计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 584-586.

• 综合、交叉与应用 • 上一篇    下一篇

基于新型遗传算法的碳酸盐岩油气藏布井研究

姜瑞忠, 杨宜渤   

  1. 中国石油大学华东石油工程学院 山东 青岛266580
  • 出版日期:2019-02-26 发布日期:2019-02-26
  • 通讯作者: 杨宜渤(1993-),男,硕士生,主要研究方向为油气渗流理论,E-mail:sublunarchess@126.com(
  • 作者简介:姜瑞忠(1964-),男,博士,教授,主要研究方向为油气田开发研究与教学,E-mail:jrzhong@126.com

Research on Well Distribution in Carbonate Reservoirs Based on Novel Genetic Algorithm

JIANG Rui-zhong, YANG Yi-bo   

  1. College of Petroleum Engineering,China University of Petroleum,Qingdao,Shangdong 266580,China
  • Online:2019-02-26 Published:2019-02-26

摘要: 塔河油田隶属碳酸盐岩油田,由于缝洞发育的随机性,因此需要在开发初期进行合理的井位确定,以最大限度地提高开发效果。通过对传统的遗传算法进行多角度的改进,提出了一种新型遗传算法,并将其率先应用于油气田开发领域,相继引入淘汰算子、精英档案,改进了种群之间协同进化过程中的共生伙伴确定策略,大幅度提高了寻优性能。最后借助塔河油田某区块的实际开发地质模型,进行相关模拟与计算,得到了比传统算法高5%的采收率和累产油量,效果良好。

关键词: 精英档案, 井位优化, 淘汰算子, 新型协同进化

Abstract: Tahe Oilfield belongs to carbonate rock field.Due to the randomness of zave development,it is necessary to establish reasonable well position at the beginning of development to improve the development effect to the maximum extent.The traditional genetic algorithm was improved in multiple sections and a new genetic algorithm was put forward,which is used in the domain of oil and gas field development.The introduction of elimination operator,elite files and the new co-evolution between the various groups,greatly improve the optimization performance.Finally,by means of the actual development of the geological model of the oil field,the relevant simulation and calculation are done,and the final recovery ratio and accumulated produced oil is more than 5% higher than the result of traditional algorithm.The effect of this algorithm is good.

Key words: Elimination operator, Elite file, New co-evolution, Well position optimization

中图分类号: 

  • TP309
[1]BITTENCOURT A C,HORNE R N.Reservoir development and design optimization[C]∥SPE AnnualTechnical Conference and Exhibition.San Antonio,SPE,1997:SPE 38895.
[2]MORALES A N,NASRABADI H,ZHU D.A new modified genetic algorithm for well placement optimization under geological uncertainties[C]∥SPE EUROPEC/EAGE Annual Conference and Exhibition.Vienna:SPE,2011:SPE143617.
[3]姜瑞忠,刘明明,徐建春,等.遗传算法在苏里格气田井位优化中的应用[J].天然气地球科学,2014,25(10):1603-1609.
[4]高雪笛,周丽娟,张树东,等.基于改进遗传算法的测试数据自动生成的研究[J].计算机科学,2017,44(3):209-214.
[5]吉根林.遗传算法研究综述[J].计算机应用与软件,2004,21(2):69-73.
[6]熊伟清,魏平,赵杰煜.遗传算法的早熟现象研究 [J].计算机应用研究,2001,18(9):12-14.
[7]王出航,刘峰.采用遗传算法和WSN的智能灯控方法设计[J].控制工程,2017,24(2):341-345.
[8]金希东.遗传算法及其应用 [D].成都:西南交通大学,1996.
[9]胡仕成,徐晓飞,李向阳.项目优化调度的病毒协同进化遗传算法[J].软件学报,2004,15(1):49-57.
[10]苗金凤,王洪国,邵增珍,等.基于多级搜索区域的协同进化遗传算法 [J].计算机应用研究,2010,27(9):3345-3347.
[11]王鸿磊,徐平平,朱文祥,等.WSN低能耗数据收集遗传粒子群算法研究[J].计算机科学,2017,44(3):79-83.
[12]袁勇,梁永全.基于协同进化遗传算法的多议题谈判[J].计算机工程,2009,35(4):187-189.
[13]王厅长,邱建东,商庆健,等.病毒协同进化遗传算法在自动化立体仓库货位优化中应用的研究[J].计算机科学,2014,41(11A):35-38.
[14]宋洵成,邹德永.采用遗传算法的PDC钻头侧向力平衡优化设计[J].中国石油大学学报(自然科学版),2006,30(4):50-52.
[1] 宁晗阳, 马苗, 杨波, 刘士昌.
密码学智能化研究进展与分析
Research Progress and Analysis on Intelligent Cryptology
计算机科学, 2022, 49(9): 288-296. https://doi.org/10.11896/jsjkx.220300053
[2] 汤凌韬, 王迪, 张鲁飞, 刘盛云.
基于安全多方计算和差分隐私的联邦学习方案
Federated Learning Scheme Based on Secure Multi-party Computation and Differential Privacy
计算机科学, 2022, 49(9): 297-305. https://doi.org/10.11896/jsjkx.210800108
[3] 柳杰灵, 凌晓波, 张蕾, 王博, 王之梁, 李子木, 张辉, 杨家海, 吴程楠.
基于战术关联的网络安全风险评估框架
Network Security Risk Assessment Framework Based on Tactical Correlation
计算机科学, 2022, 49(9): 306-311. https://doi.org/10.11896/jsjkx.210600171
[4] 吕由, 吴文渊.
隐私保护线性回归方案与应用
Privacy-preserving Linear Regression Scheme and Its Application
计算机科学, 2022, 49(9): 318-325. https://doi.org/10.11896/jsjkx.220300190
[5] 窦家维.
保护隐私的汉明距离与编辑距离计算及应用
Privacy-preserving Hamming and Edit Distance Computation and Applications
计算机科学, 2022, 49(9): 355-360. https://doi.org/10.11896/jsjkx.220100241
[6] 高春刚, 王永杰, 熊鑫立.
MTDCD:一种对抗网络入侵的混合防御机制
MTDCD:A Hybrid Defense Mechanism Against Network Intrusion
计算机科学, 2022, 49(7): 324-331. https://doi.org/10.11896/jsjkx.210600193
[7] 梁珍珍, 徐明.
基于海洋水声信道的密钥协商方案
Key Agreement Scheme Based on Ocean Acoustic Channel
计算机科学, 2022, 49(6): 356-362. https://doi.org/10.11896/jsjkx.210400097
[8] 杜鸿毅, 杨华, 刘艳红, 杨鸿鹏.
基于网络媒体的非线性动力学信息传播模型
Nonlinear Dynamics Information Dissemination Model Based on Network Media
计算机科学, 2022, 49(6A): 280-284. https://doi.org/10.11896/jsjkx.210500043
[9] 傅丽玉, 陆歌皓, 吴义明, 罗娅玲.
区块链技术的研究及其发展综述
Overview of Research and Development of Blockchain Technology
计算机科学, 2022, 49(6A): 447-461. https://doi.org/10.11896/jsjkx.210600214
[10] 卫宏儒, 李思月, 郭涌浩.
基于智能合约的秘密重建协议
Secret Reconstruction Protocol Based on Smart Contract
计算机科学, 2022, 49(6A): 469-473. https://doi.org/10.11896/jsjkx.210700033
[11] 梁懿雯, 杜育松.
抵御计时攻击的基于Knuth-Yao的二元离散高斯采样算法
Timing Attack Resilient Sampling Algorithms for Binary Gaussian Based on Knuth-Yao
计算机科学, 2022, 49(6A): 485-489. https://doi.org/10.11896/jsjkx.210600017
[12] 闫萌, 林英, 聂志深, 曹一凡, 皮欢, 张兰.
一种提高联邦学习模型鲁棒性的训练方法
Training Method to Improve Robustness of Federated Learning
计算机科学, 2022, 49(6A): 496-501. https://doi.org/10.11896/jsjkx.210400298
[13] 陈彦冰, 钟超然, 周超然, 薛凌妍, 黄海平.
基于医疗联盟链的跨域认证方案设计
Design of Cross-domain Authentication Scheme Based on Medical Consortium Chain
计算机科学, 2022, 49(6A): 537-543. https://doi.org/10.11896/jsjkx.220200139
[14] 周航, 姜河, 赵琰, 解相朋.
适用于各单元共识交易的电力区块链系统优化调度研究
Study on Optimal Scheduling of Power Blockchain System for Consensus Transaction ofEach Unit
计算机科学, 2022, 49(6A): 771-776. https://doi.org/10.11896/jsjkx.210600241
[15] 刘林云, 陈开颜, 李雄伟, 张阳, 谢方方.
基于卷积神经网络的旁路密码分析综述
Overview of Side Channel Analysis Based on Convolutional Neural Network
计算机科学, 2022, 49(5): 296-302. https://doi.org/10.11896/jsjkx.210300286
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!