A method and system for predicting the imbibition behavior of microscopic two-phase interfaces in porous media

Abstract

The present application belongs to the technical field of micro-interface dynamics research, and relates to a method and system for realizing prediction of micro two-phase interface imbibition behavior of porous media, comprising: obtaining a pore network composed of pores and throats according to a target porous medium; calculating the flow rate of injected two-phase fluid at the throat; calculating the fluid flow rate under the main interface displacement mode and the wetting mode displacement mode respectively according to the flow rate of injected two-phase fluid at the throat; determining the displacement mode of the two-phase fluid interface according to the fluid flow rate ratio under the two displacement modes; calculating the corresponding flow resistance at the throat according to the displacement mode of the two-phase fluid interface; updating the motion control equation of the two-phase fluid according to the flow resistance, thereby completing the prediction of the micro two-phase interface imbibition behavior of the porous medium. The present application clearly defines the preferential flow path and dynamic evolution mode of different types of interfaces in the displacement process in the complex pore structure of the porous medium, and realizes accurate discrimination of the fluid interface type under transient conditions.

Description

Technical Field

[0001] This invention relates to a method and system for predicting the permeation behavior of microscopic two-phase interfaces in porous media, belonging to the field of microscopic interface dynamics research technology. Background Technology

[0002] In many energy and environmental engineering fields involving multiphase flow, such as oil and gas development, carbon dioxide geological sequestration, shale oil and gas extraction, and underground hydrogen storage, the percolation behavior of fluids in porous media and the micro-interfacial dynamics play a decisive role in macroscopic flow patterns and development efficiency. These percolation processes are typically two-phase flows, exhibiting complex interfacial behaviors such as fingering, Haines jumps, capillary-driven corner flows, and main bend intrusion. Especially in heterogeneous porous media, the competition between capillary forces and viscous forces determines the fluid's transport path, retention morphology, and displacement efficiency within the pores, forming a crucial foundation for influencing reservoir residual oil distribution, recovery rate, and injection-production control strategies.

[0003] While existing research has made significant progress in revealing the dynamics of micro-interfaces through numerous microfluidic experiments and numerical simulations, challenges remain, including complex modeling, high computational resource consumption, and scale limitations, making direct application to macroscopic reservoir simulation and engineering design difficult. Furthermore, most studies focus on the interface propagation mode dominated by the main bend fluid surface, neglecting the impact of "incomplete displacement paths" such as corner flows on the adsorption process and its macroscopic effects. In fact, in the complex pore structure of core samples, the wetting film flow formed by the expansion of the wetting phase along the pore corners plays a crucial role in maintaining connectivity and inducing unstable displacement during low-speed adsorption, directly influencing the retention, fracturing, and re-migration behavior of the non-wetting phase.

[0004] Traditional network models have simplified the modeling of pore-scale seepage processes to some extent, but they remain insufficient in describing the dynamic competition between the main interface flow and the wetting film, and in predicting the micro-interface transition behavior. Especially in heterogeneous or complex porous media, accurately predicting which local regions dominate corner flow wetting film or main interface intrusion, and their impact on overall displacement behavior, still lacks a well-developed theoretical modeling framework and numerical tools. Some studies have attempted to decompose pores into multiple subchannels to construct refined network models to simulate the coexistence of main interface flow and wetting film flow; however, these models are computationally intensive and difficult to obtain parameters, making them unsuitable for the multi-scale simulation and rapid prediction needs in engineering.

[0005] Furthermore, current multi-scale simulation approaches lack a universal method that can effectively scale up the evolution of micro-interfaces to the pore network or even reservoir scale. Since micro-interface dynamics (such as instability mechanisms like snap-off, burst, and overlap) are influenced by multiple factors, including pore geometry, wettability, flow velocity, and viscosity ratio, upscaling modeling must simultaneously capture key physical mechanisms while maintaining high computational efficiency.

[0006] Therefore, there is an urgent need to develop a method and model framework that can efficiently predict the percolation behavior of microscopic two-phase interfaces, accurately describe the competitive relationship between the main interface and the wetting film, and enable upscaling simulation, so as to make up for the shortcomings of existing technologies in predicting the microscopic flow behavior of porous media and multi-scale simulation, and thus provide theoretical and tool support for improving oil recovery, optimizing injection and production schemes, and developing efficient displacement technologies. Summary of the Invention

[0007] To address the aforementioned problems, the present invention aims to provide a method and system for predicting the percolation behavior at the microscopic two-phase interface of porous media. This method overcomes the shortcomings of existing technologies in predicting the microscopic flow behavior of porous media and simulating multi-scale processes, thereby providing theoretical and tool support for improving oil recovery, optimizing injection and production schemes, and developing efficient displacement technologies.

[0008] To achieve the above objectives, the present invention proposes the following technical solution: a method for predicting the permeation behavior of a microscopic two-phase interface in porous media, comprising the following steps: obtaining a pore network composed of pores and throats based on the target porous medium; calculating the flow rate of the two-phase fluid injected into the throat; calculating the fluid flow rate under the main interface displacement mode and the wetting mode displacement mode based on the flow rate of the two-phase fluid injected into the throat; determining the displacement mode of the two-phase fluid interface based on the fluid flow rate ratio under the two displacement modes; calculating the flow resistance corresponding to the throat based on the displacement mode of the two-phase fluid interface; and updating the motion control equation of the two-phase fluid based on the flow resistance, thereby completing the prediction of the permeation behavior of the microscopic two-phase interface in porous media.

[0009] Furthermore, the fluid flow rate of the main interface displacement mode for:

[0010]

[0011] in, It is the number of transient capillaries when the two-phase interface flows through the throat; It is the cross-sectional area of ​​the throat through which the fluid flows; It is the interfacial tension of a two-phase fluid; This refers to the viscosity of the wetting phase.

[0012] Furthermore, the fluid flow rate of the wetting mold displacement mode for:

[0013]

[0014] Where C is a parameter related to the geometric characteristics of the throat interface of the pore network, B is the conductivity function of the injected fluid wetting phase in the throat, R is the cross-sectional radius of the two-phase interface flowing through the throat, and t is the flow time at the leading edge of the wetting film.

[0015] Furthermore, the method for determining the displacement mode of the two-phase fluid interface is as follows: based on the properties of the two-phase fluid and the pore network, determine the critical capillary number corresponding to each throat; simulate the permeation process of the porous medium and determine the transient capillary number when the two-phase interface flows through a throat in real time; determine whether the displacement mode of the two-phase fluid interface is the main interface displacement mode or the wetting mode displacement mode based on whether the transient capillary number reaches the critical capillary number.

[0016] Furthermore, the critical capillary number It is the transient capillary number when the fluid flow rates of the main interface displacement mode and the wetting mold displacement mode are the same, and its calculation formula is:

[0017]

[0018] Where C is a parameter related to the geometric characteristics of the throat interface of the pore network; R is the cross-sectional radius of the two-phase interface flowing through the throat. denoted as the viscosity of the wetting phase; B is the conductivity function of the injected fluid wetting phase in the throat; t is the flow time at the leading edge of the wetting film. It is the cross-sectional area of ​​the throat through which the fluid flows; It is the interfacial tension of a two-phase fluid; It is dimensionless time.

[0019] Furthermore, the formula for calculating the transient capillary number is as follows:

[0020]

[0021] in, It is the viscosity of the fluid; It is the fluid flow rate; It is the cross-sectional area of ​​the throat through which the fluid flows. It is the interfacial tension of a two-phase fluid.

[0022] Furthermore, the method for determining whether the displacement mode of the two-phase fluid interface is the main interface displacement mode or the wetting mode displacement mode based on whether the transient capillary number reaches the critical capillary number is as follows: when the two-phase fluid flows through the throat and the transient capillary number is less than the critical capillary number, the interface of the two-phase fluid changes from the main interface displacement mode to the wetting mode displacement mode; when the two-phase fluid flows through the throat and the local capillary pressure is greater than the critical capillary pressure, the interface of the two-phase fluid changes from the wetting mode displacement mode to the main interface displacement mode.

[0023] Furthermore, the method for calculating the flow resistance at the throat is as follows: the main interface displacement mode selects the Hagen-Poiseuille equation to calculate the flow resistance of the two-phase fluid; the wetting mode displacement mode selects the two-phase viscous coupling calculation formula to calculate the flow resistance of the two-phase fluid at the throat.

[0024] Furthermore, the target porous medium can be any one or more of two-dimensional porous media and three-dimensional porous media.

[0025] This invention also discloses a prediction system for the permeation behavior of a microscopic two-phase interface in porous media, comprising: a pore network module for obtaining a pore network composed of pores and throats based on the target porous medium; a flow calculation module for calculating the flow rate of the two-phase fluid injected into the throat, and calculating the fluid flow rate under the main interface displacement mode and the wetting mode displacement mode based on the flow rate of the two-phase fluid injected into the throat; a displacement mode determination module for determining the displacement mode of the two-phase fluid interface based on the fluid flow rate ratio under the two displacement modes; a flow resistance calculation module for calculating the flow resistance corresponding to the throat based on the displacement mode of the two-phase fluid interface; and an output module for updating the motion control equation of the two-phase fluid based on the flow resistance, thereby completing the prediction of the permeation behavior of the microscopic two-phase interface in porous media.

[0026] The technical solution of the present invention has at least the following technical effects or advantages:

[0027] 1. The method in this invention focuses on the dynamic prediction of the displacement interface induced by the competition of microscopic forces between two-phase fluids within a local structure. The resulting prediction method can serve as a research method and a basis for scaling up the multiphase flow process involving porous media, such as formation energy resource development, fuel cells, and CO2 geological storage.

[0028] 2. This invention constructs a microscopic two-phase interface prediction method based on the coupling mechanism of wetting film and main interface permeation behavior, clarifying the preferential flow paths and dynamic evolution modes of different types of interfaces in the displacement process in complex porous media pore structures; and introduces a critical capillary number. Quantitatively separating the wetting film flow from the main interface flow enables accurate identification of fluid interface types under transient conditions, effectively reflecting the physical evolution of microscale percolation behavior.

[0029] 3. This invention constructs a coupling mechanism between microstructure, interface behavior, and flow response. By leveraging structural scale information and interface evolution laws, it realizes an upscaling mapping process from the pore throat scale to the macroscopic seepage field, providing support for establishing a multi-scale, multi-physics field coupled seepage simulation framework.

[0030] 4. The method in this invention can effectively characterize the evolution of the fluid main interface and wetting film in porous media under complex geometric structures, achieving high-precision prediction of the microscopic two-phase interface permeation behavior and establishing a dynamic transformation mechanism driven by flow state. Based on this, the constructed upscaling calculation model not only improves the resolution of seepage simulations but also provides new tools and pathways for the research and development of complex two-phase behavior in porous media such as unconventional oil and gas reservoirs and shale oil reservoirs. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of a pore network composed of pores and throats in one embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of the microscopic interface behavior of a two-phase fluid in one embodiment of the present invention. Figure 2 (a) is a diagram showing the interface distribution of immiscible fluids inside a square-interface capillary. Figure 2 (b) is a geometric feature diagram of the wetting film on the square interface of the capillary; Figure 2 (c) is a schematic diagram of the wetting film spreading forward from its initial state;

[0033] Figure 3 This is a simulation diagram of the microscopic interface behavior of two-phase fluids in one embodiment of the present invention;

[0034] Figure 4 This is an experimental effect diagram of the permeation behavior of porous media in one embodiment of the present invention. Figure 4 (a) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 Experimental results diagram; Figure 4 (b) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -5 Experimental results diagram; Figure 4 (c) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -6 Experimental results diagram; Figure 4 (d) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -7 Experimental results diagram; Figure 4 (e) is a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -4 Experimental results diagram; Figure 4 (f) is a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -5 Experimental results diagram; Figure 4 (g) represents a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -6 Experimental results diagram; Figure 4 (h) represents a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -7 Experimental results diagram; Figure 4 (i) has a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 Experimental results diagram; Figure 4 (j) is a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -5 Experimental results diagram; Figure 4 (k) represents a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -6 Experimental results diagram; Figure 4 (l) has a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -7 Experimental results diagram;

[0035] Figure 5 This is a simulation result of a method for predicting micro-interface behavior without considering the critical capillary number in a specific embodiment of the present invention, demonstrating the permeation behavior of porous media. Figure 5 (a) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 Simulation results; Figure 5 (b) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -5 Simulation results; Figure 5 (c) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -6 Simulation results; Figure 5 (d) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -7 Simulation results; Figure 5 (e) is a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -4 Simulation results; Figure 5 (f) is a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -5 Simulation results; Figure 5 (g) represents a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -6 Simulation results; Figure 5 (h) represents a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -7 Simulation results; Figure 5 (i) has a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 Simulation results; Figure 5 (j) is a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -5 Simulation results; Figure 5 (k) represents a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -6 Simulation results; Figure 5 (l) has a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -7Simulation results;

[0036] Figure 6 This is a simulation effect diagram of the method for predicting micro-interface behavior by considering the critical capillary number in a certain embodiment of the present invention to show the permeation behavior of porous media. Figure 6 (a) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 Simulation results; Figure 6 (b) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -5 Simulation results; Figure 6 (c) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -6 Simulation results; Figure 6 (d) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -7 Simulation results; Figure 6 (e) is a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -4 Simulation results; Figure 6 (f) is a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -5 Simulation results; Figure 6 (g) represents a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -6 Simulation results; Figure 6 (h) represents a depth variation coefficient of 2.0 and a capillary count of 2.6*10. -7 Simulation results; Figure 6 (i) has a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 Simulation results; Figure 6 (j) is a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -5 Simulation results; Figure 6 (k) represents a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -6 Simulation results; Figure 6 (l) has a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -7 Simulation results;

[0037] Figure 7 This is a spatial distribution diagram of water and gas phases obtained using different research methods to study the permeation behavior of porous media in one embodiment of the present invention. Figure 7 (a) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 Figure showing experimental results for immiscible fluids; Figure 7 (b) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 The simulation results without considering the critical capillary number are shown in the figure. Figure 7 (c) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 The simulation results considering the critical capillary number are shown in the figure. Figure 7 (d) is a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 Figure showing experimental results for immiscible fluids; Figure 7 (e) has a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 The simulation results without considering the critical capillary number are shown in the figure. Figure 7 (f) is a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 The simulation results considering the critical capillary number are shown in the figure. Figure 7 (g) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 The volumetric efficiency of the wettable fluid changes over time during the infiltration process; Figure 7 (h) represents a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 The graph shows the change in the body efficiency of the wettable fluid over time during the infiltration process. Detailed Implementation

[0038] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention is described in detail through specific embodiments. However, it should be understood that the specific embodiments are provided only for a better understanding of the present invention and should not be construed as limiting the present invention. In the description of the present invention, it should be understood that the terminology used is for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0039] To deeply reveal the dynamic competition mechanism between the main interface and the wetting film flow in complex porous media and its impact on macroscopic seepage behavior, this invention provides a method and system for predicting the seepage behavior of microscopic two-phase interfaces in porous media. This method can identify the evolution mode of the two-phase interface in local regions based on pore structure and wettability characteristics, establish a quantitative mapping relationship between microscopic interface displacement behavior and pore-scale physical properties, and on this basis, achieve spatial prediction of seepage behavior and modeling of the dynamic evolution process. Simultaneously, this method organically links the microscopic interface evolution process with macroscopic displacement efficiency by constructing an upscaling computational framework of structure-behavior-response, providing new theoretical tools and technical paths for multi-scale seepage simulation, recovery prediction, and fluid control strategy optimization. The invention will be described in detail below with reference to the accompanying drawings.

[0040] Example 1

[0041] This embodiment discloses a method for predicting the percolation behavior at the microscopic two-phase interface of porous media, including the following steps:

[0042] S1 obtains a pore network consisting of pores and throats based on the target porous medium.

[0043] The target porous medium can be any one or more of two-dimensional and three-dimensional porous media. A schematic diagram of the pore network composed of pores and throats in this embodiment is shown below. Figure 1 As shown, the porous media structure is simplified and abstracted by extracting the pore network. Each pore-throat unit has its critical capillary number pre-determined based on local geometric features and fluid properties. The pore-throat unit consists of two pores of the same size and a narrow central channel (i.e., the throat). The pore unit diameter is 500 micrometers, and the throat width is 250 micrometers, forming a typical "pore-throat-pore" structure. This structure effectively reflects the geometric characteristics of the pore-throat connecting units in actual porous media and facilitates observation of the evolution and transformation between the wetting film and the main interface.

[0044] S2 calculates the flow rate of the two-phase fluid injected at the throat; based on the flow rate of the two-phase fluid injected at the throat, the fluid flow rate is calculated under the main interface displacement mode and the wetting mode displacement mode, respectively.

[0045] like Figure 2 As shown, Figure 2 (a) is an interface distribution diagram of immiscible fluids in a square interface capillary, showing the interface distribution diagram of the wetting film. Figure 2 (b) is a geometric feature diagram of the wetting film on the square interface of the capillary; Figure 2 (c) is a schematic diagram of the wetting film spreading forward from its initial state. From Figure 2 It can be seen that the microscopic two-phase interface percolation behavior mainly includes two types: fluid wetting film and fluid main interface. Two-phase interface percolation behavior refers to the distribution state of the two-phase interface at the pore throat unit of the porous medium; the main interface behavior refers to the injected wetting phase fluid completely occupying the throat, while the wetting film behavior refers to the injected wetting phase fluid flowing through the corner of the pore throat, while the non-wetting phase fluid occupies the middle region of the pore throat cross section.

[0046] Fluid flow rate in main interface displacement mode for:

[0047]

[0048] in, It is the number of transient capillaries when the two-phase interface flows through the throat; It is the cross-sectional area of ​​the throat through which the fluid flows; It is the interfacial tension of a two-phase fluid; This refers to the viscosity of the wetting phase.

[0049] Fluid flow rate under wetting displacement mode for:

[0050]

[0051] Where C is a parameter related to the geometric characteristics of the throat interface of the pore network, B is the conductivity function of the injected fluid wetting phase in the throat, R is the cross-sectional radius of the two-phase interface flowing through the throat, and t is the flow time at the leading edge of the wetting film. The flow morphology of the wetting film changes at different times. Assuming the dimensionless time is... Dimensionless time is a method that eliminates the influence of time units and converts time into a pure numerical value, which facilitates comparative analysis of different scales or systems. In this embodiment, the system is a water-gas two-phase system, and the value corresponding to dimensionless time can be determined to be 1000 through experiments.

[0052] S3 determines the displacement mode of the two-phase fluid interface based on the fluid flow ratio under the two displacement modes.

[0053] The method for determining the displacement mode at the interface of a two-phase fluid is as follows:

[0054] S3.1 Determine the critical capillary number corresponding to each throat based on the two-phase fluid properties and pore network.

[0055] Based on pore networks, and considering the properties of the injected two-phase fluid and the local structural characteristics of the pore network, the critical capillary number corresponding to each pore throat unit is determined. A critical capillary number is proposed based on the dynamic balance between the fluid wetting film flow rate and the main interface percolation flow rate. This is used to determine the priority order of the fluid wetting film and the fluid main interface during the next moment of two-phase fluid percolation. Critical capillary number It is the transient capillary number when the fluid flow rates of the main interface displacement mode and the wetting mold displacement mode are the same, and its calculation formula is:

[0056]

[0057] Where C is a parameter related to the geometric characteristics of the throat interface of the pore network; R is the cross-sectional radius of the two-phase interface flowing through the throat. denoted as the viscosity of the wetting phase; B is the conductivity function of the injected fluid wetting phase in the throat; t is the flow time at the leading edge of the wetting film. It is the cross-sectional area of ​​the throat through which the fluid flows; It is the interfacial tension of a two-phase fluid; It is dimensionless time.

[0058] S3.2 simulates the percolation process of porous media and determines the transient capillary count when the two-phase interface flows through a throat in real time.

[0059] Formula for calculating transient capillary count:

[0060]

[0061] in, It is the viscosity of the fluid; It is the fluid flow rate; It is the cross-sectional area of ​​the throat through which the fluid flows. It is the interfacial tension of a two-phase fluid.

[0062] S3.3 Determine whether the displacement mode of the two-phase fluid interface is the main interface displacement mode or the wetting mode displacement mode based on whether the transient capillary number reaches the critical capillary number.

[0063] The method for determining whether the displacement mode of a two-phase fluid interface is a main interface displacement mode or a wetting mode displacement mode based on whether the transient capillary number reaches the critical capillary number is as follows: when the two-phase fluid flows through the throat, and the transient capillary number is less than the critical capillary number, i.e. When the two-phase fluids flow through the throat, the interface changes from the main interface displacement mode to the wetting mode displacement mode. When the local capillary pressure is greater than the critical capillary pressure, the interface changes from the wetting mode displacement mode to the main interface displacement mode.

[0064] S4 calculates the flow resistance at the throat based on the displacement mode of the two-phase fluid interface.

[0065] The method for calculating the flow resistance at the throat is as follows: For the main interface displacement mode, the Hagen-Poiseuille equation is used to calculate the flow resistance of the two-phase fluid; for the wetting mode displacement mode, the two-phase viscous coupling calculation formula is used to calculate the flow resistance of the two-phase fluid at the throat. For the flow mechanisms corresponding to different interface morphologies, the Hagen-Poiseuille equation and the two-phase viscous coupling model are used for resistance calculation and velocity updates, respectively, ensuring the dynamic consistency and physical rationality of the interface behavior prediction, and further driving the dynamic evolution of the two-phase fluid in the global network.

[0066] S5 updates the motion control equations of the two-phase fluid based on the flow resistance, thereby completing the prediction of the percolation behavior of the microscopic two-phase interface in porous media.

[0067] During the simulation, five sets of fluid viscosity ratios were set ( The values ​​are 0.01, 0.1, 1, 10, and 100, respectively; corresponding to five sets of capillary tube counts ( ), respectively , , , and ,in, For wetting phase viscosity, For injection speed, The interfacial tension is used. The simulation employs a two-phase system with water as the wetting phase and gas as the non-wetting phase, and tracks the competitive evolution of the main interface and the wetting film within the pore throat unit using a dynamic network simulation numerical method.

[0068] Simulation results of two-phase fluid micro-interface behavior are shown in the figure. Figure 3 As shown in the figure, the experimental results of the permeation behavior of porous media are as follows. Figure 4 As shown, Figure 4 The horizontal axis represents the depth variation coefficient for different structures, and the plane of all structures... Figure 1 The depth varies. When the depth variation coefficient is 1, all pore structures have a depth of 40 micrometers. When the depth variation coefficient is 2, pores with a diameter less than 40 micrometers still correspond to a depth of 40 micrometers, while pores with a diameter greater than 40 micrometers correspond to a depth of 80 micrometers. When the depth variation coefficient is 3, the pore structure, based on a depth variation coefficient of 2, extends the depth of pores with a diameter greater than 80 micrometers to 120 micrometers. Each vertical column of the graph corresponds to its depth variation coefficient. (For example...) Figure 3 , Figure 4 As shown, under different combinations of conditions, the microscopic interface morphology exhibits clear demarcation characteristics: when the local transient capillary number is less than the critical capillary number, the percolation process is characterized by preferential growth of the wetting film and remote wetting through angular flow; while when the local capillary number is higher than the critical capillary number, the displacement behavior is dominated by the main interface, and the wetting film cannot achieve effective migration. The above-mentioned transformation law of interface behavior is highly consistent with the theoretical prediction of the critical capillary number proposed in this embodiment.

[0069] This embodiment verifies the applicability of the critical capillary number criterion using the most basic pore throat connection unit, confirming that the theory can accurately describe the evolution boundary of the wetting film and the main interface under various combinations of viscosity ratios and capillary numbers, providing a reliable microscopic criterion basis for predicting two-phase flow in complex porous media systems.

[0070] Example 2

[0071] Based on the same inventive concept, this embodiment discloses a method for predicting the permeation behavior of the microscopic two-phase interface in porous media. In this embodiment, the porous media model adopts a two-dimensional pore structure. The two-dimensional structure is generated from a three-dimensional digital core CT scan image of a sandstone sample using an image reconstruction algorithm, ensuring that the obtained two-dimensional planar pore structure has high consistency with the original three-dimensional digital core in terms of pore size distribution characteristics. The average pore size of the two-dimensional pore structure is approximately 100 micrometers, the maximum pore size is approximately 240 micrometers, and the thickness in the depth direction is 40 micrometers.

[0072] To systematically analyze the impact of different depth distributions in two-dimensional structures on the percolation behavior at the two-phase interface and the accuracy of upscaling simulations, this embodiment designed and fabricated three sets of microfluidic chip models with different depth configurations: the first set of models is a constant-depth structure model, where all pore units have a depth of 40 micrometers; the second set of models is a first-stage depth extension model, where pores with a diameter greater than 40 micrometers are further micro-fabricated based on the first set of models to extend their depth to 80 micrometers; the third set of models is a second-stage depth extension model, where pores with a diameter greater than 80 micrometers are further processed to a depth of 120 micrometers based on the second set of models. These three sets of models are used to investigate the influence of non-uniform depth distribution on the selection of displacement paths at the wetting film and main interface, as well as the overall percolation behavior.

[0073] In this embodiment, three types of comparative experiments and simulations were carried out in three sets of microfluidic models: (1) Upscaling numerical simulation without considering the critical capillary number mechanism and micro-interface prediction method proposed in this application, such as Figure 5 As shown; (2) Consider the upscaling numerical simulation of the method in this application, such as Figure 6 As shown; (3) Two-dimensional microscopic percolation experiments under the same conditions. Each type of comparative test was set with 4 different injection rates to cover different levels of capillary number, namely , , and Each test group corresponds to 12 water vapor distribution states (3 models × 4 capillary numbers).

[0074] like Figure 7 As shown, Figure 7 (a) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 Figure showing experimental results for immiscible fluids; Figure 7 (b) has a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 The simulation results without considering the critical capillary number are shown in the figure. Figure 7 (c) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 The simulation results considering the critical capillary number are shown in the figure. Figure 7 (d) is a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 Figure showing experimental results for immiscible fluids; Figure 7 (e) has a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 The simulation results without considering the critical capillary number are shown in the figure. Figure 7 (f) is a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 The simulation results considering the critical capillary number are shown in the figure. Figure 7(g) is a depth variation coefficient of 1.0 and a capillary count of 2.6*10. -4 The volumetric efficiency of the wettable fluid changes over time during the infiltration process; Figure 7 (h) represents a depth variation coefficient of 3.0 and a capillary count of 2.6*10. -4 The graph shows the change in the volumetric efficiency of the wettable fluid during the infiltration process over time. The displacement efficiency is defined as the proportion of water volume to the total pore space volume in the porous medium. Figure 7 (g) and Figure 7 (f) The horizontal axis is dimensionless time, defined as the ratio of the actual time t to the time t* it takes for the water to reach the outlet.

[0075] In all tests, a water-air two-phase system was used, with water as the wetting phase. By comparing the water-air distribution images and interface morphology evolution processes in three types of experimental / simulation results, it was found that the upscaling model considering the critical capillary number criterion and micro-interface evolution prediction mechanism in this invention exhibits a high degree of consistency between its water-air distribution and micro-percolation experiments, accurately predicting micro-behaviors such as wetting film migration, main interface front advancement, and interface transformation. Meanwhile, traditional upscaling simulations show significant deviations at high capillary numbers, failing to reflect the evolutionary characteristics of wetting film advance and breakage behavior at the pore-throat scale.

[0076] Example 3

[0077] Based on the same inventive concept, this embodiment discloses a prediction system for realizing the percolation behavior of microscopic two-phase interfaces in porous media, comprising:

[0078] A pore network module is used to obtain a pore network consisting of pores and throats based on the target porous medium.

[0079] The flow calculation module is used to calculate the flow rate of the two-phase fluid injected at the throat. Based on the flow rate of the two-phase fluid injected at the throat, the fluid flow rate is calculated in the main interface displacement mode and the wetting mold displacement mode, respectively.

[0080] The displacement mode determination module is used to determine the displacement mode of the two-phase fluid interface based on the fluid flow ratio of the two displacement modes.

[0081] The flow resistance calculation module is used to calculate the flow resistance at the throat based on the displacement mode of the two-phase fluid interface.

[0082] The output module is used to update the motion control equations of the two-phase fluid based on the flow resistance, thereby completing the prediction of the permeation behavior of the microscopic two-phase interface in porous media.

[0083] This invention constructs a microscopic two-phase interface prediction method based on the coupling mechanism of wetting film and main interface permeation behavior. It clarifies the preferential flow paths and dynamic evolution modes of different types of interfaces during displacement processes in complex porous media with pore-throat structures, and introduces a critical capillary number. Quantitatively separating the wetting film flow from the main interface flow enables accurate identification of fluid interface types under transient conditions, effectively reflecting the physical evolution of microscale percolation behavior.

[0084] This invention effectively characterizes the evolution of the fluid main interface and wetting film in porous media under complex geometries, achieving high-precision prediction of the microscopic two-phase interface percolation behavior and establishing a dynamic transformation mechanism driven by flow state. Based on this, the constructed upscaling calculation model not only enhances the resolution of seepage simulations but also provides new tools and pathways for the research and development of complex two-phase behavior in porous media such as unconventional oil and gas reservoirs and shale oil reservoirs.

[0085] Embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0086] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0087] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0088] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0089] The above embodiments are merely illustrative of the technical solutions of the present invention and not intended to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific embodiments of the present invention without departing from the spirit and scope of the present invention. Any modifications or equivalent substitutions should be covered within the scope of protection of the claims of the present invention. The above content is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for predicting the percolation behavior at the microscopic two-phase interface of porous media, characterized in that, Includes the following steps: Based on the target porous medium, obtain the pore network composed of pores and throats; Calculate the flow rate of the two-phase fluid injected into the throat; Based on the flow rate of the two-phase fluid injected into the throat, the fluid flow rate is calculated in the main interface displacement mode and the wetting mold displacement mode, respectively. The displacement mode of the two-phase fluid interface is determined based on the fluid flow ratio under the two displacement modes. Calculate the flow resistance at the throat based on the displacement mode of the two-phase fluid interface. Based on the flow resistance, the motion control equations of the two-phase fluid are updated, thereby completing the prediction of the percolation behavior of the microscopic two-phase interface in porous media. The method for determining the displacement mode of the two-phase fluid interface is as follows: Based on the properties of the two-phase fluid and the pore network, determine the critical capillary number corresponding to each throat; Simulate the permeation process of porous media and determine the transient capillary count when the two-phase interface flows through a throat in real time. The displacement mode of the two-phase fluid interface is determined by whether the transient capillary number reaches the critical capillary number; it is either the main interface displacement mode or the wetting mode displacement mode. The method for determining whether the displacement mode of the two-phase fluid interface is the main interface displacement mode or the wetting mode displacement mode based on whether the transient capillary number reaches the critical capillary number is as follows: When two-phase fluids flow through the throat and the transient capillary number is less than the critical capillary number, the interface of the two-phase fluids changes from the main interface displacement mode to the wetting mode displacement mode. When a two-phase fluid flows through a throat, if the local capillary pressure is greater than the critical capillary pressure, the interface between the two-phase fluids changes from the wetting mode displacement mode to the main interface displacement mode.

2. The method for predicting the percolation behavior at the microscopic two-phase interface of porous media as described in claim 1, characterized in that, Fluid flow rate in the main interface displacement mode for: in, It is the number of transient capillaries when the two-phase interface flows through the throat; It is the cross-sectional area of ​​the throat through which the fluid flows; It is the interfacial tension of a two-phase fluid; This refers to the viscosity of the wetting phase.

3. The method for predicting the percolation behavior at the microscopic two-phase interface of porous media as described in claim 1, characterized in that, Fluid flow rate in the wetting mold displacement mode for: Where C is a parameter related to the geometric characteristics of the throat interface of the pore network, B is the conductivity function of the injected fluid wetting phase in the throat, R is the cross-sectional radius of the two-phase interface flowing through the throat, and t is the flow time at the leading edge of the wetting film.

4. The method for predicting the percolation behavior at the microscopic two-phase interface of porous media as described in claim 1, characterized in that, The critical number of capillaries It is the transient capillary number when the fluid flow rates of the main interface displacement mode and the wetting mold displacement mode are the same, and its calculation formula is: Where C is a parameter related to the geometric characteristics of the throat interface of the pore network; R is the cross-sectional radius of the two-phase interface flowing through the throat. denoted as the viscosity of the wetting phase; B is the conductivity function of the injected fluid wetting phase in the throat; t is the flow time at the leading edge of the wetting film. It is the cross-sectional area of ​​the throat through which the fluid flows; It is the interfacial tension of a two-phase fluid; It is dimensionless time.

5. The method for predicting the percolation behavior at the microscopic two-phase interface of porous media as described in claim 1, characterized in that, The formula for calculating the transient capillary count is as follows: in, It is the viscosity of the fluid; It is the fluid flow rate; It is the cross-sectional area of ​​the throat through which the fluid flows. It is the interfacial tension of a two-phase fluid.

6. The method for predicting the percolation behavior at the microscopic two-phase interface of porous media as described in claim 1, characterized in that, The method for calculating the flow resistance at the throat is as follows: the main interface displacement mode selects the Hagen-Poiseuille equation to calculate the flow resistance of the two-phase fluid; the wetting mode displacement mode selects the two-phase viscous coupling calculation formula to calculate the flow resistance of the two-phase fluid at the throat.

7. The method for predicting the percolation behavior at the microscopic two-phase interface of porous media as described in claim 1, characterized in that, The target porous medium is any one or more of two-dimensional porous media and three-dimensional porous media.

8. A predictive system for the percolation behavior at the microscopic two-phase interface of porous media, characterized in that, include: A pore network module is used to obtain a pore network consisting of pores and throats based on the target porous medium. The flow calculation module is used to calculate the flow rate of the two-phase fluid injected at the throat, and to calculate the fluid flow rate under the main interface displacement mode and the wetting mold displacement mode respectively based on the flow rate of the two-phase fluid injected at the throat. The displacement mode determination module is used to determine the displacement mode of the two-phase fluid interface based on the fluid flow ratio of the two displacement modes. The flow resistance calculation module is used to calculate the flow resistance at the throat based on the displacement mode of the two-phase fluid interface. The output module is used to update the motion control equation of the two-phase fluid based on the flow resistance, thereby completing the prediction of the permeation behavior of the microscopic two-phase interface of the porous medium. The method for determining the displacement mode of the two-phase fluid interface is as follows: Based on the properties of the two-phase fluid and the pore network, determine the critical capillary number corresponding to each throat; Simulate the permeation process of porous media and determine the transient capillary count when the two-phase interface flows through a throat in real time. The displacement mode of the two-phase fluid interface is determined by whether the transient capillary number reaches the critical capillary number; it is either the main interface displacement mode or the wetting mode displacement mode. The method for determining whether the displacement mode of the two-phase fluid interface is the main interface displacement mode or the wetting mode displacement mode based on whether the transient capillary number reaches the critical capillary number is as follows: When two-phase fluids flow through the throat and the transient capillary number is less than the critical capillary number, the interface of the two-phase fluids changes from the main interface displacement mode to the wetting mode displacement mode. When a two-phase fluid flows through a throat, if the local capillary pressure is greater than the critical capillary pressure, the interface between the two-phase fluids changes from the wetting mode displacement mode to the main interface displacement mode.

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