基于高斯烟羽模型和ISSA算法的油气站场泄漏检测研究  被引量:1

Research on leak detection of oil and gas station based on Gauss plume model and ISSA algorithm

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作  者:刘若兮 陶野 赵元东 李彦华 王婷婷 梁昌晶 LIU Ruoxi;TAO Ye;ZHAO Yuandong;LI Yanhua;WANG Tingting;LIANG Changjing(No.5 Oil Production Plant of Huabei Oilfield Company,CNPC,Xinji 052300,China;New Energy Division of Huabei Oilfield Branch,CNPC,Renqiu 062552,China;The Erlian Filiale of Huabei Oilfield Company,Xilinhot 026000,China)

机构地区:[1]中国石油华北油田分公司第五采油厂,河北辛集052300 [2]中国石油华北油田分公司新能源事业部,河北任丘062552 [3]中国石油华北油田公司二连分公司,内蒙古锡林浩特026000

出  处:《石油工程建设》2024年第2期71-76,81,共7页Petroleum Engineering Construction

摘  要:为提高油气站场泄漏检测的预测精度,降低事后处理带来的经济损失和环境污染,将高斯烟羽模型作为前向气体扩散模型,通过Circle混沌映射初始化麻雀种群,将蝴蝶算法加入麻雀发现者搜索策略中,随后利用算法实现质量浓度误差最小化的迭代计算,并从迭代次数、种群规模、网格尺寸和噪声强度等方面衡量其对反演结果的影响。结果表明,算法在时间算法复杂度上与SSA算法一致,优化后算法的全局搜索能力和局部开发能力增强;通过将地理坐标系转化为标准风向坐标系,简化了计算过程;在最大迭代次数100、种群规模100、网格尺寸0.5 m×0.5 m×0.5 m的设置下,当站场内存在2个监测点受噪声影响时,3个方向上泄漏位置的最大误差分别为1.37%、1.02%、9.70%,泄漏速率的最大相对误差为0.22%,符合现场定位检测的需求。研究结果可为油气站场完整性管理水平的提升提供实际参考。In order to improve the prediction accuracy of leakage detectionat oil and gas stations and reduce the economic loss and environmental pollution caused by post-treatment,the Gaussian plume model was used as a forward gas diffusion model,the sparrow population initialized through Circle chaotic mapping,and the butterfly algorithm added to the sparrow finder search strategy;then,the ISSA algorithm was used to achieve the iterative calculation of the concentration error minimization,with its influence on the inversion results measured from the perspectives of iteration times,population size,mesh size and noise intensity.The results show that the ISSA algorithm is consistent with the SSA algorithm in the complexity of time algorithm,with the global search ability and local development ability of the optimized algorithm enhanced.By transforming the geographical coordinate system into the standard wind direction coordinate system,the calculation process was simplified.Under the settings of maximum iteration number 100,population size 100 and grid size 0.5 m×0.5 m×0.5 m,when there are two monitoring points in the station affected by noise,the maximum error of leakage position in the three directions is 1.37%,1.02%and 9.70%respectively,and the maximum relative error of leakage rate 0.22%,meeting the requirements of on-site location detection.The research results can provide practical reference for the improvement of the integrity management of oil and gas stations.

关 键 词:高斯烟羽模型 SSA 泄漏 反演模型 噪声强度 

分 类 号:TP18[自动化与计算机技术—控制理论与控制工程] TE974[自动化与计算机技术—控制科学与工程]

 

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