A method and system for calculating the conductivity of a sand-acid fracturing reservoir simulation system

Abstract

The application provides a method and system for calculating the conductivity of a sand-acid fracturing reservoir simulation system, which comprises the following steps: constructing a simulation parameter combination set around sand-acid fracturing operation parameters for reservoir types with sand-acid fracturing requirements; analyzing fracture acid erosion data of different reservoirs by using a preset fracture acid erosion calculation model, and analyzing the embedding depth and deformation data of the proppant in combination with the injection rate parameters and the proppant data; further analyzing the sand concentration of sand-acid fracturing, and setting a rough body simulation distribution coefficient in combination with the injection rate, so as to form a reservoir fracture model that presents a real fracturing state; analyzing the permeability state of the reservoir fracture model after fracturing based on the rough body simulation distribution coefficient and the reservoir closure pressure; and further calculating the corresponding conductivity in combination with the fracture width calculated according to the fracture acid erosion data, the embedding depth and deformation data of the proppant. The method solves the problem that the sand-acid fracturing conductivity cannot be quantitatively analyzed, and provides support for field acid fracturing design and productivity prediction.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of reliability test and evaluation, and particularly relates to a method and system for calculating the flow conductivity of a sand-acidizing reservoir simulation system. BACKGROUND

[0002] Among the global proven oil and gas reserves and resources to be discovered, carbonate rocks account for a significantly higher proportion, and are an important field of oil and gas exploration and development. Acid fracturing is a common stimulation method in the field of carbonate rock oil and gas reservoir development. However, for deep carbonate reservoirs, due to the high reservoir temperature and closure pressure, if conventional acid fracturing technology is used for fracturing, the acid-rock reaction will be fast and the fluid loss will be severe, resulting in a short acid etching distance, low acid etching fracture conductivity, and often unsatisfactory stimulation effect.

[0003] Technical personnel have developed sand-acidizing fracturing technology, which organically combines sand fracturing and acid fracturing technology. On the one hand, the fractures are supported by proppants, and on the other hand, acid reacts with the surface rock of the fractures to form uneven etching, combining the advantages of acid fracturing and sand fracturing, forming a complex network of acid-etched and propped fractures in the reservoir, improving the effectiveness and effective period of the stimulation measures. For example, in the patent document "Carbonate Reservoir High Conductivity Acid Fracturing Method" (201510617937.8), a non-reactive liquid is used as a preflush to create a fracture and reduce the temperature, then a high-concentration acid liquid system is injected to etch the fracture wall, and finally a high-viscosity sand-carrying liquid is used to carry proppants to fill the acid-etched fractures, thereby forming a high-conductivity fracture system, reducing oil and gas migration resistance, and improving the stimulation effect. In the invention patent "Composite Stimulation Method for Carbonate Reservoirs" (201710571875.0), a preflush is used to create a fracture, then a sand-carrying liquid is used to carry proppants to support the fracture, and finally acid is injected to etch the fracture, thereby forming a composite high-conductivity fracture with acid etching near the wellbore and proppant support far from the wellbore. In the invention patent "Sand-acidizing Aftereffect Acid Fracturing Method for Carbonate Rocks" (202010067711.6), crosslinked guanidine gum and ceramic particles are injected to form a main fracture and branch fractures paved with proppants, and then acid is injected to dissolve and expand the main fracture and branch fractures, forming a fracture system with sand-acidizing fractures as the main channel and acid-etched wormholes as the branch channel. The above documents show that sand-acidizing fracturing technology has been widely used in the field, and its flow conductivity performance will affect the development of large-scale oil and gas reservoirs. However, there is no specific method for calculating or predicting the flow conductivity after construction in existing research.

[0004] The prior art is mostly directed to the calculation or prediction of the flow conductivity for conventional fracturing processes or a single fracturing process. For example, in the patent document "A method for predicting the flow conductivity of channel fracturing (201510593843.1)", a mechanical model of channel fracturing is established, and the fitting coefficients and equivalent permeability required by the model are determined, so as to predict the flow conductivity of the channel fracturing proppant. In the patent document "Calculation of initial flow conductivity of acid fracturing cracks (201610051684.7)", the lateral tortuosity ratio and longitudinal tortuosity ratio are calculated by scanning the surface of the acid-etched rock plate, so as to further calculate the initial flow conductivity of the acid-etched cracks. The channel fracturing flow conductivity calculation methods for self-supporting fracture flow conductivity and acid-etched fracture flow conductivity are respectively given, but the calculation of the flow conductivity of sand acid fracturing is not involved, and reliable data support cannot be provided for the high-quality development of the sand acid fracturing process of the carbonate complex reservoir.

[0005] In summary, the patents related to sand acid fracturing mainly focus on the construction process, and the patents related to the analysis of flow conductivity mainly focus on the calculation of the flow conductivity of channel fracturing, self-supporting fractures, and acid-etched fractures. However, the research on the flow conductivity of the sand acid fracturing simulation system is still in the blank stage, and it is urgent to develop

[0006] The information disclosed in the background section of the present invention is only intended to deepen the understanding of the general background of the present invention, and should not be regarded as acknowledging or implying in any form that the information constitutes prior art known to those skilled in the art. SUMMARY

[0007] To solve the above problems, the present application provides a method for calculating the flow conductivity of a sand acid fracturing reservoir simulation system, which quantitatively analyzes the effect of the sand acid fracturing process and the flow conductivity of the post-fracture reservoir. In one embodiment, the method solves the problems of the prior art that cannot calculate the flow conductivity of sand acid fracturing and the long experimental period of sand acid fracturing flow conductivity. The method comprises:

[0008] The simulation parameter setting step comprehensively analyzes all reservoir types with sand acid fracturing requirements in combination with historical operation data related to the sand acid fracturing process, and constructs a simulation parameter combination set around acid concentration, acid etching time, proppant type, injection rate, and sanding intensity for the geological characteristic parameters of each type of reservoir.

[0009] The fracturing effect analysis step analyzes the acid etching data of the fractures after the acid etching effect of different reservoir types by using a preset fracture acid etching calculation model, and then analyzes the embedding depth and deformation data of the proppant in combination with the injection rate parameters and the proppant size data.

[0010] The fracturing model establishing step, the sanding concentration of the sand acid fracturing and the support agent embedding depth and deformation data analysis are analyzed, and the height distribution coefficient and the number distribution coefficient of the rough body are set based on the combination of the fracturing agent injection speed, so that the rough body with different height random distribution can reflect the reservoir fracture after the acid etching and sanding fracturing, and the reservoir fracture model showing the real sanding acid fracturing reservoir fracture state is formed.

[0011] The fracturing permeability analysis step, the height distribution coefficient and the number distribution coefficient of the rough body are combined with the closure pressure of the reservoir to analyze the permeability state of the reservoir fracture model after fracturing.

[0012] The flow conductivity determination step, the width data of the reservoir fracture after fracturing are analyzed according to the fracture acid etching data, the support agent embedding depth and the deformation data, the corresponding flow conductivity data are calculated in combination with the obtained reservoir fracture permeability, and the matching fracturing parameters and simulation parameters are associated and stored as simulation prediction result records.

[0013] As a further improvement of the present application, in one embodiment, the method further comprises:

[0014] The actual measurement verification step, a reservoir fracture model of a set size is selected as a test model, a sanding acid fracturing experiment is performed according to the corresponding simulation parameters, a fluid consistent with the reservoir properties is applied for testing, the actual measured flow conductivity value is obtained, the error between the calculated flow conductivity value and the actual measured value is calculated, and the reliability of the calculation result is analyzed.

[0015] Preferably, in one embodiment, in the simulation system construction step, it comprises:

[0016] The simulation parameter combination set is: for various types of reservoir rocks, around the acid concentration, acid etching time, support agent type, injection speed and sanding strength, each parameter is taken as the only parameter, and the simulation parameter combination set with constant other parameters and only parameter change is formulated.

[0017] Further, the number of simulation parameter combinations corresponding to various types of reservoir rocks is consistent with the number of sanding acid fracturing reservoir fracture simulation samples, and the initial permeability and initial fracture width of each simulation sample are set according to the preset requirements.

[0018] Specifically, in one embodiment, in the fracturing effect analysis step, the embedding depth of the support agent during fracturing is analyzed according to the following operation model:

[0019]

[0020] In the formula, h represents the embedding depth of the proppant, mm; D represents the initial width of the set fracture, mm; D1 represents the reservoir thickness, mm; D2 represents the diameter of the proppant, mm; η1 and η2 represent the viscosities of the proppant and the rock, respectively, MPa; t represents the operation time, days; P c represents the closure pressure of the set reservoir, MPa; E1 and E2 represent the Young's moduli of the rock and the proppant, respectively, MPa; μ1 and μ2 represent the Poisson's ratios of the rock and the proppant, respectively, dimensionless.

[0021] In one preferred embodiment, in the step of analyzing the fracturing effect, the deformation data of the proppant during fracturing is analyzed according to the following operation model:

[0022]

[0023] In the formula, β represents the deformation of the proppant, mm; D represents the initial width of the set fracture, mm; E2 represents the Young's modulus of the proppant, MPa; μ2 represents the Poisson's ratio of the proppant, dimensionless; P c represents the closure pressure of the reservoir, MPa; t represents the operation time, days.

[0024] Further, in the step of analyzing the fracturing permeability, the permeability of the fracture after the sand-acid fracturing is analyzed according to the following operation model:

[0025]

[0026]

[0027]

[0028]

[0029] In the formula: k f represents the fracture permeability, μm 2 ; k f0 represents the initial fracture permeability, μm 2 ; P c represents the closure pressure of the reservoir, MPa; P1 represents the effective modulus of the rough body, MPa; m represents the height distribution coefficient of the rough body, dimensionless; a represents the number distribution coefficient of the rough body, dimensionless; BM1 represents the bulk modulus of the rock after acid etching, MPa; BM2 represents the bulk modulus of the proppant, MPa; E1 and E2 represent the Young's moduli of the rock and the proppant, respectively, MPa; μ1 and μ2 represent the Poisson's ratios of the rock and the proppant, respectively, dimensionless; λ1 and λ2 represent the influence degrees of the acid on the Young's modulus and the Poisson's ratio of the rock, respectively, dimensionless.

[0030] In an optional embodiment, in the flow capacity determination step, the crack width W after sand-addition acid fracturing is analyzed according to the following computational model:

[0031] W = D - 2(β + h)

[0032] In the formula, β represents the deformation of the proppant, mm; D represents the initial width of the crack, mm; and h represents the embedding depth of the proppant, mm.

[0033] Furthermore, in one embodiment, in the conductivity determination step, the corresponding conductivity is calculated based on the permeability and width data of the reservoir fractures after fracturing, according to the following formula:

[0034] F RCD =k f *W

[0035] In the formula, F RCD D.cm; k represents the conductivity of reservoir fractures after acid fracturing with sand addition. f The permeability of the fracture is expressed in μm. 2 W represents the crack width after acid fracturing with sand, in mm.

[0036] Based on the application aspects of the methods described in any one or more of the above embodiments, the present invention also provides a system for calculating the conductivity of a sand-adding acid fracturing reservoir simulation system, which performs the methods described in any one or more of the above embodiments.

[0037] Compared with the closest prior art, the present invention also has the following beneficial effects:

[0038] This invention provides a method and system for calculating the conductivity of a sand-fed acid fracturing reservoir simulation system. The method constructs a set of simulated parameters around the sand-fracturing operation parameters for reservoir types that require sand-fracturing. It sets up a set of simulated parameters that covers all reservoir types and sand-fracturing construction parameters as the object of analysis for conductivity data, which can ensure the comprehensiveness and practicality of supporting actual applications and avoid the phenomenon of being unable to find the data.

[0039] Furthermore, this invention utilizes a pre-defined fracture acid etching calculation model to analyze fracture acid etching data from different reservoirs, and combines injection rate parameters and proppant data to analyze proppant embedding depth and deformation data. It then analyzes the sand-laying concentration during acid fracturing and sets a roughness simulation distribution coefficient based on the injection rate to form a reservoir fracture model that reflects the actual fracturing state. This ensures the consistency between the roughness simulation distribution coefficient and the actual fracturing effect, improves the accuracy of permeability calculation results, and provides strong support for the accuracy of subsequent quantitative analysis of conductivity. It solves the problem of being unable to quantitatively analyze the conductivity of sand-laying acid fracturing, providing support for on-site acid fracturing design and production prediction. This helps in selecting the optimal fracturing operation parameters in practical applications, obtaining fracturing fractures with the best conductivity, thereby improving the quality of fracturing operations and increasing production output.

[0040] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0041] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0042] Figure 1 This is a flowchart illustrating the method for calculating the conductivity of a sand-adding acid fracturing reservoir simulation system according to an embodiment of the present invention;

[0043] Figure 2 This is a proppant placement example diagram of the method for calculating the conductivity of the sand-added acid fracturing reservoir simulation system provided in the embodiments of the present invention;

[0044] Figure 3 This is a schematic diagram of the single proppant stress state of the method for calculating the conductivity of a sand-adding acid fracturing reservoir simulation system provided in another embodiment of the present invention;

[0045] Figure 4 This is an example diagram of a reservoir fracture simulation system based on the method for calculating the conductivity of a sand-adding acid fracturing reservoir simulation system provided in this embodiment of the invention;

[0046] Figure 5 This is a schematic diagram comparing the calculated and measured values ​​of the conductivity of the sand-adding acid fracturing reservoir simulation system provided in an embodiment of the present invention.

[0047] Figure 6 This is a comparison chart of the calculated and measured values ​​of the conductivity of the sand-adding acid fracturing reservoir simulation system provided in another embodiment of the present invention.

[0048] Figure 7 This is a schematic diagram of the flow capacity calculation system of the sand-adding acid fracturing reservoir simulation system provided in the embodiment of the present invention. Detailed Implementation

[0049] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples. Those skilled in the art will then fully understand how the present invention uses technical means to solve technical problems and achieve technical effects, and will be able to implement the present invention specifically based on the above-described implementation process. It should be noted that, as long as there is no conflict, the various embodiments and features of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0050] Although the flowchart describes the operations as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. The order of the operations can be rearranged. A process can terminate when its operation is complete, but it may also have additional steps not included in the diagram. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0051] Computer equipment includes user equipment and network equipment. User equipment or clients include, but are not limited to, computers, smartphones, PDAs, etc.; network equipment includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Computer equipment can operate independently to implement this invention, or it can connect to a network and implement this invention through interaction with other computer equipment in the network. The network in which the computer equipment is located includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, VPN network, etc.

[0052] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms “a” and “an” as used herein are also intended to include the plural. It should also be understood that the terms “comprising” and / or “including” as used herein specify the presence of the stated features, integers, steps, operations, units, and / or components, without excluding the presence or addition of one or more other features, integers, steps, operations, units, components, and / or combinations thereof.

[0053] Carbonate rocks constitute a significantly high proportion of both proven and undiscovered oil and gas reserves globally, making them a crucial area for oil and gas exploration and development. Acid fracturing is a common method for enhancing production in carbonate oil and gas reservoirs. However, for deep carbonate reservoirs, due to their high reservoir temperatures and closure pressures, conventional acid fracturing techniques often result in rapid acid-rock reactions and severe filtration loss, leading to short acid etching distances and low conductivity of the etched fractures, often resulting in unsatisfactory production enhancement effects. For carbonate oil and gas reservoirs with deep burial, high formation temperatures, and high formation closure pressures, conventional acid fracturing is insufficient to achieve good enhancement results. Therefore, proppant-assisted acid fracturing has emerged, combining the advantages of proppant fracturing and acid fracturing to significantly improve the enhancement effect.

[0054] Technicians have developed a proppant-assisted acid fracturing process that organically combines proppant fracturing and acid fracturing technologies. On one hand, proppant supports the fractures; on the other hand, acid reacts with the rock surface of the fractures, creating uneven etching. This process integrates the advantages of acid fracturing and proppant fracturing, forming a complex network of acid-etched supported fractures in the reservoir, improving the effectiveness and duration of the stimulation measures. For example, in the patent document "A High-Conductivity Acid Fracturing Method for Carbonate Reservoirs" (201510617937.8), a non-reactive liquid is first used as a pre-fracturing fluid to create fractures and cool them down. Then, a high-concentration acid system is injected to etch the fracture walls. Finally, a high-viscosity proppant-carrying fluid is used to fill the acid-etched fractures, thereby forming a high-conductivity fracture system, reducing oil and gas migration resistance, and improving the stimulation effect. In the invention patent "A Composite Stimulation Method for Carbonate Reservoirs" (20171057),... In 1875.0), a pre-fracturing fluid is first used to create fractures, then a proppant-carrying fluid is used to support the fractures, and finally acid is injected to etch the fractures, thus forming a composite high-conductivity fracture with acid etching in the near-wellbore zone and proppant support in the far-wellbore zone. In the invention patent "A fracturing method for carbonate rock with sand addition and subsequent acid fracturing" (202010067711.6), cross-linked guar gum and ceramic particles are injected to form a main fracture and branch fractures with proppant, and then acid is injected to dissolve and expand the main fracture and branch fractures, forming a fracture system with sand-added fractures as the main channel and acid-etched wormholes as the branch channels. The above documents show that the sand addition acid fracturing process has been widely used in the field, and its conductivity will affect the development of large-scale oil and gas reservoirs. However, existing studies have not given specific calculation or prediction methods for the conductivity after construction.

[0055] Existing technologies mostly focus on calculating or predicting conductivity for conventional fracturing processes or a single fracturing process. For example, the patent document "A method for predicting conductivity of channel fracturing (201510593843.1)" predicts the conductivity of the proppant by establishing a mechanical model of channel fracturing and determining the required fitting coefficient and equivalent permeability. In the patent document "A method for calculating the initial conductivity of acid-etched fractures (201610051684.7)", the transverse tortuosity ratio and longitudinal tortuosity ratio are calculated by scanning the surface of the acid-etched rock plate, thereby further calculating the initial conductivity of the acid-etched fracture. Methods for calculating the conductivity of channel fracturing for self-supporting fractures and acid-etched fractures are given respectively. However, none of them involve the calculation of conductivity of acid fracturing with proppant, and therefore cannot provide reliable data support for the high-quality implementation of acid fracturing with proppant in complex carbonate reservoirs.

[0056] In summary, patents related to sand-based acid fracturing primarily focus on construction techniques, while patents related to conductivity analysis mainly concentrate on calculating the conductivity of channel fracturing, self-supporting cracks, and acid-etched cracks. However, research on the conductivity of sand-based acid fracturing simulation systems remains lacking and urgently needs further development.

[0057] To address the aforementioned issues, this invention provides a method and system for calculating the conductivity of a sand-fracturing reservoir simulation system. This method, implemented autonomously using a computer system, constructs a set of simulation parameters based on sand-fracturing operation parameters for reservoir types requiring sand fracturing. It analyzes fracture acid etching data from different reservoirs using a pre-defined fracture acid etching calculation model, and analyzes proppant embedding depth and deformation data in conjunction with injection rate parameters and proppant data. Furthermore, it analyzes the sand-fracturing proppant concentration and sets a roughness simulation distribution coefficient based on the injection rate to form a reservoir fracture model representing the actual fracturing state. Based on the roughness simulation distribution coefficient and reservoir closure pressure, it analyzes the permeability state of the reservoir fracture model after fracturing. Finally, it calculates the corresponding conductivity by combining the fracture width analyzed based on fracture acid etching data, proppant embedding depth, and deformation data. This method solves the problem of being unable to quantitatively analyze the conductivity of sand-fracturing, providing support for on-site acid fracturing design and production prediction.

[0058] The following describes the detailed flow of the method according to an embodiment of the present invention with reference to the accompanying drawings, the steps of which can be executed in a computer system containing, for example, a set of computer-executable instructions. Although the logical order of the steps is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0059] Example 1

[0060] Figure 1This diagram illustrates a flow chart of the conductivity calculation method for the sand-adding acid fracturing reservoir simulation system provided in Embodiment 1 of the present invention. (Refer to...) Figure 1 As can be seen, the method includes the following steps.

[0061] The simulation parameter setting steps, combined with historical operation data related to the sand addition acid fracturing process, comprehensively analyze all reservoir types that meet the requirements for sand addition acid fracturing. For each type of reservoir, a set of simulation parameter combinations is constructed around the geological characteristic parameters of acid concentration, acid etching time, proppant type, injection rate and sand addition intensity.

[0062] The fracturing effect analysis steps include: using a preset fracture acid etching calculation model to analyze fracture acid etching data after acid etching of different reservoir types; and then combining injection rate parameters and proppant size data to analyze proppant embedding depth and deformation data.

[0063] In analyzing the acid etching data of fractures after acid etching of different reservoir types, considering that acid etching mainly causes unevenness on the fracture surface, one embodiment adopts the method of establishing a coordinate system on the fracture surface and defining the X, Y and Z directions to represent the length, width and height of the fracture, respectively.

[0064] To describe the morphological differences of rough rock slabs after acid etching, the height change on the crack surface was defined based on the coordinates of various points on the surface, and the changes in the cracks before and after acid etching were quantitatively analyzed:

[0065] ΔZ(X i ,Y j )=Z1(X i ,Y j )-Z2(X i ,Y j )

[0066] In the formula, ΔZ(X) i Y j Z1(X) represents the change in surface height of the acid-etched crack; i Y j ) and Z2(X i Y j The figures () represent the rock heights before and after acid etching, respectively.

[0067] Based on acid etching experimental data from a large number of rock slab samples, an acid etching analysis model was constructed by combining the geological characteristics of the rock slab samples, acid parameters, acid injection settings, and acid etching results data. In the process of analyzing the fracture acid etching data after acid etching of different reservoir types, acid pressure-related parameters were substituted into the model for prediction calculation.

[0068] During the experiment, by introducing two new evaluation parameters—the surface height distribution *hn* and the calculated surface undulation degree *εh*—the undulation trend of the crack surface can be described more intuitively and accurately. Using high-precision 3D scanning graphics and the calculation results of the evaluation parameters, the surface morphology of the crack after acid etching was described. It was found that the acid-etched cracks did not have burr-like protrusions, but the groove and pore structures increased the surface undulation. Based on the calculation of specific crack profiles before and after acid etching, the changes in the height contour line were compared. It was concluded that along the acid flow direction, the protrusions become gentler, the tortuosity decreases, and the undulation degree increases; acid etching forms grooves along the flow direction, and continuous up-and-down fluctuations are formed in the direction perpendicular to the flow direction, resulting in an increase in both the tortuosity and undulation degree.

[0069] Based on this analysis, the effects of different acid types, acid concentrations, injection rates, acid volumes, and other parameters on ΔZ(Xi, Yj) are evaluated to assess the acidification effect.

[0070] The fracturing model establishment steps include: analyzing the sand-laying concentration of acid fracturing based on the fracture acid etching data, proppant embedding depth and deformation data; and setting the height distribution coefficient m and quantity distribution coefficient a of the roughness based on the roughness and the fracturing agent injection rate, so that the randomly distributed roughness with different heights can reflect the reservoir fractures after acid etching and sand fracturing, thus forming a reservoir fracture model that presents the real state of the reservoir fractures after sand fracturing.

[0071] The fracturing permeability analysis steps, based on the height distribution coefficient m and quantity distribution coefficient a of the roughness body, combined with the closure pressure of the reservoir, analyze the permeability state of the reservoir fracture model after fracturing;

[0072] The steps for determining conductivity include analyzing the width data of reservoir fractures after fracturing based on proppant embedding depth and deformation data, calculating the corresponding conductivity data by combining the obtained reservoir fracture permeability, and storing the data in association with the matched fracturing parameters and simulation parameters as a simulation prediction result record.

[0073] To verify the feasibility of the calculation scheme of this invention, technicians designed a comparative verification based on measured conductivity data from a reservoir fracture model of a set scale. Therefore, in one embodiment, the method further includes:

[0074] The experimental verification steps are as follows: a reservoir fracture model of a set scale is selected as the test model, and a sand-addition acid fracturing experiment is performed according to the corresponding simulation parameters. Then, a fluid with the same properties as the reservoir is used for testing to obtain the measured conductivity value. The error between the calculated conductivity value and the measured value is calculated, and the reliability of the calculation results is analyzed.

[0075] In practical applications, the selected test model includes reservoir fracture models corresponding to at least one combination of simulation parameters for all reservoir types. This ensures the comprehensive reliability of the verification results relative to different reservoir types.

[0076] By employing the technical means of the above embodiments of the present invention, the quantitative analysis of the conductivity of the sand-added acid fracturing reservoir simulation system can be effectively realized, saving a large amount of actual measurement procedures and time resources, and improving the analysis efficiency of conductivity during the sand-added acid fracturing reservoir simulation process.

[0077] Furthermore, in one embodiment, the simulation system construction step includes:

[0078] The set of simulation parameters is set as follows: for various types of reservoir rocks, simulation parameters are formulated with each parameter as a unique parameter, and other parameters are kept constant while the unique parameter varies, focusing on acid concentration, acid etching time, proppant type, injection rate and sand addition intensity.

[0079] Specifically, in practical applications, the number of simulation parameter combinations corresponding to various types of reservoir rocks is set to be consistent with the number of simulated samples of sand-fed acid fracturing reservoir fractures, and the initial permeability and initial fracture width of each simulated sample are set according to preset requirements.

[0080] In hydraulic fracturing, proppant has effective fracturing strength. The proppant material, along with the high-pressure solution, enters the formation and fills the rock fractures, laying within the fracture space to prevent the fractures from closing due to stress release. Figure 2 As shown, this maintains high conductivity and has a good effect on increasing oil and gas production. However, during the process, due to various factors, proppant embedding and proppant deformation may occur to some extent, such as... Figure 3 As shown.

[0081] This invention combines a proppant embedding depth calculation method with acid-etched fracture data analysis and fracture permeability calculation methods to calculate the conductivity of reservoir fractures after sand-added acid fracturing.

[0082] Next, by performing the fracturing effect analysis step, the pre-set fracture acid etching calculation model is used to analyze the fracture acid etching data after acid etching of different reservoir types. Then, the embedding depth and deformation data of the proppant are analyzed by combining the injection rate parameters and proppant size data.

[0083] In a preferred embodiment, the proppant embedding depth during fracturing is analyzed according to the following computational model in the fracturing effect analysis step:

[0084]

[0085] In the formula, h represents the embedment depth of the proppant, mm; D represents the initial width of the fracture, mm; D1 represents the reservoir thickness, mm; D2 represents the diameter of the proppant, mm; η1 and η2 represent the viscosity of the proppant and the rock, MPa, respectively; t represents the operation time, days; Pc The set closure pressure of the reservoir is given in MPa; E1 and E2 represent the Young's modulus of the rock and proppant, respectively, in MPa; μ1 and μ2 represent the Poisson's ratio of the rock and proppant, respectively, dimensionless. Where k... f0 P c E1, E2, μ1, and μ2 can be obtained through well logging interpretation and analysis of oil and gas reservoirs or directly measured.

[0086] Furthermore, in one embodiment, in the fracturing effect analysis step, the deformation data of the proppant during fracturing is analyzed according to the following computational model:

[0087]

[0088] In the formula, β represents the deformation of the proppant, mm; D represents the initial width of the crack, mm; E2 represents the Young's modulus of the proppant, MPa; μ2 represents the Poisson's ratio of the proppant, dimensionless; P c The pressure represents the closure pressure of the reservoir, in MPa; t represents the operating time, in days.

[0089] Furthermore, by performing the fracturing model establishment step, the proppant concentration for acid fracturing is analyzed based on the fracture acid etching data and the proppant embedding depth and deformation data. Based on this, and combined with the fracturing agent injection rate, the height distribution coefficient *m* and quantity distribution coefficient *a* of the roughness are set so that the randomly distributed roughness of different heights can reflect the reservoir fractures after acid etching and proppant fracturing, forming a reservoir fracture model that presents the true state of acid fracturing reservoir fractures. Figure 4 As shown.

[0090] In practice, m is typically distributed between 0 and 1, and a is distributed between 0.01 and 0.1. In one embodiment, the relationship between m, a, and the analyzed sand concentration and injection rate is shown in the table below:

[0091]

[0092] Next, the permeability state of the reservoir fracture model after fracturing is analyzed based on the height distribution coefficient m and quantity distribution coefficient a of the roughness body, combined with the closure pressure of the reservoir.

[0093] In one embodiment, during the fracturing permeability analysis step, the permeability of the fracture after acid fracturing with added sand is analyzed according to the computational model described in the following formula:

[0094]

[0095]

[0096]

[0097]

[0098] In the formula: k f The permeability of the fracture is expressed in μm. 2 ;k f0 The initial permeability of the fracture is expressed in μm. 2 ;P c P1 represents the reservoir closure pressure (MPa); P2 represents the effective modulus of the roughness (MPa); m represents the height distribution coefficient of the roughness (dimensionless); a represents the quantity distribution coefficient of the roughness (dimensionless); BM1 represents the bulk modulus of the rock after acid etching (MPa); BM2 represents the bulk modulus of the proppant (MPa); E1 and E2 represent the Young's modulus of the rock and proppant, respectively (MPa); μ1 and μ2 represent the Poisson's ratio of the rock and proppant, respectively (dimensionless); λ1 and λ2 represent the degree of influence of acid on the Young's modulus and Poisson's ratio of the rock, respectively (dimensionless).

[0099] Furthermore, by performing the conductivity determination step, the width data of the reservoir fracture after fracturing is analyzed based on the proppant embedding depth and deformation data. The corresponding conductivity data is calculated by combining the obtained reservoir fracture permeability. This data is then associated with the matching fracturing parameters and simulation parameters and stored as a simulation prediction result record.

[0100] Specifically, in one embodiment, in the flow capacity determination step, the crack width W after sand-addition acid fracturing is analyzed according to the following computational model:

[0101] W = D - 2(β + h)

[0102] In the formula, β represents the deformation of the proppant, mm; D represents the initial width of the crack, mm; and h represents the embedding depth of the proppant, mm.

[0103] Furthermore, in one embodiment, in the conductivity determination step, the corresponding conductivity is calculated based on the permeability and width data of the reservoir fractures after fracturing, according to the following formula:

[0104] F RCD =k f *W

[0105] In the formula, F RCD D.cm; k represents the conductivity of reservoir fractures after acid fracturing with sand addition. f The permeability of the fracture is expressed in μm. 2 W represents the crack width after acid fracturing with sand, in mm.

[0106] For carbonate oil and gas reservoirs with deep burial, high formation temperature, and high formation closure pressure, conventional acid fracturing is often ineffective. Therefore, proppant-assisted acid fracturing has emerged, combining the advantages of proppant fracturing and acid fracturing to significantly improve the stimulation effect. However, currently, there is no established calculation and prediction method for conductivity, a crucial parameter for evaluating fracturing effectiveness.

[0107] According to the conductivity calculation scheme of the sand-adding acid fracturing reservoir simulation system provided in the above embodiments of the present invention, it is possible to simulate and present the sand-adding acid fracturing process for different reservoirs with sand-adding acid fracturing requirements and realize conductivity prediction calculation. The calculation results are highly reliable and can provide reliable data support for the implementation of sand-adding acid fracturing operations in the target reservoir. It helps to select the best fracturing construction parameters in practical applications and obtain the fracturing fracture with the best conductivity, thereby promoting the quality of fracturing operations and increasing the output of production operations.

[0108] Implementation Case:

[0109] Example 1: Well A in Northwest China, with a drilling flow rate of 10 m³ / min and a sand concentration of 1.5 kg / m³. 2 The proppant type is 20 / 40 mesh, and the results are compared with the model calculation results through indoor experiments.

[0110] Based on the reservoir condition and construction data of well A, the following steps are used to simulate acid fracturing with sand addition and predict the conductivity:

[0111] The simulation parameter setting steps involve constructing a set of simulation parameter combinations based on the geological characteristics of reservoir A, including the possible acid concentration, acid etching time, proppant type, injection rate, and sand addition intensity.

[0112] The fracturing effect analysis steps include: using a preset fracture acid etching calculation model to analyze the fracture acid etching data after acid etching; and then combining the injection rate parameters and proppant size data to analyze the proppant embedding depth and deformation data.

[0113] The fracturing model establishment steps include: analyzing the sand-laying concentration of acid fracturing based on the fracture acid etching data, proppant embedding depth and deformation data, and setting the height distribution coefficient m and coefficient a of the roughness based on it and the fracturing agent injection rate, so that the randomly distributed roughness of different heights can reflect the reservoir fractures after acid etching and sand fracturing, thus forming a reservoir fracture model that presents the real state of reservoir fractures after sand fracturing.

[0114] The steps of fracturing permeability analysis include analyzing the permeability state of the reservoir fracture model after fracturing based on the height distribution coefficient m and coefficient a of the rough body combined with the reservoir closure pressure.

[0115] The steps for determining conductivity include analyzing the width data of reservoir fractures after fracturing based on proppant embedding depth and deformation data, calculating the corresponding conductivity data by combining the obtained reservoir fracture permeability, and storing the data in association with the matched fracturing parameters and simulation parameters as a simulation prediction result record.

[0116] Based on the relationship between the engineering parameters and m and a, m is taken as 0.81 and a is taken as 0.08.

[0117] Figure 5 The experimental data and model data are compared. As can be seen from the figure, the data calculated by the model are in high agreement with the experimental data, indicating that the results of the model calculation are highly reliable.

[0118] Additionally, the table below shows the results when the sand concentration is 1.5 kg / m³. 2 The conductivity calculated by the model based on the experimental determination of 20 / 40 mesh proppant under different closure pressures can be seen from the table. It can be seen that the conductivity calculated by the calculation model provided in this invention has an error of less than 10%, which can provide data support that meets the requirements of authenticity.

[0119]

[0120] Example 2: Well B in Northwest China, with a construction displacement of 10m³. 3 / min, sand concentration is 1.5kg / m 2 The proppant type is 40 / 70 mesh, and the results are compared with the model calculation results through indoor experiments.

[0121] Based on the reservoir condition and construction data of well B, the following steps are used to simulate acid fracturing with sand and predict the conductivity:

[0122] The simulation parameter setting steps involve constructing a set of simulation parameter combinations based on the geological characteristics of the B reservoir, including the possible acid concentration, acid etching time, proppant type, injection rate, and sand addition intensity.

[0123] The fracturing effect analysis steps include: using a preset fracture acid etching calculation model to analyze the fracture acid etching data after acid etching; and then combining the injection rate parameters and proppant size data to analyze the proppant embedding depth and deformation data.

[0124] The fracturing model establishment steps include: analyzing the sand-laying concentration of acid fracturing based on the fracture acid etching data, proppant embedding depth and deformation data, and setting the height distribution coefficient m and coefficient a of the roughness based on it and the fracturing agent injection rate, so that the randomly distributed roughness of different heights can reflect the reservoir fractures after acid etching and sand fracturing, thus forming a reservoir fracture model that presents the real state of reservoir fractures after sand fracturing.

[0125] The steps of fracturing permeability analysis include analyzing the permeability state of the reservoir fracture model after fracturing based on the height distribution coefficient m and coefficient a of the rough body combined with the closure pressure of the reservoir.

[0126] The steps for determining conductivity include analyzing the width data of reservoir fractures after fracturing based on proppant embedding depth and deformation data, calculating the corresponding conductivity data by combining the obtained reservoir fracture permeability, and storing the data in association with the matched fracturing parameters and simulation parameters as a simulation prediction result record.

[0127] Based on the relationship between the engineering parameters and m and a, m is taken as 0.85 and a is taken as 0.05. Figure 6 The experimental data and model data are compared. As can be seen from the figure, the data calculated by the model are in high agreement with the experimental data, indicating that the results of the model calculation are highly reliable.

[0128] The table below shows the results when the sand concentration is 1.5 kg / m³. 2 The conductivity calculated by the model was determined by experiments using 40 / 70 mesh proppant under different closure pressures. As can be seen from the table, the error of the conductivity calculated by the model is within 10%.

[0129]

[0130] For the foregoing method embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0131] It should be noted that, in other embodiments of the present invention, the method can also combine one or more of the above embodiments to obtain a new method for calculating the conductivity of a sand-added acid fracturing reservoir simulation system, so as to realize the optimization simulation study of the sand-added acid fracturing process.

[0132] It should be noted that, based on the methods in any one or more embodiments of the present invention above, the present invention also provides a storage medium storing program code that can implement the methods described in any one or more embodiments above. When the program code is executed by the operating system, it can implement the flow capacity calculation method of the sand-adding acid fracturing reservoir simulation system as described above.

[0133] Example 2

[0134] The methods described in detail in the above-disclosed embodiments of the present invention can be implemented using various forms of devices or systems. Therefore, based on other aspects of the methods described in any one or more of the above embodiments, the present invention also provides a conductivity calculation system for a sand-added acid fracturing reservoir simulation system. This system is used to execute the conductivity calculation method for the sand-added acid fracturing reservoir simulation system described in any one or more of the above embodiments. Specific embodiments are given below for detailed description.

[0135] Specifically, Figure 7 The diagram shows a schematic of the conductivity calculation system of the sand-adding acid fracturing reservoir simulation system provided in an embodiment of the present invention. Figure 7 As shown, the system includes:

[0136] The simulation parameter setting module is configured to comprehensively analyze all reservoir types that require sand fracturing by combining historical operation data related to the sand fracturing process. It constructs a set of simulation parameters for each type of reservoir, focusing on the geological characteristic parameters such as acid concentration, acid etching time, proppant type, injection rate, and sand fracturing intensity.

[0137] The fracturing effect analysis module is configured to use a preset fracture acid etching calculation model to analyze fracture acid etching data after acid etching of different reservoir types, and then combine injection rate parameters and proppant size data to analyze proppant embedding depth and deformation data.

[0138] The fracturing model building module is configured to analyze the sand-laying concentration of acid fracturing based on the fracture acid etching data, proppant embedding depth and deformation data, and set the height distribution coefficient m and quantity distribution coefficient a of the roughness based on it and the fracturing agent injection rate, so that the randomly distributed roughness of different heights can reflect the reservoir fractures after acid etching and sand fracturing, and form a reservoir fracture model that presents the real state of the reservoir fractures after sand fracturing.

[0139] The fracturing permeability analysis module is configured to analyze the permeability state of the reservoir fracture model after fracturing based on the height distribution coefficient m and quantity distribution coefficient a of the roughness body combined with the closure pressure of the reservoir.

[0140] The conductivity determination module is configured to analyze the width data of reservoir fractures after fracturing based on fracture acid etching data, proppant embedding depth and deformation data, calculate the corresponding conductivity data in combination with the obtained reservoir fracture permeability, and store the data as a simulation prediction result in association with the matched fracturing parameters and simulation parameters.

[0141] Furthermore, in one embodiment, the system further includes:

[0142] The experimental verification module is configured to select a portion of the reservoir fracture model as the test model, perform a sand-addition acid fracturing experiment according to the corresponding simulation parameters, and then use a fluid with the same properties as the reservoir to test and obtain the measured conductivity value. The error between the calculated conductivity value and the measured value is calculated, and the reliability of the calculation results is analyzed.

[0143] As a further improvement of the present invention, in one embodiment, the simulation system construction module is configured as follows:

[0144] The set of simulation parameters is as follows: for various types of reservoir rocks, simulation parameter combinations are formulated with each parameter as a unique parameter, and other parameters are kept constant while the unique parameter changes, focusing on acid concentration, acid etching time, proppant type, injection rate and sand addition intensity.

[0145] Furthermore, in a preferred embodiment, the system sets the number of simulation parameter combinations corresponding to various types of reservoir rocks to be consistent with the number of simulated samples of sand-fed acid fracturing reservoir fractures, and sets the initial permeability and initial fracture width of each simulated sample according to preset requirements.

[0146] In an optional embodiment, the fracturing effect analysis module is configured to analyze the proppant embedding depth during fracturing according to the following computational model:

[0147]

[0148] In the formula, h represents the embedment depth of the proppant, mm; D represents the initial width of the fracture, mm; D1 represents the reservoir thickness, mm; D2 represents the diameter of the proppant, mm; η1 and η2 represent the viscosity of the proppant and the rock, MPa, respectively; t represents the operation time, days; P c E1 represents the closure pressure of the reservoir, MPa; E2 represents the Young's modulus of the rock and proppant, MPa, respectively; μ1 and μ2 represent the Poisson's ratio of the rock and proppant, respectively, dimensionless.

[0149] Furthermore, in one embodiment, the fracturing effect analysis module is configured to analyze the deformation data of the proppant during fracturing according to the following computational model:

[0150]

[0151] In the formula, β represents the deformation of the proppant, mm; D represents the initial width of the crack, mm; E2 represents the Young's modulus of the proppant, MPa; μ2 represents the Poisson's ratio of the proppant, dimensionless; P c The pressure represents the closure pressure of the reservoir, in MPa; t represents the operating time, in days.

[0152] Specifically, in one embodiment, the fracturing permeability analysis module is configured to analyze the permeability of the fracture after acid fracturing using the following formula:

[0153]

[0154]

[0155]

[0156]

[0157] In the formula: k f The permeability of the fracture is expressed in μm. 2 ;k f0 The initial permeability of the fracture is expressed in μm. 2 ;P c P1 represents the reservoir closure pressure (MPa); P2 represents the effective modulus of the roughness (MPa); m represents the height distribution coefficient of the roughness (dimensionless); a represents the quantity distribution coefficient of the roughness (dimensionless); BM1 represents the bulk modulus of the rock after acid etching (MPa); BM2 represents the bulk modulus of the proppant (MPa); E1 and E2 represent the Young's modulus of the rock and proppant, respectively (MPa); μ1 and μ2 represent the Poisson's ratio of the rock and proppant, respectively (dimensionless); λ1 and λ2 represent the degree of influence of acid on the Young's modulus and Poisson's ratio of the rock, respectively (dimensionless).

[0158] Furthermore, in one embodiment, the flow-guiding capacity determination module is configured to analyze the crack width W after sand-addition acid fracturing according to the following computational model:

[0159] W = D - 2(β + h)

[0160] In the formula, β represents the deformation of the proppant, mm; D represents the initial width of the crack, mm; and h represents the embedding depth of the proppant, mm.

[0161] Specifically, in one embodiment, the conductivity determination module is further configured to: calculate the corresponding conductivity based on the permeability and width data of the reservoir fractures after fracturing, according to the following formula:

[0162] F RCD =k f *W

[0163] In the formula, F RCD D.cm; k represents the conductivity of reservoir fractures after acid fracturing with sand addition. f The permeability of the fracture is expressed in μm. 2 W represents the crack width after acid fracturing with sand, in mm.

[0164] In the flow capacity calculation system of the sand-adding acid fracturing reservoir simulation system provided in this embodiment of the invention, each module or unit structure can run independently or in combination according to the simulation settings and calculation requirements to achieve the corresponding technical effects.

[0165] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps, or materials disclosed herein, but should be extended to equivalent substitutions of these features as understood by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0166] The phrase "an embodiment" in the specification means that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Therefore, the phrase "an embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0167] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for calculating the conductivity of a sand-added acid fracturing reservoir simulation system, characterized in that, The method includes: Simulation parameter setting steps: Combine historical operation data related to the sand-adding acid fracturing process to comprehensively analyze all reservoir types that require sand-adding acid fracturing, and construct simulation parameter sets for each type of reservoir based on geological characteristic parameters such as acid concentration, acid etching time, proppant type, injection rate and sand addition intensity; Fracturing effect analysis steps: Analyze the fracture acid etching data after acid etching of different reservoir types using a preset fracture acid etching calculation model, and then analyze the embedding depth and deformation data of the proppant by combining the injection rate parameters and proppant size data. The steps for establishing the fracturing model are as follows: Based on the fracture acid etching data and the proppant embedding depth and deformation data, the sand-laying concentration of the acid fracturing is analyzed, and the height distribution coefficient and quantity distribution coefficient of the roughness are set based on it and the fracturing agent injection rate, so that the randomly distributed roughness of different heights can reflect the reservoir fractures after acid etching and sand fracturing, thus forming a reservoir fracture model that presents the real state of the reservoir fractures after sand fracturing. Fracturing permeability analysis steps: Based on the height distribution coefficient and quantity distribution coefficient of the roughness body combined with the reservoir closure pressure, analyze the permeability state of the reservoir fracture model after fracturing; Steps for determining conductivity: Analyze the width data of reservoir fractures after fracturing based on fracture acid etching data, proppant embedding depth and deformation data, and then calculate the product with the obtained reservoir fracture permeability as the conductivity data. This data is then associated with the matching fracturing parameters and simulation parameters and stored as a simulation prediction result record. In the fracturing effect analysis step, the proppant embedding depth during fracturing is analyzed according to the following calculation model: In the fracturing effect analysis step, the deformation data of the proppant during fracturing is analyzed according to the following calculation model: ； In the fracturing permeability analysis step, the permeability of the fracture after sand-addition acid fracturing is analyzed according to the calculation model described in the following formula: ； In the step of determining the conductivity, the crack width W after sand-addition acid fracturing is analyzed according to the following calculation model: ； In the formula, h represents the embedment depth of the proppant, mm; D represents the initial width of the fracture, mm; D1 represents the reservoir thickness, mm; D2 represents the diameter of the proppant, mm; η1 and η2 represent the viscosity of the proppant and the rock, MPa, respectively; t represents the operation time, days; P c E1 represents the closure pressure of the reservoir, in MPa; E2 represents the Young's modulus of the rock and the Young's modulus of the proppant; μ1 and μ2 represent the Poisson's ratios of the rock and the proppant, respectively; β represents the deformation of the proppant, in mm. k f The permeability of the fracture is expressed in μm. 2 ; k f0 The initial permeability of the fracture is expressed in μm. 2 ; P 1 represents the effective modulus of the roughness, MPa; m represents the height distribution coefficient of the roughness, dimensionless.

2. The method according to claim 1, characterized in that, The method further includes: Verification steps: Select a reservoir fracture model of a set scale as the test model, perform a sand-addition acid fracturing experiment according to the corresponding simulation parameters, and use a fluid with the same properties as the reservoir to test and obtain the measured conductivity value. Calculate the error between the calculated conductivity value and the measured value, and analyze the reliability of the calculation results.

3. The method according to claim 1, characterized in that, The steps in building a simulation system include: The set of simulation parameters is as follows: for various types of reservoir rocks, simulation parameter combinations are formulated with each parameter as a unique parameter, and other parameters are kept constant while the unique parameter changes, focusing on acid concentration, acid etching time, proppant type, injection rate and sand addition intensity.

4. The method according to claim 1, characterized in that, The number of simulation parameter combinations corresponding to various types of reservoir rocks is consistent with the number of simulated samples of sand-fed acid fracturing reservoir fractures. The initial permeability and initial fracture width of each simulated sample are set according to preset requirements.

5. The method according to claim 1, characterized in that, In the permeability analysis step of fracturing, during the analysis of the permeability of the fracture after acid fracturing with sand: ； ； ； In the formula: a This represents the quantity distribution coefficient of roughness, and is dimensionless. BM1 represents the bulk modulus of the rock after acid etching, in MPa; BM2 represents the bulk modulus of the proppant, in MPa; E1 and E2 represent the Young's modulus of the rock and the proppant, respectively, in MPa; μ1 and μ2 represent the Poisson's ratio of the rock and the proppant, respectively, dimensionless; λ1 and λ2 represent the degree of influence of the acid on the Young's modulus and Poisson's ratio of the rock, respectively, dimensionless.

6. The method according to claim 1, characterized in that, In the conductivity determination step, the conductivity is calculated based on the permeability and width data of the reservoir fractures after fracturing, according to the following formula: ； In the formula, D.cm represents the conductivity of reservoir fractures after acid fracturing with sand addition. kf The permeability of the fracture is expressed in μm. 2 W represents the crack width after acid fracturing with sand, in mm.

7. A system for calculating the conductivity of a sand-added acid fracturing reservoir simulation system, characterized in that, The system performs the method as described in any one of claims 1 to 6.

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