journal article·2025-07-03Open access

A Comparative Study of Three-Dimensional Flow Based, Geometric, and Empirical Tortuosity Models in Carbonate and Sandstone Reservoirs

Benedicta Loveni Melkisedek, Yoevita Emeliana, Irwan Ary Dharmawan

Applied Sciences· Volume 15· Issue 13

Abstract

Understanding tortuosity is essential for accurately modeling fluid flow in complex porous media, particularly in the sub-surface reservoir rock; therefore, tortuosity estimation was evaluated using three approaches: Streamline streamline simulations via the Lattice Boltzmann Method (LBM), geometric pathfinding using Dijkstra’s algorithm, and empirical modeling based on pore-structure parameters. The analysis encompassed 1963 micro-Computed Tomography (micro-CT) images of Brazilian pre-salt carbonate and sandstone samples, with the effective porosity extracted from LBM velocity fields, isolating flow-contributing pores, establishing streamline tortuosity as the reference standard. Sandstones exhibited relatively narrow tortuosity ranges (Dijkstra: 1.29–1.75; Streamline: 1.18–2.61; Empirical: 1.18–4.42), whereas carbonates display greater heterogeneity (Dijkstra: 1.00–3.18; Streamline: 1.00–3.68; Empirical: 1.59–4.93). Model performance assessed using the corrected Akaike Information Criterion (AICc) revealed that the best agreement with the data was achieved by the semi-empirical model incorporating coordination number and minimum throat length (AICc = −113.11), followed by the Dijkstra-based geometrical approach (−99.74) and the empirical porosity-based model (202.23). There was a nonlinear inverse correlation between tortuosity and effective porosity across lithologies. This comprehensive comparison underscores the importance of incorporating multiple pore-scale parameters for robust tortuosity prediction, improving the understanding of flow behavior in heterogeneous reservoir rocks.
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Research context

OpenAlex topics: Hydraulic Fracturing and Reservoir Analysis · Drilling and Well Engineering · Seismic Imaging and Inversion Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Geophysics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jln. Ir. Soekarno km. 21, Jatinangor, Sumedang 45363, Indonesia

References (45)

Show source-provided references
1. Machine learning prediction of tortuosity in digital rock10.25299/jgeet.2023.8.02-2.13875 ↗
2. Estimating geometric tortuosity of saturated rocks from micro-ct images using percolation theory10.1007/s11242-024-02085-w ↗
3. Tortuosity of pore channels in tight rocks as a key parameter in fluid flow ability10.1007/s11600-023-01262-7 ↗
4. Permeability description by characteristic length tortuosity, constriction and porosity10.1007/s11242-014-0307-6 ↗
5. Yang, S., Yang, H., Peng, X., Lan, X., Yang, Y., Zhao, Y., Zhang, K., and Chen, H. (2023). Research of influencing factors on permeability for carbonate rocks based on lbm simulation: A case study of low permeability gas reservoir of Sinian Dengying formation in Sichuan basin. Front. Earth Sci., 11.10.3389/feart.2023.1091431 ↗
6. Cheng, Y., Luo, X., Zhuo, Q., Gong, Y., and Liang, L. (2024). Description of pore structure of carbonate reservoirs based on fractal dimension. Chem. Process. Syst., 12.10.3390/pr12040825 ↗
7. Zhang, Y., Tian, J., Zhang, X., Li, J., Liang, Q., and Zheng, X. (2022). Diagenesis evolution and pore types in tight sandstone of Shanxi formation reservoir in Hangjinqi area, ordos basin, northern China. Energies, 15.10.3390/en15020470 ↗
8. Diagenetic control of reservoir performance and its implications for reservoir prediction in jinci sandstone of upper carboniferous in the middle east ordos basin10.1021/acsomega.2c03542 ↗
9. Diagenesis and its impact on reservoir quality for the Chang 8 oil group tight sandstone of the Yanchang formation (upper Triassic) in southwestern ordos basin, China10.1007/s13202-017-0340-4 ↗
10. Petroleum reservoir quality prediction: Overview and contrasting approaches from sandstone and carbonate communities10.1144/SP435.21 ↗
11. Petunin, V.V., and Tutuncu, A.N. (2011, January 15–17). Porosity and permeability changes in sandstones and carbonates under stress and their correlation to rock texture. Proceedings of the SPE Canada Unconventional Resources Conference, Calgary, AB, Canada.10.2118/147401-MS ↗
12. The challenging carbonates from the pre-salt reservoirs offshore Brazil: Facies, palaeoenvironment, and diagenesis10.1016/j.jsames.2021.103202 ↗
13. Cataldo, R., Leite, E., Rebelo, T., and Mattos, N. (2022). Depth-variant pore type modeling in a pre-salt carbonate field offshore Brazil. Front. Earth Sci., 10.10.3389/feart.2022.1014573 ↗
14. Unlocking the properties of a presalt carbonate reservoir offshore Brazil with facies-constrained geostatistical inversion10.1190/tle41120832.1 ↗
15. Petrophysical correlations for the permeability of coquinas (carbonate rocks)10.1007/s11242-020-01474-1 ↗
16. Sedimentology and petrophysical analysis of pre-salt lacustrine carbonate reservoir from the santos basin, southeast Brazil10.1007/s00531-020-01932-7 ↗
17. Deep-burial hydrothermal alteration of the pre-salt carbonate reservoirs from northern Campos basin, offshore Brazil: Evidence from petrography, fluid inclusions, sr, c, and o isotopes10.1016/j.marpetgeo.2019.104143 ↗
18. Gomes, J.P. (2021). Facies, Diagenesis and Cycles Within the Pre-Salt Deposits from Barra Velha Formation, Santos Basin, Offshore Brazil. [Doctoral Thesis, University of Bristol].
19. Garcia, R., Mohammadizadeh, S., Avansi, M., Basilici, G., Bomfim, L., Cunha, O., Soares, M., Mesquita, A., Mahjour, S., and Vidal, A. (2024). Geological insights from porosity analysis for sustainable development of santos basin’s presalt carbonate reservoir. Sustainability, 16.10.3390/su16135730 ↗
20. Tortuosity: A guide through the maze10.1144/GSL.SP.1997.122.01.18 ↗
21. Multiscale method for characterization of porous microstructures and their impact on macroscopic effective permeability10.1002/nme.3220 ↗
22. Akmal, F., Nurcahya, A., Alexandra, A., Yulita, I.N., Kristanto, D., and Dharmawan, I.A. (2024). Application of machine learning for estimating the physical parameters of three-dimensional fractures. Appl. Sci., 14.10.3390/app142412037 ↗
23. A study of geometrical effects on permeability estimation in three-dimensional fractures using the lattice boltzmann method10.37934/cfdl.15.12.118 ↗
24. Estimating two-dimensional physical parameters of digital rocks using deep learning10.1088/1402-4896/ad9d08 ↗
25. MPLBM-UT: Multiphase LBM library for permeable media analysis10.1016/j.softx.2022.101097 ↗
26. Nurcahya, A., Alexandra, A., Akmal, F., and Dharmawan, I. (2024). The lattice boltzmann method and image processing techniques for effective parameter estimation of digital rock. Appl. Sci., 14.10.3390/app14177509 ↗
27. Graczyk, K.M., and Matyka, M. (2020). Predicting porosity, permeability, and tortuosity of porous media from images by deep learning. Sci. Rep., 10.10.1038/s41598-020-78415-x ↗
28. Tortuosity-porosity relation in porous media flow10.1103/PhysRevE.78.026306 ↗
29. A study of transfer learning in digital rock properties measurement10.1088/2632-2153/acf117 ↗
30. Avila, J., Pagalo, J., and Espinoza-Andaluz, A. (2022). Evaluation of geometric tortuosity for 3d digitally generated porous media considering the pore size distribution and the a-star algorithm. Sci. Rep., 12.10.1038/s41598-022-23643-6 ↗
31. Effect of pore-scale heterogeneity on scale-dependent permeability: Pore-network simulation and finite-size scaling analysis10.1029/2021WR030664 ↗
32. Permeability and pore connectivity: A new model based on network simulations10.1029/2010JB007444 ↗
33. Enhanced understanding of fluid flow and effective properties in three dimensional porous rock using lattice boltzmann simulation and image-based correlation studies10.1063/5.0268487 ↗
34. 3D FEM model to simulate Brownian motion inside trabecular tissue from human femoral head10.1080/21681163.2021.1956370 ↗
35. Vidal, A., Menezes dos Anjos, C.E., Medeiros, L., Surmas, R., Neta, A., Evsukoff, A., and Vargas, J. (2025). 16 Brazilian Pre-Salt Carbonates: Multi-Resolution Micro-ct Images, Digital Rocks Portal.
36. Neumann, R., Andreeta, M., and Lucas-Oliveira, E. (2025). 11 Sandstones: Raw, Filtered and Segmented Data, Digital Rocks Portal.
37. Ashirbekov, A., Kabdenova, B., Monaco, E., and Rojas-Solorzano, L.R. (2021). Equation of states crossover enhancement of pseudopotential lattice boltzmann modelling of CO2 flow in homogeneous porous media. Fluids, 6.10.3390/fluids6120434 ↗
38. Yu, Y., Qin, Z., Chen, S., Shu, S., and Yuan, H.-Z. (2023). Two-relaxation-time regularized lattice boltzmann model for navier-stokes equations. arXiv.10.2139/ssrn.4731725 ↗
39. Two-relaxation-time regularized lattice boltzmann model for convection-diffusion equation with spatially dependent coefficients
40. 3-d microstructure analysis of fuel cell materials: Spatial distributions of tortuosity, void size and diffusivity10.1149/2.068203jes ↗
41. Percolation theory generates a physically based description of tortuosity in saturated and unsaturated porous media10.2136/sssaj2013.01.0089 ↗
42. A new look at statistical model identification10.1109/TAC.1974.1100705 ↗
43. Regression and time series model selection in small samples10.1093/biomet/76.2.297 ↗
44. Scale dependence of tortuosity in soils under contrasting cultivation conditions10.1016/j.still.2023.105788 ↗
45. Simulations of single-fluid flow in porous media10.1142/S0129183198001369 ↗