Shale airflow seepage simulation method, device, equipment and medium

Abstract

The invention discloses a shale airflow seepage simulation method, device and equipment and a storage medium. The method comprises the steps that a seepage model of fluid flowing of a target horizontal well is obtained, the seepage model is dimensionless according to predefined dimensionless variables, and a dimensionless seepage model is obtained; determining a complex frequency domain seepage model based on Laplace transformation according to the dimensionless seepage model; determining shale gas yield data according to the complex frequency domain seepage model; and according to the shale gas yield data, determining a shale gas flow seepage simulation result. According to the technical scheme, the problem that the yield prediction accuracy of the multi-section fractured horizontal well of the shale gas reservoir is low is solved, an accurate mathematical model can be used for simulating the heterogeneity characteristics of a hydraulic fracture and a transformation area, accurate description of the shale gas seepage process is achieved, and then accurate and efficient prediction of the yield of the multi-section fractured horizontal well of the shale gas reservoir is achieved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a shale gas flow seepage simulation method, device, electronic equipment and storage medium. Background Art

[0002] Currently, shale gas resources are widely distributed and abundant, but the original permeability and porosity of shale reservoirs are extremely low, requiring the application of multi-stage horizontal well fracturing technology to achieve commercial development of shale gas reservoirs. However, after large-scale fracturing, the complex fracture network is highly heterogeneous, with the coexistence of hydraulic fractures (HF), stimulated reservoir volumes (SRV), and unstimulated reservoir volumes (NSRV). This leads to significant differences in permeability between regions, and the permeability of both HF and SRV regions varies dramatically with distance. Linear flow models struggle to accurately describe the heterogeneity of fracture networks in shale gas reservoirs, especially by ignoring the strong heterogeneity of HF and SRV regions, resulting in significant errors in production predictions.

[0003] Therefore, there is an urgent need for a heterogeneous shale gas seepage analytical simulation method to accurately characterize the heterogeneous distribution of permeability and achieve accurate and efficient prediction of the production of multi-stage fractured horizontal wells in shale gas reservoirs. Summary of the Invention

[0004] The present invention provides a shale gas flow seepage simulation method, device, equipment and storage medium to solve the problem of low accuracy in production prediction of multi-stage fractured horizontal wells in shale gas reservoirs. It can use accurate mathematical models to simulate the heterogeneous characteristics of hydraulic fractures and transformed areas, achieve accurate description of the shale gas seepage process, and thus realize accurate and efficient prediction of the production of multi-stage fractured horizontal wells in shale gas reservoirs.

[0005] According to one aspect of the present invention, a shale gas flow seepage simulation method is provided, the method comprising:

[0006] Obtaining a seepage model of fluid flow in a target horizontal well, and converting the seepage model into a dimensionless model according to predefined dimensionless variables to obtain a dimensionless seepage model;

[0007] According to the dimensionless percolation model, a complex frequency domain percolation model is determined based on Laplace transform;

[0008] Determine shale gas production data based on the complex frequency domain seepage model;

[0009] The shale gas flow seepage simulation results are determined based on the shale gas production data.

[0010] According to another aspect of the present invention, a shale gas flow seepage simulation device is provided, the device comprising:

[0011] A seepage model acquisition module is used to obtain a seepage model of fluid flow in a target horizontal well, and to convert the seepage model into a dimensionless model according to predefined dimensionless variables to obtain a dimensionless seepage model;

[0012] A complex frequency domain model determination module, configured to determine a complex frequency domain percolation model based on the dimensionless percolation model and Laplace transform;

[0013] A gas production data determination module is used to determine shale gas production data based on a complex frequency domain seepage model;

[0014] The simulation result determination module is used to determine the shale gas flow seepage simulation result based on the shale gas production data.

[0015] According to another aspect of the present invention, an electronic device is provided, comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the shale gas flow seepage simulation method described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the shale gas flow seepage simulation method according to any embodiment of the present invention when executed.

[0020] The technical solution of the embodiment of the present invention obtains a seepage model of fluid flow in a target horizontal well and, based on predefined dimensionless variables, non-dimensionalizes the seepage model to obtain a dimensionless seepage model. A complex frequency domain seepage model is then determined based on the dimensionless seepage model using a Laplace transform. Shale gas production data is then determined based on the complex frequency domain seepage model. Finally, shale gas flow simulation results are determined based on the shale gas production data. This technical solution addresses the issue of low production prediction accuracy for multi-stage fractured horizontal wells in shale gas reservoirs. By utilizing a precise mathematical model to simulate the heterogeneous characteristics of hydraulic fractures and the stimulated zone, it accurately describes the shale gas seepage process and thus enables precise and efficient production prediction for multi-stage fractured horizontal wells in shale gas reservoirs.

[0021] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 This is a flow chart of a shale gas flow seepage simulation method provided in accordance with the first embodiment of the present invention;

[0024] Figure 2A This is a flow chart of a shale gas flow seepage simulation method provided in accordance with the second embodiment of the present invention;

[0025] Figure 2B Schematic diagram of the minimum simulation unit of transient linear flow in a multi-stage fractured horizontal well according to the second embodiment of the present invention;

[0026] Figure 2C 2 is a schematic diagram of shale gas flow simulation results provided in accordance with the second embodiment of the present invention;

[0027] Figure 3 This is a schematic structural diagram of a shale gas flow seepage simulation device provided according to the third embodiment of the present invention;

[0028] Figure 4 It is a structural schematic diagram of an electronic device for implementing the shale gas flow seepage simulation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0031] Example 1

[0032] Figure 1 A flowchart of a shale gas flow simulation method is provided for the first embodiment of the present invention. This embodiment is applicable to shale gas flow simulation scenarios. The method can be executed by a shale gas flow simulation device, which can be implemented in the form of hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0033] S110 , obtaining a seepage model of fluid flow in a target horizontal well, and converting the seepage model into a dimensionless model according to predefined dimensionless variables to obtain a dimensionless seepage model.

[0034] This solution can be executed by electronic devices such as computers and servers. The electronic device can pre-acquire a seepage model of the fluid flow of a constructed target horizontal well, wherein the target horizontal well can be a multistage fracturing horizontal well (MFHW). The seepage model of the target horizontal well can include a linear flow model in an unreformed area, a spherical radial flow model in a reformed area, a linear flow model in a reformed area, and a linear flow model in a hydraulic fracture area. The electronic device can pre-define dimensionless variables, and dimensionlessly transform each physical quantity in the seepage model to obtain a dimensionless seepage model.

[0035] S120: Determine a complex frequency domain percolation model based on the dimensionless percolation model and Laplace transform.

[0036] After the percolation model is dimensionless, the electronic device may perform Laplace transform on the dimensionless percolation model to convert the dimensionless percolation model into a complex frequency domain, so as to solve the model in the complex frequency domain.

[0037] S130: Determine shale gas production data according to the complex frequency domain seepage model.

[0038] By solving the complex frequency domain seepage model, the electronic device can obtain data such as the pressure of the reformed area, the pressure of the unreformed area, and shale gas production. The shale gas production data may include shale gas production at multiple time points.

[0039] S140: Determine shale gas flow seepage simulation results based on the shale gas production data.

[0040] The electronic device can use time as the independent variable and shale gas production as the dependent variable to determine the correlation between shale gas production and time under different permeability decline conditions, and then obtain the shale gas flow simulation results.

[0041] The technical solution of the embodiment of the present invention obtains a seepage model of fluid flow in a target horizontal well and, based on predefined dimensionless variables, non-dimensionalizes the seepage model to obtain a dimensionless seepage model. A complex frequency domain seepage model is then determined based on the dimensionless seepage model using a Laplace transform. Shale gas production data is then determined based on the complex frequency domain seepage model. Finally, shale gas flow simulation results are determined based on the shale gas production data. This technical solution addresses the issue of low production prediction accuracy for multi-stage fractured horizontal wells in shale gas reservoirs. By utilizing a precise mathematical model to simulate the heterogeneous characteristics of hydraulic fractures and the stimulated zone, it accurately describes the shale gas seepage process and thus enables precise and efficient production prediction for multi-stage fractured horizontal wells in shale gas reservoirs.

[0042] Example 2

[0043] Figure 2A This is a flow chart of a shale gas flow simulation method provided in Example 2 of the present invention. This example is based on the above example and is refined. Figure 2A As shown, the method includes:

[0044] S210. Obtain a seepage model of fluid flow in the target horizontal well, wherein the seepage model includes a linear flow model in an unreformed area, a spherical radial flow model in a reformed area, a linear flow model in a reformed area, and a linear flow model in a hydraulic fracture area.

[0045] In this solution, optionally, obtaining a seepage model of fluid flow in a target horizontal well includes:

[0046] Acquiring production information of a target horizontal well, and determining a trilinear flow model of the target horizontal well based on the production information;

[0047] A seepage model of fluid flow in the target horizontal well is determined based on the trilinear flow model, the pre-acquired gas state equation, and the mass balance equation.

[0048] Figure 2B Schematic diagram of the minimum simulation unit of transient linear flow in a multi-stage fractured horizontal well according to the second embodiment of the present invention. Figure 2B As shown, to efficiently simulate the production process of a multi-stage fractured horizontal well, the gas flow during the production process can be linear, with the length and spacing of all fractures set constant to ensure the symmetry of the physical model. The electronic device can determine the minimum simulation unit based on the preset ratio of fracture stages to construct a physical model of the target horizontal well. As can be understood, the reservoir can be divided into hydraulic fracture zones, fractured stimulation zones, and unstimulated zones. Based on the physical model, the heterogeneity, multi-porosity characteristics, and fracture conductivity of the shale gas reservoir can be comprehensively described. The electronic device can construct a physical model of the target horizontal well using a trilinear flow model. Based on this trilinear flow model of the target horizontal well, the interaction between the fractures and the matrix is ​​considered to more accurately depict the mass transfer process between fractures and pores during reservoir seepage.

[0049] The electronic device can construct a seepage model of the fluid flow in the target horizontal well based on the above physical model, the pre-acquired gas state equation and mass balance equation, and factors such as natural fractures, heterogeneity of the reformed area, and hydraulic fractures.

[0050] In a feasible solution, the linear flow model in the unmodified area includes:

[0051]

[0052] p2(0,y)=p i ;

[0053] p2(t,y1)=p f ;

[0054]

[0055] The spherical radial flow model of the transformation area is:

[0056]

[0057] p m (0,r m )=p i ;

[0058] p m (t,R)=p f ;

[0059]

[0060] The linear flow model in the transformation area is:

[0061]

[0062] p f (0,x)=p i ;

[0063]

[0064]

[0065] The linear flow model in the hydraulic fracture area is:

[0066]

[0067] p F (0,y)=p i ;

[0068]

[0069]

[0070] Wherein, ρ2 represents the gas density in the unreformed area, k2 represents the matrix permeability in the unreformed area, p2 represents the gas pressure in the unreformed area, and μ represents the gas viscosity in the unreformed area. represents the matrix porosity of the unmodified area, t represents time, and ρ sc Indicates the gas density under preset standard conditions, V L represents the Langmuir volume, p L represents the Langmuir pressure, p i represents the initial reservoir pressure, y1 represents the length of the reformed area in the y direction, p f represents the fracture pressure in the reformed area, y2 represents the reservoir length in the y direction, r m represents the radius of the spherical matrix, ρ m represents the gas density in the spherical matrix, k m represents the spherical matrix permeability, p m represents the spherical matrix pressure, μ g represents the gas viscosity, represents the porosity of the spherical matrix, ρ f represents the gas density in the reformed area, k f represents the permeability of the reformed area, p f represents the reforming zone pressure, R represents the radius of the spherical matrix, represents the fracture porosity, w F represents the width of the hydraulic fracture, x1 represents the length of the transformation zone in the x direction, ρ F represents the gas density of hydraulic fracture, k F represents the hydraulic fracture permeability, p Frepresents the hydraulic fracture pressure, represents the hydraulic fracture porosity, h represents the reservoir thickness, k F0 represents the permeability at the junction of the hydraulic fracture and the wellbore, q sc Indicates the gas production under preset standard conditions.

[0071] It should be noted that to facilitate the study of the target horizontal well, the electronic equipment can construct a spatial rectangular coordinate system with any point in the target horizontal well space as the origin. The x-direction can be the extension direction of the horizontal wellbore, and the y-direction can be perpendicular to the horizontal wellbore. The preset standard conditions can be a room temperature of 20°C and a pressure of 20 MPa.

[0072] S220. According to predefined dimensionless variables, the linear flow model in the unreformed area, the spherical radial flow model in the reformed area, the linear flow model in the reformed area, and the linear flow model in the hydraulic fracture area are sequentially dimensionlessized to obtain a dimensionless model of the unreformed area, a dimensionless matrix model of the reformed area, a dimensionless fracture system model of the reformed area, and a dimensionless hydraulic fracture system model, respectively.

[0073] The dimensionless variables include gas pseudo-pressure, dimensionless pseudo-pressure, dimensionless time, dimensionless production, dimensionless distance, dimensionless diffusion coefficient and dimensionless permeability.

[0074] The gas pseudo-pressure can be expressed as:

[0075] The dimensionless pseudo-pressure can be expressed as:

[0076] Dimensionless time can be expressed as:

[0077] The dimensionless yield can be expressed as:

[0078] Dimensionless distances can include:

[0079] The dimensionless diffusion coefficient includes:

[0080] Dimensionless permeabilities include:

[0081] Where p represents pressure, represents the pressure variable used for integration, represents the gas viscosity, represents the gas compressibility factor, k F0 represents the permeability of the junction between the hydraulic fracture and the wellbore, h represents the reservoir thickness, T scIndicates the temperature under preset standard conditions, P sc Indicates the pressure under preset standard conditions, q sc represents the gas production under the preset standard conditions, T represents the initial temperature of the reservoir, ψ i represents the initial pseudo-pressure, ψ represents the pseudo-pressure, t represents the time, t D represents dimensionless time, φ F represents the porosity of hydraulic fractures, C g represents the pore compressibility coefficient, μ g represents the gas viscosity, y1 represents the length of the reformed area in the y direction, ψ w represents the pseudo-pressure at the junction of the hydraulic fracture and the wellbore, x D represents the dimensionless length of the reservoir in the x direction, x represents the length of the reservoir in the x direction, y D represents the dimensionless length of the reservoir in the y direction, y represents the length of the reservoir in the y direction, W FD represents the dimensionless hydraulic fracture width, W F represents the width of hydraulic fracture, r mD represents the dimensionless spherical matrix radius, r m represents the radius of the spherical matrix, R represents the radius of the spherical matrix, R D represents the dimensionless spherical matrix radius, η mD represents the dimensionless pressure conductivity of the spherical matrix, k m represents the permeability of the spherical matrix, φ m represents the porosity of the spherical matrix, C tm represents the comprehensive compressibility coefficient of the spherical matrix, η 2D represents the dimensionless pressure conductivity of the unreformed area, k2 represents the matrix permeability of the unreformed area, C t2 represents the comprehensive compression coefficient of the unrenovated area, k FD represents the dimensionless permeability of hydraulic fractures, k F represents the hydraulic fracture permeability, k 2D represents the dimensionless permeability of the unreconstructed area, k f0 represents the permeability of the junction between the reformed area and the hydraulic fracture, k fD represents the dimensionless permeability of the fractures in the reformed area, k f represents the fracture permeability of the reformed area, Λ f Represents a custom dimensionless quantity, k fAD represents the dimensionless average permeability of the fractures in the reformed area, k fA represents the average permeability of the fractures in the transformation area, k f (x) represents the fracture permeability distribution function of the reformed area, x1 represents the length of the reformed area in the x direction, k FAD represents the dimensionless average permeability of hydraulic fractures, k FA represents the average permeability of hydraulic fractures, k F(y) represents the hydraulic fracture permeability distribution function.

[0082] The dimensionless model of the unmodified area may include:

[0083]

[0084] ψ 2D (0,y D )=0;

[0085] ψ 2D (t D ,1)=ψ fD ;

[0086]

[0087] The dimensionless model of the matrix of the reformed area may include:

[0088]

[0089] ψ mD (0,r mD )=0;

[0090] ψ mD (t D ,1)=ψ fD ;

[0091]

[0092] The dimensionless model of the fracture system in the transformation area includes:

[0093]

[0094] ψ fD (0,x D )=0;

[0095]

[0096]

[0097] The dimensionless model of the hydraulic fracture system includes:

[0098]

[0099] ψ FD (0,y D )=0;

[0100]

[0101]

[0102] Among them, ψ2D represents the dimensionless pseudo-pressure in the unreformed area, ψ fD represents the dimensionless pseudo-pressure of the cracks in the reformed area, y D represents the dimensionless length of the reservoir in the y direction, η2 represents the pressure conductivity of the unreformed area, t D represents dimensionless time, y 2D represents the dimensionless length of the reservoir in the y direction, r mD represents the dimensionless radius of the spherical matrix, ψ mD represents the dimensionless pseudo-pressure of the spherical matrix, η m represents the spherical matrix pressure conductivity, R D represents the dimensionless radius of the spherical matrix, k fD (x D ) represents the dimensionless permeability distribution function of the fractures in the reformed area, x D represents the dimensionless length of the reservoir in the x direction, k 2D represents the dimensionless permeability of the unreconstructed area, k mD represents the dimensionless permeability of the spherical matrix, k fAD represents the dimensionless average permeability of the fractures in the reformed area, η fD It represents the dimensionless pressure conductivity coefficient of the transformation area, W FD represents the dimensionless hydraulic fracture width, ψ FD represents the dimensionless pseudo-pressure of hydraulic fracture, x 1D represents the dimensionless length of the transformation area in the x direction, k FD (y D ) represents the dimensionless permeability distribution function of hydraulic fractures.

[0103] S230. Performing Laplace transforms on the dimensionless model of the unreconstructed area, the dimensionless matrix model of the reconstructed area, the dimensionless fracture system model of the reconstructed area, and the dimensionless hydraulic fracture system model in sequence to obtain a complex frequency domain model of the unreconstructed area, a complex frequency domain model of the matrix of the reconstructed area, a complex frequency domain model of the fractures of the reconstructed area, and a complex frequency domain model of the hydraulic fractures, respectively.

[0104] It can be understood that the complex frequency domain model of the unmodified area includes:

[0105]

[0106]

[0107]

[0108] The complex frequency domain model of the transformation area matrix includes:

[0109]

[0110]

[0111]

[0112] The complex frequency domain model of the fracture in the transformation area includes:

[0113]

[0114]

[0115] The hydraulic fracture complex frequency domain model includes:

[0116]

[0117]

[0118]

[0119] in, represents the dimensionless pseudo-pressure of the unmodified area in Laplace space, s represents the complex frequency domain operator, represents the dimensionless pseudo-pressure of the crack in the reformed area in Laplace space, represents the dimensionless pseudo-pressure of the spherical matrix in Laplace space, represents the dimensionless pseudo-pressure of the hydraulic fracture in Laplace space, η IIm It represents the dimensionless pressure conductivity of the spherical matrix.

[0120] S240: Determine a first pressure solution according to the complex frequency domain model of the unmodified area.

[0121] By solving the complex frequency domain model of the unmodified area, the electronic device can obtain the first pressure solution, namely

[0122] S250 : Determine a second pressure solution according to the complex frequency domain model of the matrix in the modified area, the complex frequency domain model of the fracture in the modified area, and the first pressure solution.

[0123] In this solution, optionally, determining the second pressure solution based on the complex frequency domain model of the matrix in the modified area, the complex frequency domain model of the fracture in the modified area, and the first pressure solution includes:

[0124] Determining a third pressure solution based on the complex frequency domain model of the matrix of the transformation area and the dual medium model;

[0125] A second pressure solution is determined based on the complex frequency domain model of the fracture in the reformed area, the first pressure solution, and the third pressure solution.

[0126] Based on the dual medium model, the complex frequency domain model of the reformed area matrix can be solved to obtain the third pressure solution, namely In getting and Afterwards, as well as Substitute it into the complex frequency domain model of the fracture in the transformation area and solve the complex frequency domain model of the fracture in the transformation area to obtain the second pressure solution, that is,

[0127]

[0128] in,

[0129]

[0130]

[0131]

[0132]

[0133] ∈ represents the infinitesimal quantity required by the perturbation principle.

[0134] S260: Determine a production solution based on the hydraulic fracture complex frequency domain model and the second pressure solution.

[0135] It is understandable that electronic equipment can be used according to Calculating Data Items in Complex Frequency Domain Models of Hydraulic Fractures Substituting the calculation results into the hydraulic fracture complex frequency domain model, we can get In getting Afterwards, the electronic equipment can produce the dimensionless production in the complex frequency domain according to the bottom hole pressure. The production solution can include the production rate solution under constant bottom hole pressure in the complex frequency domain and the degradation solution under constant bottom hole pressure.

[0136] S270. Based on a preset numerical inversion model, invert the production solution from the complex frequency domain to the time domain to determine shale gas production data.

[0137] According to the production rate solution under constant bottom hole pressure in the complex frequency domain and the degradation under bottom hole pressure under constant production, the time domain inversion under production rate or transient bottom hole pressure is performed based on the Stehfest inversion algorithm to obtain the time domain inversion result, namely: in, i represents the summation variable, N represents the summation upper limit, and k represents the summation variable.

[0138] According to the physical model of the target horizontal well, the hydraulic fractures can have the same properties. The target horizontal well gas production rate should take all fractures into account. The gas production rate data can be expressed as Q D =a×n F ×q D ; Where a represents the inverse of the preset ratio of the crack stage, n F Indicates the number of hydraulic fractures. Shale gas production data can be obtained by performing dimensionless inverse calculation based on gas production rate data.

[0139] S280: Determine shale gas flow seepage simulation results based on the shale gas production data.

[0140] In a specific example, in response to the continuous permeability deterioration in the reformed area and fracture area after fracturing operations, three different types of permeability decline functions can be set to finely characterize the heterogeneous characteristics of the fracture conductivity of shale gas reservoirs and compare and verify them with the predicted results output by the prediction model in the reservoir simulation software.

[0141] Type A:k f0 =0.1×10 -3 μm 2 , k F0 =100×10 -3 μm 2 ;

[0142] Type B:k fD =1-0.865x D , k FD =1-0.865y D , k f0 =0.1×10 -3 μm 2 , k F0 =100×10 -3 μm 2 ;

[0143] Type C:k fD =1.5-0.5e xD , k FD =1.5-0.5e yD , k f0 =0.1×10 -3 μm 2 , k F0 =100×10 -3 μm 2 .

[0144] Figure 2C FIG. 1 is a schematic diagram of shale gas flow simulation results according to the second embodiment of the present invention. Figure 2CAs shown in the figure, the horizontal axis of the three groups of curves indicates time in days, and the vertical axis indicates shale gas production in 10 4 m 3 The linear curve represents the prediction result output by the prediction model in the reservoir simulation software, and the circular curve represents the production prediction result obtained by this scheme. In the early stage of production, the production prediction value of this scheme is slightly higher than the prediction result output by the prediction model in the reservoir simulation software. As time goes by, the two curves quickly tend to fit, and the relative error is always within 5%. The numerical simulation method of this scheme can effectively capture the trend of gas reservoir production changes and achieve good matching results. This scheme is accurate and reliable in describing the fracturing production flow process of heterogeneous shale gas reservoirs.

[0145] The technical solution of the embodiment of the present invention has advantages over the existing technology mainly in the following three aspects:

[0146] (1) Realize the simultaneous characterization of hydraulic fractures and SRV regional heterogeneity to improve model accuracy.

[0147] The width of the main fractures and proppant density in hydraulically fractured shale reservoirs decrease with distance from the wellbore, and the density of the secondary fracture network in the SRV zone also decreases with distance. However, traditional simulation methods often ignore the non-uniform permeability distribution of the main fractures and SRV zones, making it difficult to characterize the impact of permeability decay with distance on shale gas well production. The shale gas seepage model proposed in this proposal innovatively utilizes a perturbation method to simultaneously characterize the permeability variations in both the main fractures and the SRV zone, and derives analytical solutions for bottomhole pressure and production in this scenario. This provides a more accurate computational tool for seepage simulation and production prediction in shale gas reservoir development.

[0148] (2) A seepage model suitable for different permeability change functions is established, which has strong versatility and adaptability.

[0149] Traditional simulation methods often assume abrupt permeability changes within the reconstructed zone or restrict the mathematical function form of permeability changes, failing to accurately capture complex permeability variation patterns. In contrast, the approach in this proposal allows the use of arbitrary functions to represent permeability distributions in reservoir simulations, making the model applicable to a wide range of reservoir conditions. Using arbitrary functions to represent permeability changes more accurately reflects the continuous permeability variations in actual reservoirs, thereby improving the accuracy of simulation results. Users can select the appropriate function form based on specific problems and actual data and embed it into the model for simulation and analysis. This flexibility in customizing functions effectively improves the adaptability and versatility of the model.

[0150] (3) Rapid prediction of shale gas reservoir pressure distribution and production is achieved through analytical models.

[0151] Due to the complexity of simulating heterogeneous shale gas reservoirs, traditional simulation methods typically use numerical simulation techniques to solve gas seepage dynamics. However, numerical simulation requires discretization of the geological model, which is inefficient and time-consuming. This solution establishes an analytical model of gas seepage in heterogeneous shale gas reservoirs and effectively introduces various complex physical processes (such as gas adsorption and desorption) into the mathematical model. Combining mathematical formulas and analytical solutions, it calculates shale gas pressure distribution and gas production rate, avoiding complex numerical calculations and iterative processes, thereby achieving prediction results in a shorter time.

[0152] Example 3

[0153] Figure 3 This is a schematic diagram of the structure of a shale gas flow simulation device provided in Example 3 of the present invention. Figure 3 As shown, the device includes:

[0154] A seepage model acquisition module 310 is used to acquire a seepage model of fluid flow in a target horizontal well, and to convert the seepage model into a dimensionless model according to predefined dimensionless variables to obtain a dimensionless seepage model;

[0155] A complex frequency domain model determination module 320 is configured to determine a complex frequency domain percolation model based on the dimensionless percolation model and Laplace transform;

[0156] A gas production data determination module 330 is used to determine shale gas production data based on a complex frequency domain seepage model;

[0157] The simulation result determination module 340 is used to determine the shale gas flow simulation result based on the shale gas production data.

[0158] In this solution, optionally, the seepage model includes a linear flow model in an unreconstructed area, a spherical radial flow model in a reconstructed area, a linear flow model in a reconstructed area, and a linear flow model in a hydraulic fracture area;

[0159] The seepage model acquisition module 310 is specifically used to:

[0160] According to predefined dimensionless variables, the linear flow model in the unreformed area, the spherical radial flow model in the reformed area, the linear flow model in the reformed area, and the linear flow model in the hydraulic fracture area are sequentially dimensionlessized to obtain a dimensionless model of the unreformed area, a dimensionless matrix model of the reformed area, a dimensionless fracture system model of the reformed area, and a dimensionless hydraulic fracture system model, respectively. The dimensionless variables include gas pseudo-pressure, dimensionless pseudo-pressure, dimensionless time, dimensionless production, dimensionless distance, dimensionless diffusion coefficient, and dimensionless permeability.

[0161] Based on the above solution, optionally, the complex frequency domain model determination module 320 is specifically configured to:

[0162] Laplace transforms are performed on the dimensionless model of the unreconstructed area, the dimensionless model of the matrix of the reconstructed area, the dimensionless model of the fracture system of the reconstructed area, and the dimensionless model of the hydraulic fracture system in sequence to obtain the complex frequency domain model of the unreconstructed area, the complex frequency domain model of the matrix of the reconstructed area, the complex frequency domain model of the fracture of the reconstructed area, and the complex frequency domain model of the hydraulic fracture, respectively.

[0163] In a feasible solution, the gas production data determination module 330 includes:

[0164] a first pressure solution determining unit, configured to determine a first pressure solution based on the complex frequency domain model of the unmodified area;

[0165] a second pressure solution determining unit, configured to determine a second pressure solution based on the matrix complex frequency domain model of the reformed area, the fracture complex frequency domain model of the reformed area, and the first pressure solution;

[0166] a production solution determining unit, configured to determine a production solution based on the hydraulic fracture complex frequency domain model and the second pressure solution;

[0167] The production data determination unit is used to invert the production solution from the complex frequency domain to the time domain based on a preset numerical inversion model to determine the shale gas production data.

[0168] Based on the above solution, optionally, the second pressure solution determining unit is specifically configured to:

[0169] Determining a third pressure solution based on the complex frequency domain model of the matrix of the transformation area and the dual medium model;

[0170] A second pressure solution is determined based on the complex frequency domain model of the fracture in the reformed area, the first pressure solution, and the third pressure solution.

[0171] In this embodiment, optionally, the seepage model acquisition module 310 is further configured to:

[0172] Acquiring production information of a target horizontal well, and determining a trilinear flow model of the target horizontal well based on the production information;

[0173] A seepage model of fluid flow in the target horizontal well is determined based on the trilinear flow model, the pre-acquired gas state equation, and the mass balance equation.

[0174] In a preferred embodiment, the linear flow model in the unmodified area includes:

[0175]

[0176] p2(0,y)=p i ;

[0177] p2(t,y1)=p f ;

[0178]

[0179] The spherical radial flow model of the transformation area is:

[0180]

[0181] p m (0,r m )=p i ;

[0182] p m (t,R)=p f ;

[0183]

[0184] The linear flow model in the transformation area is:

[0185]

[0186] p f (0,x)=p i ;

[0187]

[0188] The linear flow model in the hydraulic fracture area is:

[0189]

[0190] p F (0,y)=p i ;

[0191]

[0192]

[0193] Where ρ2 represents, k2 represents the matrix permeability of the unreformed area, p2 represents the permeability of the unreformed area, μ represents the gas viscosity, represents the matrix porosity of the unmodified area, t represents time, and ρ sc Indicates the gas density under preset standard conditions, V L represents the Langmuir volume, p L represents the Langmuir pressure, p i represents the initial reservoir pressure, y1 represents the length of the reformed area in the y direction, p frepresents the fracture permeability of the reformed area, y2 represents the reservoir length in the y direction, r m represents the radius of the spherical matrix, ρ m represents the spherical matrix gas density, k m represents the spherical matrix permeability, p m represents the spherical matrix pressure, μ g represents the gas viscosity, represents the porosity of the spherical matrix, ρ f represents the gas density in the reformed area, k f represents the fracture permeability of the reformed area, p f represents the fracture pressure in the reformed area, R represents the radius of the spherical matrix, represents the fracture porosity, w F represents the width of the hydraulic fracture, x1 represents the length of the transformation zone in the x direction, ρ F represents the gas density of hydraulic fracture, k F represents the hydraulic fracture permeability, p F represents the hydraulic fracture pressure, represents the porosity of hydraulic fractures, h represents the reservoir thickness, y1 represents the length of hydraulic fractures in the y direction, k F0 represents the permeability of the junction between the hydraulic fracture and the wellbore, q sc Indicates the gas production under preset standard conditions.

[0194] The shale gas flow seepage simulation device provided in the embodiment of the present invention can execute the shale gas flow seepage simulation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0195] Example 4

[0196] Figure 4 A schematic diagram of the structure of an electronic device 410 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0197] like Figure 4As shown, the electronic device 410 includes at least one processor 411, and a memory connected to the at least one processor 411, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc., wherein the memory stores a computer program that can be executed by the at least one processor, and the processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 to the random access memory (RAM) 413. Various programs and data required for the operation of the electronic device 410 can also be stored in the RAM 413. The processor 411, ROM 412 and RAM 413 are connected to each other via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0198] Multiple components in electronic device 410 are connected to I / O interface 415, including an input unit 416, such as a keyboard, mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a magnetic disk, optical disk, etc.; and a communication unit 419, such as a network card, modem, wireless communication transceiver, etc. The communication unit 419 allows electronic device 410 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0199] Processor 411 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processors, controllers, microcontrollers, etc. Processor 411 executes the various methods and processes described above, such as the shale gas flow simulation method.

[0200] In some embodiments, the shale gas flow simulation method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the shale gas flow simulation method described above can be performed. Alternatively, in other embodiments, processor 411 can be configured to execute the shale gas flow simulation method in any other appropriate manner (e.g., via firmware).

[0201] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0202] Computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable shale gas flow simulation device, such that, when executed by the processor, the computer programs implement the functions / operations specified in the flowcharts and / or block diagrams. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0203] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0204] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0205] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0206] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0207] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0208] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A shale gas flow seepage simulation method, characterized in that: The method comprises: Obtaining a seepage model of fluid flow in a target horizontal well, and converting the seepage model into a dimensionless model according to predefined dimensionless variables to obtain a dimensionless seepage model; According to the dimensionless percolation model, a complex frequency domain percolation model is determined based on Laplace transform; determining shale gas production data according to the complex frequency domain seepage model; The shale gas flow seepage simulation results are determined based on the shale gas production data.

2. The method according to claim 1, characterized in that The seepage model includes a linear flow model in the unreconstructed area, a spherical radial flow model in the reconstructed area, a linear flow model in the reconstructed area, and a linear flow model in the hydraulic fracture area; The method of converting the percolation model into a dimensionless model according to the predefined dimensionless variables to obtain a dimensionless percolation model includes: According to predefined dimensionless variables, the linear flow model in the unreformed area, the spherical radial flow model in the reformed area, the linear flow model in the reformed area, and the linear flow model in the hydraulic fracture area are sequentially dimensionlessized to obtain a dimensionless model of the unreformed area, a dimensionless matrix model of the reformed area, a dimensionless fracture system model of the reformed area, and a dimensionless hydraulic fracture system model, respectively. The dimensionless variables include gas pseudo-pressure, dimensionless pseudo-pressure, dimensionless time, dimensionless production, dimensionless distance, dimensionless diffusion coefficient, and dimensionless permeability.

3. The method according to claim 2, characterized in that Determining a complex frequency domain percolation model based on the dimensionless percolation model and Laplace transform includes: Laplace transforms are performed on the dimensionless model of the unreconstructed area, the dimensionless model of the matrix of the reconstructed area, the dimensionless model of the fracture system of the reconstructed area, and the dimensionless model of the hydraulic fracture system in sequence to obtain the complex frequency domain model of the unreconstructed area, the complex frequency domain model of the matrix of the reconstructed area, the complex frequency domain model of the fracture of the reconstructed area, and the complex frequency domain model of the hydraulic fracture, respectively.

4. The method according to claim 3, characterized in that Determining shale gas production data according to the complex frequency domain seepage model includes: determining a first pressure solution based on the complex frequency domain model of the unmodified area; determining a second pressure solution based on the matrix complex frequency domain model of the reformed area, the fracture complex frequency domain model of the reformed area, and the first pressure solution; determining a production solution based on the hydraulic fracture complex frequency domain model and the second pressure solution; Based on a preset numerical inversion model, the production solution is inverted from the complex frequency domain to the time domain to determine the shale gas production data.

5. The method according to claim 4, characterized in that Determining a second pressure solution according to the complex frequency domain model of the matrix in the reformed area, the complex frequency domain model of the fracture in the reformed area, and the first pressure solution includes: Determining a third pressure solution based on the complex frequency domain model of the matrix of the transformation area and the dual medium model; A second pressure solution is determined based on the complex frequency domain model of the fracture in the reformed area, the first pressure solution, and the third pressure solution.

6. The method according to claim 1, characterized in that The method of obtaining a seepage model for fluid flow in a target horizontal well includes: Acquiring production information of a target horizontal well, and determining a trilinear flow model of the target horizontal well based on the production information; A seepage model of fluid flow in the target horizontal well is determined based on the trilinear flow model, the pre-acquired gas state equation, and the mass balance equation.

7. The method according to claim 2, characterized in that The linear flow model in the unmodified area includes: p2(0,y)=p i ; p2(t,y1)=p f ; The spherical radial flow model of the transformation area is: p m (0,r m )=p i ; p m (t,R)=p f ; The linear flow model in the transformation area is: p f (0,x)=p i ; The linear flow model in the hydraulic fracture area is: p F (0,y)=p i ; Wherein, ρ2 represents the gas density in the unreformed area, k2 represents the matrix permeability in the unreformed area, p2 represents the gas pressure in the unreformed area, and μ represents the gas viscosity in the unreformed area. represents the matrix porosity of the unmodified area, t represents time, and ρ sc Indicates the gas density under preset standard conditions, V L represents the Langmuir volume, p L represents the Langmuir pressure, p i represents the initial reservoir pressure, y1 represents the length of the reformed area in the y direction, p f represents the fracture pressure in the reformed area, y2 represents the reservoir length in the y direction, r m represents the radius of the spherical matrix, ρ m represents the gas density in the spherical matrix, k m represents the spherical matrix permeability, p m represents the spherical matrix pressure, μ g represents the gas viscosity, represents the porosity of the spherical matrix, ρ f represents the gas density in the reformed area, k f represents the permeability of the reformed area, p f represents the reforming zone pressure, R represents the radius of the spherical matrix, represents the fracture porosity, w F represents the width of the hydraulic fracture, x1 represents the length of the transformation zone in the x direction, ρ F represents the gas density of hydraulic fracture, k F represents the hydraulic fracture permeability, p F represents the hydraulic fracture pressure, represents the hydraulic fracture porosity, h represents the reservoir thickness, k F0 represents the permeability at the junction of the hydraulic fracture and the wellbore, q sc Indicates the gas production under preset standard conditions.

8. A shale gas flow simulation device, characterized in that: include: A seepage model acquisition module is used to obtain a seepage model of fluid flow in a target horizontal well, and to convert the seepage model into a dimensionless model according to predefined dimensionless variables to obtain a dimensionless seepage model; A complex frequency domain model determination module, configured to determine a complex frequency domain percolation model based on the dimensionless percolation model and Laplace transform; A gas production data determination module is used to determine shale gas production data based on a complex frequency domain seepage model; The simulation result determination module is used to determine the shale gas flow seepage simulation result based on the shale gas production data.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the shale gas flow seepage simulation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the shale gas flow seepage simulation method according to any one of claims 1 to 7 when executed.

Images