Pore scale modeling of fluid transport in complex reservoirs: Multi-scale digital rock construction, flow experiments and simulation methods
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Abstract
The heterogeneities of complex reservoirs are expressed in terms of multi-scale pore structure, different pore type and multiple occurrence mode. Fluid transport mechanisms notably differ from that in conventional sandstone reservoir. Conventional core scale experimental methods are not applicable to complex reservoirs because of nanoscale pore size and strong heterogeneity. Investigating pore scale fluid flow is the key to reveal flow mechanisms while the current pore scale modelling framework fails to consider the multi-scale structure, multiphase fluid-rock interaction and confined phase change. This work leverages the recent advances in pore scale modeling methods of fluid transport in complex reservoirs. The developing trend of multi-scale digital rock construction, flow experiments and simulation methods are elaborated in detail. The mentioned pore scale modeling methods in this work form the future research paradigm for understanding fluid transport mechanisms in complex reservoirs.
Document Type: Current minireview
Cited as: Song, W., Liu, F., Li, Y., Yang, Y. Pore scale modeling of fluid transport in complex reservoirs: Multi-scale digital rock construction, flow experiments and simulation methods. Capillarity, 2024, 11(3): 81-88. https://doi.org/10.46690/capi.2024.06.03
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Abidoye, L. K., Khudaida, K. J., Das, D. B. Geological carbon sequestration in the context of two-phase flow in porous media: A Review. Critical Reviews in Environmental Science and Technology, 2015, 45(11): 1105-1147.
Abu-Al-Saud, M. O., Riaz, A., Tchelepi, H. A. Multiscale level-set method for accurate modeling of immiscible two-phase flow with deposited thin films on solid surfaces. Journal of Computational Physics, 2017, 333: 297-320.
Al-Bayati, D., Saeedi, A., Myers, M., et al. An experimental investigation of immiscible-CO2-flooding efficiency in sandstone reservoirs: Influence of permeability heterogeneity. SPE Reservoir Evaluation & Engineering, 2018, 22(3): 990-997.
Al-Bayati, D., Saeedi, A., Myers, M., et al. Insights into immiscible supercritical CO2 EOR: An XCT scanner assisted flow behaviour in layered sandstone porous media. Journal of CO2 Utilization, 2019, 32: 187-195.
Alkhazmi, B., Farzaneh, S. A., Sohrabi, M., et al. An experimental investigation of WAG injection performance under near-miscible conditions in carbonate rock and comparison with sandstone. Paper SPE 190053 Presented at SPE Western Regional Meeting, Garden Grove, California, USA, 22-26 April, 2018.
Alqahtani, F. M., Althehibey, M. T., Ghasemi, M. The impact of petrophysical heterogeneity on the carbon capture utilizations and storage strategies. Paper SPE 210378 Presented at SPE Annual Technical Conference and Exhibition, Houston, Texas, USA, 3-5 October, 2022.
Cai, J., Wood, D. A., Hajibeygi, H., et al. Multiscale and multiphysics influences on fluids in unconventional reservoirs: Modeling and simulation. Advances in Geo-Energy Research, 2022, 6(2): 91-94.
Chen, H., He, X., Teng, Q., et al. Super-resolution of real world rock microcomputed tomography images using cycle-consistent generative adversarial networks. Physical Review E, 2020, 101: 023305.
Chen, L., Zhang, L., Kang, Q., et al. Nanoscale simulation of shale transport properties using the lattice Boltzmann method: Permeability and diffusivity. Scientific Report, 2015, 5: 8089.
Christou, C., Dadzie, S. K. Direct-simulation Monte Carlo investigation of a Berea porous structure. SPE Journal, 2016, 21(3): 0938-0946.
Cueto-Felgueroso, L., Fu, X., Juanes, R. Pore-scale modeling of phase change in porous media. Physical Review Fluids, 2018, 3: 084302.
Cui, R., Hassanizadeh, S. M., Sun, S. Pore-network modeling of flow in shale nanopores: Network structure, flow principles, and computational algorithms. Earth-Science Reviews, 2022, 234: 104203.
Dong, C., Loy, C. C., He, K., et al. Image super-resolution using deep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016, 38(2): 295-307.
Eshghinejadfard, A., Daroczy, L., Janiga, G., et al. Calculation of the permeability in porous media using the lattice Boltzmann method. International Journal of Heat and Fluid Flow, 2016, 62: 93-103.
Fei, L., Qin, F., Zhao, J., et al. Lattice Boltzmann modelling of isothermal two-component evaporation in porous media. Journal of Fluid Mechanics, 2023, 955: A18.
Foroughi, S., Bijeljic, B., Gao, Y., et al. Incorporation of subresolution porosity into two-phase flow models with a multiscale pore network for complex microporous rocks. Water Resources Research, 2024, 60: e2023WR036393.
Geistlinger, H., Golmohammadi, S., Zulfiqar, B., et al. The interplay between pore-scale heterogeneity, surface roughness, and wettability controls trapping in two-phase fluid displacement in porous media. Geophysical Research Letters, 2024, 51(1): e2023GL106197.
Giudici, L. M., Raeini, A. Q., Akai, T., et al. Pore-scale modeling of two-phase flow: A comparison of the generalized network model to direct numerical simulation. Physical Review E, 2023, 107: 035107.
Harris, C., Jackson, S. J., Benham, G. P., et al. The impact of heterogeneity on the capillary trapping of CO2 in the Captain Sandstone. International Journal of Greenhouse Gas Control, 2021, 112: 103511.
Herring, A. L., Robins, V., Sheppard, A. P. Topological persistence for relating microstructure and capillary fluid trapping in sandstones. Water Resources Research, 2019, 55(1): 555-573.
Hu, K., Zhang, Q., Liu, Y., et al. A developed dual-site Langmuir model to represent the high-pressure methane adsorption and thermodynamic parameters in shale. International Journal of Coal Science & Technology, 2023, 10: 59.
Jia, C., Lin, J., Zhao, W. The shale revolution and basic geological theory problems of shale and tight oil and gas. Petroleum Science Bulletin, 2023, 5: 695-706.
Karniadakis, G., Beskok, A., Aluru, N. Microflows and nanoflows: fundamentals and simulation. Beilin, Germary, Springer Science & Business Media, 2006.
Krevor, S. C. M., Pini, R., Li, B., et al. Capillary heterogeneity trapping of CO2 in a sandstone rock at reservoir conditions. Geophysical Research Letters, 2011, 38(15): L15401.
Landry, C., Prodanovi´ c, M., Karpyn, Z., et al. Estimation of fracture permeability from aperture distributions for rough and partially cemented fractures. Transport in Porous Media, 2024, 151: 689-717.
Li, J., Yang, Z., Wu, S., et al. Key issues and development direction of petroleum geology research on source rock strata in China. Advances in Geo-Energy Research, 2021, 5(2): 121-126.
Li, Y., Yang, Y., Dong, M., et al. Pore-scale characterization of CO2 trapping and oil displacement in three-phase flow in a heterogeneous layered sandstone. SPE Journal, 2024, 29(2): 1147-1160.
Liu, B., Qi, C., Zhao, X., et al. Nanoscale two-phase flow of methane and water in shale inorganic matrix. The Journal of Physical Chemistry C, 2018, 122(46): 26671-26679.
Liu, M., Mukerji, T. Multiscale fusion of digital rock images based on deep generative adversarial networks. Geophysical Research Letters, 2022, 49(9): e2022GL098342.
Liu, Q., Fu, Q., Yang, K., et al. Geomechanical modeling and inversion Analysis of the in-situ stress field in deep marine shale formations: A case study of the Longmaxi Formation, Dingshan Area, China. Frontiers in Earth Science, 2022, 9: 808535.
Mahady, K., Afkhami, S., Kondic, L. A numerical approach for the direct computation of flows including fluid-solid interaction: Modeling contact angle, film rupture, and dewetting. Physics of Fluids, 2016, 28(6): 062002.
Mirzaee, H., Kamrava, S., Tahmasebi, P. Minireview on porous media and microstructure reconstruction using machine learning techniques: Recent advances and outlook. Energy & Fuels, 2023, 37(20): 15348-15372.
Ni, H., Boon, M., Garing, C., et al. Predicting CO2 residual trapping ability based on experimental petrophysical properties for different sandstone types. International Journal of Greenhouse Gas Control, 2019, 86: 158-176.
Niu, Y., Wang, Y. D., Mostaghimi, P., et al. An innovative application of generative adversarial networks for physically accurate rock images with an unprecedented field of view. Geophysical Research Letters, 2020, 47(23): e2020GL089029.
Øren, P. E., Ruspini, L. C., Saadatfar, M., et al. In-situ porescale imaging and image-based modelling of capillary trapping for geological storage of CO2. International Journal of Greenhouse Gas Control, 2019, 87: 34-43.
Santos, J. E., Chang, B., Gigliotti, A., et al. A dataset of 3D structural and simulated transport properties of complex porous media. Scientific Data, 2022, 9: 579.
Sedghi, M., Piri, M., Goual, L. Molecular dynamics of wetting layer formation and forced water invasion in angular nanopores with mixed wettability. The Journal of Chemical Physics, 2014, 141(19): 194703.
Seyyedi, M., Clennell, M. B., Jackson, S. J. Time-lapse imaging of flow instability and rock heterogeneity impacts on CO2 plume migration in meter long sandstone cores. Advances in Water Resources, 2022, 164: 104216.
Shams, R., Masihi, M., Boozarjomehry, R. B., et al. Coupled generative adversarial and auto-encoder neural networks to reconstruct three-dimensional multi-scale porous media. Journal of Petroleum Science and Engineering, 2020, 186: 106794.
Shan, L., Bai, X., Liu, C., et al. Super-resolution reconstruction of digital rock CT images based on residual attention mechanism. Advances in Geo-Energy Research, 2022, 6(2): 157-168.
Shi, B., Jiang, H., Guo, B., et al. Modeling of flow and transport in multiscale digital rocks aided by grid coarsening of microporous domains. Journal of Hydrology, 2024, 633: 131003.
Song, W., Yao, B., Sun, H., et al. Nanoscale three-phase transport in a shale pore network with phase change and solid-fluid interaction. Energy & Fuels, 2023, 37(18): 13851-13865.
Song, W., Yao, J., Zhang, K., et al. Understanding gas transport mechanisms in shale gas reservoir: Pore network modelling approach. Advances in Geo-Energy Research, 2022a, 6(4): 359-360.
Song, W., Yao, J., Zhang, K., et al. The impacts of pore structure and relative humidity on gas transport in shale: A numerical study by the image-based multi-scale pore network model. Transport in Porous Media, 2022b, 144: 229-253.
Song, W., Liu, L., Wang, D., et al. Nanoscale confined multicomponent hydrocarbon thermodynamic phase behavior and multiphase transport ability in nanoporous material. Chemical Engineering Journal, 2020, 382: 122974.
Song, W., Yao, J., Zhang, K., et al. Nano-scale multicomponent hydrocarbon thermodynamic transport mechanisms in shale oil reservoir. Journal of Petroleum Science and Engineering, 2022c, 219: 111093.
Tahmasebi, P. Nanoscale and multiresolution models for shale samples. Fuel, 2018, 217: 218-225. Tan, Y., Li, Q., Xu, L., et al. A critical review of carbon dioxide enhanced oil recovery in carbonate reservoirs. Fuel, 2022, 328: 125256.
Tang, Y., Hou, C., He, Y., et al. Review on pore structure characterization and microscopic flow mechanism of CO2 f looding in porous media. Energy Technology, 2021, 9: 2000787.
Tanino, Y., Blunt, M. J. Capillary trapping in sandstones and carbonates: Dependence on pore structure. Water Resources Research, 2012, 48(8): W08525.
Wang, D., Yao, J., Chen, Z., et al. Multiphase flow model from pores to cores in organic-rich shale. Journal of Petroleum Science and Engineering, 2020a, 194: 107317.
Wang, D., Yao, J., Chen Z, et al. Assessment of extended Derjaguin-Landau-Verwey-Overbeek-based water film on multiphase transport behavior in shale microfractures. AIChE Journal, 2021, 67(4): e17162.
Wang, H., Cai, J., Su, Y., et al. Pore-scale study on shale oil-CO2-water miscibility, competitive adsorption, and multiphase flow behaviors. Langmuir, 2023, 39(34): 12226 12234.
Wang, J., Chen, L., Kang, Q., et al. The lattice Boltzmann method for isothermal micro-gaseous flow and its application in shale gas flow: A review. International Journal of Heat and Mass Transfer, 2016, 95: 94-108.
Wang, Y. D., Armstrong, R. T., Mostaghimi, P. Enhancing resolution of digital rock images with super resolution convolutional neural networks. Journal of Petroleum Science and Engineering, 2019, 182: 106261.
Wang, Y. D., Armstrong, R. T., Mostaghimi, P. Boosting resolution and recovering texture of 2D and 3D micro-CT images with deep learning. Water Resources Research, 2020b, 56(1): e2019WR026052.
Wei, P., Xie, Z., Lu, H., et al., Component divide-and-conquer for real-world image super-resolution, in Lecture Notes in Computer Science, edited by A. Vedaldi, H. Bischof, T. Brox, et al., Cham, Switzerland, pp. 101-117, 2020.
Wu, Y., An, S., Tahmasebi, P., et al. An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features. Fuel, 2023, 352: 128753.
Wu, Y., Tahmasebi, P., Lin, C., et al. Multiscale modeling of shale samples based on low-and high-resolution images. Marine and Petroleum Geology, 2019, 109: 9-21.
Xing, Z., Yao, J., Liu, L., et al. Efficiently reconstructing highquality details of 3D digital rocks with super-resolution transformer. Energy, 2024, 300: 131499.
Xu, T., Wang, J., Lu, Y., et al. Exploring pore-scale production characteristics of oil shale after CO2 huff ‘n’ puff in fractured shale with varied permeability. International Journal of Coal Science & Technology, 2024, 11: 1-10.
Yan, P., Teng, Q., Ma, Z., et al. Modeling finer microstructure of random heterogeneous porous materials by fusing 2D high- and 3D low- resolution images. Computers and Geotechnics, 2024, 168: 106145.
Yang, Y., Liu, F., Yao, J., et al. Multi-scale reconstruction of porous media from low-resolution core images using conditional generative adversarial networks. Journal of Natural Gas Science and Engineering, 2022, 99: 104411.
Yang, Y., Liu, F., Zhang, Q., et al. Recent advances in multiscale digital rock reconstruction, flow simulation, and experiments during shale gas production. Energy & Fuels, 2023, 37(4): 2475-2497.
Yang, Y., Wang, K., Zhang, L., et al. Pore-scale simulation of shale oil flow based on pore network model. Fuel, 2019, 251: 683-692.
Yang, Y., Yao, J., Wang, C., et al. New pore space characterization method of shale matrix formation by considering organic and inorganic pores. Journal of Natural Gas Science and Engineering, 2015, 27(2): 496-503.
Yao, J., Sun, H., Li, A., et al. Modern system of multiphase f low in porous media and its development trend. Chinese Science Bulletin, 2018, 63: 425-451.
Yao, J., Song, W., Wang, D., et al. Multi-scale pore network modelling of fluid mass transfer in nano-micro porous media. International Journal of Heat and Mass Transfer, 2019, 141: 156-167.
Zhang, B., Kang, J., Kang, T., et al. Molecular dynamics simulations of CH4 diffusion in kaolinite: Influence of water content. International Journal of Coal Science & Technology, 2019, 6: 556-563.
Zhang, H., Zhu, H., Wu, X., et al. Status quo and future trends of green and clean energy technology toward “dual carbon” goal. Petroleum Science Bulletin, 2023a, 5: 555-576.
Zhang, T., Javadpour, F., Yin, Y., et al. Upscaling water flow in composite nanoporous shale matrix using Lattice Boltzmann Method. Water Resources Research, 2020, 56(4): e2019WR026007.
Zhang, X., Li, H., Tan, X., et al. Coupling effects of temperature, confining pressure, and pore pressure on permeability and average pore size of Longmaxi shale. Deep Underground Science and Engineering, 2023b, 2(4): 359-370.
Zhao, B., Saxena, N., Hofmann, R., et al. Enhancing resolution of micro-CT images of reservoir rocks using super resolution. Computers & Geosciences, 2023, 170: 105265.
Zhao, J., Yao, J., Zhang, M., et al. Study of gas flow charac teristics in tight porous media with a microscale lattice boltzmann model. Scientific Reports, 2016, 6: 32393.
Zhu, Q., Song, W., Yang, Y., et al. An advection-diffusion-mechanical deformation integral model to predict coal matrix methane permeability combining digital rock physics with laboratory measurements. Applied Geochemistry, 2021, 126: 104861.
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