3D Porous Media Research Articles

Quantification of the fluid saturation of three phases of NAPL/Water/Gas in 2D porous media systems using a light transmission technique

Determining transient fluid saturations in a multi-phase system is important for understanding the system’s flow characteristics and performing effective subsurface remediation. This paper investigates the models to quantify the fluid saturations of three phases of NAPL/Water/Gas in 2D porous media systems using a noninvasive light transmission technique. Four light intensity-saturation models (LISMs) to quantify fluid saturations from light intensities with only two parameters are proposed. Four LISMs can be divided into two classes: one based on assumption A of individual drainage and the other based on assumption B of combined drainage. LISMs are verified by two experiments conducted in NAPL invading into Water/Air and Water/Biogenic-Gas conditions, respectively. Results show that the model which based on assumption A and drainage of water first is the best type and show the strongest linear correlation between calculated results and measured data (R2 of 0.974 for air condition and R2 of 0.996 for biogenic gas condition). This study developed the innovative LISMs and applied them to three phases of NAPL/Water/Gas systems, which provides a methodology to acquire effective three fluid saturations in a continuous, quantitative, and real time way.

Prediction of effective diffusivity of porous media using deep learning method based on sample structure information self-amplification

Effective diffusivity is one of the basic transport coefficients used to describe the mass transport capability of a porous medium. In this study, a deep learning method based on a convolutional neural network (CNN) with sample structure information self-amplification is proposed to predict the effective diffusivity of a porous medium, which is considerably influenced by the morphological and topological parameters of the porous medium. In this method, the geometric structures of three-dimensional (3D) porous media are reproduced via a stochastic reconstruction method. Datasets of the effective diffusivities of the reconstructed porous media were first established by the pore-scale lattice Boltzmann method (LBM) simulation. A large number of geometric structures of 3D porous media are obtained using the proposed sample structure information self-amplification approach. The 3D geometric structure information and corresponding effective diffusivities are directionally applied to a CNN for training and prediction. The effective diffusivities of media with porosities ranging from 0.48 to 0.58 are employed as training datasets, and the effective diffusivities of media with a broader porosity range of 0.39 to 0.79 are predicted by CNN. The CNN model can achieve a fast and accurate prediction of the effective diffusivity. The relative error between the CNN and LBM is 0.026%–8.95% with porosities ranging from 0.39 to 0.79. For a typical case with a porosity of 0.5, the computation time required by the CNN model is only 3 × 10−4 h, while the computation time for the same case is 16.96 h using the LBM. These findings indicate that the proposed deep learning method has a powerful learning ability; it is time-saving, provides accurate predictions, and can serve as a promising and powerful tool to predict the transport coefficients of complex porous media.

Experimental study of seepage flow properties with biofilm development in porous media with different filter morphologies

Biofilm growth can impact seepage flow properties in the porous media, thereby affecting the performance of the infiltration systems. To better understand and characterize the biofilm distribution and its effect on seepage flow fields in the porous media with different morphologies, two-dimensional transparent flow cells were developed using X-ray images of zeolite, gravel, and ceramsite columns to study the effect of biofilm development and the pore structure on seepage flow properties. The results revealed that the filter morphology and biofilm growth significantly impacted the seepage flow field in porous media. With biofilm growth, a preferential flow pathway was more likely to be formed in angular filter cells (zeolite-shaped cells) than spherical filter cells (ceramsite-shaped cells). It was also found that microbial growth rate was closely related to seepage flowrate in 2D porous media cells. The biofilm grew faster in the areas with higher seepage flowrate. The biofilm accumulation did not seem to affect the location of the preferential seepage flow, probably due to the high permeability of the biofilm in the large pore throats. Although the water head loss of ceramsite-shaped cells was larger than that of two others due to its relatively smaller size of pore throat, the ceramsite-shaped cells presented small dead zone and short-circuiting, which means that ceramiste filter media had higher hydraulic efficiency.

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO2-water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO2 (scCO2)-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO2). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO2 and showed that the variations in the relative permeability curves for both water and scCO2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. The impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

Slice-to-voxel stochastic reconstructions on porous media with hybrid deep generative model

Three-dimensional (3D) microstructures are useful for studying the spatial structures and physical properties of porous media. A number of stochastic reconstructions are essential to discover the geometry and topology of the porous media and the its flow behavior. While several deep-learning based generative models have been proposed to deal with the issue, the obstacles about stable training and difficulty in convergence limit the application of these models. To address these problems, a hybrid deep generative model for 3D porous media reconstruction is proposed. The hybrid model is composed of a variant autoencoder (VAE) and a generative adversarial network (GAN). It receives a two-dimensional image as input and generates 3D porous media. The encoder from VAE characterizes the statistical and morphological information of input image and generates a low-dimensional feature vector for generator. Benefiting from the hybrid model, the training becomes more stable and the generative capability is enhanced as well. Furthermore, a simple but useful loss function is used to help improve accuracy. The proposed model is tested on both isotropic and anisotropic porous media. The results show the synthetic realizations have good agreement to the targets on visual inspection, statistical functions and two-phase flow simulation.

Parametric Nonlinear Model Reduction Using K-Means Clustering for Miscible Flow Simulation

This work considers the model order reduction approach for parametrized viscous fingering in a horizontal flow through a 2D porous media domain. A technique for constructing an optimal low-dimensional basis for a multidimensional parameter domain is introduced by combining K-means clustering with proper orthogonal decomposition (POD). In particular, we first randomly generate parameter vectors in multidimensional parameter domain of interest. Next, we perform the K-means clustering algorithm on these parameter vectors to find the centroids. POD basis is then generated from the solutions of the parametrized systems corresponding to these parameter centroids. The resulting POD basis is then used with Galerkin projection to construct reduced-order systems for various parameter vectors in the given domain together with applying the discrete empirical interpolation method (DEIM) to further reduce the computational complexity in nonlinear terms of the miscible flow model. The numerical results with varying different parameters are demonstrated to be efficient in decreasing simulation time while maintaining accuracy compared to the full-order model for various parameter values.

Image-based effective medium approximation for fast permeability evaluation of porous media core samples

An image-based effective medium approximation (EMA) is developed so as to permit very fast transport properties evaluations of 3D porous media. From an image-based porous network (IBPN) built upon digital image processing of 3D binary images, we focus on throat’s local geometrical properties at the pore scale, for being the most sensible structural units which build up the local pressure. This approach is a 3D image–based extension of the critical point approach proposed in 2D fractures. We show, from analyzing various core rock samples available in the literature, that the asymptotic assumptions associated with the preeminence of critical points in throats are indeed geometrically relevant. We then describe how the image-based EMA evaluated from the conductances computed from the discrete IBPN can be reliably evaluated. The proposed method is evaluated upon the estimation of core sample permeability from binarized image obtained using X-ray tomography. Since it combines digital image treatments with statistical data post-processing without the need of computational fluid dynamics (CFD) computation, it is extremely cost efficient. The results are compared with a micro-scale Stokes flow computation in various rock samples. The sensitivity to the pore discretization also is discussed and illustrated.

A 3D-1D coupled blood flow and oxygen transport model to generate microvascular networks.

In this work, we introduce an algorithmic approach to generate microvascular networks starting from larger vessels that can be reconstructed without noticeable segmentation errors. Contrary to larger vessels, the reconstruction of fine-scale components of microvascular networks shows significant segmentation errors, and an accurate mapping is time and cost intense. Thus there is a need for fast and reliable reconstruction algorithms yielding surrogate networks having similar stochastic properties as the original ones. The microvascular networks are constructed in a marching way by adding vessels to the outlets of the vascular tree from the previous step. To optimise the structure of the vascular trees, we use Murray's law to determine the radii of the vessels and bifurcation angles. In each step, we compute the local gradient of the partial pressure of oxygen and adapt the orientation of the new vessels to this gradient. At the same time, we use the partial pressure of oxygen to check whether the considered tissue block is supplied sufficiently with oxygen. Computing the partial pressure of oxygen, we use a 3D-1D coupled model for blood flow and oxygen transport. To decrease the complexity of a fully coupled 3D model, we reduce the blood vessel network to a 1D graph structure and use a bi-directional coupling with the tissue which is described by a 3D homogeneous porous medium. The resulting surrogate networks are analysed with respect to morphological and physiological aspects.

Suitability of 2D modelling to evaluate flow properties in 3D porous media

The employment of 2D models to investigate the properties of 3D flows in porous media is ubiquitous in the literature. The limitations of such approaches are often overlooked. Here, we assess to which extent 2D flows in porous media are suitable representations of 3D flows. To this purpose, we compare representative elementary volume (REV) scales obtained by 2D and 3D numerical simulations of flow in porous media. The stationarity of several quantities, namely porosity, permeability, mean and variance of velocity, is evaluated in terms of both classical and innovative statistics. The variance of velocity, strictly connected to the hydrodynamic dispersion, is included in the analysis in order to extend conclusions to transport phenomena. Pore scale flow is simulated by means of a Lattice Boltzmann model. The results from pore scale simulations point out that the 2D approach often leads to inconsistent results, due to the profound difference between 2D and 3D flows through porous media. We employ the error in the evaluation of REV as a quantitative measure for the reliability of a 2D approach. Moreover, we show that the acceptance threshold for a 2D representation to be valid strongly depends on which flow/transport quantity is sought.

Numerical investigation of the interaction between hydraulic fractures and natural fractures in porous media based on an enriched FEM

A fully coupled enriched-FEM (XFEM) model is proposed to investigate the interaction between hydraulic fractures and natural fractures in finite 2D porous media. The weak forms of both equilibrium and continuity equations are discretized in an enriched form in the space and by the Newmark scheme in the time domain. The Newton-Raphson method is adopted to solve these discretized equations. To account for the fluid flow in the porous matrix, 2D fluid leakage from the fractures to the matrix is considered by imposing internal flux boundary conditions on the fracture surfaces. A posteriori analysis is carried out to determine the equivalent leak off coefficient of the 1D Carter’s leak off law. The frictional contact of the fracture surface is modeled by the penalty method in the model. The junction ridge function is adopted to describe the weak discontinuities of the pressure field in the elements containing fracture intersection points. A crack initiation criterion based on the average tensile stress along the natural fracture is used to determine whether a hydraulic fracture can cross a natural fracture. The presented model is first validated against the analytical solutions of the KGD model and then several numerical examples are simulated to investigate the effects of the natural fracture properties, treatment parameters, matrix permeability, anisotropy stress and approaching angle on the interaction between hydraulic fractures and natural fractures. The numerical results suggest the acceptable accuracy and robustness of the presented model on modeling fracture interaction behaviors in the presence of fluid leakage into matrix.

Darcy and inertial fluid flow simulations in porous media using the non-orthogonal central moments lattice Boltzmann method

In this study, two-dimensional (2D) and three-dimensional (3D) lattice Boltzmann method (LBM) has been investigated using the non-orthogonal central moments collision method in order to study the Darcy and inertial (non-Darcy) fluid flow in porous media. A GPU parallel CUDA code has been developed and is employed to study the proposed method. A comparative study has been performed between the non-orthogonal central moments method and the Bhatnagar–Groos–Krook (BGK) method to measure the permeability. The effect of selecting sets of relaxation times and no-slip boundary conditions has been investigated using the 2D hexagonal and 3D body-centered cubic (BCC) structure, and an appropriate model has been presented for flow simulation in porous media. The comparison of the permeability obtained by the proposed numerical method with the analytical solutions shows that the proposed model is highly accurate and eliminates the dependence of permeability on the viscosity, which is one of the problems in the LBM. This model’s capability has been evaluated to simulate Darcy and inertial flows using 2D hexagonal geometry, 2D granular porous media with a random structure, 3D BCC geometry, 3D porous media with a random structure, and real porous media created by using computed tomography (CT) images. In addition, the apparent permeability, the non-Darcy β factor, and the onset of non-Darcy flow have been predicted to demonstrate the capability of the proposed method. The results show the high capability of the proposed model for fluid flow simulation in porous media with complex geometries; so, this model can be used as a powerful and stable tool with the capability of fluid flow simulation in porous media from the Darcy regime to large Reynolds numbers and the inertial regime.

Numerical investigation of Herschel–Bulkley fluid flows in 2D porous media: Yielding behaviour and tortuosity

Hydraulic tortuosity is commonly used as an input to macroscopic flow models in porous media, accounting for the sinuosity of the streamlines. It is well known that hydraulic tortuosity does not depend on the applied pressure gradient for Newtonian creeping flows. Nevertheless, this is not necessarily the case for yield stress fluids flows, given the directional nature of both yielding and shear-thinning behaviour. This study aims at a breakthrough on the relationship between the hydraulic tortuosity and the level of yielding. To do so, the hydraulic tortuosity of the flow paths is evaluated in 2D porous media by means of direct numerical simulations and subsequently put in relation with the morphological information of the medium provided by pore-network modelling. Moreover, the effects of pore dimensions, spatial disorder and rheological parameters on yielding behaviour are examined. In most situations, the reported tortuosity values are lower than those obtained for Newtonian fluids.

Experimental study on the displacement patterns and the phase diagram of immiscible fluid displacement in three-dimensional porous media

The immiscible fluid displacement pattern, controlled by the balance of viscous and capillary forces has a significant effect on the recovery or storage efficiency in subsurface processes. The phase diagram of displacement patterns has been extensively studied for the two-dimensional (2D) micromodel; however, that of the three-dimensional (3D) porous media has received little attention. This work experimentally studied the immiscible drainage displacement in an unconsolidated packed bed at the pore scale with a wide range of capillary number Ca and viscosity ratio M using X-ray micro-tomography. Three typical displacement patterns, namely viscous fingering, capillary fingering, and stable displacement, were observed in 3D porous media. The rough location of three displacement patterns on the Ca–M diagram was consistent with previous studies in 2D micromodel. The boundaries for three regimes were determined based on the quantitative analyses of the saturation distribution as functions of Ca and M. Compared with the result in 2D micromodel, a broader transition zone between different regimes was found in 3D porous media. The characterizations of finger structures (e.g. fractal dimension and finger width) were applied to reveal the mechanism of how the injected fluid invades the pores and throats inside porous media for different displacement patterns. The average fractal dimension of capillary fingerings was 2.58 ± 0.05, which agrees with the 2.55 defined by the invasion percolation theory. For the viscous fingering, where the viscous force dominates the invasion process, the invading fluid follows a several preferential flow paths in the same direction as the injection and the finger width was only 1 to 2 pore bodies. Besides, the invasion dynamics under continuous injection conditions were compared for typical viscous and capillary fingerings. This study may improve our understanding of the dynamics of displacement processes jointly governed by the viscous/capillary forces in 3D porous media. Furthermore, the phase diagram under various conditions (i.e. a wide range of Ca and M) can help to find a suitable reservoir conditions for subsurface processes.

Using energy balance to determine pore-scale wettability

HypothesisBased on energy balance during two-phase displacement in porous media, it has recently been shown that a thermodynamically consistent contact angle can be determined from micro-tomography images. However, the impact of viscous dissipation on the energy balance has not been fully understood. Furthermore, it is of great importance to determine the spatial distribution of wettability. We use direct numerical simulation to validate the determination of the thermodynamic contact angle both in an entire domain and on a pore-by-pore basis. SimulationsTwo-phase direct numerical simulations are performed on complex 3D porous media with three wettability states: uniformly water-wet, uniformly oil-wet, and non-uniform mixed-wet. Using the simulated fluid configurations, the thermodynamic contact angle is computed, then compared with the input contact angles. FindingsThe impact of viscous dissipation on the energy balance is quantified; it is insignificant for water flooding in water-wet and mixed-wet media, resulting in an accurate estimation of a representative contact angle for the entire domain even if viscous effects are ignored. An increasing trend in the computed thermodynamic contact angle during water injection is shown to be a manifestation of the displacement sequence. Furthermore, the spatial distribution of wettability can be represented by the thermodynamic contact angle computed on a pore-by-pore basis.

Scaling of two-phase water-steam relative permeability and thermal fluxes in porous media

Two-phase water-steam flow conditions are frequently encountered in many engineering applications, including geothermal reservoirs. Although routine calculations are based on the multiphase Darcy’s law, the role of the topology of the flowing phases at the pore-scale is usually neglected in the estimation of relative permeabilities. Instead, the latter are frequently computed using empirical models like the Corey correlation. In this work, we first apply the model for relative permeabilities based on pore-scale flow regimes developed by Picchi and Battiato (2019), Relative permeability scaling from pore-scale flow regimes, Water Resour. Res. 55, 3215–3233, to scenarios typical of geothermal reservoirs and then extend it by deriving the scaling laws for the transmissibilities and the thermal properties as a function of temperature. First, we discuss the scaling behavior of normalized relative permeabilities in terms of viscosity ratio and capillary number of water-steam systems and, then, we provide a validation of the model against experimental data available in the literature. The model captures well the data trends collected in real 3D porous media. These results suggest that water-steam relative permeabilities follow the same scaling behavior of gas-liquid systems where the non-wetting phase is much less viscous than the wetting phase. Finally, we investigate the impact that relative permeabilities have on heat transfer rates at two-phase flow conditions and the scaling of mass and energy transmissibility and thermal properties of the mixture. An estimation of the exergy carried by the two-phase water-steam mixture is also included.

Pore-scale model of two phase flow in 2D porous media: Influences of interfacial tension and heterogeneity effects on CO2 injection in the tight oil reservoir

The CO2 injection in tight reservoir is different from the conventional reservoir. For the porous media, the pore throat in the matrix reaches the level of nanopore, and the heterogeneity leads to huge difference during CO2 injection. For the interaction of fluids, the reduction of interfacial tension caused by CO2 is benefit to enhance oil recovery. To reveal the mechanism, pore scale model from tight formation is built and the influences of interfacial tension and heterogeneity are investigated. First, the migration of two-phase interface is studied by coupled with level set (LS) equation and Navier-Stokes (NS) equation. And finite element method (FEM) with interfacial adaptive mesh refinement is employed to solve the equation system. The results reach highly agreement compared with analytical solution and phase field method. Then, the pore throat distribution characteristics of porous media model are built by the scanning electron micrograph (SEM). Finally, based on the real porous media model from the SEM image, the influences of interfacial tension and heterogeneity are investigated. The pore scale model considering fluid and medium mechanism during CO2 injection provides a better understanding of interfacial tension and heterogeneity effect in tight oil reservoirs.

Generalized thermoelastic interaction in a two-dimensional porous medium under dual phase lag model

Purpose The purpose of this study is to use the generalized model for thermoelastic wave under the dual phase lag (DPL) model to compute the increment of temperature, the components of displacement, the changes in volume fraction field and the stress components in a two-dimensional (2D) porous medium. Design/methodology/approach Using Fourier and Laplace transformations with the eigenvalue technique, the exact solutions of all physical quantities are obtained. Findings The derived method is evaluated with numerical results, which are applied to the porous medium in a simplified geometry. Originality/value Finally, the outcomes are graphically represented to show the difference among the models of classical dynamical coupled, the Lord and Shulman and DPL.

Optimizing pink-beam fast X-ray microtomography for multiphase flow in 3D porous media.

A fast pink-beam X-ray microtomography methodology was developed at the GSECARS 13-BMD beamline at the Advanced Photon Source to study multiphase flow in porous media. The white beam X-ray distribution of the Advanced Photon Source is modified using a 1-mm copper filter and the beam is reflected off a platinum mirror angled at 1.5 mrad, resulting in a pink beam with X-ray intensities predominately in the range of 40-60 keV. Bubble formation in the wetting phase and wettability alteration of the solid phase from x-ray exposure can be a problem with high flux and high energy beams, but the suggested pink-beam configuration mitigates these effects. With a 14-second acquisition time for capturing a complete dataset, the evolving fluid-fronts of nonequilibrium three-dimensional multiphase flow can be studied in real-time and the images contain adequate image contrast and quality to measure important multiphase quantities such as contact angles and interfacial areas. LAY DESCRIPTION: Understanding how fluids are transported through porous materials is pertinent to many important societal processes in the environment (e.g. groundwater flow for drinking water) and industry (e.g. drying of industrial materials such as pulp and paper). To develop accurate models and theories of this fluid transportation, experiments need to track fluids in 3-dimensions quickly. This is difficult to do as most materials are opaque and therefore cameras cannot capture fluid movement directly. But, with the help of x-rays, scientists can track fluids in 3D using an imaging technique called x-ray microtomography (μCT). Standard μCT takes about 15 minutes for one image which can produce blurry images if fluids are flowing quickly through the material. We present a technique, fast μCT, which uses a larger spectrum of x-rays than the standard technique and acquires a 3D image in 14 seconds. With the large amount of x-rays utilized in this technique, bubbles can start to form in the fluids from x-ray exposure. We optimized the utilized x-ray spectrum to limit bubble formation while still achieving a rapid 3D image acquisition that has adequate image quality and contrast. With this technique, scientists can study fluid transport in 3D porous materials in near real-time for the improvement of models used to ensure public and environmental health.

Stochastic reconstruction of 3D porous media from 2D images using generative adversarial networks

Micro computed tomography (CT) provides petrophysics laboratories with the ability to image three dimensional porous media at pore scale. However, evaluating flow properties requires the acquisition of a large number of representative images, which is often unfeasible. Stochastic reconstruction methods are algorithms able to generate novel, realistic rock images from a small sample, thus avoiding a large acquisition process. A more convenient approach would use only two dimensional images, replacing 3D scans with images of the rock cuttings made during the drilling. This would extend the technique to media having pores smaller than the resolution of the micro-CT, but that can be imaged by microscopy.We introduce a novel method for 2D-to-3D reconstruction of the structure of porous media by applying generative adversarial neural networks. We compare several measures of pore morphology between simulated and acquired images. Experiments include bead pack, Berea sandstone, and Ketton limestone images. Results show that our GANs-based method can reconstruct three-dimensional images of porous media at different scales that are representative of the morphology of the original images. Also, compared to classical stochastic methods of image reconstruction, the generation of multiple images is much faster.

3D measurements of hydrate surface area during hydrate dissociation in porous media using dynamic 3D imaging

A better understanding of the kinetics of hydrate dissociation is essential to reliably predict gas production potential from natural hydrate reservoirs. Most hydrate dissociation models assume hydrates to be a constant number of equal-sized spheres dissociating at a constant rate. This paper uses dynamic 3D synchrotron micro-computed tomography (SMT) imaging to study hydrate surface area evolution during Xenon hydrate dissociation. Hydrates are formed inside a high-pressure low-temperature cell filled with partially saturated ASTM 20-30 Ottawa sand. Hydrate dissociation is initiated through depressurization in the first experiment and through thermal stimulation in the second experiment. During dissociation, continuous full 3D SMT images were acquired where each scan took 45 s to complete. A combination of cementing, pore-filling, and surface coating pore habits were observed for the depressurization experiment and pore-filling for the thermal stimulation experiment. Surface coating hydrates dissociate faster than hydrates with pore-filling pore habit due to the higher specific area which allows for more surface for hydrates to dissociate it. Direct measurements of hydrate volume and hydrate surface area suggest that even with a combination of hydrate pore habits formed within the 3D porous media, estimation of hydrate surface area as a linear relation with (hydrate volume)2/3 is best for hydrate saturation less than a threshold value depending on the dissociation method and driving force. (hydrate volume)2 and (hydrate volume)3 were found to better estimate hydrate interfacial area in comparison to (hydrate volume)2/3 for the depressurization experiment and thermal stimulation experiment, respectively.