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Risk assessment of decommissioning options using Bayesian networks

机译:利用贝叶斯网络风险评估退役选项

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For complex and costly decommissioning activities it is beneficial, if not necessary, that all relevant risks are identified and assessed on an overall basis, treating and assessing all risks within the same theoretical framework. Only then may the different options be consistently compared and the risks associated with decommissioning demonstrated and documented to the different parties of interest. The present paper suggests an approach for assessing the risks associated with the decommissioning of offshore facilities. The approach takes basis in a discrete point in time representation of the considered decommissioning options where important phases of the options are represented in terms of event scenarios. Using the possibilities of Bayesian Probabilistic Networks (BPN) the failure probabilities and risk events involved in the modeling of an option may then be analyzed for each phase and added up time-wise over the entire decommissioning process. The principles of BPNs are shortly described and the proposed approach is illustrated by an example linking the operational and structural risks in connection with a re-float decommissioning option for a concrete offshore platform. It is shown how the sensitivity may be evaluated on the basis of the BPNs, thus providing a valuable framework to first improve the risk model in terms of the representation of important scenarios, then for deciding where to apply additional safety measures most effectively, and last but not least to demonstrated and document the contributions to the mission failure probability.
机译:对于复杂和昂贵的退役活动,如果没有必要,则有益,即所有相关风险都是在整体基础上进行确定和评估,对待和评估同一理论框架内的所有风险。只有这样,才能持续不同的选择,并且对退役有关的风险证明并记录在不同的利益方方面。本文建议评估与离岸设施退役有关的风险的方法。该方法以离散的时间点为基础,考虑到所考虑的退役选项,其中选项的重要阶段是在事件方案方面代表的。利用贝叶斯概率网络(BPN)的可能性,可以为每个阶段分析选项建模中涉及的故障概率和风险事件,并在整个退役过程中添加了上方面的时间。短暂描述了BPN的原理,并且通过将操作和结构风险联系在一起的混凝土海上平台的重新浮动退役选项,通过示例来说明所提出的方法。示出了如何基于BPNS评估灵敏度,从而提供有价值的框架,以便在重要场景的表示方面首先改进风险模型,然后决定最有效地应用额外的安全措施,并且最后但并非最不愿意证明并向任务失败概率造成的贡献。

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