Pore structure effect on reservoir electrical properties and well logging evaluation

被引:0
|
作者
Huan-Lin Bian
Ju Guan
Zhi-Qiang Mao
Xiao-Dong Ju
Gui-Qing Han
机构
[1] China University of Petroleum,College of Geophysics and Information Engineering
[2] China University of Petroleum,Key Laboratory of Earth Prospect and Information Technology
[3] Geoscience Center of CNPC Great Wall Drilling Company,undefined
来源
Applied Geophysics | 2014年 / 11卷
关键词
pore structure; reservoir quality; resistivity; low-resistivity hydrocarbon-bearing zone; log evaluation;
D O I
暂无
中图分类号
学科分类号
摘要
The reservoir pore structure controls the reservoir quality and resistivity response of hydrocarbon-bearing zones and thus, critically affects logging interpretation. We use petrophysical data in three types of reservoir with different pore structure characteristics to show that the complexity of pore structure had a significant effect on the effective porosity and permeability regardless of geological factors responsible for the formation of pore structure. Moreover,, the distribution and content of conductive fluids in the reservoir varies dramatically owing to pore structure differences, which also induces resistivity variations in reservoir rocks. Hence, the origin of low-resistivity hydrocarbon-bearing zones, except for those with conductive matrix and mud filtrate invasion, is attributed to the complexity of the pore structures. Consequently, reservoir-specific evaluation models, parameters, and criteria should be chosen for resistivity log interpretation to make a reliable evaluation of reservoir quality and fluids.
引用
收藏
页码:374 / 383
页数:9
相关论文
共 50 条
  • [31] Well logging interpreting evaluation of heterogenous sandstone reservoir in block X in the middle of Junggar Basin
    Sun, Pei-An
    Zhu, Zhong-Kuan
    Jianghan Shiyou Xueyuan Xuebao/Journal of Jianghan Petroleum Institute, 2004, 26 (01): : 54 - 56
  • [32] Evaluation of fractured–vuggy reservoir by electrical imaging logging based on a de-noising method
    Fanghui Xu
    Zhuwen Wang
    Wenhua Wang
    Acta Geophysica, 2021, 69 : 761 - 772
  • [33] Characterization and Evaluation of Carbonate Reservoir Pore Structure Based on Machine Learning
    Hou, Jue
    Zhao, Lun
    Zeng, Xing
    Zhao, Wenqi
    Chen, Yefei
    Li, Jianxin
    Wang, Shuqin
    Wang, Jincai
    Song, Heng
    ENERGIES, 2022, 15 (19)
  • [34] Carbonate reservoir logging evaluation for Tazhong field
    Guan, Ju
    Li, Jun
    Guo, Xiuli
    Shiyou Kan Tan Yu Kai Fa/Petroleum Exploration and Development, 25 (04): : 84 - 86
  • [35] A Framework of Data Mining for Logging Reservoir Evaluation
    Ren, Yili
    Ren, Yiting
    2016 13TH INTERNATIONAL CONFERENCE ON SERVICE SYSTEMS AND SERVICE MANAGEMENT, 2016,
  • [36] Logging Evaluation of Permeability in Heterogeneous Conglomerate Reservoir
    Zhang, Xiaoling
    Li, Danmei
    Zhang, Ming
    Li, Chunlei
    PROCEEDINGS OF THE INTERNATIONAL FIELD EXPLORATION AND DEVELOPMENT CONFERENCE 2017, 2019, : 155 - 164
  • [37] Logging evaluation of lamina structure and reservoir quality in shale oil reservoir of Fengcheng Formation in Mahu Sag, China
    Wang, Song
    Wang, Guiwen
    Huang, Liliang
    Song, Lianteng
    Zhang, Yilin
    Li, Dong
    Huang, Yuyue
    MARINE AND PETROLEUM GEOLOGY, 2021, 133
  • [38] Data mining and well logging interpretation: application to a conglomerate reservoir
    Shi Ning
    Li Hong-Qi
    Luo Wei-Ping
    APPLIED GEOPHYSICS, 2015, 12 (02) : 263 - 272
  • [39] Study on recognizing oolid reservoir from well logging information
    Xia, H.Q.
    Yang, H.B.
    Zhu, S.J.
    Liu, H.Q.
    Zhang, X.H.
    Ren, X.G.
    Hu, Z.P.
    Xinan Shiyou Xueyuan Xuebao/Journal of Southwestern Petroleum Institute, 2001, 23 (02):
  • [40] Data mining and well logging interpretation: application to a conglomerate reservoir
    Ning Shi
    Hong-Qi Li
    Wei-Ping Luo
    Applied Geophysics, 2015, 12 : 263 - 272