基于天鹰优化器(AO)算法的气田管网布局优化  

Optimization of Gas Field Pipeline Network Layout Based on Aquila optimizer

作　　者：陈卓 田洋阳[1,2] 马田田 王宁宁 CHEN Zhuo;TIAN Yang-yang;MA Tian-tian;WANG Ning-ning(College of Petroleum Engineering,Xi'an Shiyou University,Xi'an Shaanxi 710065,China;Key Laboratory of Special Stimulation Technology for Oil and Gas Fields of Shaanxi Province,Xi'an Shaanxi 710065,China;Xi'an Fengyuan Gas Co.,Ltd.,Xi'an Shaanxi 710117,China)

机构地区：[1]西安石油大学石油工程学院,陕西西安710065 [2]陕西省油气田特种增产技术重点实验室,陕西西安710065 [3]西安丰源燃气有限公司,陕西西安710117

出　　处：《当代化工》2022年第12期2898-2902,2906,共6页Contemporary Chemical Industry

基　　金：陕西省教育厅专项科研计划项目,(项目编号:21JK0831)。

摘　　要：在进行天然气田地面集输系统建设时,气田管网是其重要的组成部分,为减少地面管网集输系统建设成本、节约管网建设资源,使用天鹰优化器(AO)算法结合气田建设工程约束实际条件,对集输管网进行布局优化,以达到最小管网投资的目的。通过MATLAB软件对天鹰优化器算法进行编码实现,对所建立的气田管网数学模型分别进行分层规划以及整体规划。结果表明:整体规划所建立的气田管网优于分层规划所建立的气田管网。通过与标准粒子群、改进粒子群算法进行比较,验证了天鹰优化器算法的有效性以及稳定性。In the construction of the surface gathering and transportation system of natural gas fields, the gas field pipeline network is an important part of it. In order to reduce the construction cost of the surface pipeline network gathering and transportation system and save the resources of the pipeline network construction, the Aquila optimizer(AO) algorithm was used in conjunction with the gas field construction project. Based on the actual constrain conditions, the layout of the gathering and transportation pipeline network should be optimized to achieve the goal of minimum pipeline network investment. In this paper, the AO algorithm was coded by MATLAB software, and the mathematical model of the established gas field pipeline network was implemented by layered planning and overall planning. The results showed that the gas field pipeline network established by the overall planning was better than that established by the layered planning method. Compared with the standard particle swarm and improved particle swarm algorithm, the effectiveness and stability of the AO algorithm were verified.

关 键 词：气田管网 天鹰优化器 集输布局 优化设计 

分 类 号：TE41[石油与天然气工程—油气田开发工程] TE862