基于CT的数字岩心三维建模

doi:10.13278/j.cnki.jjuese.20160305

吉林大学学报(地球科学版) ›› 2018, Vol. 48 ›› Issue (1): 307-317.doi: 10.13278/j.cnki.jjuese.20160305

基于CT的数字岩心三维建模

林承焰^1,2, 王杨^1,2, 杨山³, 任丽华^1,2, 由春梅⁴, 吴松涛⁵, 吴玉其^1,2, 张依旻^1,2

1. 中国石油大学(华东)地球科学与技术学院, 山东青岛 266580;
2. 山东省油藏地质重点实验室, 山东青岛 266580;
3. 中国石油西南油气田分公司勘探开发研究院, 成都 610051;
4. 大庆油田有限责任公司勘探开发研究院, 黑龙江大庆 163000;
5. 中石油勘探开发研究院, 北京 100083

收稿日期:2016-10-20 出版日期:2018-01-26 发布日期:2018-01-26
作者简介:林承焰(1963-),男,教授,博士生导师,主要从事储层地质学与油藏描述的教学与科研工作,E-mail:lincy@upc.edu.cn
基金资助:
“十三五”国家科技重大专项（2016ZX05054012）

3D Modeling of Digital Core Based on X-ray Computed Tomography

Lin Chengyan^1,2, Wang Yang^1,2, Yang Shan³, Ren Lihua^1,2, You Chunmei⁴, Wu Songtao⁵, Wu Yuqi^1,2, Zhang Yimin^1,2

1. School of Geosciences, China University of Petroleum(East China), Qingdao 266580, Shandong, China;
2. Reservoir Geology Key Laboratory of Shandong Province, Qingdao 266580, Shandong, China;
3. Exploration and Development Research Institute of Southwest Oil & Gas Field Company, PetroChina, Chengdu 610051, China;
4. Research Institute of Exploration and Development of Daqing Oilfield Company Ltd, Daqing 163000, Heilongjiang, China;
5. Research Institute of Petroleum Exploration and Development, Beijing 100083, China

Received:2016-10-20 Online:2018-01-26 Published:2018-01-26
Supported by:
Supported by National Science and Technology Major Project(2016ZX05054012)

摘要/Abstract

摘要： 为研究储层微观孔隙结构和建立微观渗流模型，本文通过对东营凹陷沙三中亚段H152井区的典型低渗透储层岩样进行CT（computed tomography）扫描及图像处理，建立了微观尺度的数字岩心模型；继而经过对该模型进行分析和计算，提取了储层孔喉网络模型，在三维空间上直观、清晰地显示了不同尺度的孔隙及喉道的形态、大小和分布；最后通过对孔隙结构特征、孔隙度、渗透率和压降等动静态参数的分析和计算，建立了储层岩样的微观渗流模型。根据算法对比和参数分析结果认为：与传统中值滤波相比，非局部均值滤波算法可在相似性比较的基础上进行滤波处理，从而提高模型的准确性；基于CT的数字岩心建模可为地质研究提供可靠的数字模型；根据近似等压面假设的微观渗流数值模拟分析了流体渗流特征，为揭示低渗透储层流体渗流规律提供了一种新的途径。

关键词: 数字岩心, 孔隙结构, 孔喉网络模型, 建模, 微观渗流, CT, 东营凹陷

Abstract: In order to study the micropore structure of petroleum reservoir and develop 3D micro percolation model, CT(computed tomography)scanning and image processing of typical low- permeability reservoirs were carried out in the H152 area of the middle section of Shahejie Formation in Dongying depression, and a micro digital core model was established. Then, through the analysis and calculation of the model, the reservoir pore throat network model attributions of different scales of pores and throats were displayed intuitively and clearly in three-dimensional space. Based on the analysis and calculation of dynamic and static parameters such as pore structure, porosity, permeability and pressure drop, a micro percolation model of reservoir samples was established. According to the comparison of algorithm and analysis of the parameters, it is concluded that:Compared with the traditional median filter, the non-local-means filter algorithm that based on the comparison of similarity and the accuracy of the model is improved; The CT-based digital core can provide a reliable digital model for geological research; Based on the assumption of isobaric surface, the numerical simulation of percolation was carried out, and the characteristics of fluid transport were analyzed. The numerical simulation of percolation provides a new way to reveal the transport law of low permeability reservoir.

Key words: digital core, pore structure, pore-network model, modeling, micro percolation, computed tomography, Dongying depression

中图分类号:

TE122.2

林承焰, 王杨, 杨山, 任丽华, 由春梅, 吴松涛, 吴玉其, 张依旻. 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, Ren Lihua, You Chunmei, Wu Songtao, Wu Yuqi, Zhang Yimin. 3D Modeling of Digital Core Based on X-ray Computed Tomography[J]. Journal of Jilin University(Earth Science Edition), 2018, 48(1): 307-317.

参考文献

[1] 刘学锋. 基于数字岩心的岩石声电特性微观数值模拟研究[D].青岛:中国石油大学(华东),2010. Liu Xuefeng. Numerical Simulation of Elastic and Electrical Properties of Rock Based on Digital Cores[D]. Qingdao: China University of Petroleum (East China), 2010.
[2] Rosenberg E, Lynch J, Guéroult P, et al. High Re-solution 3D Reconstructions of Rocks and Composites[J]. Oil & Gas Science & Technology, 1999, 54(4):497-511.
[3] Arns C. H. The Influence of Morphology on Physical Properties of Reservoir Rocks[D]. Sydney: The University of New South Wales, 2002.
[4] 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 on Digital Core Technology[J]. Petroleum Geology and Recovery Efficiency, 2005,12(6):52-54.
[5] 谢一婷. 基于数字岩心技术的低渗油藏渗流机理及合理井距研究[D].成都:西南石油大学,2013. Xie Yiting. The Research of Seepage Flow in Low Permeability Reservoir and the Reasonable Well Spacing Based on Digital Core Technology[D]. Chengdu: Southwest Petroleum University, 2013.
[6] Joshi M. A Class of Stochastic Models for Porous Media[D]. Lawrence Kansas: University of Kansas, 1974.
[7] Hazlett R D. Statistical Characterization and Stochastic Modeling of Pore Networks in Relation to Fluid Flow[J]. Mathematical Geosciences, 1997, 29(6):801-822.
[8] Bakke S, Ren P E. 3-D Pore-Scale Modelling of Sandstones and Flow Simulations in the Pore Networks[J]. Spe Journal, 1997, 2(2):136-149.
[9] Arns C H, Averdunk H, Bauget F, et al. Digital Core Laboratory: Reservoir Core Analysis from 3D Images[C]// The 6th North America Rock Mechanics Symposium (NARMS). Houston: American Rock Mechanics Association, 2004: ARMA-04-498.
[10] 刘洋. 过程法构建数字岩心技术[D].青岛:中国石油大学(华东),2007. Liu Yang. Construction of Digital Core by Process-Based Simulation Method[D]. Qingdao: China University of Petroleum (East China), 2007.
[11] Youssef S, Rosenberg E, Gland N F, et al. High Resolution CT And Pore-Network Models To Assess Petrophysical Properties Of Homogeneous And Heterogeneous Carbonates[C]// Reservoir Characterization and Simulation Conference. Abu Dhabi: Society of Petroleum Engineers. doi:10.2118/111427-MS.
[12] Ryazanov A V, Sorbie K S, Dijke M I J V. Structure of Residual Oil as a Function of Wettability Using Pore-Network Modelling[J]. Advances in Water Resources, 2014, 63(2):11-21.
[13] 刘向君,朱洪林,梁利喜. 基于微CT技术的砂岩数字岩石物理实验[J]. 地球物理学报, 2014, 57(4):1133-1140. Liu Xiangjun, Zhu Honglin, Liang Lixi. Digital Rock Physics of Sandstone Based on Micro-CT Technology[J]. Chinese Journal of Geophysics, 2014, 57(4): 1133-1140.
[14] 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 Oil Filed[J]. Journal of Jilin University (Earth Science Edition), 2016, 46(2): 379-387.
[15] Pan C, Hilpert M, Miller C T. Lattice-Boltzmann Simulation of Two-Phase Flow in Porous Media[J]. Water Resources Research, 2004, 40(1):62-74.
[16] 屈乐. 基于低渗透储层的三维数字岩心建模及应用[D].西安:西北大学,2014. Qu Le. Modeling and Application of Three-Dimensional Digital Cores of Low Permeability Reservoir[D]. Xi'an: Northwestern University, 2014.
[17] 刘学锋,张伟伟,孙建孟. 三维数字岩心建模方法综述[J]. 地球物理学进展,2013,28(6):3066-3072. Liu Xuefeng, Zhang Weiwei, Sun Jianmeng. Methods of Constructing 3-D Digital Cores: A Review[J]. Progress in Geophysical, 2013,28(6):3066-3072.
[18] 王晨晨,姚军,杨永飞,等. 基于CT扫描法构建数字岩心的分辨率选取研究[J]. 科学技术与工程,2013,13(4):1049-1052. Wang Chenchen, Yao Jun, Yang Yongfei, et al. The Research of Selected Resolution Based on CT Scanning Method for Constructing Digital Core[J]. Science, Technology and Engineering, 2013,13(4):1049-1052.
[19] 张爽,周慧鑫,牛肖雪,等. 基于非局部均值滤波与时域高通滤波的非均匀性校正算法[J]. 光子学报,2014,43(1):147-150. Zhang Shuang, Zhou Huixin, Niu Xiaoxue, et al. Temporal High-Pass Filter Nonunifority Correction Algorithm Based on Non-Local Means Filter for Infrared Focal Plane Array[J]. Acta Photonica Sinica, 2014, 43(1): 147-150.
[20] 杨山. 基于驱替实验及数字岩心的微观剩余油研究[D].青岛:中国石油大学(华东),2015. Yang Shan.The Research of Microscopic Remaining Oil on the Basis of Displacement Experiment and Digital Core[D]. Qingdao: China University of Petroleum (East China), 2015.
[21] 任奕明. 微观水驱油网络模拟研究[D].成都:西南石油大学,2014. Ren Yiming. The Network Simulation of Microscopic Water Flooding[D]. Chengdu: Southwest Petroleum University, 2014.
[22] Mohammadmoradi P, Kantzas A. Pore-Scale Perme-ability Calculation Using CFD and DSMC Techniques[J]. Journal of Petroleum Science & Engineering, 2016, 146:515-525.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

基于CT的数字岩心三维建模

3D Modeling of Digital Core Based on X-ray Computed Tomography

PDF (PC)

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 10

[1]	纪泽雨, 唐华风, 李本仙. 无机天然氢类型、成因及我国生氢潜力 [J]. 吉林大学学报(地球科学版), 2026, 56(2): 413-434.
[2]	汪俊, 王哲, 李书华, 高红芳, 黄永健. 南海管事平顶海山密度结构及其构造意义[J]. 吉林大学学报(地球科学版), 2025, 55(5): 1691-1701.
[3]	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.
[4]	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.
[5]	曹成刚, 谭俊, 贾玉山, 方永坤, 石凯章, 黄碧云, . 沙丘覆盖区深部三维可视化找矿预测应用——以祁漫塔格那陵郭勒河西铁多金属矿为例 [J]. 吉林大学学报(地球科学版), 2025, 55(2): 417-437.
[6]	谭晓辉, 黄灏, 胡荣光, 邓奕球, 曾经文, 王秀娟. 东莞市水乡地区农业土壤重金属污染特征及风险评价[J]. 吉林大学学报(地球科学版), 2025, 55(2): 587-600.
[7]	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.
[8]	魏虹羽, 李世超, 王伟安. 地球动力学数值模拟算法的应用现状与展望[J]. 吉林大学学报(地球科学版), 2025, 55(1): 98-124.
[9]	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.
[10]	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.
[11]	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.
[12]	赵忠海, 崔晓梦, 孙景贵, 陈俊, 乔锴, 梁杉杉, Manirambona Alain Jospin . 基于三维地质-地球物理建模的深部成矿预测——以黑河地区永新金矿床为例 [J]. 吉林大学学报(地球科学版), 2024, 54(2): 498-515.
[13]	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.
[14]	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.
[15]	闫海洋, 周辉, 刘海波, 徐朝红, 孙赞东, 刘昭, 罗敏学. 基于EZW算法的叠前地震数据分频压缩技术[J]. 吉林大学学报(地球科学版), 2023, 53(4): 1238-1238.