Toward direct pore-scale modeling of three-phase displacements

Mohammadmoradi, Peyman; Kantzas, Apostolos

doi:10.1016/j.advwatres.2017.10.010

Cited by 17 publications

(5 citation statements)

References 33 publications

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“…Such a tool is crucial to understand fully the underlying mechanisms of non-aqueous phase liquid (e.g., hydrocarbon, chlorinated solvents) trapped in the unsaturated zone by capillary effects and to propose innovative remediation strategies. In the literature, Bayestehparvin et al (2015) use a Volume-of-Fluid approach, Helland et al (2017) and Mohammadmoradi and Kantzas (2017) use quasi-static displacement using a Level-Set method, Tartakovsky and Panchenko (2016) use Smooth Particle Hydrodynamics, Dinariev and Evseev (2016) use a phase-field method and van Kats and Egberts (1999) and Jiang and Tsuji (2017) use a lattice-Boltzmann method to investigate three-phase Navier-Stokes flow at pore scale. The development of efficient three-phase flow simulators at the pore-scale is still under development and microfluidic experiments will help to assess the robustness of the computational models.…”

Section: Three-phase Flowmentioning

confidence: 99%

Computational Microfluidics for Geosciences

2021

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Computational microfluidics for geosciences is the third leg of the scientific strategy that includes microfluidic experiments and high-resolution imaging for deciphering coupled processes in geological porous media. This modeling approach solves the fundamental equations of continuum mechanics in the exact geometry of porous materials. Computational microfluidics intends to complement and augment laboratory experiments. Although the field is still in its infancy, the recent progress in modeling multiphase flow and reactive transport at the pore-scale has shed new light on the coupled mechanisms occurring in geological porous media already. In this paper, we review the state-of-the-art computational microfluidics for geosciences, the open challenges, and the future trends.

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Section: Three-phase Flowmentioning

confidence: 99%

Computational Microfluidics for Geosciences

2021

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“…Assuming the spherical pore body shapes, the location of the pores and the corresponding radiuses of the spheres were determined from the medium using the expanding sphere method. Subsequently, filling‐grain sizes were extracted from the pore size distribution data obtained in the previous step . Random filling‐grains were then chosen and placed in adequate void spaces until no more grains were available to fill the void.…”

Section: Fluid Flow Propertiesmentioning

confidence: 99%

“…Pore scale modelling methods have been studied and developed for decades starting with Fatt's network model, which was developed in 1951 . Throughout the years, more advanced pore scale flow simulation methods such as random and dynamic network modelling, morphological modelling, and direct methods such as computational fluid dynamics (CFD) were developed that can calculate single‐phase and two‐phase flow properties in complex geometries . Such models can predict petrophysical (eg, porosity, permeability, and formation factor) and flow properties (eg, capillary pressure, and relative permeability curves) inside a porous medium taking into account complex physical phenomenon occurring at such scale.…”

Section: Introductionmentioning

confidence: 99%

Scale‐up of pore‐level relative permeability from micro‐ to macro‐scale

Bashtani

Kantzas

2020

Can J Chem Eng

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Scaling up relative permeability curves of wetting and nonwetting phase of drainage and imbibition processes from pore scale to macro scale is a challenge. A new method for scaling up relative permeability from micro‐ to macro‐scale is proposed based on electrical analogy of multiphase fluid flow at pore scale. The method is validated against four synthetic porous media generated using homogeneous and heterogeneous grain size distributions, each of which were cut into eight sub‐segments. Single‐phase and two‐phase flow properties were calculated for the main blocks and the subsequent sub‐segments using random network modelling technique. Then, the subsegments were randomly distributed in space to reconstruct the main blocks and the proposed scale‐up method was employed to calculate the relative permeability curves of the reconstructed blocks. Results were compared to the ones obtained directly from the network model of the original blocks and show good agreement between the calculated and scaled‐up relative permeability curves of primary drainage and secondary imbibition. Furthermore, the model was tested on real media. Eight network models were extracted from pore size distribution of core samples obtained from the Green River basin located in the Mesaverde Formation. Flow properties obtained from the network models were validated against experimental data and good agreement was observed. These network models show a higher level of heterogeneity at micro‐scale. Then, the scale‐up methods were employed in order to reconstruct the macro‐scale sample and predict its properties. Scale‐up methods successfully predict the single‐phase and two‐phase flow properties of the sample.

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“…In this section we use the pore morphological simulation algorithm to simulate pore‐level capillary‐dominant displacements directly through tomography images. For each image stack, the simulation workflow starts with segmentation and binarization and continues with the following: (1) applying expanding spheres to the binarized image to extract the pore size distribution; (2) defining connectivity and contact angle maps through the pore and matrix entities, respectively; (3) setting appropriate initial (e.g., saturating fluids and pressure) and boundary conditions (source and sink); (4) changing the invading phase pressure (drainage and imbibition) and updating the interfaces until at each pressure‐step the capillary equilibrium is reached; and (5) reporting pressure‐saturation points and extracting fluid occupancies.…”

Section: Workflow Of Numerical Simulationmentioning

confidence: 99%

Modelling shale spontaneous water intake using semi‐analytical and numerical approaches

Mohammadmoradi

Kantzas

2018

Can J Chem Eng

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Shale matrix water intake during hydraulic fracturing is considered undesirable due to the high volume of unrestrained water loss; however, it is also rewarding because it can reduce the possibility of groundwater contamination. The water intake also plays a dual role in changing the shale production performance; water imbibition into matrix pores can dramatically reduce the effective permeability and, at the same time, might enhance hydrocarbon production by creating adsorption-induced micro-fractures. Quantifying the formation intake capacity and its breadth is the key to optimizing fracturing operation, flowback, and production strategy. This work entails complementary semi-analytical and numerical analyses and investigates the effects of basic rock and fluid properties, wettability heterogeneity, and pore space connectivity on the shale imbibition characteristics. We consider a semi-analytical formulation of the spontaneous water imbibition, together with model results and validations, and try to provide a framework to link the capillary imbibition capacity/rate to lab-scale observations. The core-scale measurements provide input for a sensitivity study on the matrix imbibition capacity in six shale plays in North America. The results suggest that rock permeability, hydraulic tortuosity, and initial and residual hydrocarbon saturations are among the most influential factors on the spontaneous water intake during shut-in periods. Direct quasi-static simulations are then conducted through a submicron tomography image of the Eagle Ford shale, and two-phase pore-level fluid occupancies are reconstructed during spontaneous and forced imbibition processes. According to the numerical results, the presence of continuous organic matter laminae can lower the destructive effects of water imbibition on the hydrocarbon permeability.

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Toward direct pore-scale modeling of three-phase displacements

Cited by 17 publications

References 33 publications

Computational Microfluidics for Geosciences

Computational Microfluidics for Geosciences

Scale‐up of pore‐level relative permeability from micro‐ to macro‐scale

Modelling shale spontaneous water intake using semi‐analytical and numerical approaches

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