集输管道腐蚀期限预测方法研究

发布时间：2018-06-14 19:30

本文选题：集输管道 + 腐蚀速率　；参考：《西安石油大学》2015年硕士论文

【摘要】：陕北A区块长2层油田随着开发时间的延长,油田地面集输系统配套管道腐蚀加剧,高含水、高含硫区块管道腐蚀情况更为复杂、严重。目前该区块年均因腐蚀而更换的各类管道长约30公里,直接经济损失约500万元,因管道腐蚀破漏而引发的安全环保问题亦频繁发生,次生影响尤为严重。腐蚀是影响埋地管线使用寿命的主要因素之一,管道腐蚀期限预测方法的研究将为管道腐蚀情况监控和提前补强提供依据。在腐蚀速率预测的前提下,首先调研陕北A区块长2层集输管线的腐蚀现状,分析站点输送介质。采用挂片失重法的室内实验评价影响A区块管线(20#钢)各种因素的腐蚀性。在实验的基础上,利用灰色关联法分析实验数据,评价各因素对腐蚀速率的影响程度大小,并进行排序,找出腐蚀速率的主要影响因素。结合遗传BP神经网络算法,对不同因素影响下的管线腐蚀速率进行预测,根据结果绘制对比曲线图,对比结果表明,预测结果与实验结果拟合度较高。进一步说明,将实验模拟和算法预测相结合可作为A区块集输管道腐蚀期限预测的良好工具。
[Abstract]:With the extension of development time, the pipeline corrosion of the ground gathering and transportation system of the oil field is aggravated and high water cut, and the corrosion of the high sulphur area pipeline is more complicated and serious. At present, the various kinds of pipelines replaced by corrosion in this block are about 30 kilometers long, and the direct economic loss is lost about 5 million yuan, which is caused by the leakage of the pipeline corrosion. The problems of safety and environmental protection also occur frequently, and the secondary impact is particularly serious. Corrosion is one of the main factors affecting the life of buried pipelines. The study of pipeline corrosion duration prediction method will provide basis for pipeline corrosion monitoring and advance reinforcement. Under the premise of corrosion rate prediction, the first investigation of the long 2 layer gathering pipeline in the A block of Northern Shaanxi Province The corrosion status of the site is analyzed. The corrosivity of various factors affecting the A block pipeline (20# steel) is evaluated by the laboratory experiment of hanging weight loss. On the basis of the experiment, the experimental data are analyzed by the grey correlation method, and the influence degree of each factor on the corrosion rate is evaluated, and the main effects of the corrosion rate are found out. In combination with the genetic BP neural network algorithm, the corrosion rate of pipelines under the influence of different factors is predicted, and the contrast curves are drawn according to the results. The comparison results show that the fitting of the prediction results with the experimental results is higher. Further illustrates that the combination of the experimental simulation and the algorithm prediction can be used as the good prediction of the corrosion period of the pipeline for the A block gathering and transportation. Good tools.
【学位授予单位】：西安石油大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TE988.2

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