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APPLICATION OF BAYES' MODEL TO OIL/GAS PROCESSING NETWORKS FAILURES

机译:贝叶斯模型在油/天然气处理网络故障中的应用

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This paper seeks to present the uncertain events that occur during the assessment and management of corrosion data survey by using Bayes' Model. In decision making, uncertainty about the outcomes of various situations is an important element of the analysis of the alternative strategies from which the choice must be made. The two main interpretations of probability in this paper are objective and subjective probabilities. Bayesian conditional probability theory is the approach adopted in the assessment of subjective probability. The Bayesian (or subjectivist) interpretation views the probability of an event as a subjective degree of belief, which taken into account all relevant knowledge and information. The cornerstone of Bayesian probability theory is the inversion formula due to Bayes. This paper therefore models pipeline oil/gas failures in line with Bayesian methods of diagnostic inference and evidence patterns along six broad categories of oil/gas failures: stress rupture, lack of quality control, environment, sand erosion, corrosion, and natural cause. The data generated in this study are from survey, which runs from Makaraba, Utonana, Abiteye, Dibi, Olero Creek, Opuekeba, and terminating at the Escravos Tank Farm of the Chevron western swamp facilities.
机译:本文旨在通过使用贝叶斯模型,展示在评估和管理腐蚀数据调查期间发生的不确定事件。在决策中,关于各种情况的结果的不确定性是分析必须进行选择的替代战略的重要因素。本文概率的两个主要解释是客观和主观概率。贝叶斯条件概率理论是对主观概率评估采用的方法。贝叶斯(或主旨)解释将事件视为主观信仰程度的概率,这考虑了所有相关知识和信息。贝叶斯概率理论的基石是由于贝叶斯导致的反转公式。因此,本文模拟了管道油/气体故障,符合贝叶斯诊断推理和沿六大类石油/天然气故障的证据模式:压力破裂,缺乏质量控制,环境,沙子腐蚀,腐蚀和自然原因。本研究中生成的数据来自调查,该调查从Makaraba,Utonana,Abiteye,Dibi,Olero Creek,Opuekeba运行,并在雪佛龙西沼泽设施的Escravos坦克农场终止。

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