页岩油微观渗流机理研究进展

王鸣川; 王燃; 岳慧; 张薇; 王付勇; 陈志强

doi:10.11781/sysydz202401098

页岩油微观渗流机理研究进展

doi: 10.11781/sysydz202401098

王鸣川^{1, 2,},
王燃^{1, 2},
岳慧^{1, 3},
张薇^{1, 2},
王付勇^{1, 3},
陈志强^{1, 2}

1.
中国石化页岩油气勘探开发重点实验室, 北京 102206
2.
中国石化石油勘探开发研究院, 北京 102206
3.
中国石油大学(北京) 非常规油气科学技术研究院, 北京 102249

基金项目:

中国石化重点基础前瞻研究项目 P22205

详细信息

作者简介:
王鸣川(1985-), 男, 博士, 副研究员, 从事地质建模与油藏数值模拟研究。E-mail: wangmc.syky@sinopec.com

中图分类号: TE311
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出版历程
- 收稿日期: 2023-08-14
- 修回日期: 2023-12-12
- 刊出日期: 2024-01-28

Research progress of microscopic percolation mechanism of shale oil

WANG Mingchuan^{1, 2
,},
WANG Ran^{1, 2},
YUE Hui^{1, 3},
ZHANG Wei^{1, 2},
WANG Fuyong^{1, 3},
CHEN Zhiqiang^{1, 2}

1.
SINOPEC Key Laboratory of Shale Oil/Gas Exploration and Production Technology, Beijing 102206, China
2.
SINOPEC Petroleum Exploration and Production Research Institute, Beijing 102206, China
3.
Unconventional Petroleum Research Institute, China University of Petroleum (Beijing), Beijing 102249, China

摘要

摘要: 页岩油已成为全球非常规油气资源勘探开发的重点，但其开发面临诸多挑战。针对页岩油赋存孔隙空间复杂、渗流机理尚不明确和研究方法亟需探索的关键问题，从孔隙尺度和岩心尺度，系统阐述了页岩油微观渗流机理在实验方法和计算模拟方面的研究现状，探讨了目前存在的问题和未来研究的发展趋势。结果显示，目前多种实验方法结合能较好表征页岩孔隙结构，但对微尺度与岩心尺度流动的表征尚存在不足；孔隙尺度流动机理研究以格子玻尔兹曼方法为代表的直接法和以孔隙网络模拟为代表的间接法为主，但对微尺度效应的考虑有待完善；岩心尺度流动机理研究主要为基于毛管束模型和分形理论，建立考虑边界层效应的渗流模型。指出充分考虑页岩油微纳米孔隙中流动边界吸附/滑移、密度/黏度非均质性、应力敏感、启动压力梯度等因素，耦合不同尺度渗流机理，构建能够准确表征页岩油多相多尺度流动特征的数学模型是未来的主要研究方向。
- 孔隙网络模型 /
- 格子玻尔兹曼方法 /
- 数字岩心 /
- 非线性渗流 /
- 渗流机理 /
- 页岩油
Abstract: Shale oil has become the focus of the exploration and development of unconventional oil and gas resources in the world, but its development faces many challenges. Aiming at the complex pore space, the unclear percolation mechanism, and the urgent need to explore research methods of shale oil, this paper systematically expounded the research status of microscopic percolation mechanism of shale oil in experimental methods and computational simulation, and discussed the existing problems and the development trend of future research from the perspective of pore-scale and core-scale. The results show that the combination of various experimental methods can well characterize the pore structure of shale, but the characterization of micro-scale and core-scale flow is still insufficient. The direct method represented by Lattice Boltzmann Method and the indirect method represented by pore network simulation are the main methods to study pore-scale flow mechanism, but the consideration of micro-scale effect needs to be improved. The study of core-scale flow mechanism is mainly to establish a percolation model considering boundary layer effect based on capillary bundle model and fractal theory. It is pointed out that the main future research direction is to fully consider the factors such as boundary adsorption/slip, density/viscosity heterogeneity, stress sensitivity, start-up pressure gradient of shale oil in micro-nano pores, realize multi-scale percolation mechanism coupling, and establish a mathematical model that can accurately characterize the multi-phase and multi-scale flow of shale oil.
- pore network model (PNM) /
- Lattice Boltzmann Method (LBM) /
- digital core /
- nonlinear percolation /
- percolation mechanism /
- shale oil
注释:

利益冲突声明/Conflict of Interests

所有作者声明不存在利益冲突。

All authors disclose no relevant conflict of interests.

作者贡献/Authors’Contributions

王鸣川参与论文设计、写作和修改；王燃，岳慧，张薇，王付勇，陈志强参与论文写作和修改。所有作者均阅读并同意最终稿件的提交。

The study was designed and the manuscript was drafted and revised by WANG Mingchuan. WANG Ran, YUE Hui, ZHANG Wei, WANG Fuyong and CHEN Zhiqiang also participated in drafting and revising the manuscript. All the authors have read the last version of paper and consented for submission.

HTML全文

图 1 页岩储集空间表征的实验方法及适用范围

Figure 1. Experimental method and application range of shale reservoir space characterization

下载: 全尺寸图片幻灯片

图 2 基于孔隙网络模型的微观渗流模拟技术路线

Figure 2. Technical route of microscopic percolation simulation based on pore network model

下载: 全尺寸图片幻灯片

表 1 非线性渗流数学模型及特点

Table 1. Nonlinear percolation mathematical model and its characteristics

模型分类	参考文献	速度方程	模型特点
分段模型	PRADA等^[89]	$\left\{\begin{array}{cc} v=0 & \nabla_p \leq \nabla p_{\mathrm{TPG}} \\ v=\frac{k}{\mu}\left(\nabla_p-\nabla_{p_{\mathrm{TPG}}}\right) & \nabla_p>\nabla p_{\mathrm{TPG}} \end{array}\right.$	模型简单，渗流曲线不连续，不能体现非线性渗流
	黄延章^[84]	$\text { ① }\left\{\begin{array}{cl} v=0 & \nabla p \leq \nabla p_{\mathrm{a}} \\ v=\frac{k}{\mu}\left(\nabla_p-\nabla_{p_{\mathrm{a}}}\right)^n & \nabla_{p_{\mathrm{a}}}<\nabla p \leq \nabla p_{\mathrm{b}} \\ v=\frac{k}{\mu} \nabla p & \nabla p>\nabla p_{\mathrm{b}} \end{array}\right.$	模型①考虑了启动压力梯度及非线性渗流段；模型②在数学处理中应用较为便捷，未体现启动压力梯度；模型③考虑了启动压力梯度，但对于低压力梯度时大孔道中的流动预测偏低
		$② \left\{ {\begin{array}{*{20}{l}} {v = {{\left( {\frac{k}{\mu }} \right)}_1}\nabla p}&{\nabla p \leqslant \nabla {p_{\text{b}}}} \\ {v = {{\left( {\frac{k}{\mu }} \right)}_2}\nabla p}&{\nabla p > \nabla {p_{\text{b}}}} \end{array}} \right.$
		$\text { ③ }\left\{\begin{array}{cl} v=0 & \nabla p \leq \nabla p_{\mathrm{c}} \\ v=\frac{k}{\mu}\left(\nabla p-\nabla p_{\mathrm{c}}\right) & \nabla p>\nabla p_{\mathrm{c}} \end{array}\right.$
	阮敏等^[90]	$\left\{\begin{array}{cc} v=a_1(\nabla p)^n & \nabla p \leq \nabla p_{\mathrm{b}} \\ v=a_2\left(\nabla p-\nabla p_{\mathrm{c}}\right) & \nabla p>\nabla p_{\mathrm{b}} \end{array}\right.$	考虑了非线性渗流段，a₁, a₂, n由实验测量确定
	LI等^[91]	$\left\{\begin{array}{cl} v=0 & \nabla p \leq \nabla p_{\mathrm{a}} \\ v=a \frac{k}{\mu}\left(\nabla p_{\mathrm{b}}-\nabla p\right)^n & \nabla p_{\mathrm{a}}<\nabla p \leq \nabla p_{\mathrm{b}} \\ v=\frac{k}{\mu}\left(\nabla p-\nabla p_{\mathrm{b}}\right) & \nabla p>\nabla p_{\mathrm{b}} \end{array}\right.$	渗流曲线连续，a为非线性常数
多参数模型	邓英尔等^[86]	$v\left(a_1+\frac{a_2}{1+b v}\right)=-\nabla p$	模型简单，a₁，a₂，b均由实验确定
	杨清立等^[92]	$v=\frac{k}{\mu}\left(1-\frac{1}{a+b\|\nabla p\|}\right) \nabla_p$	模型简单，a为非线性渗流段的影响因子，b相当于拟启动压力梯度的倒数；a和b均由实验确定
	黄延章等^[85]	$v=\frac{k}{\mu}\left(1-\frac{\nabla p_{\mathrm{c}}}{\nabla p+\nabla p_{\mathrm{c}}-\nabla p_{\mathrm{a}}}\right) \nabla_p$	连续函数，模型参数简单
	姜瑞忠等^[81]	$v=\frac{k}{\mu}\left(1-\frac{c_1}{\nabla_p-c_2}\right) \nabla_p$	c₁和c₂是反映启动压力梯度和非线性渗流的特征参数，通过实验拟合得到
	时宇等^[93]	$v=\frac{a \pi c_{\mathrm{k}}(\nabla p)}{8 \mu}\left[\nabla p-\frac{c_{\mathrm{p}}\left(\nabla_p\right)}{c_{\mathrm{k}}(\nabla p)} \nabla p_{\mathrm{a}}\right]$	非线性渗流与拟线性渗流段的划分通过实验确定，a为喉道拟合参数
	杨仁锋等^[79]	$v=\frac{k}{\mu}\left(1-\frac{\xi_1}{\nabla p}-\frac{\xi_1 \xi_2}{\nabla p\left(\nabla p-\xi_2\right)}\right) \nabla_p$	边界层为非牛顿流体；流体存在屈服应力值；ξ₁₊ξ₂为真实启动压力梯度
	XIONG等^[94]	$v=\frac{k\left(1-\delta_{\mathrm{D}} \mathrm{e}^{-c_{\varphi} \nabla_p}\right)^4}{\mu} \nabla_p$	边界层不可动且随着压力梯度的升高而降低
	WANG等^[95]	$v=-\frac{k}{\mu}\left(\frac{1}{1+a \mathrm{e}^{-b\left\|\nabla_p\right\|}}\right) \nabla_p$	没有启动压力梯度，只有非线性渗流段。a和b由实验数据拟合得到
分形模型	CAI^[96]	$v=\frac{k_{\mathrm{f}}}{\mu_{\mathrm{d}}}\left(\nabla_p-\frac{16 \tau_0}{3} \frac{3+D_{\mathrm{T}}-D_{\mathrm{f}}}{3-D_{\mathrm{f}}} \frac{D_{\mathrm{max}}^{-D_{\mathrm{f}}}}{L_0^{1-D_{\mathrm{r}}}}\right)$	渗流曲线不连续，流体为宾汉流体，多孔介质采用分形理论描述，忽略了非线性渗流段
	HUANG等^[97]	$v = \frac{{\nabla p}}{\mu }\left[ {\frac{{\pi {D_{\text{f}}}r_{\max }^{3 + {D_{\text{T}}}}}}{{A{2^{4 - {D_{\text{T}}}}}L_0^{{D_{\text{T}}} - 1}\left( {3 - {D_{\text{f}}} + {D_{\text{T}}}} \right)}}} \right.\left. { - \frac{{\pi {D_{\text{f}}}r_{{\text{max }}}^{{D_{\text{f}}}}{a_1}{a_3}^{{a_4}}\mu T}}{{A{2^{2 - {D_{\text{T}}}}}L_0^{{D_{\text{T}}} - 1}}}\nabla {p^{{a_4}}}} \right]$	基于毛管束模型，管径分布符合分形幂关系，边界层描述采用考虑影响因素的拟合模型，a₁、a₃、a₄通过拟合非线性流实验、微管实验等实验测得
	WANG等^[98]	$v = \frac{\pi }{{32\left( {{D_{\text{T}}} + 3} \right)}}\frac{{\nabla p}}{\mu }\frac{{L_0^{1 - {D_{\text{T}}}}}}{A}{D_{\text{f}}}D_{_{\max }}^{^{{D_{\text{f}}}}}\int_{{D_{\min }}}^{{D_{\max }}} {{{\left( {1 - \frac{{2h}}{D}} \right)}^{\left( {{D_{\text{T}}} + 3} \right)}}} {D^{{D_{\text{T}}} - {D_{\text{f}}} + 2}}{\text{d}}D$	考虑边界层分布及边界层厚度随压力梯度的变化关系
注：v为渗流速度；μ为流体黏度；k为渗透率；$\nabla p$为压力梯度；$\nabla p_{\mathrm{TPG}}$为启动压力梯度；$\nabla p_{\mathrm{a}}$、$\nabla p_{\mathrm{b}}$、$\nabla p_{\mathrm{c}}$分别为最小、最大和拟启动压力梯度；c_p、c_k为喉道半径与压力梯度的分段函数；δ_D为无因次边界层厚度；c_φ为非达西参数；k_f为孔隙介质分形渗透率；τ₀为流体屈服强度；μ_d为流体塑性黏度；D_f为喉道分形维数；D_T为毛细管弯曲度分形维数；L₀为岩心样品直线长度；r_max为最大毛细管半径；A为毛管束模型横截面积；T为与孔隙和喉道特征相关的常数；D为孔喉直径；D_min，D_max为最小、最大孔喉直径；h为非流体流动边界层厚度。

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参考文献(103)

[1]	沈云琦, 金之钧, 苏建政, 等. 中国陆相页岩油储层水平渗透率与垂直渗透率特征: 以渤海湾盆地济阳坳陷和江汉盆地潜江凹陷为例[J]. 石油与天然气地质, 2022, 43(2): 378-389. SHEN Yunqi, JIN Zhijun, SUN Jianzheng, et al. Characteristics of horizontal and vertical permeability of continental shale oil reservoirs in China: a case from Jiyang Depression in Bohai Bay Basin and Qianjiang Sag in Jianghan Basin[J]. Oil & Gas Geo-logy, 2022, 43(2): 378-389.
[2]	黎茂稳, 金之钧, 董明哲, 等. 陆相页岩形成演化与页岩油富集机理研究进展[J]. 石油实验地质, 2020, 42(4): 489-505. doi: 10.11781/sysydz202004489 LI Maowen, JIN Zhijun, DONG Mingzhe, et al. Advances in the basic study of lacustrine shale evolution and shale oil accumulation[J]. Petroleum Geology & Experiment, 2020, 42(4): 489-505. doi: 10.11781/sysydz202004489
[3]	杜金虎, 胡素云, 庞正炼, 等. 中国陆相页岩油类型、潜力及前景[J]. 中国石油勘探, 2019, 24(5): 560-568. doi: 10.3969/j.issn.1672-7703.2019.05.003 DU Jinhu, HU Suyun, PANG Zhenglian, et al. The types, potentials and prospects of continental shale oil in China[J]. China Petroleum Exploration, 2019, 24(5): 560-568. doi: 10.3969/j.issn.1672-7703.2019.05.003
[4]	张仁贵, 刘迪仁, 彭成, 等. 中国陆相页岩油勘探开发现状及展望[J]. 现代化工, 2022, 42(3): 6-10. ZHANG Rengui, LIU Diren, PENG Cheng, et al. Current status and prospects of China's continental shale oil exploration and development[J]. Modern Chemical Industry, 2022, 42(3): 6-10.
[5]	金之钧. 页岩革命及其意义[J]. 经济导刊, 2019(10): 49-52. JIN Zhijun. The shale revolution and what it means[J]. Economic Herald, 2019(10): 49-52.
[6]	金之钧, 王冠平, 刘光祥, 等. 中国陆相页岩油研究进展与关键科学问题[J]. 石油学报, 2021, 42(7): 821-835. JIN Zhijun, WANG Guanping, LIU Guangxiang, et al. Research progress and key scientific issues of continental shale oil in China[J]. Acta Petrolei Sinica, 2021, 42(7): 821-835.
[7]	金之钧, 白振瑞, 高波, 等. 中国迎来页岩油气革命了吗?[J]. 石油与天然气地质, 2019, 40(3): 451-458. JIN Zhijun, BAI Zhenrui, GAO Bo, et al. Has China ushered in the shale oil and gas revolution?[J]. Oil & Gas Geology, 2019, 40(3): 451-458.
[8]	杨永飞, 刘志辉, 姚军, 等. 基于叠加数字岩心和孔隙网络模型的页岩基质储层孔隙空间表征方法[J]. 中国科学(技术科学), 2018, 48(5): 488-498. YANG Yongfei, LIU Zhihui, YAO Jun, et al. Pore space characterization method of shale matrix formation based on superposed digital rock and pore-network model[J]. Scientia Sinica (Technologica), 2018, 48(5): 488-498.
[9]	邹才能, 杨智, 崔景伟, 等. 页岩油形成机制、地质特征及发展对策[J]. 石油勘探与开发, 2013, 40(1): 14-26. ZOU Caineng, YANG Zhi, CUI Jingwei, et al. Formation mechanism, geological characteristics and development strategy of nonmarine shale oil in China[J]. Petroleum Exploration and Deve-lopment, 2013, 40(1): 14-26.
[10]	STEVENS S H, MOODHE K D, KUUSKRAA V A. China shale gas and shale oil resource evaluation and technical challenges[C]//SPE Asia Pacific Oil and Gas Conference and Exhibition. Jakarta: SPE, 2013.
[11]	卢双舫, 薛海涛, 王民, 等. 页岩油评价中的若干关键问题及研究趋势[J]. 石油学报, 2016, 37(10): 1309-1322. doi: 10.7623/syxb201610012 LU Shuangfang, XUE Haitao, WANG Min, et al. Several key issues and research trends in evaluation of shale oil[J]. Acta Petrolei Sinica, 2016, 37(10): 1309-1322. doi: 10.7623/syxb201610012
[12]	蔡建超. 多孔介质自发渗吸关键问题与思考[J]. 计算物理, 2021, 38(5): 505-512. CAI Jianchao. Some key issues and thoughts on spontaneous imbibition in porous media[J]. Chinese Journal of Computational Physics, 2021, 38(5): 505-512.
[13]	ZOU Caineng, JIN Xu, ZHU Rukai, et al. Do shale pore throats have a threshold diameter for oil storage?[J]. Scientific Reports, 2015, 5(1): 13619. doi: 10.1038/srep13619
[14]	李吉君, 史颖琳, 黄振凯, 等. 松辽盆地北部陆相泥页岩孔隙特征及其对页岩油赋存的影响[J]. 中国石油大学学报(自然科学版), 2015, 39(4): 27-34. doi: 10.3969/j.issn.1673-5005.2015.04.004 LI Jijun, SHI Yinglin, HUANG Zhenkai, et al. Pore characteristics of continental shale and its impact on storage of shale oil in northern Songliao Basin[J]. Journal of China University of Petroleum (Edition of Natural Science), 2015, 39(4): 27-34. doi: 10.3969/j.issn.1673-5005.2015.04.004
[15]	雷浩, 郑有恒, 何建华, 等. 页岩油藏流体渗流特征物理模拟新方法[J]. 石油学报, 2021, 42(10): 1346-1356. doi: 10.7623/syxb202110008 LEI Hao, ZHENG Youheng, HE Jianhua, et al. A new method for physical simulation of flow characteristics of fluids in shale oil reservoirs[J]. Acta Petrolei Sinica, 2021, 42(10): 1346-1356. doi: 10.7623/syxb202110008
[16]	杜殿发, 张耀祖, 张莉娜, 等. 页岩气藏渗流机理研究进展与展望[J]. 非常规油气, 2021, 8(3): 1-9. DU Dianfa, ZHANG Yaozu, ZHANG Lina, et al. Research progress and prospect of seepage mechanism in shale gas reservoirs[J]. Unconventional Oil & Gas, 2021, 8(3): 1-9.
[17]	徐文明, 蒋启贵, 刘伟新, 等. 江汉盆地潜江凹陷盐间潜3⁴油组储层微观结构特征及与物性的关系[J]. 石油实验地质, 2020, 42(4): 565-574. doi: 10.11781/sysydz202004565 XU Wenming, JIANG Qigui, LIU Weixin, et al. Micro-pore structure in an inter-salt shale oil reservoir and the relationship with physical properties in the fourth section of the third member of Qianjiang Formation, Qianjiang Sag, Jianghan Basin[J]. Petroleum Geology & Experiment, 2020, 42(4): 565-574. doi: 10.11781/sysydz202004565
[18]	田善思. 页岩储层孔隙微观特征及页岩油赋存与可动性评价[D]. 青岛: 中国石油大学(华东), 2019. TIAN Shansi. Micro-pore characteristics of shale reservoirs and evaluation of shale oil occurrence and movability[D]. Qingdao: China University of Petroleum (East China), 2019.
[19]	FISHMAN N S, HACKLEY P C, LOWERS H A, et al. The nature of porosity in organic-rich mudstones of the Upper Jurassic Kimmeridge Clay Formation, North Sea, offshore United Kingdom[J]. International Journal of Coal Geology, 2012, 103: 32-50. doi: 10.1016/j.coal.2012.07.012
[20]	CURTIS M E, CARDOTT B J, SONDERGELD C H, et al. Deve-lopment of organic porosity in the Woodford shale with increasing thermal maturity[J]. International Journal of Coal Geology, 2012, 103: 26-31. doi: 10.1016/j.coal.2012.08.004
[21]	MILLIKEN K L, RUDNICKI M, AWWILLER D N, et al. Organic matter-hosted pore system, Marcellus Formation (Devonian), Pennsylvania[J]. AAPG Bulletin, 2013, 97(2): 177-200. doi: 10.1306/07231212048
[22]	CHEN Lei, JIANG Zhenxue, LIU Keyu, et al. Effect of lithofacies on gas storage capacity of marine and continental shales in the Sichuan Basin, China[J]. Journal of Natural Gas Science and Engineering, 2016, 36: 773-785. doi: 10.1016/j.jngse.2016.11.024
[23]	MASTALERZ M, SCHIMMELMANN A, DROBNIAK A, et al. Porosity of Devonian and Mississippian New Albany shale across a maturation gradient: insights from organic petrology, gas adsorption, and mercury intrusion[J]. AAPG Bulletin, 2013, 97(10): 1621-1643. doi: 10.1306/04011312194
[24]	ZHANG Pengfei, LU Shuangfang, LI Junqian. Characterization of pore size distributions of shale oil reservoirs: a case study from Dongying Sag, Bohai Bay Basin, China[J]. Marine and Petroleum Geology, 2019, 100: 297-308. doi: 10.1016/j.marpetgeo.2018.11.024
[25]	GUO Xusheng, LI Yuping, LIU Ruobing, et al. Characteristics and controlling factors of micropore structures of the Longmaxi shale in the Jiaoshiba area, Sichuan Basin[J]. Natural Gas Industry B, 2014, 1(2): 165-171. doi: 10.1016/j.ngib.2014.11.007
[26]	杨琦, 毛峥, 邵明仁. 页岩气储层纳米孔隙结构的研究方法及展望[J]. 能源化工, 2021, 42(2): 7-13. doi: 10.3969/j.issn.1006-7906.2021.02.003 YANG Qi, MAO Zheng, SHAO Mingren. Research methods and prospects of nanopore structure in shale gas reservoirs[J]. Energy Chemical Industry, 2021, 42(2): 7-13. doi: 10.3969/j.issn.1006-7906.2021.02.003
[27]	MASTALERZ M, HE Linlin, MELNICHENKO Y B, et al. Porosity of coal and shale: insights from gas adsorption and SANS/USANS techniques[J]. Energy & Fuels, 2012, 26(8): 5109-5120.
[28]	窦锦爱, 林业青, 邵丰, 等. 页岩气储层孔隙结构表征技术及实验方法研究进展[J]. 西安科技大学学报, 2020, 40(6): 1019-1030. DOU Jinai, LIN Yeqing, SHAO Feng, et al. Advances in characte-rization techniques and experimental methods of shale gas reservoir pore structure[J]. Journal of Xi'an University of Science and Technology, 2020, 40(6): 1019-1030.
[29]	YAO Lanlan, YANG Zhengming, LI Haibo, et al. Study on the flow mechanism of shale oil with different injection media[J]. Advances in Civil Engineering, 2021, 2021: 6668563.
[30]	张宝辉, 丁强, 张静, 等. 鄂尔多斯盆地页岩油微观存储空间类型及其成因机制: 以新安边油田安83区块长7为例[J]. 当代化工研究, 2021(24): 82-84. doi: 10.3969/j.issn.1672-8114.2021.24.028 ZHANG Baohui, DING Qiang, ZHANG Jing, et al. Microscopic storage space type of shale oil in ordos basin and its genesis mechanism-case in point: Long 7 in an 83 block of Xin'anbian oilfield[J]. Modern Chemical Research, 2021(24): 82-84. doi: 10.3969/j.issn.1672-8114.2021.24.028
[31]	刘毅, 陆正元, 戚明辉, 等. 渤海湾盆地沾化凹陷沙河街组页岩油微观储集特征[J]. 石油实验地质, 2017, 39(2): 180-185. doi: 10.11781/sysydz201702180 LIU Yi, LU Zhengyuan, QI Minghui, et al. Microscopic characteristics of shale oil reservoirs in Shahejie Formation in Zhanhua Sag, Bohai Bay Basin[J]. Petroleum Geology & Experiment, 2017, 39(2): 180-185. doi: 10.11781/sysydz201702180
[32]	ZHONG Junjie, ZANDAVI S H, LI Huawei, et al. Condensation in one-dimensional dead-end nanochannels[J]. ACS Nano, 2017, 11(1): 304-313. doi: 10.1021/acsnano.6b05666
[33]	ZHONG Junjie, ABEDINI A, XU Lining, et al. Nanomodel visualization of fluid injections in tight formations[J]. Nanoscale, 2018, 10(46): 21994-22002. doi: 10.1039/C8NR06937A
[34]	WU Qihua, OK J T, SUN Yongpeng, et al. Optic imaging of single and two-phase pressure-driven flows in nano-scale channels[J]. Lab on a Chip, 2013, 13(6): 1165-1171. doi: 10.1039/c2lc41259d
[35]	NGUYEN P, CAREY J W, VISWANATHAN H S, et al. Effectiveness of supercritical-CO₂ and N₂ huff-and-puff methods of enhanced oil recovery in shale fracture networks using microfluidic experiments[J]. Applied Energy, 2018, 230: 160-174. doi: 10.1016/j.apenergy.2018.08.098
[36]	桑茜, 张少杰, 朱超凡, 等. 陆相页岩油储层可动流体的核磁共振研究[J]. 中国科技论文, 2017, 12(9): 978-983. doi: 10.3969/j.issn.2095-2783.2017.09.003 SANG Qian, ZHANG Shaojie, ZHU Chaofan, et al. Study on movable fluid of continental shale oil reservoir with NMR technology[J]. China Science Paper, 2017, 12(9): 978-983. doi: 10.3969/j.issn.2095-2783.2017.09.003
[37]	桑茜. 页岩油气渗流实验方法及有效动用条件研究[D]. 青岛: 中国石油大学(华东), 2017. SANG Qian. Experimental methods and effective production conditions of shale oil and gas[D]. Qingdao: China University of Petroleum (East China), 2017.
[38]	李蕾, 郝永卯, 王程伟, 等. 页岩油藏单相流体低速渗流特征[J]. 特种油气藏, 2021, 28(6): 70-75. doi: 10.3969/j.issn.1006-6535.2021.06.009 LI Lei, HAO Yongmao, WANG Chengwei, et al. Low-velocity see-page characteristics of single-phase fluid in shale reservoir[J]. Special Oil & Gas Reservoirs, 2021, 28(6): 70-75. doi: 10.3969/j.issn.1006-6535.2021.06.009
[39]	李蕾, 王程伟, 姚传进, 等. 页岩气低速渗流模拟实验系统设计[J]. 实验技术与管理, 2020, 37(11): 79-82. LI Lei, WANG Chengwei, YAO Chuanjin, et al. Design of simulation experimental system for shale gas low-velocity seepage[J]. Experimental Technology and Management, 2020, 37(11): 79-82.
[40]	ZHAO Xinyi, SANG Qian, LI Yajun, et al. Mobilization of oil in organic matter and its contribution to oil production during primary production in shale[J]. Fuel, 2021, 287: 119449. doi: 10.1016/j.fuel.2020.119449
[41]	王子强, 李春涛, 张代燕, 等. 吉木萨尔凹陷页岩油储集层渗流机理[J]. 新疆石油地质, 2019, 40(6): 695-700. WANG Ziqiang, LI Chuntao, ZHANG Daiyan, et al. Flow mechanism of shale oil reservoir in Jimsar Sag[J]. Xinjiang Petroleum Geology, 2019, 40(6): 695-700.
[42]	马炳杰, 范菲, 孙志刚, 等. 济阳坳陷纹层状页岩油流动能力影响因素实验[J]. 大庆石油地质与开发, 2022, 41(5): 153-159. MA Bingjie, FAN Fei, SUN Zhigang, et al. Experimental study on influencing factors of shale oil flow capacity in laminar shale in Jiyang Depression[J]. Petroleum Geology & Oilfield Development in Daqing, 2022, 41(5): 153-159.
[43]	李子靳. 基于核磁共振技术的页岩油可动性实验研究[D]. 青岛: 中国石油大学(华东), 2020. LI Zijin. Experimental study on mobility of shale oil based on nuclear magnetic resonance technology[D]. Qingdao: China University of Petroleum (East China), 2020.
[44]	郭志强. 页岩油可动性评价: 以济阳坳陷沙河街组为例[D]. 青岛: 中国石油大学(华东), 2020. GUO Zhiqiang. Evaluation of shale oil mobility: a case study of Shahejie Formation in Jiyang Depression[D]. Qingdao: China University of Petroleum (East China), 2020.
[45]	赵国翔, 姚约东, 王链, 等. 页岩油藏微尺度流动特征及应力敏感性分析[J]. 断块油气田, 2021, 28(2): 247-252. ZHAO Guoxiang, YAO Yuedong, WANG Lian, et al. Microscale transport behaviors of shale oil and stress sensitivity analysis[J]. Fault-Block Oil & Gas Field, 2021, 28(2): 247-252.
[46]	WANG Wendong, WANG Han, SU Yuliang, et al. Simulation of liquid flow transport in nanoscale porous media using lattice Boltzmann method[J]. Journal of the Taiwan Institute of Chemical Engineers, 2021, 121: 128-138. doi: 10.1016/j.jtice.2021.03.044
[47]	ZHAO Jianlin, KANG Qinjun, YAO Jun, et al. Lattice Boltzmann simulation of liquid flow in nanoporous media[J]. International Journal of Heat and Mass Transfer, 2018, 125: 1131-1143. doi: 10.1016/j.ijheatmasstransfer.2018.04.123
[48]	苏玉亮, 王瀚, 詹世远, 等. 页岩油微尺度流动表征及模拟研究进展[J]. 深圳大学学报(理工版), 2021, 38(6): 579-589. SU Yuliang, WANG Han, ZHAN Shiyuan, et al. Research progress on characterization and simulation of shale oil flow in microscale[J]. Journal of Shenzhen University (Science and Engineering), 2021, 38(6): 579-589.
[49]	姚军, 赵建林, 张敏, 等. 基于格子Boltzmann方法的页岩气微观流动模拟[J]. 石油学报, 2015, 36(10): 1280-1289. YAO Jun, ZHAO Jianlin, ZHANG Min, et al. Microscale shale gas flow simulation based on Lattice Boltzmann method[J]. Acta Petrolei Sinica, 2015, 36(10): 1280-1289.
[50]	WU Keliu, CHEN Zhangxin, LI Jing, et al. Wettability effect on nanoconfined water flow[J]. Proceedings of the National Academy of Sciences of the United States of America, 2017, 114(13): 3358-3363.
[51]	TAN S P, PIRI M. Equation-of-state modeling of confined-fluid phase equilibria in nanopores[J]. Fluid Phase Equilibria, 2015, 393: 48-63. doi: 10.1016/j.fluid.2015.02.028
[52]	MA Yixin, JAMILI A. Using simplified local density/Peng-Robinson equation of state to study the effects of confinement in shale formations on phase behavior[C]//SPE Unconventional Resources Conference. The Woodlands: SPE, 2014.
[53]	WANG Han, SU Yuliang, ZHAO Zhenfeng, et al. Apparent permeability model for shale oil transport through elliptic nanopores considering wall-oil interaction[J]. Journal of Petroleum Science and Engineering, 2019, 176: 1041-1052. doi: 10.1016/j.petrol.2019.02.027
[54]	ZHANG Tao, LI Xiangfang, YIN Ying, et al. The transport behaviors of oil in nanopores and nanoporous media of shale[J]. Fuel, 2019, 242: 305-315. doi: 10.1016/j.fuel.2019.01.042
[55]	WANG Han, WANG Wendong, SU Yuliang. Lattice Boltzmann model for oil/water two-phase flow in nanoporous media consider-ing heterogeneous viscosity, liquid/solid, and liquid/liquid slip[J]. SPE Journal, 2022, 27(6): 3508-3524. doi: 10.2118/210564-PA
[56]	WANG Han, SU Yuliang, WANG Wendong, et al. A new fractal apparent permeability model for liquid flow in tortuous nano-pores from lattice Boltzmann simulations to the theoretical model[J]. Fractals, 2021, 29(7): 2150233. doi: 10.1142/S0218348X21502339
[57]	FATHI E, AKKUTLU I Y. Lattice Boltzmann method for simulation of shale gas transport in kerogen[J]. SPE Journal, 2013, 18(1): 27-37. doi: 10.2118/146821-PA
[58]	ZHANG Xiaoling, XIAO Lizhi, SHAN Xiaowen, et al. Lattice Boltzmann simulation of shale gas transport in organic nano-pores[J]. Scientific Reports, 2014, 4(1): 4843. doi: 10.1038/srep04843
[59]	PURCELL W R. Capillary pressures; their measurement using mercury and the calculation of permeability therefrom[J]. Treatise of Petroleum Geology Reprint Series, 1987, 3: 225-234.
[60]	FATT I. The network model of porous media[J]. Transactions of the AIME, 1956, 207(1): 144-181. doi: 10.2118/574-G
[61]	LOWRY M I, MILLER C T. Pore-scale modeling of nonwetting-phase residual in porous media[J]. Water Resources Research, 1995, 31(3): 455-473. doi: 10.1029/94WR02849
[62]	SONG Wenhui, YAO Jun, WANG Dongying, et al. Nanoscale confined gas and water multiphase transport in nanoporous shale with dual surface wettability[J]. Advances in Water Resources, 2019, 130: 300-313. doi: 10.1016/j.advwatres.2019.06.012
[63]	徐模. 数字岩心及孔隙网络模型的构建方法研究[D]. 成都: 西南石油大学, 2017. XU Mo. Method of digital core construction and pore network extraction[D]. Chengdu: Southwest Petroleum University, 2017.
[64]	杨永飞. 孔隙级油气水三相渗流模拟[D]. 青岛: 中国石油大学, 2010. YANG Yongfei. Pore-scale modelling of oil-gas-water three-phase flow in porous media[D]. Qingdao: China University of Petroleum (East China), 2010.
[65]	王晨晨. 碳酸盐岩介质双孔隙网络模型构建理论与方法[D]. 青岛: 中国石油大学(华东), 2013. WANG Chenchen. Construction theory and method of dual pore network model in carbonate media[D]. Qingdao: China University of Petroleum (East China), 2013.
[66]	张晴. 页岩多尺度孔隙网络模型建立及评价[D]. 北京: 中国石油大学(北京), 2016. ZHANG Qing. Shale multi-scale pore network construction and evaluation[D]. Beijing: China University of Petroleum (Beijing), 2016.
[67]	屈乐, 孙卫, 杜环虹, 等. 基于CT扫描的三维数字岩心孔隙结构表征方法及应用: 以莫北油田116井区三工河组为例[J]. 现代地质, 2014, 28(1): 190-196. doi: 10.3969/j.issn.1000-8527.2014.01.020 QU Le, SUN Wei, DU Huanhong, et al. Characterization technique of pore structure by 3D digital core based on CT scanning and its application: an example from Sangonghe Formation of 116 well field in Mobei oilfield[J]. Geoscience, 2014, 28(1): 190-196. doi: 10.3969/j.issn.1000-8527.2014.01.020
[68]	赵建鹏, 崔利凯, 陈惠, 等. 基于CT扫描数字岩心的岩石微观结构定量表征方法[J]. 现代地质, 2020, 34(6): 1205-1213. ZHAO Jianpeng, CUI Likai, CHEN Hui, et al. Quantitative characte-rization of rock microstructure of digital core based on CT scanning[J]. Geoscience, 2020, 34(6): 1205-1213.
[69]	DONG Hu, BLUNT M J. Pore-network extraction from micro-computerized-tomography images[J]. Physical Review E, 2009, 80(3): 036307. doi: 10.1103/PhysRevE.80.036307
[70]	黄盟, 冯翠菊, 王婷婷, 等. 中轴线法在低渗透性油藏孔隙结构认识中的应用[J]. 石化技术, 2019, 26(8): 112-113. HUANG Meng, FENG Cuiju, WANG Tingting, et al. Application of center axis method in understanding pore structure of low permeability reservoir[J]. Petrochemical Industry Technology, 2019, 26(8): 112-113.
[71]	闫国亮. 基于数字岩心储层渗透率模型研究[D]. 青岛: 中国石油大学(华东), 2013. YAN Guoliang. Research of permeability models of reservoirs based on digital cores[D]. Qingdao: China University of Petroleum (East China), 2013.
[72]	HUANG Xinwo, BANDILLA K W, CELIA M A. Multi-physics pore-network modeling of two-phase shale matrix flows[J]. Transport in Porous Media, 2016, 111(1): 123-141. doi: 10.1007/s11242-015-0584-8
[73]	盛军, 阳成, 徐立, 等. 数字岩心技术在致密储层微观渗流特征研究中的应用[J]. 西安石油大学学报(自然科学版), 2018, 33(5): 83-89. SHENG Jun, YANG Cheng, XU Li, et al. Application of digital core technology in the study of microscopic seepage characteristics of tight reservoirs[J]. Journal of Xi'an Shiyou University (Natural Science), 2018, 33(5): 83-89.
[74]	CUI Ronghao, FENG Qihong, CHEN Hongwei, et al. Multiscale random pore network modeling of oil-water two-phase slip flow in shale matrix[J]. Journal of Petroleum Science and Engineering, 2019, 175: 46-59. doi: 10.1016/j.petrol.2018.12.026
[75]	WANG Sen, FENG Qihong, JAVADPOUR F, et al. Multiscale modeling of shale apparent permeability: an integrated study of molecular dynamics and pore network model[C]//SPE Annual Technical Conference and Exhibition. San Antonio: SPE, 2017.
[76]	宋文辉, 刘磊, 孙海, 等. 基于数字岩心的页岩油储层孔隙结构表征与流动能力研究[J]. 油气藏评价与开发, 2021, 11(4): 497-505. SONG Wenhui, LIU Lei, SUN Hai, et al. Pore structure characterization and flow ability of shale oil reservoir based on digital cores[J]. Petroleum Reservoir Evaluation and Development, 2021, 11(4): 497-505.
[77]	ZHANG Wei, FENG Qihong, WANG Sen, et al. Pore network modeling of oil and water transport in nanoporous shale with mixed wettability[J]. Journal of Petroleum Science and Engineering, 2022, 209: 109884. doi: 10.1016/j.petrol.2021.109884
[78]	杨仁锋, 姜瑞忠, 刘世华. 低渗透油藏单相及两相非线性渗流新模型[J]. 辽宁工程技术大学学报(自然科学版), 2011, 30(S1): 60-65. YANG Renfeng, JIANG Ruizhong, LIU Shihua. New model of single-phase and two-phase nonlinear flow in low permeability reservoirs[J]. Journal of Liaoning Technical University (Natural Science Edition), 2011, 30(S1): 60-65.
[79]	杨仁锋, 姜瑞忠, 刘世华. 低渗透油藏考虑非线性渗流的必要性论证[J]. 断块油气田, 2011, 18(4): 493-497. YANG Renfeng, JIANG Ruizhong, LIU Shihua. Demonstration of essentiality of considering nonlinear flow in low permeability reservoir[J]. Fault-Block Oil & Gas Field, 2011, 18(4): 493-497.
[80]	李中锋, 何顺利. 低渗透储层非达西渗流机理探讨[J]. 特种油气藏, 2005, 12(2): 35-38. LI Zhongfeng, HE Shunli. Non-Darcy percolation mechanism in low permeability reservoir[J]. Special Oil & Gas Reservoirs, 2005, 12(2): 35-38.
[81]	姜瑞忠, 李林凯, 徐建春, 等. 低渗透油藏非线性渗流新模型及试井分析[J]. 石油学报, 2012, 33(2): 264-268. JIANG Ruizhong, LI Linkai, XU Jianchun, et al. A nonlinear mathematical model for low-permeability reservoirs and well-testing analysis[J]. Acta Petrolei Sinica, 2012, 33(2): 264-268.
[82]	杨正明. 低渗透油藏渗流机理及其应用[D]. 廊坊: 中国科学院研究生院(渗流流体力学研究所), 2005. YANG Zhengming. Porous flow mechanics for low permeability reservoirs and its application[D]. Langfang: University of Chinese Academy of Sciences (Institute of Porous Flow and Fluid Mechanics), 2005.
[83]	刘丽, 闵令元, 孙志刚, 等. 济阳坳陷页岩油储层孔隙结构与渗流特征[J]. 油气地质与采收率, 2021, 28(1): 106-114. LIU Li, MIN Lingyuan, SUN Zhigang, et al. Pore structure and percolation characteristics in shale oil reservoir of Jiyang Depression[J]. Petroleum Geology and Recovery Efficiency, 2021, 28(1): 106-114.
[84]	黄延章. 低渗透油层非线性渗流特征[J]. 特种油气藏, 1997, 4(1): 9-14. HUANG Yanzhang. Nonlinear percolation feature in low permeability reservoir[J]. Special Oil & Gas Reservoirs, 1997, 4(1): 9-14.
[85]	黄延章, 杨正明, 何英, 等. 低渗透多孔介质中的非线性渗流理论[J]. 力学与实践, 2013, 35(5): 1-8. HUANG Yanzhang, YANG Zhengming, HE Ying, et al. Nonlinear porous flow in low permeability porous media[J]. Mechanics in Engineering, 2013, 35(5): 1-8.
[86]	邓英尔, 刘慈群. 低渗油藏非线性渗流规律数学模型及其应用[J]. 石油学报, 2001, 22(4): 72-77. DENG Yinger, LIU Ciqun. Mathematical model of nonlinear flow law in low permeability porous media and its application[J]. Acta Petrolei Sinica, 2001, 22(4): 72-77.
[87]	徐绍良, 岳湘安, 侯吉瑞, 等. 边界层流体对低渗透油藏渗流特性的影响[J]. 西安石油大学学报(自然科学版), 2007, 22(2): 26-28. XU Shaoliang, YUE Xiangan, HOU Jirui, et al. Influence of boundary-layer fluid on the seepage characteristic of low-permeability reservoir[J]. Journal of Xi'an Shiyou University(Natural Science Edition), 2007, 22(2): 26-28.
[88]	刘德新, 岳湘安, 燕松, 等. 吸附水层对低渗透油藏渗流的影响机理[J]. 油气地质与采收率, 2005, 12(6): 40-42. LIU Dexin, YUE Xiangan, YAN Song, et al. Influential mechanism of adsorbed water layers on percolation in low permeability oil reservoir[J]. Petroleum Geology and Recovery Efficiency, 2005, 12(6): 40-42.
[89]	PRADA A, CIVAN F. Modification of Darcy's law for the threshold pressure gradient[J]. Journal of Petroleum Science and Engineering, 1999, 22(4): 237-240. doi: 10.1016/S0920-4105(98)00083-7
[90]	阮敏, 何秋轩, 任晓娟. 低渗透油层渗流特征及对油田开发的影响[J]. 特种油气藏, 1998, 5(3): 23-28. RUAN Min, HE Qiuxuan, REN Xiaojuan. Low permeability reservoir percolation characteristics and its influence on oil field development[J]. Special Oil & Gas Reservoirs, 1998, 5(3): 23-28.
[91]	LI Daolun, ZHA Wenshu, LIU Shufeng, et al. Pressure transient analysis of low permeability reservoir with pseudo threshold pressure gradient[J]. Journal of Petroleum Science and Engineering, 2016, 147: 308-316. doi: 10.1016/j.petrol.2016.05.036
[92]	杨清立, 杨正明, 王一飞, 等. 特低渗透油藏渗流理论研究[J]. 钻采工艺, 2007, 30(6): 52-54. YANG Qingli, YANG Zhengming, WANG Yifei, et al. Study on flow theory in ultra-low permeability oil reservoir[J]. Drilling & Production Technology, 2007, 30(6): 52-54.
[93]	时宇, 杨正明, 黄延章. 低渗透储层非线性渗流模型研究[J]. 石油学报, 2009, 30(5): 731-734. SHI Yu, YANG Zhengming, HUANG Yanzhang. Study on non-linear seepage flow model for low-permeability reservoir[J]. Acta Petrolei Sinica, 2009, 30(5): 731-734.
[94]	XIONG Yi, YU Jinbiao, SUN Hongxia, et al. A new non-Darcy flow model for low-velocity multiphase flow in tight reservoirs[J]. Transport in Porous Media, 2017, 117(3): 367-383. doi: 10.1007/s11242-017-0838-8
[95]	WANG Xiukun, SHENG J J. Effect of low-velocity non-Darcy flow on well production performance in shale and tight oil reservoirs[J]. Fuel, 2017, 190: 41-46. doi: 10.1016/j.fuel.2016.11.040
[96]	CAI Jianchao. A fractal approach to low velocity non-Darcy flow in a low permeability porous medium[J]. Chinese Physics B, 2014, 23(4): 044701. doi: 10.1088/1674-1056/23/4/044701
[97]	HUANG Shan, YAO Yuedong, ZHANG Shuang, et al. A fractal model for oil transport in tight porous media[J]. Transport in Porous Media, 2018, 121(3): 725-739. doi: 10.1007/s11242-017-0982-1
[98]	WANG Fuyong, LIU Zhichao, CAI Jianchao, et al. A fractal model for low-velocity non-Darcy flow in tight oil reservoirs considering boundary-layer effect[J]. Fractals, 2018, 26(5): 1850077. doi: 10.1142/S0218348X18500779
[99]	刘志超. 致密油藏渗流规律与渗吸提高采收率机理研究[D]. 北京: 中国石油大学(北京), 2019. LIU Zhichao. The study on seepage regularity and imbibition enhanced oil recovery of tight sandstone reservoir[D]. Beijing: China University of Petroleum (Beijing), 2019.
[100]	胡世旺, 张赛, 汪振毅. 考虑多层吸附诱导流的页岩微纳米孔道渗流分形模型[J]. 特种油气藏, 2023, 30(1): 139-146. HU Shiwang, ZHANG Sai, WANG Zhenyi. Fractal model of micro-nano pore seepage in shale considering the multi-layer adsorption induced Flow[J]. Special Oil & Gas Reservoirs, 2023, 30(1): 139-146.
[101]	孙强, 孙志刚, 张超. DLH油田低渗砂岩孔隙分形定量表征方法研究[J]. 西南石油大学学报(自然科学版), 2023, 45(1): 105-116. SUN Qiang, SUN Zhigang, ZHANG Chao. A study on fractal quantitative characterization method of low permeability sandstone pore in DLH oilfield[J]. Journal of Southwest Petroleum University (Science & Technology Edition), 2023, 45(1): 105-116.
[102]	王伟, 陈朝兵, 许爽, 等. 鄂尔多斯盆地延长组致密砂岩不同尺度孔喉分形特征及其控制因素[J]. 石油实验地质, 2022, 44(1): 33-40. doi: 10.11781/sysydz202201033 WANG Wei, CHEN Zhaobing, XU Shuang, et al. Fractal characte-ristics and its controlling factors of pore-throat with different scales in tight sandstones of the Yanchang Formation in the Ordos Basin[J]. Petroleum Geology & Experiment, 2022, 44(1): 33-40. doi: 10.11781/sysydz202201033
[103]	吴伟, 梁志凯, 郑马嘉, 等. 页岩储层孔隙结构与分形特征演化规律[J]. 油气地质与采收率, 2022, 29(4): 35-45. WU Wei, LIANG Zhikai, ZHENG Majia, et al. Pore structures in shale reservoirs and evolution laws of fractal characteristics[J]. Petroleum Geology and Recovery Efficiency, 2022, 29(4): 35-45.