油气藏评价与开发 ›› 2025, Vol. 15 ›› Issue (3): 500-507.doi: 10.13809/j.cnki.cn32-1825/te.2025.03.017

• 油气开发 • 上一篇    下一篇

基于改进饥饿游戏搜索算法的CO2水气交替驱注入参数优化

吴公益1(), 孙宇新2, 孙晓飞2, 姬洪明1, 张艳玉2   

  1. 1.中国石化华东油气分公司泰州采油厂,江苏 泰州 225300
    2.中国石油大学(华东)石油工程学院,山东 青岛 266580
  • 收稿日期:2025-01-06 发布日期:2025-05-28 出版日期:2025-06-26
  • 作者简介:吴公益(1982—),男,硕士,高级工程师,从事油田开发管理工作。地址:江苏省泰州市海陵区南通路99号,邮政编码:225300。E-mail:50750032@qq.com
  • 基金资助:
    国家重点研发计划项目“区域二氧化碳捕集与封存关键技术研发与示范”(2022YFE0206800)

Optimization of CO2 water-alternating-gas injection parameters based on an improved hunger game search algorithm

WU Gongyi1(), SUN Yuxin2, SUN Xiaofei2, JI Hongming1, ZHANG Yanyu2   

  1. 1. Taizhou Oil Production Plant, Sinopec East China Oil & Gas Company, Taizhou, Jiangsu 225300, China
    2. School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, Shandong 266580, China
  • Received:2025-01-06 Online:2025-05-28 Published:2025-06-26

摘要:

CO2驱是目前低渗透油藏提高采收率的重要手段,但受油藏非均质性影响,长期注气极易导致CO2气窜,使得油藏中存在大量剩余油,极大影响CO2驱开发效果。CO2水气交替驱(CO2 WAG)是一种抑制低渗油田CO2气窜的有效技术,其实施过程中涉及注入速度、段塞大小和气水比等众多注入参数,不合理的注入参数难以发挥其提高原油采收率作用。传统油藏数值模拟方法确定最优注入参数方案费时费力,成本高,大型油田多井复杂注入参数组合下甚至难以实现。该研究将饥饿游戏搜索算法引入CO2水气交替驱注入参数优化过程,并利用混沌映射函数提高其初始注入参数取值的随机性和多样性,形成一种新的混沌映射函数改进饥饿游戏搜索算法,实现算法与油藏数值模拟软件的协同智能优化,提高典型油田CO2水气交替驱注入参数优化的精度和效率。研究表明:与Logistic、Gussia和Singer混沌映射函数相比,Tent混沌映射函数所得混沌值和频数分布更加均匀,适合于改进饥饿游戏搜索算法。Tent混沌映射函数改进饥饿游戏搜索算法是一种有效的CO2水气交替驱注入参数优化方法。该算法所得CO2水气交替驱最优注入参数方案累积产油量为34.974×104 m3,比饥饿游戏搜索算法所得累积产油量增加0.213×104 m3,比现有CO2水气交替驱注入参数方案增加5.820×104 m3,为现场CO2水气交替驱高效实施提供了有效技术手段。

关键词: 低渗油田, CO2水气交替驱, 混沌映射函数, 饥饿游戏搜索算法, 注入参数优化

Abstract:

CO2 flooding is an important method to enhance oil recovery in low-permeability reservoirs. However, due to the heterogeneity of the reservoir, long-term CO2 injection can easily lead to CO2 gas channeling, leaving a large amount of residual oil in the reservoir, which severely impacts the effectiveness of CO2 flooding. CO2-water-alternating-gas flooding (CO2 WAG) is an effective technique to suppress CO2 gas channeling in low-permeability oilfields. During the implementation of CO2 WAG, numerous injection parameters such as injection rate, slug size, and gas-water ratio are involved. Unreasonable injection parameters make it difficult to achieve improved oil recovery. Traditional reservoir numerical simulation methods for determining optimal injection parameters are time-consuming, labor-intensive, and costly, and may be unfeasible in large oilfields with complex multi-well injection parameter combinations. The hunger game search algorithm was introduced to optimize the injection parameters for CO2 WAG, with the addition of chaotic mapping functions to enhance the randomness and diversity of initial injection parameter values. This new approach formed an improved hunger game search algorithm based on chaotic mapping functions, allowing for collaborative intelligent optimization between the algorithm and reservoir simulation software. This method enhanced the accuracy and efficiency of CO2 WAG injection parameter optimization for typical oilfields. Compared to the Logistic, Gaussian, and Singer chaotic mapping functions, the Tent chaotic mapping function resulted in more evenly distributed chaotic values and frequency distributions, making it a better choice for improving the hunger game search algorithm. The hunger game search algorithm improved by the Tent chaotic mapping function is an effective method for optimizing CO2 WAG injection parameters. The optimal CO2 WAG injection parameters derived from this approach lead to a cumulative oil production of 34.974×104 m³, a 0.213×104 m³ increase over the results from the Hunger Game Search algorithm, and 5.820×104 m³ more than the current CO2 WAG injection parameter scheme. This approach provides an effective technical solution for the efficient implementation of CO2 WAG in the field.

Key words: low-permeability oilfields, CO2 water-alternating-gas (CO2 WAG) flooding, chaotic mapping function, hunger game search algorithm, optimization of injection parameters

中图分类号: 

  • TE348