| 摘要: |
| 海底管道是海洋油气输送的主要方式, 其运行状况直接关系到海上油气田的安全和海洋生态环境的质量。本文先以海底管道出露悬空作为故障树的顶事件, 分析出海洋环境中各项基本事件, 构建针对海洋环境的海底管道故障树模型; 再以灰色模糊识别为理论基础, 量化对海底管道安全有影响的海洋环境因素, 并以层次分析法对每个风险因素进行分级赋权, 确定评价指标范围和权重, 进而构建海洋环境条件的海底管道风险评价体系。利用该体系对平湖油气田海底管道4个区段进行环境风险评价, 避免了将整段管道一同评价导致的信息均等化, 评价结果不能真实反映风险等级高的区段的情况; 评价结果与管道2014～2016年现场检测数据对比, 两者均显示P2分区中海底管道的风险等级较高, 说明了该模型具有一定的合理性和实用性。 |
| 关键词: 海底管道 环境风险评价 灰色模糊综合评价模型 海洋因素 |
| DOI：10.11759/hykx20170417001 |
| 分类号: |
| 基金项目:海洋公益性行业科研专项项目(201305026); 国家海洋局重点实验室开放研究基金课题(MATHAB201607) |
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| Quantitative assessment of environmental risk for exposed and dangling marine pipeline |
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LI Jia-jun,GUO Wei-qi,ZHANG Jie,CHEN Xin-xi
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| Abstract: |
| The submarine pipeline, whose operating conditions are directly related to the safety of the offshore oil and gas fields and quality of the marine ecological environment, is a major route of marine oil and gas transportation. In this study, an exposed and dangling submarine pipeline was used as the top of the fault tree to analyze the basic events of the marine environment. Subsequently, a submarine pipeline fault tree model for the marine environment was developed. Then, based on the theory of grey fuzzy identification, a risk assessment system of the submarine pipeline was established based on the grey fuzzy recognition theory and the analytic hierarchy process for each enhanced risk factor. With the above system, the environmental risk assessment of the submarine pipeline in the Pinghu oil and gas field was divided into four segments and risk assessment was carried out to avoid the equalization of information caused by the evaluation of the entire pipeline. The evaluation results cannot truly reflect the situation of the high-stakes segments. A comparison between the evaluation results and the on-site data from 2014 to 2016 showed that the risk level of the submarine pipeline in the P2 segment was higher than those in other segments. It was demonstrated that this model is reasonable and practical. |
| Key words: Pinghu oil and gas pipeline environmental risk assessment comprehensive evaluation model of grey fuzzy marine factor |
