Method, device and equipment for determining reservoir fracture conductivity

Abstract

The application discloses a method, device and equipment for determining reservoir fracture conductivity, wherein the method comprises the following steps: acquiring fracture data of a target reservoir; determining a fracture width distribution result of a support fracture in the target reservoir based on the fracture data, wherein the fracture width distribution result comprises a continuous distribution result of a fracture width of the support fracture along a fracture length and a fracture height direction of the support fracture; and determining a conductivity distribution of the target reservoir based on the fracture width distribution result and a pre-determined mapping relationship between the fracture width and the conductivity, wherein the conductivity distribution represents a distribution of the conductivity of the support fracture of the target reservoir along the fracture length and the fracture height direction of the support fracture. The application can obtain a more accurate and reliable conductivity distribution, and can predict the conductivity of the support fracture in multiple dimensions, so that the prediction of the conductivity distribution is more comprehensive.

Description

Technical Field

[0001] This application relates to the field of tight sandstone reservoir stimulation technology, and in particular to a method, apparatus and equipment for determining the conductivity of reservoir fractures. Background Technology

[0002] Hydraulic fracturing is a key technology for the efficient development of unconventional reservoirs. It involves pumping a viscous fluid into the well from the surface, fracturing the reservoir under high pressure at the bottom of the well, and creating hydraulically dynamic fractures. The fluid then carries proppant into the fractures, creating support within the fractures and preventing complete closure. This establishes efficient flow channels for oil and gas, leading to high production. Therefore, the size and flow performance of the hydraulically dynamic fractures and the propped fractures are crucial to the effectiveness of fracturing.

[0003] To better determine the conductivity of artificial fractures, current methods employ proppant fracturing to assess this conductivity. These methods primarily rely on experimental, numerical modeling, and statistical approaches, achieving a certain degree of predictability. However, current methods suffer from limitations such as small scale, insufficient dimensionality, significant discrepancies with actual artificial fractures, and inaccurate results. Consequently, they fail to construct a reasonable conductivity distribution profile of artificial fractures at the field scale, thus hindering their support for fracturing scheme design and oil and gas well production enhancement. Summary of the Invention

[0004] The purpose of this application is to provide a method, apparatus, and device for determining the conductivity of reservoir fractures, so as to solve the problem of inaccurate conductivity determination results.

[0005] To address the aforementioned technical problems, the first aspect of this specification provides a method for determining the conductivity of reservoir fractures, comprising:

[0006] Acquire fracture data of the target reservoir;

[0007] Based on the fracture data, the fracture width distribution of the supporting fractures in the target reservoir is determined, wherein the fracture width distribution includes the continuous distribution of the fracture width of the supporting fractures along the fracture length and fracture height directions of the supporting fractures.

[0008] Based on the fracture width distribution results and the predetermined mapping relationship between fracture width and conductivity, the conductivity distribution of the target reservoir is determined, wherein the conductivity distribution characterizes the distribution of the conductivity of the supported fractures of the target reservoir along the fracture length and fracture height directions.

[0009] In some embodiments, acquiring fracture data of the target reservoir includes:

[0010] Obtain core profiles of the target reservoir;

[0011] Collect dynamic fracture data of the core column profile, including fracture length data, fracture width data, and fracture height data.

[0012] In some embodiments, determining the fracture width distribution of the supported fractures in the target reservoir based on the fracture data includes:

[0013] Based on the fracture length and fracture height data of the dynamic fracture, the filtration loss coefficient of the fracturing fluid in the dynamic fracture of the target reservoir is determined.

[0014] Based on the suture height data, the suture length data, the suture width data, and the filtration coefficient, the suture width distribution result is determined.

[0015] In some embodiments, the filtration coefficient is determined by the following formula:

[0016]

[0017] Where L represents the fracture half-length of the dynamic fracture, q represents the fracturing fluid velocity, G represents the shear modulus of the target reservoir, ν represents the Poisson's ratio of the target reservoir, and H f ψ represents the fracture height of the dynamic fracture, μ represents the viscosity of the fracturing fluid, and ψ represents the filtration loss coefficient of the fracturing fluid.

[0018] In some embodiments, determining the suture width distribution result based on the suture height data, the suture length data, the suture width data, and the filtration coefficient includes:

[0019] Based on the fracture height data, fracture length data, fracture width data, the mapping relationship between fracture length and fracture height in the dynamic fractures of the target reservoir, and the mapping relationship between fracture width and fracture length in the dynamic fractures of the target reservoir, the first fracture width distribution of the dynamic fractures in the target reservoir along the fracture height direction and the fracture length direction is determined.

[0020] Based on the aforementioned filtration coefficient, the mapping relationship between fracture width and fracture height, and the mapping relationship between fracture width and fracturing time, the second fracture width distribution of the longitudinal section of the fracture at the fracture opening in the target reservoir is determined.

[0021] The seam width distribution result is determined based on the first seam width distribution and the second seam width distribution.

[0022] In some embodiments, the second seam width distribution data is determined by the following formula:

[0023]

[0024]

[0025] Where W(0,t) represents the center fracture width at the fracture opening when the fracturing operation time is t, t represents the fracturing operation time, q represents the fracturing fluid velocity, G represents the shear modulus of the target reservoir, ν represents the Poisson's ratio of the target reservoir, and H f ψ represents the fracture height of the dynamic fracture, μ represents the viscosity of the fracturing fluid, ψ represents the filtration loss coefficient of the fracturing fluid, x represents the abscissa of the fracture on the longitudinal section with the fracture center as the origin, and y represents the ordinate of the fracture on the longitudinal section with the fracture center as the origin.

[0026] In some embodiments, before determining the conductivity distribution of the target reservoir based on the fracture width distribution results and a predetermined mapping relationship between fracture width and conductivity, the process includes:

[0027] Determine the target equilibrium flow rate of the proppant that supports the fractures in the target reservoir;

[0028] The equilibrium height of the target reservoir is determined based on the mapping relationship between the equilibrium flow rate and equilibrium height of the proppant and the target equilibrium flow rate.

[0029] The conductivity of the supporting fractures in the target reservoir above the equilibrium height is determined to be zero.

[0030] The second aspect of this specification provides an apparatus for determining the conductivity of reservoir fractures, comprising:

[0031] The data acquisition module is used to acquire fracture data of the target reservoir;

[0032] The fracture width determination module is used to determine the fracture width distribution result of the supporting fracture in the target reservoir based on the fracture data, wherein the fracture width distribution result includes the continuous distribution result of the fracture width of the supporting fracture along the fracture length and fracture height directions of the supporting fracture;

[0033] The conductivity determination module is used to determine the conductivity distribution of the target reservoir based on the fracture width distribution results and a pre-determined mapping relationship between fracture width and conductivity, wherein the conductivity distribution characterizes the distribution of the conductivity of the supported fractures of the target reservoir along the fracture length and fracture height directions.

[0034] A third aspect of this specification provides an electronic device, comprising: a memory and a processor, wherein the processor and the memory are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to implement the steps of the method described in any of the first aspects.

[0035] A fourth aspect of this specification provides a computer storage medium storing computer program instructions that, when executed, implement the steps of the method described in any of the first aspects.

[0036] The method for determining the conductivity of reservoir fractures provided in this specification involves acquiring fracture data of the target reservoir and, based on this data, determining the continuous fracture width distribution of the supported fractures along the fracture length and height directions. Then, based on the fracture width distribution and the simulation of the mapping relationship between fracture width and conductivity data obtained experimentally, the conductivity distribution of the target reservoir can be determined. The conductivity distribution characterizes the distribution of the conductivity of the supported fractures in the target reservoir along the fracture length and height directions. This application, through measured fracture data, can more accurately determine the width distribution of the supported fractures in the target reservoir, providing a foundation for obtaining a true and reliable conductivity distribution. Furthermore, this application also simulates the mapping relationship between fracture width and conductivity using experimental data, resulting in a more accurate conductivity distribution. In addition, by determining the width distribution of the supported fractures in the fracture length and height directions, this application can predict the conductivity of the supported fractures in multiple dimensions, leading to a more comprehensive prediction of the conductivity distribution. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0038] Figure 1 The diagram shown is a flowchart illustrating a method for determining the conductivity of reservoir fractures according to an embodiment of this application.

[0039] Figure 2 The diagram shown is a flowchart illustrating a method for determining seam width distribution according to an embodiment of this application.

[0040] Figure 3 The diagram shown is a schematic representation of a dynamic crack according to an embodiment of this application.

[0041] Figure 4 The diagram shown is a flowchart illustrating another method for determining the conductivity of reservoir fractures provided in an embodiment of this application.

[0042] Figure 5 The diagram shown is a schematic representation of a well location according to an embodiment of this application.

[0043] Figure 6 The figure shown is a schematic diagram of the mapping relationship between crack width and crack length provided in an embodiment of this application;

[0044] Figure 7 The diagram shown is a schematic representation of the linear relationship between slit width and flow guiding capacity provided in an embodiment of this application.

[0045] Figure 8 The diagram shown is a schematic representation of a flow-guiding capacity distribution provided in an embodiment of this application.

[0046] Figure 9 The diagram shown is a schematic diagram of the program modules of a device for determining the conductivity of reservoir fractures according to an embodiment of this application;

[0047] Figure 10 The diagram shown is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0048] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0049] As mentioned earlier, the size and flow performance of dynamic fractures and propped fractures are crucial to the effectiveness of fracturing. Longer propped fractures, higher propped fractures, and greater propped fracture conductivity result in greater post-fracturing oil and gas production, reflecting a better fracturing effect. Because reservoirs are deeply buried underground, artificial fractures are not directly visible, making the determination of their length, width, height, and conductivity quite limited. Currently, the common approach is to deploy equipment in the surface wellbore and monitor the changes and morphology of artificial fractures using changes in signals such as acoustic waves, electromagnetic waves, and temperature during fracturing. Methods such as microseismic monitoring, wide-area electromagnetic methods, and adjacent-well fiber optic monitoring have, to some extent, achieved the ability to measure changes in the length and height of artificial fractures and have proposed concepts similar to reservoir stimulation volume to quantify artificial fractures. However, these methods have inherent errors, mainly due to reservoir heterogeneity, signal propagation strength, and the operating principles of the equipment, leading to significant discrepancies between the determined results and actual values. Meanwhile, this type of method only identifies artificial dynamic fractures and cannot identify supporting fractures that truly contribute to production. Therefore, it is very necessary to better analyze and identify artificial dynamic fractures and supporting fractures. The results of this analysis will optimize the design of strong support fracturing schemes and further improve the production efficiency of oil and gas wells.

[0050] To better determine the conductivity of artificial fractures, existing methods using sand fracturing have achieved a certain degree of prediction of the conductivity of artificial fractures from experimental, numerical modeling, and mathematical statistics perspectives. However, these methods suffer from problems such as small scale of conductivity determination, insufficient dimensionality, significant differences from actual artificial fractures, and inaccurate results. Consequently, they cannot achieve a reasonable construction of the conductivity distribution profile of artificial fractures at the field scale, and their support for fracturing scheme design and oil and gas well production improvement is weak.

[0051] Considering that existing methods for determining conductivity rely solely on theoretical calculations to determine the width distribution of supporting fractures and have limited predictive dimensions for conductivity distribution, this application proposes a method for determining multidimensional conductivity distribution based on measured fracture data from reservoirs.

[0052] Based on the above ideas, this application provides a method for determining the conductivity of reservoir fractures. This method involves acquiring fracture data of the target reservoir and, based on the fracture data, determining the continuous fracture width distribution of the supporting fractures in the target reservoir along the fracture length and height directions. Then, based on the fracture width distribution and the mapping relationship between fracture width and conductivity determined by simulation using experimentally obtained fracture width data and conductivity data of the supporting fractures, the conductivity distribution of the target reservoir is determined. The conductivity distribution characterizes the distribution of the conductivity of the supporting fractures in the target reservoir along the fracture length and height directions.

[0053] This application, through measured fracture data, can more accurately determine the width distribution of supported fractures in the target reservoir, providing a foundation for obtaining a true and reliable conductivity distribution. Furthermore, this application also simulates the mapping relationship between fracture width and conductivity using experimental data, yielding a more accurate conductivity distribution. In addition, this application determines the width distribution of supported fractures in the fracture length and height directions, enabling prediction of the conductivity of supported fractures in multiple dimensions, resulting in a more comprehensive prediction of the conductivity distribution.

[0054] It is understood that the methods provided in this application can be applied to electronic devices, which can refer to electronic devices with data computing, processing, and storage capabilities. These electronic devices can be terminals such as PCs (Personal Computers), tablets, smartphones, wearable devices, and intelligent robots; they can also be servers. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0055] The method for determining the conductivity of reservoir fractures provided in the embodiments of this application will be described below with reference to the accompanying drawings.

[0056] Figure 1 The diagram shown is a flowchart illustrating a method for determining the conductivity of reservoir fractures according to an embodiment of this application. Figure 1 As shown, the method may include:

[0057] S101: Obtain fracture data of the target reservoir.

[0058] It is understandable that, since it is impossible to collect fracture data of the propped fractures in the target reservoir, fracture data of the dynamic fractures in the target reservoir can be collected to determine the fracture width distribution of the propped fractures. That is, the fracture data obtained in step S101 is the fracture data of the dynamic fractures in the target reservoir. The fracture data may include the geometric dimensions of the dynamic fractures.

[0059] In some embodiments, acquiring fracture data of the target reservoir includes: acquiring a core column profile of the target reservoir; and collecting dynamic fracture data of the core column profile, wherein the fracture data includes fracture length data, fracture width data, and fracture height data.

[0060] In some embodiments, core profiles can be obtained in the following ways:

[0061] (1) Select a horizontal well corresponding to the target reservoir for hydraulic fracturing, and ensure that the horizontal section of the wellbore trajectory is perpendicular to the direction of the maximum horizontal principal stress. After hydraulic fracturing is completed, collect relevant data during the real-time hydraulic fracturing process, which may include engineering geological parameters (such as the well section, Young's modulus, Poisson's ratio, shear modulus, minimum horizontal principal stress, etc.) and construction parameters (such as construction time, construction flow rate, fracturing fluid viscosity, etc.).

[0062] (2) Drill a high-angle well within 50 to 200 m of the horizontal section of the horizontal well for core sampling to preserve the shape. Take out the core from the range of 50 to 200 m of the horizontal well. The core length can be determined based on the actual situation.

[0063] (3) The core column obtained in the previous step is divided along the direction perpendicular to the cross section of the core, and the cross section is scanned by electron microscopy to obtain a core column cross section containing dynamic cracks.

[0064] Furthermore, in some embodiments, the number of dynamic fractures can be marked on the core column profile, and the lateral and longitudinal distances from each depth of the dynamic fractures to the horizontal wellbore can be measured based on the relative positions of the wellbore trajectories of highly deviated and horizontal wells. The fracture length data can be obtained based on the lateral distance, and the fracture height data can be obtained based on the longitudinal distance.

[0065] S102: Based on the fracture data, determine the fracture width distribution of the supporting fractures in the target reservoir, wherein the fracture width distribution includes the continuous distribution of the fracture width of the supporting fractures along the fracture length and fracture height directions of the supporting fractures.

[0066] In some embodiments, determining the fracture width distribution of the supported fractures in the target reservoir based on the fracture data includes: determining the filtration coefficient of fracturing fluid in the dynamic fractures of the target reservoir based on the fracture length data and fracture height data of the dynamic fractures; and determining the fracture width distribution based on the fracture height data, the fracture length data, the fracture width data, and the filtration coefficient.

[0067] In some embodiments, determining the fracturing fluid filtration coefficient based on dynamic fracture length and height data may include: determining the mapping relationship between the fracturing fluid filtration coefficient and the dynamic fracture length and height, and then determining the fracturing fluid filtration coefficient based on measured dynamic fracture length and height data of the target reservoir. That is, by calibrating the fracturing fluid filtration coefficient using measured data, a fracturing fluid filtration coefficient more closely matches the target reservoir is obtained, thereby making the calculated fracture width distribution and conductivity distribution more realistic and reliable.

[0068] In some embodiments, the filtration coefficient can be determined by the following formula:

[0069]

[0070] Where L represents the fracture half-length of the dynamic fracture, q represents the fracturing fluid velocity, G represents the shear modulus of the target reservoir, ν represents the Poisson's ratio of the target reservoir, and H f ψ represents the fracture height of the dynamic fracture, μ represents the viscosity of the fracturing fluid, and ψ represents the filtration loss coefficient of the fracturing fluid.

[0071] It is understandable that the crack length and height data at the crack opening of a dynamic crack cannot be obtained through actual measurement data, thus making it impossible to determine the crack width distribution at the crack opening. However, the crack width at the crack opening, as the maximum crack width of the dynamic crack, can be determined by using the above formula (1) and the filtering coefficient calibrated with actual measurement data. Based on the calibrated filtering coefficient, the crack width distribution at the crack opening can be calculated. Using the crack width distribution at the crack opening as a boundary constraint to determine the crack width distribution of the supporting crack, a more accurate and reliable crack width distribution result can be obtained.

[0072] Figure 2 The diagram shown is a flowchart illustrating a method for determining seam width distribution according to an embodiment of this application.

[0073] like Figure 2As shown, in some embodiments, determining the seam width distribution result based on the seam height data, the seam length data, the seam width data, and the filtering coefficient may include:

[0074] S201: Based on the fracture height data, fracture length data, fracture width data, the mapping relationship between fracture length and fracture height in the dynamic fractures of the target reservoir, and the mapping relationship between fracture width and fracture length in the dynamic fractures of the target reservoir, determine the first fracture width distribution of the dynamic fractures of the target reservoir along the fracture height direction and the fracture length direction.

[0075] In some embodiments, a dynamic crack can be considered as an ellipsoid, and each cross-section of the dynamic crack can be considered as an ellipse. For example, Figure 3 The diagram shown is a structural schematic of a dynamic crack provided in an embodiment of this application. Figure 3 As shown, a dynamic crack can be considered as an ellipsoid, with the center point of the ellipsoid being the center point of the crack's opening. A coordinate system can be constructed with the center point of the crack's opening as the origin. The y-axis of this coordinate system represents the crack width, the x-axis represents the crack length, and the z-axis represents the crack height. For the longitudinal section S of the dynamic crack, the mapping relationship between the crack width and height on this section satisfies the equation of an ellipse, where the coefficients of this ellipse equation are the crack height H of the dynamic crack on that longitudinal section. f And the crack width, which in turn allows us to determine the crack height H of the dynamic crack in that longitudinal section. f The crack width and ellipse equation are used to determine the crack width distribution along the crack height direction of the dynamic crack in the longitudinal section.

[0076] Continue to refer to Figure 3 As shown, in some embodiments, since the dynamic crack can be considered as an ellipsoid, the mapping relationship between the crack width and crack length, and the mapping relationship between the crack length and crack height, also satisfy the elliptic equation. Furthermore, based on the elliptic equation and measured crack length and width data, the crack width distribution of a single longitudinal section can be extended to multiple longitudinal sections of the dynamic crack to obtain the crack width distribution of the dynamic crack in three-dimensional space. That is, the first crack width distribution along the crack length and crack height directions is obtained.

[0077] In some embodiments, the first seam width distribution can be determined in the following way:

[0078] The crack width, length, and height data of the dynamic cracks obtained from the core section are integrated into vector form, which can be represented as dynamic crack width vector, dynamic crack length vector, and dynamic crack height vector. Since the dynamic crack width, length, and height vectors belong to different longitudinal sections of the dynamic cracks, a projection method is used to project the crack width, height, and length of different cracks onto the same crack, so that the crack has multiple points (i.e., multiple longitudinal sections) with dynamic crack length, width, and height values. Then, according to the ellipse equation, the first crack width distribution on the crack profile corresponding to each point can be calculated.

[0079] S202: Based on the filtration coefficient, the mapping relationship between fracture width and fracture height, and the mapping relationship between fracture width and fracturing time, determine the second fracture width distribution of the longitudinal section of the fracture at the fracture opening of the target reservoir.

[0080] It is understandable that since the crack length and height data at the crack opening of a dynamic crack cannot be obtained through actual measurement data, the crack width distribution at the crack opening cannot be determined. Since the crack width at the crack opening is the maximum crack width of the dynamic crack, it is necessary to calibrate the filtering coefficient using measured data through formula (1). Therefore, in step S202, the second crack width distribution at the crack opening can be calculated based on the calibrated filtering coefficient, and this second crack width distribution can be used as a boundary constraint condition to determine the crack width distribution of the supporting crack, thus obtaining a more accurate and reliable crack width distribution result.

[0081] In some embodiments, the second seam width distribution data is determined by the following formula:

[0082]

[0083]

[0084] Where W(0,t) represents the center fracture width at the fracture opening when the fracturing operation time is t, t represents the fracturing operation time, q represents the fracturing fluid velocity, G represents the shear modulus of the target reservoir, ν represents the Poisson's ratio of the target reservoir, and H f ψ represents the fracture height of the dynamic fracture, μ represents the viscosity of the fracturing fluid, ψ represents the filtration loss coefficient of the fracturing fluid, w represents the fracture width on the longitudinal section of the fracture at the fracture opening in the target reservoir, x represents the abscissa of the fracture on the longitudinal section with the fracture center as the origin, and y represents the ordinate of the fracture on the longitudinal section with the fracture center as the origin.

[0085] It is understandable that the fracturing operation time refers to the time from the start of fracturing fluid injection until the dynamic fracture is fully formed. As the fracturing time increases, the width of the fracture at the opening of the dynamic fracture will also change. The center width of the fracture at the opening can be determined based on the fracturing time (e.g., Figure 3The W(0,t) shown in the figure is used to substitute the seam width into formula (3). By listing the y values, a series of x values ​​are obtained using formula (3). The obtained x is the second seam width distribution.

[0086] S203: Determine the seam width distribution result based on the first seam width distribution and the second seam width distribution.

[0087] It can be understood that the first crack width distribution obtained in step S201 is discrete crack width distribution data, which is obtained by acquiring crack data of the longitudinal sections of multiple dynamic cracks, corresponding to the crack width distribution of multiple dynamic cracks. In step S203, the second crack width distribution obtained in step S202 can be used as a constraint condition for the crack width distribution result of the support crack, and the first crack width distribution obtained in step S201 can be interpolated to obtain a continuous crack width distribution result, which is the crack width distribution result of the support crack.

[0088] S103: Based on the fracture width distribution results and the predetermined mapping relationship between fracture width and conductivity, determine the conductivity distribution of the target reservoir, wherein the conductivity distribution characterizes the distribution of the conductivity of the supported fractures of the target reservoir along the fracture length and fracture height directions.

[0089] It is understandable that the predetermined mapping relationship between the fracture width and the conductivity is determined through simulation using experimentally obtained fracture width data and conductivity data of the supporting fracture. Specifically, the mapping relationship between the fracture width and the conductivity is determined in the following way:

[0090] Assuming that the formation closure stress remains constant, i.e., the strength of proppant compaction within the fracture is the same, the proppant on each propped fracture wall surface of the core column profile is collected and weighed to obtain the proppant mass set. Based on the core diameter and the proppant mass on the propped fracture wall surface, the proppant surface density set can be obtained.

[0091] Furthermore, an indoor proppant conductivity testing instrument can be used to measure the proppant conductivity of the fracture. The length, width, and height of the proppant chamber are l, w, and h, respectively, where w represents the proppant filling thickness, which is the fracture width in this case. The mass of proppant required to fill the proppant chamber for each fracture width is obtained by using the cross-sectional area of ​​the proppant chamber and the surface density of the proppant. Then, the calculated required mass of proppant is filled into the proppant chamber, and a proppant conductivity test experiment is conducted. The proppant chamber is used to simulate an artificial fracture.

[0092] During the experiment, data such as fluid velocity, fluid viscosity, guide chamber height, guide chamber length, and pressure difference between the upstream and downstream sides of the guide chamber can be collected in the supporting crack. Then, based on the relationship between the flow capacity, the guide chamber width, and relevant fluid parameters, the flow capacity under different guide chamber widths can be determined. Furthermore, based on the guide chamber width and the corresponding flow capacity, the mapping relationship between the crack width and the flow capacity can be simulated, and a linear equation characterizing the mapping relationship between the flow capacity and the crack width can be obtained.

[0093] In some embodiments, the flow guiding capacity of the flow guiding chamber corresponding to different flow guiding chamber widths can be determined by the following formula:

[0094]

[0095] Among them, WK f The flow-guiding capacity of the flow-guiding chamber, i.e. the flow-guiding capacity of the supporting crack, is represented by Q, which represents the flow velocity of the fluid during the experiment, μ1, which represents the viscosity of the fluid during the experiment, h, which represents the height of the flow-guiding chamber, l, which represents the length of the flow-guiding chamber, w, which represents the width of the flow-guiding chamber, and ΔP, which represents the pressure difference between the upstream and downstream sides of the flow-guiding chamber.

[0096] In some embodiments, the linear relationship between the slot width and the flow carrying capacity can be expressed by the following formula:

[0097] WK f =kw+s Formula (5)

[0098] Where k represents the slope and s represents the intercept.

[0099] In some embodiments, since the proppant cannot completely fill the dynamic crack, there exists an equilibrium height for the proppant within the dynamic crack. Below the equilibrium height, the proppant completely fills the propping crack, and the conductivity distribution below the equilibrium height can be determined using the aforementioned mapping relationship between crack width and conductivity, as well as the crack width distribution results. Above the equilibrium height, there is no proppant, therefore no fluid conduction, i.e., the conductivity above the equilibrium height is 0. Since the equilibrium height of the proppant is related to the proppant's static velocity, the resistance velocity of transport, and the equilibrium flow velocity, the equilibrium height of the proppant can be determined by determining the equilibrium flow velocity of the proppant. The method for determining the equilibrium height will be combined with... Figure 4 A detailed introduction will be provided.

[0100] Figure 4 The diagram shown is a flowchart illustrating another method for determining the conductivity of reservoir fractures provided in an embodiment of this application.

[0101] like Figure 4 As shown, in some embodiments, before step S103, that is, before determining the conductivity distribution of the target reservoir based on the fracture width distribution results and the predetermined mapping relationship between fracture width and conductivity, the following steps are included:

[0102] S104: Determine the target equilibrium flow rate of the proppant supporting the fractures in the target reservoir.

[0103] In some embodiments, taking a point within the proppant fracture as an example, the equilibrium flow velocity of the proppant can first be determined by calculating its settling velocity. It is understood that the settling velocity is related to the flow regime, proppant concentration, fracture wall effect, and the Reynolds number of the proppant, and their relationships can be shown in Table 1 below:

[0104] Table 1

[0105]

[0106] As can be understood, Table 1 above characterizes the relationship between the Reynolds number and the drag coefficient and concentration correction coefficient. Wherein, C... f It can represent the volume fraction of liquid in the proppant, equivalent to porosity, and the Reynolds number R. ep =ρ f d p v p / μ,ρ p It can represent the true density of proppant particles; d p It can represent proppant particle support; ρ f It can represent the density of the proppant; g can represent the acceleration due to gravity.

[0107] To consider the effect of artificial crack wall effect on settlement velocity, the wall correction factor f can be used. w To make corrections, the wall correction factor can be calculated in the following way:

[0108]

[0109] Here, w can represent the width of the supporting crack. It can be understood that for 1 < Rep ≤ 100, the wall correction coefficient calculated by the above formula can be obtained through linear interpolation.

[0110] Furthermore, the settling velocity of the proppant can be determined based on the wall correction coefficient calculated using the above formula, and the free settling velocity and concentration correction coefficients in Table 1. The settling velocity of the proppant can be determined using the following formula:

[0111] v t =f c f w v p Formula (7)

[0112] Among them, v t This indicates the settling velocity of the proppant.

[0113] In some embodiments, the relationship between equilibrium flow velocity, resistance velocity, and equilibrium height satisfies the following formula:

[0114]

[0115]

[0116] Among them, v EQ It can represent the equilibrium flow rate of the proppant, h EQ It can represent the equilibrium height of the proppant, v WEQ The resistance velocity at equilibrium can be represented by q, and the flow rate at the cross section can be represented by μ. f R can represent the viscosity of a liquid. h It can represent the hydraulic radius.

[0117] In some embodiments, the relationship between the resistance velocity of proppant transport and the equilibrium flow velocity satisfies the following formula:

[0118]

[0119] Among them, v EQ1 The equilibrium velocity of the proppant in laminar flow, v EQ2 ρ represents the equilibrium velocity of the proppant in turbulent flow. sl ρ represents the density of the sand-mixing solution. f φ represents the density of the liquid, S represents the proportion of sand and gravel in the proppant, and φ represents the porosity of the sand pile.

[0120] It is understood that the equilibrium flow velocity of the support crack can be obtained by using the above formulas (6) to (10) and Table 1.

[0121] S105: Determine the equilibrium height of the target reservoir based on the mapping relationship between the proppant equilibrium flow rate and equilibrium height, and the target equilibrium flow rate.

[0122] In some embodiments, the balance can be determined by the following formula:

[0123]

[0124] Among them, H f H represents the crack height of a dynamic crack. EQ This indicates the equilibrium height supporting the crack.

[0125] S106: Determine that the conductivity of the supporting fractures in the target reservoir above the equilibrium height is zero.

[0126] Further, in some embodiments, step S103, based on the fracture width distribution results and a predetermined mapping relationship between fracture width and conductivity, determines the conductivity distribution of the target reservoir, including:

[0127] Based on the fracture width distribution results and the mapping relationship between fracture width and conductivity, the conductivity distribution of the supported fractures in the target reservoir below the equilibrium height is determined.

[0128] The method for determining the conductivity of reservoir fractures provided in this application determines the filtration coefficient of fracturing fluid and the longitudinal section distribution of fracture width at the fracture opening through measured fracture data. A conductivity test experiment is then used to simulate the mapping relationship between fracture width and conductivity, resulting in higher accuracy of the fracture width distribution and the mapping relationship. Based on the pre-determined mapping relationship and fracture width distribution, the conductivity distribution in the fracture length and height directions is obtained. This application fully integrates three dimensions: field-scale coring experiments, theoretical model calculations, and indoor experimental tests. The calculation processes are mutually supportive and interdependent, resulting in high accuracy of the calculated conductivity. Furthermore, it enables effective prediction of the conductivity distribution of artificial fractures at the field scale, from points to lines and then to surfaces, obtaining the conductivity distribution in three-dimensional space. This provides support for optimizing fracturing scheme design and improving the efficiency of post-fracturing production in oil and gas wells.

[0129] The method for determining the conductivity of reservoir fractures provided in this application will be further described below with reference to specific embodiments.

[0130] In this embodiment, taking the Y3 tight gas well in a certain area of ​​the Sichuan Basin as an example, the method for determining the conductivity of energy storage fractures provided in this application embodiment is used to predict the conductivity distribution in the artificial fractures after horizontal well fracturing. Specifically, it may include the following steps:

[0131] S1. Hydraulic fracturing was carried out on well Y3. The horizontal section of the wellbore trajectory was perpendicular to the direction of the maximum horizontal principal stress. Wide-area electromagnetic monitoring was conducted simultaneously. After hydraulic fracturing, relevant data were collected, including engineering geological parameters (well section, Young's modulus E, Poisson's ratio v, shear modulus G, minimum horizontal principal stress Pσ) and construction parameters (construction time t, construction flow rate Q, fracturing fluid viscosity u). The collected data are shown in Table 2 below.

[0132] Table 2

[0133]

[0134] S2. Drill a highly deviated well within a horizontal section 50–200 m from well Y3 for conformal coring. Extract core samples from a distance of 50–200 m from the horizontal well, with a core length of L. The relative positions of the two wells are as follows: Figure 5 As shown.

[0135] S3. The core column of length L is divided along the direction perpendicular to the cross-section of the core, and the cross-section is scanned by electron microscopy to obtain a core column cross-section containing dynamic cracks and some support cracks.

[0136] S4. Mark the depth and number of dynamic cracks and support cracks on the core column profile, respectively. The number of dynamic cracks and support cracks are represented by m and n, respectively, where m = 18 and n = 15; record the depth vector Dm of the dynamic cracks and measure the width w of the dynamic cracks. m The dynamic seam width vector Wm is obtained.

[0137] S5. Based on the relative positions of the wellbore trajectories of highly deviated wells and horizontal wells, measure the lateral distance L from each depth in the depth vector Dm to the horizontal wellbore. m and longitudinal distance H m The dynamic seam length vector Lm and the dynamic seam height vector Hm are obtained respectively.

[0138] S6. Assume the longitudinal section of the artificial fracture within the formation is elliptical, and the fracture height H f H remains unchanged during the extension process. f It is equal to twice the maximum value in the dynamic seam height vector Hm, where H f =32.5m;

[0139] S7. Determine the relationship between the fracture length and fracture height at any given time (i.e., formula (1) mentioned above), where the maximum dynamic fracture length is the maximum value in the dynamic fracture length vector Lm. In this embodiment, the maximum dynamic fracture length is L = 173.6. The filtration coefficient ψ of the fracturing fluid in this embodiment can be determined using formula (1), as well as the fracture height and fracture length, to calibrate the fracturing fluid filtration coefficient. Furthermore, based on the calibrated fracturing fluid filtration coefficient, the mapping relationship between the fracture width and fracture length can be obtained, which can be expressed as follows: Figure 6 As shown, it can be understood that as the crack length (i.e., crack length) increases, the crack width (i.e., crack width) gradually decreases.

[0140] S8. Based on the fracturing fluid filtration coefficient ψ = 0.0002 m / min obtained in step S8. 1 / 2 The width of the central crack at the fracture opening after the fracturing operation can be obtained, which is calculated using formula (2) above. In this embodiment, the width of the fracture opening at the end of the operation is calculated to be W = 0.063m. According to formula (3) above, the second fracture width distribution on the longitudinal section of the fracture at the fracture opening at the end of the operation can be obtained. The second fracture width distribution calculated here can be used as the boundary constraint condition for the fracture width distribution result.

[0141] S9. Based on the fact that the dynamic crack width vector Wm, dynamic crack length vector Lm, and dynamic crack height vector Hm obtained from the centering point belong to different artificial cracks, a projection method is used to project the crack width, crack height, and crack length of different cracks onto the same crack, so that the crack has dynamic crack length, dynamic crack width, and dynamic crack height values ​​at multiple points. Then, according to the ellipse equation, the first crack width distribution on the crack profile corresponding to each point can be calculated.

[0142] In steps S10, S8, and S9, the second crack width distribution and the first crack width distribution are obtained respectively, but they are not continuous. Therefore, the two-dimensional interpolation function inside MATLAB can be used to interpolate the continuous crack width distribution along the entire crack length direction based on the crack width distribution in steps S8 and S9, that is, the crack width distribution of the support crack.

[0143] S11. Assuming that the formation closure stress remains constant and the proppant filling degree of each support fracture wall is the same, i.e. the strength of proppant compaction within the fracture is the same, the proppant on each support fracture wall is collected and weighed to obtain the proppant mass set M. Based on the core diameter and the proppant mass on the support fracture wall, the proppant surface density set ρ can be obtained.

[0144] S12. Using an indoor flow-conducting capacity testing instrument, measure the flow-conducting capacity of the support crack. The length, width, and height of the flow-conducting chamber are l, w, and h, respectively, where w is the thickness of the proppant filling and the width of the support crack. The mass of proppant required for each support crack width is obtained by using the cross-sectional area of ​​the flow-conducting chamber and the surface density of the proppant. Then, the flow-conducting capacity value for each width can be obtained using the formula (4) mentioned above. Based on the width and its corresponding flow-conducting capacity, the formula (5) mentioned above can be obtained, which is the mapping relationship between crack width and flow-conducting capacity.

[0145] In this embodiment, the simulated mapping relationship between the slit width and the flow guiding capacity can be as follows: Figure 7 As shown. Figure 7 The horizontal axis represents the width of the support joint (i.e., the width of the support crack), and the vertical axis represents the flow conduction capacity. In the simulated formula (5), k is 3.8396 and s is 1.771.

[0146] S13. Based on Table 1 and formulas (6) to (10) in step S104 above, the equilibrium velocity of the supporting crack can be calculated. In the specific calculation, the sand-carrying fluid mixture is calculated according to the turbulent state, and the results are 2.13 m / s and 0.21 m / s respectively. At this time, it is necessary to further verify the correctness of the flow state. The calculated Reynolds number Rep=16324>3000 is satisfied, so the flow state is satisfied. Therefore, the equilibrium velocity of 2.13 m / s is correct.

[0147] S14. After obtaining the equilibrium flow velocity, the equilibrium height can be obtained using formula (11) mentioned above, and the equilibrium height H of a certain point in the support crack can be calculated. EQ =22.5m.

[0148] S15. Calculate the equilibrium height of a point in the artificial crack using steps S13 and S14. This method can be used to obtain the equilibrium height of the entire support crack. Simultaneously, there is no proppant filling above the equilibrium height, therefore the conductivity is 0D·cm. Below the equilibrium height, using the linear relationship between crack width and conductivity obtained in step S12 and the crack width distribution results obtained in step S10, the conductivity values ​​at different locations can be obtained, thus yielding the conductivity distribution of the support crack.

[0149] In this embodiment, the flow-guiding capacity distribution obtained based on steps S1 to S15 can be as follows: Figure 8 As shown in the figure, different gray values ​​can represent the flow conduction capacity corresponding to the crack height and crack length. The horizontal axis represents half the crack length of the supporting crack, and the vertical axis represents the crack height of the supporting crack.

[0150] This application also provides an apparatus for determining the conductivity of reservoir fractures. Figure 9 The diagram shown is a schematic representation of the program modules of a device for determining the conductivity of reservoir fractures according to an embodiment of this application. Figure 9 As shown, the apparatus 900 for determining the conductivity of reservoir fractures may include:

[0151] The data acquisition module 901 is used to acquire fracture data of the target reservoir.

[0152] The fracture width determination module 902 is used to determine the fracture width distribution result of the supporting fracture in the target reservoir based on the fracture data, wherein the fracture width distribution result includes the continuous distribution result of the fracture width of the supporting fracture along the fracture length and fracture height directions of the supporting fracture.

[0153] The conductivity determination module 903 is used to determine the conductivity distribution of the target reservoir based on the fracture width distribution results and the mapping relationship between fracture width and conductivity. The mapping relationship between fracture width and conductivity is determined by simulation using experimentally obtained fracture width data and conductivity data of the supporting fractures. The conductivity distribution characterizes the distribution of the conductivity of the supporting fractures in the target reservoir along the fracture length and fracture height directions.

[0154] The descriptions and functions of the above units can be understood by referring to the section on methods for determining the conductivity of reservoir fractures, and will not be repeated here.

[0155] This specification also provides a computer storage medium storing computer program instructions, which, when executed, implement the steps of the method for determining the conductivity of reservoir fractures described above.

[0156] This specification also provides a computer program product comprising a computer program that, when executed by a processor, implements the steps of the method for determining the conductivity of reservoir fractures described above.

[0157] This invention also provides an electronic device, such as... Figure 10 As shown, the electronic device may include a processor 1001 and a memory 1002, wherein the processor 1001 and the memory 1002 may be connected via a bus or other means. Figure 10 Taking the example of a connection between China and Israel via a bus.

[0158] Processor 1001 may be a central processing unit (CPU). Processor 1001 may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof.

[0159] Memory 1002, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the method for determining the conductivity of reservoir fractures in this embodiment of the invention (e.g., Figure 9 The data acquisition module 901, fracture width determination module 902, and flow capacity determination module 903 are shown. The processor 1001 executes various functional applications and data processing by running non-transitory software programs, instructions, and modules stored in the memory 1002, thereby realizing the method for determining the flow capacity of reservoir fractures in the above method embodiments.

[0160] The memory 1002 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor 1001, etc. Furthermore, the memory 1002 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 1002 may optionally include memory remotely located relative to the processor 1001, and these remote memories may be connected to the processor 1001 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0161] The one or more modules are stored in the memory 1002, and when executed by the processor 1001, they perform the following: Figure 1 The method for determining the conductivity of reservoir fractures in the illustrated embodiment.

[0162] The specific details of the aforementioned electronic device can be understood by referring to the relevant descriptions and effects in the above method embodiments, and will not be repeated here.

[0163] This specification also provides a computer storage medium storing computer program instructions, which, when executed, implement the steps of the method for determining the conductivity of reservoir fractures described above.

[0164] This specification also provides a computer program product comprising a computer program that, when executed by a processor, implements the steps of the method for determining the conductivity of reservoir fractures described above.

[0165] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0166] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, please refer to each other. The focus of each embodiment is to describe the differences from other embodiments.

[0167] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions.

[0168] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0169] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute certain parts of the methods of various embodiments of this application.

[0170] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0171] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0172] Although this application has been described through embodiments, those skilled in the art will know that this application has many modifications and variations without departing from the spirit of this application, and it is intended that the appended claims cover such modifications and variations without departing from the spirit of this application.

Claims

1. A method for determining the conductivity of reservoir fractures, characterized in that, include: Acquire fracture data of the target reservoir; Based on the fracture data, the fracture width distribution of the supporting fractures in the target reservoir is determined, wherein the fracture width distribution includes the continuous distribution of the fracture width of the supporting fractures along the fracture length and fracture height directions of the supporting fractures. Based on the fracture width distribution results and the predetermined mapping relationship between fracture width and conductivity, the conductivity distribution of the target reservoir is determined, wherein the conductivity distribution characterizes the distribution of the conductivity of the supported fractures of the target reservoir along the fracture length and fracture height directions. Based on the fracture data, the fracture width distribution of the supported fractures in the target reservoir is determined, including: Based on the fracture length and fracture height data of the dynamic fracture, the filtration coefficient of the fracturing fluid in the dynamic fracture of the target reservoir is determined. Based on the fracture height data, fracture length data, fracture width data, the mapping relationship between fracture length and fracture height in the dynamic fractures of the target reservoir, and the mapping relationship between fracture width and fracture length in the dynamic fractures of the target reservoir, the first fracture width distribution of the dynamic fractures in the target reservoir along the fracture height direction and the fracture length direction is determined. Based on the aforementioned filtration coefficient, the mapping relationship between fracture width and fracture height, and the mapping relationship between fracture width and fracturing time, the second fracture width distribution of the longitudinal section of the fracture at the fracture opening in the target reservoir is determined. The seam width distribution result is determined based on the first seam width distribution and the second seam width distribution; The filtration loss coefficient is determined by the following formula: ； in, This represents the crack half-length of a dynamic crack. Indicates the fracturing fluid flow rate. Indicates the shear modulus of the target reservoir. This represents the Poisson's ratio of the target reservoir. This indicates the crack height of a dynamic crack. This indicates the viscosity of the fracturing fluid. Indicates the filtration loss coefficient of the fracturing fluid; The second seam width distribution data is determined by the following formula: ； ； in, The time for fracturing operations is indicated as The center seam width at the seam opening, Indicates the time of fracturing operation. Indicates the fracturing fluid flow rate. Indicates the shear modulus of the target reservoir. This represents the Poisson's ratio of the target reservoir. This indicates the crack height of a dynamic crack. This indicates the viscosity of the fracturing fluid. This represents the filtration loss coefficient of the fracturing fluid. denoted by x, the fracture width on the longitudinal section of the fracture at the fracture opening in the target reservoir; x represents the abscissa of the fracture on the longitudinal section with the fracture center as the origin; and y represents the ordinate of the fracture on the longitudinal section with the fracture center as the origin.

2. The method according to claim 1, characterized in that, Acquire fracture data of the target reservoir, including: Obtain core profiles of the target reservoir; Collect dynamic fracture data of the core column profile, including fracture length data, fracture width data, and fracture height data.

3. The method according to claim 1, characterized in that, Before determining the conductivity distribution of the target reservoir based on the fracture width distribution results and the predetermined mapping relationship between fracture width and conductivity, the following steps are included: Determine the target equilibrium flow rate of the proppant that supports the fractures in the target reservoir; The equilibrium height of the target reservoir is determined based on the mapping relationship between the equilibrium flow rate and equilibrium height of the proppant and the target equilibrium flow rate. The conductivity of the supporting fractures in the target reservoir above the equilibrium height is determined to be zero.

4. A device for determining the conductivity of reservoir fractures, characterized in that, include: The data acquisition module is used to acquire fracture data of the target reservoir; The fracture width determination module is used to determine the fracture width distribution result of the supporting fracture in the target reservoir based on the fracture data, wherein the fracture width distribution result includes the continuous distribution result of the fracture width of the supporting fracture along the fracture length and fracture height directions of the supporting fracture; The conductivity determination module is used to determine the conductivity distribution of the target reservoir based on the fracture width distribution result and a pre-determined mapping relationship between fracture width and conductivity, wherein the conductivity distribution characterizes the distribution of the conductivity of the supported fractures of the target reservoir along the fracture length and fracture height directions. The seam width determination module is specifically used for: Based on the fracture length and fracture height data of the dynamic fracture, the filtration coefficient of the fracturing fluid in the dynamic fracture of the target reservoir is determined. Based on the fracture height data, fracture length data, fracture width data, the mapping relationship between fracture length and fracture height in the dynamic fractures of the target reservoir, and the mapping relationship between fracture width and fracture length in the dynamic fractures of the target reservoir, the first fracture width distribution of the dynamic fractures in the target reservoir along the fracture height direction and the fracture length direction is determined. Based on the aforementioned filtration coefficient, the mapping relationship between fracture width and fracture height, and the mapping relationship between fracture width and fracturing time, the second fracture width distribution of the longitudinal section of the fracture at the fracture opening in the target reservoir is determined. The seam width distribution result is determined based on the first seam width distribution and the second seam width distribution; The filtration loss coefficient is determined by the following formula: ； in, This represents the crack half-length of a dynamic crack. Indicates the fracturing fluid flow rate. Indicates the shear modulus of the target reservoir. This represents the Poisson's ratio of the target reservoir. This indicates the crack height of a dynamic crack. This indicates the viscosity of the fracturing fluid. Indicates the filtration loss coefficient of the fracturing fluid; The second seam width distribution data is determined by the following formula: ； ； in, The time for fracturing operations is indicated as The center seam width at the seam opening, Indicates the time of fracturing operation. Indicates the fracturing fluid flow rate. Indicates the shear modulus of the target reservoir. This represents the Poisson's ratio of the target reservoir. This indicates the crack height of a dynamic crack. This indicates the viscosity of the fracturing fluid. This represents the filtration loss coefficient of the fracturing fluid. denoted by x, the fracture width on the longitudinal section of the fracture at the fracture opening in the target reservoir; x represents the abscissa of the fracture on the longitudinal section with the fracture center as the origin; and y represents the ordinate of the fracture on the longitudinal section with the fracture center as the origin.

5. An electronic device, characterized in that, include: A memory and a processor, the processor and the memory being communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to implement the steps of the method according to any one of claims 1 to 3.

6. A computer storage medium, characterized in that, The computer storage medium stores computer program instructions, which, when executed, implement the steps of the method according to any one of claims 1 to 3.

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