Method for predicting microseismic magnitude induced by geothermal reservoir fracture slip

Abstract

The application provides a method for predicting microseismic magnitude induced by fracture slip of a geothermal reservoir. The method comprises: determining a plurality of sets of injection parameters for fluid injection into a fracture of a rock and a first stiffness of the rock, the fracture of the rock being in a critical slip state; determining a slip displacement corresponding to each set of injection parameters, a first area of the fracture, and a first energy generated, the first energy being acoustic emission energy generated by the slip; determining a first seismic moment corresponding to each set of injection parameters based on the first stiffness, the first area, and the slip displacement; and determining a seismic model between the injection parameters and the seismic moment based on a plurality of first energies and a plurality of first seismic moments. In this way, the accuracy of the microseismic magnitude prediction model for reservoir reconstruction of a hot dry rock enhanced geothermal system can be improved.

Description

Technical Field

[0001] This application relates to the field of deep geothermal development technology, and in particular to a method for predicting the magnitude of microseismic events induced by fracture slippage in geothermal reservoirs. Background Technology

[0002] In the development of Enhanced Geothermal Systems (EGS), fluids are injected into underground reservoirs to fracturate the rock mass, creating a complex network of fractures that improves reservoir permeability and establishes underground circulation channels.

[0003] Currently, the relationship between fluid injection and microseismic activity can be studied by combining indoor experiments with field monitoring. However, the accuracy of microseismic magnitude prediction models during reservoir stimulation in hot dry rock enhanced geothermal systems remains a concern. Summary of the Invention

[0004] This application provides a method for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs, which addresses the problem of low accuracy in microseismic magnitude prediction models during reservoir stimulation in hot dry rock enhanced geothermal systems.

[0005] In a first aspect, embodiments of this application provide a method for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs. This method includes:

[0006] Multiple sets of injection parameters and the first stiffness of the rock were determined for fluid injection into the rock fractures, and the rock fractures were in a critical slip state.

[0007] Determine the slip displacement, the first area of ​​the crack, and the first energy generated for each set of injection parameters. The first energy is the acoustic emission energy generated by the slip.

[0008] Based on the first stiffness, the first area, and the slip displacement, determine the first seismic moment corresponding to each group of injection parameters;

[0009] Based on multiple sets of injection parameters and the first seismic moment corresponding to each set of injection parameters, a seismic model between injection parameters and seismic moment is established.

[0010] The earthquake model is validated based on multiple first energies and multiple first seismic moments.

[0011] According to one or more embodiments of this application, a seismic model is determined based on multiple first energies and multiple first seismic moments, including:

[0012] Based on multiple first energies and multiple first seismic moments, the first correlation between acoustic emission energy and seismic moment is determined;

[0013] Based on the first correlation, the earthquake model is validated.

[0014] According to one or more embodiments of this application, a seismic model is determined based on multiple sets of injection parameters and a first correlation relationship, including:

[0015] Based on the first energy corresponding to each group of injection parameters and the first correlation relationship, the second seismic moment corresponding to the first energy corresponding to each group of injection parameters is determined.

[0016] Multiple injection parameters are input into the seismic model to obtain the third seismic moment corresponding to each injection parameter;

[0017] The earthquake model is validated based on the second seismic moment corresponding to the first energy of each group of injection parameters, and the third seismic moment corresponding to multiple injection parameters.

[0018] According to one or more embodiments of this application, a first correlation relationship between acoustic emission energy and seismic moment is determined based on a plurality of first energies and a plurality of first seismic moments, including:

[0019] Determine the initial correlation between the first energy and the seismic moment, including the first weight and the first correction parameter;

[0020] Based on each first energy and the first seismic moment corresponding to each first energy, the first weight is fitted to obtain the second weight, and the first correction parameter is fitted to obtain the second correction parameter;

[0021] The first association relationship is determined based on the second weight and the second correction parameter.

[0022] According to one or more embodiments of this application, for any set of injection parameters, determining the first energy corresponding to each set of injection parameters includes:

[0023] Acquire acoustic emission events during each slip of the crack;

[0024] Based on acoustic emission events, the voltage information corresponding to each slip of the crack is determined. The voltage information is used to indicate the voltage signal that changes over time when an acoustic emission event occurs.

[0025] The first energy is determined based on the voltage information.

[0026] According to one or more embodiments of this application, the method further includes:

[0027] Obtain the target injection parameters, which are used to inject fluid into the rock mass of the underground reservoir;

[0028] Input the target injection parameters into the seismic model to obtain the target seismic moment;

[0029] Based on the target seismic moment, the magnitude of the underground reservoir is determined. The magnitude is the predicted magnitude of the underground reservoir when fluid is injected into the rock based on the target injection parameters.

[0030] Secondly, embodiments of this application provide a device for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs. This device includes a first determining module, a second determining module, a third determining module, a fourth determining module, and a verification module, wherein:

[0031] The first determining module is used to determine multiple sets of injection parameters for fluid injection into the rock fractures and the first stiffness of the rock, where the rock fractures are in a critical slip state.

[0032] The second determining module is used to determine the slip displacement, the first area of ​​the crack and the first energy generated corresponding to each group of injection parameters, wherein the first energy is the acoustic emission energy generated by the slip.

[0033] The third determining module is used to determine the first seismic moment corresponding to each group of injection parameters based on the first stiffness, the first area, and the slip displacement.

[0034] The fourth determination module is used to determine the seismic model between the injection parameters and the seismic moment based on multiple first energies and multiple first seismic moments;

[0035] The verification module is used to verify the earthquake model based on multiple first energies and multiple first seismic moments.

[0036] Thirdly, embodiments of this application provide a terminal device, including:

[0037] At least one processor and memory;

[0038] The memory stores the instructions that the computer executes;

[0039] At least one processor executes computer execution instructions stored in memory, causing at least one processor to perform the first aspect above and various possible methods for predicting the magnitude of microseismic events induced by fracture slippage in geothermal reservoirs.

[0040] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions. When a processor executes the computer-executable instructions, it implements the first aspect above and various possible methods for predicting the magnitude of microseismic events induced by fracture slippage in geothermal reservoirs.

[0041] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect above and various possible methods for predicting the magnitude of microseismic events induced by fracture slippage in geothermal reservoirs.

[0042] This application provides a method, apparatus, and terminal device for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs. The terminal device can determine multiple sets of injection parameters for fluid injection into rock fractures and the rock's first stiffness, wherein the rock fractures are in a critical slip state. The terminal device can determine the slip displacement, the first area of ​​the fracture, and the first energy generated corresponding to each set of injection parameters, where the first energy is the acoustic emission energy generated by the slip. Based on the first stiffness, first area, and slip displacement, the terminal device can determine the first seismic moment corresponding to each set of injection parameters. Based on multiple first energies and multiple first seismic moments, the terminal device can determine a seismic model relating the injection parameters and the seismic moment. In this method, because the terminal device can establish the relationship between injection parameters and microseismic magnitude, the accuracy of the microseismic magnitude prediction model during reservoir stimulation in hot dry rock enhanced geothermal systems can be improved. Attached Figure Description

[0043] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0044] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0045] Figure 2 A flowchart illustrating a method for predicting the magnitude of microseismic events induced by fracture slip in a geothermal reservoir, provided as an embodiment of this application;

[0046] Figure 3 A flowchart illustrating a method for determining the first energy corresponding to injection parameters, provided in an embodiment of this application;

[0047] Figure 4 A schematic diagram of a process for determining the magnitude of an underground reservoir, provided as an embodiment of this application;

[0048] Figure 5 A schematic diagram of a geothermal reservoir fracture slip-induced microseismic magnitude prediction device provided in this application embodiment;

[0049] Figure 6 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application.

[0050] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0051] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0052] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0053] In related technologies, when conducting reservoir stimulation of hot dry rock enhanced geothermal systems, terminal equipment can study the relationship between fluid injection and microseismic activity through a combination of indoor experiments and field monitoring. Currently, terminal equipment can simulate fracture slip behavior through triaxial shear experiments and obtain energy release information through acoustic emission monitoring systems to analyze the correlation between fracture slip and microseismic activity. For example, some studies have established empirical relationships between fracture slip and energy release by measuring fracture slip displacement and the number of acoustic emission events. However, these methods do not establish a direct correlation between injection parameters (such as pressure, displacement, number of cycles, temperature, etc.) and microseismic magnitude, resulting in low accuracy in predicting microseismic magnitude. Related technologies often use empirical models or statistical methods to correlate fracture slip behavior with microseismic magnitude, but the accuracy of these models is relatively low.

[0054] To address the technical problems in related technologies, this application provides a method for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs. The terminal device can determine multiple sets of injection parameters for fluid injection into rock fractures and the first stiffness of the rock, wherein the rock fractures are in a critical slip state. The terminal device can determine the slip displacement, the first area of ​​the fracture, and the first energy generated corresponding to each set of injection parameters, wherein the first energy is the acoustic emission energy generated by the slip. Based on the first stiffness, the first area, and the slip displacement, the terminal device can determine the first seismic moment corresponding to each set of injection parameters. Based on multiple first energies and multiple first seismic moments, the terminal device can determine a first correlation between acoustic emission energy and seismic moment. Based on multiple sets of injection parameters and the first correlation, the terminal device can determine a seismic model. Based on the first energy corresponding to each set of injection parameters and the first correlation, the terminal device can determine a second seismic moment corresponding to each set of injection parameters. Based on multiple sets of injection parameters and multiple second seismic moments, the terminal device can fit the seismic model.

[0055] In this way, since the terminal equipment can establish models from injection parameters to fracture slip behavior, then to acoustic emission energy, and finally to seismic moment, the accuracy of the model can be improved, thereby improving the accuracy of the microseismic magnitude prediction model during reservoir stimulation of hot dry rock enhanced geothermal systems.

[0056] Below, in conjunction with Figure 1 The application scenarios of the embodiments of this application will be described.

[0057] Figure 1 This is a schematic diagram illustrating an application scenario provided by an embodiment of this application. Please refer to [link / reference]. Figure 1 The system includes a high-temperature, high-pressure triaxial seepage experimental setup, a fluid injection device, an acoustic emission signal acquisition device, and a fracture slip displacement sensor. The high-temperature, high-pressure triaxial seepage experimental setup can apply confining pressure and axial stress to simulate the temperature and pressure environment of deep rock masses, bringing fractures to a critical slip state, and simulating actual reservoir conditions through fluid saturation treatment. The terminal equipment can control the fluid injection device to inject fluid in a cyclic injection mode and record different injection parameters (pressure, displacement, number of cycles, temperature, etc.). The acoustic emission signal acquisition device can collect acoustic emission signals during fracture slip in real time for subsequent acoustic emission energy calculation. The fracture slip displacement sensor can detect fracture slip displacement in real time.

[0058] It should be noted that, Figure 1 This is an example of an application scenario for the embodiments of this application, and is not intended to limit the application scenario of the embodiments of this application. The terminal device may also use other methods to predict the magnitude of microseismic events, and the embodiments of this application do not limit this.

[0059] Figure 2 A flowchart illustrating a method for predicting the magnitude of microseismic events induced by fracture slip in a geothermal reservoir, provided in this application embodiment, can be found in the attached diagram. Figure 2 The method may include:

[0060] S201. Determine multiple sets of injection parameters for fluid injection into the cracks of the rock and the first stiffness of the rock.

[0061] In some embodiments, the terminal device can apply confining pressure and axial stress to the rock sample by controlling a high-temperature and high-pressure triaxial seepage experimental device, and perform fluid saturation treatment to bring the crack to a state close to the critical slip.

[0062] Confining pressure can generate normal stress on the crack, "pressing" the two sides of the crack together to resist slippage. Axial stress can be decomposed into a shear stress component on the crack surface, which can drive the crack to slide.

[0063] The confining pressure and axial stress satisfy the following formula:

[0064] ;

[0065] ;

[0066] in, For shear stress, For axial stress, For confining pressure, For the total normal stress, Axial stress With total normal stress The included angle.

[0067] The injection parameters can be parameters used by the fluid injection device during fluid injection. For example, injection parameters may include pressure P, displacement Q, number of cycles N, and temperature T. For instance, when the rock is granite, while keeping the confining pressure and axial stress constant, the terminal equipment can control the fluid injection device to perform the fluid injection process and record the injection pressure P as 20.0 MPa, the injection displacement Q as 12 m³ / min, the number of cycles N as 5, and the temperature T as 180°C. This application does not limit these parameters.

[0068] The first stiffness can be used to indicate the stiffness of the rock mass. For example, the first stiffness can be the rock mass shear modulus. For example, when the rock is granite, the rock mass shear modulus of granite can be 20 GPa. The embodiments of this application do not limit this.

[0069] The fluid saturation treatment can be a process in which a terminal device controls a fluid injection device to inject a target fluid (distilled water) into a rock sample containing pre-fabricated fractures, so that it completely fills the pores and fracture spaces of the rock. This application does not limit this process.

[0070] Axial stress and pore pressure within the crack satisfy the following formula:

[0071] ;

[0072] in, For frictional strength, The coefficient of friction, This refers to the pore pressure within the crack.

[0073] It should be noted that the critical slip state can be the state in which rock fractures do not slip when the frictional strength equals the shear stress.

[0074] S202. Determine the slip displacement, the first area of ​​the crack, and the first energy generated corresponding to each group of injection parameters.

[0075] In some embodiments, the terminal device can monitor crack slip displacement in real time using a crack slip displacement sensor. For example, during a single fluid injection process, the terminal device records in real time that the crack has slipped by 5.0 × 10⁻⁻⁻⁶ cm⁻¹. 5 The slip displacement m. This application does not limit this aspect in its embodiments.

[0076] The first area can be used to indicate the crack area of ​​the prepared rock sample. For example, when the rock is granite, the terminal device can determine the crack area of ​​the granite to be 5.0 × 10⁻³ m² during sampling. This application does not limit this aspect.

[0077] The first energy can be used to indicate the intensity of energy release during rock fracture slippage. For example, the first energy can be the acoustic emission energy. For instance, when the rock is granite, the acoustic emission energy can be 3.16 × 10⁻⁶. 6 J. The embodiments in this application are not limited in this respect.

[0078] S203. Based on the first stiffness, the first area, and the slip displacement, determine the first seismic moment corresponding to each group of injection parameters.

[0079] The first seismic moment can be used to characterize the elastic strain energy level released during crack slippage. For example, when the rock is granite, the seismic moment during granite crack slippage is 1.0 × 10⁻⁶. 4 N·m. This application does not limit the scope of the embodiments.

[0080] In some embodiments, the first stiffness, the first area, and the slip displacement satisfy the following formula:

[0081] M0 = μAD;

[0082] Where M0 is the seismic moment (N·m), μ is the rock mass shear modulus, A is the crack area (m²), and D is the average slip displacement (m).

[0083] For example, the crack area of ​​the granite is A = 0.01 m², and the slip displacement is 5.0 × 10⁻ 5 m, the rock mass shear modulus μ is 2.0×10¹ 0 When Pa, substituting into the above formula, the seismic moment M0 is calculated to be 1.0 × 10⁻⁶. 4 N·m. This application does not limit the scope of the embodiments.

[0084] S204. Based on multiple sets of injection parameters and the first seismic moment corresponding to each set of injection parameters, a seismic model between the injection parameters and the seismic moment is established.

[0085] The seismic model can be expressed as a conversion formula between injection parameters (pressure P, displacement Q, number of cycles N, and temperature T) and seismic moment.

[0086] In some embodiments, the injection parameters and the seismic moment satisfy the following formula:

[0087] M0=f(P,Q,N,T);

[0088] This can be further written as an empirical model:

[0089] M0=aln(P)+bln(Q)+cln(N)+dT+C;

[0090] Where M0 is the seismic moment (N·m), P is the injection pressure (MPa); Q is the injection rate (m³ / min); N is the number of cycles; T is the temperature (°C); a, b, c, d are experimental fitting coefficients, and C is a constant term.

[0091] For example:

[0092] The first set of injection parameters are: injection pressure P = 20.0 MPa, injection flow rate Q = 3.0 m³ / min, number of cycles N = 5, temperature T = 150℃, and first seismic moment = 2.30e4 N•m.

[0093] The second set of injection parameters are: injection pressure P = 30.0 MPa, injection flow rate Q = 4.5 m³ / min, number of cycles N = 8, temperature T = 180℃, and first seismic moment = 2.82e4 N•m.

[0094] The third set of injection parameters are: injection pressure P = 40.0 MPa, injection flow rate Q = 6.0 m³ / min, number of cycles N = 12, temperature T = 200℃, and first seismic moment = 3.37e4 N•m.

[0095] The fourth set of injection parameters are: injection pressure P = 25.0 MPa, injection flow rate Q = 5.0 m³ / min, number of cycles N = 10, temperature T = 170℃, and first seismic moment = 3.16e4 N•m.

[0096] The fifth set of injection parameters are: injection pressure P = 35.0 MPa, injection flow rate Q = 7.0 m³ / min, number of cycles N = 15, temperature T = 190℃, and first seismic moment = 3.72e4 N•m.

[0097] It should be noted that the injection parameters in this embodiment are applicable to the flexible circulation injection stimulation scenario of large-scale dry hot rock reservoirs with a burial depth of 3000~5000m. If it is a test well / small-scale reservoir, the discharge rate can be adjusted appropriately.

[0098] The terminal device can take the natural logarithm of the independent variables P, Q, and N, and then combine it with T and a constant term to fit the dependent variable M0, obtaining a set of coefficients: a = 1.12 × 10⁻⁶. 4b is 8.45 × 10³, c is 2.31 × 10³, d is 5.01 × 10¹, and C (the constant term) is -4.82 × 10¹. 4 This application does not limit the scope of the embodiments.

[0099] At this point, the empirical model can be expressed as:

[0100] ;

[0101] Where M0 is the seismic moment (N·m), P is the injection pressure (MPa), Q is the injection flow rate (m³ / min), N is the number of cycles, and T is the temperature (°C).

[0102] S205. The earthquake model is validated based on multiple first energies and multiple first seismic moments.

[0103] In some embodiments, the terminal device can determine the seismic model between the injected parameters and the seismic moment based on the following feasible implementation: determining a first correlation between acoustic emission energy and seismic moment based on multiple first energies and multiple first seismic moments; and validating the seismic model based on the first correlation. This can improve the accuracy of the microseismic magnitude prediction model during reservoir stimulation in hot dry rock enhanced geothermal systems.

[0104] The first correlation can be expressed as a conversion formula between the first energy and the first seismic moment. For example, when the rock is granite, the first correlation can be a conversion formula between the acoustic emission energy and the seismic moment generated when the granite cracks slide.

[0105] Acoustic emission energy and seismic moment satisfy the following formula:

[0106] ;

[0107] Where M0 is the seismic moment (N·m). The acoustic emission energy is (J). This is an empirical coefficient (obtained by fitting experimental data, and varies slightly depending on different rock types and loading conditions).

[0108] In some embodiments, the terminal device can determine a first correlation between acoustic emission energy and seismic moment based on the following feasible implementation: determining an initial correlation between the first energy and the seismic moment, the initial correlation including a first weight and a first correction parameter; fitting the first weight to obtain a second weight based on each first energy and the first seismic moment corresponding to each first energy, and fitting the first correction parameter to obtain a second correction parameter; and determining the first correlation based on the second weight and the second correction parameter. This can improve the accuracy of the microseismic magnitude prediction model during reservoir stimulation in hot dry rock enhanced geothermal systems.

[0109] In some embodiments, the initial correlation can be used to simulate the relationship between a first energy and a seismic moment. For example, the initial correlation may include a first weight and a first correction parameter.

[0110] The first weight can be used to indicate the change caused by each unit of acoustic emission energy. The first correction parameter can be used to zero-correct the seismic moment reference value.

[0111] For example, when the rock is granite, the acoustic emission energy under the same set of injection parameters is 2.51 × 10⁻⁶ when the granite fracture slips. 6 J, the crack slip displacement is 1.2 × 10⁻ 4 m, the crack area is 0.008 m², the rock shear modulus is 2.4e10 Pa, and according to the conversion formula between crack slip displacement and seismic moment, the actual seismic moment can be obtained as 6.76e4 N·m. Here, we assume the empirical coefficients of the formula for the first correlation relationship. The values ​​are 9.0e3 and 1.0e4 respectively, resulting in a predicted seismic moment of 6.76e4 N·m. The error between the actual and predicted seismic moments is calculated to be -4.456e4 N·m. This application does not limit the specifics of the embodiments.

[0112] The second weight can be a modified amount indicating the change caused by each unit of acoustic emission energy. The second correction parameter can be a modified reference value for zeroing the seismic moment.

[0113] For example, based on the error value:

[0114] First adjustment of experience coefficient The values ​​are 7.2e3 and 1.5e4 respectively, resulting in a predicted seismic moment of 6.108e4 N·m. The error between the actual and predicted seismic moments is calculated to be -3.804e4 N·m.

[0115] Second adjustment of experience coefficient The values ​​are 6.5e3 and 1.3e4 respectively, resulting in a predicted seismic moment of 5.460e4 N·m. The error between the actual seismic moment and the predicted seismic moment is calculated to be -3.156e4 N·m.

[0116] Third adjustment of experience coefficient The values ​​are 5.0e3 and 1.0e4 respectively, resulting in a predicted seismic moment of 4.200e4 N·m. The error between the actual seismic moment and the predicted seismic moment is calculated to be -1.896e4 N·m.

[0117] Fourth adjustment of the experience coefficient The values ​​are 4.0e3 and 0.8e4 respectively, resulting in a predicted seismic moment of 3.360e4 N·m. The error between the actual seismic moment and the predicted seismic moment is calculated to be -1.056e4 N·m.

[0118] Fifth adjustment of experience coefficient The values ​​are 3.0e3 and 0.4e4 respectively, resulting in a predicted seismic moment of 2.320e4 N·m. The error between the actual seismic moment and the predicted seismic moment is calculated to be -160 N·m.

[0119] Sixth adjustment of experience coefficient The values ​​are 2.9e3 and 4.481e4, respectively, resulting in a predicted seismic moment of 3.360e4 N·m. The error between the actual and predicted seismic moments is calculated to be 0. This application does not limit the scope of the embodiments described herein.

[0120] This formula can also be implemented in the following way:

[0121] For example, when the rock is granite, and the granite cracks slip, the terminal device can acquire 6 sets of data:

[0122] Under the first set of injection parameters, the acoustic emission energy is 1.58 × 10⁻⁶. 5 At time J, the seismic moment is 1.0 × 10³ N·m;

[0123] Under the second set of injection parameters, the acoustic emission energy is 5.01 × 10⁻⁶. 5 At time J, the seismic moment is 3.2 × 10³ N·m;

[0124] Under the third set of injection parameters, the acoustic emission energy is 1.58 × 10⁻⁶. 6 At time J, the seismic moment is 1.0 × 10⁻⁶. 4 N·m;

[0125] Under the fourth set of injection parameters, the acoustic emission energy is 5.01 × 10⁻⁶. 6 At time J, the seismic moment is 3.2 × 10⁻⁶. 4 N·m;

[0126] Under the fifth set of injection parameters, the acoustic emission energy is 1.58 × 10⁻⁶. 7 At time J, the seismic moment is 1.0 × 10⁻⁶. 5 N·m;

[0127] Under the sixth set of injection parameters, the acoustic emission energy is 5.01 × 10⁻⁶. 7 At time J, the seismic moment is 3.2 × 10⁻⁶. 5 N·m.

[0128] The terminal device can perform linear regression on six sets of data, and the data shows a good linear distribution in a log-log coordinate system. Empirical coefficients can be obtained through fitting. The values ​​are 16666.67 and -66666.67 respectively, meaning the first association relationship can be expressed by the following formula:

[0129] ;

[0130] Where M0 is the seismic moment (N·m). The acoustic emission energy is (J).

[0131] In some embodiments, the terminal device can determine the seismic model based on the following feasible implementation: determining the second seismic moment corresponding to the first energy of each group of injected parameters based on the first energy and the first correlation relationship; inputting multiple injected parameters into the seismic model to obtain the third seismic moment corresponding to each injected parameter; and validating the seismic model based on the second seismic moment corresponding to the first energy of each group of injected parameters and the third seismic moment corresponding to multiple injected parameters. This can improve the accuracy of the microseismic magnitude prediction model during reservoir stimulation of hot dry rock enhanced geothermal systems.

[0132] The second seismic moment can be calculated from the verified first correlation and the first energy corresponding to each set of injection parameters. For example, when the rock is granite, the second seismic moment of granite can be obtained by substituting the acoustic emission energy corresponding to each injection parameter into the formula of the first correlation.

[0133] The third seismic moment can be obtained by substituting the injection parameters into the seismic model. For example, when the rock is granite, the third seismic moment of granite can be obtained by substituting each injection parameter into the seismic model.

[0134] In some embodiments, the terminal device can verify the seismic model based on a second seismic moment and a third seismic moment. For example, the terminal device can verify the seismic model based on the second seismic moment calculated from a first correlation and the third seismic moment obtained by substituting the injected parameters into the seismic model. For example, the terminal device can substitute the acoustic emission energy corresponding to the injected parameters into the first correlation to obtain the second seismic moment, and substitute the same set of injected parameters into the empirical model to obtain the third seismic moment.

[0135] For example:

[0136] The empirical model can be represented as:

[0137] ;

[0138] Where M0 is the seismic moment (N·m), P is the injection pressure (MPa), Q is the injection flow rate (m³ / min), N is the number of cycles, and T is the temperature (°C).

[0139] First set of injection parameters: injection pressure P = 20.0 MPa, injection flow rate Q = 3.0 m³ / min, number of cycles N = 5, temperature T = 150℃, corresponding acoustic emission energy. The value is 2.51e6J. Substituting this into the first correlation, we obtain the second seismic moment as 2.304e4 N·m, with an absolute error of -0.004e4 and a relative error of -0.17%.

[0140] The second set of injection parameters: injection pressure P is 30.0 MPa, injection flow rate Q is 4.5 m³ / min, number of cycles N is 8, temperature T is 180℃, and the corresponding acoustic emission energy... The value is 6.31e6J. Substituting this into the first correlation relationship, we obtain the second seismic moment as 2.826e4 N·m, with an absolute error of -0.006e4 and a relative error of -0.21%.

[0141] The third set of injection parameters: injection pressure P = 40.0 MPa, injection flow rate Q = 6.0 m³ / min, number of cycles N = 12, temperature T = 200℃, and corresponding acoustic emission energy. Substituting 1.58e7J into the first correlation equation, we obtain the second seismic moment as 3.365e4 N·m, with an absolute error of +0.005e4 and a relative error of +0.15%.

[0142] The fourth set of injection parameters: injection pressure P = 25.0 MPa, injection flow rate Q = 5.0 m³ / min, number of cycles N = 10, temperature T = 170℃, and corresponding acoustic emission energy. Substituting 1.00e7J into the first correlation relationship, we obtain the second seismic moment as 3.155e4 N·m, with an absolute error of +0.004e4 and a relative error of +0.16%.

[0143] The fifth set of injection parameters: injection pressure P = 35.0 MPa, injection flow rate Q = 7.0 m³ / min, number of cycles N = 15, temperature T = 190℃, and corresponding acoustic emission energy. The value is 2.51e7J. Substituting this into the first correlation, we obtain the second seismic moment as 3.724e4N·m, with an absolute error of -0.004e4 and a relative error of -0.11%.

[0144] It should be noted that the injection parameters in this embodiment are applicable to the flexible circulation injection stimulation scenario of large-scale dry hot rock reservoirs with a burial depth of 3000~5000m. If it is a test well / small-scale reservoir, the discharge rate can be adjusted appropriately.

[0145] It should be noted that the "third seismic moment" predicted by the above empirical model and the "second seismic moment" calculated through the "first correlation" of acoustic emission are in high agreement across all five sets of data, with a maximum relative error of no more than 0.21%. This indicates that the model can very well reflect the quantitative relationship between injection parameters and seismic moments under different working conditions for the current experimental rock sample (granite).

[0146] This application provides a method for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs. The terminal device can determine multiple sets of injection parameters for fluid injection into rock fractures and the rock's first stiffness. The terminal device can also determine the slip displacement, the first area of ​​the fracture, and the first energy generated corresponding to each set of injection parameters. Based on the first stiffness, the first area, and the slip displacement, the terminal device can determine the first seismic moment corresponding to each set of injection parameters. Furthermore, based on multiple first energies and multiple first seismic moments, the terminal device can determine a seismic model relating the injection parameters and the seismic moment. Thus, because the terminal device can establish a model from injection parameters to fracture slip behavior, then to acoustic emission energy, and finally to the seismic moment, the accuracy of the model can be improved, thereby enhancing the accuracy of the microseismic magnitude prediction model during reservoir stimulation in hot dry rock enhanced geothermal systems.

[0147] exist Figure 2 Based on the embodiments shown, the following, in conjunction with Figure 3 The method for determining the first energy corresponding to any set of injection parameters in the above-mentioned method for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs will be explained in detail.

[0148] Figure 3 A flowchart illustrating a method for determining the first energy corresponding to injection parameters, provided in an embodiment of this application, can be found here. Figure 3 The method may include:

[0149] S301, Obtain the acoustic emission events during each slip of the crack.

[0150] In some embodiments, the terminal device can acquire the acoustic emission event of each slide through an acoustic emission signal acquisition device. For example, when the amplitude or energy of the signal voltage exceeds a preset threshold, the terminal device can determine that a valid acoustic emission event has started, and when the signal remains below the threshold for a period of time, the terminal device can determine that the event has ended.

[0151] For example, when the rock is granite, the event trigger threshold is set to 50mV. When the acoustic emission signal acquisition device detects that the signal voltage continuously exceeds 50mV, the terminal device marks the start of the event and continues to record until the signal falls back below the threshold and remains there for a certain period of time. For instance, in a crack slip, the system identifies a signal exceeding the threshold for 300µs and marks it as an independent acoustic emission event. This application does not limit the scope of the embodiments.

[0152] S302. Based on acoustic emission events, determine the voltage information corresponding to each slip of the crack.

[0153] In some embodiments, voltage information can be used to indicate the voltage signal that changes over time when an acoustic emission event occurs. For example, a terminal device can acquire an acoustic emission signal using an acoustic emission signal acquisition device. For example, the acoustic emission signal acquisition device can be a piezoelectric ceramic sensor. This application does not limit this aspect.

[0154] For example, when a crack undergoes shear slip under fluid injection, a transient acoustic emission event is generated. The acoustic emission signal acquisition device can convert this mechanical wave into a weak analog voltage signal. This analog voltage signal is transmitted via a shielded cable to a preamplifier and a high-speed data acquisition card connected to the terminal equipment. The acquisition card synchronously samples and performs analog-to-digital conversion on the signal at a sampling rate of 10MHz (i.e., sampling interval Δt = 0.1µs), converting it into a discrete digital voltage sequence V1, V2, ..., V_n. This application does not limit the scope of the embodiments described herein.

[0155] S303. Determine the first energy based on voltage information.

[0156] In some embodiments, the acoustic emission signal voltage satisfies the following formula:

[0157] ;

[0158] Under discrete sampling conditions, the following formula is satisfied:

[0159] ;

[0160] in, The acoustic emission energy is (J). Let V be the voltage value (V) of the acoustic emission signal at the i-th sampling time. R is the sampling time interval (s), and R is the input impedance (Ω) of the acoustic emission acquisition system.

[0161] This application provides a method for determining the degree of correlation. A terminal device can acquire acoustic emission events during each fracture slip, determine the voltage information corresponding to each slip based on these events, and then determine a first energy level based on the voltage information. In this way, because the terminal device can control the acoustic emission energy signal acquisition device to accurately identify acoustic emission energy events and calculate the corresponding slip acoustic emission energy based on the real-time recorded acoustic emission energy signals, accurate data is provided for subsequent calculations. Therefore, the accuracy of the microseismic magnitude prediction model during reservoir stimulation in hot dry rock enhanced geothermal systems can be improved.

[0162] Based on any of the above embodiments, the above-mentioned method for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs also includes a method for determining the magnitude of underground reservoirs. The following, in conjunction with... Figure 4 The method for determining the magnitude of underground reservoirs is explained in detail.

[0163] Figure 4 This is a schematic flowchart illustrating a method for determining the magnitude of an earthquake in a subsurface reservoir, provided as an embodiment of this application. Please refer to [link / reference]. Figure 4 The method may include:

[0164] S401, Obtain target injection parameters.

[0165] The target injection parameters are used to inject fluid into the rock mass of the underground reservoir. For example, in the development process of the target rock, the target injection parameters may include pressure P, flow rate Q, number of cycles N, and temperature T. For example, when the rock is granite, for a granite reservoir with a burial depth of about 3500 meters and a temperature T of about 180°C, the injection pressure P can be 40.0 MPa, the injection flow rate Q can be 8 m³ / min, and the total number of cycles N using flexible circulation injection can be 15 times, with each cycle lasting 24 hours (12 hours of pressurization and 12 hours of pressure stabilization or depressurization). This application does not limit these parameters.

[0166] In some embodiments, the terminal device can acquire the target injection parameters through a fluid injection device. For example, the terminal device can acquire the target injection parameters through a high-pressure injection pump, a control valve assembly, and their integrated control system. This application does not limit this approach.

[0167] S402. Input the target injection parameters into the seismic model to obtain the target seismic moment.

[0168] In some embodiments, the terminal device can calculate the target seismic moment by inputting the acquired target injection parameters into the seismic model based on the obtained seismic model. For example, if the obtained seismic model of granite is:

[0169] ;

[0170] in, Let P be the seismic moment (N·m), P be the pressure (MPa), Q be the displacement (m³ / min), N be the number of cycles, and T be the temperature (°C).

[0171] For example, the target injection parameters obtained by the terminal device are:

[0172] P=40.0MPa, Q=8.0m³ / min, N=15, T=180°C;

[0173] The target injection parameters are substituted into the seismic model of the granite to calculate the seismic moment. The value is 2.7869e8 N·m. This application does not limit the specific embodiment to this value.

[0174] S403. Determine the magnitude of the underground reservoir based on the target seismic moment.

[0175] In some embodiments, the magnitude can be a predicted magnitude of the subsurface reservoir when fluid is injected into the rock based on target injection parameters. For example, a terminal device can determine the magnitude of the subsurface reservoir using the target seismic moment corresponding to the target injection parameters.

[0176] In some embodiments, the target seismic moment and magnitude satisfy the following seismic relationship formula:

[0177] ;

[0178] Among them, M w Moment magnitude, The seismic moment is (N·m).

[0179] For example, when the target seismic moment of granite The target seismic moment is 2.7869e8 N·m. Substituting this target seismic moment into the seismological relation formula, the magnitude M of the subsurface reservoir is calculated. w The value is -0.44. This application does not limit the specific values ​​expressed in its embodiments.

[0180] This application provides a method for determining the magnitude of an underground reservoir. A terminal device can acquire target injection parameters, input these parameters into a seismic model to obtain a target seismic moment, and then determine the magnitude of the underground reservoir based on this target seismic moment. Thus, since the terminal device can directly derive the seismic moment from a validated model of injection parameters and seismic moment, and obtain the moment magnitude using formulas relating seismic parameters and seismic moment, the efficiency of microseismic magnitude prediction during reservoir stimulation in hot dry rock enhanced geothermal systems can be improved.

[0181] Figure 5This is a schematic diagram of a microseismic magnitude prediction device induced by fracture slip in a geothermal reservoir, provided in this application. Please refer to... Figure 5 The geothermal reservoir fracture slip-induced microseismic magnitude prediction device 500 includes a first determination module 501, a second determination module 502, a third determination module 503, a fourth determination module 504, a verification module 505, and an acquisition module 506, wherein:

[0182] The first determining module 501 is used to determine multiple sets of injection parameters for fluid injection into the rock fractures and the first stiffness of the rock, wherein the rock fractures are in a critical slip state.

[0183] The second determining module 502 is used to determine the slip displacement, the first area of ​​the crack and the first energy generated corresponding to each group of injection parameters, wherein the first energy is the acoustic emission energy generated by the slip.

[0184] The third determining module 503 is used to determine the first seismic moment corresponding to each group of injection parameters based on the first stiffness, the first area and the slip displacement;

[0185] The fourth determination module 504 is used to establish a seismic model between the injection parameters and the seismic moment based on multiple sets of injection parameters and the first seismic moment corresponding to each set of injection parameters.

[0186] The verification module 505 is used to verify the seismic model based on multiple first energies and multiple first seismic moments.

[0187] According to one or more embodiments of this application, the verification module 505 is specifically used for:

[0188] Based on multiple first energies and multiple first seismic moments, the first correlation between acoustic emission energy and seismic moment is determined;

[0189] The earthquake model was validated based on the first correlation.

[0190] According to one or more embodiments of this application, the verification module 505 is specifically used for:

[0191] Based on the first energy corresponding to each group of injection parameters and the first correlation relationship, the second seismic moment corresponding to the first energy corresponding to each group of injection parameters is determined.

[0192] Multiple injection parameters are input into the seismic model to obtain the third seismic moment corresponding to each injection parameter;

[0193] The seismic model is validated based on the second seismic moment corresponding to the first energy of each group of injection parameters, and the third seismic moment corresponding to multiple injection parameters.

[0194] According to one or more embodiments of this application, the verification module 505 is specifically used for:

[0195] Determine the initial correlation between the first energy and the seismic moment, including the first weight and the first correction parameter;

[0196] Based on each first energy and the first seismic moment corresponding to each first energy, the first weight is fitted to obtain the second weight, and the first correction parameter is fitted to obtain the second correction parameter;

[0197] The first association relationship is determined based on the second weight and the second correction parameter.

[0198] According to one or more embodiments of this application, the second determining module 502 is specifically used for:

[0199] Acquire acoustic emission events during each slip of the crack;

[0200] Based on acoustic emission events, the voltage information corresponding to each slip of the crack is determined. The voltage information is used to indicate the voltage signal that changes over time when an acoustic emission event occurs.

[0201] The first energy is determined based on the voltage information.

[0202] According to one or more embodiments of this application, the acquisition module 506 is specifically used for:

[0203] Obtain the target injection parameters, which are used to inject fluid into the rock mass of the underground reservoir;

[0204] Input the target injection parameters into the seismic model to obtain the target seismic moment;

[0205] Based on the target seismic moment, the magnitude of the underground reservoir is determined. The magnitude is the predicted magnitude of the underground reservoir when fluid is injected into the rock based on the target injection parameters.

[0206] This embodiment provides a geothermal reservoir fracture slip-induced microseismic magnitude prediction device, which can perform the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0207] Figure 6 This is a schematic diagram of the structure of a terminal device provided in this embodiment. Please refer to [link / reference]. Figure 6The diagram illustrates a structural schematic of a terminal device 600 suitable for implementing this embodiment. The terminal device may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, personal digital assistants (PDAs), portable Android devices (PADs), portable media players (PMPs), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 6 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0208] like Figure 6 As shown, the terminal device 600 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 602 or a program loaded from storage device 608 into random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the terminal device 600. The processing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0209] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows terminal device 600 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 A terminal device 600 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0210] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, it performs the functions defined in the methods of the embodiments of this application.

[0211] It should be noted that the computer-readable medium described above in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0212] The aforementioned computer-readable medium may be included in the aforementioned terminal device; or it may exist independently and not assembled into the terminal device.

[0213] The aforementioned computer-readable medium carries one or more programs, which, when executed by the terminal device, cause the terminal device to perform the method shown in the above embodiments.

[0214] This application provides a computer-readable storage medium storing computer-executable instructions. When a processor executes the computer-executable instructions, it implements various methods that may be involved in the above embodiments.

[0215] This application provides a computer program product, including a computer program that, when executed by a processor, implements various methods that may be involved in the above embodiments.

[0216] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0217] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0218] The units described in the embodiments of this application can be implemented in software or in hardware. The name of a unit does not necessarily limit the unit itself; for example, the first acquisition unit can also be described as "a unit that acquires at least two Internet Protocol addresses".

[0219] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0220] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0221] It should be noted that the terms "a" and "a plurality of" used in this application are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0222] The names of the messages or information exchanged between multiple devices in the embodiments of this application are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0223] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and provisions. The data may include information, parameters and messages, such as flow switching indication information.

[0224] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

[0225] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. Multitasking and parallel processing may be advantageous in certain contexts. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this application. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments. Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely exemplary forms of implementing the claims.

Claims

1. A method for predicting the magnitude of microseismic events induced by fracture slip in geothermal reservoirs, characterized in that, include: Multiple sets of injection parameters for fluid injection into rock fractures and the first stiffness of the rock are determined, wherein the rock fractures are in a critical slip state; Determine the slip displacement, the first area of ​​the crack, and the first energy generated for each set of injection parameters, where the first energy is the acoustic emission energy generated by the slip. Based on the first stiffness, the first area, and the slip displacement, determine the first seismic moment corresponding to each group of injection parameters; Based on multiple sets of injection parameters and the first seismic moment corresponding to each set of injection parameters, a seismic model between injection parameters and seismic moment is established. The earthquake model is validated based on multiple first energies and multiple first seismic moments.

2. The method according to claim 1, characterized in that, Based on multiple first energies and multiple first seismic moments, a seismic model is established between the injection parameters and the seismic moment, including: Based on the plurality of first energies and the plurality of first seismic moments, a first correlation relationship between the acoustic emission energy and the seismic moment is determined; Based on the first correlation, the earthquake model is validated.

3. The method according to claim 2, characterized in that, Based on the first correlation, the earthquake model is validated, including: Based on the first energy corresponding to each group of injection parameters and the first correlation relationship, the second seismic moment corresponding to the first energy corresponding to each group of injection parameters is determined. Multiple injection parameters are input into the seismic model to obtain the third seismic moment corresponding to each injection parameter; The earthquake model is validated based on the second seismic moment corresponding to the first energy of each group of injection parameters, and the third seismic moment corresponding to multiple injection parameters.

4. The method according to claim 2, characterized in that, Based on the plurality of first energies and the plurality of first seismic moments, a first correlation relationship is determined between the acoustic emission energy and the seismic moment, including: Determine the initial correlation between the first energy and the seismic moment, wherein the initial correlation includes a first weight and a first correction parameter; Based on each first energy and the first seismic moment corresponding to each first energy, the first weight is fitted to obtain the second weight, and the first correction parameter is fitted to obtain the second correction parameter; The first association relationship is determined based on the second weight and the second correction parameter.

5. The method according to any one of claims 1-4, characterized in that, For any set of injection parameters; determine the first energy corresponding to each set of injection parameters, including: Acquire acoustic emission events during each slip of the crack; Based on acoustic emission events, the voltage information corresponding to each slip of the crack is determined, and the voltage information is used to indicate the voltage signal that changes over time when the acoustic emission event occurs; Based on the voltage information, the first energy is determined.

6. The method according to any one of claims 1-4, characterized in that, The method further includes: Obtain target injection parameters, which are used to inject fluid into the rock mass of the underground reservoir; The target injection parameters are input into the earthquake model to obtain the target seismic moment; Based on the target seismic moment, the magnitude of the underground reservoir is determined, wherein the magnitude is the predicted magnitude of the underground reservoir when fluid is injected into the rock based on the target injection parameters.

7. A device for predicting the magnitude of microseismic events induced by fracture slippage in geothermal reservoirs, characterized in that, It includes a first determining module, a second determining module, a third determining module, a fourth determining module, and a verification module, wherein: The first determining module is used to determine multiple sets of injection parameters for fluid injection into the cracks of the rock and the first stiffness of the rock, wherein the cracks of the rock are in a critical slip state. The second determining module is used to determine the slip displacement, the first area of ​​the crack, and the first energy generated corresponding to each group of injection parameters, wherein the first energy is the acoustic emission energy generated by the slip. The third determining module is used to determine the first seismic moment corresponding to each group of injection parameters based on the first stiffness, the first area and the slip displacement; The fourth determining module is used to determine the seismic model between the injection parameters and the seismic moment based on multiple first energies and multiple first seismic moments; The verification module is used to establish a seismic model between the injection parameters and the seismic moment based on multiple sets of injection parameters and the first seismic moment corresponding to each set of injection parameters.

8. A terminal device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 7.

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