基于改进秃鹰搜索算法的聚合物驱油井组劈分
作者:
基金项目:

国家自然科学基金(42002138); 黑龙江省博士后专项(LBH-Q20077); 黑龙江省优秀青年教师基础研究支持计划(YQJH2023073); 黑龙江省研究生课程思政建设项目计算智能及石油大数据分析导学思政团队(YJSKCSZ_202303)


Polymer Flooding Well Group Splitting Based on Improved Bald Eagle Search Algorithm
Author:
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [25]
  • |
  • 相似文献 [20]
  • | | |
  • 文章评论
    摘要:

    针对现有聚合物用量劈分算法, 在处理不同区块井组时自适应性不足的问题, 本文提出基于改进秃鹰搜索算法的聚合物驱油井组劈分方法, 首先通过灰色关联度分析法获得初步劈分系数, 进而计算每个采油井的累计注入量与实际产液量的差值, 并设定合理阈值范围和约束条件; 其次通过引入Sobol序列和ICMIC映射、黄金正弦莱维飞行引导机制及非线性收敛因子和自适应惯性权重策略改进秃鹰搜索算法, 增强算法的搜索能力和收敛精度; 最后利用改进秃鹰搜索算法对某油田实际区块内井组劈分系数优化模型进行求解, 结果表明计算出的劈分注入量与实际产液量吻合度较高, 具有较好的劈分精度.

    Abstract:

    Given the insufficient adaptability of existing polymer dosage splitting algorithms when dealing with well groups in different blocks, this study proposes a polymer flooding well group splitting method based on an improved bald eagle search algorithm. Firstly, the preliminary splitting coefficients are obtained through grey correlation analysis. Then, the difference between the cumulative injection volume and the actual fluid production volume of each extraction well is calculated, and a reasonable threshold range and constraint conditions are set. Secondly, the bald eagle search algorithm is improved by introducing Sobol sequence and ICMIC mapping, golden sine Lévy flight guidance mechanism, nonlinear convergence factor, and adaptive inertia weighting strategy, which enhances the algorithm’s searching capability and convergence accuracy. Finally, the improved bald eagle search algorithm is used to solve the optimization model of well group splitting coefficients in the actual block of an oilfield. The results show that the calculated splitting injection volume has a high degree of agreement with the actual fluid production volume and has good splitting accuracy.

    参考文献
    [1] 张西子. 聚合物驱油技术提高油田采收率分析与研究. 内江科技, 2022, 43(9): 79–80.
    [2] 孙雨威. 聚合物驱油的影响因素. 化学工程与装备, 2023, (12): 42–44.
    [3] 张庆凯. 聚合物驱油效果影响因素与相关技术分析. 中国石油和化工标准与质量, 2023, 43(12): 18–20.
    [4] 梁爽. 聚合物驱油在老油田应用的发展方向. 化学工程与装备, 2024(5): 168–170, 60.
    [5] 周萍. 聚合物驱油机理及增效途径. 化学工程与装备, 2023, (11): 41–43.
    [6] Yu QN, Liu YK, Shen AQ. An improved splitting method of liquid production with in thick reservoir. Advances in Petroleum Exploration and Development, 2015, 10(1): 18–21.
    [7] Hu QH, Wang X, Tan YM, et al. The production split method in multilayer reservoir based on grey relational analysis. IOP Conference Series: Earth and Environmental Science, 2018, 113: 012018.
    [8] 付强, 薛国庆, 任超群, 等. 多层合采井产量劈分新方法在W油田的应用. 断块油气田, 2019, 26(4): 512–515.
    [9] 龙海宁, 喻高明, 傅宣豪. 结合灰色关联改进反距离加权插值法的劈分新方法. 科学技术与工程, 2019, 19(36): 140–146.
    [10] 马立民, 于忠良, 余成林, 等. 基于节点分析劈分法的多层油藏井间动态连通性分析. 科学技术与工程, 2022, 22(11): 4335–4343.
    [11] 尹洪军, 张俊廷, 张欢欢, 等. 应用灰色关联分析方法确定分层注水量公式. 数学的实践与认识, 2012, 42(13): 94–99.
    [12] Alsattar HA, Zaidan AA, Zaidan BB. Novel meta-heuristic bald eagle search optimisation algorithm. Artificial Intelligence Review, 2020, 53(3): 2237–2264.
    [13] 周辉, 张玉, 肖烈禧, 等. 基于改进秃鹰算法的微电网群经济优化调度研究. 太阳能学报, 2024, 45(2): 328–335.
    [14] 宋寒冬, 陈正寿, 杜炳鑫, 等. 基于改进秃鹰算法的自旋转水射流喷头布局优化方法. https://link.cnki.net/urlid/11.5946.tp.20240122.1627.005. [2024-01-23] (2024-09-09).
    [15] 黄鹤, 温夏露, 杨澜, 等. 基于疯狂捕猎秃鹰算法的K均值互补迭代聚类优化. 浙江大学学报(工学版), 2023, 57(11): 2147–2159.
    [16] Wang QY, Zhang XQ, Zhao XH. Image encryption algorithm based on improved iterative chaotic map with infinite collapses and Gray code. Physica Scripta, 2024, 99(2): 025232.
    [17] Sirsant S, Hamouda MA, Shaaban MF, et al. A chaotic Sobol sequence-based multi-objective evolutionary algorithm for optimal design and expansion of water networks. Sustainable Cities and Society, 2022, 87: 104215.
    [18] 邓佳欣, 张达敏, 何庆, 等. 结合莱维飞行和布朗运动的金鹰算法. 系统仿真学报, 2023, 35(6): 1290–1307.
    [19] 徐慧玲, 刘升, 李安东. 基于双向局部开发和黄金正弦的异构导向的鲸鱼优化算法. 计算机工程与科学, 2024, 46(6): 1128–1140.
    [20] 牛赛克, 孙丽颖. 基于自适应调整惯性权重的改进粒子群优化算法. 辽宁工业大学学报(自然科学版), 2023, 43(6): 400–403, 409.
    [21] Mirjalili S, Mirjalili SM, Lewis A. Grey wolf optimizer. Advances in Engineering Sftware, 2014, 69: 46–61.
    [22] Kennedy J, Eberhart R. Particle swarm optimization. Proceedings of the 1995 International Conference on Neural Networks. Perth: IEEE, 1995. 1942–1948.
    [23] Arora S, Singh S. Butterfly optimization algorithm: A novel approach for global optimization. Soft Computing, 2019, 23(3): 715–734.
    [24] Mirjalili S, Lewis A. The whale optimization algorithm. Advances in Engineering Software, 2016, 95: 51–67.
    [25] Mirjalili S. SCA: A Sine Cosine Algorithm for solving optimization problems. Knowledge-based Systems, 2016, 96: 120–133.
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

张强,陈诚,李青,薛冰.基于改进秃鹰搜索算法的聚合物驱油井组劈分.计算机系统应用,2025,34(2):254-263

复制
分享
文章指标
  • 点击次数:70
  • 下载次数: 299
  • HTML阅读次数: 71
  • 引用次数: 0
历史
  • 收稿日期:2024-07-30
  • 最后修改日期:2024-09-03
  • 在线发布日期: 2024-12-19
文章二维码
您是第11197721位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京海淀区中关村南四街4号 中科院软件园区 7号楼305房间,邮政编码:100190
电话:010-62661041 传真: Email:csa (a) iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号