智能柱塞气举排液技术应用研究  

Research on the application of intelligent plunger gaslift drainage technology

作　　者：杜芳利 袁书龙 刘为恺 武改红 景帅 DU Fangli;YUAN Shulong;LIU Weikai;WU Gaihong;JING Shuai(Yanchang Petroleum(Group)Co.,Ltd.,Gas Field Company,Yan'an Shaanxi 716000,China)

机构地区：[1]延长石油(集团)有限责任公司气田公司,陕西延安716000

出　　处：《石油化工应用》2024年第11期41-45,共5页Petrochemical Industry Application

摘　　要：延安气田开发层系是上古生界致密砂岩和下古生界海相碳酸盐岩,气藏认识普遍含水,排水采气是气田稳产的最重要措施。针对气井井筒积液分析、积液时机判断、优选气井排液方式难点问题,提出临界携液模型修正计算方法,应用智能柱塞自优化排液工艺研究。分别探讨了拽力系数CD取值对系数α的影响,计算不同尺寸生产管柱条件下的临界携液流量。通过建立柱塞井筒积液识别模型,利用边缘控制算法预测压力增长趋势与开井阶段气量指标模型对照,从而确定最佳关井时间点。最终得出临界携液模型优选系数α为1.85,对应的拽力系数CD为1.15,计算值符合研究区块气井实际生产动态。同时,智能控制算法能够实现对积液识别、自优化及时有效地清除井筒积液,排液效果明显,相比专人制定的开关井制度日增气为5%~8%,开井时率较之前提升6%~11%。研究结果表明,智能控制算法能够有效降低人员劳动强度,提高措施有效率,人工调参至少下降70%;能够实现全生命周期指导气井最佳生产状态,是未来数字气田发展趋势。The development strata of Yan'an gasfield consist of tight sandstones from the Upper Paleozoic and marine carbonate rocks from the Lower Paleozoic. Gas reservoirs are generally known to contain water, and drainage for gas production is the most important measure for stable production of the gasfield. A critical fluid carrying model correction calculation method is proposed to address the difficult issues of analyzing fluid accumulation in gas wells, determining the timing of fluid accumulation, and optimizing the drainage method of gas wells, research on the application of intelligent plunger self optimization drainage process. We separately explored the influence of the pulling force coefficient C_(D) on the coefficient value α and calculated the critical liquid carrying capacity under different sizes of production pipe columns. By establishing a plunger wellbore fluid accumulation identification model, using edge control algorithm to predict pressure growth trend and comparing it with the gas volume index model during the opening stage, the optimal shut in time point can be determined. The final optimal coefficient α for the critical liquid carrying model is 1.85, and the corresponding drag coefficient C_(D) is 1.15. The calculated values are in line with the actual production performance of gas wells in the study block. At the same time, intelligent control algorithms can achieve timely and effective removal of wellbore fluid accumulation through liquid identification, self optimization, and significant drainage effects. Compared with the well opening and closing system formulated by a dedicated person, the daily gas production rate is 5%~8%, and the well opening rate is increased by 6%~11% compared to before. The research results show that intelligent control algorithms can effectively reduce personnel labor intensity, improve the efficiency of measures, and reduce manual parameter adjustment by at least 70%. They can achieve the best production state of gas wells throughout the entire life cycle, which is

关 键 词：智能柱塞 临界携液模型 边缘控制算法 井筒积液判别 

分 类 号：TE375[石油与天然气工程—油气田开发工程]