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基于机采和集油系统整体能耗最低的集油参数优化方法
董世民,王宏博,孙秀荣,童志雄,孙亮
(燕山大学机械工程学院,河北秦皇岛 066004)
摘要:
将环状集油环上的抽油机井与集油管网作为研究对象,基于多相水平管流模型和抽油机井动态参数的仿真技术建立集油管网压降、抽油机井井口油压与集油系统掺水参数关系的仿真模型及抽油机井输入功率、油井产量与井口油压之间关系的数学模型,即抽油机井输入功率、油井产量与掺水参数之间关系的数学模型。分别以集油和机采系统总能耗最低、集油和机采系统效益最大为优化设计的目标函数,建立集油系统掺水参数优化设计的数学模型。结果表明:井口油压对抽油机井输入功率与油井产量有显著影响;掺水温度与掺水流量对集油和机采系统总能耗、总效益具有显著影响,将机采与集油系统作为整体优化可显著提高系统整体经济效益。
关键词:  集油系统  机采系统  掺水参数  整体仿真  整体优化
DOI:10.3969/j.issn.1673-5005.2017.05.015
分类号::TE 933
文献标识码:A
基金项目:国家自然科学基金项目(51174175)
Oil gathering parameters optimization method based on the lowest energy consumption of machine mining and oil gathering system
DONG Shimin, WANG Hongbo, SUN Xiurong, TONG Zhixiong, SUN Liang
(School of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, China)
Abstract:
The pumping well of the annular oil collecting ring, and the oil gathering pipe network are taken to analyze. Based on the multiphase flow model in the horizontal tube, in combination with the simulation technology on the dynamic parameters of the pumping, the simulation model on the relationship among the pressure drop in the oil gathering pipe network, the wellhead pressure of the pumping well and the watered parameters in the oil gathering system is built. Then another simulation model on the relationship among the input power of pumping wells, oil production and wellhead pressure is also given. Taking the lowest energy consumption and the biggest system benefit as the objective function for optimization, a mathematical model on the watered parameters optimization in the oil gathering system is presented. The results show that the inlet oil pressure has a significant effect on the input power and well production, and the water temperature and flow have great influences on the total energy consumption and system benefit. The overall optimization on the machine mining and oil gathering system can significantly improve the overall economic benefit of the system.
Key words:  oil gathering system  machine mining system  watered parameters  overall simulation  overall optimization
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