Deep coal bed gas reservoir nested medium gas-water two-phase production dynamic prediction method

Abstract

This invention discloses a method for predicting the dynamic production of gas-water two-phase gas in nested media in deep coalbed methane reservoirs. The method takes into account the complex fracture network formed by segmented multi-cluster fracturing in deep coalbed methane, the nonlinear flow mechanisms of coalbed methane such as adsorption-desorption, diffusion, and stress sensitivity, and the flow characteristics of gas-water two-phase gas in the nested media of "matrix-cleavage-fracture". Therefore, it can more accurately obtain key seepage parameters of the fracture network, the stress sensitivity coefficient of the coal reservoir, the adsorption coefficient, and accurately and rapidly predict the dynamic production of gas-water two-phase gas.

Description

Technical Field

[0001] This invention relates to a dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs, specifically to an integrated dynamic prediction method, device, medium, and equipment for gas-water two-phase production in nested media of "matrix-cleavage-fracture" in deep coalbed methane reservoirs, belonging to the field of oil and gas field development technology. Background Technology

[0002] Compared to shallow coalbed methane reservoirs, deep coalbed methane reservoirs have poorer physical properties and higher in-situ stress, resulting in poor adaptability to conventional fracturing techniques. Their large-scale development necessitates the use of long horizontal wells and large-scale hydraulic fracturing technology. Since coal seams themselves are a dual-porosity media system composed of matrix and cleavage, and deep coal seams simultaneously develop and retain numerous natural fractures, fracturing will create a complex nested "matrix-cleavage-fracture" media system.

[0003] The degree of fracturing stimulation is one of the main factors restricting the production capacity of deep coalbed methane wells. Therefore, a thorough understanding of the fracturing stimulation body is a prerequisite for optimized fracturing design and efficient development of deep coalbed methane. Simultaneously, to predict the production capacity of deep coalbed methane wells, it is necessary to clarify the adsorption and desorption characteristics of deep coalbed methane and the nonlinear flow mechanism in micro- and nano-pores. Furthermore, coalbed methane development inevitably involves a gas-water two-phase flow stage, and the gas-water two-phase flow characteristics in the nested media of deep coalbed methane reservoirs are even more complex. Deep coal seams are located in a high-stress environment, and the reservoirs exhibit strong stress sensitivity. This stress sensitivity has a severe negative impact on gas-water permeability, directly affecting the stable production capacity of gas wells. Therefore, accurate prediction of the production capacity of deep coalbed methane wells must consider the influence of stress sensitivity and the gas-water two-phase flow characteristics in the nested media. Thus, establishing a dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs is of great significance for deep coalbed methane development scheme design, fracturing evaluation, production dynamic analysis, and prediction.

[0004] Currently, methods for predicting the production capacity of deep coalbed methane wells mainly include analytical, semi-analytical, and numerical simulation methods. Analytical methods are typically based on steady-state flow theory, establishing a coalbed methane well production capacity calculation model. This is mainly achieved by introducing two-phase pseudo-pressures to linearize the equations and deriving the production capacity equation for water-producing gas wells using conformal transformation and the principle of potential superposition, converting water production into gas production for evaluation. However, when dealing with the nonlinearity of the two-phase flow equations, this method usually only introduces two-phase pseudo-pressures to simplify the solution, neglecting the influence of nonlinear flow parameters. Furthermore, analytical methods struggle to characterize complex fracture networks, resulting in large errors in production capacity prediction. Semi-analytical methods are primarily based on the linear flow assumption. This method can effectively characterize fracture network modified bodies and is computationally convenient, leading to its widespread application. However, existing semi-analytical methods are only applicable to single-phase fluid production capacity prediction. For the two-phase flow of gas and water encountered during coalbed methane development, the semi-analytical model is no longer suitable due to the severe nonlinearity of the mathematical model itself. Numerical simulation methods can explicitly characterize the parameters of artificial fractures and handle multiphase fluid flow problems. However, the preprocessing is complex. To obtain high simulation accuracy, mesh refinement of the fractures is required, resulting in a large number of meshes and low computational efficiency when processing tens of thousands of case analyses. Therefore, there is an urgent need to establish a method for predicting the gas-water two-phase production dynamics in nested media of deep coalbed methane reservoirs. This is of great significance for accurately describing the characteristics of pressure fracture networks in deep coalbed methane reservoirs, revealing the gas-water two-phase seepage laws in the "matrix-cleavage-fracture" nested media, and rapidly and accurately predicting the gas-water two-phase production dynamics. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides an integrated prediction method, apparatus, medium, and equipment for gas-water two-phase production dynamics in a nested "matrix-cleavage-fracture" medium in deep coalbed methane reservoirs. It considers the complex fracture network formed by segmented multi-cluster fracturing in deep coalbed methane, the nonlinear flow mechanisms of coalbed methane adsorption-desorption, diffusion, and stress sensitivity, as well as the gas-water two-phase flow characteristics in the nested "matrix-cleavage-fracture" medium. This allows for more accurate acquisition of key seepage parameters of the fracture network, coal reservoir stress sensitivity coefficient, adsorption coefficient, and accurate and rapid prediction of gas-water two-phase production dynamics.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs, comprising the following steps:

[0008] Step S10: Analyze the spatial distribution and basic characteristics of the fracture network formed by hydraulic fracturing in deep coal seams, clarify the adsorption and desorption mechanism, diffusion mechanism, and gas-water two-phase flow mechanism of gas in the nested medium of deep coal seam gas reservoirs, and perform precise characterization step by step.

[0009] Step S20: Based on the basic characteristics of the spatial distribution and seepage parameters, the adsorption and desorption mechanism, the diffusion mechanism, and the gas-water two-phase seepage mechanism, establish a physical model for dynamic analysis of gas-water two-phase production in nested media of deep coal seam gas reservoirs.

[0010] Step S30: Establish a mathematical model based on the physical model;

[0011] Step S40: Solve the mathematical model to obtain the gas and water two-phase production solution;

[0012] Step S50: Based on the gas and water two-phase production solution, obtain the theoretical curve of the gas-water two-phase production dynamic analysis of the nested medium in deep coalbed gas reservoirs;

[0013] Step S60: Fit and interpret the theoretical curve with the actual well production data to obtain key seepage parameters of the reservoir and fractures, and then predict the gas and water two-phase production dynamics.

[0014] Furthermore, the specific operation process of step S10 is as follows:

[0015] Step S101: Based on the propagation law of the pressure fracture and the results of microseismic monitoring, analyze the basic characteristics of the spatial distribution and seepage parameters of the fracture network;

[0016] Step S102: Based on the aforementioned basic characteristics, the induced and natural fractures in the fracture network are characterized using the equivalent continuous medium method.

[0017] Step S103: Based on the desorption, diffusion, and seepage characteristics during the drainage process of coalbed methane reservoirs, the Langmuir isothermal adsorption law is used to characterize the gas adsorption-desorption mechanism in the nested medium of the deep coalbed methane reservoir, the quasi-steady-state diffusion of Fick's first diffusion law is used to characterize the gas diffusion mechanism in the nested medium of the deep coalbed methane reservoir, and Darcy's law is used to characterize the gas-water two-phase seepage mechanism.

[0018] Furthermore, the establishment of the physical model for the dynamic analysis of gas-water two-phase production in the nested medium of deep coalbed methane reservoirs in step S20 includes:

[0019] Based on the basic characteristics of artificial fracture networks, cleavage, and matrix in deep coal seams, from the perspective of establishing a seepage mathematical model, the complex fracture network is treated as an equivalent fracturing body. At the same time, considering the gas adsorption-desorption, diffusion, and gas-water two-phase seepage effects in the nested medium of deep coal seam gas reservoirs, the fracturing body is characterized by a trilinear flow model. In this way, a physical model for the dynamic analysis of gas-water two-phase production in the nested medium of deep coal seam gas reservoirs is established.

[0020] In step S20, the assumptions of the physical model include:

[0021] (1) The top, bottom and lateral boundaries of the three regions in the deep coal seam are all closed;

[0022] (2) All deep coal seams were fractured, and the fractures were symmetrical with the shaft.

[0023] (3) The artificial fractures are vertical and penetrate the reservoir, and intersect only at the perforation of the horizontal well, while the rest of the horizontal well is sealed.

[0024] (4) The artificial fractures are directly connected to the wellbore, and the fluid flows into the production wellbore only through the fractures. The fluid in the reservoir continuously flows to the fractures to provide energy supply.

[0025] (5) Consider the reservoir permeability stress sensitivity;

[0026] (6) Considering the co-production of gas and water, both the coal seam cleavage and artificial fractures are two-phase flow of gas and water, and conform to isothermal Darcy flow.

[0027] (7) The adsorption and desorption of coalbed methane in the matrix follows the Langmuir theory;

[0028] (8) Compared with gas, the compressibility coefficient of formation water is small and can be ignored;

[0029] (9) The effects of gravity and capillary force are not considered.

[0030] Furthermore, the mathematical model establishment process for the dynamic analysis of gas-water two-phase production in the nested medium of deep coalbed methane reservoirs in step S30 is as follows:

[0031] Step S301: Based on dimensionless parameters and their definitions, establish the fluid seepage equations and boundary conditions for the external cleavage system and the coal matrix system;

[0032] The vapor phase flow equation and boundary conditions are treated with pseudo-pressure and pseudo-time. The vapor phase flow equation for the outer zone cleavage system is as follows:

[0033]

[0034] The pseudo-steady-state diffusion equation of coalbed methane in the matrix system is as follows:

[0035]

[0036] The boundary conditions are:

[0037]

[0038] The aqueous phase flow equations are treated in real-time, and the dimensionless governing equations for the aqueous phase of the outer zone cleavage system are as follows:

[0039]

[0040] The boundary conditions are:

[0041]

[0042] In the formula: ψ f1D —The internal cleavage system has dimensionless pseudo-pressure; ψ f2D —Dimensionless pseudo-pressure in the outer zone cleavage system; p f1D —The internal cleavage system has dimensionless pressure; p f2D —Dimensionless pressure in the outer zone cleavage system; V m2D —Adsorption concentration of dimensionless coal matrix particles in the outer zone; V ED —Equilibrium adsorption concentration of dimensionless coal matrix particles in the outer zone; k frg —Relative gas-phase permeability in the cleavage system; k frw —Relative permeability of the aqueous phase in the cleavage system; x D —Dimensionless length (x-coordinate direction); x eD —Dimensionless outer boundary distance (x-coordinate direction); η f2D —Dimensionless pressure conductivity coefficient of the gas phase in the outer zone cleavage system; η f2wD —Dimensionless pressure conductivity coefficient of the aqueous phase in the outer zone cleavage system; t aD —Dimensionless pseudotime; t D —Dimensionless time; ω2—Storage capacity coefficient of the outer zone cleavage system; λ2—Channeling coefficient of the outer zone cleavage system; β—Coalbed methane adsorption coefficient.

[0043] Step S302: Based on dimensionless parameters and their definitions, establish the fluid seepage equations and boundary conditions in the inner zone cleavage and coal matrix system;

[0044] The vapor phase flow equation and boundary conditions are treated with pseudo-pressure and pseudo-time. The vapor phase flow equation for the inner zone cleavage system is as follows:

[0045]

[0046] The pseudo-steady-state diffusion equation of coalbed methane in the matrix system is as follows:

[0047]

[0048] The boundary conditions are:

[0049]

[0050] The aqueous phase flow equations are treated with real-time conditions. The dimensionless governing equations for the aqueous phase in the inner zone cleavage system are as follows:

[0051]

[0052] The boundary conditions are:

[0053]

[0054] In the formula: ψ FD —The artificial fracture system is dimensionless pseudo-pressure; p FD —The artificial fracture system has dimensionless pressure; V m1D —Adsorption concentration of dimensionless coal matrix particles in the inner zone; y D —Dimensionless length (y-coordinate direction); y eD —Dimensionless outer boundary distance (y-coordinate direction); η f1D —Dimensionless pressure conductivity coefficient of the gas phase in the inner zone cleavage system; η f1wD —Dimensionless pressure conductivity coefficient of the aqueous phase in the inner zone cleaving system; ω1—Storage capacity coefficient of the inner zone cleaving system; λ1—Channeling coefficient of the inner zone cleaving system.

[0055] Step S303: Based on dimensionless parameters and their definitions, establish the fluid seepage equation and boundary conditions in the artificial fracture system;

[0056] The gas-phase flow equation and boundary conditions are treated with pseudo-pressure and pseudo-time. The gas-phase flow equation for the artificial fracture system is as follows:

[0057]

[0058] The boundary conditions are:

[0059]

[0060] The aqueous phase seepage equations are treated with real-time data. The dimensionless governing equations for the aqueous phase in the artificial fracture system are as follows:

[0061]

[0062] The boundary conditions are:

[0063]

[0064] In the formula: C FD —Dimensionless artificial fracture conductivity; η FD —Dimensionless pressure conductivity coefficient of the gas phase in an artificial fracture system; η FwD —Dimensionless pressure conductivity of the aqueous phase in an artificial fracture system; w FD —Dimensionless artificial crack width; k Frg —Relative gas permeability in the artificial fracture system; k Frw —Relative permeability of the water phase in an artificial fracture system.

[0065] Furthermore, in step S40, the step of solving the mathematical model for the dynamic analysis of gas-water two-phase production in a nested medium of deep coalbed methane reservoirs using a semi-analytical method mainly includes:

[0066] Step S401: Discretize the production time into multiple time steps. In each time step, the pressure-related parameter (μ) g B g ) and parameters related to saturation (k) frg k frw k Frg k Frw The average pressure and average saturation within the operating range are updated and replaced respectively. Therefore, the nonlinear parameters at each time step can be treated as constant approximations. After dealing with the nonlinear seepage problem, the gas phase and water phase yields at each time step can be obtained by directly solving the equations.

[0067] Step S402: Solve the gas-water two-phase flow equations from step 301 using the Laplace transform to obtain the pressure solution of the gas-phase flow equations for the outer zone cleavage system in Laplace space, as follows:

[0068]

[0069]

[0070]

[0071]

[0072] The pressure solution of the aqueous phase seepage equation in Laplace space is as follows:

[0073]

[0074]

[0075]

[0076] In the formula, The dimensionless pressure of the gas phase in the inner region of the Lagrange space cleavage system; The dimensionless pressure of the gas phase in the outer region cleavage system under Lagrange space; The dimensionless pressure of the aqueous phase in the inner region cleavage system under Lagrange space; Let be the dimensionless pressure of the aqueous phase in the outer zone cleavage system under Laplace space; u is the Laplace operator.

[0077] Step S403: Solve the gas-water two-phase flow equations from step 302 using the Laplace transform to obtain the pressure solution of the gas-phase flow equations for the inner cleavage system in Laplace space, as follows:

[0078]

[0079]

[0080]

[0081]

[0082] The pressure solution of the aqueous phase seepage equation in Laplace space is as follows:

[0083]

[0084]

[0085]

[0086]

[0087] In the formula, The dimensionless pressure of the gas phase in an artificial fracture system in Laplace space; The dimensionless pressure of the water phase in the artificial fracture system under Laplace space.

[0088] Step S404: Solve the gas and water two-phase flow equations from step 303 using the Laplace transform to obtain the pressure solution of the gas phase flow equation in Laplace space for the artificial fracture system, as follows:

[0089]

[0090]

[0091] The pressure solution of the aqueous phase seepage equation in Laplace space is as follows:

[0092]

[0093]

[0094] Solving steps S402, S403, and S404 simultaneously yields the solution to the mathematical model for dynamic analysis of gas-water two-phase production in nested media of deep coalbed methane reservoirs.

[0095] The solution for gas phase yield is:

[0096]

[0097] The aqueous phase yield solution is:

[0098]

[0099] In the formula, The solution for gas phase production in Lagrange space; The yield solution for the aqueous phase in the Laplace space.

[0100] Step S405: Integrate all stress-sensitive terms into the pressure conductivity coefficient and use it as a function of the mean formation pressure, as follows:

[0101]

[0102] In the formula, k f For cleavage permeability, mD; k fi γ is the initial cleavage permeability, mD; γ is the permeability modulus, MPa. -1 ;p i The original formation pressure is expressed in MPa. The mean formation pressure is expressed in MPa.

[0103] Step S406: Calculate the mean formation pressure and mean saturation using the mass balance method. The mean pressure function constructed from the mass balance equation is as follows:

[0104]

[0105]

[0106]

[0107] The constructed mean pressure Newton iteration format is as follows:

[0108]

[0109] In the formula: S gi —Initial gas saturation; —Average gas saturation; S wi —Initial water saturation; —Average water saturation; B gi —Gas volume coefficient at the initial moment; —Average gas volume coefficient; B wi —The initial formation water volume coefficient; —Average formation water volume factor; x inv —The range of movement along the crack direction in the inner zone, m; y inv —The range of movement perpendicular to the crack direction in the inner zone, in meters (m); φ m —Reservoir porosity; H—Reservoir thickness, m; x F — Crack half-length, m; t — Production time, h; q g —Daily gas production, 10 4 m 3 / d;q w —Daily water production, m 3 / d;c t—Comprehensive formation compressibility, MPa -1 .

[0110] The mean formation pressure and mean saturation are obtained by using Newton's iteration calculation. Then, the nonlinear parameters at each time step are updated using the mean pressure and saturation within the scope of the calculation. By iteratively calculating step by step, the solution of the mathematical model for the dynamic analysis of gas-water two-phase production in the nested medium of deep coalbed gas reservoirs can be obtained. Then, the gas-water two-phase production capacity curve can be plotted programmatically to predict the dynamics of gas-water production.

[0111] Step S50: Based on the theoretical analysis model, the gas-water two-phase production solution is used to obtain the theoretical curve of the gas-water two-phase production dynamic analysis of the nested medium in deep coal seam gas reservoirs.

[0112] In this step, given the gas reservoir parameters, fluid parameters, and fracture parameters, a theoretical template curve for predicting the dynamic production of gas-water two-phase gas in nested media of deep coal seam gas reservoirs can be generated using the gas-water two-phase production solution. At the same time, the influence of sensitivity parameters can also be analyzed.

[0113] Step S60: Fit the theoretical curve with the actual well production data to obtain the key seepage parameters of the reservoir and fractures, and then predict the production dynamics of the gas and water phases.

[0114] The specific process for this step is as follows:

[0115] Step S601: Normalize the theoretical curves. The gas production curve is plotted with the material balance time as the x-axis and the normalized production as the y-axis. The water production curve is plotted with the material balance time as the x-axis and the normalized production as the y-axis. This method can be used to handle problems with variable production and variable pressure.

[0116]

[0117]

[0118]

[0119]

[0120] In the formula: q g —Theoretical gas production, m 3 / d;q Ng —Regulated gas production; q w —Theoretical water production, m 3 / d;q Nw —Regulated water production; ψ i —Initial simulated pressure, MPa 2 / (mPa·s); ψ wf —Pseudo-bottomhole flowing pressure, MPa 2 / (mPa·s); pi —Initial pressure, MPa; p wf — Bottom hole flowing pressure, MPa; t ca —Pseudo-time of mass equilibrium; t a —Material equilibrium time; G—Cumulative gas production; W—Cumulative water production; c t —Comprehensive compressibility, MPa -1 .

[0121] Step S602: Normalize the actual production data and use Matlab software to plot the measured daily gas production and daily water production curves.

[0122] Step S603: Given the initial reservoir parameters, fluid parameters, and fracture parameters, set the time step and use Matlab software to plot the theoretical gas production and water production curves.

[0123] Step S604: Fit the theoretical sample curve with the measured curve, adjust the parameters and iteratively calculate the key seepage parameters of the reservoir and fractures, and then predict the gas-water two-phase production dynamics. The above fitting interpretation parameters and prediction results have important guiding significance for the fracturing optimization design and development scheme adjustment of deep coal seam gas reservoirs.

[0124] Secondly, the present invention provides a device for predicting the dynamic production of gas-water two-phase gas in nested media in deep coalbed methane reservoirs, comprising the following components:

[0125] The first processing unit is used to analyze the spatial distribution of the fracture network and the basic characteristics of seepage parameters formed by hydraulic fracturing in deep coal seams, clarify the adsorption-desorption-diffusion of gas and the dynamic balance mechanism of gas-water two-phase seepage in the nested medium of coalbed methane reservoirs, and perform precise characterization step by step.

[0126] The second processing unit is used to establish a physical model for dynamic analysis of gas-water two-phase production in nested media of deep coal seam gas reservoirs based on the basic characteristics of the fracture network of hydraulic fracturing in deep coal seams and the gas adsorption-desorption-diffusion and gas-water two-phase seepage mechanism in the nested medium.

[0127] The third processing unit is used to establish a mathematical model for dynamic analysis of gas-water two-phase production in nested media of deep coalbed methane reservoirs based on the physical model.

[0128] The fourth processing unit is used to solve the mathematical model using a semi-analytical method to obtain the gas and water two-phase yield solution.

[0129] The fifth processing unit is used to obtain the theoretical curve of the gas-water two-phase production dynamic analysis of the nested medium in deep coal seam gas reservoirs based on the gas and water two-phase production solution.

[0130] The sixth processing unit is used to fit and interpret the theoretical curve with the actual well production data to obtain key seepage parameters of the reservoir and fractures, and then predict the gas and water two-phase production dynamics.

[0131] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon; when the computer program is executed by a processor, it implements the steps of the dynamic prediction method.

[0132] Thirdly, the present invention provides a computer device, including a processor and a memory for storing a computer program; the processor implements the dynamic prediction method when executing the computer program.

[0133] The beneficial effects of this invention are as follows:

[0134] First, this invention describes the gas-water two-phase flow characteristics and dynamic changes in gas well production in nested media of deep coalbed gas reservoirs by establishing physical and mathematical models. The physical model considers the basic characteristics of hydraulic fracturing fracture network, gas adsorption-desorption-diffusion in nested media, gas-water two-phase seepage mechanism, and stress sensitivity effect of coal reservoirs, which are more in line with reality. Therefore, it can more realistically reflect the flow law of gas-water two-phase fluid in nested media.

[0135] Secondly, this invention utilizes a semi-analytical method based on flow material balance and successive iterative replacement to calculate the dimensionless production solution of gas-water two-phase flow in deep coalbed methane wells. At the same time, it clarifies the flow characteristics of gas-water two-phase flow in nested media and its impact on production dynamics, effectively solving the problem of difficulty in efficiently and accurately solving the gas-water two-phase flow model in deep coalbed methane reservoirs. This method has the advantages of fast calculation speed and good fitting effect.

[0136] Third, this invention uses the generated theoretical curve of gas-water two-phase production dynamics prediction of nested medium in deep coal seam gas reservoirs to fit and interpret the actual production data of the gas field, and obtains key seepage parameters, stress sensitivity coefficient, adsorption coefficient, etc. of the fracturing network. It also accurately predicts the gas-water two-phase production dynamics for the next 20 years. The results can provide reference and guidance for the optimization design and development scheme adjustment of fracturing in deep coal seam gas reservoirs. Attached Figure Description

[0137] Figure 1 This is a schematic flowchart of an embodiment of the dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs provided by the present invention.

[0138] Figure 2 This is a schematic diagram of the physical model of a horizontal well in a deep coalbed methane reservoir, as described in an embodiment of the present invention.

[0139] Figure 3This is the theoretical curve for predicting the dynamic production of gas-water two-phase gas in nested media in deep coalbed methane reservoirs in this embodiment of the invention.

[0140] Figure 4 This is a schematic diagram showing the fitting of theoretical curves and measured production data for dynamic prediction of gas-water two-phase production in nested media of deep coalbed methane reservoirs. Detailed Implementation

[0141] The present invention will now be described in further detail with reference to embodiments and accompanying drawings.

[0142] Figure 1 This is a schematic flowchart of the dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs, as described in an embodiment of the present invention. Figure 1 As shown, the dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs in this embodiment of the invention may include the following steps:

[0143] Step S10: Analyze the spatial distribution and basic characteristics of the fracture network formed by hydraulic fracturing in deep coal seams, clarify the dynamic equilibrium mechanism of gas adsorption-desorption-diffusion and gas-water two-phase seepage in the nested medium of deep coal seam gas reservoirs, and perform precise characterization step by step.

[0144] In this step, based on the understanding of the extension law of deep coal seam pressure fractures and the results of microseismic monitoring, the fractures in the fracture network are subdivided into artificial fractures and natural fractures according to parameters such as fracture formation mechanism, scale, distribution density and conductivity.

[0145] In this step, based on the spatial distribution and seepage parameters of the fracture network, the induced fractures and natural fractures in the fracture network are characterized using the equivalent continuous medium method.

[0146] In this step, based on the desorption, diffusion, and seepage characteristics during the coalbed methane reservoir drainage process, the Langmuir isotherm adsorption law is used to characterize the adsorption and desorption mechanism in the nested medium of coalbed methane, as follows:

[0147]

[0148] Where: V—adsorption capacity, m 3 V L —Langmuir volume, m 3 / m 3 ;ψ L —Langmuir simulated pressure, MPa 2 / (mPa·s).

[0149] The diffusion mechanism in nested media of coalbed methane is characterized by quasi-steady-state diffusion using Fick's first diffusion law, as follows:

[0150]

[0151] Where: D—gas diffusion coefficient, m 2 / s;V m —The average gas concentration within the coal matrix block under pseudo-steady-state diffusion conditions, m 3 / m 3 V E —Gas concentration at the interface between the coal matrix block and the cleavage, m 3 / m 3 ;σ s —Shape factor of coal matrix block, 1 / m 2 .

[0152] Darcy's law is used to characterize the gas-water two-phase flow mechanism in cleavages and fractures, as follows:

[0153]

[0154] In the formula: v fg —Gas seepage velocity in the cleavage system, m / s; v fw — Formation water seepage velocity in the cleavage system, m / s; v Fg —Gas seepage velocity in the artificial fracture system, m / s; v Fw —Formation water seepage velocity in the artificial fracture system, m / s; μ g —Gas viscosity, mPa·s; μ w — Formation water viscosity, mPa·s; kJ f —Pergeusia, mD; k frg —Relative gas-phase permeability of the cleavage system; k frw —Relative permeability of the aqueous phase in the cleavage system; k F —Crack permeability, mD; k Frg —Relative gas permeability of the fracture system; k Frw —Relative permeability of the water phase in the fracture system.

[0155] Step S20: Based on the spatial distribution and basic characteristics of the fracture network formed by hydraulic fracturing in deep coal seams and the dynamic equilibrium mechanism of gas adsorption-desorption-diffusion and gas-water two-phase seepage in the nested medium of deep coal seam gas reservoirs, a physical model for the dynamic analysis of gas-water two-phase production in the nested medium of deep coal seam gas reservoirs is established.

[0156] In this step, based on the basic characteristics of artificial fracture networks, cleavage, and matrix in deep coal seams, the complex fracture network is processed into an equivalent fracturing body from the perspective of establishing a seepage mathematical model. At the same time, considering the gas adsorption-desorption, diffusion, and gas-water two-phase seepage effects in the nested medium of deep coal seam gas reservoirs, the fracturing body is characterized by a trilinear flow model, thereby establishing a physical model for the dynamic analysis of gas-water two-phase production in the nested medium of deep coal seam gas reservoirs.

[0157] The equivalent fracturing body consists of an artificial main fracture, an inner fracturing zone, and an outer fracturing zone. The inner fracturing zone primarily considers the complex fracture network system formed by fracturing, treating it as a "nested medium" of artificial fractures, natural fractures, cleavage, and matrix, such as... Figure 2 As shown, the outer zone of the fracturing-modified area, since it has not been subjected to fracturing modification, is treated as a "dual medium" of cleavage and matrix.

[0158] In the aforementioned trilinear flow model, the fluid flow is divided into three regions: the linear flow region of the inner fracture zone, the linear flow region of the formation fluid perpendicular to the fracture zone, and the linear flow region of the outer fluid parallel to the fracture zone. In each region, the fluid flow is treated as linear flow, that is, the outer fluid flows linearly into the inner fracture medium, the fluid in the inner cleavage zone flows linearly into the inner fracture medium, and then flows linearly from the inner fracture zone into the artificial fracture.

[0159] Before establishing the seepage mathematical model, it is necessary to first define the assumptions of the physical model. Based on the multi-medium nested model of deep coalbed methane reservoirs, the assumptions of the physical model include:

[0160] (1) The top, bottom and lateral boundaries of the three regions in the deep coal seam are all closed;

[0161] (2) All deep coal seams were fractured, and the fractures were symmetrical with the shaft.

[0162] (3) The artificial fractures are vertical and penetrate the reservoir, and intersect only at the perforation of the horizontal well, while the rest of the horizontal well is sealed.

[0163] (4) The artificial fractures are directly connected to the wellbore, and the fluid flows into the production wellbore only through the fractures. The fluid in the reservoir continuously flows to the fractures to provide energy supply.

[0164] (5) Consider the reservoir permeability stress sensitivity;

[0165] (6) Considering the co-production of gas and water, both the coal seam cleavage and artificial fractures are two-phase flow of gas and water, and conform to isothermal Darcy flow.

[0166] (7) The adsorption and desorption of coalbed methane in the matrix follows the Langmuir theory;

[0167] (8) Compared with gas, the compressibility coefficient of formation water is small and can be ignored;

[0168] (9) The effects of gravity and capillary force are not considered.

[0169] Step S30: Based on the physical model, establish a mathematical model for dynamic analysis of gas-water two-phase production in nested media of deep coalbed methane reservoirs.

[0170] In this step, based on the assumptions of the physical model, the flow process in the production stage is divided into three parts: outer zone flow, inner zone flow, and artificial fracture flow. Seepage models for the fluid flow in each part are then established. The specific steps are as follows:

[0171] Step S301: The migration of coalbed methane in the inner and outer zones involves several processes: desorption, diffusion, and seepage. In the matrix, desorption and diffusion are the primary mechanisms; seepage due to pressure differences is absent. The adsorption and desorption processes of coalbed methane are characterized using Langmuir's isothermal adsorption law, the diffusion process using Fick's first law (quasi-steady-state diffusion), and the gas-water two-phase seepage in the cleavage system using Darcy's equation. This yields the actual seepage equation for the outer zone matrix-cleavage system. To simplify the mathematical model, dimensionless parameters and their definitions are introduced. The gas-phase flow equation is treated with quasi-pressure and quasi-time. The dimensionless gas-phase seepage equation for the outer zone cleavage system is:

[0172]

[0173] The pseudo-steady-state diffusion equation of coalbed methane in the matrix system is as follows:

[0174]

[0175] The adsorption of adsorbed gas in the outer coal seam matrix conforms to the Langmuir isotherm adsorption law, and the dimensionless equation is as follows:

[0176] V ED =βψ f2D

[0177] The boundary conditions are:

[0178]

[0179] The aqueous phase flow equations for the outer zone cleavage system are treated in real time, and the dimensionless aqueous phase seepage equations are as follows:

[0180]

[0181] The boundary conditions are:

[0182]

[0183] In the formula: ψf1D —The internal cleavage system has dimensionless pseudo-pressure; ψ f2D —Dimensionless pseudo-pressure in the outer zone cleavage system; p f1D —The internal cleavage system has dimensionless pressure; p f2D —Dimensionless pressure in the outer zone cleavage system; V m2D —Adsorption concentration of dimensionless coal matrix particles in the outer zone; V ED —Equilibrium adsorption concentration of dimensionless coal matrix particles in the outer zone; k frg —Relative gas-phase permeability in the cleavage system; k frw —Relative permeability of the aqueous phase in the cleavage system; x D —Dimensionless length (x-coordinate direction); x eD —Dimensionless outer boundary distance (x-coordinate direction); η f2D —Dimensionless pressure conductivity coefficient of the gas phase in the outer zone cleavage system; η f2wD —Dimensionless pressure conductivity coefficient of the aqueous phase in the outer zone cleavage system; t aD —Dimensionless pseudotime; t D —Dimensionless time; ω2—Storage capacity coefficient of the outer zone cleavage system; λ2—Channeling coefficient of the outer zone cleavage system; β—Coalbed methane adsorption coefficient.

[0184] Step S302: The inner zone mainly considers the complex fracture network system formed by fracturing. The fracture system is equivalent to a dual-medium system, characterized using the Kazemi unsteady-state flow model. The adsorption and desorption process of coalbed methane in the inner zone is characterized using Langmuir's isothermal adsorption law, and the diffusion process is characterized using Fick's first law of quasi-steady-state diffusion. The gas-water two-phase flow in the cleavage system is characterized using Darcy's equation. Introducing dimensionless parameters and their definitions, the dimensionless inner zone nested medium flow equation is obtained, including the flow equations for fractures, cleavages, and the matrix. In this step, the inner zone fracture system flow equation is:

[0185]

[0186] The vapor phase flow equation for the inner zone cleavage system is:

[0187]

[0188] The pseudo-steady-state diffusion equation for coalbed methane in the inner zone within the matrix system is as follows:

[0189]

[0190] The adsorption of the gas in the inner zone follows the Langmuir isotherm adsorption law, and the dimensionless equation is as follows:

[0191] V ED =βψ f1D

[0192] The boundary conditions are:

[0193]

[0194] The water flow equations for the internal fracture system are calculated using real-time conditions, and the dimensionless seepage equations are as follows:

[0195]

[0196] The aqueous flow equations for the inner zone cleavage system are treated in real-time, and the dimensionless seepage equations are as follows:

[0197]

[0198] The boundary conditions are:

[0199]

[0200] Step S303: The gas-water two-phase flow in the artificial fracture system is characterized using the Darcy equation, with dimensionless parameters introduced and defined. The gas-phase flow equation is treated with pseudo-pressure and pseudo-time. In this step, the gas-phase flow equation of the artificial fracture system is as follows:

[0201]

[0202] The boundary conditions are:

[0203]

[0204] The aqueous phase flow equations are processed using real-time conditions. In this step, the aqueous phase seepage equations for the artificial fracture system are as follows:

[0205]

[0206] The boundary conditions are:

[0207]

[0208] In the formula: C FD —Dimensionless artificial fracture conductivity; η FD —Dimensionless pressure conductivity coefficient of the gas phase in an artificial fracture system; η FwD —Dimensionless pressure conductivity of the aqueous phase in an artificial fracture system; w FD —Dimensionless artificial crack width; k Frg —Relative gas permeability in the artificial fracture system; k Frw —Relative permeability of the water phase in an artificial fracture system.

[0209] Step S40: Using a semi-analytical method, solve the mathematical model for dynamic analysis of gas-water two-phase production in nested media of deep coalbed gas reservoirs to obtain the gas and water two-phase production solutions.

[0210] In this step, a semi-analytical method is used to solve the mathematical model of the gas-water two-phase production dynamics analysis of nested media in deep coalbed methane reservoirs, obtaining the gas-water two-phase solution. The semi-analytical method combines flow mass balance and iterative replacement. The flow mass balance method is used to calculate the average pressure and average saturation of the reservoir, and the nonlinear parameters in the seepage model are updated iteratively to gradually linearize the seepage model, thereby obtaining the semi-analytical solution of the mathematical model. This method can accurately handle the nonlinear seepage problem of gas-water two-phase flow and has the high computational efficiency of analytical methods.

[0211] This method may specifically include the following steps:

[0212] Step S401: Discretize the production time into multiple time steps. In each time step, the pressure-related parameter (μ) g B g ) and parameters related to saturation (k) frg k frw k Frg k Frw The average pressure and average saturation within the operating range are updated and replaced respectively. Therefore, the nonlinear parameters at each time step can be treated as constant approximations. After dealing with the nonlinear seepage problem, the gas phase and water phase yields at each time step can be obtained by directly solving the equations.

[0213] Step S402: Perform a Laplace transform on the gas-water two-phase flow equations of the outer zone to obtain the pressure solution of the gas-phase flow equations of the outer zone cleavage system in Laplace space:

[0214]

[0215]

[0216]

[0217]

[0218] The pressure solution of the external aqueous phase seepage equation in Laplace space is:

[0219]

[0220]

[0221]

[0222] In the formula: —Dimensionless pressure of the gas phase in the inner region of the Lagrange space cleavage system; —Dimensionless pressure of the gas phase in the outer zone cleavage system under Lagrange space; —Dimensionless pressure of the aqueous phase in the inner zone cleavage system under Lagrange space; p f2D —Dimensionless pressure of the aqueous phase in the outer zone cleavage system under Laplace space; u is the Laplace operator.

[0223] Step S403: Perform a Laplace transform on the gas-water two-phase flow equation in the inner zone to obtain the pressure solution of the gas-phase flow equation in the Laplace space for the inner zone fracture system:

[0224]

[0225]

[0226]

[0227]

[0228] The pressure solution of the aqueous seepage equation for the internal fracture system in Laplace space is:

[0229]

[0230]

[0231]

[0232]

[0233] In the formula: —Dimensionless pressure of the gas phase in an artificial fracture system under Laplace space; —Dimensionless pressure of the aqueous phase in an artificial fracture system under Laplace space.

[0234] Step S404: Perform a Laplace transform on the gas-water two-phase flow equation of the artificial fracture system to obtain the pressure solution of the gas-phase flow equation in Laplace space:

[0235]

[0236]

[0237] The pressure solution of the aqueous flow equation for the artificial fracture system in Laplace space is:

[0238]

[0239]

[0240] Solving steps S402, S403, and S404 simultaneously yields the solution to the mathematical model for dynamic analysis of gas-water two-phase production in nested media of deep coalbed methane reservoirs.

[0241] The solution for gas phase yield is:

[0242]

[0243] The aqueous phase yield solution is:

[0244]

[0245] In the formula, The solution for gas phase production in Lagrange space; The yield solution for the aqueous phase in the Laplace space.

[0246] Step S405: Integrate all stress-sensitive terms into the pressure conductivity coefficient and use it as a function of the mean formation pressure, as follows:

[0247]

[0248] In the formula: k f —Pergeusia, mD; k fi — Initial cleavage permeability, mD; γ — Permeability modulus, MPa -1 ;p i —Original formation pressure, MPa; —Mean formation pressure, MPa.

[0249] Step S406: As described in step S401, at each time step, the pressure-related parameters (μ) in the gas-water two-phase production solution and stress-sensitive terms are... g B g ) and parameters related to saturation (k) frg k frw k Frg k Frw The mean pressure and mean saturation within the operational range are updated and replaced respectively, while the mean formation pressure and mean saturation are calculated by the flow mass balance method.

[0250] The process of establishing the fluid balance equation is as follows:

[0251] The gas phase mass balance equation is:

[0252]

[0253] The equilibrium equation for the aqueous phase is:

[0254]

[0255] The operational range of the inner zone along the crack direction and perpendicular to the crack direction are as follows:

[0256]

[0257]

[0258] The saturation of the gas and water phases satisfies the following relationship:

[0259]

[0260] The average pressure function can be constructed from the gas-water two-phase flow mass balance equations, as follows:

[0261]

[0262]

[0263]

[0264] The further constructed mean pressure Newton iteration scheme is as follows:

[0265]

[0266] In the formula: S gi —Initial gas saturation; —Average gas saturation; S wi —Initial water saturation; —Average water saturation; B gi —Gas volume coefficient at the initial moment; —Average gas volume coefficient; B wi —The initial formation water volume coefficient; —Average formation water volume factor; x inv —The range of movement along the crack direction in the inner zone, m; y inv —The range of movement perpendicular to the crack direction in the inner zone, in meters (m); φ m —Matrix porosity; H—Reservoir thickness, m; x F — Crack half-length, m; t — Production time, h; q g —Daily gas production, 10 4 m 3 / d;q w —Daily water production, m 3 / d;c t —Comprehensive formation compressibility, MPa -1 .

[0267] The mean formation pressure and mean saturation are calculated using the fluid mass balance method. Then, the nonlinear parameters at each time step are updated and replaced one by one. Through iterative calculation, the solution of the mathematical model for the dynamic analysis of gas-water two-phase production in the nested medium of deep coalbed methane reservoirs can be obtained. Then, Matlab software is used to program and solve the problem to draw the theoretical template curve for predicting the dynamic production of gas and water two-phase production, thereby predicting the dynamic production of gas and water.

[0268] Step S50: Based on the gas and water two-phase production solution of the theoretical analysis model, obtain the theoretical curve of gas-water two-phase production dynamic analysis of the nested medium in deep coal seam gas reservoir.

[0269] In this step, given the gas reservoir parameters, fluid parameters, and fracture parameters, a theoretical template curve for predicting the dynamic production of gas-water two-phase gas in nested media of deep coal seam gas reservoirs can be generated using the gas-water two-phase production solution. At the same time, the influence of sensitivity parameters can also be analyzed.

[0270] Figure 3 These are the theoretical curves of the dynamic analysis model of gas-water two-phase production in nested media of deep coalbed methane reservoirs in this embodiment of the invention. The curve on the left is the gas production curve, and the curve on the right is the water production curve.

[0271] Step S60: Fit the theoretical curve with the actual well production data to obtain the key seepage parameters of the reservoir and fractures, and then predict the production dynamics of the gas and water phases.

[0272] The specific process for this step is as follows:

[0273] Step S601: Normalize the theoretical curves. The gas production curve is plotted with the material balance time as the x-axis and the normalized production as the y-axis. The water production curve is plotted with the material balance time as the x-axis and the normalized production as the y-axis. This method can be used to handle problems with variable production and variable pressure.

[0274]

[0275]

[0276]

[0277]

[0278] In the formula: q g —Theoretical gas production, m 3 / d;q Ng —Regulated gas production; q w —Theoretical water production, m 3 / d;q Nw —Regulated water production; ψ i —Initial simulated pressure, MPa2 / (mPa·s); ψ wf —Pseudo-bottomhole flowing pressure, MPa 2 / (mPa·s); p i —Initial pressure, MPa; p wf — Bottom hole flowing pressure, MPa; t ca —Pseudo-time of mass equilibrium; t a —Material equilibrium time; G—Cumulative gas production; W—Cumulative water production; c t —Comprehensive compressibility, MPa -1 .

[0279] Step S602: Normalize the actual production data and use Matlab software to plot the measured daily gas production and daily water production curves.

[0280] Step S603: Given the initial reservoir parameters, fluid parameters, and fracture parameters, set the time step and use Matlab software to plot the theoretical gas production and water production curves.

[0281] Step S604: Fit the theoretical sample curve with the measured curve, adjust the parameters and iteratively calculate the key seepage parameters of the reservoir and fractures, and then predict the gas-water two-phase production dynamics. The above fitting interpretation parameters and prediction results have important guiding significance for the fracturing optimization design and development scheme adjustment of deep coal seam gas reservoirs.

[0282] The following is a specific embodiment of the dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs in this invention:

[0283] Example 1

[0284] This case study uses production data from CBM1, a multi-stage fractured horizontal well in a coalbed methane reservoir in the Ordos Basin. CBM1 is a horizontal well in a coalbed methane field in the Ordos Basin, with an interval of 2002–2498m and a well length of 1000m. It was put into production in March 2021, with a formation pressure of 18.9 MPa in the middle of the formation. Eight stages of mixed water fracturing were performed on this well. Production dynamic data from March 1, 2021 to August 18, 2022 were used for fitting and interpretation, and then gas-water two-phase production capacity prediction was carried out based on the fitting results.

[0285] The dynamic prediction method for gas-water two-phase production in deep coalbed methane reservoirs, as described in this invention, was used to fit the production dynamic data of well CBM1. The double logarithmic fitting curve is shown below. Figure 4 As shown in the figure, the model fits the production of the gas-water two-phase mixture in deep coalbed methane wells very well very well.

[0286] Table 1 shows the reservoir and fracture parameters of the well obtained after fitting and inversion. Comparison reveals that the inversion results are consistent with the geological characteristics and actual production of the gas reservoir. The obtained key seepage parameters of the reservoir and fractures can provide theoretical guidance for predicting the production capacity of coalbed methane wells, optimizing fracturing parameters, and evaluating post-fracturing effects.

[0287] Using this model to predict future production, the daily gas production is projected to be 0.12 × 10⁻⁶ after 20 years of production. 4 m 3 / d, daily water production is 0.44m³ 3 / d, cumulative gas production is 0.11×10 8 m 3 The cumulative water production was 0.41 × 10⁻⁶. 4 m 3 The results can provide reference and guidance for adjusting development plans for deep coalbed methane reservoirs.

[0288] Table 1

[0289] parameter Value parameter Value Artificial crack half length, m 78 Fracture conductivity, D·cm 0.23 Penetration rate of the transformation area, mD 2.25 Reservoir permeability, mD 0.05 Storage capacity coefficient 0.052 Crossflow coefficient <![CDATA[1.3×10 -5 ]]> Adsorption coefficient 0.91 <![CDATA[Stress sensitivity coefficient, MPa -1 > 0.07

[0290] The dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs in this invention has the following beneficial effects:

[0291] First, this invention describes the gas-water two-phase flow characteristics of nested media in deep coalbed gas reservoirs and the dynamic changes in gas well production by establishing physical and mathematical models. The physical model considers the basic characteristics of hydraulic fracturing fracture network, gas adsorption-desorption-diffusion in nested media, gas-water two-phase seepage mechanism, and stress sensitivity effect of coal reservoirs, which are more in line with reality. It can more realistically reflect the flow law of gas-water two-phase fluid in nested media.

[0292] Secondly, this invention uses a semi-analytical method based on flow material balance and successive iterative replacement to calculate the dimensionless production solution of gas-water two-phase flow in deep coalbed methane wells. At the same time, it clarifies the flow characteristics of gas-water two-phase flow in nested media and its impact on production dynamics. This effectively solves the problem that the gas-water two-phase flow model of deep coalbed methane reservoirs is difficult to solve efficiently and accurately. This method has the advantages of fast calculation speed and good fitting effect.

[0293] Third, this invention uses the generated theoretical curve of gas-water two-phase production dynamics prediction of nested medium in deep coal seam gas reservoirs to fit and interpret the actual production data of the gas field, and obtains key seepage parameters, stress sensitivity coefficient, adsorption coefficient, etc. of the fracturing network. It also accurately predicts the gas-water two-phase production dynamics for the next 20 years. The results can provide reference and guidance for the optimization design and development scheme adjustment of fracturing in deep coal seam gas reservoirs.

[0294] Example 2

[0295] An apparatus for dynamically predicting the gas-water two-phase production of nested media in deep coalbed methane reservoirs includes a processor and a memory for storing a computer program; the processor executes instructions issued by the computer program to realize the dynamic prediction method for the gas-water two-phase production of nested media in deep coalbed methane reservoirs.

[0296] In this embodiment, the memory may include a physical device for storing information, typically digitizing the information and then storing it using a medium employing electrical, magnetic, or optical methods. The memory described in this embodiment may further include: devices that store information using electrical energy, such as RAM and ROM; devices that store information using magnetic energy, such as hard disks, floppy disks, magnetic tapes, magnetic core memory, bubble memory, and USB flash drives; and devices that store information using optical methods, such as CDs or DVDs. Of course, there are other types of memory, such as quantum memories, graphene memories, etc. In this embodiment, the processor can be implemented in any suitable manner. For example, the processor may take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. The specific functions implemented by the processor and memory of the server provided in this specification can be explained in comparison with the foregoing embodiments in this specification.

[0297] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All equivalent changes or modifications made according to the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs, comprising the following steps: Step S10: Analyze the spatial distribution and basic characteristics of the fracture network formed by hydraulic fracturing in deep coal seams, clarify the adsorption and desorption mechanism, diffusion mechanism, and gas-water two-phase flow mechanism of gas in the nested medium of deep coal seam gas reservoirs, and perform precise characterization step by step. Step S20: Based on the basic characteristics of the spatial distribution and seepage parameters, the adsorption and desorption mechanism, the diffusion mechanism, and the gas-water two-phase seepage mechanism, establish a physical model for dynamic analysis of gas-water two-phase production in nested media of deep coal seam gas reservoirs. Step S30: Establish a mathematical model based on the physical model; Step S40: Solve the mathematical model to obtain the gas and water two-phase production solution; Step S50: Based on the gas and water two-phase production solution, obtain the theoretical curve of the gas-water two-phase production dynamic analysis of the nested medium in deep coalbed gas reservoirs; Step S60: Fit and interpret the theoretical curve with the actual well production data to obtain key seepage parameters of the reservoir and fractures, and then predict the gas and water two-phase production dynamics. In step S30, the mathematical model is established as follows: Step S301: Based on dimensionless parameters and their definitions, establish the fluid seepage equations and boundary conditions for the external cleavage system and the coal matrix system; The vapor phase flow equation and boundary conditions are treated with pseudo-pressure and pseudo-time. The vapor phase flow equation for the outer zone cleavage system is as follows: The pseudo-steady-state diffusion equation of coalbed methane in the matrix system is as follows: The boundary conditions are: The aqueous phase flow equations are treated in real-time, and the dimensionless governing equations for the aqueous phase of the outer zone cleavage system are as follows: The boundary conditions are: In the formula: ψ f1D —Dimensionless pseudo-pressure in the inner zone cleavage system; ψ f2D —Dimensionless pseudo-pressure in the outer zone cleavage system; p f1D —Dimensionless pressure in the inner zone cleavage system; p f2D —Dimensionless pressure in the outer zone cleavage system; V m2D —Adsorption concentration of dimensionless coal matrix particles in the outer zone; V ED —Equilibrium adsorption concentration of dimensionless coal matrix particles in the outer zone; k frg —Relative permeability of the gas phase in the cleavage system; k frw —Relative permeability of the aqueous phase in the cleavage system; x D —Dimensionless length; x eD —Dimensionless outer boundary distance; η f2D —Dimensionless pressure coefficient of the gas phase in the outer zone cleaving system; η f2wD —Dimensionless pressure conductivity coefficient of the aqueous phase in the outer zone cleavage system; t aD —Dimensionless approximation of time; t D —Dimensionless time; ω 2—Reservoir capacity coefficient of the outer zone cutting system; λ 2—Channeling coefficient of the outer zone cleavage system; β —Coalbed methane adsorption coefficient; Step S302: Based on dimensionless parameters and their definitions, establish the fluid seepage equations and boundary conditions in the inner zone cleavage and coal matrix system; The vapor phase flow equation and boundary conditions are treated with pseudo-pressure and pseudo-time. The vapor phase flow equation for the inner zone cleavage system is as follows: The pseudo-steady-state diffusion equation of coalbed methane in the matrix system is as follows: The boundary conditions are: The aqueous phase flow equations are treated with real-time conditions. The dimensionless governing equations for the aqueous phase in the inner zone cleavage system are as follows: The boundary conditions are: In the formula: ψ FD —The artificial fracture system is dimensionless pseudo-pressure; p FD —The artificial fracture system has dimensionless pressure; V m1D —Adsorption concentration of dimensionless coal matrix particles in the inner zone; y D —Dimensionless length; y eD —Dimensionless outer boundary distance; η f1D —Dimensionless pressure conductivity coefficient of the gas phase in the inner zone cleaving system; η f1wD —Dimensionless pressure coefficient of the aqueous phase in the inner zone cleaving system; ω 1—Inner zone cleavage system storage capacity coefficient; λ 1—Internal zone cleavage system crossflow coefficient; Step S303: Based on dimensionless parameters and their definitions, establish the fluid seepage equation and boundary conditions in the artificial fracture system; The gas-phase flow equation and boundary conditions are treated with pseudo-pressure and pseudo-time. The gas-phase flow equation for the artificial fracture system is as follows: The boundary conditions are: The aqueous phase seepage equations are treated with real-time data. The dimensionless governing equations for the aqueous phase in the artificial fracture system are as follows: The boundary conditions are: In the formula: C FD —Dimensionless artificial fracture conductivity; η FD —Dimensionless pressure conductivity coefficient of the gas phase in an artificial fracture system; η FwD —Dimensionless pressure conductivity coefficient of the aqueous phase in an artificial fracture system; w FD —Dimensionless artificial crack width; k Frg —Relative gas permeability in an artificial fracture system; k Frw —Relative permeability of the water phase in an artificial fracture system.

2. The dynamic prediction method according to claim 1, characterized in that: The operation steps of step S10 include: Step S101: Based on the propagation law of the pressure fracture and the results of microseismic monitoring, analyze the basic characteristics of the spatial distribution and seepage parameters of the fracture network; Step S102: Based on the aforementioned basic characteristics, the induced and natural fractures in the fracture network are characterized using the equivalent continuous medium method. Step S103: Based on the desorption, diffusion, and seepage characteristics during the drainage process of coalbed methane reservoirs, the adsorption and desorption mechanism of gas in the nested medium of deep coalbed methane reservoirs is characterized by Langmuir isothermal adsorption law, the diffusion mechanism of gas in the nested medium of deep coalbed methane reservoirs is characterized by quasi-steady-state diffusion using Fick's first diffusion law, and the gas-water two-phase seepage mechanism is characterized by Darcy's law.

3. The dynamic prediction method according to claim 1, characterized in that: In step S20, the process of establishing the physical model is as follows: Based on the basic characteristics of artificial fracture networks, cleavage, and matrix in deep coal seams, from the perspective of establishing a seepage mathematical model, the complex fracture network is treated as an equivalent fracturing body. At the same time, considering the gas adsorption and desorption mechanism, diffusion mechanism, and gas-water two-phase seepage mechanism in the nested medium of deep coal seam gas reservoirs, the fracturing body is characterized by a trilinear flow model. In this way, a physical model for the dynamic analysis of gas-water two-phase production in the nested medium of deep coal seam gas reservoirs is established.

4. The dynamic prediction method according to claim 1, characterized in that: In step S20, the assumptions of the physical model include: (1) The top, bottom and lateral boundaries of the three regions of the deep coal seam are all closed; (2) The deep coal seam is completely fractured, and the fractures are symmetrical with the shaft. (3) The artificial fractures are vertical and penetrate the reservoir, and intersect only at the perforation of the horizontal well, while the other sections of the horizontal well are sealed. (4) The artificial fractures are directly connected to the wellbore, and the fluid flows into the production wellbore only through the fractures. The fluid in the reservoir continuously flows to the fractures to provide energy supply. (5) Consider the reservoir permeability stress sensitivity; (6) Considering the co-production of gas and water, both the coal seam cleavage and the artificial fractures are two-phase flow of gas and water, and conform to isothermal Darcy flow. (7) The adsorption and desorption of coalbed methane in the matrix follows the Langmuir theory; (8) Compared with gas, the compressibility coefficient of formation water is small and can be ignored; (9) The effects of gravity and capillary force are not considered.

5. The dynamic prediction method according to claim 1, characterized in that: Step S40, which involves solving the mathematical model using a semi-analytical method, includes: A semi-analytical method is adopted by combining fluid balance and successive iterative replacement. The fluid balance method is used to calculate the average pressure and average saturation of the reservoir, and the nonlinear parameters in the seepage model are updated one by one to gradually realize the linearization of the seepage model, thereby obtaining the semi-analytical solution of the mathematical model.

6. The dynamic prediction method according to claim 1, characterized in that: In step S50, given the gas reservoir parameters, fluid parameters, and fracture parameters, the gas-water two-phase production solution is used to generate the theoretical curve for predicting the dynamic production of the gas-water two-phase mixture in the nested medium of deep coal seam gas reservoirs, and the influence of the sensitivity parameters is analyzed.

7. An apparatus for implementing the dynamic prediction method for gas-water two-phase production in nested media of deep coalbed methane reservoirs according to any one of claims 1-6, comprising the following components: The first processing unit is used to analyze the spatial distribution of the fracture network and the basic characteristics of seepage parameters formed by hydraulic fracturing in deep coal seams, clarify the adsorption-desorption-diffusion of gas and the dynamic balance mechanism of gas-water two-phase seepage in the nested medium of coalbed methane reservoirs, and perform precise characterization step by step. The second processing unit is used to establish a physical model for dynamic analysis of gas-water two-phase production in nested media of deep coal seam gas reservoirs based on the basic characteristics of the fracture network of hydraulic fracturing in deep coal seams and the gas adsorption-desorption-diffusion and gas-water two-phase seepage mechanism in the nested medium. The third processing unit is used to establish a mathematical model for dynamic analysis of gas-water two-phase production in nested media of deep coalbed methane reservoirs based on the physical model. The fourth processing unit is used to solve the mathematical model using a semi-analytical method to obtain the gas and water two-phase yield solution. The fifth processing unit is used to obtain the theoretical curve of the gas-water two-phase production dynamic analysis of the nested medium in deep coal seam gas reservoirs based on the gas and water two-phase production solution. The sixth processing unit is used to fit and interpret the theoretical curve with the actual well production data to obtain key seepage parameters of the reservoir and fractures, and then predict the gas and water two-phase production dynamics.

8. A computer-readable storage medium having a computer program stored thereon; said computer program, when executed by a processor, implements the steps of the dynamic prediction method according to any one of claims 1-6.

9. A computer device comprising a processor and a memory for storing a computer program; wherein the processor, when executing the computer program, implements the dynamic prediction method according to any one of claims 1-6.

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