石油学报 ›› 2019, Vol. 40 ›› Issue (8): 975-982.DOI: 10.7623/syxb201908008

• 油田开发 • 上一篇    下一篇

深水气井水合物沉积预测新模型

高永海1,2, 孟文波3, 崔燕春1, 张崇3, 陈野1, 董钊3, 孙金声1,2, 孙宝江1,2   

  1. 1. 中国石油大学(华东)非常规油气开发教育部重点实验室 山东青岛 266580;
    2. 中国石油大学(华东)石油工程学院 山东青岛 266580;
    3. 中海石油(中国)有限公司湛江分公司 广东湛江 524057
  • 收稿日期:2018-07-10 修回日期:2019-06-10 出版日期:2019-08-25 发布日期:2019-08-28
  • 通讯作者: 孙宝江,男,1963年11月生,1985年获华东石油学院学士学位,1999年获北京大学流体力学专业博士学位,现为中国石油大学(华东)教授,主要从事海洋石油工程、井控、多相流动、油气井流体力学与工程研究工作。Email:sunbj1128@126.com
  • 作者简介:高永海,男,1977年9月生,2000年获山东工程学院学士学位,2008年获中国石油大学(华东)油气井工程专业博士学位,现为中国石油大学(华东)副教授,主要从事海洋石油工程、井筒多相流研究工作。Email:upcgaoyh@126.com
  • 基金资助:

    国家自然科学基金项目(No.51876222)、教育部创新团队项目(IRT_14R58)和中国海洋石油集团公司重大专项"深水测试关键技术研究"(CNOOC-KJ135ZDXM05LTDZJ02)资助。

A new prediction model for hydrate deposition in deepwater gas well

Gao Yonghai1,2, Meng Wenbo3, Cui Yanchun1, Zhang Chong3, Chen Ye1, Dong Zhao3, Sun Jinsheng1,2, Sun Baojiang1,2   

  1. 1. Key Laboratory of Unconventional Oil & Gas Development, Ministry of Education, China University of Petroleum, Shandong Qingdao 266580, China;
    2. School of Petroleum Engineering, China University of Petroleum, Shandong Qingdao 266580, China;
    3. Zhanjiang Branch, CNOOC China Limited, Guangdong Zhanjiang 524057, China
  • Received:2018-07-10 Revised:2019-06-10 Online:2019-08-25 Published:2019-08-28

摘要:

由水合物聚结、沉积导致的井筒堵塞是气井测试中常见的安全隐患。预测水合物的生成与沉积规律,有利于控制事故风险、降低生产损失。通过对水合物颗粒在管流气核区和管壁附近的生成与运移机理分析的基础上,引入液滴沉积比率和转化比率,建立了一种适用于环雾流条件下的水合物沉积预测新模型,并参照实际工况设计了实验验证。实验结果表明,理论值与实验值趋势一致,平均偏差为4.9%,验证了模型的可靠性。以深水井X井为例,通过数值模拟探究了不同位置处水合物沉积规律。试算结果表明,水合物沉积堵塞过程可以划分为4个阶段,其中初始沉积阶段、临界沉积阶段所占时间比例较短,而沉积亚稳态生长阶段、沉积快速生长阶段所占时间比例较长。水合物堵塞主要发生在井筒偏上部分,尤其是井口附近。随着深度的增长,水合物沉积速率与沉积厚度逐渐减少,且减小幅度逐渐增大,堵塞风险减小。

关键词: 深水, 水合物颗粒, 转化比率, 沉积预测模型, 沉积规律

Abstract:

The wellbore blockage caused by hydrate coalescence and deposition is a common safety hazard in gas well testing. The prediction on hydrate formation and deposition laws is conductive to control accident risk and reduce production loss. This paper analyzes the formation and migration of hydrate particles at the tube center and inner wall, respectively. Through introducing the droplet deposition ratio and conversion ratio, a new hydrate deposition prediction model suitable for annular mist flow has been established on the basis of mechanism analysis; it has been verified by experiment simulating the actual reaction under field conditions. The theoretical and experimental values show the same trend with an average deviation of 4.9%, thus validating the reliability of the model. Taking a deepwater well as a case, the hydrate deposition laws at different positions have been studied by numerical simulation. The calculation results indicate that the hydrate deposition and blockage process can be divided into four stages, in which the initial deposition stage and the critical deposition stage account for shorter time, while the deposition metastable growth stage and the deposition rapid growth stage account for longer time. Hydrate blockage mainly occurs in the upper part of wellbore, especially the area near the wellhead. With the increase of depth, the hydrate deposition rate and deposition layer thickness gradually decrease, and the decreasing range increases gradually, reducing the wellbore blockage risk.

Key words: deepwater, hydrate particle, conversion ratio, deposition prediction model, deposition rules

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