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Probabilistic assessment of external corrosion rates in buried oil and gas pipelines

机译:埋地油气管道外部腐蚀速率的概率评价

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Quantitative risk assessment due to external corrosion requires an estimation of corrosion rates which is a challenging task for pipeline engineers because of the uncertainty in data related to environmental and physical variables such as soil type, drainage, soil chemistry, CP effectiveness, coating type and coating properties. Unfortunately, the research into quantitative assessment of external corrosion rates and the probability of failure of a buried pipeline is limited and has not progressed significantly. The reason is the complex mechanism of external corrosion, numerous factors affecting it, and the uncertainty in the knowledge of the variables. There is the need of a probabilistic external corrosion methodology that compiles in one framework field data, multiple analytical methods (i.e. mechanistic models from various sources and multiple risk modelling methods are combined in one unified method) and expert knowledge. In this paper a novel model for quantitative assessment of corrosion rates using Bayesian network method is proposed. Bayesian Networks are graphical models based on cause-consequence relationships that are quantified through conditional probability tables based on a combination of information available from subject matter experts, mechanistic models, and field data. A case study is presented to assess the probability of failure due to external corrosion in a crude oil buried pipeline located in Eastern China. The model was validated using in-line inspection data.
机译:由于外部腐蚀导致的定量风险评估需要估算腐蚀速率,这是管道工程师的具有挑战性的,因为与土壤类型,排水,土壤化学,CP效能,涂层类型和涂层有关的数据和物理变量有关的数据不确定性特性。遗憾的是,对外部腐蚀速率的定量评估以及埋地管道失效概率的研究有限,并且尚未显着进行。原因是外部腐蚀的复杂机制,影响它的许多因素,以及变量知识的不确定性。需要一种概率的外部腐蚀方法,其在一个框架现场数据中编译多种分析方法(即来自各种来源的机械模型以及多种风险建模方法的组合在一个统一的方法中,专家知识。本文提出了一种新型,用于使用贝叶斯网络方法进行腐蚀速率的定量评估模型。贝叶斯网络是基于原因的图形模型,其基于根据来自主题专家,机械模型和现场数据可获得的信息的组合来通过条件概率表量化的导致后果关系。提出了一个案例研究以评估由于位于中国东部的原油埋地管道的外部腐蚀,评估失败的可能性。使用在线检查数据进行验证该模型。

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