基于数字岩心分形特征的渗透率预测方法

doi:10.13278/j.cnki.jjuese.20190148

摘要/Abstract

摘要： 基于数字岩心技术，对岩心CT扫描图像进行处理，结合分形理论求取数字岩心的分形特征参数并通过构建数字岩心的等效分形介质模型对岩心渗透率进行预测。首先对两块砂岩岩心进行了微米CT扫描，提取岩心孔隙网络模型，分析岩心孔隙结构特征，结果表明岩心的孔喉半径分布与孔喉配位数分布对岩心渗透率有一定影响；其次利用MATLAB、Image J等软件对CT扫描得到的数字岩心及帝国理工学院网站公开的数字岩心进行处理，基于分形理论求取数字岩心分形维数、迂曲度、迂曲度分形维数和最大孔隙直径等参数；最后基于分形渗透率模型对岩心渗透率进行预测。结果表明：预测渗透率与岩心渗透率具有良好的相关性，相关系数大于0.97。因此，基于数字岩心技术，通过构建数字岩心等效分形介质模型，可以有效预测岩心渗透率。

关键词: 数字岩心, CT扫描, 渗透率, 分形, 孔隙结构

Abstract: Based on digital rock technology, the core CT scanning images are processed to obtain the core fractal parameters with fractal theory, and then the core permeability is predicted by constructing an equivalent fractal model of digital rock. In this study, firstly, the micro-CT scanning experiments of two sandstones were carried out,the core pore network models were extracted, and the pore throat structures were analyzed. Further, these two digital rocks and nine digital rocks from the Imperial College were processed to obtain the fractal parameters including fractal dimension, tortuosity, tortuosity dimension, and maximum pore radius by using MATLAB and Image J. Finally, based on the fractal permeability model, the permeability of cores was predicted. The results show that the pore throat radius distribution and pore coordination number distribution have influence on core permeability. The predicted permeability has a good correlation with the core permeability, and the correlation coefficient is greater than 0.97. Therefore, the core permeability can be effectively predicted based on digital rock technology by constructing an equivalent fractal model.

Key words: digital rock, CT scanning, permeability, fractal, pore structure

中图分类号:

TE311

杨坤, 王付勇, 曾繁超, 赵久玉, 王聪乐. 基于数字岩心分形特征的渗透率预测方法[J]. 吉林大学学报(地球科学版), 2020, 50(4): 1003-1011.

Yang Kun, Wang Fuyong, Zeng Fanchao, Zhao Jiuyu, Wang Congle. Permeability Prediction Based on Fractal Characteristics of Digital Rock[J]. Journal of Jilin University(Earth Science Edition), 2020, 50(4): 1003-1011.

参考文献

[1] 姚军,赵秀才,衣艳静,等. 数字岩心技术现状及展望[J]. 油气地质与采收率, 2005, 12(6):52-54. Yao Jun, Zhao Xiucai, Yi Yanjing, et al. Status and Prospect of Digital Core Technology[J]. Petroleum Geology and Recovery Efficiency, 2005,12(6):52-54.
[2] 潘汝江,何翔,肖维民,等. CT扫描技术在岩心三维重建中的应用[J]. CT理论与应用研究, 2018, 27(3):349-356. Pan Rujiang, He Xiang, Xiao Weimin, et al. Application of CT Scanning Technique in Core 3D Reconstruction[J]. CT Theory and Application, 2018, 27(3):349-356.
[3] 王鑫元,沈忠山,张东,等. 基于全直径岩心CT扫描技术的三元复合驱后微观孔隙结构特征[J]. 大庆石油地质与开发, 2019, 38(2):81-86. Wang Xinyuan, Shen Zhongshan, Zhang Dong, et al.Microscopic Pore Structure Characteristics After ASP Flooding Based on CT Scanning Technique of the Full-Diameter Core[J]. Petroleum Geology and Oilfield Development in Daqing, 2019, 38(2):81-86.
[4] Dvorkin J, Walls J, Tutuncu A, et al. Rock Property Determination Using Digital Rock Physics[C]//Geophysics of the 21st Century:The Leap into the Future, SEG Technical Program Expanded Abstracts 2003. Moscow:European Association of Geoscientists & Engineers, 2003:cp-38-00040.
[5] 李易霖,张云峰,丛琳,等. X-CT扫描成像技术在致密砂岩微观孔隙结构表征中的应用:以大安油田扶余油层为例[J]. 吉林大学学报(地球科学版), 2016, 46(2):379-387. Li Yilin, Zhang Yunfeng, Cong Lin, et al. Application of X-CT Scanning Technique in the Characterization of Micro Pore Structure of Tight Sandstone Reservoir:An Example from Fuyu Oil Layer in Daan Oilfield[J]. Journal of Jilin University (Earth Science Edition), 2016, 46(2):379-387.
[6] 赵玲,石雪,夏慧芬. 数字岩心孔隙网络模型的构建方法[J]. 科学技术与工程, 2018, 18(26):32-38. Zhao Ling, Shi Xue, Xia Huifen. Construction Method of Digital Core Pore Network Model[J]. Science Technology and Engineering, 2018, 18(26):32-38.
[7] Adler P M, Jacquin C G, Thovert J F. The Formation Factor of Reconstructed Porous Media[J]. Water Resources Research, 1992, 28(6):1571-1576.
[8] Hazlett R D. Statistical Characterization and Stochastic Modeling of Pore Networks in Relation to Fluid Flow[J]. Mathematical Geology, 1992, 29(6):801-822.
[9] Bryant S, Blunt M. Prediction of Relative Permeability in Simple Porous Media[J]. Physical Review:A:Atomic, Molecular, and Optical Physics, 1992, 46(4):2004-2011.
[10] 姚军,王晨晨,杨永飞,等. 碳酸盐岩双孔隙网络模型的构建方法和微观渗流模拟研究[J]. 中国科学:物理学力学天文学, 2013, 43(7):896-902. Yao Jun, Wang Chenchen, Yang Yongfei, et al. The Construction Method and Microscopic Flow Simulation of Carbonate Dual Pore Network Model[J]. Scientia Sinica:Physica,Mechanica & Astronomica, 2013, 43(7):896-902.
[11] 赵明,郁伯铭. 数字岩心孔隙结构的分形表征及渗透率预测[J]. 重庆大学学报, 2011, 34(4):88-94. Zhao Ming, Yu Boming. The Fractal Characterization of Pore Structure for Some Numerical Rocks and Prediction of Permeabilities[J]. Journal of Chongqing University, 2011, 34(4):88-94.
[12] Sun H, Yao J, Cao Y, et al. Characterization of Gas Transport Behaviors in Shale Gas and Tight Gas Reservoirs by Digital Rock Analysis[J]. International Journal of Heat and Mass Transfer, 2017, 104:227-239.
[13] 林承焰,王杨,杨山,等. 基于CT的数字岩心三维建模[J]. 吉林大学学报(地球科学版),2018, 48(1):307-317. Lin Chengyan, Wang Yang, Yang Shan, et al. 3D Modeling of Digital Core Based on X-Ray Computed Tomography[J]. Journal of Jilin University (Earth Science Edition), 2018, 48(1):307-317.
[14] Golparvar A, Zhou Y, Wu K, et al. A Comprehensive Review of Pore Scale Modeling Methodologies for Multiphase Flow in Porous Media[J]. Advances in Geo-Energy Research, 2018, 2(4):418-440.
[15] Dong H, Blunt M J. Pore-Network Extraction from Micro-Computerized-Tomography Images[J]. Physical Review E, 2009, 80(3):036307.
[16] Mandelbrot B B. The Fractal Geometry of Nature[M]. New York:WH Freeman, 1983.
[17] Yu B, Cheng P. A Fractal Permeability Model for Bi-dispersed Porous Media[J]. International Journal of Heat and Mass Transfer, 2002, 45(14):2983-2993.
[18] Yu B. Fractal Character for Tortuous Streamtubes in Porous Media[J]. Chinese Physics Letters, 2005, 22(1):158.
[19] Wu J, Yu B. A Fractal Resistance Model for Flow Through Porous Media[J]. International Journal of Heat and Mass Transfer, 2007, 50(19/20):3925-3932.
[20] Wang F, Jiao L, Lian P, et al. Apparent Gas Permeability, Intrinsic Permeability and Liquid Permeability of Fractal Porous Media:Carbonate Rock Study with Experiments and Mathematical Modelling[J]. Journal of Petroleum Science and Engineering, 2019, 173:1304-1315.
[21] 尹贤龙. 基于图像分形维数估计的最小盒计数法的研究[J]. 电气应用, 2006,25(9):93-96. Yin Xianlong. Research of Minimum Box-Counting Method Based on Image Fractal Dimension Estimation[J]. Elerctrotechnical Application, 2006, 25(9):93-96.
[22] 曹俊贤,宋春林. 分形维数的计算及改进[J]. 信息技术与信息化, 2017(10):19-23. Cao Junxian, Song Chunlin. Calculation and Improvement of the Fractal Dimension[J]. Information Technology and Informatization, 2017(10):19-23.
[23] 王聪乐. 砂岩油藏孔隙结构分形表征与渗透率模型研究[D]. 北京:中国石油大学(北京), 2018. Wang Congle. Reasearch on Fractal Characterization of Pore Structure and Permeability Model in Sandstone Reservoirs[D]. Beijing:China University of Petroleum (Beijing), 2018.
[24] Al-Raoush R I, Madhoun I T. TORT3D:A MATLAB Code to Compute Geometric Tortuosity from 3D Images of Unconsolidated Porous Media[J]. Powder Technology, 2017, 320:99-107.
[25] Imperial Colleage. Micro-CT Images and Networks[DB/OL].[2019-05-23]. http://www.imperial.ac.uk/earth-science/research/research-groups/per-m/research/pore-scale-modelling/micro-ct-images-and-networks/.

相关文章 15

[1]	危润初, 蒋维剑, 欧阳琦, 盛丰, 谌宏伟, 黄荷, 帅焕. 基于图像分析的岩土颗粒介质逾渗规律 [J]. 吉林大学学报(地球科学版), 2026, 56(2): 625-634.
[2]	王梓麟, 时婧玥, 杨英, 徐栋, 曾泉树, 张益畅. 深层煤岩孔隙结构表征及压裂缝导流能力影响因素[J]. 吉林大学学报(地球科学版), 2025, 55(4): 1061-1076.
[3]	路研, 刘宗宾, 廖新武, 李超, 王亚. 低渗透砂岩油藏水驱渗流特征[J]. 吉林大学学报(地球科学版), 2025, 55(4): 1077-1090.
[4]	王福刚, 管小桐, 何庆成, 程辉, 杨国华, 程中乐, 王耀辉. 考虑边界层流体黏度变化的黏性土低速非达西渗流数学模型[J]. 吉林大学学报(地球科学版), 2025, 55(3): 893-905.
[5]	高波, 潘哲君, 刘连杰, 李玲玲, 洪淑新, 潘会芳, 张波. 松辽盆地徐家围子断陷沙河子组砂砾岩储层有效性综合评价[J]. 吉林大学学报(地球科学版), 2025, 55(1): 31-45.
[6]	袁益龙, 唐佳伟, 李鹏, 何瑞敏, 郭强, 钟承昊. 热-力耦合作用下花岗岩粗糙裂隙渗透率演化规律[J]. 吉林大学学报(地球科学版), 2025, 55(1): 179-187.
[7]	王亚, 刘宗宾, 马奎前, 路研, 刘超. 基于LDA协同SSOM算法的低渗透砂岩孔隙结构评价[J]. 吉林大学学报(地球科学版), 2025, 55(1): 298-311.
[8]	刘宗宾, 李超, 路研, 王亚, 黄建廷. 基于孔隙结构表征的低渗透砂岩流体赋存特征及渗透率评价[J]. 吉林大学学报(地球科学版), 2024, 54(4): 1124-1136.
[9]	谢通, 陈威, 潘诗洋, 石万忠, 王亿, 张焱林, 段轲, 任志军. 鄂西地区二叠系大隆组含气页岩岩相类型及储层特征[J]. 吉林大学学报(地球科学版), 2024, 54(4): 1154-1176.
[10]	刘硕, 王飞, 于瑞, 高建星, 师昊, 朱玉双. 致密砂岩储层微观孔喉结构及其分形特征[J]. 吉林大学学报(地球科学版), 2024, 54(1): 96-107.
[11]	崔中良, 周家喜, 罗开. 赣南兴国—宁都萤石成矿带分形结构及成矿与找矿前景#br#[J]. 吉林大学学报(地球科学版), 2024, 54(1): 108-124.
[12]	张文, 蓝升, 马文良, 王佳. 新疆油页岩升温过程中孔隙结构演化特征[J]. 吉林大学学报(地球科学版), 2023, 53(6): 1689-1705.
[13]	熊安亮, 程国峰, 李东涛, 丁维盼, 刘宇羲, 陈刚, 杨磊, 袁耀利, 朱玉双, 刘林玉. 超低渗储层微观孔隙结构及剩余油分布特征——以吴起油田白豹地区长4+5为例[J]. 吉林大学学报(地球科学版), 2023, 53(5): 1338-1351.
[14]	赵越, 李磊, 司运航, 王会敏. 浅层页岩气储层孔隙分形特征及控制因素——以云南昭通地区龙马溪组为例[J]. 吉林大学学报(地球科学版), 2022, 52(6): 1813-1829.
[15]	侯贤沐, 王付勇, 宰芸, 廉培庆. 基于机器学习和测井数据的碳酸盐岩孔隙度与渗透率预测[J]. 吉林大学学报(地球科学版), 2022, 52(2): 644-653.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed