After a critical review of available pore-scale analytical and numerical approaches to estimate permeability of porous media, this paper presents a practical framework to examine and quantify the impact of variation of confining stress during the production lifecycle of a reservoir on the pore space deformation and absolute permeability of rocks formed by spherical grains.

Comparable to commonly used thin sections in CAT scan, spatial and geometrical information of sphere packings, generated using an advanced 3D distinct element method, were embedded into multiple binary images. We then constructed the corresponding pore network, employing an updated pore geometry extraction algorithm, and performed pore-scale fluid flow simulation to evaluate pore connectivity of packings of spherical grains, as imperfect-yet-effective analogues for porous rocks. The variations of pore deformation and computed permeability, with a change in confining stress applied to the packed material, were carefully tracked and systematically analyzed.

Aiming for a better pore-scale understanding of deformation effects on macro-scale transport properties, we initially identified the REV (Representative Elementary Volume) requirements for adequate representation of generated throat and body structure of pores. To obtain accurate porosity values, guidelines to process binary images with optimal resolution were provided. The workflow was then applied to simple cubic geometry and random packings of mono-dispersed particles to compute their permeabilities. The capability and limitations of developed workflow to predict the macroscopic hydraulic properties of porous media were summarized. The evolution of permeability and porosity in a contracting simple cube system under various levels of confining stress were quantitatively tracked. Lastly, the differences in behaviour between our simulation results and available analytical/numerical solutions and experimental studies in current literature were demonstrated.

Extending our modeling approach into a virtual laboratory technique helps to quantify stress-dependent variations of pore space and permeability of spherical grain packings. Given grain size distribution and stress path, modeling environment can be calibrated as a predictive tool to evaluate the behavior of porosity and permeability, hence transport qualities, of rock analogues under varying conditions of reservoir stress. Our analysis provides valuable insights in upscaling such properties for processes where dynamic geomechanical changes are significant.

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