturing onshore-specific risk factors and enabling real-time risk updates. Practical implications include enhanced pipeline safety through real-time monitoring and targeted maintenance, as well as improving resource allocation to mitigate the highest risks. In sum, the integrated framework offers both a theoretical advancement in probabilistic risk modeling and an operational tool for safer pipeline decision-making.