辽宁石油化工大学学报

辽宁石油化工大学学报 ›› 2022, Vol. 42 ›› Issue (5): 50-56.DOI: 10.3969/j.issn.1672-6952.2022.05.008

• 石油与天然气工程(天然气水合物专栏) • 上一篇    下一篇

干预作业下深水气井井筒水合物沉积规律研究

邹发宝1(), 张海翔1,2,3,4, 霍伟欣1, 陈曦1, 干毕成1,2, 李佳雯5, 冯加志6   

  1. 1.东北石油大学 石油工程学院,黑龙江 大庆 163318
    2.东北石油大学 三亚海洋油气研究院,海南 三亚 572025
    3.黑龙江省天然气水合物高效开发重点实验室,黑龙江 大庆 163318
    4.东北石油大学 提高油气采收率教育部重点实验室,黑龙江 大庆 163318
    5.大庆油田有限责任公司 第四采油厂,黑龙江 大庆 163000
    6.东北石油大学 非常规油气研究院,黑龙江 大庆 163318
  • 收稿日期:2022-06-07 修回日期:2022-06-27 出版日期:2022-10-25 发布日期:2022-11-18
  • 通讯作者: 张海翔
  • 作者简介:邹发宝(1997⁃),男,硕士研究生,从事海上油气田开发方面的研究;E⁃mail:zoufabao@foxmail.com
  • 基金资助:
    海南省自然科学基金项目面上项目(521MS0793)

Study of Hydrate Deposition Pattern in Deepwater Gas Wellbore under Intervention Operation

Fabao Zou1(), Haixiang Zhang1,2,3,4, Weixin Huo1, Xi Chen1, Bicheng Gan1,2, Jiawen Li5, Jiazhi Feng6   

  1. 1.School of Petroleum Engineering,Northeast Petroleum University,Daqing Heilongjiang,163318,China
    2.Sanya Offshore Oil and Gas Research Institute,Northeast Petroleum University,Sanya Hainan 572025,China
    3.Heilongjiang Key Laboratory of Natural Gas Hydrate Development,Daqing Heilongjiang 163318,China
    4.Key Laboratory of Enhanced Oil Recovery,Northeast Petroleum University,Daqing Heilongjiang 163318,China
    5.Fourth Oil Extraction Plant,Daqing Oilfield Co. Ltd. ,Daqing Heilongjiang 163000,China
    6.Institute of Unconventional Oil & Gas,Northeast Petroleum University,Daqing Heilongjiang 163318,China
  • Received:2022-06-07 Revised:2022-06-27 Published:2022-10-25 Online:2022-11-18
  • Contact: Haixiang Zhang

摘要:

了解水合物沉积规律,可为深水气井干预作业方案优化及井筒内水合物防治提供思路。在气液两相流动模型的基础上,结合干预作业工具下放引起的热量交换和摩阻梯度变化,建立了干预作业下井筒压力和温度预测模型,采用迭代法对温度和压力模型耦合求解。基于水合物生长动力学模型,结合井筒温度和压力预测结果,建立水合物沉积模型,分析了干预作业下井筒内水合物沉积规律。结果表明,产量的增加导致井筒内压差升高,高产量下泥线处井筒温度较高;随着干预作业工具的下放,井筒内压力升高,但压力升高幅度逐渐减小,井口处压力的最大升高幅度约为3.0 MPa;干预作业工具直径占比小于50%时,干预作业工具直径越大,井筒压力越高;井筒泥线位置是水合物沉积堵塞高风险区域,低产井的水合物沉积速度比高产井的水合物沉积速度快;干预作业工具下放至泥线附近时井筒水合物沉积速度最快,干预作业工具直径占比50%时井筒水合物沉积速度较快。

关键词: 干预作业, 井筒温压预测, 水合物沉积, 深水气井

Abstract:

Understanding the hydrate deposition law can provide ideas for the optimization of intervention operation plans and the prevention and control of hydrate in the wellbore of deepwater gas wells. On the basis of the gas?liquid two?phase flow model, a wellbore pressure and temperature prediction model was developed based on the heat exchange and frictional gradient changes caused by the lowering of the intervention tool, and the temperature and pressure models were coupled to solve by the iterative method. Based on the hydrate growth kinetic model, combined with the wellbore temperature and pressure prediction results, a hydrate deposition model was established, and the hydrate deposition law in the wellbore under intervention operations was analyzed. The results showed that the increase of production led to the increase of pressure difference in the wellbore and the higher wellbore temperature at the mudline under high production. With the release of the intervention tool, the pressure in the wellbore increases, but the pressure increase gradually decreases, and the maximum pressure increase at the wellhead is about 3.0 MPa. When the proportion of the intervention tool diameter is less than 50%, the larger the tool diameter, the higher the wellbore pressure. The location of the wellbore mudline is a high?risk area for hydrate deposition plugging, and the rate of hydrate deposition in low?producing wells is faster than that in high?producing wells. The wellbore hydrate deposition rate is the fastest when the intervention tool is placed near the mudline, and the wellbore hydrate deposition rate is faster when the intervention tool diameter accounts for 50%.

Key words: Intervention operation, Wellbore temperature and pressure prediction, Hydrate deposition, Deepwater gas well

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引用本文

邹发宝, 张海翔, 霍伟欣, 陈曦, 干毕成, 李佳雯, 冯加志. 干预作业下深水气井井筒水合物沉积规律研究[J]. 辽宁石油化工大学学报, 2022, 42(5): 50-56.

Fabao Zou, Haixiang Zhang, Weixin Huo, Xi Chen, Bicheng Gan, Jiawen Li, Jiazhi Feng. Study of Hydrate Deposition Pattern in Deepwater Gas Wellbore under Intervention Operation[J]. Journal of Liaoning Petrochemical University, 2022, 42(5): 50-56.

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