Pore‑scale hydraulic properties of virtual sandstone microstructures: spatial variations and voxel scale effects

• Autorzy: Zhao Zhi , Zhou Xiao-Ping , Chen Jun‑Wei

Identyfikatory

DOI

10.1007/s43452-022-00566-7

• Języki publikacji: EN

Abstrakty

EN

This paper aims at studying spatial variations and voxel scale effects on digital-permeability of sandstone reservoirs at small-scale. X-ray μ-CT imaging is applied to capture various pore-structures. Digital pore-scale analysis is employed to quantitatively analyze voxel scale effects on microstructures with connective pore space and invalid pores. The coupling multipoint statistics-marching cube (MPS-MC) three-dimensional (3D) reconstruction is used to construct 3D virtual micro-channel models with connective seepage channels. Pore network numerical simulations with valid realistic geometries are conducted to deeply understand voxel scale effects on microscopic hydraulic properties of sandstone reservoirs. The results show that digital porosity, micro-pore and micro-grain size gradually become stable with a voxel scale larger than 3003. The spatial variation of permeability and voxel scale effects relates extremely to the seepage index and digital porosity. As digital porosity is less than 30%, the seepage index increases with an exponential manner, and as digital porosity is larger than 30%, it decreases with a logarithm manner. The permeability is easy to evaluate by the established logarithm relation between the permeability and seepage index with relative errors all less than 5%. The proposed permeability-seepage index in the digital analysis framework provides excellent approaches to effectively evaluate the hydraulic properties of rock reservoirs.

Słowa kluczowe

EN

X-ray μ-CT imaging; spatial location variation; voxel size effect; pore scale variable; digital permeability

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2023
• Tom: Vol. 23, no. 1
• Strony: art. no. e22, 2023
• Opis fizyczny: Bibliogr. 43 poz., rys., tab., wykr.

Twórcy

autor

Zhao Zhi

• School of Civil Engineering, Wuhan University, Wuhan 430072, China

autor

Zhou Xiao-Ping

• School of Civil Engineering, Wuhan University, Wuhan 430072, China
• School of Civil Engineering, Chongqing University, Chongqing 400045, China

autor

Chen Jun‑Wei

• School of Civil Engineering, Wuhan University, Wuhan 430072, China

Bibliografia

• 1. Shi J, Zhang JH, Zhang CY, Jiang TT, Huang G. Numerical model on predicting hydraulic fracture propagation in low-permeability sandstone. Int J Damage Mech. 2020;1:1-24.
• 2. Zhang LF, Zhou FJ, Zhang SC, Li Z, Wang J, Wang YC. Evaluation of permeability damage caused by drilling and fracturing fluids in tight low permeability sandstone reservoirs. J Petrol Sci Eng. 2019;175:1122-35.
• 3. Yu QY, Dai ZX, Zhang ZE, Soltanian MR, Yin SX. Estimation of sandstone permeability with SEM images based on fractal theory. Transp Porous Med. 2019;126:701-12.
• 4. Zhu SN, Sun JC, Wei GQ, Zhang DW, Wang JM, Lei S, Liu XS. Numerical simulation-based correction of relative permeability hysteresis in water-invaded underground gas storage during multi-cycle injection and production. Pet Explor Dev. 2021;48(1):190-200.
• 5. Lin QB, Cao P, Wen GP, Meng JJ, Cao RH, Zhao ZY. Crack coalescence in rock-like specimens with two dissimilar layers and pre-existing double parallel joints under uniaxial compression. Int J Rock Mech Min Sci. 2021;139: 104621.
• 6. Feng F, Wang P, Wei Z, Jiang G, Xu D, Zhang J, Zhang J. A new method for predicting the permeability of sandstone in deep reservoirs. Geofluids. 2020;2020:1-16.
• 7. Wang HL, Xu WY, Cai M, Xiang ZP, Kong Q. Gas permeability and porosity evolution of a porous sandstone under repeated loading and unloading conditions. Rock Mech Rock Eng. 2017;50:2071-83.
• 8. Zhao Z, Zhou XP. An integrated method for 3D reconstruction model of porous geomaterials through 2D CT images. Comput Geosci. 2019;123:83-94.
• 9. Zhao Z, Zhou XP, Qian QH. Fracture characterization and permeability prediction by pore scale variables extracted from X-ray CT images of porous geomaterials. Sci China Technol Sci. 2020;63(5):755-67.
• 10. Zhou JQ, Chen YF, Wang LC, Cardenas MB. Universal relationship between viscous and inertial permeability of geologic porous media. Geophys Res Lett. 2019;46(3):1441-8.
• 11. Zhao Z, Zhou XP. Pore-scale effect on the hydrate variation and flow behaviors in microstructures using X-ray CT imaging. J Hydrol. 2020;584: 124678.
• 12. Jiang TW, Yao W, Sun XW, Qi CY, Li X, Xia KW, Zhang J, Nasseri MHB. Evolution of anisotropic permeability of fractured sandstones subjected to true-triaxial stresses during reservoir depletion. J Petrol Sci Eng. 2021;200: 108251.
• 13. Lin QB, Cao P, Cao RH, Lin H, Meng JJ. Mechanical behavior around double circular openings in a jointed rock mass under uniaxial compression. Arch Civ Mech Eng. 2020;20(1):1-18.
• 14. Nordlund M, Penha DJL, Stolz S, Kuczaj A, Winkelmann C, Geurts BJ. A new analytical model for the permeability of anisotropic structured porous media. Int J Eng Sci. 2013;68:38-60.
• 15. Liu WC, Yao J, Cheng ZX, Zhu WY. An exact analytical solution of moving boundary problem of radial fluid flow in an infinite low-permeability reservoir with threshold pressure gradient. J Petrol Sci Eng. 2019;175:9-21.
• 16. Yu BC, Zhao HG, Tian JB, Liu C, Song ZL, Liu YB, Li MH. Modeling study of sandstone permeability under true triaxial stress based on backpropagation neural network, genetic programming, and multiple regression analysis. J Nat Gas Sci Eng. 2021;86: 103742.
• 17. Chao ZM, Ma GT, Wang M. Experimental and numerical modelling of the mechanical behaviour of low-permeability sandstone considering hydromechanics. Mech Mater. 2020;148: 103454.
• 18. Xiao WJ, Zhang DM, Wang XJ. Experimental study on progressive failure process and permeability characteristics of red sandstone under seepage pressure. Eng Geol. 2020;265: 105406.
• 19. Wang FY, Cheng H. Effect of tortuosity on the stress-dependent permeability of tight sandstones: analytical modelling and experimentation. Mar Pet Geol. 2020;120: 104524.
• 20. Hangi M, Wheeler V, Lipińskia W. Numerical determination of permeability and Forchheimer coefficient in dual-scale porous media. Int Commun Heat Mass Transfer. 2021;122: 105089.
• 21. Yang T, Liu HY, Tang CA. Scale effect in macroscopic permeability of jointed rock mass using a coupled stress-damage-flow method. Eng Geol. 2017;228:121-36.
• 22. Bandyopadhyay K, Mallik J, Shajahan R, Agarwal N. Closing the gap between analytical and measured coal permeability. Fuel. 2020;281: 118752.
• 23. Alpak FO, Berg S, Zacharoudiou I. Prediction of fluid topology and relative permeability in imbibition in sandstone rock by direct numerical simulation. Adv Water Resour. 2018;122:49-59.
• 24. Andra H, Combaret N, Dvorkin J, Glatt E, Han J, Kabel M, Keehm Y, Krzikalla F, Lee M, Madonna C, Marsh M, Mukerji T, Saenger EH, Sain R, Saxena N, Ricker S, Wiegmann A, Zhan X. Digital rock physics benchmarks-part II: computing effective properties. Comput Geosci. 2013;50:33-43.
• 25. Buckman J, Chudi O, Lewis H, Couples G, Huang TS, Jiang ZY. Synthetic digital rock methods to estimate the impact of quartz cementation on porosity & permeability: assessment of Miocene turbidite sandstones and prediction of deeper Oligocene sandstones, Niger Delta Basin. J Petrol Sci Eng. 2020;184: 106538.
• 26. Zhao Z, Zhou XP. 3D digital analysis of cracking behaviors of rocks through 3D reconstruction model under triaxial compression. J Eng Mech. 2020;146(8):04020084.
• 27. Chen M, Yang SQ, Ranjith PG, Zhang YC. Cracking behavior of rock containing non-persistent joints with various joints inclinations. Theoret Appl Fract Mech. 2020;109: 102701.
• 28. Zhou XP, Zhao Z, Li Z. Cracking behaviors and hydraulic properties evaluation based on fractural microstructure models in geomaterials. Int J Rock Mech Min Sci. 2020;130: 104304.
• 29. Zhou XP, Zhao Z. Digital evaluation of nanoscale-pore shale fractal dimension with microstructural insights into shale permeability. J Nat Gas Sci Eng. 2020;75: 103137.
• 30. Zhao Z, Zhou XP. Digital microstructure insights to phase evolution and thermal flow properties of hydrates by X-ray computed tomography. Sci China Technol Sci. 2020;64(1):187-202.
• 31. Chen JW, Zhou XP, Zhou LS, Berto F. Simple and effective approach to modeling crack propagation in the framework of extended finite element method. Theoret Appl Fract Mech. 2020;106: 102452.
• 32. Shou YD, Zhou XP. A coupled hydro-mechanical non-ordinary state-based peridynamics for the fissured porous rocks. Eng Anal Boundary Elem. 2020;213:133-46.
• 33. Ni HY, Liu JF, Huang BX, Pu H, Meng QB, Wang YG, Sha ZH. Quantitative analysis of pore structure and permeability characteristics of sandstone using SEM and CT images. J Nat Gas Sci Eng. 2021;88: 103861.
• 34. Hu C, Liu XL, Jia YG, Duan ZB. Permeability anisotropy of methane hydrate-bearing sands: Insights from CT scanning and pore network modelling. Comput Geotech. 2020;123: 103568.
• 35. Dakhelpour-Ghoveifel J, Shahverdi H. Prediction of gas-oil capillary pressure of carbonate rock using pore network modeling. J Petrol Sci Eng. 2020;195: 107861.
• 36. Tembely M, AlSumaiti AM, Alameri WS. Machine and deep learning for estimating the permeability of complex carbonate rock from X-ray micro-computed tomography. Energy Rep. 2021;7:1460-72.
• 37. Hou P, Liang X, Gao F, Dong JB, He J, Xue Y. Quantitative visualization and characteristics of gas flow in 3D pore-fracture system of tight rock based on lattice Boltzmann simulation. J Nat Gas Sci Eng. 2021;89: 103867.
• 38. Cnudde V, Boone MN. High-resolution X-ray computed tomography in geosciences: a review of the current technology and applications. Earth-Sci Rev. 2013;123:1-17.
• 39. Beckingham LE, Peters CA, Um W, Jonesc KW, Lindquistd WB. 2D and 3D imaging resolution trade-offs in quantifying pore throats for prediction of permeability. Adv Water Resour. 2013;62:1-12.
• 40. Shou YD, Zhao Z, Zhou XP. Sensitivity analysis of segmentation techniques and voxel resolution on rock physical properties by X-ray imaging. J Struct Geol. 2020;133: 103978.
• 41. Li J, Hussaini SR, Dvorkin J. Permeability-porosity relations from single image of natural rock: subsampling approach. J Petrol Sci Eng. 2020;194: 107541.
• 42. Meyer F. Topographic distance and watershed lines. Signal Process. 1994;38(1):113-25.
• 43. Sedgewick R. Algorithms in C. 3rd ed. New York: Addison-Wesley; 1998. p. 11-20.

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)