Two-phase Fluid Research Articles

Prediction of pressure and temperature profiles for two-phase flow in multilayered gas wells by DTS data

Downhole temperature and pressure data are crucial information to help us understand the fluid flow dynamics in the reservoir. With the advancement of downhole monitoring technology, high-precision and high-resolution monitoring instruments facilitate qualitative and quantitative utilization of transient downhole temperature and pressure data in monitoring applications. The distributed temperature sensors (DTSs) overcome the limitations of traditional monitoring techniques and achieve real-time temperature monitoring in complex downhole conditions. However, the physical phenomena and response mechanisms hidden in the temperature data obtained by (DTSs) in transient, multilayered combined production and two-phase gas wells have not been thoroughly studied yet.Gas-water two-phase fluid flow in the reservoir is the prime consideration of this study. In this paper, based on the principles of mass, energy conservation, Darcy's law, and the second laws of thermodynamics, a forward model is established to predict pressure and temperature distribution in a multilayered vertical gas well system by coupling the flow model and thermal model. The model considers the changes of fluid high-pressure properties and microheat effects such as the Joule-Thomson effect, viscous friction to reach the desired solution. Subsequently, the model is solved numerically and used for sensitivity analysis of parameters influencing temperature and pressure distribution, such as gas production rates, permeability, Joule-Thomson coefficient. At last, the model is applied to a multilayer combined production well. The results of the example show the pressure, temperature and production profile can be predicted precisely.

Numerical Two-Phase Simulations of Alkaline Water Electrolyzers

Alkaline water electrolyzers (AWE) have several advantages over other types of electrolyzers, including their high efficiency and especially their relatively low cost due to the usage of non-precious metal catalysts, such as nickel and iron, for the electrodes. Information about local quantities and physical phenomena such as the formation of gas bubbles, current densities, temperatures or local species concentrations within a running cell are important for their improvement. Multiphysical computational fluid dynamics (CFD) simulations of electrochemical components using detailed three-dimensional models can provide valuable insight on local behaviors and characteristics that are difficult or impossible to measure experimentally.This work extends the CFD library openFuelCell2 1, which has been implemented using the open-source platform OpenFOAM®, to simulate AWE cells. The model considers the major transport phenomena, including two-phase fluid flow, heat and mass transfer, electrochemical reactions, species transfer and charge transfer in the various functional regions of the cell. It employs an Eulerian-Eulerian approach to characterize the behavior of each phase comprising interphase mass transport, momentum exchange and heat transfer. Appropriate mapping functions are used to couple the physically distinct regions together. A Butler-Volmer equation characterizes the electrochemical reactions that are assumed to occur in electrodes of finite thickness.This model is used to simulate a single zero-gap AWE cell, depicted in Fig. 1, for different operating conditions such as varying temperatures and volumetric flow rates. The conducted studies provide insight into the local formation of the created gas phase (bubbles), the distribution of species within the gas and electrolyte and their impact towards the performance of the running cell. These numerically obtained results are compared to in-house available and gathered experimental data. Figure 1 demonstrates that the polarization curves obtained at various temperatures are in good agreement with the experimental data. Figure 1

Geochemical modelling of heavy metal deposition in a geothermal heat exchanger

Heavy metal deposition and corrosion of carbon and low alloy steels exposed to geothermal two-phase fluids and brine solutions under acidic fluid conditions have been widely reported. Similarly, near neutral conditions can result in the precipitation of arsenic and antimony scales that can limit heat exchange. Geochemistry modelling has been undertaken to explain observed deposition and scaling in a two-phase geothermal fluid heat exchanger with a view to predicting the risk of heavy metal deposition and corrosion and heavy metal scaling in geothermal process fluids for new and existing energy facilities. Understanding of the geochemical parameters that control deposition, scaling and corrosion will allow the prediction of the risk of heavy metal deposition and scaling at the design stage for geothermal energy plants and assist in the selection of materials and processes that will give reliable long-term performance. The developed models have application in other industries for prediction of risk of scaling and corrosion and for process development support for example for the gettering of heavy metals from contaminated liquids and soils.

Derivation and simulation of a two-phase fluid deformable surface model

To explore the impact of surface viscosity on coexisting fluid domains in biomembranes we consider two-phase fluid deformable surfaces as model systems for biomembranes. Such surfaces are modelled by incompressible surface Navier–Stokes–Cahn–Hilliard-like equations with bending forces. We derive this model using the Lagrange–d’Alembert principle considering various dissipation mechanisms. The highly nonlinear model is solved numerically to explore the tight interplay between surface evolution, surface phase composition, surface curvature and surface hydrodynamics. It is demonstrated that hydrodynamics can enhance bulging and furrow formation, which both can further develop to pinch-offs. The numerical approach builds on a Taylor–Hood element for the surface Navier–Stokes part, a semi-implicit approach for the Cahn–Hilliard part, higher-order surface parametrizations, appropriate approximations of the geometric quantities, and mesh redistribution. We demonstrate convergence properties that are known to be optimal for simplified subproblems.

Physics-informed neural networks for heat transfer prediction in two-phase flows

This paper presents data-driven simulations of two-phase fluid processes with heat transfer. A Physics-Informed Neural Network (PINN) was applied to capture the behaviour of phase interfaces in two-phase flows and model the hydrodynamics and heat transfer of flow configurations representative of established numerical test cases. The developed PINN approach was trained on simulation data derived from physically based Computational Fluid Dynamics (CFD) simulations with interface capturing. The present study considers fundamental problems, including tracking the rise of a single gas bubble in a denser fluid and exploring the heat transfer in the wake of a bubble rising close to a heated wall. Tracking of a rising bubble phase interface of fluids with disparate properties was performed, revealing a maximum error of only 5.2% at the interface edge and a maximum error of 2.8% at the position of the centre of mass. Inferred (hidden variable) flows are studied in addition to a purely extrapolative inverse isothermal bubble case. When no velocity data was supplied, velocity field predictions remained accurate. Rise of an inferred isothermal bubble with unseen fluid properties was found to produce a maximum mean-squared error of 0.28 and centre of mass error of 1.25%. For the case of the rising bubble with a hot wall, the maximum error in the temperature domain using specified boundary conditions was 6.8%, while the bubble position analysis reveals a maximum positional error of 3.6%. These results demonstrate that PINN is agnostic to geometry and fluid properties when studying the combined effects of convection and buoyancy on two-phase flows for the first time. This work serves as a starting point for PINN in multiphase cases involving heat transfer over a range of geometries. Eventually, PINN will be used in such cases to provide solutions for forward, inverse, and extrapolative cases. Each of which represent a dramatic saving in computational cost compared to traditional CFD.

A thermo-hydro-mechanical damage model for lined rock cavern for compressed air energy storage

Large-scale compressed air energy storage (CAES) technology is regarded as an effective way to alleviate the instability of electricity generated from renewable sources such as wind and solar power, which involves the expensive construction of underground caverns to store highly pressurized and high-temperature compressed air. This study documents mechanical behavior and gas permeability of granite under temperature-pressure synchronous cyclic loading, and the response of the surrounding rock to Thermo-Hydro-Mechanical-Damage (THMD) evolution. Firstly, physical experiments were conducted to examine mechanical property and gas permeability evolutions of granite due to temperature-pressure synchronous cyclic loading. Based on these experiments, equations describing the damage evolution of granite were deduced. Subsequently, using these equations in combination with a thermo-hydro-mechanical coupled model of porous media with two-phase fluid flow, a sophisticated computational routine for the thermo-hydro-mechanical-damage analysis of underground gas storage caverns was developed. Lastly, numerical simulations were conducted to study heat transfer, two-phase seepage, and mechanical response of a CAES cavern under operating conditions. Under low to medium pressure and high-temperature synchronous cyclic loading, granite exhibited a significant variation in elastic modulus and compressive strength. Also, its permeability showed a substantial increase due to damage evolution. After two months of operation, prominent heat transfer was observed in the surrounding rock, particularly in the region extending to approximately 10 m from the inner surface of the cavern, exceeding the range of gas leakage diffusion within the cavern. The plastic zone of surrounding rock is distributed above the cavern's roof and below its bottom. Moreover, areas with higher damage are concentrated in the surrounding rock near the cavern's side walls. These findings contributed to our understanding of the behavior of granite in the context of CAES technology and provided valuable insights for the design and operation of gas storage caverns. The development of the THMD model offered a valuable tool for investigating stress and deformation characteristics of the lining and surrounding rock in CAES plants.

GenEOS: An accurate equation of state for the fast calculation of two-phase geofluids properties based on gene expression programming

Numerical simulation of two-phase multicomponent flows requires solving continuity, momentum, energy, and transport equations. Typically, these conservation equations are solved for computing the main variables of pressure, enthalpy, velocity, and composition. Variation of thermophysical properties (e.g., density, viscosity, etc.) as functions of the main variables necessitates introducing equations of state (EOS) to the modeling scheme, equating the number of unknowns and equations. The problem arises here as almost all the available EOSs in the literature receive temperature as an input, which is not a main variable. Guessing temperature, as an unknown input, imposes more iterations on the already iterative algorithm of the EOS and increases the computational cost. The primary focus of this study is to provide highly-precise, but fast EOS scheme for calculating two-phase fluid properties using artificial intelligence algorithms. In the first step, a Fugacity-Activity model is implemented to supply a supervised learning algorithm with a large dataset. The provided data are fed into a machine-learning (ML) model called gene expression programming (GEP). The outputs of this GEP model are high-preciseness explicit formulas for non-iterative computing of temperature and equilibrium constants. Testing the proposed GEP equations for 1,000,000 arbitrary sets of inputs revealed high accuracy in predicting desired outputs (e.g., < 0.6% error in calculating temperature). Implementing GEP equations in modeling platforms can result in ∼90% reduction in EOS-related computational cost. This ML-based EOS is a transparent box for computing thermophysical properties of two-phase mixtures containing H2O, CO2, CH4, N2, H2S, NaCl, KCl, CaCl2, and MgCl2.

A Comparative Analysis on Single and Two Phase Casson Fluid under Aligned Magnetic Field Effect and Newtonian Heating

This research investigates the impact of aligned magnetic fields and Newtonian heating on single and two-phase Casson fluid (a mixture of Casson fluid and dust particles), addressing a notable knowledge gap in comparing the two fluid models under the same effect. The problem of this study lies in the need to understand the similarities or differences in the reaction of these fluids to external forces. To achieve this, the governing equations for both fluids were formulated using a boundary layer approximation and numerical solutions were obtained utilizing the 'bvp4c' function within MATLAB software. The analysis revealed comparable trends in flow and thermal behaviour between the two fluids, it also showed that the magnetic field exerted a more pronounced influence on flow properties compared to forces such as buoyancy and inertia. Conversely, Newtonian heating conditions had a more significant impact on thermal properties compared to the magnetic field. Additionally, the single-phase Casson fluid showed higher velocity and temperature profiles than the two-phase Casson fluid phases. These findings suggest that the presence of dust particles reduces the velocity and temperature magnitudes of the Casson fluid.

Research on the effects of slurry uniformity and mixing power of continuous cementing slurry mixers based on statistical and CFD methods

To enhance the efficiency of continuous cement mixing in well cementing, a Computational Fluid Dynamics (CFD) approach was employed to investigate the mud flow and mixing processes within the continuous mixing system. This study aims to analyze the influence of various design factors and their interactions on the mixing of different slurries in the well cementing slurry continuous mixer. Using the Response Surface Methodology (RSM) with a Box-Behnken model, this work combines the Euler-Euler multiphase flow model, k-turbulence model, and the Multiple Reference Frame (MRF) method to simulate two-phase fluid flow and agitator rotation, establishing the CFD model of the mixing system. The CFD model, coupled with the RSM method, analyzed four design factors: impeller diameter (400–800 mm), design density (1.4–2.6 g/cm³), impeller speed (100–300 rpm), and particle size (20–500 μm), studying their impact on two response variables, slurry mixing uniformity, and total power consumption. Through RSM and multiple regression analyses, predictive models for slurry mixing uniformity and corresponding power consumption were established under different design factors. Data comparison analysis revealed excellent agreement between predicted and actual results. Findings indicate that, when using uniformity or power as evaluation criteria, the P-value is smallest for impeller speed and largest for particle size. Hence, the impeller speed exhibited the strongest correlation with both, followed by impeller diameter, and lastly, design density and particle size. Only the interaction between impeller diameter and impeller speed (P-value <0.0001) significantly influenced both power and mixing uniformity, with its significance ranking just below the linear effects of impeller speed and diameter. Slurry uniformity decreased with increased design density and particle size, while power consumption exhibited the opposite trend. Uniformity increased with increasing impeller speed, but when the uniformity reached its maximum, further speed increments led to a slight decrease in uniformity, accompanied by a sharp increase in power. This was significantly influenced by the quadratic effect of impeller speed (P-value <0.0001), with its significance weaker than the linear effects. The proposed predictive model accurately forecasts response values for any given design parameter, providing a research direction for optimizing mixer design and selecting corresponding design parameters. This approach streamlines the study of mud mixing systems, reducing research time and costs. Moreover, it offers scientific guidance for optimizing operational parameters corresponding to well cementing conditions.

Two-phase interaction in isothermal hydro-mechanical-chemical coupling for improved carbon geological sequestration modelling

ABSTRACT Geological sequestration is an established method to store carbon deep underground. Many studies have proposed coupled constitutive models that can simulate such a complicated process; however, the coupling effect of multi-phase fluid flow and transport of chemical solutes in the liquid phase remains to be investigated. This study presents a multi-phase non-reactive hydro-mechanical-chemical constitutive framework under isothermal conditions based on mixture coupling theory. Non-equilibrium thermodynamics is used to generate an entropy production equation, and phenomenological equations use this to derive the chemical transport and interaction between two-phase fluid flows. This study proposes novel terms in the final governing equations. The model results are in good agreement with the results of a benchmark experiment and those found in the literature; the model has been used to compare the behaviour of carbon dioxide in the gas and supercritical phases. Sensitivity analysis was conducted to determine the effect of the parameters in the new terms. Sensitivity analysis revealed the significant impact of relative permeability and saturation values on the new terms, emphasising the importance of understanding frictional behaviour in porous media for accurate fluid flow modelling and prediction. This study urges further experimentation and model refinement to improve carbon sequestration modelling in larger formations.

On aeroelastic flutter assessment of thick nanoshell convening two-phase fluid flow using mathematical simulation and deep-neural networks

It is well known that flow-induced vibration occurs often in many different sectors. Dynamic fluid forces are produced by the flow, and these forces cause the system to become excited. One of the most prominent flows in nature and industrial domains, such as industrial facilities, is the multiphase flow which may contribute to creating noise and vibration. As one specific example of a multiphase flow, a two-phase flow relies heavily on flow arrangement for its characteristics. Furthermore, despite the most recent developments and advancements, flow-induced vibration is still considered an open topic. So, in this work, for the first time, frequency analysis of a thick nanoshell convening two-phase fluid flow subjected to aerodynamic pressure is presented. Via nonlocal strain gradient theory (NSGT), Hamilton's principle, trigonometric shear deformation theory, the reappraisal of the fluid-structure interaction relation, and non-conservative aerodynamic pressure formulation, the governing equations, and various boundary conditions of the system are presented. After that, using the generalized differential quadrature method (GDQM) the obtained governing equations are solved, numerically. For more verification of the results, the results are compared with the outcomes of the artificial neural network (ANN) model. For this purpose, the obtained results using mathematical modeling are presented to generate the training dataset and test dataset of the neural network in batches. Finally, some suggestions for improving the stability of the thick nanoshell convening two-phase fluid flow subjected to aerodynamic pressure are presented for future handbooks.

Dynamic behavior of axially functionally graded pipe conveying gas–liquid two-phase flow

The dynamic behavior of an axially functionally graded pipeline conveying gas–liquid two-phase flow is studied using the Euler–Bernoulli beam model and the generalized integral transform method (GITT). The influence of changes in functionally graded material parameters, boundary conditions, and gas volumetric fraction of two-phase flow on the linear stability of functionally graded pipes is investigated. The results indicate that the gradient of elastic modulus has a significant influence on the complex frequency, critical velocity for instability, and coupling flutter of the functionally graded pipeline. Additionally, the gradient of density has a significant effect on the complex frequency of the functionally graded pipe. The boundary conditions of the pipe have a significant influence on its dynamic response. The pipe exhibits higher stability when both ends are fixed, followed by the combination of fixed support and simple support. Conversely, the condition of simply supported at both ends is the most susceptible to instability. The gas volumetric fraction also plays a significant role in the dynamic behavior of functionally graded pipes conveying gas–liquid two-phase fluids.

Pressure Analysis Investigation of PEM Electrolyzer Cell Used for Green Hydrogen Production

Increasing environmental concerns with climate change have led many people around the world to demand urgent action, forcing national governments to seek alternatives to carbon-based fuels. In the light of all this, it is of critical importance for our civilization that carbon-based energy sources are rapidly replaced by renewable and sustainable sources without carbon emissions. For this reason, the use of these clean energy sources and the efficiency of the processes in their production is a very important issue. In this study, 3-dimensional, two-phase (hydrogen and water) computational fluid dynamics (CFD) analysis was performed in a polymer electrolysis membrane cell (PEM). Analysis took place for 30 seconds. The water flow rate was kept constant at 260 ml/min. As a result of the analysis, pressure, gas volume fraction and velocity data in the manifolds and in the electrolysis channels where the electrolysis process takes place were interpreted. While the pressure change in the cell was quite high in the range of 0-1.8 seconds from the beginning of the flow, it was observed that a balance was formed in the pressure distribution after 1.8 seconds. It is understood that the number of channels in the model is a factor for the pressure inside the manifold and the cell. However, it was observed that the unit gas production amount in the cell also changed along the channels.

Effects of displacement velocity on interfacial reconstruction events during immiscible two-phase displacement

During the two-phase fluid displacement in porous media, with the increase in capillary number Ca, different wettability effects are suppressed; however, its potential control mechanism has not been clarified. Therefore, in this study, we have analyzed the pore scale process related to interface reconfiguration events in detail and profoundly clarified the nature of a series of interface reconfiguration events being suppressed. Based on typical pore throat, we elaborated and confirmed that the development and evolution direction of fluid displacement mode always follow the principle of minimum operating power. That is to say, in order to avoid extra work, the system will compare all the potential moving meniscus at the displacement front and always choose the local path with the minimum operating power (Po=ΔpQ) of the system for displacement. Under this theory, a series of interface reconfiguration events are considered energy favorable self-regulation events derived by the system in order to avoid extra energy consumption. However, the appearance and disappearance of interface reconstruction events are considered to be the result of the mechanism of “self-regulation of surface energy change rate” and “self-regulation of viscosity dissipation rate” in order to approach the minimum operating power. This study provides us with a sufficient physical explanation to understand the nature of the wettability effect being suppressed.

Rising of asymmetric bubble through milli-tubes: Experimental, theoretical and numerical analysis

Appearance of Taylor bubble is ubiquitous in two-phase fluid flow through millimeter-sized tubes. Precise control over bubble generation and stability in those tubes are instrumental in unit processes in fine chemical industries. In this article, we systematically study the role of wall surface wettability in the structure and dynamics of the gaseous bubble flowing through water across milli-tubes. Specifically, from imaging experiments, we find that in a non-wettable milli-tube, the bubble loses its axial symmetry to reduce contact of the liquid phase with the tube wall. Moreover, we observe that the bubble speed is significantly higher in hydrophobic-coated tubes in comparison to the tubes without coating. Computational simulation balancing the viscous, gravitational, and surface forces recovers the observed effect of surface wettability on bubble shape and velocity. Finally, we establish the observed quantitative correlation between the bubble velocity and the surface wettability using an analytical model. Altogether, integrating experiments, numerical simulation, and theoretical analysis, we demonstrated the significant influence of wall-surface wettability in the shape and velocity of the Taylor bubble through milli-tubes.

A Lumped-Parameter Model of a Smart Ventilation unit for nearly Zero Energy Buildings

In the present work, a simple model of a ventilation unit used for residential purposes is proposed, which was developed by means of MATLAB Simulink and the Simscape toolbox, also including the Moist Air and Two-Phase fluid libraries. This study falls in the realm of air conditioning in nearly Zero Energy Buildings. The model presented here is focused mostly on the aeraulic system. A parametric analysis of various installation conditions was conducted to assess and enhance the combined heat pump and the air distribution system performance, under various operating conditions. Therefore, the overall approach included several parameters, such as outdoor and indoor air temperature, humidity, static pressure, pressure drop in the intake and the distribution ducts, and filter fouling. The model serves as a predictive tool to evaluate the effectiveness of the whole system, in both design and off-design conditions; notably, critical conditions are emphasized, which are associated to severe fouling conditions, making the use of an additional fan ineffective.

On the use of a tailored fluid-fluid Green's function to predict scattering from two-phase fluid interfaces

In naval applications, the precise knowledge of the acoustical behaviour of two-phase fluids is of interest. Indeed, they appear in many configurations as bubbles curtains, cavitation (along propellers and pipes) or two-phase turbulent boundary layers and wakes (gas exhaust). To model this problem, we focus on a Boundary Element/ Boundary Element coupling for low to moderate frequencies. We propose two approaches: (a) solving the Helmholtz equations in each phase by introducing the free field Green's function and (b) determining a tailored Green's function, taking into account the presence of the two-phase fluid. The determination of a tailored Green's function has two main advantages: (i) it allows a reduction of the numerical model, since it contains all the information on the fluid-fluid coupling, in particular the transmission conditions and resonances and (ii) it is source-independent and thus it gives directly the answer to any source. Numerical tests on the evaluation of radiated noise are performed to determine the efficiency of the approach based on a tailored Green's function compared to the free-field based one.

Nonconforming mixed finite element method for the diffuse interface model of two-phase fluid flows

In this work, we consider a nonconforming mixed finite element method (MFEM) for a parabolic system consisting of the Cahn-Hilliard equations and the Navier-Stokes equations, which describes a diffuse interface model for the flow of two incompressible and immiscible fluids. We focus on the superconvergence analysis for the corresponding first order convex splitting scheme, where the bilinear element is used to approximate the Cahn-Hilliard equation in space, and the constrained nonconforming rotated (CNR) Q1 element together with the Q0 constant element to the Navier-Stokes equations. By use of the high accuracy properties of the elements and some specific techniques, the superclose results of order O(h2+τ) for the concentration ϕ and the chemical potential ω in the H1-norm, the velocity u in the broken H1-norm and the pressure p in L2-norm are strictly proved. Here, h is the subdivision parameter and τ, the time step. It is worth to say that we derive a new high accuracy character through the integral identity technique for the chosen elements, which plays a quite significant role in getting the final error results. Furthermore, the global superconvergence results of the corresponding variables are concluded by the interpolated postprocessing technique. Numerical tests are provided to justify the performance of the theoretical analysis.

Numerical prediction of the two-phase flow and radiation effects on the thermal environment and ablation of solid rocket nozzle

The effects of two-phase flow and radiative heat transfer have a significant impact on the internal thermal environment and thermochemical ablation process in aluminized solid rocket motor (SRM). However, these two effects were not revealed systematically in previous studies. In this paper, a multiscale methodology combined radiative properties of molten alumina particles at microscale calculated by Mie theory and the two-phase flow and radiative heat transfer at macroscale calculated by Eulerian-Lagrangian method coupling with discrete ordinate method is constructed within aluminized SRM. The convection and radiation are coupled with the chemical kinetics to predict the thermochemical ablation and thermal environment. The influence of two-phase fluid flow and thermal radiation on the internal thermal environment and thermochemical ablation of a SRM nozzle is analyzed quantitatively. Comparisons are made among the methodologies that models the alumina particles as gas species, considers the effect of two-phase flow and considers the effects of two-phase flow and radiative heat transfer. The results show that the erosion rate and total heat flux at the inner wall in the convergent section increase noticeably when considering the effect of two-phase flow. Meanwhile, the erosion rate in the divergent section also increases and the thermal environment is dependent on the particle size and aluminum content. Radiative heat transfer considerably enhances the total heat flux, especially in the convergent section. On the contrary, its impact on the erosion rate is very small except for the inner wall with very low temperature.

Snap-Off during Imbibition in Porous Media: Mechanisms, Influencing Factors, and Impacts

The phenomenon of snap-off during imbibition in porous media, a fundamental two-phase fluid flow phenomenon, plays a crucial role in both crude oil production and carbon dioxide (CO2) utilization and storage. In porous media where two phases coexist, the instability of the phase interface may give rise to various displacement phenomena, including pore–body filling, piston-like displacement, and snap-off. Snap-off, characterized by the generation of discrete liquid droplets or gas bubbles, assumes paramount significance. This study provides a comprehensive overview of snap-off mechanisms, influencing factors, and impacts. Snap-off initiation arises from variations in the curvature radius at the interface between two phases within narrow regions, primarily influenced by capillary pressure. It can be influenced by factors such as the characteristics of multiphase fluids, the wettability of porous media, as well as the pore–throat geometry and topology within porous media. In turn, snap-off exerts a discernible influence on the fluid dynamics within the porous medium, resulting in impacts that encompass unrecoverable oil droplet formation, the oil bridging effect, drainage–imbibition hysteresis, strong foam generation and transient/dynamic effects. Although the snap-off phenomenon exerts detrimental effects during the conventional waterflooding in oil production, its potential is harnessed for beneficial outcomes in CO2-EOR and CO2 storage. This study significantly advances our understanding of snap-off and its multifaceted roles in multiphase fluid dynamics, offering vital insights for the precise prediction of fluid flow behavior and strategic control. These valuable insights can serve as a theoretical foundation to guide our deliberate modulation of snap-off phenomena, aiming at optimizing oil-recovery processes and enhancing the safety and stability of CO2 storage.