IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i4p1368-d748917.html
   My bibliography  Save this article

Microscopic Conductivity Mechanism and Saturation Evaluation of Tight Sandstone Reservoirs: A Case Study from Bonan Oilfield, China

Author

Listed:
  • Jianmeng Sun

    (School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China)

  • Ping Feng

    (School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China)

  • Peng Chi

    (School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China)

  • Weichao Yan

    (Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Lab. of Submarine Geosciences and Prospecting Techniques, MOE and College of Marine Geosciences, Ocean University of China, Qingdao 266100, China
    Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China)

Abstract

Core samples of the tight sandstone reservoir in the Bonan Oilfield were analyzed by using multiple petrophysical experimental techniques, then a multi-scale three-dimensional digital rock model was constructed. The pore structure parameters of tight sandstone and homogeneous Berea sandstone were compared. The electrical simulation method based on the digital rock model was utilized to quantitatively reveal the influence of five micro-pore structure parameters (pore size, throat size, pore-throat size, coordination number, and shape factor) on the rock’s electrical properties. In addition, the saturation of tight sandstone reservoirs was evaluated in combination with the three-component automatic mixed-connection conductivity model. The results show that the “non-Archie” phenomenon in sandstone is obvious, which is mainly caused by the small radius of the maximum connected pore throat and the complex structure of the pore throat. We noted that: with an increase in pore radius, throat radius, and coordination number, the formation factor decreases and tends to be stable; the pore-throat size increases and the formation factor decreases in the form of power function; the shape factor increases, and the formation factor increases; the larger the pore–throat ratio and shape factor, the greater the resistivity index; with an increase in coordination number, the resistivity index decreases; and the pore-throat size has no effect on the resistivity index. The calculation accuracy of oil saturation is improved by 6.54% by constructing the three-component automatic mixed-conductivity saturation model of tight sandstone.

Suggested Citation

  • Jianmeng Sun & Ping Feng & Peng Chi & Weichao Yan, 2022. "Microscopic Conductivity Mechanism and Saturation Evaluation of Tight Sandstone Reservoirs: A Case Study from Bonan Oilfield, China," Energies, MDPI, vol. 15(4), pages 1-27, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1368-:d:748917
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/4/1368/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/4/1368/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhaohui Xu & Peiqiang Zhao & Zhenlin Wang & Mehdi Ostadhassan & Zhonghua Pan, 2018. "Characterization and Consecutive Prediction of Pore Structures in Tight Oil Reservoirs," Energies, MDPI, vol. 11(10), pages 1-15, October.
    2. Wang, Ke-Wen & Sun, Jian-Meng & Guan, Ji-Teng & Zhu, Da-Wei, 2007. "A percolation study of electrical properties of reservoir rocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 19-26.
    3. Juncheng Qiao & Xianzheng Zhao & Jianhui Zeng & Guomeng Han & Shu Jiang & Sen Feng & Xiao Feng, 2019. "The Impacts of Nano-Micrometer Pore Structure on the Gas Migration and Accumulation in Tight Sandstone Gas Reservoirs," Energies, MDPI, vol. 12(21), pages 1-24, October.
    4. Golsanami, Naser & Jayasuriya, Madusanka N. & Yan, Weichao & Fernando, Shanilka G. & Liu, Xuefeng & Cui, Likai & Zhang, Xuepeng & Yasin, Qamar & Dong, Huaimin & Dong, Xu, 2022. "Characterizing clay textures and their impact on the reservoir using deep learning and Lattice-Boltzmann simulation applied to SEM images," Energy, Elsevier, vol. 240(C).
    5. Xiaojun Zha & Fuqiang Lai & Xuanbo Gao & Yang Gao & Nan Jiang & Long Luo & Yingyan Li & Jia Wang & Shouchang Peng & Xun Luo & Xianfeng Tan, 2021. "Characteristics and Genetic Mechanism of Pore Throat Structure of Shale Oil Reservoir in Saline Lake—A Case Study of Shale Oil of the Lucaogou Formation in Jimsar Sag, Junggar Basin," Energies, MDPI, vol. 14(24), pages 1-25, December.
    6. Mengqi Wang & Jun Xie & Fajun Guo & Yawei Zhou & Xudong Yang & Ziang Meng, 2020. "Determination of NMR T 2 Cutoff and CT Scanning for Pore Structure Evaluation in Mixed Siliciclastic–Carbonate Rocks before and after Acidification," Energies, MDPI, vol. 13(6), pages 1-29, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiangyang Hu & Renjie Cheng & Hengrong Zhang & Jitian Zhu & Peng Chi & Jianmeng Sun, 2024. "Three-Water Differential Parallel Conductivity Saturation Model of Low-Permeability Tight Oil and Gas Reservoirs," Energies, MDPI, vol. 17(7), pages 1-19, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiangyang Hu & Renjie Cheng & Hengrong Zhang & Jitian Zhu & Peng Chi & Jianmeng Sun, 2024. "Three-Water Differential Parallel Conductivity Saturation Model of Low-Permeability Tight Oil and Gas Reservoirs," Energies, MDPI, vol. 17(7), pages 1-19, April.
    2. Shiming Zhang & Chunlei Yu & Junwei Su & Dengke Liu, 2022. "Splicing Method of Micro-Nano-Scale Pore Radius Distribution in Tight Sandstone Reservoir," Energies, MDPI, vol. 15(5), pages 1-10, February.
    3. Lin, Jianjun & Chen, Huisu & Liu, Lin & Zhang, Rongling, 2020. "Impact of particle size ratio on the percolation thresholds of 2D bidisperse granular systems composed of overlapping superellipses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    4. Zhongcheng Li & Zhidong Bao & Zhaosheng Wei & Hongxue Wang & Wanchun Zhao & Wentao Dong & Zheng Shen & Fan Wu & Wanting Tian & Lei Li, 2022. "Characteristics and Affecting Factors of K 2 qn 1 Member Shale Oil Reservoir in Southern Songliao Basin, China," Energies, MDPI, vol. 15(6), pages 1-21, March.
    5. Huang, Xudong & Yang, Dong & Kang, Zhiqin, 2021. "Impact of pore distribution characteristics on percolation threshold based on site percolation theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    6. Shriram Ashok Kumar & Maliha Tasnim & Zohvin Singh Basnyat & Faezeh Karimi & Kaveh Khalilpour, 2022. "Resilience Analysis of Australian Electricity and Gas Transmission Networks," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    7. Pengfei Zhao & Xiangyu Fan & Qiangui Zhang & Xiang Wang & Mingming Zhang & Jiawei Ran & Da Lv & Jinhua Liu & Juntian Shuai & Hao Wu, 2019. "The Effect of Hydration on Pores of Shale Oil Reservoirs in the Third Submember of the Triassic Chang 7 Member in Southern Ordos Basin," Energies, MDPI, vol. 12(20), pages 1-20, October.
    8. Feng Sha & Lizhi Xiao & Zhiqiang Mao & Chen Jia, 2018. "Petrophysical Characterization and Fractal Analysis of Carbonate Reservoirs of the Eastern Margin of the Pre-Caspian Basin," Energies, MDPI, vol. 12(1), pages 1-17, December.
    9. Li, Fuli & Yan, Wei & Kong, Xianyong & Li, Juan & Zhang, Wei & Kang, Zeze & Yang, Tao & Tang, Qing & Wang, Kongyang & Tan, Chaodong, 2024. "Study on multi-factor casing damage prediction method based on machine learning," Energy, Elsevier, vol. 296(C).
    10. Naser Golsanami & Bin Gong & Sajjad Negahban, 2022. "Evaluating the Effect of New Gas Solubility and Bubble Point Pressure Models on PVT Parameters and Optimizing Injected Gas Rate in Gas-Lift Dual Gradient Drilling," Energies, MDPI, vol. 15(3), pages 1-25, February.
    11. Linghui Sun & Ninghong Jia & Chun Feng & Lu Wang & Siyuan Liu & Weifeng Lyu, 2023. "Exploration of Oil/Water/Gas Occurrence State in Shale Reservoir by Molecular Dynamics Simulation," Energies, MDPI, vol. 16(21), pages 1-14, October.
    12. Han, Dongho & Kwon, Sanguk & Lee, Miyoung & Kim, Jonghoon & Yoo, Kisoo, 2023. "Electrochemical impedance spectroscopy image transformation-based convolutional neural network for diagnosis of external environment classification affecting abnormal aging of Li-ion batteries," Applied Energy, Elsevier, vol. 345(C).
    13. Xiaolong Guo & Bin Yan & Juyi Zeng & Guangzhi Zhang & Lin Li & You Zhou & Rui Yang, 2022. "Seismic Anisotropic Fluid Identification in Fractured Carbonate Reservoirs," Energies, MDPI, vol. 15(19), pages 1-15, September.
    14. Weichao Yan & Fujing Sun & Jianmeng Sun & Naser Golsanami, 2021. "Distribution Model of Fluid Components and Quantitative Calculation of Movable Oil in Inter-Salt Shale Using 2D NMR," Energies, MDPI, vol. 14(9), pages 1-17, April.
    15. Yuan Zhang & Yuan Di & Yang Shi & Jinghong Hu, 2018. "Cyclic CH 4 Injection for Enhanced Oil Recovery in the Eagle Ford Shale Reservoirs," Energies, MDPI, vol. 11(11), pages 1-15, November.
    16. Kang, Yili & Ma, Chenglin & Xu, Chengyuan & You, Lijun & You, Zhenjiang, 2023. "Prediction of drilling fluid lost-circulation zone based on deep learning," Energy, Elsevier, vol. 276(C).
    17. Kunkun Jia & Jianhui Zeng & Xin Wang & Bo Li & Xiangcheng Gao & Kangting Wang, 2022. "Wettability of Tight Sandstone Reservoir and Its Impacts on the Oil Migration and Accumulation: A Case Study of Shahejie Formation in Dongying Depression, Bohai Bay Basin," Energies, MDPI, vol. 15(12), pages 1-19, June.
    18. Jianchao Cai & Zhien Zhang & Qinjun Kang & Harpreet Singh, 2019. "Recent Advances in Flow and Transport Properties of Unconventional Reservoirs," Energies, MDPI, vol. 12(10), pages 1-5, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1368-:d:748917. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.