Thermal conductivity of granular porous media: A pore scale modeling approach
Source abstract
Abstract
Pore scale modeling method has been widely used in the petrophysical studies to estimate macroscopic properties (e.g. porosity, permeability, and electrical resistivity) of porous media with respect to their micro structures. Although there is a sumptuous literature about the application of the method to study flow in porous media, there are fewer studies regarding its application to thermal conduction characterization, and the estimation of effective thermal conductivity, which is a salient parameter in many engineering surveys (e.g. geothermal resources and heavy oil recovery). By considering thermal contact resistance, we demonstrate the robustness of the method for predicting the effective thermal conductivity. According to our results obtained from Utah oil sand samples simulations, the simulation of thermal contact resistance is pivotal to grant reliable estimates of effective thermal conductivity. Our estimated effective thermal conductivities exhibit a better compatibility with the experimental data in companion with some famous experimental and analytical equations for the calculation of the effective thermal conductivity. In addition, we reconstruct a porous medium for an Alberta oil sand sample. By increasing roughness, we observe the effect of thermal contact resistance in the decrease of the effective thermal conductivity. However, the roughness effect becomes more noticeable when there is a higher thermal conductivity of solid to fluid ratio. Moreover, by considering the thermal resistance in porous media with different grains sizes, we find that the effective thermal conductivity augments with increased grain size. Our observation is in a reasonable accordance with experimental results. This demonstrates the usefulness of our modeling approach for further computational studies of heat transfer in porous media.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Enhanced Oil Recovery Techniques · Hydrocarbon exploration and reservoir analysis · Geophysical and Geoelectrical Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Michigan Technological University 1 Geological and Mining Engineering and Sciences, , Houghton, MI 49931, United States
University of Calgary 2 Chemical and Petroleum Engineering Department, , Calgary, T2N 1N4, Canada
Funding
Natural Sciences and Engineering Research Council of Canada
References (63)
Show source-provided references
1. Theoretical studies on the gravity drainage of heavy oil during in-situ steam heating10.1002/cjce.5450590407 ↗
2. Computing thermal conductivities of rocks from chips and conventional specimen10.1029/JZ070i020p05227 ↗
3. An improved method of computing the thermal conductivity of fluid-filled sedimentary rocks10.1190/1.1440596 ↗
4. Two effective thermal conductivity models for porous media with hollow spherical agglomerates10.1007/s10765-006-0032-7 ↗
5. An effective thermal conductivity model of geological porous media for coupled thermo-hydro-mechanical systems with multiphase flow10.1016/j.ijrmms.2009.04.010 ↗
6. Analysis of conductive and convective heat transfer in a sedimentary basin, demonstrated for the Rheingraben10.1111/j.1365-246X.1990.tb00693.x ↗
7. The Measuremenot f Thermal Conductivityo f Deep-Sea Sediments by a Needle-Probe Method10.1029/JZ064i010p01557 ↗
8. A steady-state method for the rapid measurement of the thermal conductivity of rocks10.1088/0950-7671/34/5/304 ↗
9. Characterization of rock thermal conductivity by high-resolution optical scanning. 28 (2)10.1016/S0375-6505(99)00007-3 ↗
10. Thermal conductivity of porous media10.1063/1.1728419 ↗
11. Predicting thermal conductivities of formations from other known properties10.2118/4171-PA ↗
12. Prediction of thermal conductivity in rocks from other physical parameters and from standard geophysical well logs
13. Measurements of specific heat, thermal conductivity and thermal diffusivity of Utah tar sands10.1016/0016-2361(85)90283-2 ↗
14. Thermal conductivity estimation in sedimentary basins10.1016/0040-1951(94)00225-X ↗
15. Thermal Conductivities of Argillaceous Sediments
16. The effect of grain size on thermal conductivity of quartz sands and silts10.1144/petgeo.4.2.165 ↗
17. 1993a, Network Model Evaluation of Permeability and Spatial Correlation in a Real Random Sphere Packing10.1007/BF00614635 ↗
18. Effect of multiphase fluid saturation on the thermal conductivity of geologic media
19. Evaluation of effective thermal conductivity from the structure of a packed bed10.1016/S0009-2509(99)00125-6 ↗
20. An analysis of the influence of material structure on the effective thermal conductivity of theoretical porous materials using finite element simulations
21. Predictions of effective physical properties of complex multiphase materials
22. Lattice Boltzamnn simulation for thermal conductivity estimation in heterogeneous materials10.4028/www.scientific.net/DDF.283-286.364 ↗
23. The effective thermal conductivity of porous media based on statistical self-similarity10.1016/j.physleta.2009.10.015 ↗
24. Effective thermal conductivity of fluid-saturated rocks: Experiment and modeling10.1016/j.enggeo.2012.03.001 ↗
25. Temperature and Pressure Dependence of the Effective Thermal Conductivity of Geomaterials: Numerical Investigation by the Immersed Interface Method10.1155/2013/456931 ↗
26. Mesoscopic Predictions of the Effective Thermal Conductivity of Microscale Random Porous Media10.1103/PhysRevE.75.036702 ↗
27. Nonideal gas flow and heat transfer in micro- and nanochannels using the direct simulation Monte Carlo method10.1103/PhysRevE.68.046704 ↗
28. The network model of porous media (in three parts)10.2118/574-G ↗
29. Prediction of relative permeability in simple porous media10.1103/PhysRevA.46.2004 ↗
30. A new model for granular porous media: Part I. Model formulation10.1002/aic.690190110 ↗
31. 1979
32. Model of the constricted unit cell type for isotropic granular porous media10.1002/aic.690230620 ↗
33. Oil ganglion dynamics during immiscible displacement: model formulation10.1002/aic.690260315 ↗
34. Effective medium theory and network theory applied to the transport properties of rock10.1029/JB095iB05p06993 ↗
35. The future of rock physics: Computational methods vs. lab testing
36. Digital rock physics: 3D imaging of core materialand correlations to acoustic and flow properties10.1190/1.3064143 ↗
37. A passive seismic survey over a gas field: Analysis of low-frequency anomalies10.1190/1.3078402 ↗
38. Petrophysical Laboratory Measurements for Basin and Resrervoir Evaluation10.1016/0264-8172(95)00091-7 ↗
39. Extending predictive capabilities to network models10.2118/52052-PA ↗
40. Random packings and the structure of simple liquids. I. The geometry of random close packing10.1098/rspa.1970.0189 ↗
41. Transport properties of disordered continuum systems10.1103/PhysRevB.39.11965 ↗
42. Predictive pore-scale modeling of single and multiphase flow10.1007/s11242-004-5468-2 ↗
43. Connectivity of Pore Space as a Control on Two-Phase Flow Properties of Tight-Gas Sandstones10.1007/s11242-012-0017-x ↗
44. 1971
45. Pore-size dependence of the thermal conductivity of porous silicon, A phonon hydrodynamic approach10.1063/1.3462936 ↗
46. J. J. Zhao, “Thermophysical properties and heat transfer mechanisms of microsclae and nanoscale structures in aerogel-based composite insulators,” PhD Thesis, Tsinghua University, Beijing, China, 2012.
47. Mesoscopic simulation pf phase distribution effects on the effective thermal conductivity of micro-granular porous media10.1016/j.jcis.2007.03.038 ↗
48. 1999
49. A simple and efficient method for the evaluation of effective thermal conductivity of open-cell foam-like structures10.1016/j.ijheatmasstransfer.2013.07.032 ↗
50. Performance of thermal lattice Boltzmann and finite volume methods for the solution of heat conduction equation in 2D and 3D composite media with inclined and curved interfaces10.1016/j.ijheatmasstransfer.2014.05.051 ↗
51. 2004
52. Bi-CGSTAB: A fast and smoothly converging variant of Bi-CG for the solution of nonsymmetric linear systems10.1137/0913035 ↗
53. 1986
54. Conductive heat transport across rough surfaces and interfaces between two conforming media10.1016/S0017-9310(00)00225-8 ↗
55. RPredictions of effective phy sical prop erties of complex multiphas e mat erials10.1016/j.mser.2008.07.001 ↗
56. Modeling of effective thermal conductivity of consolidated porous media with different saturations: A test case of Gabbro rocks10.1007/s10765-007-0203-1 ↗
57. Review of Thermal Conductance Models for Joints Incorporating Enhancement Materials10.2514/2.6732 ↗
58. Conductive heat transport across rough surfaces and interfaces between two conforming media10.1016/S0017-9310(00)00225-8 ↗
59. Thermal Contact Conductance of Non-Flat, Rough, Metallic Coated Metals10.1115/1.1464565 ↗
60. Discrete thermal element modelling of heat conduction in particle systems: Basic formulations10.1016/j.jcp.2008.01.031 ↗
61. Discrete thermal element modelling of heat conduction in particle systems: Pipe-network model and transient analysis10.1016/j.powtec.2009.03.001 ↗
62. 1973
63. Fractal characterization and simulation of rough surfaces10.1016/0043-1648(90)90154-3 ↗