Interfacial phenomena in shale reservoirs: Molecular insights into adsorption, wettability, and nanoconfined flow.

Rate-transient analysis (RTA) is a robust technique for evaluating reservoir/stimulation properties and for forecasting production from shale reservoirs. However, knowledge of fluid storage and flow mechanisms, and controlling rock and fluid parameters, is critical for obtaining meaningful information from RTA. It is common practice to use PVT data measured in laboratories (i.e. bulk fluid properties) for reservoir modeling and production data analysis purposes. These measurement techniques were developed for conventional reservoirs and cannot explain some of the anomalous fluid production behaviors observed for shale gas-condensate wells, such as long-term constant gas/oil ratio (GOR) trends. One explanation for this behavior is that the PVT properties of fluids are affected by confinement in nano-scale pores, and hence deviate from bulk fluid properties. In order to study the effects of pore confinement on fluid properties in shales, the simplified local density (SLD) model is used. The SLD model can be used to estimate fluid density gradients from pore wall to pore center, and therefore explicitly considers pore geometry in adsorption modeling. This model can also be used to adjust the confined fluid critical properties, phase envelope and viscosity. Significant shifts in phase envelope and fluid properties due to pore confinement are observed in this work. Importantly, the corrected equation-of-state predicts a later onset for condensate dropout in shale reservoirs than for bulk systems. The SLD model is also used to estimate adsorbed layer thickness, which in turn is used to modify flow calculations. The corrections for fluid properties, adsorbed layer thickness and non-Darcy flow are then analytically incorporated into transient linear flow analysis of nanoporous shale gas-condensate wells. Analysis of simulated cases using the "corrected" (for pore confinement effects) and "uncorrected" RTA is performed to quantify errors associated with the latter. This study demonstrates that failure to account for pore confinement effects on fluid properties and fluid flow results in errors in linear flow parameter estimation using RTA, but the error depends on the fluid composition, pore size, permeability and pressure. The effects of pore confinement should therefore be considered for proper evaluation of shale gas-condensate reservoirs using analytical or numerical methods.

Gas injection presents unique enhanced oil recovery (EOR) mechanisms in shale reservoirs compared to conventional reservoirs due to the complex nature of fluid transport and fluid-solid interaction in nanopores. We propose a multiphase multicomponent transport model for primary production and gas injection in shale reservoirs considering dual scale porous medium and fluid-solid interactions in nanopores. The shale matrix is separated into macropore and nanopore based on pore size distribution. The density functional theory is employed, accounting for fluid-solid interactions, to compute the inhomogeneous fluid density distribution and phase behavior within multiscale matrix. The calculated fluid thermodynamic properties and transmissibility values are then integrated into the multiphase multicomponent transport model grounded in the Maxwell-Stefan theory to simulate primary production and gas injection processes. Our research underscores the precision of density functional theory in capturing intricate fluid inhomogeneities within nanopores, which is overlooked by the cubic equation of state. The fluid system within varying pores can be classified into confined fluid and bulk fluid, separated by a pore width threshold of 30 nm. Distinct fluid compositions are observed in macropores and nanopores, with heavy components exhibiting a preference for distribution in nanopores due to stronger fluid-solid interactions compared to light components. During primary production period, the robust fluid-solid interactions in nanopores impede the mobility of heavy components, leading to their confinement. Consequently, heavy components within nanopores are difficult to extract during primary production processes. During the CO2 injection period, the injected CO2 induces a significant alteration in fluid composition within both macropores and nanopores, promoting fluid redistribution. The competitive fluid-solid interaction of CO2 results in efficient adsorption on pore walls, displacing propane from nanopores.

Interest in understanding the underlying physical mysteries that result in production from liquid rich shale (LRS) reservoirs is growing globally. Compositional modeling of fractured multiphase shale reservoirs is a complex process that is yet to be fully understood. Our quest in this work is to explore some of the key fundamentals of flow in nano-porous media. This study analyzes the impact of capillary pressure and critical property shifts due to the pore proximity effect on hydrocarbon production in multiple realistic scenarios of flow in shale reservoirs. While many past researches have attempted to show the significance of nano-forces in shale reservoirs, the actual impact that these have on large-scale hydrocarbon production is not fully understood. Response of wells in shale oil reservoirs is tied to both reservoir conditions and fluid system of interest. This work provides an assessment of the magnitude and the ultimate significance of the forces that arise in tight pores, using a fully compositional reservoir simulator. We studied the impact of capillary pressure amidst variations in pore size distributions, fluid composition, reservoir pressure conditions and the presence of fractures that are typical to shale reservoirs. In conventional compositional modeling phase behavior is assumed to be independent of capillary pressure. However, in the presence of nano-pores the magnitude of the differences in phase pressures can be very large. Here we present a systematic study of the influence of this phenomenon on recovery from shale reservoirs. Our findings indicate that the impact of these nano-forces on hydrocarbon production is influenced by variations in shale reservoir/fluid properties. Shale reservoirs entail a great deal of geological uncertainty, and can contain a wide spectrum of hydrocarbon fluids that may range from low GOR black oil to dry gas. Further complications arise from uncertain pore size distribution and improperly characterized fracture networks.

An improved convolutional architecture for quantitative characterization of pore networks in fine-grained rocks using FIB-SEM

Gas production from shale reservoirs is expected to last for hundred years by some estimates. However, the phase behavior of gas in shale reservoirs is inherently more complex compared to the conventional ones. In shale reservoirs, a large amount of gas is stored in nano-size pores which are an integral part of kerogen structure. The phase behavior of this fluid is significantly different from those in the bulk and is still far from being fully investigated. Better understanding of the influence of nano-confinement on the fluid phase behavior should help in estimating the amount of gas in place and to develop an optimum production plan to maximize the recovery. Using molecular dynamics simulations, we modeled methane's phase behavior in shale gas reservoirs wherein the nano-pores in the kerogen play a major role in adsorption of the gas molecules. A fully atomistic model was used for methane and the pore walls; the pore walls were represented by graphite sheets. Eight pores of width ranging from 0.7 nm up to 4.0 nm were considered; the pores were connected to a bulk volume (reservoir). The amount of free and adsorbed gas in the pores was calculated in the pressure range from 6000 to 100 psi. The results demonstrate the influence of pore size on the mechanism of gas release and its dynamics. The gas production rate from pores is a result of the interplay between the rate of transport of a free gas molecule out of the pore, and the rate of desorption of the adsorbed gas from the pore wall. For the smallest pores, adsorption plays the main role in controlling the dynamics as compared with the large ones. Our data can be utilized for predicting the rate of gas production from shale gas based on the pore size distribution and fluid composition.

More and more attention has been paid to the oil and gas flow mechanisms in shale reservoirs. The solid–fluid interaction becomes significant when the pores are in the nanoscale. The interaction changes the fluid’s physical properties and leads to different flow mechanisms in shale reservoirs from those in conventional reservoirs. By using a Simplified Local Density–Peng Robinson transport model, we consider the density and viscosity profiles, which result from solid–fluid interaction. Gas rarefaction effect is negligible at high pressure, so we assume it is viscous flow. Considering the density- and viscosity-changing effects, we proposed a slit permeability model. The velocity profiles are obtained by this newly established model. This proposed model is validated by matching the density profile and velocity profile from molecular dynamic simulation. Then, the effects of pressure and pore size on gas and oil flow mechanisms are also studied in this work. The results show that both gas and oil exhibit enhanced flow rates in nanopores. Gas-phase flow in nanopores is dominated by the density-changing effect (adsorption), while the oil-phase flow is mainly controlled by the viscosity-changing effect. Both gas and oil permeability quickly decrease to the Darcy permeability when the slit aperture becomes large. The results reported in this work are representative and should significantly help us understand the mechanisms of oil and gas flow in shale reservoirs.

The implementation of cyclic gas injection, commonly known as huff-n-puff, holds significant promise in augmenting hydrocarbon recovery from shale oil reservoirs and addressing condensate blockage in liquid-rich shale formations. The effectiveness of huff-n-puff, however, depends greatly on the composition of both the reservoir fluid and the injected gas. Particularly in ultratight shale reservoirs, where diffusion and sorption play pivotal roles, a precise understanding of their influence on huff-n-puff performance becomes crucial for accurate predictions of oil recovery and solvent retention. To thoroughly assess the huff-n-puff process in shale reservoirs, we conducted extensive large-scale numerical simulations using a dual-porosity naturally fractured compositional model that incorporates molecular diffusion and sorption mechanisms. The Langmuir's adsorption model was employed to account for adsorption effects within the system. Rigorous grid block sensitivity analysis was performed to minimize numerical errors and enhance simulation accuracy. By evaluating the impact of diffusion and sorption on production performance for different fluid and injection gas combinations, we established correlations between the considered characteristics and the huff-n-puff performance. To conduct this evaluation, we selected the Eagle Ford Formation, a highly developed shale with a wide range of pressure-volume-temperature (PVT) windows, from dry gas to black oil. The simulation outcomes revealed that methane (CH4) and cyclic-produced gas exhibited the highest recovery potential, while carbon dioxide (CO2) yielded the lowest production results. The performance of the solvent was notably influenced by the content of light components in the fluid and the gas-oil ratio (GOR). Neglecting molecular diffusion, especially during the soaking period, led to underestimation of recovery factors, whereas disregarding the adsorption effect resulted in overestimation of recovery. Furthermore, we observed that the adsorption of intermediate components on the surface of organic pores in shale gas condensate effectively pushed condensate out of the pores, mitigating condensate blockage around the wellbore. This work aims to provide further insights into the huff-n-puff performance in shale reservoirs by focusing on the reservoir fluid and injection gas compositions. The results of this work will improve our understanding of the relationship between fluid compositions and diffusion and sorption. Furthermore, our findings provide insights into the optimization of the huff-n-puff process in shale reservoirs.

Understanding the complex pore architecture of shale reservoirs remains a key challenge for accurate assessment of gas storage and transport behavior. A comprehensive investigation was conducted to quantify the nanopore architecture and fractal characteristics in shale formations from both the marine and continental depositional environments. A combination of X-ray diffraction (XRD), low-pressure nitrogen and carbon-dioxide adsorption (LP-N 2 A/-CO 2 A), and scanning electron microscope (SEM) were employed to investigate mineral composition, pore geometry, specific surface area, pore volume, and heterogeneity across micro- to macro-scales. SEM imaging revealed pronounced variability in pore morphology and heterogeneity, with fractal dimensions highly dependent on magnification and imaging location. These results highlight the importance of multi-scale imaging for representative quantification of shale pore networks. Gas adsorption results showed that microporous specific surface area (SSA) and pore volume (PV) are positively correlated with total organic carbon (TOC), whereas meso-/macro- porous development is primarily influenced by clay mineral content. Pore size distribution (PSD) trends differ notably by depositional environment: marine shale samples exhibit unimodal PSDs, while the continental sample displays a bimodal pattern. Fractal dimensions derived from Frenkel–Halsey–Hill (FHH) analysis of LP-N₂A isotherms ( D ₂ = 2.61–2.89) indicate varying degrees of surface roughness and pore complexity. The combined application of adsorption analysis, imaging, and fractal theory offers a robust framework for characterizing pore systems and assessing storage capacity and transport potential in shale reservoirs.

The transient flow between matrix and natural fractures significantly impacts the exploitation of shale oil reservoirs. Existing characterization models, however, primarily target conventional fractured reservoirs, neglecting the specific mechanisms of shale, including nonlinear flow and stress sensitivity. A new characterization model for shale matrix-natural fracture flow is developed by incorporating these critical mechanisms. The shale reservoir flow equations were first constructed considering nonlinear flow and the stress sensitivity of the matrix. Then, the governing equations are solved numerically using a fully implicit scheme. Based on the equations, the dimensionless shape factor for matrix-fracture flow is derived via the material balance method. Our results demonstrate the time-dependent behavior of the shape factor in shale reservoirs, with values lower than in conventional fractured reservoirs except during initial flow periods. More pronounced nonlinear flow characteristics in the shale matrix result in smaller dimensionless shape factors. In addition, increased stress sensitivity in the shale matrix leads to more significant permeability reduction, yielding smaller dimensionless shape factors. An empirical correlation between dimensionless shape factor and dimensionless time is established through multiple numerical simulations and regression analysis. This model improves matrix-fracture flow characterization in shale systems and can be employed in reservoir numerical simulations to accurately predict the well-production performance, which is essential for the efficient exploitation of shale oil.

Hydraulic fracturing for shale gas production involves pumping large volumes of water; as a consequence of this, produced water management is an important topic to address in order to sustainably produce shale gas. It has been well documented that only approximately 10-40% of the pumped fluids will be produced back to the surface, and that there will be increased concentrations of various ions in the flowback water during this process. This flowback water, with high total dissolved solids and high concentrations of certain ions, presents a significant risk of mineral scaling (Blauch, 2009). In general, it can be very challenging to identify the in situ formation water composition in shale reservoirs since samples of the formation water can be difficult to obtain. They may have been contaminated during the drilling process, reactions may have taken place due to fluid mixing between the injected fluid and the formation water, or simply they may not have been preserved appropriately (Pan, 2017). Some calculations of formation water compositions require to be preceded based on the observed compositional data; thereafter, the predicted formation water compositions are validated by comparison with the observed total dissolved solids (TDS) data. A two-phase 3D numerical flow model has been developed that includes a hydraulic fracture and is populated with shale reservoir properties. (This model assumes the hydraulic fracture is already established – i.e. the calculations include coupled flow and component transport, but the geomechanics are not considered). It is used to simulate fluid transport mechanisms within the shale system and to address the question – what causes the significant retention of fracture fluid in shale reservoirs. A series of simulations was performed to achieve a history match with observed flowback water data in a western Canadian basin (the Horn River Basin). A further two-phase 3D flow model was developed to examine the scaling tendency due to the evolving produced brine composition over the lifetime of the well. It is based on the previously history matched model and includes the fracture fluid and formation water compositions to predict precipitation of minerals. Finally, scale inhibitor injection was simulated to examine the impact of inhibitor retention on well protection.

The current models for predicting the phase behavior of gas injection in shale can be highly unreliable because nanopores (with diameters less than 50 nm) form a significant pore volume in many shale formations. Conventional PVT models cannot describe the phase behavior in nanopores. Here, we present a practical framework to regenerate the PVT considering the shale nanopores effect for a more reliable compositional simulation of gas injection in shale reservoirs by using existing commercial simulators. The pore-size distribution in shale reservoirs can be discretized into a bulk-region (fractures and macropores) and nanopores. We use a pore-size-dependent equation of state (PR-C EOS) to describe the phase behavior of the fluid for each pore. Bulk fluid characterization with laboratory PVT reports determines the bulk fluid parameters for the PR-C EOS. The confinement parameters for the PR-C EOS are from the reported database (Luo et al. 2018a). Further, multi-scale phase equilibria are calculated by minimizing the free energy. We model the multi-scale constant composition expansion and constant volume depletion with volume expansion per stage. The modeling generates multi-scale PVT (formation volume factor, saturation, etc.) for the shale reservoir, which is used to retrain the Peng–Robinson equation of state (PR EOS) by modifying the acentric factor, binary interactions, and critical temperature and pressure. The retrained PR EOS is then applied in a commercial compositional simulator to forecast gas injection improved oil recovery (IOR) in shale. We also use the updated gas saturations in the multi-scale PVT model to modify the relative permeability tables used in the compositional simulation. We predict significantly higher gas production and lower oil production when the effect of shale nanopores on the phase behavior and updated relative permeability are considered in the compositional simulation of the primary depletion of shale reservoirs. In the gas injection improved oil recovery (IOR) stage, the cumulative oil production is enhanced with both the original and multi-scale PVT models. However, when the effect of nanopores is not considered in the compositional simulation, the increases in the cumulative oil production and cumulative gas production can be underestimated and overestimated, respectively. This can have significant consequences on the economic evaluation of the gas IOR projects in shale reservoirs. The application of multi-scale phase equilibria in shale reservoirs is challenging in compositional simulators. Our proposed framework enables engineers to incorporate multi-scale phase equilibria from the PR-C EOS in their shale reservoir simulations. It does not require a change in the cubic equations of state in current developed commercial compositional simulators, thus preserving the efficiency of the compositional simulators.

Because of the confinement effects in shale formations, fluid flow is different compared to conventional reservoirs. The interactions between the fluid molecules and porous wall inside nanopores play such an important role that can change the phase behavior of the fluids. The fluids in shale reservoirs are usually stored in two forms, free fluids and adsorbed fluids. The region where free fluids are stored has negligible fluid-wall interactions while the region for adsorbed fluids is under strong pore wall influence. The current available equations of state cannot capture the phase behavior of the adsorbed phase in porous media due to the ignorance of the fluid-wall interactions. This paper discussed the effects of the fluid-wall interactions on fluid phase behavior from a modeling of of view. The production from shale reservoirs in the US has shifted from gas windows to condensate windows and oil windows recently due to low natural gas price. Liquid-rich shales, such as Barnett, Eagle Ford, and Marcellus are brought more attentions than ever before. Thus, it is critical to understand the fluid phase behavior and properties and their impacts on production in the condensate systems. Our work focuses on the predictions of fluid critical property change and fluid density change inside nanoporous media. Simplified Local-Density theory for single component coupled with modified Peng-Robinson Equation of State was used to predict the density profiles of dry gas (pure methane) in confined pores. The model was then extended to mixtures for the study of condensate systems. Our results showed that due to the fluid-wall interactions, the fluid density is not uniformly distributed across the pore. The fluid density is higher near the wall than that in the center region of the pore. It also showed that depending on fluid types, temperature, pressure and pore sizes, the fluid density profile would change. The pore size range we focused on was from 2 nm to 10 nm. In order to present the condensate system, a synthetic mixture of 75% methane and 25% n-butane is used. It is found that fluid composition is not uniform across the pore. Heavier component (n-butane) tends to accumulate near the wall while lighter component (methane) would like to stay in the center region of the pore. For a 10 nm wide pore, the composition of n-butane of the synthetic mixture can be as high as 66% close to the pore wall.

This paper investigates the phenomenon of anomalous imbibition in shale reservoir rocks through a combination of numerical and experimental approaches. Shale gas reservoirs present unique challenges due to their low permeability and complex pore structure, significantly influencing fluid transport mechanisms. Spontaneous imbibition, where water (or fracturing fluids) infiltrates the shale matrix and displaces the gas driven by capillary force, plays a critical role in the recovery efficiency of shale gas reservoirs. Fluid spontaneous imbibition in heterogeneous porous media, such as tight and shale formations, often exhibits anomalous behavior dominated by multiple time-spatial scales. Based on direct experimental evidence of anomalous imbibition process, this work proposes a fractional derivative model to quantitatively analyze the complete early-to-late time dynamics of the anomalous imbibition in shale gas reservoirs. Prior research on the anomalous imbibition process has primarily focused on fractal models and has compared results with indirect indicators, such as the cumulative imbibed volume derived from imbibition experiments. This study introduces direct observations and quantifications of the anomalous imbibition dynamics, utilizing saturation distributions converted from Computed Tomography (CT) numbers. A fractional diffusion model is proposed, and the resulting non-linear fractional differential equations are solved numerically using the finite-difference method. The proposed model solution accurately captures the complete early-to-late time behavior of cumulative recovery volume and the wetting phase front propagations which exhibit anomalous phenomena.

Determination of solvation free energy of carbon dioxide (CO2) in the mixture of brine, Alfa Olefin Sulfonate (AOS) and CH4 after foam fracturing in the shale reservoirs on enhanced shale gas recovery (ESGR)

Homogenized lattice Boltzmann model for simulating multi-phase flows in heterogeneous porous media