Joint inversion method for near-wellbore characteristics of hydraulic fractures based on high-frequency tube waves and water hammer

Abstract

The present invention discloses a joint inversion method for near-wellbore characteristics of fracturing cracks based on high-frequency tube waves and water hammer, and relates to the technical field of fracturing crack inversion. The method comprises the following steps: establishing a tube wave wellbore fracture model; segmenting, zero-filling and Fourier transforming the tube wave excitation signal before fracturing, and then substituting it into the tube wave wellbore fracture model for inversion to obtain the optimal tube wave quality factor and the optimal tube wave velocity, and correcting the model; calculating the depth of the main fracturing fluid inlet point based on the pump-off water hammer curve; segmenting, zero-filling and Fourier transforming the tube wave excitation signal after fracturing, and then substituting it into the corrected tube wave wellbore fracture model for inversion. According to the method of the present invention, the calculated echo signal is closer to the actual situation, and the depth of the main fluid inlet point is predetermined, which is conducive to the accurate and rapid inversion of the tube wave, and can greatly save the inversion time.

Description

Technical Field

[0001] The present invention relates to the technical field of hydraulic fracture inversion, and in particular to a joint inversion method for hydraulic fracture near-wellbore characteristics based on high-frequency tube waves and water hammer. Background Art

[0002] Fracture diagnosis technology based on wellbore pressure / pressure wave signals has the advantages of low cost, no impact on on-site processes, and high efficiency. The earliest to appear was the fracturing construction pressure curve diagnostic technology. Based on the fracturing construction curve, this technology analyzes the changes in construction pressure caused by changes in displacement and sand ratio, clarifies the characteristics of fracture extension and fracture network complexity under different reservoir conditions, and conducts qualitative identification of fracture characteristics and quantitative characterization of fracture parameters. However, in the process of evaluating fracture parameters, this method is affected by human subjective experience, making it difficult to accurately judge the fracture morphology. With the development of artificial intelligence technology, this method has been given new vitality and has been well applied in the evaluation of the effectiveness of temporary plugging in fracturing. In 2018, Schlumberger launched the high-frequency pressure analysis technology WellWatcher Stim®. This technology uses the water hammer effect caused by the pump stop during fracturing to perform inverse spectrum analysis of the pressure oscillation signal, quickly judging bottomhole events such as sleeve opening, bridge plug setting, and temporary plugging diversion, and has been widely promoted in the field. On this basis, Hu Xiaodong et al. from China University of Petroleum (Beijing) compared the reflection method, cepstrum method, half-cycle method, full-cycle method, Fourier fundamental frequency method and Fourier third harmonic method, solved the water hammer wave velocity, and proposed two indicators for evaluating the filtering effect: cepstrum response resolution and cepstrum peak signal-to-noise ratio; Ding Liangliang et al. from Southwest Petroleum University established a fracturing sand plugging wellbore water hammer model and formed a fracturing sand plugging prediction method based on the fracturing construction curve; Hao Youzhi et al. from the University of Science and Technology of China clarified the correlation between the time domain waveform characteristics of water hammer and the severity of casing change based on the casing change wellbore water hammer model; Carey, Liu Wei and Liu Lijun from Chengdu University of Technology used an electrical equivalent model to characterize the changes in flow or pressure of fracturing cracks, coupled the wellbore water hammer model, and carried out an inversion study on the fracture geometry.

[0003] However, the existing hydraulic fracturing fracture inversion requires a lot of data, is difficult to perform and takes a long time. Summary of the Invention

[0004] To solve at least one of the above problems, the present invention proposes a joint inversion method for near-wellbore characteristics of hydraulic fractures based on high-frequency tube waves and water hammer.

[0005] The technical solution of the present invention is: a joint inversion method for near-wellbore characteristics of hydraulic fractures based on high-frequency tube waves and water hammer, comprising the following steps:

[0006] S1. Establishing a tube wave wellbore fracture model based on excitation source parameters, wellbore parameters and fracture parameters;

[0007] S2. Taking the pre-fracturing excitation wave and the first pre-fracturing echo before a single-stage fracturing, performing time domain segmentation between the pre-fracturing excitation wave and the first pre-fracturing echo, padding the data after the segmentation point with zeros, and performing Fourier transform on the zero-padded data to obtain a frequency spectrum curve of the pre-fracturing excitation wave; taking the tube wave quality factor and tube wave velocity as inversion targets, bringing the frequency spectrum curve of the pre-fracturing excitation wave, different tube wave quality factors, and different tube wave velocities into the tube wave wellbore fracture model for inversion to obtain the optimal tube wave quality factor and optimal tube wave velocity, and then calibrating the tube wave wellbore fracture model;

[0008] S3. Determine the depth of the main liquid inlet point based on the pump-off water hammer pressure curve of the single-stage fracturing;

[0009] S4. Take the post-fracturing excitation wave and the first post-fracturing echo after a single-stage fracturing, perform time domain segmentation between the post-fracturing excitation wave and the first post-fracturing echo, fill the data after the segmentation point with zero, and perform Fourier transform on the zero-filled data to obtain the frequency spectrum curve of the post-fracturing excitation wave; take the fracture conductivity coefficient and fracture height as the inversion target, substitute the frequency spectrum curve of the post-fracturing excitation wave, the tube wave quality factor, the tube wave velocity and the depth of the main liquid inlet point into the tube wave wellbore fracture model for inversion.

[0010] Beneficial effects: 1. The present invention adopts the method of splitting the tube wave excitation signal, filling zeros and performing Fourier transform to obtain the frequency domain characteristics of the excitation wave. Compared with the use of theoretical waveforms such as Gaussian pulses and Ricker wavelets, the calculated echo signal is closer to the actual situation, which is conducive to the accurate and rapid inversion of tube waves; 2. The present invention determines the depth of the main liquid inlet point before post-pressure inversion. Compared with the three inversion target parameters of conventional post-pressure inversion, the present invention reduces it to two inversion target parameters: fracture conductivity and fracture height, which can greatly save inversion time. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is the distribution diagram of the inversion error before compression;

[0012] Figure 2 This is a diagram showing the simulation results of the pump-off water hammer curve of the existing wellbore-fracture coupling system water hammer model;

[0013] Figure 3 The inversion result diagram of the depth variation with time based on the pump-off water hammer curve;

[0014] Figure 4 This is the inversion result diagram of the pressure change with the depth based on the pump-off water hammer curve;

[0015] Figure 5 The inversion error distribution diagram of fracture conductivity and fracture height after compression. DETAILED DESCRIPTION

[0016] The specific implementation methods of the present invention will be clearly and completely described below with reference to examples. Obviously, the examples described are only part of the embodiments of the present invention, rather than all the embodiments.

[0017] A joint inversion method for near-wellbore characteristics of hydraulic fractures based on high-frequency tube waves and water hammer includes the following steps:

[0018] S1. Establishing a tube wave wellbore fracture model based on excitation source parameters, wellbore parameters and fracture parameters;

[0019] When establishing a tube wave wellbore fracture model, the following parameters are required: the excitation source parameters include the Gaussian function time scale, pulse amplitude, frequency, tube wave quality factor, and well depth; the wellbore parameters include wellbore diameter, tube wave velocity, fluid density, fracture porosity, conductivity, fluid viscosity, and fracture permeability; and the fracture parameters include fracture width, fracture height, number of single-cluster fractures, and solid shear modulus.

[0020] The method for establishing a tube-wave wellbore fracture model is currently available. For reference, the method proposed by Chao Liang et al. in the article "Hydraulic fracture diagnostics from Krauklis-wave resonance and tube-wave reflections" can be used. Tube-wave wellbore fracture models are divided into two types: the tube-wave wellbore model and the tube-wave fracture model.

[0021] In this embodiment, for the tube wave wellbore model, the tube wave quality factor is used to characterize the attenuation of the tube wave propagation process in the wellbore. Before fracturing, the wellbore is isolated by a bridge plug, and after fracturing, the fracture is multi-cluster perforation. The reflection coefficient of the tube wave can be expressed as:

[0022] ;

[0023] ;

[0024] in: R ( ω ) is the frequency-varying reflection coefficient, which is a function of the tube wave frequency and is dimensionless; Z f ( ω ) is the frequency-dependent crack impedance, which is a function of the tube wave frequency; Z T is the wellbore wave impedance, kg / (m 4 s); ρ is the wellbore liquid density, kg / m 3 ; c T is the wellbore pipe wave velocity, m / s; AT is the cross-sectional area inside the wellbore, m 2 .

[0025] The pressure at the wellhead is related to the injected fluid flow rate and can be expressed in the frequency domain as:

[0026]

[0027] ;

[0028] in: h is the length of the tube wave propagating in the wellbore, that is, the depth from the wellhead to the fracture or bridge plug, m; ω 0 is the reference angular frequency, rad / s, which is taken as 10 rad / s in this paper; ω is the angular frequency of the tube wave; Q T is the injection flow rate at the wellhead, m 3 / s; represents the wellhead pressure in the frequency domain; represents the wellhead injection rate in the frequency domain; It represents the time factor considering tube wave reflection; i represents the unit of imaginary number.

[0029] In this example, the tube wave fracture model assumes that fluid movement in proppant-containing fractures is one-dimensional Darcy flow, and the fracture geometry satisfies the PKN model. Within the low-frequency range (≤5 Hz), the tube wave wavelength is sufficiently long (assuming a wave velocity of 1500 m / s, the wavelength of a tube wave at a frequency of 5 Hz is 300 m), and the perforation length of a single segment is less than 100 m. Since different perforation clusters experience the same pressure wave, multiple fracture clusters can be treated as a single fracture. For a single fracture, the mass conservation equation for the fluid in the fracture can be expressed as:

[0030] ;

[0031] Where, is the density of the liquid in the crack, kg / m 3 ; q is the fluid flow rate in the crack, m 3 / s; is the porosity of the proppant in the fracture, dimensionless; A f is the flow area of the fluid in the crack, m 2 ; t is time, s; x is the length of the fluid flow area from the wellbore, m.

[0032] The propagation law of tube waves in the fracture proppant layer satisfies Darcy's formula:

[0033] ;

[0034] Where, is the permeability of the proppant in the fracture, D; μ is the viscosity of the fluid in the fracture, Pa·s; is the pressure of the fluid in the crack, Pa.

[0035] According to the PKN model, assuming that the cross section of the fracture is an ellipse, the width of the fracture (on the order of millimeters to centimeters) is much smaller than the wavelength of the tube wave (on the order of hundreds of meters to kilometers), and in the low frequency range (≤5Hz), we get The equivalent impedance of an elliptical crack can be expressed as:

[0036] ;

[0037] Where, N is the cluster number of hydraulic fractures, dimensionless; G * is the shear modulus of the formation rock, Pa; i is the unit of imaginary number; ω is the angular frequency of the tube wave, rad / s; w is the width of the crack, m; H is the height of the crack, m.

[0038] The above model also has boundary conditions. In this embodiment, the boundary conditions are set as follows:

[0039] Wellhead boundary conditions: Assume that the change pattern of the injection flow at the wellhead satisfies the Gaussian function, and its spectrum is also a Gaussian function:

[0040] ;

[0041] Where, is the amplitude of the Gaussian pulse function, m 3 / s; is the unit of imaginary number; t is time, s; t c is the center time of the Gaussian pulse signal, s; is the frequency domain function of the Gaussian pulse flow at the wellhead.

[0042] In the embodiment of the present invention, a Gaussian function is used as the characteristic frequency, and the energy exceeding this frequency is relatively small. Other excitation functions are also applicable to the wellbore-fracture system tube wave model established in this paper.

[0043] Bottom hole boundary conditions: For the completely sealed bottom hole condition, that is, after the bridge plug is set and before single-stage fracturing, the reflection coefficient of the bridge plug can be expressed as

[0044] ;

[0045] Where, R b Represents the reflection coefficient of the bridge plug.

[0046] In this step, the parameters for establishing the tube wave wellbore fracture model are based on those of Dunham et al. (2017), some of which are shown in Table 1.

[0047] Table 1 Some parameters for establishing the tube wave wellbore fracture model

[0048]

[0049] S2. Taking the pre-fracturing excitation wave and the first pre-fracturing echo before single-stage fracturing, performing time domain segmentation between the pre-fracturing excitation wave and the first pre-fracturing echo, zero-padding the data after the segmentation point, and performing Fourier transform on the zero-padding data to obtain a frequency spectrum curve of the pre-fracturing excitation wave; taking the tube wave quality factor and the tube wave velocity as inversion targets, bringing the frequency spectrum curve of the pre-fracturing excitation wave, different tube wave quality factors, and different tube wave velocities into the tube wave wellbore fracture model for inversion to obtain the optimal tube wave quality factor and the optimal tube wave velocity, and calibrating the tube wave wellbore fracture model; which mainly includes the following sub-steps:

[0050] Stimulate the tube wave before fracturing and record the time domain curve of the tube wave before fracturing;

[0051] Based on the pre-compression tube wave time domain curve, the pre-compression excitation wave and the first pre-compression echo are obtained. A stable point is selected between the pre-compression excitation wave and the first pre-compression echo to perform time domain segmentation. The data after the segmentation point, including the first pre-compression echo, is padded with zeros. The zero-padded pre-compression tube wave time domain curve is Fourier transformed to obtain the spectrum curve of the pre-compression excitation wave.

[0052] The spectrum curve, tube wave quality factor, and tube wave velocity of the pre-compression excitation wave are substituted into the tube wave wellbore fracture model to obtain the time domain curve of the first echo before compression. The characteristic value of the first echo before compression is calculated based on the first objective function. The first objective function is as follows: , where Φ (m) represents the first objective function; w obs Represents the characteristics of the observed data; w forword is the characteristic of the forward model data; ‖·‖2 represents the L2 norm operator;

[0053] By changing the tube wave quality factor and tube wave velocity, repeatedly substituting them into the tube wave wellbore fracture model and calculating the eigenvalue of the first echo before pressure, the error distribution between the eigenvalue of the first echo of the simulated data and the eigenvalue of the measured first echo was determined, and the optimal tube wave quality factor and optimal tube wave velocity were found. The tube wave wellbore fracture model was then corrected based on the optimal tube wave quality factor and optimal tube wave velocity.

[0054] In this embodiment, the tube wave velocity in the wellbore can be expressed as follows: ,in , where: K e f f is the effective bulk elastic modulus, K is the volume elastic model of the wellbore fluid, G is the shear modulus, E is the elastic modulus, e is the casing wall thickness, D is the casing diameter, c T is the tube wave velocity.

[0055] As can be seen from the above, many factors influence tube wave velocity, including wellbore fluid properties, wellbore geometry and elastic parameters, and formation properties. The most significant factors affecting tube wave velocity are the wellbore fluid's bulk modulus and density, which are influenced by pressure, temperature, gas content, and tube wave frequency. In pure water, when the liquid pressure is 13.79 to 68.95 MPa, the tube wave velocity is 1524 to 1645 m / s.

[0056] Based on the time-domain characteristics of tube wave echoes, this paper proposes a tube wave velocity inversion metric: the difference between the time corresponding to the maximum value of the excitation wave and the time corresponding to the maximum value of the first echo. This is defined as the tube wave's flight time, or the time it takes for the tube wave to propagate from the wellhead to the bottom of the well and then return to the wellhead. Analysis of the quantitative relationship between flight time and velocity at different wave velocities reveals a nearly linear negative correlation between flight time and velocity, with a monotonically decreasing pattern. This principle indicates that once the tube wave's flight time is determined, a unique tube wave velocity can be found. This conclusion lays the theoretical foundation for tube wave velocity inversion.

[0057] Tube waves are mechanical waves that exhibit oscillator damping properties during wellbore propagation. The speed of energy loss can be characterized by the tube wave quality factor. According to the definition and calculation expression of the tube wave quality factor, the larger the tube wave quality factor, the slower the tube wave decays, and vice versa. According to existing technology, the tube wave quality factor in a wellbore-fracture system ranges from approximately 10 to 100. Based on an established tube wave model for wellbore-fracture coupling, the time domain characteristics of the wellbore echo under different tube wave quality factors were calculated. Simulation results show that the tube wave quality factor primarily affects the amplitude of the wellbore echo: the larger the tube wave quality factor, the greater the amplitude of the wellhead echo. Over time, the amplitude of multiple echoes from the wellhead decays exponentially.

[0058] In this embodiment, Gaussian pulse is used as the excitation signal at the wellhead, and the errors between different wave velocities and different tube wave quality factors and the actual parameters are finally obtained as follows: Figure 1 As shown in the figure, the optimal tube wave quality factor obtained by inversion is 29.2 and the optimal tube wave velocity is 1250.5 m / s, which are close to the actual tube wave quality factor of 30 and the actual tube wave velocity of 1250 m / s in this example (the actual values are determined by forward modeling), indicating that the inversion result is relatively accurate.

[0059] S3. Determine the depth of the main liquid inlet point based on the fracturing pump-off water hammer pressure curve;

[0060] Take the single-stage fracturing pump-off water hammer pressure curve, perform Fourier transform, and obtain the frequency spectrum curve of the pump-off water hammer curve;

[0061] Take the peak difference of the spectrum curve of the pump-stop water hammer curve and calculate the average value. Based on the average value, calculate the reflection period of the water hammer wave and obtain the preliminary wave velocity of the water hammer.

[0062] In this embodiment, based on the simulation parameter data, combined with the existing wellbore-fracture coupling system water hammer model (reference "Fracturing Pump Stop Water Hammer Pressure Wave Signal Filtering Method and Characteristic Analysis", Hu Xiaodong), the pump stop theoretical displacement data of the fracturing pump is used to obtain the pump stop water hammer signal. The specific shape of the curve is as follows: Figure 2 As shown. Figure 2 It can be seen that the simulated pump stop water hammer signal is clean and clear, with multiple oscillation cycles and a long duration. The water hammer effect is obvious. This figure can provide initial data for subsequent calculations.

[0063] The depth of the main fluid inlet point of a single-stage fracturing is calculated based on the frequency difference method or the two-dimensional cepstrum method.

[0064] Then, the method of this embodiment is adopted to obtain a two-dimensional cepstrum interpretation diagram using a two-dimensional cepstrum calculation method, as shown in FIG. Figure 3As shown in the figure, the pump stop time is 400s, and the color at 4500m is darker, indicating that the water hammer signal is strong; as time goes by, the color of this position gradually becomes lighter, indicating that the water hammer signal gradually weakens.

[0065] The specific value of the two-dimensional cepstrum at the time point changes along the depth change curve, such as Figure 4 As shown in the figure, a local minimum exists at the injection point at 4500 m. Therefore, selecting a point on the 2D cepstrum can effectively locate the depth of the main injection point. In addition, the injection point will show a periodic signal on the 2D cepstrum curve, with odd-numbered signals being negative and even-numbered signals being positive, with positive and negative signals alternating.

[0066] S4. Take the post-fracturing excitation wave and the first post-fracturing echo after a single-stage fracturing, perform time domain segmentation between the post-fracturing excitation wave and the first post-fracturing echo, fill the data after the segmentation point with zero, and perform Fourier transform on the zero-filled data to obtain the frequency spectrum curve of the post-fracturing excitation wave; take the fracture conductivity coefficient and fracture height as the inversion target, substitute the frequency spectrum curve of the post-fracturing excitation wave, the tube wave quality factor, the tube wave velocity and the depth of the main liquid inlet point into the tube wave wellbore fracture model for inversion.

[0067] Typically, the inversion targets for post-fracturing inversion are the depth of the primary fluid inlet point, the conductivity, and the fracture height. Because these three parameters need to be inverted, and constraints between them are difficult to establish, there is a high degree of multiplicity, making it difficult to quickly and accurately invert fracture characteristics. However, the present invention determines the depth of the primary fluid inlet point, eliminating one inversion parameter and reducing the uncertainty of fracture inversion. This significantly reduces the difficulty and time of inversion.

[0068] This step includes the following sub-steps:

[0069] Stimulate the tube wave after fracturing and record the time domain curve of the tube wave after fracturing;

[0070] Based on the time domain curve of the post-compression tube wave, the post-compression excitation wave and the first post-compression echo are obtained. A stable point is selected between the post-compression excitation wave and the first post-compression echo to perform time domain segmentation. The data after the segmentation point, including the first post-compression echo, is padded with zeros. The zero-padded time domain curve of the post-compression tube wave is Fourier transformed to obtain the spectrum curve of the post-compression excitation wave.

[0071] The spectrum curve, tube wave quality factor, tube wave velocity, and depth of the main liquid inlet point of the post-pressure excitation wave are substituted into the corrected tube wave wellbore fracture model to obtain the time domain curve of the first post-pressure echo. The characteristic value of the first post-pressure echo is calculated based on the second objective function. The second objective function is as follows: , where v 1 represents the amplitude of the first local extreme value of the first echo; v2 represents the amplitude of the second local extreme value of the first echo; w is the second objective function. For existing methods, the objective function they use is usually the error of the entire waveform. However, in the actual test process, there are certain differences between the inversion parameters and the measured parameters: for the measured parameters, due to the presence of a certain baseline drift phenomenon in the tube wave sensor, the tube wave echo of the inversion parameter is an ideal waveform with a baseline of 0. Therefore, in such a case, not only will the amount of calculation be large, but when the echo is weak, it will be difficult to find the minimum value in the parameter space, resulting in a large error in the final result. In this embodiment, a second objective function is proposed, which uses the local extreme value of the first echo to calculate it. It can effectively overcome the problem of baseline drift of the actual echo signal, so that the forward echo waveform and the actual measured waveform are in good agreement, while also greatly reducing the amount of calculation, saving time and computing power.

[0072] Based on the measured value of the first echo in the time domain curve of the tube wave after compression, the second objective function value in the simulation parameter space is calculated and obtained w and the measured second objective function value w The fracture conductivity and fracture height with the smallest error are inverted; the error here is the smallest and can be expressed by the difference method, that is, the second objective function value in the simulation parameter space w and the measured second objective function value w The smaller the absolute value of the difference, the more accurate the result.

[0073] The final inversion result is as follows Figure 5 As shown, from Figure 5 As can be seen, within the set range of conductivity and fracture height, the error function still reaches a global minimum (located at the blue cross). This example demonstrates that the proposed tube wave-water hammer joint inversion algorithm, using water hammer positioning to first constrain the depth of the primary inlet point, can accurately invert fracture conductivity and fracture height.

[0074] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention is disclosed above with reference to the preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can, without departing from the scope of the technical solution of the present invention, make slight changes or modifications to the technical contents disclosed above into equivalent embodiments with equivalent changes. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A joint inversion method for near-wellbore characteristics of hydraulic fractures based on high-frequency tube waves and water hammer, characterized in that: The following steps are included: S1. Establishing a tube wave wellbore fracture model based on excitation source parameters, wellbore parameters and fracture parameters; S2. Taking the pre-fracturing excitation wave and the first pre-fracturing echo before a single-stage fracturing, performing time domain segmentation between the pre-fracturing excitation wave and the first pre-fracturing echo, padding the data after the segmentation point with zeros, and performing Fourier transform on the zero-padded data to obtain a frequency spectrum curve of the pre-fracturing excitation wave; taking the tube wave quality factor and tube wave velocity as inversion targets, bringing the frequency spectrum curve of the pre-fracturing excitation wave, different tube wave quality factors, and different tube wave velocities into the tube wave wellbore fracture model for inversion to obtain the optimal tube wave quality factor and optimal tube wave velocity, and then calibrating the tube wave wellbore fracture model; S3. Determine the depth of the main liquid inlet point based on the pump-off water hammer pressure curve of the single-stage fracturing; S4. Take the post-fracturing excitation wave and the first post-fracturing echo after a single-stage fracturing, perform time domain segmentation between the post-fracturing excitation wave and the first post-fracturing echo, fill the data after the segmentation point with zero, and perform Fourier transform on the zero-filled data to obtain the frequency spectrum curve of the post-fracturing excitation wave; take the fracture conductivity coefficient and fracture height as the inversion target, substitute the frequency spectrum curve of the post-fracturing excitation wave, the tube wave quality factor, the tube wave velocity and the depth of the main liquid inlet point into the tube wave wellbore fracture model for inversion.

2. The method according to claim 1, characterized in that In S1, the excitation source parameters include Gaussian function time scale, pulse amplitude, frequency, tube wave quality factor and well depth; the wellbore parameters include wellbore diameter, tube wave velocity, fluid density, fracture porosity, conductivity, fluid viscosity and fracture permeability; the fracture parameters include fracture width, fracture height, number of single cluster fractures and solid shear modulus.

3. The method according to claim 1, characterized in that In S1, the tube wave wellbore fracture model includes a tube wave wellbore model and a tube wave fracture model.

4. The method according to claim 1, wherein S2 includes the following sub-steps: Stimulate the tube wave before fracturing and record the time domain curve of the tube wave before fracturing; Based on the pre-compression tube wave time domain curve, the pre-compression excitation wave and the first pre-compression echo are obtained. A stable point is selected between the pre-compression excitation wave and the first pre-compression echo to perform time domain segmentation. The data after the segmentation point, including the first pre-compression echo, is padded with zeros. The zero-padded pre-compression tube wave time domain curve is Fourier transformed to obtain the spectrum curve of the pre-compression excitation wave. The spectrum curve, tube wave quality factor and tube wave velocity of the excitation wave before pressure are substituted into the tube wave wellbore fracture model to obtain the time domain curve of the first echo before pressure, and the pre-pressure echo is calculated based on the first objective function. Φ (m) value, the first objective function is as follows: , where Φ (m) represents the first objective function; w obs Represents the characteristics of the observed data; w forword is the characteristic of the forward model data; ‖·‖2 represents the L2 norm operator; Change the tube wave quality factor and tube wave velocity, repeatedly substitute them into the tube wave wellbore fracture model and calculate the pre-pressure Φ The optimal tube wave quality factor and the optimal tube wave velocity are found, and the tube wave wellbore fracture model is calibrated based on the optimal tube wave quality factor and the optimal tube wave velocity.

5. The method according to claim 1, wherein S3 includes the following steps: Take the single-stage fracturing pump-off water hammer pressure curve, perform Fourier transform, and obtain the frequency spectrum curve of the pump-off water hammer curve; Take the peak difference of the spectrum curve of the pump-stop water hammer curve and calculate the average value. Based on the average value, calculate the reflection period of the water hammer wave and obtain the preliminary wave velocity of the water hammer. The depth of the main fluid inlet point of a single-stage fracturing is calculated based on the frequency difference method or the two-dimensional cepstrum method.

6. The method according to claim 1, characterized in that S4 includes the following sub-steps: Stimulate the tube wave after single-stage fracturing and record the tube wave time domain curve after fracturing; Based on the time domain curve of the post-compression tube wave, the post-compression excitation wave and the first post-compression echo are obtained. A stable point is selected between the post-compression excitation wave and the first post-compression echo to perform time domain segmentation. The data after the segmentation point, including the first post-compression echo, is padded with zeros. The zero-padded time domain curve of the post-compression tube wave is Fourier transformed to obtain the spectrum curve of the post-compression excitation wave. The spectrum curve, tube wave quality factor, tube wave velocity, and depth of the main liquid inlet point of the post-pressure excitation wave are substituted into the corrected tube wave wellbore fracture model to obtain the time domain curve of the first post-pressure echo. The characteristic value of the first post-pressure echo is calculated based on the second objective function. The second objective function is as follows: , where v 1 represents the amplitude of the first local extreme value of the first echo; v 2 represents the amplitude of the second local extreme value of the first echo; w is the second objective function value; Based on the measured value of the first echo in the time domain curve of the tube wave after compression, the second objective function value in the simulation parameter space is calculated and obtained w The minimum fracture conductivity and fracture height, the inversion is completed.

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