• 中国出版政府奖提名奖

    中国百强科技报刊

    湖北出版政府奖

    中国高校百佳科技期刊

    中国最美期刊

    留言板

    尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

    姓名
    邮箱
    手机号码
    标题
    留言内容
    验证码

    基于核磁共振表征渝西地区五峰组-龙一1亚段页岩储层孔隙结构及非均质性

    王子萌 蒋裕强 付永红 雷治安 徐昌海 袁竟舟 文冉 王占磊 谷一凡 尹兴平

    王子萌, 蒋裕强, 付永红, 雷治安, 徐昌海, 袁竟舟, 文冉, 王占磊, 谷一凡, 尹兴平, 2022. 基于核磁共振表征渝西地区五峰组-龙一1亚段页岩储层孔隙结构及非均质性. 地球科学, 47(2): 490-504. doi: 10.3799/dqkx.2021.076
    引用本文: 王子萌, 蒋裕强, 付永红, 雷治安, 徐昌海, 袁竟舟, 文冉, 王占磊, 谷一凡, 尹兴平, 2022. 基于核磁共振表征渝西地区五峰组-龙一1亚段页岩储层孔隙结构及非均质性. 地球科学, 47(2): 490-504. doi: 10.3799/dqkx.2021.076
    Wang Zimeng, Jiang Yuqiang, Fu Yonghong, Lei Zhian, Xu Changhai, Yuan Jingzhou, Wen Ran, Wang Zhanlei, Gu Yifan, Yin Xingping, 2022. Characterization of Pore Structure and Heterogeneity of Shale Reservoir from Wufeng Formation-Sublayers Long-11 in Western Chongqing Based on Nuclear Magnetic Resonance. Earth Science, 47(2): 490-504. doi: 10.3799/dqkx.2021.076
    Citation: Wang Zimeng, Jiang Yuqiang, Fu Yonghong, Lei Zhian, Xu Changhai, Yuan Jingzhou, Wen Ran, Wang Zhanlei, Gu Yifan, Yin Xingping, 2022. Characterization of Pore Structure and Heterogeneity of Shale Reservoir from Wufeng Formation-Sublayers Long-11 in Western Chongqing Based on Nuclear Magnetic Resonance. Earth Science, 47(2): 490-504. doi: 10.3799/dqkx.2021.076

    基于核磁共振表征渝西地区五峰组-龙一1亚段页岩储层孔隙结构及非均质性

    doi: 10.3799/dqkx.2021.076
    基金项目: 

    中石油-西南石油大学创新联合体项目二课题一专题四“复杂地质条件下川南深层/昭通中浅层海相页岩气赋存机制及控制因素研究” 2020CX020104

    四川省应用基础研究项目“海相页岩气建产核心区智能评价系统研究(省重)” 2019YJ0346

    四川省苗子工程重点项目“基于压裂液返排规律评价页岩气储层压裂效果的方法研究” 2019JDRC0095

    高等学校学科创新引智计划(111计划)“深层海相页岩气高效开发学科创新引智基地” D18016

    详细信息
      作者简介:

      王子萌(1997-), 男, 硕士研究生, 主要从事油气储层地质与油气藏开发地质研究工作.ORCID: 0000-0002-8110-9950.E-mail: wzm0v0@foxmail.com

    • 中图分类号: P618

    Characterization of Pore Structure and Heterogeneity of Shale Reservoir from Wufeng Formation-Sublayers Long-11 in Western Chongqing Based on Nuclear Magnetic Resonance

    • 摘要: 选取渝西地区五峰组-龙一1亚段富有机质页岩开展场发射扫描电镜、核磁共振和X射线衍射等实验,在图像处理和多重分形理论的基础上,分析了页岩储层孔隙结构特征及非均质性.结果表明:(1)扫描电镜分析认为,研究区有机孔平均孔径偏小, < 50 nm的有机孔数量占比82%,>100 nm的有机孔面孔率占比52%;(2)依据核磁T2谱峰形态划分为Ⅰ~Ⅲ类,分别为单峰、双峰和三峰3种类型,Ⅲ类页岩储层孔径、孔隙度较大,具备更优越的储集条件和渗流能力;(3)基于多重分形理论表征储层非均质性,石英含量越高,黏土含量越低非均质性越弱,进而控制着孔隙度和渗透率的大小.多重分形参数与矿物组分、物性参数的联系有效表征了储层孔隙结构,并为其非均质性的评估提供了新的视角.

       

    • 图  1  研究区位置(a、b)、研究区构造背景(c)与Z206井柱状图(d)

      Fig.  1.  Location of the study area (a, b), the structural background of the study area (c) and the column diagram of the Z206 well (d)

      图  2  五峰-龙马溪组页岩储层有机质孔隙的形成和生长过程

      Huang et al.(2020)修改

      Fig.  2.  Formation and growth process of organic matter pores in shale reservoirs of Wufeng Longmaxi formation

      图  3  研究区页岩有机质孔隙数量、占比及面孔率分布图

      Fig.  3.  Pore diameter distribution of shale organic matter in the study area

      图  4  研究区页岩有机质孔隙数量、占比及面孔率分布

      Fig.  4.  Pore diameter distribution of shale organic matter in the study area

      图  5  核磁共振T2分布及孔隙结构参数计算示意图

      Fig.  5.  NMR T2 distribution and schematic diagram of pore structure parameter calculation

      图  6  渗透率与核磁共振孔隙结构参数相关性

      Fig.  6.  Correlation graph between permeability and NMR pore structure parameters

      图  7  多重分形参数示意图

      Fig.  7.  Schematic diagram of multifractal parameters

      图  8  不同类型的T2分布及其对应的多重分形谱函数和广义分形维数谱

      a~c为Ⅰ型,d~e为Ⅱ型,g~i为Ⅲ型

      Fig.  8.  Different types of T2 distributions and their corresponding multifractal spectra and generalized fractal dimensions

      图  9  多重分形参数与孔隙度、渗透率相关性图

      Fig.  9.  Correlation diagram of multifractal parameters with porosity and permeability

      图  10  多重分形参数与矿物组分相关性图

      Fig.  10.  Correlation diagram of multifractal parameters and mineral composition

      表  1  样品矿物组成及有机质含量

      Table  1.   Mineral composition and organic matter content of samples

      井号 样品 层位 深度 TOC 矿物组分(%)
      (m) (%) 黏土 石英 长石 方解石 白云石
      Z205 #7 龙马溪组 3 327.6 2.24 37.9 42.2 6.7 3.9 5.5
      Z205 #12 龙马溪组 3 331.6 2.87 14.6 55.2 3.2 14.5 9.2
      Z205 #11 龙马溪组 3 346.2 4.30 16.1 46.3 1.8 11.4 22.9
      Z205 #4 五峰组 3 352.3 1.01 20.4 50.7 5.8 10.3 9.4
      Z203 #17 龙马溪组 4 100.8 4.56 10.2 64.7 2.8 6.3 13.0
      Z203 #16 龙马溪组 4 104.1 4.85 13.4 68.1 2.9 7.1 4.3
      Z203 #18 龙马溪组 4 105.7 5.43 23.4 32.8 4.3 27.5 10.2
      Z206 #3 龙马溪组 4 223.8 1.67 33.0 48.1 6.2 4.9 5.4
      Z206 #5 龙马溪组 4 259.0 2.51 22.7 48.5 8.2 8.6 9.1
      Z206 #6 五峰组 4 270.1 2.02 15.4 55.6 5.6 13.3 7.6
      Z206 #2 五峰组 4 273.2 1.67 21.7 65.2 3.7 1.7 3.2
      Z206 #1 五峰组 4 274.7 1.54 30.3 51.1 4.8 6.6 6.5
      Z208 #9 龙马溪组 4 351.4 2.91 41.7 22.2 6.3 13.0 10.4
      Z208 #10 龙马溪组 4 361.3 3.98 41.0 43.0 4.4 2.4 6.5
      Z208 #13 龙马溪组 4 366.0 4.64 29.3 42.5 11.3 3.2 6.7
      Z208 #8 龙马溪组 4 366.7 4.64 23.7 60.2 6.4 4.5 4.2
      Z208 #14 五峰组 4 370.6 2.86 36.8 37.1 6.1 12.4 6.2
      Z208 #15 五峰组 4 373.7 1.05 46.2 28.4 8.2 9.5 4.8
      下载: 导出CSV

      表  2  岩石物理性质及核磁共振孔隙结构参数

      Table  2.   Physical properties and pore structure parameters from NMR tests

      T2分布类型 样品 φHe(%) kHe(mD) φNMR(%) kSDR(mD) T15(ms) T35(ms) T50(ms) Tlm(ms)
      #1 3.23 0.003 3.13 0.001 5.20 0.50 0.29 0.53
      #2 4.22 0.003 2.80 0.000 1.28 0.42 0.26 0.40
      #3 3.55 0.002 3.17 0.000 0.95 0.38 0.24 0.32
      #4 3.14 0.007 3.28 0.007 13.16 0.76 0.37 0.85
      #5 3.03 0.008 2.98 0.003 13.69 0.65 0.33 0.76
      #6 2.78 0.004 2.42 0.001 21.07 0.54 0.27 0.75
      平均 3.33 0.004 2.96 0.002 9.23 0.54 0.29 0.60
      #7 5.16 0.023 4.30 0.015 3.98 1.01 0.47 0.73
      #8 4.35 0.011 3.94 0.018 5.05 1.19 0.55 0.90
      #9 5.90 0.027 4.97 0.047 4.95 1.54 0.72 0.89
      #10 4.21 0.018 4.59 0.102 29.12 1.92 0.64 1.41
      #11 4.22 0.010 4.05 0.011 5.41 0.97 0.44 0.72
      #12 4.54 0.012 3.64 0.016 6.20 1.37 0.63 0.97
      平均 4.73 0.017 4.25 0.035 9.12 1.33 0.58 0.94
      #13 7.40 0.015 7.19 0.570 7.48 3.30 1.84 1.64
      #14 6.47 0.015 6.68 0.608 9.38 2.96 1.56 1.96
      #15 6.87 0.014 9.08 1.831 15.91 3.36 1.68 2.26
      #16 4.49 0.017 4.98 0.244 12.47 3.12 1.51 1.86
      #17 5.49 0.014 5.73 0.234 8.24 3.03 1.45 1.50
      #18 4.56 0.013 5.52 0.185 8.56 3.21 1.49 1.41
      #18 4.56 0.013 5.52 0.185 8.56 3.21 1.49 1.41
      平均 5.69 0.014 6.39 0.551 10.09 3.17 1.57 1.72
      下载: 导出CSV

      表  3  多重分形特征参数

      Table  3.   Multifractal characteristic parameters

      样品 Dmin Dmax D0 D1 D2 D0-Dmax Dmin-D0 ΔD amax amin a0 Δa
      #1 2.02 0.70 1.00 0.85 0.75 0.30 1.03 1.32 2.20 0.68 1.00 1.52
      #2 1.98 0.68 1.00 0.82 0.73 0.31 0.98 1.29 2.17 0.66 1.00 1.51
      #3 2.09 0.67 1.00 0.80 0.71 0.33 1.10 1.42 2.25 0.65 1.00 1.60
      #4 2.02 0.74 1.00 0.89 0.79 0.26 1.02 1.28 2.22 0.71 1.00 1.51
      #5 2.00 0.73 1.00 0.88 0.78 0.27 1.00 1.28 2.19 0.70 1.00 1.49
      #6 1.95 0.71 1.00 0.88 0.77 0.29 0.96 1.25 2.15 0.68 1.00 1.46
      #7 2.14 0.77 1.00 0.87 0.81 0.23 1.15 1.38 2.32 0.74 1.00 1.58
      #8 2.11 0.78 1.00 0.88 0.82 0.22 1.11 1.33 2.30 0.76 1.00 1.53
      #9 2.18 0.79 1.00 0.87 0.82 0.21 1.19 1.39 2.36 0.78 1.00 1.58
      #10 2.16 0.79 1.00 0.90 0.85 0.20 1.16 1.36 2.34 0.76 1.00 1.57
      #11 2.13 0.76 1.00 0.88 0.81 0.24 1.13 1.37 2.31 0.74 1.00 1.57
      #12 2.10 0.79 1.00 0.89 0.82 0.21 1.10 1.31 2.28 0.77 1.00 1.51
      #13 2.27 0.75 1.00 0.86 0.81 0.25 1.28 1.52 2.45 0.72 1.00 1.73
      #14 2.23 0.78 1.00 0.89 0.83 0.21 1.24 1.45 2.42 0.75 1.00 1.67
      #15 2.29 0.80 1.00 0.89 0.85 0.20 1.29 1.49 2.50 0.77 1.00 1.72
      #16 2.12 0.81 1.00 0.91 0.85 0.18 1.12 1.30 2.32 0.79 1.00 1.53
      #17 2.18 0.80 1.00 0.89 0.84 0.20 1.18 1.38 2.39 0.77 1.00 1.61
      #18 2.22 0.81 1.00 0.87 0.84 0.19 1.22 1.41 2.38 0.78 1.00 1.60
      下载: 导出CSV
    • Ge, X. M., Fan, Y. R., Li, J. T., et al., 2015. Pore Structure Characterization and Classification Using Multifractal Theory: An Application in Santanghu Basin of Western China. Journal of Petroleum Science and Engineering, 127(1/2): 297-304. https://doi.org/10.1016/j.petrol.2015.01.004
      Hou, X. W., Zhu, Y. M., Wang, Y., et al., 2019. Experimental Study of the Interplay between Pore System and Permeability Using Pore Compressibility for High Rank Coal Reservoirs. Fuel, 254(1): 115712. https://doi.org/10.1016/j.fuel.2019.115712
      Hu, Y. B., Guo, Y.H., Zhang, J.J., et al., 2020. A Method to Determine Nuclear Magnetic Resonance Cutoff Value of Tight Sandstone Reservoir Based on Multifractal Analysis. Energy Science & Engineering, 8(4): 1135-1148. https://doi.org/10.1002/ese3.574
      Huang, C., Ju, Y. W., Zhu, H. J., et al., 2020. Investigation of Formation and Evolution of Organic Matter Pores in Marine Shale by Helium Ion Microscope: An Example from the Lower Silurian Longmaxi Shale, South China. Marine and Petroleum Geology, 120(6): 104550. https://doi.org/10.1016/j.marpetgeo.2020.104550
      Jiang, Y.Q., Liu, X.W., Fu, Y.H., et al., 2019. Evaluation of Effective Porosity in Marine Shale Reservoir, Western Chongqing. Acta Petrolei Sinica, 40(10): 1233-1243 (in Chinese with English abstract).
      Lai, J., Wang, G. W., Fan, Z. Y., et al., 2018. Fractal Analysis of Tight Shaly Sandstones Using Nuclear Magnetic Resonance Measurements. AAPG Bulletin, 102(2): 175-193. https://doi.org/10.1306/0425171609817007
      Li, A., Ding, W. L., Wang, R. Y., et al., 2017. Petrophysical Characterization of Shale Reservoir Based on Nuclear Magnetic Resonance (NMR) Experiment: A Case Study of Lower Cambrian Qiongzhusi Formation in Eastern Yunnan Province, South China. Journal of Natural Gas Science and Engineering, 37(4): 29-38. https://doi.org/10.1016/j.jngse.2016.11.034
      Li, T., 2008. Multifractal Theory and Some Applications(Dissertation). Beijing Jiaotong University, Beijing, 2-7 (in Chinese with English abstract).
      Liu, K. Q., Ostadhassan, M., Kong, L. Y., 2019. Fractal and Multifractal Characteristics of Pore Throats in the Bakken Shale. Transport in Porous Media, 126(3): 579-598. https://doi.org/10.1007/s11242-018-1130-2
      Liu, Z. S., Liu, D. M., Cai, Y. D., et al., 2020. Application of Nuclear Magnetic Resonance (NMR) in Coalbed Methane and Shale Reservoirs: A Review. International Journal of Coal Geology, 218(3): 103261. https://doi.org/10.1016/j.coal.2019.103261
      Loucks, R. G., Reed, R. M., Ruppel, S. C., et al., 2012. Spectrum of Pore Types and Networks in Mudrocks and a Descriptive Classification for Matrix-Related Mudrock Pores. AAPG Bulletin, 96(6): 1071-1098. https://doi.org/10.1306/08171111061
      Luo, S.Y., Chen, X.H., Li, H., et al., 2019. Shale Gas Accumulation Conditions and Target Optimization of Lower Cambrian Shuijingtuo Formation in Yichang Area, West Hubei. Earth Science, 44(11): 3598-3615 (in Chinese with English abstract).
      Ma, X.H., 2018. Enrichment Laws and Scale Effective Development of Shale Gas in the Southern Sichuan Basin. Natural Gas Industry, 38(10): 1-10 (in Chinese with English abstract).
      Mao, Z. Q., Xiao, L., Wang, Z. N., et al., 2012. Estimation of Permeability by Integrating Nuclear Magnetic Resonance (NMR) Logs with Mercury Injection Capillary Pressure (MICP) Data in Tight Gas Sands. Applied Magnetic Resonance, 44(4): 449-468. https://doi.org/10.1007/s00723-012-0384-z
      Ramandi, H. L., Mostaghimi, P., Armstrong, R. T., et al., 2016. Porosity and Permeability Characterization of Coal: A Micro-Computed Tomography Study. International Journal of Coal Geology, 154-155: 57-68. https://doi.org/10.1016/j.coal.2015.10.001
      Rezaee, R., Saeedi, A., Clennell, B., 2012. Tight Gas Sands Permeability Estimation from Mercury Injection Capillary Pressure and Nuclear Magnetic Resonance Data. Journal of Petroleum Science and Engineering, 88-89(4): 92-99. https://doi.org/10.1016/j.petrol.2011.12.014
      Sun, W., Zuo, Y. J., Wu, Z. H., et al., 2019. Fractal Analysis of Pores and the Pore Structure of the Lower Cambrian Niutitang Shale in Northern Guizhou Province: Investigations Using NMR, SEM and Image Analyses. Marine and Petroleum Geology, 99(1): 416-428. https://doi.org/10.1016/j.marpetgeo.2018.10.042
      Sun, Y., Zhai, C., Xu, J. Z., et al., 2020. A Method for Accurate Characterisation of the Pore Structure of a Coal Mass Based on Two-Dimensional Nuclear Magnetic Resonance T1-T2. Fuel, 262(10): 116574. https://doi.org/10.1016/j.fuel.2019.116574
      Wang, C., Zhang, B.Q., Shu, Z.G., et al., 2019. Shale Lamination and Its Influence on Shale Reservoir Quality of Wufeng Formation-Longmaxi Formation in Jiaoshiba Area. Earth Science, 44(3): 972-982 (in Chinese with English abstract).
      Wang, C.Y., Bao, Y., Ju, Y.W., et al., 2020. Micropore Structure Evolution of Organic Matters in Coal Measures due to Bioconversion Using FE-SEM, HIP and N2 Adsorption Experiments. Earth Science, 45(1): 251-262 (in Chinese with English abstract).
      Wang, Q. T., Wang, T. L., Liu, W. P., et al., 2019. Relationships among Composition, Porosity and Permeability of Longmaxi Shale Reservoir in the Weiyuan Block, Sichuan Basin, China. Marine and Petroleum Geology, 102: 33-47. https://doi.org/10.1016/j.marpetgeo.2018.12.026
      Wang, Z.G., 2019. Reservoir Formation Conditions and Key Efficient Exploration & Development Technologies for Marine Shale Gas Fields in Fuling Area, South China. Acta Petrolei Sinica, 40(3): 370-382 (in Chinese with English abstract).
      Wu, J. G., Yuan, Y., Niu, S. Y., et al., 2020. Multiscale Characterization of Pore Structure and Connectivity of Wufeng-Longmaxi Shale in Sichuan Basin, China. Marine and Petroleum Geology, 120(2/3): 104514. https://doi.org/10.1016/j.marpetgeo.2020.104514
      Wu, Y. Q., Tahmasebi, P., Lin, C. Y., et al., 2019. A Comprehensive Study on Geometric, Topological and Fractal Characterizations of Pore Systems in Low-Permeability Reservoirs Based on SEM, MICP, NMR, and X-Ray CT Experiments. Marine and Petroleum Geology, 103: 12-28. https://doi.org/10.1016/j.marpetgeo.2019.02.003
      Xiao, D.S., Zhao, R.W., Yang, X., et al., 2019. Characterization, Classification and Contribution of Marine Shale Gas Reservoirs. Oil & Gas Geology, 40(6): 1215-1225 (in Chinese with English abstract).
      Yao, Y. B., Liu, D. M., Che, Y., et al., 2010. Petrophysical Characterization of Coals by Low-Field Nuclear Magnetic Resonance (NMR). Fuel, 89(7): 1371-1380. https://doi.org/10.1016/j.fuel.2009.11.005
      Yu, C., Nie, H.K., Zeng, C.L., et al., 2014. Shale Reservoir Space Characteristics and the Effect on Gas Content in Lower Palaeozoic Erathem of the Eastern Sichuan Basin. Acta Geologica Sinica, 88(7): 1311-1320 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-DZXE201407008.htm
      Zhang, K. X., Lai, J., Bai, G. P., et al., 2020. Comparison of Fractal Models Using NMR and CT Analysis in Low Permeability Sandstones. Marine and Petroleum Geology, 112(6): 104069. https://doi.org/10.1016/j.marpetgeo.2019.104069
      Zhang, P., Huang, Y.Q., Zhang, J.C., et al., 2018. Fractal characteristics of the Longtan formation transitional shale in northwest Guizhou. Journal of China Coal Society, 43(6): 1580-1588 (in Chinese with English abstract).
      Zhao, P. Q., Wang, Z. L., Sun, Z. C., et al., 2017. Investigation on the Pore Structure and Multifractal Characteristics of Tight Oil Reservoirs Using NMR Measurements: Permian Lucaogou Formation in Jimusaer Sag, Junggar Basin. Marine and Petroleum Geology, 86(4): 1067-1081. https://doi.org/10.1016/j.marpetgeo.2017.07.011
      Zheng, S. J., Yao, Y. B., Liu, D. M., et al., 2019. Nuclear Magnetic Resonance T2 Cutoffs of Coals: A Novel Method by Multifractal Analysis Theory. Fuel, 241(6): 715-724. https://doi.org/10.1016/j.fuel.2018.12.044
      Zhou, S.W., Xue, H.Q., Guo, W., et al., 2016. A New Nuclear Magnetic Resonance Permeability Model of Shale of Longmaxi Formation in Southern Sichuan Basin. Journal of China University of Petroleum(Edition of Natural Science), 40(1): 56-61 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-SYDX201601008.htm
      Zhu, R.K., Wu, S.T., Su, L., et al., 2016. Problems and Future Works of Porous Texture Characterization of Tight Reservoirs in China. Acta Petrolei Sinica, 37(11): 1323-1336 (in Chinese with English abstract).
      蒋裕强, 刘雄伟, 付永红, 等, 2019. 渝西地区海相页岩储层孔隙有效性评价. 石油学报, 40(10): 1233-1243. doi: 10.7623/syxb201910008
      李彤, 2008. 多重分形原理及其若干应用(硕士学位论文). 北京: 北京交通大学, 2-7.
      罗胜元, 陈孝红, 李海, 等, 2019. 鄂西宜昌下寒武统水井沱组页岩气聚集条件与含气特征. 地球科学, 44(11): 3598-3615. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX201911002.htm
      马新华, 2018. 四川盆地南部页岩气富集规律与规模有效开发探索. 天然气工业, 38(10): 1-10. doi: 10.3787/j.issn.1000-0976.2018.10.001
      王超, 张柏桥, 舒志国, 等, 2019. 焦石坝地区五峰组-龙马溪组页岩纹层发育特征及其储集意义. 地球科学, 44(3): 972-982. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX201903024.htm
      王超勇, 鲍园, 琚宜文, 等, 2019. 利用FE-SEM、HIP、N_2吸附实验表征生物气化煤系有机岩储层微观孔隙结构演化. 地球科学, 45(1): 251-262. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX202001020.htm
      王志刚, 2019. 涪陵大型海相页岩气田成藏条件及高效勘探开发关键技术. 石油学报, 40(3): 370-382. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB201903011.htm
      肖佃师, 赵仁文, 杨潇, 等, 2019. 海相页岩气储层孔隙表征、分类及贡献. 石油与天然气地质, 40(6): 1215-1225. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201906006.htm
      余川, 聂海宽, 曾春林, 等, 2014. 四川盆地东部下古生界页岩储集空间特征及其对含气性的影响. 地质学报, 88(7): 1311-1320. https://www.cnki.com.cn/Article/CJFDTOTAL-DZXE201407008.htm
      张鹏, 黄宇琪, 张金川, 等, 2018. 黔西北地区龙潭组海陆过渡相泥页岩孔隙分形特征. 煤炭学报, 43(6): 1580-1588. https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB201806010.htm
      周尚文, 薛华庆, 郭伟, 等, 2016. 川南龙马溪组页岩核磁渗透率新模型研究. 中国石油大学学报(自然科学版), 40(1): 56-61. doi: 10.3969/j.issn.1673-5005.2016.01.008
      朱如凯, 吴松涛, 苏玲, 等, 2016. 中国致密储层孔隙结构表征需注意的问题及未来发展方向. 石油学报, 37(11): 1323-1336. doi: 10.7623/syxb201611001
    • 加载中
    图(10) / 表(3)
    计量
    • 文章访问数:  1217
    • HTML全文浏览量:  941
    • PDF下载量:  91
    • 被引次数: 0
    出版历程
    • 收稿日期:  2021-07-09
    • 刊出日期:  2022-02-25

    目录

      /

      返回文章
      返回