THERMAL SCIENCE

International Scientific Journal

TOPOLOGICAL REPRESENTATION OF THE POROUS STRUCTURE AND ITS EVOLUTION OF RESERVOIR SANDSTONE UNDER EXCAVATION-INDUCED LOADS

ABSTRACT
The porous structure of a reservoir rock greatly influences its evolutive deformation and fracture behavior during excavation of natural resources reservoirs. Most numerical models for porous structures have been used to predict the quasi-static mechanical properties, but few are available to accurately characterize the evolution process of the porous structure and its influence on the macroscopic properties of reservoir rocks. This study reports a novel method to characterize the porous structure of sandstone using its topological parameters and to determine the laws that govern the evolutive deformation and failure of the topological structure under various uniaxial compressive loads. A numerical model of the porous sandstone was established based on the pore characteristics that were acquired using computed tomography imaging techniques. The analytical method that integrates the grassfire algorithm and the maximum inscribed sphere algorithm was proposed to create the 3-D topological model of the deformed porous structure, through which the topological parameters of the structure were measured and identified. The evolution processes of the porous structure under various loads were characterized using its equivalent topological model and parameters. This study opens a new way to characterize the dynamic evolution of the pore structure of reservoir sandstone under excavation disturbance.
KEYWORDS
PAPER SUBMITTED: 2017-03-10
PAPER REVISED: 2017-05-01
PAPER ACCEPTED: 2017-05-22
PUBLISHED ONLINE: 2017-12-02
DOI REFERENCE: https://doi.org/10.2298/TSCI17S1285J
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2017, VOLUME 21, ISSUE Supplement 1, PAGES [S285 - S292]
REFERENCES
  1. Fahimifar, A., et al., Analytical Solution for the Excavation of Circular Tunnels in a Viscoelastic Burger's Material under Hydrostatic Stress Field, Tunn. Undergr. Sp. Tech., 25 (2010), 4, pp. 297-304
  2. Stiros, S. C., Kontogianni, V. A., Coulomb Stress Changes: from Earthquakes to Underground Excavation Failures, Int. J. Rock Mech. Min., 46 (2009), 1, pp. 182-187
  3. Cueto, N., et al., Rock Fabric, Pore Geometry and Mineralogy Effects on Water Transport in Fractured Dolostones, Eng. Geol., 107 (2009), 1-2, pp. 1-15
  4. Sabatakakis, N., et al., Index Properties and Strength Variation Controlled by Microstructure for Sedimentary Rocks, Eng. Geol., 97 (2008), 1-2, pp. 80-90
  5. Zaretskiy, Y., et al., Efficient Flow and Transport Simulations in Reconstructed 3D Pore Geometries, Adv. Water Resour., 33 (2010), 12, pp. 1508-1516
  6. Varloteaux, C., et al., Pore Network Modelling to Determine the Transport Properties in Presence of a Reactive Fluid: From Pore to Reservoir Scale, Adv. Water Resour., 53 (2013), 2, pp. 87- 100
  7. Bultreys, T., et al., Multi-Scale, Micro-Computed Tomography-Based Pore Network Models to Simulate Drainage in Heterogeneous Rocks, Adv. Water Resour., 78 (2015), Apr., pp. 36-49
  8. Kate, J. M., Gokhale, C. S., A Simple Method to Estimate Complete Pore Size Distribution of Rocks, Eng. Geol., 84 (2006), 1-2, pp. 48-69
  9. Bera, B., et al., Understanding the Micro Structure of Berea Sandstone by the Simultaneous Use of Micro- Computed Tomography (Micro-CT) and Focused Ion Beam-Scanning Electron Microscopy (FIBSEM), Micron, 42 (2011), 5, pp. 412-418
  10. De Boever, W., et al., Data-Fusion of High Resolution X-Ray CT, SEM and EDS for 3D and Pseudo-3D Chemical and Structural Characterization of Sandstone, Micron, 74 (2015), July, pp. 15- 21
  11. Omer, M. F., Cathodoluminescence Petrography for Provenance Studies of the Sandstones of Ora Formation (Devonian-Carboniferous), Iraqi Kurdistan Region, Northern Iraq, Journal of African Earth Sciences, 109 (2015), Sept., pp. 195-210
  12. Rosenbrand, E., et al., Permeability in Rotliegend Gas Sandstones to Gas and Brine as Predicted from NMR, Mercury Injection and Image Analysis, Marine & Petroleum Geology, 64 (2015), June, pp.189-202
  13. Liu, X. F., et al., Numerical Simulation of Rock Electrical Properties Based on Digital Cores, J. Appl. Geophys., 6 (2009), 1, pp. 1-7
  14. Luo, G., Wang, L. 3D Morphology Algorithm Implementation and Application, in: High Quality Artificial Digital Core Modeling (Ed. Z. Qian et al.), Springer, Heidelberg, Berlin, 2012, pp. 817-822
  15. Zhu, W., et al., Digital Core Modeling from Irregular Grains, J. Appl. Geophys., 85 (2012), 10, pp. 37-42
  16. Bakke, S., Ren, P. E., 3-D Pore-Scale Modelling of Sandstones and Flow Simulations in the Pore Networks, SPE, 2 (1997), 2, pp. 136-149
  17. Hazlett, R. D., Statistical Characterization and Stochastic Modeling of Pore Networks in Relation to Fluid Flow, Mathematical Geology, 29 (1997), 6, pp. 801-822
  18. Ren, P. E., Bakke, S., Process Based Reconstruction of Sandstones and Prediction of Transport Properties, Trans Porous Med., 46 (2002), 2-3, pp. 311-343
  19. Quiblier, J. A., A New Three-Dimensional Modeling Technique for Studying Porous Media, J. Colloid Interf. Sci., 98 (1984), 1, pp. 84-102
  20. Yeong, C. L. Y., Torquato, S., Reconstructing Random Media. II. Three-Dimensional Media from Two-Dimensional Cuts, Phys. Rev. E, Statistical Physics Plasmas Fluids & Related Interdisciplinary Topics, 58 (1998), 1, pp. 224-233
  21. Blunt, M. J., et al., Pore-Scale Imaging and Modelling, Adv. Water Resour., 51 (2013), 1, pp. 197-216
  22. Ju, Y., et al., 3D Numerical Reconstruction of Well-Connected Porous Structure of Rock Using Fractal Algorithms, Comput. Methods Appl. Mech. Eng., 279 (2014), 9, pp. 212-226
  23. Knackstedt, M. A., et al., Pore Network Modelling of Two-Phase Flow in Porous Rock: The Effect of Correlated Heterogeneity, Adv. Water Resour., 24 (2001), 3-4, pp. 257-277
  24. Su, N., Study of Effects of Pore Space Topological Structure on Water-Oil Two Phase Flow (in Chinese), Journal of Chongqing University of Science & Technology, (2013), 3, pp. 52-58
  25. Valvatne, P. H., et al., Predictive Pore-Scale Modeling of Single and Multiphase Flow, Transport Porous Med., 58 (2005), 1-2, pp. 23-41
  26. Ju, Y., et al., Computer Program for Extracting and Analyzing Fractures in Rocks and Concretes (in Chinese), Software Copyright Registration, Reg # 0530646, Beijing, 2013
  27. Kaestner, A., et al., Imaging and Image Processing in Porous Media Research, Adv. Water Resour., 31 (2008), 9, pp. 1174-1187
  28. Otsu, N., A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems Man & Cybernetics, 9 (1979), 1, pp. 62-66
  29. Ju, Y., et al., A Statistical Model for Porous Structure of Rocks, Sci. China Technol. Sc., 51 (2008), 11, pp. 2040-2058
  30. Wang, J. B., 3D Reconstruction of Porous Rock and Numerical Simulations of Fluid Flow at Mesoscale Levels (in Chinese), Ph. D. thesis, China University of Mining and Technology, Beijing, 2014
  31. Yang, Y. M., Study on Modeling Porous Structures of Rocks and Mechanical Properties (in Chinese), Ph. D. thesis, China University of Mining and Technology, Beijing, 2008
  32. Blum, H., A Transformation for Extracting New Descriptors of Shape, Models for the Perception of Speech & Visual Form, 19 (1967), 5, pp. 362-380
  33. Alraoush, R., et al., Comparison of Network Generation Techniques for Unconsolidated Porous Media, Soil Sci. Soc. Am. J., 67 (2003), 7, pp. 1687-1700

© 2017 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence