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1. Speeding-up Simulation of Multiphase Flow in Digital Images of Heterogeneous Porous Media by Curvelet Transformation

   https://doi.org/10.1007/s11242-021-01559-5  

   Aljasmi, Abdullah; Sahimi, Muhammad (March 2021, Transport in Porous Media)

   Blunt, MJ (Ed.)

   Multiphase fluid flow in porous media is important to a wide variety of processes of fundamental scientific and practical importance. Developing a model for the pore space of porous media represents the first step for simulating such flows. With rapid increase in the computation power and advances in instrumentation and imaging processes, it has become feasible to carry out simulation of multiphase flow in two- and three-dimensional images of porous media, hence dispensing with development of models of pore space that are based on approximating their morphology. Image-based simulations are, however, very time consuming. We describe an approach for speeding-up image-based simulation of multiphase flow in porous media based on curvelet transformations, which are specifically designed for processing of images that contain complex curved surfaces. Most porous media contain correlations in their morphology and, therefore, their images carry redundant information that, in the curvelet transform space, can be removed efficiently and accurately in order to obtain a coarser image with which the computations are far less intensive. We utilize the methodology to simulate two-phase flow of oil and water in two-dimensional digital images of sandstone and carbonate samples, and demonstrate that while the results with the curvelet-processed images are as accurate as those with the original ones, the computations are speeded up by a factor of 110–150. Thus, the methodology opens the way toward achieving the ultimate goal of simulation of multiphase flow in porous media, namely, making image-based computations a standard practice. 

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2. Speeding-up image-based simulation of two-phase flow in porous media with lattice-Boltzmann method using three-dimensional curvelet transforms

   https://doi.org/10.1063/5.0065857  

   Aljasmi, Abdullah; Sahimi, Muhammad (November 2021, Physics of Fluids)

   Blunt, MJ (Ed.)

   Multiphase fluid flow in porous media is relevant to many fundamental scientific problems as well as numerous practical applications. With advances in instrumentations, it has become possible to obtain high-resolution three-dimensional (3D) images of complex porous media and use them directly in the simulation of multiphase flows. A prime method for carrying out such simulations is the color-fluid lattice Boltzmann method with multi-relaxation time (CFLB-MRT) collision operator. The simulations are, however, time consuming and intensive. We propose a method to accelerate image-based computations with the CFLB-MRT method, in which the 3D image is preprocessed by curvelet transforming it and eliminating those details that do not contribute significantly to multiphase flow. The coarsening is done by thresholding the image. After inverting the coarser image back to the real space, it is utilized in the simulation of multiphase flow by the CFLB-MRT approach. As the test of the method, we carry out simulation of a two-phase flow problem in which the porous media are initially saturated by brine or water, which is then displaced by CO2 or oil, injected into the pore space. The simulations are carried out with two types of sandstone. We show that the method accelerates the computations significantly by a factor of up to 35. 

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3. Simulating fluid flow in complex porous materials by integrating the governing equations with deep-layered machines

   https://doi.org/10.1038/s41524-021-00598-2  

   Kamrava, Serveh; Sahimi, Muhammad; Tahmasebi, Pejman (December 2021, npj Computational Materials)

   Abstract Fluid flow in heterogeneous porous media arises in many systems, from biological tissues to composite materials, soil, wood, and paper. With advances in instrumentations, high-resolution images of porous media can be obtained and used directly in the simulation of fluid flow. The computations are, however, highly intensive. Although machine learning (ML) algorithms have been used for predicting flow properties of porous media, they lack a rigorous, physics-based foundation and rely on correlations. We introduce an ML approach that incorporates mass conservation and the Navier–Stokes equations in its learning process. By training the algorithm to relatively limited data obtained from the solutions of the equations over a time interval, we show that the approach provides highly accurate predictions for the flow properties of porous media at all other times and spatial locations, while reducing the computation time. We also show that when the network is used for a different porous medium, it again provides very accurate predictions. 

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4. Spatial Characterization of Wetting in Porous Media Using Local Lattice-Boltzmann Simulations

   https://doi.org/10.1007/s11242-023-02044-x  

   Erfani, Hamidreza; Haghani, Reza; McClure, James; Boek, Edo; Berg, Carl Fredrik (February 2024, Transport in Porous Media)

   Abstract Wettability is one of the critical parameters affecting multiphase flow in porous media. The wettability is determined by the affinity of fluids to the rock surface, which varies due to factors such as mineral heterogeneity, roughness, ageing, and pore-space geometry. It is well known that wettability varies spatially in natural rocks, and it is still generally considered a constant parameter in pore-scale simulation studies. The accuracy of pore-scale simulation of multiphase flow in porous media is undermined by such inadequate wettability models. The advent of in situ visualization techniques, e.g. X-ray imaging and microtomography, enables us to characterize the spatial distribution of wetting more accurately. There are several approaches for such characterization. Most include the construction of a meshed surface of the interface surfaces in a segmented X-ray image and are known to have significant errors arising from insufficient resolution and surface-smoothing algorithms. This work presents a novel approach for spatial determination of wetting properties using local lattice-Boltzmann simulations. The scheme is computationally efficient as the segmented X-ray image is divided into subdomains before conducting the lattice-Boltzmann simulations, enabling fast simulations. To test the proposed method, it was applied to two synthetic cases with known wettability and three datasets of imaged fluid distributions. The wettability map was obtained for all samples using local lattice-Boltzmann calculations on trapped ganglia and optimization on surface affinity parameters. The results were quantitatively compared with a previously developed geometrical contact angle determination method. The two synthetic cases were used to validate the results of the developed workflow, as well as to compare the wettability results with the geometrical analysis method. It is shown that the developed workflow accurately characterizes the wetting state in the synthetic porous media with an acceptable uncertainty and is better to capture extreme wetting conditions. For the three datasets of imaged fluid distributions, our results show that the obtained contact angle distributions are consistent with the geometrical method. However, the obtained contact angle distributions tend to have a narrower span and are considered more realistic compared to the geometrical method. Finally, our results show the potential of the proposed scheme to efficiently obtain wettability maps of porous media using X-ray images of multiphase fluid distributions. The developed workflow can help for more accurate characterization of the wettability map in the porous media using limited experimental data, and hence more accurate digital rock analysis of multiphase flow in porous media. 

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5. 3D Printing Reactive Porous Media: Calcite Precipitation Kinetics on Surface Functionalized Polymer Films and 3D-printed Cores

   https://doi.org/10.69631/ipj.v2i2nr71  

   Senthil_Kumar, Harrish Kumar; Nahian, Abdullah Al; Braziel, Nailah; Shi, Zhoufan; Torrance, Madelyn; Shinde, Vinita V; Beckingham, Lauren E; Beckingham, Bryan S (June 2025, InterPore Journal)

   Mineral precipitation reactions in porous media can change the porosity and permeability of the rock formations. Predicting the rate of reaction and impacts on formation properties is challenging due to a lack of understanding of mineral precipitation reaction kinetics and mechanisms in porous media. This is furthermore challenging due to the highly heterogeneous nature of natural porous media. Here, we aim to develop a novel experimental platform leveraging 3D printing to facilitate replicable mineral precipitation experiments in controlled, heterogenous porous media systems. This requires fundamental understanding of the kinetics of mineral precipitation on the polymer materials used to fabricate the 3D printed porous media. In this work, we manipulate (via sulfonation) material surfaces (high impact polystyrene, HIPS) to promote calcite precipitation from supersaturated solutions to inform the design of synthetic subsurface systems. Calcite precipitation on HIPS films of varied surface sulfonation is confirmed using X-ray diffraction (XRD) analysis and weight-based precipitation experiments where increased precipitation with increased surface functionalization and solution saturation index are observed. This approach is then applied to 3D-printed porous media to enhance understanding of geochemical reactions, specifically calcite precipitation. Three dimensional images of Bentheimer Sandstone are used as the basis for 3D-printed porous media samples. Two 3D-printed samples were functionalized with acid to activate the surface and promote mineral precipitation. Functionalized and unfunctionalized samples underwent calcite precipitation core flooding experiments with oversaturated calcite solutions for 96 hours. Three dimensional X-ray micro-CT imaging revealed calcite growth in functionalized samples, with a calcite volume fraction of approximately 2.6% and a substantial reduction in porosity. Unfunctionalized samples exhibited diminished calcite precipitation and porosity changes. These findings demonstrate that reactive 3D-printed porous media can provide a versatile geochemical modeling and experimentation platform. Functionalizing 3D printed samples enhances reactivity, allowing investigations of mineral precipitation processes in complex porous media. This research highlights the potential for further exploration of 3D-printed media in various geochemical contexts. 

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