摘要
通过对油田集输管网的分析研究,建立了基于产量距离之和最小的井组最优划分的数学模型,并采用基于整数编码的遗传算法对模型进行了求解。实例计算表明:建立的以产量距离之和最小为目标的数学模型更能反映集油管网投资的经济性,采用基于整数编码的遗传算法进行求解,其寻优效益高,且收敛性和稳定性也较好。最后求得的产量距离和为18937.93 km.t/d,比文献[2]中的划分结果小1381.07 km.t/d.
By analyzing and researching the oil gas gathering and transportation pipeline network,taking the shortest total yield distance as the object function,a mathematical molel is established for dividing the group of wells optimally,then it has solved the model by Genetic Algorithm(GA) based on integer coding.The calculation of the examples' shows that the mathematical model with the shortest total yield distance as the object function can better reflect economical value of investment in the oil gathering pipeline;meanwhile,the profit of seeking the optimal result by GA based on integer coding is higher,thus helping obtain a better astringency and stability.As a result,the final shortest total yield distance is 18 937.93 km·t/d,which was 1 381.07 km·t/d shorter than the result of the literature[2].
出处
《管道技术与设备》
CAS
2007年第6期1-2,4,共3页
Pipeline Technique and Equipment
基金
西南石油大学研究生创新基金(cxjj27026)
关键词
集输管网
井组划分
优化设计
数学模型
遗传算法
gathering and transferring pipeline networks
well group division
optimal design
mathematical model
Genetic Algorithm
作者简介
吴华丽(1982-),硕士研究生,研究方向为油气管网系统优化运行及管理.
