Calibrating Lattice Boltzmann flow simulations and estimating uncertainty in the permeability of complex porous media

Hosa, Aleksandra; Curtis, Andrew; Wood, Rachel

doi:10.1016/j.advwatres.2016.04.020

Cited by 18 publications

(9 citation statements)

References 45 publications

(76 reference statements)

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“…This analysis indicates that the same intrinsic permeability should be obtained with different choice of model parameters at the Navier-Stokes level. However, both τ and N grid can affect calculated value of permeability as previously reported (Ferréol and Rothman, 1995;Pan et al, 2006;Hosa et al, 2016;Prestininzi et al, 2016) and demonstrated in the above 2D case. As Fig.…”

Section: Resultsmentioning

confidence: 83%

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On the unintentional rarefaction effect in LBM modeling of intrinsic permeability

Li¹,

Ho²,

Wu³

et al. 2018

Adv. Geo-Energy Res.

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Lattice Boltzmann method (LBM) has been applied to predict flow properties of porous media including intrinsic permeability, where it is implicitly assumed that the LBM is equivalent to the incompressible (or near incompressible) Navier-Stokes equation. However, in LBM simulations, high-order moments, which are completely neglected in the Navier-Stokes equation, are still available through particle distribution functions. To ensure that the LBM simulation is correctly working at the Navier-Stokes hydrodynamic level, the high-order moments have to be negligible. This requires that the Knudsen number (Kn) is small so that rarefaction effect can be ignored. In our study, we elaborate this issue in LBM modeling of porous media flows, which is particularly important for gas flows in ultra-tight media. The influence of Reynolds number (Re) on the intrinsic permeability is also discussed.

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Section: Resultsmentioning

confidence: 83%

“…intrinsic permeability (Ferréol and Rothman, 1995;Spaid and Phelan, 1997;Pan et al, 2006;Hosa et al, 2016;Prestininzi et al, 2016). The standard LBM is regarded as an alternative method to computational fluid dynamics (CFD), equivalent to solving the incompressible (or near incompressible) NavierStokes equation.…”

Section: Introductionmentioning

confidence: 99%

On the unintentional rarefaction effect in LBM modeling of intrinsic permeability

Li¹,

Ho²,

Wu³

et al. 2018

Adv. Geo-Energy Res.

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“…Pore structure plays an important role in the properties of porous media. However, due to the complexity of microstructure and irregularity of pore structure, it is always a challenging task to predict permeability [4][5][6][7][8]. The microstructures of oolitic graintone and dolograinstone can be found in previous study [9,10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Porous Media Permeability Model Based on Fractal Theory and Ideal Particle Pore-Space Geometry Assumption

Wang

Zhao

et al. 2020

Energies

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In this paper, a novel porous media permeability model is established by using particle model, capillary bundle model and fractal theory. The three-dimensional irregular spatial characteristics composed of two ideal particles are considered in the model. Compared with previous models, the results of our model are closer to the experimental data. The results show that the tortuosity fractal dimension is negatively correlated with porosity, while the pore area fractal dimension is positively correlated with porosity; The permeability is negatively correlated with the tortuosity fractal dimension and positively correlated with the integral fractal dimension of pore surface and particle radius. When the tortuosity fractal dimension is close to 1 and the pore area fractal dimension is close to 2, the faster the permeability changes, the greater the impact. Different particle arrangement has great influence on porous media permeability. When the porosity is close to 0 and close to 1, the greater the difference coefficient is, the more the permeability of different arrangement is affected. In addition, the larger the particle radius is, the greater the permeability difference coefficient will be, and the greater the permeability difference will be for different particle arrangements. With the increase of fractal dimension, the permeability difference coefficient first decreases and then increases. When the pore area fractal dimension approaches 2, the permeability difference coefficient changes faster and reaches the minimum value, and when the tortuosity fractal dimension approaches 1, the permeability difference coefficient changes faster and reaches the minimum value. Our research is helpful to further understand the connotation of medium transmission in porous media.

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“…Using the measured rock porosity, it is possible to determine a threshold in the grayscale, to discriminate between pores and rock, and use this threshold to filter the attenuation values of the X-ray microtomography image to generate a binary (0 for rock site, 1 for pore site) representation of the rock and the pore space [25]. The binarization process defines all voxels with monochromatic value less than a threshold to be pore space or void, and the rest to be solid and consequently the segmented porosity monotonously decreases with the threshold value [26]. In a combination with the breakthrough in computational methods, we can make direct flow simulations through the pore space of real rock samples to calculate their permeabilities.…”

Section: Introductionmentioning

confidence: 99%

Consistent prediction of absolute permeability in carbonates without upscaling

Khodja

Hussaini

et al. 2020

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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We describe a study focused on the absolute permeability of reservoir carbonate rocks from the Middle East and involving comparison of experimental data and numerical estimates obtained by combining digital-rock and Lattice-Boltzmann Methods (LBM). The question of the “representativeness” of the site at which the simulation is performed is addressed as follows. First, a low-resolution, CT X-ray scan of the core plug is performed to identify regions of large porosity (millimeter-sized vugs, etc.). These regions are then avoided to postselect smaller sites (site volume ~ 1 mm3) which are to be scanned at higher resolutions (voxel size < dominant pore-throat size of the core plug). A “representativeness” criterion based on an empirically-inspired “representativeness” measure (R-measure) is used to eliminate those sites for which R > b, where b is an upper bound (typically, b = 1). Essentially, the measure estimates how well the postselected sites capture the experimental porosity and the dominant pore-throat size of the core plug. This leads to a small set of sites for which the simulations are both computationally manageable and yield a reasonable estimate of the permeability: the experimental and predicted values differ by a factor of about 3 on average, which is a particularly significant result given the challenging heterogeneous pore space of carbonate samples. We believe the suggested methodology to be an adequate and practical way to circumvent upscaling.

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Calibrating Lattice Boltzmann flow simulations and estimating uncertainty in the permeability of complex porous media

Cited by 18 publications

References 45 publications

On the unintentional rarefaction effect in LBM modeling of intrinsic permeability

On the unintentional rarefaction effect in LBM modeling of intrinsic permeability

A Novel Porous Media Permeability Model Based on Fractal Theory and Ideal Particle Pore-Space Geometry Assumption

Consistent prediction of absolute permeability in carbonates without upscaling

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