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

• 地球探测与信息技术 • 上一篇    下一篇

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. 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 Chengyan1,2, Wang Yang1,2, Yang Shan3, Ren Lihua1,2, You Chunmei4, Wu Songtao5, Wu Yuqi1,2, Zhang Yimin1,2   

  1. 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)

PDF (PC)

644

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
[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.
[1] 林敉若, 操应长, 葸克来, 王健, 陈洪, 吴俊军. 阜康凹陷东部斜坡带二叠系储层特征及控制因素[J]. 吉林大学学报(地球科学版), 2018, 48(4): 991-1007.
[2] 赵谦平, 张丽霞, 尹锦涛, 俞雨溪, 姜呈馥, 王晖, 高潮. 含粉砂质层页岩储层孔隙结构和物性特征:以张家滩陆相页岩为例[J]. 吉林大学学报(地球科学版), 2018, 48(4): 1018-1029.
[3] 郑国磊, 徐新学, 李世斌, 袁航, 马为, 叶青. 天津市重力数据反演解释[J]. 吉林大学学报(地球科学版), 2018, 48(4): 1221-1230.
[4] 贾艳聪, 操应长, 林畅松, 王健. 东营凹陷博兴洼陷沙四上亚段滩坝优质储层形成机理与分布特征[J]. 吉林大学学报(地球科学版), 2018, 48(3): 652-664.
[5] 冯小龙, 敖卫华, 唐玄. 陆相页岩气储层孔隙发育特征及其主控因素分析:以鄂尔多斯盆地长7段为例[J]. 吉林大学学报(地球科学版), 2018, 48(3): 678-692.
[6] 李志明, 张隽, 鲍云杰, 曹婷婷, 徐二社, 芮晓庆, 陈红宇, 杨琦, 张庆珍. 沾化凹陷渤南洼陷沙一段湖相富有机质烃源岩岩石学与孔隙结构特征:以罗63井和义21井取心段为例[J]. 吉林大学学报(地球科学版), 2018, 48(1): 39-52.
[7] 崔利凯, 孙建孟, 闫伟超, 高银山, 王洪君, 宋丽媛. 基于多分辨率图像融合的多尺度多组分数字岩心构建[J]. 吉林大学学报(地球科学版), 2017, 47(6): 1904-1912.
[8] 张宝一, 杨莉, 陈笑扬, 邓浩, 毛先成. 基于图切地质剖面的区域成矿地质体三维建模与资源评价——以桂西南地区锰矿为例[J]. 吉林大学学报(地球科学版), 2017, 47(3): 933-948.
[9] 吴志春, 郭福生, 林子瑜, 侯曼青, 罗建群. 三维地质建模中的多源数据融合技术与方法[J]. 吉林大学学报(地球科学版), 2016, 46(6): 1895-1913.
[10] 张雨晴, 王晖, 范廷恩, 宋来明, 聂妍, 梁旭, 陈飞. 花岗岩潜山储层裂缝建模表征方法——以渤海花岗岩潜山A油田为例[J]. 吉林大学学报(地球科学版), 2016, 46(5): 1312-1320.
[11] 白永强, 刘美, 杨春梅, 姜振学. 基于AFM表征的页岩孔隙特征及其与解析气量关系[J]. 吉林大学学报(地球科学版), 2016, 46(5): 1332-1341.
[12] 朱传华, 王伟锋, 王青振, 李玉坤. 非均质储层三维构造应力场模拟方法[J]. 吉林大学学报(地球科学版), 2016, 46(5): 1580-1588.
[13] 李易霖, 张云峰, 丛琳, 谢舟, 闫明, 田肖雄. 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.
[14] 郑香伟, 吴健, 何胜林, 胡向阳, 梁玉楠. 基于流动单元的砂砾岩储层渗透率测井精细评价[J]. 吉林大学学报(地球科学版), 2016, 46(1): 286-294.
[15] 赵利, 李理, 董大伟. 基于小波变换的盆地沉积-构造波动分析[J]. 吉林大学学报(地球科学版), 2015, 45(4): 1227-1236.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(地球科学版)》编辑部
地址：长春市西民主大街938号(130026)　电话：+86-431-88502374；13756165364　E-mail: xuebao1956@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发