| [1] |
楚泽涵, 高杰, 黄隆基, 等. 地球物理测井方法与原理[M]. 北京: 石油工业出版社, 2007.
|
|
[CHU Z H, GAO J, HUANG L J, et al. Geophysical logging methods and principles[M]. Beijing: Petroleum Industry Press, 2007.]
|
| [2] |
KOZENY J. Ueber kapillare leitung des wassers im boden, sitzungsberichte[J]. Royal Academy of Science, 1927, 136(2): 271-306.
|
| [3] |
CARMAN P C. Fluid flow through granular beds[J]. Chemical Engineering Research and Design, 1997, 75: S32-S48.
doi: 10.1016/S0263-8762(97)80003-2
URL
|
| [4] |
陈瑶, 何宗斌, 覃莹瑶, 等. 基于核磁共振测井的储层渗透率计算方法综述[J]. 能源与环保, 2022, 44(1): 125-131.
|
|
[CHEN Y, HE Z B, QIN Y Y, et al. Review of reservoir permeability calculation methods based on nuclear magnetic resonance logging[J]. China Energy and Environmental Protection, 2022, 44(1): 125-131.]
|
| [5] |
李宁, 王克文, 武宏亮, 等. 渗透率测井评价: 现状及发展方向[J]. 石油科学通报, 2023, 8(4): 432-444.
|
|
[LI N, WANG K W, WU H L, et al. Permeability logging evaluation: Current status and development directions[J]. Petroleum Science Bulletin, 2023, 8(4): 432-444.]
|
| [6] |
KENYON W E, DAY P I, STRALEY C, et al. A three-part study of NMR longitudinal relaxation properties of water-saturated sandstones[J]. SPE Formation Evaluation, 1988, 3(3): 622-636.
doi: 10.2118/15643-PA
URL
|
| [7] |
COATES G R, MILLER M, GILLEN M, et al. The MRIL in Conoco 33-1 an investigation of a new magnetic resonance imaging log[C]. SPWLA 32nd Annual Logging Symposium, Midland, Texas, June 1991.
|
| [8] |
KOLODZIE S. Analysis of pore throat size and use of the waxman-smits equation to determine OOIP in Spindle Field, Colorado[C]. SPE Annual Technical Conference and Exhibition, Dallas, Texas, September 1980: SPE-9382-MS.
|
| [9] |
PITTMAN E D. Relationship of porosity and permeability to various parameters derived from mercury injection-capillary pressure curves for sandstone[J]. AAPG Bulletin, 1992, 76(2): 191-198.
doi: 10.1306/BDFF87A4-1718-11D7-8645000102C1865D
URL
|
| [10] |
肖忠祥, 肖亮. 基于核磁共振测井和毛管压力的储层渗透率计算方法[J]. 原子能科学技术, 2008, 42(10): 868-871.
doi: 10.7538/yzk.2008.42.10.0868
|
|
[XIAO Z X, XIAO L. Method to calculate reservoir permeability using nuclear magnetic resonance logging and capillary pressure data[J]. Atomic Energy Science and Technology, 2008, 42(10): 868-871.]
|
| [11] |
XIAO L, ZOU C C, MAO Z Q, et al. A new technique for synthetizing capillary pressure (Pc) curves using NMR logs in tight gas sandstone reservoirs[J]. Journal of Petroleum Science and Engineering, 2016, 145: 493-501.
doi: 10.1016/j.petrol.2016.06.002
URL
|
| [12] |
YU B M, CHENG P. A fractal permeability model for bi-dispersed porous media[J]. International Journal of Heat and Mass Transfer, 2002, 45(14): 2983-2993.
doi: 10.1016/S0017-9310(02)00014-5
URL
|
| [13] |
CHENG H, WANG F G, YANG G H, et al. Prediction of relative permeability from capillary pressure based on the fractal capillary bundle model[J]. Applied Thermal Engineering, 2024, 239: 122093.
doi: 10.1016/j.applthermaleng.2023.122093
URL
|
| [14] |
DOU W C, LIU L F, JIA L B, et al. Pore structure, fractal characteristics and permeability prediction of tight sandstones: A case study from Yanchang Formation, Ordos Basin, China[J]. Marine and Petroleum Geology, 2021, 123: 104737.
doi: 10.1016/j.marpetgeo.2020.104737
URL
|
| [15] |
QU Y Q, SUN W, TAO R D, et al. Pore-throat structure and fractal characteristics of tight sandstones in Yanchang Formation, Ordos Basin[J]. Marine and Petroleum Geology, 2020, 120: 104573.
doi: 10.1016/j.marpetgeo.2020.104573
URL
|
| [16] |
杨兴旺, 赵杰, 朱友青. 利用孔隙分类法计算火成岩储层渗透率的方法及其应用[J]. 测井技术, 2010, 34(2): 164-167.
|
|
[YANG X W, ZHAO J, ZHU Y Q. A P3A method to calculate volcanic reservoir permeability and its application[J]. Well Logging Technology, 2010, 34(2): 164-167.]
|
| [17] |
GONÇALVES L, VICTOR R A, BARROSO E V. Enhancing permeability estimation methods in Brazilian pre-salt complex carbonate reservoirs[J]. Geoenergy Science and Engineering, 2024, 243: 213345.
doi: 10.1016/j.geoen.2024.213345
URL
|
| [18] |
罗刚, 罗嗣慧, 肖立志, 等. 机器学习在核磁共振测井数据处理中的应用进展[J]. 测井技术, 2023, 47(6): 643-652.
|
|
[LUO G, LUO S H, XIAO L Z, et al. Progress and prospect for machine learning applied in NMR logging[J]. Well Logging Technology, 2023, 47(6): 643-652.]
|
| [19] |
徐鹏宇, 周怀来, 官俊洁, 等. 碳酸盐岩储层自适应模型常规测井渗透率预测[J]. 石油地球物理勘探, 2022, 57(5): 1192-1203+1007-1008.
doi: 10.13810/j.cnki.issn.1000-7210.2022.05.021
|
|
[XU P Y, ZHOU H L, GUAN J J, et al. Permeability prediction of carbonate reservoirs by conventional logging with adaptive model[J]. Oil Geophysical Prospecting, 2022, 57(5): 1192-1203+1007-1008.]
doi: 10.13810/j.cnki.issn.1000-7210.2022.05.021
|
| [20] |
MAHDY A, ZAKARIA W, HELMI A, et al. Machine learning approach for core permeability prediction from well logs in Sandstone Reservoir, Mediterranean Sea, Egypt[J]. Journal of Applied Geophysics, 2024, 220: 105249.
doi: 10.1016/j.jappgeo.2023.105249
URL
|
| [21] |
吴勃翰, 李芳, 汤翟, 等. 基于双驱动模型的低渗气藏测井渗透率预测方法——以莺歌海盆地东方气田为例[J]. 新疆石油地质, 2025, 46(5): 622-629.
|
|
[WU B H, LI F, TANG D, et al. A logging-based permeability prediction method based on dual-driven model for low-permeability gas reservoirs: A case study of Dongfang gas field in Yinggehai Basin[J]. Xinjiang Petroleum Geology, 2025, 46(5): 622-629.]
|
| [22] |
杨清, 管耀, 冯进, 等. 基于流动单元分类与优选的致密砂岩储层测井渗透率评价方法[J]. 石油钻探技术, 2025, 53(2): 181-190.
|
|
[YANG Q, GUAN Y, FENG J, et al. Permeability evaluation from logs in tight sandstone reservoirs based on classification and optimization of flow units[J]. Petroleum Drilling Techniques, 2025, 53(2): 181-190.]
|
| [23] |
王道伸, 辛红刚, 葸克来, 等. 致密砂岩储层孔喉结构特征及其对含油性的控制作用——以鄂尔多斯盆地志靖—安塞地区延长组8段为例[J]. 天然气地球科学, 2024, 35(4): 623-634.
doi: 10.11764/j.issn.1672-1926.2023.10.009
|
|
[WANG D S, XIN H G, XI K L, et al. Characteristics of pore throat structure and its control on oiliness in tight sandstone reservoirs: Case study of the 8th member of Yanchang Formation in Zhijing-Ansai area, Ordos Basin[J]. Natural Gas Geoscience, 2024, 35(4): 623-634.]
|
| [24] |
KANITPANYACHAROEN W PARKINSON, D Y, DE CARLO F, et al. A comparative study of X-ray tomographic microscopy on shales at different synchrotron facilities: ALS, APS and SLS[J]. Journal of Synchrotron Radiation, 2013, 20(Pt 1): 172-180.
doi: 10.1107/S0909049512044354
URL
|
| [25] |
赵圣贤, 刘勇, 李博, 等. 四川盆地泸州区块五峰组-龙马溪组页岩气储层孔隙连通性特征及模式[J]. 石油与天然气地质, 2024, 45(6): 1720-1735.
|
|
[ZHAO S X, LIU Y, LI B, et al. Characteristics and patterns of the pore connectivity in shale gas reservoirs in the Wufeng-Longmaxi Formations, Luzhou Block, Sichuan Basin[J]. Oil & Gas Geology, 2024, 45(6): 1720-1735.]
|
| [26] |
孙亮, 王晓琦, 金旭, 等. 微纳米孔隙空间三维表征与连通性定量分析[J]. 石油勘探与开发, 2016, 43(3): 490-498.
doi: 10.11698/PED.2016.03.22
|
|
[SUN L, WANG X Q, JIN X, et al. Three dimensional characterization and quantitative connectivity analysis of micro/nano pore space[J]. Petroleum Exploration and Development, 2016, 43(3): 490-498.]
doi: 10.11698/PED.2016.03.22
|
| [27] |
王静, 郗兆栋, 陆冬华. 基于恒速压汞技术研究页岩气储层孔隙结构: 以湘西北地区五峰组页岩为例[J]. 地质与勘探, 2021, 57(2): 450-456.
|
|
[WANG J, XI Z D, LU D H. Pore structure of shale gas reservoirs revealed by constant-speed mercury injection experiments: A case study of Wufeng Formation shale from northwestern Hunan Province[J]. Geology and Exploration, 2021, 57(2): 450-456.]
|
| [28] |
吴春燕, 展转盈, 李文厚, 等. 联合压汞法表征致密油储层孔喉特征: 以陕北定边地区延长组长7段为例[J]. 地质科学, 2023, 58(2): 710-722.
|
|
[WU C Y, ZHAN Z Y, LI W H, et al. The combination methods of mercury intrusion to characterize pore-throat characteristics in tight oil reservoir: A case study of Yanchangzu Chang 7 reservoir in Dingbian area of Shanbei[J]. Chinese Journal of Geology, 2023, 58(2): 710-722.]
|
| [29] |
何雨丹, 毛志强, 肖立志, 等. 利用核磁共振T2分布构造毛管压力曲线的新方法[J]. 吉林大学学报(地球科学版), 2005, 35(2): 177-181.
|
|
[HE Y D, MAO Z Q, XIAO L Z, et al. A new method to obtain capillary pressure curve using NMR T2 distribution[J]. Journal of Jilin University (Earth Science Edition), 2005, 35(2): 177-181.]
|
| [30] |
XIAO L, CHEN Z M, YUAN Y C. A novel method to construct capillary pressure curves by using NMR log data and its application in reservoir evaluation[C]. International Petroleum Technology Conference, Kuala Lumpur, Malaysia, December 2008: IPTC-11863-MS.
|
| [31] |
XIAO L, MAO Z Q, JIN Y. Tight gas sandstone reservoirs evaluation from nuclear magnetic resonance (NMR) logs: Case studies[J]. Arabian Journal for Science and Engineering, 2015, 40(4): 1223-1237.
doi: 10.1007/s13369-015-1608-y
URL
|
| [32] |
宁传祥, 姜振学, 高之业, 等. 用核磁共振和高压压汞定量评价储层孔隙连通性——以沾化凹陷沙三下亚段为例[J]. 中国矿业大学学报, 2017, 46(3): 578-585.
|
|
[NING C X, JIANG Z X, GAO Z Y, et al. Quantitative evaluation of pore connectivity with nuclear magnetic resonance and high pressure mercury injection: A case study of the lower section of Es3 in Zhanhua Sag[J]. Journal of China University of Mining & Technology, 2017, 46(3): 578-585.]
|
| [33] |
黄宏, 闫伟超, 刘航, 等. 四川盆地高石梯-磨溪地区深层碳酸盐岩储层渗透率评价[J]. 测井技术, 2020, 44(5): 462-467.
|
|
[HUANG H, YAN W C, LIU H, et al. Permeability log evaluation of deep carbonate reservoirs in Gaoshiti-Moxi Block, Sichuan Basin[J]. Well Logging Technology, 2020, 44(5): 462-467.]
|
| [34] |
YAO Y B, LIU D M. Comparison of low-field NMR and mercury intrusion porosimetry in characterizing pore size distributions of coals[J]. Fuel, 2012, 95: 152-158.
doi: 10.1016/j.fuel.2011.12.039
URL
|