Wettability is a key parameter that determines the distribution and behavior of fluids in the porous media of oil reservoirs. Understanding and controlling wettability significantly impacts the effectiveness of various enhanced oil recovery (EOR) methods and CO2 sequestration. This review article provides a comprehensive analysis of various methods for measuring and altering wettability, classifying them by mechanisms and discussing their applications and limitations. The main methods for measuring wettability include spontaneous imbibition methods such as Amott–Harvey tests and USBM, contact angle measurement methods, and methods based on the characteristics of imbibed fluids such as infrared spectroscopy (IR) and nuclear magnetic resonance (NMR). These methods offer varying degrees of accuracy and applicability depending on the properties of rocks and fluids. Altering the wettability of rocks is crucial for enhancing oil recovery efficiency. The article discusses methods such as low-salinity water flooding (LSWF), the use of surfactants (SAAs), and carbonated water injection (CWI). LSWF has shown effectiveness in increasing water wettability and improving oil displacement. Surfactants alter interfacial tension and wettability, aiding in better oil displacement. CWI also contributes to altering the wettability of the rock surface to a more water-wet state. An important aspect is also the alteration of wettability through the dissolution and precipitation of minerals in rocks. The process of dissolution and precipitation affects pore structure, capillary pressure, and relative permeabilities, which in turn alters wettability and oil displacement efficiency.

Relative phase permeability is an important characteristic of multiphase flow in porous media. Its assessment is an urgent issue when the pore structure changes due to rock dissolution. This article examines the effect of carbonate rock dissolution on two-phase flow based on images obtained by X-ray microcomputed tomography with a spatial resolution of ~18 µm. The characteristics of the two-phase flow were calculated through pore network modeling. The studies were conducted on 20 sub-volumes, which were extracted from cylindrical samples A and B with permeabilities of 0.72 and 0.29 D. HCl solutions (12% and 18%) were injected into samples A and B at a rate of 8 and 2 mL/min, respectively. Due to rock dissolution, the porosity and absolute permeability of the sub-volumes increased by 1.1–33% and 44–368%, respectively. Due to dissolution, the residual oil and water saturations decreased by 20–46% and 25–60%, respectively. These results showed that an increase in absolute permeability led to a significant reduction in residual oil and water saturations. These results also demonstrated that rock dissolution resulted in a change in the spatial heterogeneity of the relative phase permeabilities. The spatial heterogeneity increased in sample A after rock dissolution, while in sample B, it decreased.

This work develops and systematically evaluates a physics-informed neural network (PINN) solver for the fully coupled, time-dependent Muskat–Leverett system with capillarity modeled in the pressure equation. A single shallow–wide multilayer perceptron jointly predicts wetting pressure and water saturation; physical capillary pressure regularizes the saturation front, while a small numerical diffusion term in the saturation residual acts as a training stabilizer rather than a shock-capturing device. To guarantee admissible states in stiff regimes, we introduce a saturation soft-clamping head enforcing $0<{\mathrm{S}}_{\mathrm{w}}<1$ and activate it selectively for stiff mobility ratios. Using IMPES solutions as reference, we perform a sensitivity study over network depth and width, interior collocation and boundary data density, mobility ratio, and injection pressure. Shallow-wide networks (10 layers × 50 neurons) consistently outperform deeper architectures, and increasing interior collocation points from 5000 to 50,000 reduces mean saturation error by about half, whereas additional boundary data have a much weaker effect. Accuracy is highest at an intermediate mobility ratio and improves monotonically with higher injection pressure, which sharpens yet better conditions the front. Across all regimes, pressure trains easily while saturation determines model selection, and the PINN serves as a physics-consistent surrogate for what-if studies in two-phase porous-media flow.

Permeability is a key transport property of porous materials, and its accurate evaluation is relevant when studying applied tasks, such as CO₂ injection into reservoirs and investigating groundwater quality. This study examines the dependence of permeability on total and connected porosity, hydraulic tortuosity, specific surface area, and mean pore radius based on the data of 408 cubic sub-volumes extracted from heterogeneous and naturally fractured cylindrical carbonate samples, before and after injection of HCl solutions. These parameters were computed using pore-scale modeling of fluid flow. Our results show that permeability correlates well with porosity and mean pore radius, with correlation coefficients of $R^2\approx 0.65-0.79$ for heterogeneous samples. It was found that the presence of natural fractures significantly influenced the relationship between permeability and other parameters. The relationship between permeability $k$, tortuosity $\tau$, and specific surface area $S$ is described by the power laws $k~{\tau }^{-\alpha }$ and $k~S^{-\beta }$, with coefficients $\alpha$ and $\beta$ substantially exceeding those in the Kozeny–Carman equation. It was also found that there is a parabolic relationship between connected and total porosities, both before and after rock dissolution with $R^2\approx 0.96-0.99$. This allowed for an estimation of percolation threshold porosity in accordance with the literature data.