Investigation of coal elastic properties based on digital core technology and finite element method
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Abstract
Rock elastic properties play an important role in the geological characteristics of reservoirs. The analysis of these properties is normally based physical experiments on rocks. However, such conventional physical experiments cannot meet actual requirements when the rock is fragile or has complex composition. With the development of computer technology and the application of micro-computed tomography scanning technology, digital rock physics technologies came into existence. In this work, micro-computed tomography was applied to obtain high-quality three-dimensional images of coal samples. Next, the image multi-threshold segmentation method was used to divide the grayscale image into three reasonable components, including mineral, organic matrix, and pores. Digital rock models with different gas saturations were established using mathematical morphology based methods. Five volume samples were selected from the original large digital rock model under different conditions of porosity, mineral, and gas saturation. Based on these three-dimensional digital cores and the finite element method, the effective elastic moduli of coal rock mass were simulated and the compressional wave velocity and shear wave velocity were computed. Results show that, in the absence of filled minerals, both bulk and shear moduli decrease with rising porosity; compressional and shear wave velocities decline, and the ratio of compressional wave velocity to shear wave velocity increases. However, a more realistic study considering filled minerals demonstrates decreasing shear wave velocity and counterintuitively rising compressional wave velocity when the porosity increases. Gas saturation only affects the compressional wave velocity. The obtained results improve our understanding of rock elastic behaviors in the coalbed.
Cited as: Andhumoudine, A. B., Nie, X., Zhou, Q., Yu, J., Kane, O.I., Jin, L., Djaroun, R.R. Investigation of coal elastic properties based on digital core technology and finite element method. Advances in Geo-Energy Research, 2021, 5(1): 53-63, doi: 10.46690/ager.2021.01.06
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Al-Marzouqi, H. Digital rock physics: Using CT scans to compute rock properties. IEEE Signal Processing Magazine, 2018, 35(2): 121-131.
Andrä, H., Combaret, N., Dvorkin, J., et al. Digital rock physics benchmarks-part II: Computing effective properties. Computers & Geosciences, 2013, 50: 33-43. Arns, C. H. The Influence of Morphology on Physical Properties of Reservoir Rocks. Sydney, The University of New South Wales, 2002.
Chauhan, S., Rühaak, W., Khan, F., et al. Processing of rock core microtomography images: Using seven different machine learning algorithms. Computers & Geosciences, 2016, 86: 120-128.
Chen, X., Zhou, Y. Applications of digital core analysis and hydraulic flow units in petrophysical characterization. Advances in Geo-Energy Research, 2017, 1(1): 18-30.
Combaret, N., Dvorkin, J., Glatt, E., et al. Digital rock physics benchmarks-part II: Computing effective properties. Computers & Geosciences, 2013, 50: 33-43.
Cui, T., Moore, C., Raiber, M. Probabilistic assessment of the impact of coal seam gas development on groundwater: Surat Basin, Australia. Hydrogeology Journal, 2018, 26: 2357-2377.
Dvorkin, J. Rock physics: Recent history and advances, in Geophysics and Ocean Waves Studies [Working Title], 2020.
Garboczi, E. J., Day, A. R. An algorithm for computing the effective linear elastic properties of heterogeneous materials: Results for composites with equal phase poisson ratios. Journal of the Mechanics and Physics of Solids, 1995, 43: 1349-1362.
Gentzis, T., Bolen, D. The use of numerical simulation in predicting coalbed methane producibility from the Gates coals, Alberta Inner Foothills, Canada: Comparison with Mannville coal CBM production in the Alberta Syncline. International Journal of Coal Geology, 2008, 74: 215-236.
Haralick, R. M., Sternberg, S. R., Zhuang, X. Image Analysis Using Mathematical Morphology. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1987, PAMI-9: 532-550.
Hu, S., Hoffman, E. A., Reinhardt, J. M. Automatic lung segmentation for accurate quantitation of volumetric Xray CT images. IEEE Transactions on Medical Imaging, 2001, 20(6): 490-498.
Huang, T., Yang, G., Tang, G. A fast two-dimensional median filtering algorithm. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1979, 27(1): 13-18.
Icke, I., Hanchi, J., Haralick, R. M., et al. TR-2005001: Automatic target detection in E3D images using mathematical morphology techniques. Computer science technical reports, CUNY Academic Works, 2005.
Liu, X., Sun, J., Wang, H. Numerical simulation of rock electrical properties based on digital cores. Applied Geophysics, 2009, 6: 1-7.
Madonna, C., Quintal, B., Frehner, M., et al. Synchrotron-based X-ray tomographic microscopy for rock physics investigations. Geophysics, 2013, 78: D53-D64.
Makarynska, D., Gurevich, B., Ciz, R., et al. Finite element modeling of the effective elastic properties of partially saturated rocks. Computers & Geosciences, 2008, 34: 647-657.
Maximenko, A., Kadet, V. V. Determination of relative permeabilities using the network models of porous media. Journal of Petroleum Science and Engineering, 2000, 28(3): 145-152.
Moore, T. A. Coalbed methane: A review. International Journal of Coal Geology, 2012, 101: 36-81.
Nie, X., Zhang, C., Wang, C., et al. Variable secondary porosity modeling of carbonate rocks based on μ-CT images. Open Geosciences, 2019, 11: 617-626.
Nie, X., Zou, C., Li, Z., et al. Numerical simulation of the electrical properties of shale gas reservoir rock based on digital core. Journal of Geophysics and Engineering, 2016, 13: 481-490.
Peng, C., Zou, C., Zhou, T., et al. Factors affecting coalbed methane (CBM) well productivity in the Shizhuangnan block of southern Qinshui basin, North China: Investigation by geophysical log, experiment and production data. Fuel, 2017, 191: 427-441.
Serra, J. Image Analysis and Mathematical Morphology. Academic Press, New York, USA, 1982.
Sun, H., Vega, S., Tao, G. Analysis of heterogeneity and permeability anisotropy in carbonate rock samples using digital rock physics. Journal of Petroleum Science and Engineering, 2017, 156: 419-429
Sun, J., Zhao, J., Liu, X., et al. Pore-scale analysis of electrical properties in thinly bedded rock using digital rock physics. Journal of Geophysics and Engineering, 2014, 11: 055008.
Vishal, V., Mahanta, B., Pradhan, S. P., et al. Simulation of CO2 enhanced coalbed methane recovery in Jharia coalfields, India. Energy, 2018, 159: 1185-1194.
Wang, H., Fehler, M. The wavefield of acoustic logging in a cased-hole with a single casing-Part I: A monopole tool. Geophysical Journal International, 2018, 212: 612-626.
Wang, H., Tao, G., Shang, X. F., et al. Stability of finite difference numerical simulations of acoustic logging-while-drilling with different perfectly matched layer schemes. Applied Geophysics, 2013a, 10: 384-396.
Wang, H., Tao, G., Zhang, K. Wavefield simulation and analysis with the finite-element method for acoustic logging while drilling in horizontal and deviated wells. Geophysics, 2013b, 78: D525-D543.
Wei, D., Tong, W. Research on edge detection based on mathematical morphology algorithm. Paper Presented at Proceedings of 2010 International Conference on Optoelectronics and Image Processing, Haikou, China, 11-12 November, 2010.
Wei, Y., Nie, X., Jin, L. Investigation of sensitivity of shale elastic properties to rock components based on a digital core technology and finite element method. Arabian Journal of Geosciences, 2018, 11: 224.
Zhang, J. Research on image processing based on mathematical morphology. Agro Food Industry Hi-Tech, 2017, 28: 2738-2742.
Zhang, W., Fu, L., Zhang, Y., et al. Computation of elastic properties of 3D digital cores from the Longmaxi shale. Applied Geophysics, 2016, 13: 364-374.
Zhao, J., Chen, H., Li, N. The study of elastic properties of fractured porous rock based on digital rock. IOP Conference Series: Earth and Environmental Science, 2020, 514: 022022.
Zhao, J., Sun, J., Liu, X., et al. Numerical simulation of the electrical properties of fractured rock based on digital rock technology. Journal of Geophysics and Engineering, 2013, 10: 055009.
DOI: https://doi.org/10.46690/ager.2021.01.06
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