Abstract
A 3-D digital core describes the pore space microstructure of rocks. An X-ray micro CT scan is the most accurate and direct but costly method to obtain a 3-D digital core. In this study, we propose a hybrid method which combines sedimentation simulation and simulated annealing (SA) method to generate 3-D digital cores based on 2-D images of rocks. The method starts with the sedimentation simulation to build a 3-D digital core, which is the initial configuration for the SA method. We update the initial digital core using the SA method to match the auto-correlation function of the 2-D rock image and eventually build the final 3-D digital core. Compared with the typical SA method, the hybrid method has significantly reduced the computation time. Local porosity theory is applied to quantitatively compare the reconstructed 3-D digital cores with the X-ray micro CT 3-D images. The results indicate that the 3-D digital cores reconstructed by the hybrid method have homogeneity and geometric connectivity similar to those of the X-ray micro CT image. The formation factors and permeabilities of the reconstructed 3-D digital cores are estimated using the finite element method (FEM) and lattice Boltzmann method (LBM), respectively. The simulated results are in good agreement with the experimental measurements. Comparison of the simulation results suggests that the digital cores reconstructed by the hybrid method more closely reflect the true transport properties than the typical SA method alone.
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References
Arns, C. H., 2002, The influence of morphology on physical properties of reservoir rocks: PhD Thesis, The University of New South Wales.
Biswal, B., Manwart, C., Hilfer R, Bakke, S., and Oren, P. E., 1999, Quantitative analysis of experimental and synthetic microstructures for sedimentary rock: Physica A, 273(3), 452–475.
Dvorkin, J., Walls, J., Tutuncu, A., Prasad, M., Nur, A., and Mese, A., 2003, Rock property determination using digital rock physics: 73rd Ann. Internat. Mtg, Soc. Expl. Geophys., Expanded Abstracts, 1660–1663.
Fredrich, J., Greaves, K. H., and Martin, J. W., 1993, Pore geometry and transport properties of Fontainebleau sandstone: International Journal of Rock Mechanics and Mining Sciences, 30(7), 691–697.
Garboczi, E. J., 1998, Finite element and finite difference programs for computing the linear electric and linear elastic properties of digital images of random materials: Technical report, NIST Internal Report 6269.
Hazlett, R. D., 1997, Statistical characterization and stochastic modeling of pore networks in relation to fluid flow: Mathematical Geology, 29(4), 801–822.
Hidajat, I., Rastogi, A., Singh, M., and Mohanty, K. K., 2002, Transport properties of porous media from thin sections: SPE 69623.
Jacquin, C.G., 1964. Correlation entre la permeabilite et les caracteristiques geometriques du gres de Fontainebleau: Revue de I’iInstitut Francais du Perole, 19, 921–937.
Joshi, M., 1974, A class of stochastic models for porous media: PhD Thesis, University of Kansas.
Keehm, Y., 2003, Computational rock physics: transport properties in porous media and applications: PhD Thesis, Stanford: Stanford University.
Liu, X. F., Sun, J. M., and Wang, H. T., 2009, Numerical simulation of rock electrical properties based on digital cores: Applied Geophysics, 6(1), 1–7.
Oren, P. E., and Bakke, S., 2000, Process based reconstruction of sandstones and predictions of transport properties: Transport in Porous Media, 46(2), 311–343.
Oren, P. E., and Bakke, S., 2003, Reconstruction of Berea sandstone and pore-scale modeling of wettability effects: Journal of Petroleum Science and Engineering, 39(2), 177–199.
Shi, Y., and Zhang Y. W., 2008, Simulation of random packing of spherical particles with different size distributions: Applied Physics A: Materials Science and Processing, 92(3), 621–626.
Yao, J., Zhao X. C., Yi, Y. J., and Tao, J., 2007, Analysis methods for reservoir rock’s microstructure: Journal of China University of Petroleum (Edition of Natural Science) (in Chinese), 31(1), 80–86.
Yeong, C. L. Y., and Torquato S., 1998a, Reconstructing random media: Physical Review E, 57(1), 495–506.
Yeong, C. L. Y., and Torquato S., 1998b, Reconstructing random media. II. Three-dimensional media from twodimensional cuts: Physical Review E, 58(1), 224–233.
Zhao, X. C., Yao, J., Tao, J., and Yi, N. J., 2007a, A method of constructing digital core by simulated annealing algorithm: Applied Mathematics A, Journal of Chinese Universities (in Chinese), 22(2), 127–133.
Zhao, X. C., Yao, J., and Yi, Y. J., 2007b, A new stochastic method of reconstructing porous media: Transport in Porous Media, 69(1), 1–11.
Zhu, Y. H., Tao, G., and Fang, W., 2007, Application of image processing technique in digital core modeling: Journal of Oil and Gas Technology (in Chinese), 29(5), 54–57.
Zhu, Y. H., and Tao, G., 2007, Sequential indicator simulation technique and its application in 3D digital core modeling: Well Logging Technology (in Chinese), 31(2), 112–115.
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The work is sponsored by NSFC (Grant No. 40574030) and CNPC Research Project (Grant No. 06A30102).
Liu Xuefeng, see biography and photo in the APPLIED GEOPHYSICS March 2009 issue, P. 7.
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Liu, X., Sun, J. & Wang, H. Reconstruction of 3-D digital cores using a hybrid method. Appl. Geophys. 6, 105–112 (2009). https://doi.org/10.1007/s11770-009-0017-y
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DOI: https://doi.org/10.1007/s11770-009-0017-y