油气田开发

利用数字岩心抽象孔隙模型计算孔隙体积压缩系数

  • 隋微波 ,
  • 权子涵 ,
  • 侯亚南 ,
  • 程浩然
展开
  • 1. 中国石油大学(北京)油气资源与探测国家重点实验室,北京 102249;
    2. 中国石油大学(北京)石油工程学院,北京 102249;
    3. 深圳清华大学研究院,广东深圳 518057;
    4. 清能艾科(深圳)能源技术有限公司,广东深圳 518057
隋微波(1981-),女,黑龙江大庆人,博士,中国石油大学(北京)石油工程学院副教授,主要从事数字岩心、微观渗流和智能完井方面的研究工作。地址:北京市昌平区府学路18号石油工程学院,邮政编码:102249。E-mail: suiweibo@cup.edu.cn

收稿日期: 2019-07-03

  网络出版日期: 2020-05-19

基金资助

国家自然科学基金项目“应力敏感条件下的数字岩心微观渗流分析方法研究”(51474224); 深圳市海外高层次人才资金(KQTD2017033114582189); 深圳市科学技术创新委员会项目(JCYJ20170817152743178)

Estimating pore volume compressibility by spheroidal pore modeling of digital rocks

  • SUI Weibo ,
  • QUAN Zihan ,
  • HOU Yanan ,
  • CHENG Haoran
Expand
  • 1. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China;
    2. College of Petroleum Engineering, China University of Petroleum, Beijing 102249, China;
    3. Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China;
    4. ICORE GROUP, Shenzhen 518057, China

Received date: 2019-07-03

  Online published: 2020-05-19

摘要

将真实孔隙简化抽象为长椭球孔、扁椭球孔和球形孔3种类型,基于细观力学理论建立数字岩心的三维抽象孔隙模型;结合Eshelby等效介质理论考虑不同类型孔隙微观结构变形的本构关系,在单孔、多孔和混合孔隙弹性变形条件下研究孔隙结构特征对孔隙体积压缩系数的影响。研究表明,数字岩心的孔隙体积压缩系数与孔隙度、孔隙纵横比以及不同类型孔隙体积占比有关:①长椭球孔孔隙压缩系数与孔隙纵横比正相关,扁椭球孔孔隙压缩系数与孔隙纵横比负相关。②孔隙纵横比满足高斯分布且纵横比均值相同,长椭球孔、扁椭球孔纵横比分布越集中孔隙压缩系数越大,相同应力条件下变形量越大。③孔隙压缩系数随孔隙度增大而增大。④孔隙度一定,扁椭球孔、球形孔越多岩石越容易发生变形,孔隙压缩系数越大;长椭球孔越多岩石越不容易变形,孔隙压缩系数越小。通过10种典型数字岩心样品孔隙体积压缩系数计算结果检验,数字岩心真实孔隙体积压缩系数解析计算方法可用于数字岩心样品的孔隙体积压缩系数计算。图12表1参23

本文引用格式

隋微波 , 权子涵 , 侯亚南 , 程浩然 . 利用数字岩心抽象孔隙模型计算孔隙体积压缩系数[J]. 石油勘探与开发, 2020 , 47(3) : 564 -572 . DOI: 10.11698/PED.2020.03.12

Abstract

The real pores in digital cores were simplified into three abstractive types, including prolate ellipsoids, oblate ellipsoids and spheroids. The three-dimensional elliptical-pore model of digital core was established based on mesoscopic mechanical theory. The constitutive relationship of different types of pore microstructure deformation was studied with Eshelby equivalent medium theory, and the effects of pore microstructure on pore volume compressibility under elastic deformation conditions of one type, multiple types and mixed types of pores were investigated. The results showed that the pore volume compressibility coefficient of digital core is closely related with porosity, pore aspect ratio and volumetric proportions of different types of pores. (1) The compressibility coefficient of prolate ellipsoidal pore is positively correlated with the pore aspect ratio, while that of oblate ellipsoidal pore is negatively correlated with the pore aspect ratio. (2) At the same average value of pore aspect ratio satisfying Gaussian distribution, the more concentrated the range of pore aspect ratio, the higher the compressibility coefficient of both prolate and oblate ellipsoidal pores will be, and the larger the deformation under the same stress condition. (3) The pore compressibility coefficient increases with porosity. (4) At a constant porosity value, the higher the proportion of oblate ellipsoidal and spherical pores in the rock, the more easier for the rock to deform, and the higher the compressibility coefficient of the rock is, while the higher the proportion of prolate ellipsoidal pores in the rock, the more difficult it is for rock to deform, and the lower the compressibility coefficient of the rock is. By calculating pore compressibility coefficient of ten classical digital rock samples, the presented analytical elliptical-pore model based on real pore structure of digital rocks can be applied to calculation of pore volume compressibility coefficient of digital rock sample.

参考文献

[1] TORQUATO S.Random heterogeneous material: Microstructure and macroscopic properties[M]. New York: Springer, 2002: 1-3.
[2] ARNS C, KNACKSTEDT M, PINCZEWSKI W.Computation of linear elastic properties from microtomographic images: Methodology and agreement between theory and experiment[J]. Geophysics, 2002, 67(5): 1396-1405.
[3] ZIMMERMAN R.The effect of pore structure on the pore and bulk compressibilites of consolidated sandstones[D]. Berkeley, USA: University of California, 1979: 36.
[4] 姚军, 孙海, 李爱芬, 等. 现代油气渗流力学体系及其发展趋势[J]. 科学通报, 2018, 63(4): 425-451.
YAO Jun, SUN Hai, LI Aifen, et al.Modern system of multiphase flow in porous media and its development trend[J]. Chinese Science Bulletin, 2018, 63(4): 425-451.
[5] 林承焰, 吴玉其, 任丽华, 等. 数字岩心建模方法研究现状及展望[J]. 地球物理学进展, 2018, 33(2): 679-689.
LIN Chengyan, WU Yuqi, REN Lihua, et al.Review of digital core modeling methods[J]. Progress in Geophysics, 2018, 33(2): 679-689.
[6] ANDRA H, COMBARET N, DVORKIN J, et al.Digital rock physics benchmarks—Part Ⅰ: Imaging and segmentation[J]. Computers & Geosciences, 2013, 50(1): 25-32.
[7] HAN J, COMBARET N, DVORKIN J, et al.Digital rock physics benchmarks—Part Ⅱ: Computing effective properties[J]. Computers & Geosciences, 2013, 50(1): 33-43.
[8] WALLS J, ARMBRUSTER M.Shale reservoir evaluation improved by dual energy X-ray CT imaging[J]. Journal of Petroleum Technology, 2012, 64(11): 28-32.
[9] SUN H, VEGA S, TAO G.Analysis of heterogeneity and permeability anisotropy in carbonate rock samples using digital rock physics[J]. Journal of Petroleum Science and Engineering, 2017, 156(7): 419-429.
[10] 李俊键, 刘洋, 高亚军, 等. 微观孔喉结构非均质性对剩余油分布形态的影响[J]. 石油勘探与开发, 2018, 45(6): 1043-1052.
LI Junjian, LIU Yang, GAO Yajun, et al.Effects of microscopic pore structure heterogeneity on the distribution and morphology of remaining oil[J]. Petroleum Exploration and Development, 2018, 45(6): 1043-1052.
[11] 曹耐, 雷刚. 致密储集层加压-卸压过程应力敏感性[J]. 石油勘探与开发, 2019, 46(1): 132-138.
CAO Nai, LEI Gang.Stress sensitivity of tight reservoir during pressure loading and unloading process[J]. Petroleum Exploration and Development, 2019, 46(1): 132-138.
[12] DAKE L.Fundamentals of reservoir engineering[M]. Amsterdam: Elsevier, 1978: 71-76.
[13] KAMAL M.Transient well testing[M]. Richardson, TX: Society of Petroleum Engineers, 2009: 8-9
[14] SADOWSKY M, STERNBERG E, CHICAGO H.Stress concentration around an ellipsoidal cavity in an infinite body under arbitrary plane stress perpendicular to the axis of revolution of cavity[J]. Journal of Applied Mechanics, 1947, 14(3): 191-201.
[15] SADOWSKY M, STERNBERG E.Stress concentration around a triaxial ellipsoidal cavity[J]. Journal of Applied Mechanics, 1949, 16(2): 149-157.
[16] MAVKO G, MUKERJI T, DVORKIN J.The rock physics handbook: Tools for seismic analysis of porous media[M]. Cambridge: Cambridge University Press, 2009: 58-59.
[17] ESHELBY J D.The determination of the elastic field of an ellipsoidal inclusion, and related problems[J]. Proceedings of the Royal Society of London, 1957, 241(1226): 376-396.
[18] HILL R.A self-consistent mechanics of composite materials[J]. Journal of the Mechanics and Physics of Solids, 1965, 13(4): 213-222.
[19] BUDIANSKY B.On the elastic moduli of some heterogeneous materials[J]. Journal of the Mechanics and Physics of Solids, 1965, 13(4): 223-227.
[20] WU T.The effect of inclusion shape on the elastic moduli of a two-phase material[J]. International Journal of Solids and Structures, 1966, 2(1): 1-8.
[21] 张研, 韩林. 细观力学基础[M]. 北京: 科学出版社, 2014: 92.
ZHANG Yan, HAN Lin.Foundation of mesomechanics[M]. Beijing: China Science Publishing & Media Ltd, 2014: 92.
[22] UT AUSTIN. Digital rock portal[EB/OL]. (2018-01-18)[2019-11-25]. https://edx.netl.doe.gov/dataset/ digital-rock-portal.
[23] DONG H.Micro-CT imaging and pore network extraction[D]. London: Imperial College, 2007.
文章导航

/