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RESEARCH PRODUCT
Digital rock physics, chemistry, and biology: challenges and prospects of pore-scale modelling approach
Saeid SadeghnejadFrieder EnzmannMichael Kerstensubject
PhysicsChemistryFlow (psychology)Direct numerical simulation010501 environmental sciencesBiology010502 geochemistry & geophysics01 natural sciencesPollutionCharacterization (materials science)Permeability (earth sciences)Geochemistry and PetrologyVoid (composites)Fluid dynamicsEnvironmental ChemistryPorosityBiological system0105 earth and related environmental sciencesNetwork modeldescription
Abstract Conventional and unconventional hydrocarbon rocks have complicated pore structures with heterogeneities distributed over various length scales (from nanometre to centimetre or even larger scales). Effective characterization of the properties of such rocks based on their digital twins is a challenging task. Digital rock physics (DRP) can be used to quantify the structural and morphological parameters of rocks directly and predict flow transport properties at the pore scale. Digital rock chemistry (DRC) or biology (DRB) applies when the changes in pore structures are due to interaction with solutes or microbial activities. Fluid–rock interactions or microbial activities complicate fluid flow by introducing new heterogeneities at the pore scale. DRP/DRC/DRB modelling approaches can achieve an understanding of spatiotemporal porosity/permeability relationships that develop at the pore scale during reactive flow or microbial activities. There has recently been a surge in publications on the modelling of pore-scale models. However, this approach has many challenges, from theoretical issues such as how best to combine rock properties at different resolutions to technical challenges such as performing simulations using pore-scale models that contain too many pores and throats. Multiscale pore modelling approaches are generally categorized using the number of scales represented, the minimum being a dual-scale pore model, in which both void and porous voxels (e.g., unresolved pores) are modelled simultaneously. Two common approaches that can be implemented to predict rocks' behaviour across different scales are direct numerical simulation (DNS) and pore network model (PNM). Multiscale PNMs received more attention because of their ability to model a wide pore size distribution at various scales, while multiscale DNS requires resource-demanding Navier-Stokes-Brinkman models in GB voxel space. An overview of the recent progress and challenges involved in modelling digital rock physics, chemistry, and biology of multiscale systems is presented here.
year | journal | country | edition | language |
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2021-08-01 | Applied Geochemistry |