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.

Fractures, vugs, and pores constitute the main pore space in carbonate reservoirs. The associated pore structure—which is of key importance in terms of hydrocarbon production and fluid flow—varies with effective stress. However, there is a serious lack of data with regard to how precisely the pore morphology changes as a function of effective stress; we thus carried out in situ loading‐unloading experiments (up to 20 MPa effective stress) where two carbonate samples (fractured and vuggy) were examined with X‐ray computed tomography at high resolution in 3‐D. The results showed that after loading, porosity decreased exponentially, followed by an increase during unloading where it did not recover to its initial value. This was mainly because of the stress effect on large pore space (i.e., fractures and vugs). For fractured carbonate, the unrecovered porosity can be linked to similar reduction of the surface area and the average aperture of the fracture. Clearly, the changes in pore morphology were more significant in the fractured carbonate (including extension, connection, and disconnection of fractures) during both loading and unloading, while the vuggy carbonate experienced irreversible structural damage. The vuggy carbonate has bigger porosity variation than fractured carbonate to the mechanical loading‐unloading cycle. This work thus demonstrates how carbonate pore morphology changes with depth (higher effective stresses are encountered deeper in the reservoir) or during production (with hydrocarbon depletion the effective stress increases).

Wavenumber, group velocity, phase velocity, and frequency-dependent attenuation characterize the propagation of surface waves in dispersive, attenuating media. We use a mathematical model based on the generalized [Formula: see text] transform to simultaneously estimate these characteristic parameters for later use in joint inversion for near-surface shear wave velocity. We use a scaling factor in the generalized S transform to enable the application of the method in a highly dispersive medium. We introduce a cost function in the [Formula: see text]-domain to estimate an optimum value for the scaling factor. We also use the cost function to generalize the application of the method for noisy data, especially data with a low signal-to-noise ratio at low frequencies. In that case, the estimated wavenumber is perturbed. As a solution, we estimate wavenumber perturbation by minimizing the cost function, using Simulated Annealing. We use synthetic and real data to show the efficiency of the method for the estimation of the propagation parameters of highly dispersive and noisy media.

Purpose Thermal conduction anisotropy, which is defined by the dependency of thermal conductivity on direction, is an important parameter in many engineering and research studies such as the design of nuclear waste depositional sites. In this context, the authors aim to investigate the effect of grain shape in thermal conduction anisotropy using pore scale modeling that utilizes real shapes of grains, pores and throats to characterize petrophysical properties of a porous medium. Design/methodology/approach The authors generalize the swelling circle approach to generate porous media composed of randomly arranged but regularly oriented elliptical grains at various grain ratios and porosities. Unlike previous studies that use fitting parameters to capture the effect of grain–grain thermal contact resistance, the authors apply roughness to grains’ surface. The authors utilize Lattice Boltzmann method to solve steady state heat conduction through medium. Findings Based on the results, when the temperature field is not parallel to either major or minor axes of grains, the overall heat flux vector makes a “deviation angle” with the temperature field. Deviation angle increases by augmenting the ratio of thermal conductivities of solid to fluid and the aspect ratios of grains. In addition, the authors show that porosity and surface roughness can considerably change the anisotropic properties of a porous medium whose grains are elliptical in shape. Originality/value The authors developed an algorithm for generation of non-circular-based porous medium with a novel approach to include grain surface roughness. In previous studies, the effect of grain contacts has been simulated using fitting parameters, whereas in this work, the authors impose the roughness based on the its fractal geometry.

We have developed the slant stacking approach in the generalized S-transform (GST) domain of seismic data for the estimation of the group velocity of the multimodal surface wave. We used two versions of the GST. The constant-scale GST uses a constant scaling factor in the Gaussian window to control the spectral time-frequency localization. We found that a smaller scaling factor should be chosen for the lowfrequency surface wave, whereas for higher frequencies, a larger scaling factor should be chosen. Therefore, the transform exhibits a trade-off in the group velocity resolution of low frequencies with small values of the scaling factor and the group velocity resolution of high frequencies with large values of the scaling factor. The modified S-transform (MST), another version of the GST used in this study, enhanced the time-frequency resolution by projecting the frequency into a linear frequency function in the Gaussian window. This property allowed us to estimate the group velocity for a broad range of frequencies. We demonstrated the robustness of the MST for the estimation of the group velocity by synthetic and real data examples.