细粒岩孔隙主控因素多解性问题与解析技术

doi:10.7623/syxb202606005

石油学报 ›› 2026, Vol. 47 ›› Issue (6): 1190-1203,1257.DOI: 10.7623/syxb202606005

• 地质勘探 • 上一篇

细粒岩孔隙主控因素多解性问题与解析技术

董琳^1,2, 王梓毅^1,2, 梅启亮^3,4, 朱如凯^5,6, 金之钧^2,5

1. 北京大学造山带与地壳演化教育部重点实验室北京 100871;
2. 北京大学地球与空间科学学院北京 100871;
3. 中国石油长庆油田公司陕西西安 710018;
4. 低渗透油气田勘探开发国家工程实验室陕西西安 710018;
5. 北京大学能源研究院北京 100871;
6. 中国石油勘探开发研究院北京 100083

收稿日期:2025-01-22 修回日期:2025-06-06 发布日期:2026-07-02
通讯作者: 王梓毅,男,1991年4月生,2021年获中国科学院大学矿物学、岩石学、矿床学博士学位,现为北京大学博士后、助理研究员,主要从事石油与天然气地质学研究工作。Email:ziyi-wang@pku.edu.cn
作者简介:董琳,女,1980年2月生,2007年获美国Virginia Tech大学博士学位,现为北京大学地球与空间科学学院长聘副教授、博士生导师,主要从事沉积地球化学和非常规油气研究工作。Email:lin.dong@pku.edu.cn
基金资助:
国家自然科学基金项目(No.42090021)资助。

The ambiguity-resolution problem and analytical techniques of the primary controlling factors for fine-grained rock pore characteristics

Dong Lin^1,2, Wang Ziyi^1,2, Mei Qiliang^3,4, Zhu Rukai^5,6, Jin Zhijun^2,5

1. MOE Key Laboratory of Orogenic Belts and Crustal Evolution, Peking University, Beijing 100871, China;
2. School of Earth and Space Sciences, Peking University, Beijing 100871, China;
3. PetroChina Changqing Oilfield Company, Shaanxi Xi'an 710018, China;
4. National Engineering Laboratory for Exploration and Development of Low-Permeability Oil & Gas Fields, Shaanxi Xi'an 710018, China;
5. Institute of Energy, Peking University, Beijing 100871, China;
6. PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China

Received:2025-01-22 Revised:2025-06-06 Published:2026-07-02

摘要/Abstract

摘要： 精准刻画细粒岩孔隙特征并揭示其主控因素,是制定非常规油气高效勘探开发方案的重要科学基础。传统研究常基于孔隙参数(如比孔容、分形维数等)和地质变量(如总有机碳、矿物组成等)的相关性分析来推断主控因素。然而,单纯的统计学关联难以揭示变量间复杂的成因联系,常引发地质解释的多解性,为准确揭示孔隙发育机理带来挑战。针对这一问题,系统梳理了细粒岩孔隙特征主控因素的多解性问题及其解析技术的研究进展,重点总结了4方面成果和认识:①地质变量间的多重共线性是引发孔隙参数与非主控因素间形成伪相关性的内在机制,传统相关性分析在主控因素研究中存在固有方法的局限;②在鄂尔多斯盆地三叠系延长组7段开展的技术应用表明,将孔隙子群体定量表征与传统相关性分析相结合,可以解析伪相关引发的地质解释多解性,增强主控因素分析的可靠性;③采用基于通用方程的改进累积尺寸分布模型和基于孔隙自相似性原理的小尺度介孔预测模型,可以助力多解性解析方法在孔隙分形领域和介孔尺度研究中的有效应用;④当前的多解性解析技术仍存在不足,在未来的研究中融合成因推断等机器学习方法,有望进一步提升该技术的应用效果与智能化水平。研究旨在为细粒岩孔隙评价和成储机制研究提供理论参考与技术启示。

关键词: 细粒岩孔隙, 伪相关, 多重共线性, 多解性解析, 主控因素

Abstract: Accurate characterization of pore systems in fine-grained rocks and the elucidation of their primary controlling factors provide a vital scientific basis for formulating efficient unconventional hydrocarbon exploration and development strategies. Conventional research often infers dominant controlling factors through correlation analysis between pore parameters (e.g., specific pore volume, fractal dimension) and geological variables (e.g., total organic carbon, mineral composition). However, simplistic statistical associations fail to reveal the intricate genetic linkages among variables, leading to ambiguity in geological interpretations and posing significant challenges to the precise deciphering of pore development mechanisms. To address this issue, this study systematically reviews the research progress regarding the ambiguity of primary controlling factors for fine-grained rock pore characteristics and their corresponding analytical techniques, highlighting four key advancements and insights. (1) Multicollinearity among geological variables is the intrinsic mechanism driving spurious correlations between pore parameters and non-dominant factors, illustrating the inherent methodological limitations of conventional correlation analysis in identifying primary controlling factors. (2) Empirical analyses of the Member 7 of Triassic Yanchang Formation in Ordos Basin demonstrate that integrating the quantitative characterization of pore subpopulations with traditional correlation analysis can resolve the ambiguity in geological interpretations caused by spurious correlations, thereby enhancing the reliability of primary controlling factor identification. (3) Utilizing an improved cumulative size distribution model derived from general equations alongside a small-scale mesopore prediction model based on pore self-similarity principles facilitates the effective application of ambiguity-resolution methods in the research of pore fractals and mesopore sizes. (4) Current ambiguity-resolution techniques still exhibit limitations. Integrating machine learning approaches, such as causal inference, into future research holds promise for further enhancing the practical efficacy and intelligence of these techniques. This study aims to provide theoretical references and technical insights for the evaluation of fine-grained rock pores and the investigation of reservoir-formation mechanisms.

Key words: fine-grained rock pore, spurious correlation, multicollinearity, ambiguity-resolution, primary controlling factors

中图分类号:

TE122.2

董琳, 王梓毅, 梅启亮, 朱如凯, 金之钧. 细粒岩孔隙主控因素多解性问题与解析技术[J]. 石油学报, 2026, 47(6): 1190-1203,1257.

Dong Lin, Wang Ziyi, Mei Qiliang, Zhu Rukai, Jin Zhijun. The ambiguity-resolution problem and analytical techniques of the primary controlling factors for fine-grained rock pore characteristics[J]. Acta Petrolei Sinica, 2026, 47(6): 1190-1203,1257.

参考文献

[1] 金之钧,朱如凯,梁新平,等. 当前陆相页岩油勘探开发值得关注的几个问题[J].石油勘探与开发,2021,48(6):1276-1287.
JIN Zhijun,ZHU Rukai,LIANG Xinping,et al.Several issues worthy of attention in current lacustrine shale oil exploration and development[J].Petroleum Exploration and Development,2021,48(6):1276-1287.
[2] 赵文智,胡素云,侯连华,等.中国陆相页岩油类型、资源潜力及与致密油的边界[J].石油勘探与开发,2020,47(1):1-10.
ZHAO Wenzhi,HU Suyun,HOU Lianhua,et al.Types and resource potential of continental shale oil in China and its boundary with tight oil[J].Petroleum Exploration and Development,2020,47(1):1-10.
[3] 邹才能,潘松圻,荆振华,等.页岩油气革命及影响[J].石油学报,2020,41(1):1-12.
ZOU Caineng,PAN Songqi,JING Zhenhua,et al.Shale oil and gas revolution and its impact[J].Acta Petrolei Sinica,41(1):1-12.
[4] 郭旭升,王濡岳,申宝剑,等.中国页岩气地质特征、资源潜力与发展方向[J].石油勘探与开发,2025,52(1):15-28.
GUO Xusheng,WANG Ruyue,SHEN Baojian,et al.Geological characteristics,resource potential,and development direction of shale gas in China[J].Petroleum Exploration and Development,2025,52(1):15-28.
[5] KRANCK K,SMITH P C,MILLIGAN T G.Grain-size characteristics of fine-grained unflocculated sediments II:'Multi-Round’ distributions[J].Sedimentology,1996,43(3):597-606.
[6] JIANG Zaixing,DUAN Hongjie,LIANG Chao,et al.Classification of hydrocarbon-bearing fine-grained sedimentary rocks[J].Journal of Earth Science,2017,28(6):693-976.
[7] PICARD M D.Classification of fine-grained sedimentary rocks[J].Journal of Sedimentary Research,1971,41(1):179-195.
[8] MACQUAKER J H S,ADAMS A E.Maximizing information from fine-grained sedimentary rocks:an inclusive nomenclature for mudstones[J].Journal of Sedimentary Research,2003,73(5):735-744.
[9] LOUCKS R G,REED R M,RUPPEL S C,et al.Morphology,genesis,and distribution of nanometer-scale pores in siliceous mudstones of the Mississippian Barnett shale[J].Journal of Sedimentary Research,2009,79(12):848-861.
[10] ZUO J Y,GUO Xuqiang,LIU Yansheng,et al.Impact of capillary pressure and nanopore confinement on phase behaviors of shale gas and oil[J].Energy & Fuels,2018,32(4):4705-4714.
[11] PITAKBUNKATE T,BALBUENA P B,MORIDIS G J,et al.Effect of confinement on pressure/volume/temperature properties of hydrocarbons in shale reservoirs[J].SPE Journal,2016,21(2):621-634.
[12] ZHANG Jizhen,LI Xianqing,WEI Qiang,et al.Characterization of full-sized pore structure and fractal characteristics of marine-continental transitional Longtan Formation shale of Sichuan Basin,South China[J].Energy & Fuels,2017,31(10):10490-10504.
[13] LOUCKS R G,REED R M,RUPPEL S C,et al.Spectrum of pore types and networks in mudrocks and a descriptive classification for matrix-related mudrock pores[J].AAPG Bulletin,2012,96(6):1071-1098.
[14] 赵建华,于孟想,陈扬,等.硅质成岩演化过程及其对页岩储层孔隙发育的控制作用——以四川盆地奥陶系五峰组和志留系龙马溪组为例[J].石油学报,2025,46(12):2273-2285.
ZHAO Jianhua,YU Mengxiang,CHEN Yang,et al.Silica diagenetic evolution and its control on pore development in shale reservoirs:a case study of the Ordovician Wufeng Formation and Silurian Longmaxi Formation in the Sichuan Basin[J].Acta Petrolei Sinica,2025,46(12):2273-2285.
[15] LIU Wenping,LIU Jun,CAI Molun,et al.Pore evolution characteristic of shale in the Longmaxi Formation,Sichuan Basin[J].Petroleum Research,2017,2(4):291-300.
[16] XIONG Shuling,GAO Zhiye,WEI Weihang,et al.Differential effects of pore structure of mineral and maceral components on the methane adsorption capacity evolution of the Lower Jurassic Da’anzhai Member of the Ziliujing Formation lacustrine shale,Sichuan Basin,China[J].Marine and Petroleum Geology,2023,147:106017.
[17] GORAL J,DEO M,MCLENNAN J,et al.Macro- and micro-compression testing of shales[J].Journal of Petroleum Science and Engineerin g,2020,191:107034.
[18] CAO Taotao,DENG Mo,SONG Zhiguang,et al.Characteristics and controlling factors of pore structure of the Permian shale in southern Anhui Province,East China[J].Journal of Natural Gas Science and Engineering,2018,60:228-245.
[19] 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.
[20] WANG Ziyi,ZHANG Liuping,GAO Yuan,et al.Pore properties of the lacustrine shale in the upper part of the Sha-4 Member of the Paleogene Shahejie Formation in the Dongying depression in East China[J].Geofluids,2021,2021:6616843.
[21] IQBAL M A,REZAEE R,SMITH G,et al.Shale lithofacies controls on porosity and pore structure:an example from Ordovician Goldwyer Formation, Canning Basin,Western Australia[J].Journal of Natural Gas Science and Engineering,2021,89:103888.
[22] TENG Xian,AHN Y,LIN Yuru.VISPUR:visual aids for identifying and interpreting spurious associations in data-driven decisions[J].IEEE Transactions on Visualization and Computer Graphics,2024,30(1):219-229.
[23] SIMON H A.Spurious correlation:a causal interpretation[J].Journal of the American Statistical Association,1954,49(267):467-479.
[24] ALTMAN N,KRZYWINSKI M.Association,correlation and causation[J].Nature Methods,2015,12(10):899-900.
[25] HAIG B D.Spurious correlation[M]//SALKIND H J.Encyclopedia of measurement and statistics.Thousand Oaks:Sage Publications,2007.
[26] WANG Ziyi,DONG Lin,JIN Zhijun,et al.Efforts to untie the multicollinearity knot and identify factors controlling macropore structures in shale oil reservoirs[J].Advances in Geo-Energy Research,2024,11(3):194-207.
[27] WANG Ziyi,DONG Lin,JIN Zhijun,et al.Introducing an enhanced cumulative size distribution model to unearth the origins of macropore heterogeneity of the Chang-7 shale oil reservoirs in the Ordos Basin[J].Fractal and Fractional,2024,8(12):732.
[28] WANG Ziyi,DONG Lin,JIN Zhijun,et al.Shale pore investigation beyond the practical pore resolution limits of scanning electron microscopy[J].Energy & Fuels,2025,39(11):5312-5327.
[29] M ARILL K A.Advanced statistics:linear regression,Part I:simple linear regression[J].Academic Emergency Medicine,2004,11(1): 87-93.
[30] 何晓群,闵素芹.应用回归分析[M].北京:高等教育出版社,2014.
HE Xiaoqun,MIN Suqin.Applied regression analysis[M].Beijing:Higher Education Press,2014.
[31] LI Fulai,WANG Maozhen,LIU Shaobo,et al.Pore characteristics and influencing factors of different types of shales[J].Marine and Petroleum Geology,2019,102:391-401.
[32] HUANG Weikai,MA Xiaofeng,ZHOU Xinping,et al.Characteristics and controlling factors of pore structure of shale in the 7th Member of Yanchang Formation in Huachi area,Ordos Basin,China[J].Journal of Natural Gas Geoscience,2023,8(5):319-336.
[33] NGUYEN Q V,HUANG Maolin,SIMOFF S.Enhancing scatter-plots with start-plots for visualising multi-dimensional data[C]//202024th International Conference Information Visualisation (IV).Melbourne,Australia:IEEE,2020:80-85.
[34] WANG Guanping,JIN Zhijun,ZHANG Qian,et al.Effects of clay minerals and organic matter on pore evolution of the early mature lacustrine shale in the Ordos Basin,China[J].Journal of Asian Earth Sciences,2023,246:105516.
[35] XU Lingling,PAN Renfang,HU Haiyan,et al.Contribution of various shale components to pore system:insights from attributes analysis[J].Journal of Marine Science and Engineering,2023,11(7):1327.
[36] CHAN J Y L,LEOW S M H,BEA K T,et al.Mitigating the multicollinearity problem and its machine learning approach:a review[J].Mathematics,2022,10(8):1283.
[37] SHRESTHA N.Detecting multicollinearity in regression analysis[J].American Journal of Applied Mathematics and Statistics,2020,8(2):39-42.
[38] KIM J H.Multicollinearity and misleading statistical results[J].Korean Journal of Anesthesiology,2019,72(6):558-569.
[39] DESBOULETS L D D.A review on variable selection in regression analysis[J].Econometrics,2018,6(4):45.
[40] EFROYMSON M A.Multiple regression analysis[M]//RALSTON A,WILF H S.Mathematical methods for digital computers.New York:John Wiley,1960.
[41] HAMAKER H C.On multiple regression analysis[J].Statistica Neerlandica,1962,16(1):31-56.
[42] WOLD S,RUHE A,WOLD H,et al.The collinearity problem in linear regression.The Partial Least Squares (PLS) approach to generalized inverses[J].SIAM Journal on Scientific and Statistical Computing,1984,5(3):735-743.
[43] L IU Bo,MOHAMMADI M R,MA Zhongliang,et al.Pore structure evolution of Qingshankou shale (kerogen type I) during artificial maturation via hydrous and anhydrous pyrolysis:experimental study and intelligent modeling[J].Energy,2023,282:128359.
[44] LIU Kouqi,OSTADHASSAN M,ZHOU Jie,et al.Nanoscale pore structure characterization of the Bakken shale in the USA[J].Fuel,2017,209:567-578.
[45] LIU Chenyu,ZHANG Xinlian,NGUYEN T T,et al.Partial least squares regression and principal component analysis:similarity and differences between two popular variable reduction approaches[J].General Psychiatry,2022,35(1):e100662.
[46] 王惠文,吴载斌,孟洁.偏最小二乘回归的线性与非线性方法[M].北京:国防工业出版社,2006.
WANG Huiwen,WU Zaibin,MENG Jie.Partial least-squares regression:linear and nonlinear methods[M].Beijing:National Defense Industry Press,2006.
[47] WAKELING I N,MORRIS J J.A test of significance for partial least squares regression[J].Journal of Chemometrics,1993,7(4): 291-304.
[48] XU Lu,FU Haiyan,GOODARZI M,et al.Stochastic cross validation[J].Chemometrics and Intelligent Laboratory Systems,2018,175:74-81.
[49] WOLD S,SJÖSTRÖM M,ERIKSSON L.PLS-regression:a basic tool of chemometrics[J].Chemometrics and Intelligent Laboratory Systems,2001,58(2):109-130.
[50] MAHIEU B,QANNARI E M,JAILLAIS B.Extension and significance testing of Variable Importance in Projection (VIP) indices in partial least squares regression and principal components analysis[J].Chemometrics and Intelligent Laboratory Systems,2023,242:104986.
[51] STOCCHER M,LOCCI E,D'ALOJA E,et al.PLS2 in metabolomics[J].Metabolites,2019,9(3):51.
[52] FAVILLA S,DURANTE C,VIGNI M L,et al.Assessing feature relevance in NPLS models by VIP[J].Chemometrics and Intelligent Laboratory Systems,2013,129:76-86.
[53] SONG Liaosha,MARTIN K,CARR T R,et al.Porosity and storage capacity of Middle Devonian shale:a function of thermal maturity,total organic carbon,and clay content[J].Fuel,2019,241:1036-1044.
[54] SHALDYBIN M V,LOPUSHNYAK Y M,GONCHAROV I V,et al.The mineralogy of the clayey-silty siliceous rocks in the Bazhenov shale Formation (Upper Jurassic) in the west Siberian Basin,Russia:the role of diagenesis and possible implications for their exploitation as an unconventional hydrocarbon reservoir[J].Applied Clay Science,2017,136:75-89.
[55] ZHOU Kai,ZHANG Shuo,YANG Minfang,et al.Palaeoclimatic influence on lake palaeoenvironment and organic matter accumulation in the Middle Jurassic Shimengou Formation (Qaidam Basin,NW China)[J].Geoenergy Science and Engineering,2024,233:212581.
[56] JI Changjun,LIU Tianfu,CHEN Yun,et al.Nanoscale pore structure and fractal characteristics of lacustrine shale:a case study of the Upper Cretaceous Qingshankou shales,Southern Songliao Basin,China[J].PLOS One,2024,19(10):e0309346.
[57] MILLIKEN K L,ESCH W L,REED R M,et al.Grain assemblages and strong diagenetic overprinting in siliceous mudrocks,Barnett shale (Mississippian),Fort Worth Basin,Texas[J].AAPG Bulletin,2012,96(8):1553-1578.
[58] WANG Liang,FU Yonghong,LI Jun,et al.Mineral and pore structure characteristics of gas shale in Longmaxi Formation:a case study of Jiaoshiba gas field in the southern Sichuan Basin,China[J].Arabian Journal of Geosciences,2016,9(19):733.
[59] ROCHA H V,SANT'ANNA L G,RODRIGUES C F A,et al.The paleoenvironmental and thermal histories of the Permian Irati Formation shale in the Paraná Basin,Brazil:an integrated approach based on mineralogical and organic imprints[J].Marine and Petroleum Geology,2023,154:106328.
[60] AKINTOLA G O,AMPONSAH-DACOSTA F,RUPPRECHT S,et al.Petrographic,mineralogical,morphological and organic constraints of the Permian shaly-coal in the Tuli Basin of Limpopo-Area Karoo-Aged Basin,South Africa:implication for potential gas generation[J].Heliyon,2023,9(3):e14446.
[61] KUMAR S,DAS S,BASTIA R,et al.Mineralogical and morphological characterization of Older Cambay shale from North Cambay Basin,India:implication for shale oil/gas development[J].Marine and Petroleum Geology,2018,97:339-354.
[62] JADOON Q K,ROBERTS E,BLENKINSOP T,等.澳大利亚库珀盆地二叠系Roseneath组与Murteree组页岩矿物模拟及岩石物性参数[J].石油勘探与开发,2016,43(2):253-260.
JADOON Q K,ROBERTS E,BLENKINSOP T,et al.Mineralogical modelling and petrophysical parameters in Permian gas shales from the Roseneath and Murteree formations,Cooper Basin,Australia[J].Petroleum Exploration and Development,2016,43(2):253-260.
[63] CAO Yan,JIN Zhijun,ZHU Rukai,et al.Pore systems and their correlation with oil enrichment in various lithofacies of saline lacustrine shale strata[J].International Journal of Coal Geology,2024,282:104444.
[64] WU Lanyu,LU Yangbo,JIANG Shu,et al.Pore structure characterization of different lithofacies in marine shale:a case study of the Upper Ordovician Wufeng-Lower Silurian Longmaxi Formation in the Sichuan Basin,SW China[J].Journal of Natural Gas Science and Engineering,2018,57:203-215.
[65] 倪良田,杜玉山,蒋龙,等.济阳坳陷富碳酸盐页岩纹层结构的差异性及其对储层品质的影响——以东营凹陷沙河街组页岩为例[J].石油学报,2024,45(11):1621-1637.
NI Liangtian,DU Yushan,JIANG Long,et al.Difference in laminated structure of carbonate-rich shale and its effects on reservoir quality in Jiyang depression:a case study of Shahejie Formation shale in Dongying sag[J].Acta Petrolei Sinica,2024,45(11):1621-1637.
[66] LIU Ruiyin,ZHOU Wen,XU Hao,et al.Impact of minerals and sealing systems on the pore characteristics of the Qiongzhusi Formation shale in the southern Sichuan Basin[J].ACS Omega,2022,7(18):15821-15840.
[67] LIU Kouqi,OSTADHASSAN M.Multi-scale fractal analysis of pores in shale rocks[J].Journal of Applied Geophysics,2017,140:1-10.
[68] SANEI H.Genesis of solid bitumen[J].Scientific Reports,2020,10(1):15595.
[69] MEI Qiliang,GUO Ruiliang,ZHOU Xinping,et al.Pore structure characteristics and impact factors of laminated shale oil reservoir in Chang 7₃ sub-member of Ordos Basin,China[J].Journal of Natural Gas Geoscience,2023,8(4):227-243.
[70] SU Siyuan,JIANG Zhenxue,SHAN Xuanlong,et al.The effects of shale pore structure and mineral components on shale oil accumulation in the Zhanhua sag,Jiyang depression,Bohai Bay Basin,China[J].Journal of Petroleum Science and Engineering,2018,165:365-374.
[71] LIU Quanyou,LI Peng,JIN Zhijun,et al.Preservation of organic matter in shale linked to bacterial sulfate reduction (BSR) and volcanic activity under marine and lacustrine depositional environments[J].Marine and Petroleum Geology,2021,127:104950.
[72] ZHANG Wang,JIN Zhijun,LIU Quanyou,et al.The C-S-Fe system evolution reveals organic matter preservation in lacustrine shales of Yanchang Formation,Ordos Basin,China[J].Marine and Petroleum Geology,2022,142:105734.
[73] JIANG Fujie,CHEN Di,CHEN Jian,et al.Fractal analysis of shale pore structure of continental gas shale reservoir in the Ordos Basin,NW China[J].Energy & Fuels,2016,30(6):4676-4689.
[74] YANG Feng,NING Zhengfu,LIU Huiqing.Fractal characteristics of shales from a shale gas reservoir in the Sichuan Basin,China[J].Fuel,2014,115:378-384.
[75] LU Hao,LI Qing,YUE Dali,et al.Quantitative characterization and formation mechanism of the pore system heterogeneity:examples from organic-rich laminated and organic-poor layered shales of the Upper Triassic Chang 7 Member in the southern Ordos Basin,China[J].Marine and Petroleum Geology,2023,147:105999.
[76] JIAO Kun,YAO Suping,LIU Chun,et al.The characterization and quantitative analysis of nanopores in unconventional gas reservoirs utilizing FESEM-FIB and image processing:an example from the lower Silurian Longmaxi shale,Upper Yangtze region,China[J].International Journal of Coal Geology,2014,128-129:1-11.
[77] PAN Jienan,WANG Kai,HOU Quanlin,et al.Micro-pores and fractures of coals analysed by field emission scanning electron microscopy and fractal theory[J].Fuel,2016,164:277-285.
[78] YU Boming,LI Jianhua,LI Zhihua,et al.Permeabilities of unsaturated fractal porous media[J].International Journal of Multiphase Flow,2003,29(10):1625-1642.
[79] 刘夫贵,杨永飞,杨海元,等.基于生成对抗网络的页岩孔隙结构参数表征方法——图像数据增强、超分辨率重构和多矿物相分割[J].石油勘探与开发,2025,52(5):1118-1130.
LIU Fugui,YANG Yongfei,YANG Haiyuan,et al.Pore structure properties characterization of shale using generative adversarial network:image augmentation,super-resolution reconstruction,and multi-mineral auto-segmentation[J].Petroleum Exploration and Development,2025,52(5):1118-1130.
[80] NOTTE J,WARD B,ECONOMOU N,et al.An introduction to the helium ion microscope[J].AIP Conference Proceedings,2007,931(1):489-496.
[81] WU Jianguo,LUO Chao,ZHONG Kesu,et al.Innovative characterization of organic nanopores in marine shale by the integration of HIM and SEM[J].Energy,2023,282:128390.
[82] HOUBEN M E,DESBOIS G,URAI J L.Pore morphology and distribution in the shaly facies of Opalinus Clay (Mont Terri,Switzerland):insights from representative 2D BIB-SEM investigations on mm to nm scale[J].Applied Clay Science,2013,71:82-97.
[83] KLAVER J,DESBOIS G,LITTKE R,et al.BIB-SEM characterization of pore space morphology and distribution in postmature to overmature samples from the Haynesville and Bossier shales[J].Marine and Petroleum Geology,2015,59:451-466.
[84] XING Jieqi,XIAN Haiyang,YANG Yiping,et al.Nanoscale mineralogical characterization of terrestrial and extraterrestrial samples by transmission electron microscopy:a review[J].ACS Earth and Space Chemistry,2023,7(2):289-302.
[85] JIAO Licheng,WANG Yuhan,LIU Xu,et al.Causal inference meets deep learning:a comprehensive survey[J].Research,2024,7:0467.

细粒岩孔隙主控因素多解性问题与解析技术

The ambiguity-resolution problem and analytical techniques of the primary controlling factors for fine-grained rock pore characteristics

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	廖文毫, 曾溅辉, 韩俊, 王鑫, 黄诚, 刘亚洲, 朱莲花. 顺北地区主干走滑断裂之间次级断裂区油气成藏特征与富集主控因素定量评价[J]. 石油学报, 2026, 47(5): 1024-1044.
[2]	杨海风, 房舟, 王飞龙, 姜福杰, 齐振国, 刘梦醒, 郑晓薇, 陈迪, 胡涛. 渤海湾盆地沙河街组—东营组深部热液对有机质富集的影响及模式[J]. 石油学报, 2025, 46(6): 1089-1107.
[3]	胡晨林, 边静, 唐勇, 韦波, 张斌, 桑树勋, 李鑫, 冯烁. 中国富油煤形成机制与地质产出研究进展及趋势[J]. 石油学报, 2025, 46(10): 1985-2000.
[4]	王茂云, 曾溅辉, 王小娟, 陈冬霞, 吴长江, 潘珂, 张欢乐, 崔虎旺. 源-储分离型致密砂岩气藏中气水分布控制因素——以四川盆地中部地区沙溪庙组致密砂岩气为例[J]. 石油学报, 2024, 45(8): 1187-1201,1218.
[5]	赵波, 丁寒生, 尹淑敏, 张永成, 李忠权, 孙国昕, 刘筝. 松辽盆地北部中央隆起带基岩潜山天然气成藏主控因素与成藏模式[J]. 石油学报, 2024, 45(12): 1783-1799.
[6]	党伟, 张金川, 聂海宽, 王凤琴, 唐玄, 蒋恕, 魏晓亮, 刘秋波, 李沛, 李菲, 孙江涛. 页岩油微观赋存特征及其主控因素——以鄂尔多斯盆地延安地区延长组7段3亚段陆相页岩为例[J]. 石油学报, 2022, 43(4): 507-523.
[7]	唐勇, 宋永, 郭旭光, 赵靖舟, 吴涛, 黄立良, 何文军, 吴伟涛, 吴和源. 准噶尔盆地玛湖凹陷源上致密砾岩油富集的主控因素[J]. 石油学报, 2022, 43(2): 192-206.
[8]	刘翰林, 邹才能, 邱振, 潘松圻, 张文正, 荆振华, 郝记华, 尹帅, 吴松涛, 李士祥, 郭秋雷. 鄂尔多斯盆地延长组7段3亚段异常高有机质沉积富集因素[J]. 石油学报, 2022, 43(11): 1520-1541.
[9]	刘凯旋, 陈践发, 付娆, 汪华, 罗冰, 戴鑫, 师肖飞, 董勍伟. 富氦天然气藏成藏特征及主控因素[J]. 石油学报, 2022, 43(11): 1652-1663.
[10]	吴建发, 赵圣贤, 范存辉, 夏自强, 季春海, 张成林, 曹埒焰. 川南长宁地区龙马溪组富有机质页岩裂缝发育特征及其与含气性的关系[J]. 石油学报, 2021, 42(4): 428-446.
[11]	刘春, 陈世加, 赵继龙, 陈戈, 苏洲, 高乔. 远源油气成藏条件与富集主控因素——以库车坳陷南部斜坡带中生界-新生界油气藏为例[J]. 石油学报, 2021, 42(3): 307-318.
[12]	赵贤正, 李宏军, 付立新, 崔宇, 韩国猛, 楼达, 蒲秀刚, 刘国全, 姜文亚, 董雄英, 邹磊落. 渤海湾盆地黄骅坳陷古生界煤成凝析气藏特征、主控因素与发育模式[J]. 石油学报, 2021, 42(12): 1592-1604.
[13]	冯林杰, 蒋裕强, 刘菲, 谷一凡, 王占磊, 钟克修, 廖义沙. 川东地区开江—梁平海槽南段飞仙关组鲕滩储层特征及主控因素[J]. 石油学报, 2021, 42(10): 1287-1298.
[14]	代一丁, 牛子铖, 汪旭东, 王小龙, 肖张波, 张凯迪, 赵璇. 珠江口盆地陆丰凹陷古近系与新近系油气富集规律的差异及其主控因素[J]. 石油学报, 2019, 40(s1): 41-52.
[15]	朱筱敏, 葛家旺, 吴陈冰洁, 张向涛, 汪旭东, 李晓燕, 黎明. 珠江口盆地陆丰凹陷深层砂岩储层特征及主控因素[J]. 石油学报, 2019, 40(s1): 69-80.