This article presents a new risk model for estimating the probability of allision risk (the impact between a ship under way and a stationary installation) from passing vessels on the Norwegian Continental Shelf (NCS). Offshore petroleum operators on the NCS are required by the Norwegian Petroleum Safety Authority (PSA) to perform risk assessments to estimate the probability of impacts between ships and offshore installations, both for field related and passing (merchant) vessels. This has typically been done using the aging industry standard COLLIDE risk model, but this article presents a new risk model based on a Bayesian Belief Network (BBN) that can replace the old COLLIDE model for passing vessels. The new risk model incorporates a wider range of risk influencing factors (RIFs) and enables a holistic and detailed analysis of risk factors, barrier elements and dependencies. Even though the risk of allision with passing vessels is very small, the potential consequences can be critical. The new risk model is more transparent and provides a better understanding of the mechanisms behind allision risk calculations. The results from the new model are aligned with industry expectations, indicating an overall satisfactory performance. The article discusses several key elements, such as the use of expert judgement to estimate RIFs when no empirical data is available, model sensitivity, and a comparative assessment of the new risk model to the old COLLIDE model.

本文介绍了一种新的风险模型，用于估算在挪威大陆架（NCS）上越过船只而引起的变态风险（航行中的船舶与固定安装之间的影响）的可能性。挪威石油安全局（PSA）要求NCS上的近海石油经营者进行风险评估，以评估船舶和近海设施之间的碰撞对现场和通行（商船）船舶的可能性。通常使用老化的行业标准COLLIDE风险模型来完成此操作，但是本文提出了一种基于贝叶斯信念网络（BBN）的新风险模型，该模型可以替代过往船只的旧COLLIDE模型。新的风险模型结合了更广泛的风险影响因素（RIF），并可以对风险因素进行全面而详细的分析，障碍要素和依赖性。即使经过血管发生变态的风险很小，潜在的后果也很关键。新的风险模型更加透明，可以更好地理解变态风险计算背后的机制。新模型的结果符合行业预期，表明总体表现令人满意。本文讨论了几个关键要素，例如在没有经验数据时使用专家判断来估计RIF，模型敏感性以及新风险模型与旧COLLIDE模型的比较评估。新的风险模型更加透明，可以更好地理解变态风险计算背后的机制。新模型的结果符合行业预期，表明总体表现令人满意。本文讨论了几个关键要素，例如在没有经验数据时使用专家判断来估计RIF，模型敏感性以及新风险模型与旧COLLIDE模型的比较评估。新的风险模型更加透明，可以更好地理解变态风险计算背后的机制。新模型的结果符合行业预期，表明总体表现令人满意。本文讨论了几个关键要素，例如在没有经验数据时使用专家判断来估计RIF，模型敏感性以及新风险模型与旧COLLIDE模型的比较评估。