Study on Wettability and Static Imbibition Law of Tight Reservoir Based on Nuclear Magnetic Resonance Test

被引:1
|
作者
Chen, Shilin [1 ,2 ]
Liu, Xuewei [2 ]
Xiong, Shengchun [2 ]
Liu, Guozhong [2 ]
Wang, Xiangyang [3 ]
机构
[1] Univ Chinese Acad Sci, Coll Engn Sci, Beijing, Peoples R China
[2] PetroChina, Res Inst Petr Explorat & Dev, Beijing, Peoples R China
[3] CNPC Engn Technol R&D Co Ltd, Beijing, Peoples R China
关键词
tight reservoir; nuclear magnetic resonance; wettability; static imbibition; imbibition law;
D O I
10.1007/s10553-023-01537-1
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The research on tight oil is one of the hot spots nowadays. China has rich tight oil resources, with a wide distribution range and great development potential. For tight reservoirs, this paper proposes a method to test the rock wettability of tight reservoirs using the nuclear magnetic resonance (NMR) technology. Based on the idea of combining the NMR technology with indoor physical simulation, and on the basis of T2 relaxation time, the mixed wettability index is calculated through the limit of T2 relaxation time of 1 ms to evaluate the wettability of tight reservoirs. The design contrast experiment has studied the influence of wettability on the imbibition law, and concluded that the imbibition rate of hydrophilic rock samples is higher than that of lipophilic rock samples, but the ultimate recovery rate of lipophilic rock samples is higher than that of hydrophilic rock samples, which provides a basis for the development of tight reservoirs.
引用
收藏
页码:375 / 382
页数:8
相关论文
共 50 条
  • [1] Study on Wettability and Static Imbibition Law of Tight Reservoir Based on Nuclear Magnetic Resonance Test
    Chen Shilin
    Liu Xuewei
    Xiong Shengchun
    Liu Guozhong
    Wang Xiangyang
    Chemistry and Technology of Fuels and Oils, 2023, 59 : 375 - 382
  • [2] Experimental Investigation of Spontaneous Imbibition in a Tight Reservoir with Nuclear Magnetic Resonance Testing
    Lai, Fengpeng
    Li, Zhiping
    Wei, Qing
    Zhang, Tiantian
    Zhao, Qianhui
    ENERGY & FUELS, 2016, 30 (11) : 8932 - 8940
  • [3] Study of the Imbibition Behavior of Hydrophilic Tight Sandstone Reservoirs Based on Nuclear Magnetic Resonance
    Ren, Xiaoxia
    Li, Aifen
    Wang, Guijuan
    He, Bingqing
    Fu, Shuaishi
    ENERGY & FUELS, 2018, 32 (07) : 7762 - 7772
  • [4] Nuclear magnetic resonance study on wettability of shale oil reservoir
    Yao, Lanlan
    Yang, Zhengming
    Li, Haibo
    Zhou, Tiyao
    Zhang, Yapu
    Wang, Ning
    Du, Meng
    Huang, Qianhui
    Chen, Xinliang
    Meng, Huan
    FRONTIERS IN EARTH SCIENCE, 2024, 12
  • [5] Nuclear magnetic resonance study on imbibition and stress sensitivity of lamellar shale oil reservoir
    Wei, Jianguang
    Fu, Lanqing
    Zhao, Guozhong
    Zhao, Xiaoqing
    Liu, Xinrong
    Wang, Anlun
    Wang, Yan
    Cao, Sheng
    Jin, Yuhan
    Yang, Fengrui
    Liu, Tianyang
    Yang, Ying
    ENERGY, 2023, 282
  • [6] Experimental Investigation on the Imbibition Behavior of Nanofluids in the Tight Oil and Gas Reservoir through the Application of Nuclear Magnetic Resonance Method
    Li, Hui
    Wang, Can
    Li, Ben
    Wen, Xixia
    Li, Jianchuan
    Tian, Lu
    ENERGIES, 2023, 16 (01)
  • [7] Experimental Study of Forced Imbibition in Tight Reservoirs Based on Nuclear Magnetic Resonance under High-Pressure Conditions
    Li, Xiaoshan
    Yang, Liu
    Sun, Dezhi
    Ling, Bingjian
    Wang, Suling
    ENERGIES, 2024, 17 (12)
  • [8] Mixed Wettability Modeling and Nuclear Magnetic Resonance Characterization in Tight Sandstone
    Liang, Can
    Xiao, Lizhi
    Jia, Zijian
    Guo, Long
    Luo, Sihui
    Wang, Zhengyi
    ENERGY & FUELS, 2023, 37 (03) : 1962 - 1974
  • [9] Mixed Wettability Modeling and Nuclear Magnetic Resonance Characterization in Tight Sandstone
    Liang, Can
    Xiao, Lizhi
    Jia, Zijian
    Guo, Long
    Luo, Sihui
    Wang, Zhengyi
    ENERGY & FUELS, 2023,
  • [10] STUDY ON MOVABILITY OF SPONTANEOUS IMBIBITION OIL RECOVERY FROM TIGHT RESERVOIRS BASED ON NUCLEAR MAGNETIC RESONANCE PORE CLASSIFICATION METHOD
    Li T.
    Gao H.
    Wang M.
    Feng Y.
    Wang C.
    Cheng Z.
    Lixue Xuebao/Chinese Journal of Theoretical and Applied Mechanics, 2023, 55 (03): : 643 - 655