Pore-scale Model Research Articles

Triggering interfacial instabilities during forced imbibition by adjusting the aspect ratio in depth-variable microfluidic porous media.

We present a comprehensive description of the aspect ratio impact on interfacial instability in porous media where a wetting liquid displaces a nonwetting fluid. Building on microfluidic experiments, we evidence imbibition scenarios yielding interfacial instabilities and macroscopic morphologies under different depth confinements, which were controlled by aspect ratio and capillary number. We report a phenomenon whereby a smaller aspect ratio of depth-variable microfluidic porous media and lower capillary number trigger interfacial instability during forced imbibition; otherwise, a larger aspect ratio of uniform-depth microfluidic porous media and higher capillary number will suppress the interfacial instability, which seemingly ignored or contradicts conventional expectations with compact and faceted growth during imbibition. Pore-scale theoretical analytical models, numerical simulations, as well as microfluidic experiments were combined for characteristics of microscopic interfacial dynamics and macroscopic displacement results as a function of aspect ratio, depth variation, and capillary number. Our results present a complete dynamic view of the imbibition process over a full range of regimes from interfacial stabilization to destabilization. We predict the mode of imbibition in porous media based on pore-scale interfacial behavior, which fits well with microfluidic experiments. The study provides insights into the role of aspect ratio in controlling interfacial instabilities in microfluidic porous media. The finding provides design or prediction principles for engineered porous media, such as microfluidic devices, membranes, fabric, exchange columns, and even soil and rocks concerning their desired immiscible imbibition behavior.

Effects of liquid water on transport in the catalyst layer of proton exchange membrane fuel cells

Catalyst layers (CLs) of proton exchange membrane fuel cells (PEMFCs) where the electrochemical reactions take place have a critical effect on the cell performance and liquid water forming in CLs during operation can influence the reactive transport processes which is challenge for experimental observation due to the temporal and spatial limitation. In this study, nanoscale structures of CLs in PEMFCs are reconstructed with pores, carbon, platinum (Pt) particles, and ionomers fully resolved. Distributions of liquid water with different saturations and wettabilities within nanoscale structures are simulated by the lattice Boltzmann method. Pore-scale modeling of oxygen reactive transport in the nanoscale structures is implemented, with oxygen diffusion in pores and ionomers, as well as an electrochemical reaction at the Pt surface considered. Effects of liquid water on the pore size distribution, electrochemical area, and oxygen concentration distribution are discussed. Liquid water in hydrophilic CL tends to form a film covering the reactive sites, while that in hydrophobic CL forms a droplet preferentially occupying large pores. For the hydrophilic case, local transport resistance increases significantly under a low saturation, while for the hydrophobic case, a remarkable increase in the local transport resistance can only be found after liquid water saturation higher than 0.8. Finally, the conjecture that liquid water in pores with a size smaller than a threshold pore size can conduct protons is considered. Different values of the threshold pore size are studied. The results show that when the threshold value is greater than 10 nm, the local transport resistance will decrease as the liquid water saturation increases, which means the optimizing strategy of CL needs to carefully consider the effects of liquid water.

Enhancing pore network extraction performance via seed-based pore region growing segmentation

Pore-scale modeling, aided by imaging advancements and computational power, is now a vital tool for comprehending fluid flow and transport in porous media. It allows detailed exploration of pore structures and analysis of fluid dynamics and mass transport at smallest scales. This work presents the Pore Region Growing (PREGO) Algorithm, a novel approach to address segmentation challenges encountered in large-sized 3D images used for pore network modeling. The algorithm overcomes limitations of traditional methods like the watershed algorithm, in both computational time and memory of the pore segmentation. Like the watershed method, the proposed work involves identifying seed points, then grows each to fill their respective basis. The algorithm differs from existing approaches in that it efficiently prioritizes and grows the seed points using a FIFO queue, resulting in well-defined segmentation with clear and smooth boundaries between neighboring regions. The output was validated by demonstrating the algorithm's robustness in predicting diffusive behavior and viscous fluid flow within the pore phase network, with excellent agreement in comparison to lattice Boltzmann simulations and experimental data. The proposed algorithm was also shown to accurately predict transport properties under varying porosity, and different types of real porous media images. The evaluation of the Intersection over Union (IoU) and Dice Similarity Coefficient (DSC) metrics revealed that the PREGO technique had a maximum error of 5.44%, whereas the Watershed method exhibited a comparatively higher error rate of 22.3%. Structural analysis of physical properties revealed PREGO captures pore and throat sizes in close agreement with existing approaches. Crucially, computational performance analysis demonstrated its efficiency, significantly reducing memory consumption by 50% and CPU time speed up of 3.35X compared to the standard watershed algorithm using a priority queue.

Experimental and numerical investigation of Non-Darcy flow in propped hydraulic fractures: Identification and characterization

Non-Darcy flow occurs in all porous media. The phenomenon of non-Darcy flow is particularly evident in propped fractures. It is crucial to understand the causes of non-Darcy flow, identify its onset, and characterize it quantitatively. We first observed the phenomenon of non-Darcy flow in propped fractures through laboratory experiments. Subsequently, 75 pore-scale propped fracture models with different porosities, apertures, and proppant particle sizes were established, and 2850 simulations at different pressure gradients were performed to identify and quantitatively characterize the non-Darcy flow in propped fractures. Calculation of the non-Darcy coefficients of various regions in the numerical model revealed that non-Darcy flow arises due to flow resistance. A model for predicting the crucial Reynolds number based on the apparent permeability (Rec=ehkD−1β−1/99) was proposed to enable more accurate identification of the onset of non-Darcy flow, and the predicted results were in strong accord with the observed data. A more constitutive non-Darcy coefficient prediction model was developed to quantify the non-Darcy effect, which is expressed as β=408af−0.34s−0.76φ−4.44. This study explains the root cause of non-Darcy flow in propped fractures, identifies the occurrence of non-Darcy flow more efficiently, and accurately characterizes non-Darcy flow.

Validating mechanistic models of fluid displacement during imbibition

Pore-scale modelling is an important tool to improve our understanding of multiphase flow in porous media. Slow fluid invasion is commonly modelled using quasi-static pore network models (PNM). These models simulate the invasion in a network of simplified pores and throats by invading network elements in order of the quasi-static “invasion” capillary pressure needed for the invading fluid to enter. Despite a multitude of studies that address the predictiveness of PNM, it remains unclear what the leading causes of errors in these methods are, particularly during imbibition. To address this, we developed a novel method to directly validate the invasion capillary pressure models that underlie quasi-static PNM for the first time. The new method compares these models to local capillary pressures measured during in-situ flow experiments visualized with 4D μCT. We applied this to two different open-source PNM extractions from a μCT dataset of a glass beads pack that underwent slow imbibition. This methodology is limited by the temporal resolution of the data, hence we tested assumptions regarding displacement sequences when individual displacements could not be resolved. To constrain the uncertainty on the input parameters, we used local contact angles measured from the μCT images. In the PNMs we investigated, the model-predicted invasion-Pc values were on average greater than the direct measurements made using curvatures from the μCT images. Important sources of mismatch were the difficulty to accurately describe the pore space of a beadpack as a network of pores and throats, as well as the relatively low temporal resolution of the μCT dataset. The method presented here can be used to direct the development of improved pore network models.

A deep learning upscaling framework: Reactive transport and mineral precipitation in fracture-matrix systems

Pore-scale modeling has limited applicability at large scales due to its high computational cost. One common approach to upscale pore-scale models is the use of effective medium theories, which homogenize small-scale features in a porous structure and characterize the medium by macroscale properties (e.g., permeability) and equations (e.g., Darcy’s law). However, there are classes of physical processes for which effective medium approximations may become inaccurate, e.g., mineral precipitation and clogging during reactive transport. We have developed a deep learning upscaling framework, in which pore-scale modeling is directly employed in macroscale systems, without relying on effective medium approximations. The upscaling framework is first developed for general multiscale systems and then applied to modeling reactive transport with mineral precipitation in the altered layer in fracture-matrix structures. Solute transport from the fractures to the matrix is modeled as a wall boundary condition for the fractures, which, in turn, is predicted by recurrent neural networks using the concentration histories at the fracture-matrix boundary. Specifically, we consider a meter-scale fracture network embedded in sandstones, where the smallest feature is at the micron scale. The proposed framework allows us to span five orders of magnitude in length scales by capturing mineral precipitation in the altered layer of the rock matrix at the pore scale across the entire meter-scale fracture network.

Wettability effect on displacement in disordered media under preferential flow conditions

Preferential flow in a porous medium is commonly encountered in many practical applications. Our previous studies have discovered the preferential flow-induced non-monotonic wettability effect on displacement (J. Fluid Mech, vol. 942, 2022a, R5), but whether this non-monotonic rule is consistent for different disordered media and the impact of the interplay between the disorder and wettability under preferential flow conditions is still not well understood. Here, we combine microfluidic experiments, pore-scale simulations and theoretical analysis to study the impact of the disorder on the invading process where wettability varies from strongly water wet to strongly oil wet. Even though the strongly disordered matrix varies to a uniform state, the generality of the preferential flow-induced non-monotonic wettability effect is still proved. However, the previous pore-scale dynamics based on the strongly disordered matrix cannot explain the invading behaviour in the uniform matrix under preferential flow conditions. New mechanisms for the uniform matrix are further investigated by pore-scale modelling, which indicates that the balance of microscopic imbibition ability and the macroscopic interfacial stability dominate the invading process. We derive a theoretical model to describe the wettability effect and predict the optimal contact angle, which fits well with experimental and simulation results. Our work extends the understanding of the impact of preferential flow conditions on the wettability effect and is also of practical significance for engineering applications, such as geological CO2 sequestration, enhanced hydrocarbon recovery, soil wetting, liquid-infused material fabrication and microfluidic device design.

Effects of agglomerate structure and operating humidity on the catalyst layer performance of PEM fuel cells

Understanding the transport mechanism in catalyst layer (CL) agglomerates is crucial to enhance Pt utilization and overall fuel cell performance. In this study, high-resolution porous agglomerates are stochastically reconstructed, and capillary condensation of water in agglomerates is directly simulated using a lattice Boltzmann pseudopotential model. On this basis, a pore-scale electrochemical model is developed to investigate the effects of agglomerate structure and operating humidity on local transport resistance and agglomerate effectiveness at different Pt loadings. The results reveal that liquid water formed above 70%RH improves the electrochemical surface area (ECSA) of agglomerates with low ionomer content. An optimum I/C of 0.4 in agglomerates is determined by balancing the activated ECSA and oxygen transport resistance. Through the comparison of local transport resistance with limiting current data, an additional oxygen dissolution resistance of 60–350 s m−1 at the pore/ionomer or ionomer/Pt interface is quantified. The lowest local transport resistance of the agglomerate is achieved at about 70%RH, while condensed water at higher humidities hampers oxygen diffusion within the agglomerate, leading to reduced Pt utilization. Agglomerate size significantly affects the local transport resistance only when excessive ionomer or liquid water severely blocks primary pores. Finally, a novel multiscale coupling strategy integrating the porous agglomerate sub-model with a continuous-scale CL model is proposed, offering innovative insights into comprehending the relationship between CL structure and the performance of proton exchange membrane fuel cells.

Drying-induced volumetric behaviour of clays interpreted via binary pore-scale modelling

The volumetric response upon drying is relevant in the geotechnical and ceramic industry due to the key role played in crack formation. The volumetric response of clays upon drying is relatively complex; the void ratio decreases considerably in the saturated state, levels off almost abruptly at the onset of desaturation, and increases at very low water contents. This paper presents an original deformable pore-network model (DPNM) to elucidate the micromechanisms controlling the complex volumetric response of clays upon drying. The main features of the DPNM are the ‘binary’ approach (pores in the clay are assumed to be either fully saturated with water or dry) and the use of independent tests to calibrate the parameters of the model (compression behaviour of saturated reconstituted clay and dry powder). The DPNM shows that all pores shrink as pore-water tension increases in the saturated state, although the larger pores contribute more to the overall reduction in void ratio. At the onset of desaturation, the larger pores dry out and rebound, whereas the smaller pores remain saturated and shrink. At very low water content/high pore-water tension, the desaturation of the smaller pores causes them to rebound, thus generating a macroscopic increase in the void ratio.

Ostwald ripening of multi-component bubbles in porous media: A theory and a pore-scale model of how bubble populations equilibrate

Bubbles trapped inside porous materials occur in many applications ranging from geologic CO2 sequestration, underground hydrogen storage (UHS), groundwater remediation, to fuel cells and electrolyzers. If partially miscible in their surrounding wetting phase, bubbles can evolve through a process called Ostwald ripening, in which those with a high interfacial curvature dissolve fastest and feed into bubbles with a low curvature. For single-component bubbles, the physics are relatively well-understood. This work focuses on the ripening of bubbles comprised of multiple components, which remains unexplored. We first present a pore-network model (PNM) to simulate the temporal evolution of a population of partially miscible, multi-component bubbles inside a heterogeneous porous microstructure. We then use the model to identify the different ripening regimes between two adjacent bubbles, some rather counterintuitive. We also show that, under conditions prevalent in the subsurface, multi-component ripening proceeds in two stages separated in timescale: partitioning and coevolution. Based on this insight, we propose a theory to predict the probability density function (PDF) of bubble sizes at the ends of partitioning and coevolution (i.e., equilibrium) from their initial state and the pore-size distribution. The theory is systematically compared against the PNM and very good agreement is found. Limitations of both the PNM and theory are discussed and implications for UHS are outlined.

A simplified pore-scale model for slow drainage including film-flow effects

Liquid-filled corners and capillary bridges can establish networks connecting seemingly isolated clusters during drainage in porous media. Coupled with drainage through the bulk of pores and throats, the flow through these networks constitutes a secondary drainage mechanism that can significantly affect fluid configurations and residual saturations. In order to investigate the prevalence of this drainage mechanism, we propose a quasi-static pore-network model based on modifying the trapped-cluster-identification algorithm in an invasion-percolation model. With the modification, wetting-phase connectivity is provided by direct successions of pores and throats, represented by sites and bonds, as well as by chains of interconnected capillary bridges. The advancement of the fluid interface in the porous matrix is determined by the bonds’ invasion thresholds and local capillary pressure values, calculated taking into consideration gravitational effects. With the proposed model, experimentally verified phenomena related to slow drainage in granular porous media are reproduced, showing good qualitative agreement.

Enhanced performance of pinned metal foam heat sinks with dielectric coolant – A pore-scale numerical study

Recent advancements in the development of microprocessors have resulted in the design of smaller microchips with improved performance. The new designs require proper cooling systems to prevent performance degradation and permanent damage to the chips. Extended surfaces, including fin, pin, or metal foam, are one of the prominent approaches in cooling systems designs. So far, there has been limited research, especially considering pore-scale analysis on the combination of pin/fin with metal foam, which is expected to offer promising cooling performance. This study aims to evaluate the performance of pinned metal foam heat sinks with dielectric coolant as a potential cooling system for microchips. A three-dimensional pore-scale numerical model is developed to analyze the performance of the proposed heat sinks. The effect of different parameters such as Reynolds number, heat flux, pore density, and different pin shapes are investigated. The results reveal that at a Reynolds number of 100, almost all the metal foam heat sinks enhance the heat transfer performance, which can be as large as 22% in some cases. Furthermore, adding pins increases the heat energy dissipation with a slight penalty of pressure drop depending on its hydrodynamic adaptation. Too dense or loose metal foam either increases the pressure drop or decreases the heat transfer rate, deviating from the optimum range. Lastly, it is revealed that heat flux from the heater does not significantly change the performance of the pinned metal foam heat sinks.

Modeling of formation damage during smart water flooding in sandstone reservoirs

Impairment of permeability has been observed as an effective factor in production decline during secondary and tertiary recovery processes such as water flooding. Among different permeability damage mechanisms, fines migration and deposition is known as the main mechanism which occurs due to pore throat clogging and blocking. Because injected water and formation water are usually incompatible, permeability damage evaluation and scale formation prediction must be done before the water flooding process in the oil field is implemented. For this purpose, compatibility tests and core flood experiments are common, but experimental approaches with time and facility limitations are expensive. Thus, by decreasing the time required for conducting experiments, modeling approaches can replace the routine laboratory experiments. Based on thermodynamic balance and the solubility of ions in water, scale development due to seawater injection in an Iranian oil field was predicted in this work using the OLI ScaleChem software. After that, it was suggested that special water be introduced to help reduce the amount of scales that had accumulated in the rock pore space. The extent of permeability damage in various seawater injection scenarios was then assessed via dynamic core flood experiments. Finally, scales-seawater injection into the core was simulated using digital core analysis (DCA) results and the pore scale modeling approach. The core flood experiment data are consistent with the scale formation prediction made by the OLI ScaleChem software, which indicates that smart water can be determined by optimizing the salinity and ion content of injected water. Also, results of permeability damage prediction by our modeling approach have good agreement with the core flood experiment data. Therefore, our modeling approach can replace the conventional core flood experiments as a low-cost method with high computational efficiency and high enough accuracy to evaluate formation damage in the water flooding process.

Fractal Pore-Scale Model for Effective Thermal Conductivity of Multiscale Unsaturated Porous Media

Fractal Pore-Scale Model for Effective Thermal Conductivity of Multiscale Unsaturated Porous Media

Predicting PEMFC performance from a volumetric image of catalyst layer structure using pore network modeling

A pore-scale model of a PEMFC cathode catalyst layer was developed using the pore network approach and used to predict polarization behavior. A volumetric image of a PEMFC catalyst layer was obtained using FIB-SEM with 4 nm resolution in all 3 directions. The original image only differentiated between solid and void, so a simple but effective algorithm was developed to insert tightly packed, but non-overlapping carbon spheres into the solid phase, which were then decorated with catalyst sites. The resultant image was a 4-phase image containing void, ionomer, carbon, and catalyst, each in proportion to the known Pt loading, carbon-to-ionomer ratio, and porosity. A multiphase pore network model was extracted from this image, and multiphysics simulations were conducted to predict the polarization behavior of an operating cell. It was shown that not only can beginning of life polarization performance be predicted with minimal fitting parameters, but degraded performance 30 k cycles was also well captured with no additional fitting. This latter result was accomplished by deleting catalyst sites from the network in proportion to the experimentally observed distribution of electrochemical surface area loss, obtained from TEM image of catalyst loading. The model included partitioning of oxygen into the ionomer phase, explicitly incorporating the oxygen transport resistance which dominates cell performance at higher current density. Although Knudsen diffusion is present at the scales present (<100nm), it represented a negligible fraction of the total transport resistance, which was dominated by the low solubility and slow diffusivity in the ionomer phase. This work showed that the performance of a typical PEMFC is highly dependent on the structural details of the catalyst layer, to the extent that polarization curves can be well predicted by direct inspection of an image of the catalyst layer. This work paves the way for a deeper understanding of the structure-performance relationship in these complex materials and the search for optimized catalyst layer designs.

A Pore-Scale Model for Electrokinetic In situ Recovery of Copper: The Influence of Mineral Occurrence, Zeta Potential, and Electric Potential

Electrokinetic in-situ recovery is an alternative to conventional mining, relying on the application of an electric potential to enhance the subsurface flow of ions. Understanding the pore-scale flow and ion transport under electric potential is essential for petrophysical properties estimation and flow behavior characterization. The governing physics of electrokinetic transport is electromigration and electroosmotic flow, which depend on the electric potential gradient, mineral occurrence, domain morphology (tortuosity and porosity, grain size and distribution, etc.), and electrolyte properties (local pH distribution and lixiviant type and concentration, etc.). Herein, mineral occurrence and its associated zeta potential are investigated for EK transport. The new Ek model which is designed to solve the EK flow in complex porous media in a highly parallelizable manner includes three coupled equations: (1) Poisson equation, (2) Nernst–Planck equation, and (3) Navier–Stokes equation. These equations were solved using the lattice Boltzmann method within X-ray computed microtomography images. The proposed model is validated against COMSOL multiphysics in a two-dimensional microchannel in terms of fluid flow behavior when the electrical double layer is both resolvable and unresolvable. A more complex chalcopyrite-silica system is then obtained by micro-CT scanning to evaluate the model performance. The effects of mineral occurrence, zeta potential, and electric potential on the three-dimensional chalcopyrite-silica system were evaluated. Although the positive zeta potential of chalcopyrite can induce a flow of ferric ion counter to the direction of electromigration, the net effect is dependent on the occurrence of chalcopyrite. However, the ion flux induced by electromigration was the dominant transport mechanism, whereas advection induced by electroosmosis made a lower contribution. Overall, a pore-scale EK model is proposed for direct simulation on pore-scale images. The proposed model can be coupled with other geochemical models for full physicochemical transport simulations. Meanwhile, electrokinetic transport shows promise as a human-controllable technique because the electromigration of ions and the applied electric potential can be easily controlled externally.Graphical abstract

Pore-scale melting behaviors in composite phase change material with porosity gradients

Latent heat storage is a promising thermal energy storage solution to tackle the time–space conflict in energy demand. However, the low thermal conductivity of pure phase change material may limit the thermal energy storage performance of latent heat storage systems. In this work, porous support with gradient porosity and high thermal conductivity is incorporated into the phase change material to minimize the total melting time. A pore-scale lattice Boltzmann model for simulating the melting process of composite phase change material is established to investigate the effect of gradient porosity on the dynamic melting process. The results show that the two-dimensional gradient porosity structure can significantly improve the melting rate of composite phase change material. Compared with a uniform porosity structure, the melting time can be reduced by up to 8.58% in this work. By considering the changes in dominant heat transfer mechanisms during the melting process and the asymmetric evolution of the upper and lower parts of the melting front, the two-dimensional gradient porosity structure combines the advantages of horizontal and vertical one-dimensional gradient porosity structure. It is also found that the gradient porosity structures slow down the melting process of composite phase change material when the porosity is too small in the lower right corner of the square cavity or when the two-dimensional gradient porosity is divided too finely. The solid phase change material in this area mainly relies on thermal convection for melting, and it can significantly delay the melting time when the flow velocity is low, with a maximum extension of 26.58% of the melting time as compared to a uniform porosity structure.

Image-based pore-scale modelling of the effect of wettability on breakthrough capillary pressure in gas diffusion layers

Wettability design is of crucial importance for the optimization of multiphase flow behaviour in gas diffusion layers (GDLs) in fuel cells. The accumulation of electrochemically-generated water in the GDLs will impact fuel cell performance. Hence, it is necessary to understand multiphase displacement to design optimal pore structures and wettability to allow the rapid flow of gases and water in GDLs over a wide saturation range. This work uses high-resolution in situ three-dimensional X-ray imaging combined with a pore network model to investigate the breakthrough capillary pressure and water saturation in GDLs manufactured with different mass fractions of polytetrafluoroethylene coating: 5, 20, 40, and 60%, making them more hydrophobic. We first demonstrate that the pore network extraction method provides representative networks for the fibrous porous media examined. Then, using a pore-network flow model we simulate water invasion into initially gas-filled fibrous media, and analyze the effect of wettability on breakthrough capillary pressure and water saturation. With an appropriate pore-scale characterization of wettability, a pore network model can match experimental results and predict displacement behaviour.

Reactive transport modeling for assessing coupled hydrogeochemical processes at interfaces in deep geological repositories: from the laboratory to the real world

Abstract. Deep geological repositories with a multi-barrier concept are foreseen by various countries for the disposal of high-level radioactive waste. Simulation tools for a close-to-reality description of repository evolution scenarios are required, especially to resolve the challenging task of comparing and assessing the long-term safety of different repository concepts in different host rocks within the German site-selection process. Chemical, thermal, and pressure gradients at the interfaces of the different barriers in a repository can lead to mineral dissolution and precipitation, generating non-linear responses in transport and mechanical properties of barrier materials and host rocks. Reactive transport modeling (RTM) can be applied to investigate these perturbations and processes across temporal and spatial scales to assess subsurface evolution. Nevertheless, implementing RTM at the continuum scale while accounting for pore-scale heterogeneities and geometry evolution remains a challenge. Pore-scale simulations offer the potential to capture the complex evolution of porous media over a broad range of Peclet and Damköhler numbers, and they can be utilized to improve the RTM by using upscaling methods (Prasianakis et al., 2020). In this context, we developed “lab-on-a-chip” experiments, combining time-lapse high-resolution optical microscopy and confocal Raman spectroscopy to test extended constitutive equations to classically employed Archie's law to improve the description of changes in transport properties (e.g., diffusivity) in evolving porous media in RTM. The 3D Raman tomography of the porous media combined with pore-scale modeling enabled the derivation of upscaled transport parameters. Our results highlight the importance of calibrating pore-scale models with quantitative experiments prior to simulations over a wide range of Peclet and Damköhler numbers, whose results can be further used for the derivation of upscaled modeling parameters. The derived and parameterized constitutive equations based on simple systems have been tested in reactive transport models as a sensitivity case study to evaluate uncertainties in the predictions of the evolution of real subsurface systems such as clay–cement interfaces in deep geological repositories.

Pore-Scale Investigation of Decomposition-Methods-Dependent Fluid Flow Properties in Hydrate-Bearing Sediments

Summary Depressurization (PD) and thermal stimulation (TS) are the primary methods for producing gas from natural gas hydrate (NGH) sediments. Fluid flow properties of the hydrate sediment, such as permeability, are fundamental parameters for simulating both processes. Most of the existing formulated permeability models are based on the numerical or experimental investigation of hydrate morphology evolution without considering the decomposition methods. In this study, we investigate the hydrate-decomposition-methods (PD and TS processes)-dependent fluid flow properties of hydrate sediments, which is achieved by microcomputed tomography (micro-CT) scanning of hydrate morphology evolution during PD- and TS-induced decomposition, as well as pore-scale modeling of fluid flow in the extracted 3D fluid-rock-hydrate images. We find that the decomposition behavior during TS is much more complicated than that during PD. The retardation zone in the PD sample increases the heterogeneity of the pore structure, while the secondary hydrates generated during TS cause even more heterogeneity in the pore space. The better facilitation of the TS method on hydrate split is favorable for the continuity of the gas phase. The pore-scale fluid flow simulation shows that the modified Kozeny-Carman (K-C) model is the best to describe the evolution of the normalized permeability with hydrate saturation during PD. However, a single model is not sufficient to describe the normalized permeability during TS decomposition due to the stronger heterogeneous porous structure reformed by the local accumulation of secondary hydrates. The two-phase flow capability is best at the initial stage of PD decomposition, while the two-phase flow region becomes wider as TS decomposition progresses. These results provide significant references for the simulation of the natural hydrate extraction process using different decomposition methods.