Effects of Cementation on Elastic Property and Permeability of Reservoir Rocks
-
摘要: 为研究岩石颗粒胶结方式对储层岩石弹性和渗流性质的影响，采用过程模拟法构建了三维数字岩心，在此基础上，分别利用有限元方法和格子玻尔兹曼方法研究了胶结物均匀生长、沿孔隙生长和沿喉道生长3种胶结方式对岩石弹性和渗流特性的影响规律.结果表明：岩石颗粒胶结方式会影响岩石刚性和孔隙连通性，引起岩石弹性模量和渗透率的变化.在相同孔隙度下，胶结物沿喉道生长形成的岩石抗压性最强，渗透率最小；沿孔隙生长形成的岩石抗压性最弱，渗透率最大.3种胶结方式下，岩石弹性模量随着胶结物含量增加而增大，变化率近似相等；岩石渗透率随着胶结物含量的增加而减小，岩石渗透性对颗粒胶结方式的变化更敏感.Abstract: In order to investigate the efects of cementation on elastic properties and permeability of reservoir rocks, a 3D digital model of core was constructed. Then this model was simulated using the process-based method and finite element lattice Boltzmann method. The results show that cementation influences the rock stiffness and pore connectivity, controlling elastic modulus and rock permeability, respectively. Given same porosity, rocks with cement occurring in the pore throats have high elastic modulus and low permeability; whereas rocks with cement precipitating within pores have low elastic modulus and high permeability. Among the simulated three cementation scenarios, the rock elastic modulus increases with increasing amount of cement, and there is a linear relationship between them, Rock permeability, however, deceases with increasing amount of cement, because permeability is more sensitive to where cements precipitate than rock elastic parameters.
-
图 5 不同胶结方式所构建三维数字岩心的横截面
a.胶结方式Ⅰ；b.胶结方式Ⅱ；c.胶结方式Ⅲ
Fig. 5. Cross-section of digital rocks with different cementation modes
表 1 数字岩心模拟参数
Table 1. The parameter of digital rocks
模拟参数 数值 孔隙度 0.350 0.300 0.250 0.200 0.150 0.100 0.050 压实因子 0.015 0.015 0.015 0.015 0.015 0.015 0.015 成岩因子 0.000 0.038 0.079 0.126 0.182 0.252 0.360 
下载: 导出CSV
-
Chen, H., Chen, S., Mathaeus, W. H., 1992. Recovery of the Navier-Stokes Equation Using a Lattice Gas Boltzmann Method. Physical Review A, 45(8): 5339-5342. doi: 10.1103/PhysRevA.45.R5339 Ding, X. G., Ye, S. Y., Gao, Z. J., 2005. Development and Applications of Grain Size Analysis Technique. Global Geology, 24(2) : 203-207 (in Chinese with English abstract). Garboczi, E. J., 1998. Finite Element and Finite Difference Programs for Computing the Linear Electric and Elastic Properties of Digital Images of Random Materials. NIST Internal Report 6269, Gaithersburg. Ji, C. J., Yi, H. S., Xia, G. Q., 2012. An Image-Analysis. Technique to Measure Grain-Size V ariation in Thin Sections of Clastic Sediments. Geological Science and Technology In formation, 31(3): 122-127 (in Chinese with English abstract). Liu, X. F., Sun, J. M., Wang, H. T., 2009a. Reconstruction of 3-D Digital Cores Using a Hybrid Method. A pplied Geophysics, 6(2): 105-112. doi: 10.1007/s11770-009-0017-y Liu, X. F., Sun, J. M., Wang, H. T., 2009b. Numerical Simulation of Rock Electrical Properties Based on Digital Cores. Applied Geophysics, 6(l): 1- 7. doi: 10.1007/s11770-009-0001-6 Madadi, M., Jones, A. C., Arns, C. H., et al., 2009. 3D Imaging and Simulation of Elastic Properties of Porous Materials. Computing in Science and Engineering, ll(4): 65-73. doi: 10.1109/MCSE.2009.110 Okabe, H., Blunt, M. J., 2004. Prediction of Permeability for Porous Media Reconstructed Using Multiple-Point Statistics. Physical Review E, 70(6): 066135. doi: 10.1103/PhysRevE.70.066135 Øren, P. E., Bakke, S., 2002. Process Based Reconstruction of Sandstones and Predictions of Transport Properties. Transport in Porous Media, 46(2-3): 311-343. doi: 10.1023/A:1015031122338 Qian, Y. H., Humieres, D. D., Lallemand, P., 1992. Lattice BGK Model for Navier-Stokes Equation. Europhysics Letters, 17(6): 479-484. doi: 10.1209/0295-5075/17/6/001 Rosenberg, E., Lynch, J., Gueroult, P., et al., 1999. High Resolution 3D Reconstructions of Rocks and Composites. Oil & Gas Science and Technology, 54(4) : 497-511. doi: 10.2516/ogst:1999043 Schwartz, L. M., Kimminau, S., 1987. Analysis of Electrical Conduction in the Grain Consolidation Model. Geophysics, 52(10): 1402-1411. doi: 10.1190/1.1442252 Wang, C. C., Yao, J., Yang, Y. F., et al., 2012. Percolation Properties Analysis of Carbonate Digital Core Based on Lattice Boltzmann Method. Journal of China University of Petroleum, 36(6): 94-98 (in Chinese with English abstract). Wu, K.J., Van Dijke, M. I. J., Couples, G. D., et al., 2006. 3D Stochastic Modelling of Heterogeneous; Porous Media-Applications to Reservoir Rocks. Transport in Porous Media, 65(3) : 443-467. doi: 10.1007/s11242-006-0006-z Zhang, J. Y., Sun, J. M., 2012. Rock Elastic Properties Determined by Using Digital Rock and Effective Medium Model. Journal of Oil and Gas Technology, 34(2): 65-70 (in Chinese with English abstract). Zhu, Y. H., Tao, G., 2007. Sequential Indicator Simulation Technique and Its Application in 3D Digital Core Modeling. Well Logging Technology, 31(2): 112-115 (in Chinese with English abstract). 丁喜桂, 叶思源, 高宗军, 2005. 粒度分析理论技术进展及其应用. 世界地质, 24(2): 203-207. doi: 10.3969/j.issn.1004-5589.2005.02.017 季长军, 伊海生, 夏国清, 2012. 图像分析技术在碎屑岩粒度分析中的应用. 地质科技情报, 31(3): 122-127. doi: 10.3969/j.issn.1000-7849.2012.03.019 王晨晨, 姚军, 杨永飞, 等, 2012. 基于格子玻尔兹曼方法的碳酸盐岩数字岩心渗流特征分析. 中国石油大学学报(自然科学版), 36(6): 94-98. doi: 10.3969/j.issn.1673-5005.2012.06.017 张晋言, 孙建孟, 2012. 应用数字岩心和有效介质模型研究岩石弹性性质. 石油天然气学报, 34(2): 65-70. doi: 10.3969/j.issn.1000-9752.2012.02.014 朱益华, 陶果, 2007. 顺序指示模拟技术及其在3D数字岩心建模中的应用. 测井技术, 31(2): 112-115. doi: 10.3969/j.issn.1004-1338.2007.02.005 -
点击查看大图
图(7) / 表(1)
计量
- 文章访问数: 4620
- HTML全文浏览量: 592
- PDF下载量: 1139
- 被引次数: 0
