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Distribution Model of Fluid Components and Quantitative Calculation of Movable Oil in Inter-Salt Shale Using 2D NMR

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  • Weichao Yan

    (Shandong Provincial Key Laboratory of Deep Oil and Gas, Qingdao 266580, China
    School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China)

  • Fujing Sun

    (Shandong Provincial Key Laboratory of Deep Oil and Gas, Qingdao 266580, China
    School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China)

  • Jianmeng Sun

    (Shandong Provincial Key Laboratory of Deep Oil and Gas, Qingdao 266580, China
    School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China)

  • Naser Golsanami

    (State Key Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, China
    College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao 266590, China)

Abstract

Some inter-salt shale reservoirs have high oil saturations but the soluble salts in their complex lithology pose considerable challenges to their production. Low-field nuclear magnetic resonance (NMR) has been widely used in evaluating physical properties, fluid characteristics, and fluid saturation of conventional oil and gas reservoirs as well as common shale reservoirs. However, the fluid distribution analysis and fluid saturation calculations in inter-salt shale based on NMR results have not been investigated because of existing technical difficulties. Herein, to explore the fluid distribution patterns and movable oil saturation of the inter-salt shale, a specific experimental scheme was designed which is based on the joint adaptation of multi-state saturation, multi-temperature heating, and NMR measurements. This novel approach was applied to the inter-salt shale core samples from the Qianjiang Sag of the Jianghan Basin in China. The experiments were conducted using two sets of inter-salt shale samples, namely cylindrical and powder samples. Additionally, by comparing the one-dimensional (1D) and two-dimensional (2D) NMR results of these samples in oil-saturated and octamethylcyclotetrasiloxane-saturated states, the distributions of free movable oil and water were obtained. Meanwhile, the distributions of the free residual oil, adsorbed oil, and kerogen in the samples were obtained by comparing the 2D NMR T 1 - T 2 maps of the original samples with the sample heated to five different temperatures of 80, 200, 350, 450, and 600 °C. This research puts forward a 2D NMR identification graph for fluid components in the inter-salt shale reservoirs. Our experimental scheme effectively solves the problems of fluid composition distribution and movable oil saturation calculation in the study area, which is of notable importance for subsequent exploration and production practices.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:9:p:2447-:d:543166
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    References listed on IDEAS

    as
    1. Naser Golsanami & Xuepeng Zhang & Weichao Yan & Linjun Yu & Huaimin Dong & Xu Dong & Likai Cui & Madusanka Nirosh Jayasuriya & Shanilka Gimhan Fernando & Ehsan Barzgar, 2021. "NMR-Based Study of the Pore Types’ Contribution to the Elastic Response of the Reservoir Rock," Energies, MDPI, vol. 14(5), pages 1-26, March.
    2. Sou-Sen Leu & Tao-Ming Ying, 2020. "Replacement and Maintenance Decision Analysis for Hydraulic Machinery Facilities at Reservoirs under Imperfect Maintenance," Energies, MDPI, vol. 13(10), pages 1-10, May.
    3. 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.
    4. Zhang Qiang & Qamar Yasin & Naser Golsanami & Qizhen Du, 2020. "Prediction of Reservoir Quality from Log-Core and Seismic Inversion Analysis with an Artificial Neural Network: A Case Study from the Sawan Gas Field, Pakistan," Energies, MDPI, vol. 13(2), pages 1-19, January.
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    Cited by:

    1. Yangbo Lu & Feng Yang & Ting’an Bai & Bing Han & Yongchao Lu & Han Gao, 2022. "Shale Oil Occurrence Mechanisms: A Comprehensive Review of the Occurrence State, Occurrence Space, and Movability of Shale Oil," Energies, MDPI, vol. 15(24), pages 1-16, December.
    2. Lanlan Yao & Qihong Lei & Zhengming Yang & Youan He & Haibo Li & Guoxi Zhao & Zigang Zheng & Haitao Hou & Meng Du & Liangbing Cheng, 2023. "Online Nuclear Magnetic Resonance Analysis of the Effect of Stress Changes on the Porosity and Permeability of Shale Oil Reservoirs," Energies, MDPI, vol. 16(3), pages 1-17, January.
    3. 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.
    4. Qiyang Gou & Shang Xu, 2023. "The Controls of Laminae on Lacustrine Shale Oil Content in China: A Review from Generation, Retention, and Storage," Energies, MDPI, vol. 16(4), pages 1-17, February.

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