Fracturing crack near-well characteristic joint inversion method based on high-frequency tube wave and water attack

Abstract

The invention discloses a joint inversion method for near-well characteristics of a fracturing crack based on high-frequency tube waves and water attack, and relates to the technical field of fracturing crack inversion. The method comprises the following steps: establishing a tube wave shaft crack model; carrying out segmentation, zero padding and Fourier transform on the pre-pressing pipe wave excitation signal, then substituting the pre-pressing pipe wave excitation signal into a pipe wave shaft crack model for inversion to obtain an optimal pipe wave quality factor and an optimal pipe wave velocity, and correcting the model; the depth of a fracturing main liquid inlet point is calculated based on a pump stopping water attack curve; and performing segmentation, zero padding and Fourier transform on the pressed pipe wave excitation signal, and then substituting the pressed pipe wave excitation signal into the corrected pipe wave wellbore crack model for inversion. According to the method, the echo signal obtained through calculation is closer to the real situation, the depth of the main liquid inlet point is determined in advance, accurate and rapid inversion of the tube wave is facilitated, and meanwhile the inversion time can be greatly saved.

Description

Technical Field

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

[0002] Fracture diagnosis techniques based on wellbore pressure / pressure wave signals have the advantages of low cost, no impact on on-site processes, and high efficiency. The earliest one is the hydraulic fracturing construction pressure curve diagnosis technique. Based on the hydraulic fracturing construction curve, this technique analyzes the law of construction pressure change caused by the changes in displacement and sand ratio, clarifies the characteristics such as 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 artificial subjective experience, and it is difficult to accurately judge the fracture morphology. With the development of artificial intelligence technology, this method has been given new vitality and has achieved good applications in the evaluation of the effectiveness of hydraulic fracturing temporary plugging. In 2018, Schlumberger introduced the high-frequency pressure analysis technology WellWatcher Stim®, which uses the water hammer effect excited by pump shut-off during hydraulic fracturing to conduct cepstrum analysis of pressure oscillation signals, quickly judge downhole events such as sliding 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 indexes for evaluating the filtering effect, namely cepstrum response resolution and cepstrum frequency peak signal-to-noise ratio; Ding Liangliang et al. from Southwest Petroleum University established a water hammer model for sand plugging in the wellbore during hydraulic fracturing and formed a prediction method for sand plugging during hydraulic fracturing based on the hydraulic fracturing construction curve; Hao Youzhi et al. from the University of Science and Technology of China clarified the correlation law between the time-domain waveform characteristics of water hammer and the severity of casing deformation based on the water hammer model of deformed casing; Carey, Liu Wei, and Liu Lijun from Chengdu University of Technology used an electrical equivalent model to characterize the changes in flow rate or pressure of hydraulic fractures, coupled the wellbore water hammer model, and carried out the inversion research on fracture geometry.

[0003] However, the existing hydraulic fracture inversion requires a large amount of data, with great inversion difficulty and long inversion 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 pipe waves and water hammer.

[0005] The technical solution of the present invention is as follows: A joint inversion method for near-wellbore characteristics of hydraulic fractures based on high-frequency pipe waves and water hammer, comprising the following steps: S1. Establish a pipe wave wellbore fracture model based on excitation source parameters, wellbore parameters, and fracture parameters; S2. Take the pre - fracturing excitation wave and the first echo before single - stage fracturing. Perform time - domain segmentation between the pre - fracturing excitation wave and the first echo before fracturing, fill zeros for the data after the segmentation point, and perform Fourier transform on the zero - filled data to obtain the spectral curve of the pre - fracturing excitation wave. Taking the tube wave quality factor and tube wave velocity as the inversion targets, substitute the spectral 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 correct the tube wave wellbore fracture model; S3. Based on the single - stage fracturing shut - in water - hammer pressure curve, determine the depth of the main liquid - injection point; S4. Take the post - fracturing excitation wave and the first echo after single - stage fracturing. Perform time - domain segmentation between the post - fracturing excitation wave and the first echo after fracturing, fill zeros for the data after the segmentation point, and perform Fourier transform on the zero - filled data to obtain the spectral curve of the post - fracturing excitation wave. Taking the fracture conductivity and fracture height as the inversion targets, substitute the spectral curve of the post - fracturing excitation wave, the tube wave quality factor, the tube wave velocity, and the depth of the main liquid - injection point into the tube wave wellbore fracture model for inversion to obtain the results.

[0006] Beneficial effects: 1. The present invention uses the method of segmenting the tube wave excitation signal, filling zeros, and performing Fourier transform to obtain the frequency - domain characteristics of the excitation wave. Compared with using theoretical waveforms such as Gaussian pulses and Ricker wavelets, the calculated echo signal is closer to the actual situation, which is beneficial to the accurate and rapid inversion of tube waves; 2. The present invention determines the depth of the main liquid - injection point before post - fracturing inversion. Compared with the three inversion target parameters of conventional post - fracturing inversion, the present invention reduces to two inversion target parameters, namely fracture conductivity and fracture height, which can greatly save the inversion time. Description of the Drawings

[0007] Figure 1 It is the pre - fracturing inversion error distribution diagram; Figure 2 It is the simulation result diagram of the shut - in water - hammer curve of the existing wellbore - fracture coupling system water - hammer model; Figure 3 It is the inversion result diagram of the depth changing with time based on the shut - in water - hammer curve; Figure 4 It is the inversion result diagram of the pressure changing with the depth based on the shut - in water - hammer curve; Figure 5 It is the post - fracturing fracture conductivity and fracture height inversion error distribution diagram. Detailed Embodiments

[0008] The following will clearly and completely describe the specific embodiments of the present invention in combination with examples. Obviously, the described examples are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0009] A joint inversion method for near-wellbore characteristics of hydraulic fracture based on high-frequency tube waves and water hammer, comprising the following steps: S1. Establish a tube wave wellbore fracture model based on excitation source parameters, wellbore parameters and fracture parameters; When establishing the tube wave wellbore fracture model, the following parameters are required: 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.

[0010] The method for establishing the tube wave wellbore fracture model is an existing technology, and reference can be made to the method proposed by CHAO LIANG et al. in the literature "Hydraulic fracture diagnostics from Krauklis-wave resonance and tube-wave reflections". Among them, the tube wave wellbore fracture model is divided into a tube wave wellbore model and a tube wave fracture model.

[0011] In this embodiment, for the tube wave wellbore model, the tube wave quality factor is used to characterize the attenuation of the tube wave during the propagation in the wellbore. Before fracturing, the wellbore is sealed by a bridge plug, and after fracturing, the fracture is multi-cluster perforation. The reflection coefficient of the tube wave can be expressed as: ; ; Where: R ( ω ) is the reflection coefficient varying with frequency, and this coefficient is a function of the tube wave frequency, dimensionless; Z f ( ω ) is the fracture impedance varying with frequency, and this coefficient is a function of the tube wave frequency; Z T is the wellbore tube wave impedance, kg / (m 4 ·s); ρ is the wellbore liquid density, kg / m 3 ; c T is the wellbore tube wave velocity, m / s; A T is the cross-sectional area inside the wellbore, m 2 .

[0012] The pressure at the wellhead is related to the injected fluid flow rate and can be expressed in the frequency domain as:

[0013] ; Wherein: h is the propagation length of the pipe wave in the wellbore, i.e., the well depth from the wellhead to the fracture or bridge plug, m; ω 0 is the reference angular frequency, rad / s, and in this paper, 10 rad / s is taken; ω is the angular frequency of the pipe wave; Q T is the flow rate injected at the wellhead, m 3 / s; represents the wellhead pressure in the frequency domain; represents the wellhead injection flow rate in the frequency domain; represents the time factor considering the reflection of the pipe wave; i represents the unit of imaginary number.

[0014] In this embodiment, for the pipe wave fracture model, it is assumed that the movement of the liquid in the fracture containing proppant is one-dimensional Darcy seepage, and the geometric shape of the fracturing fracture satisfies the PKN model. In the low-frequency range (≤5 Hz), the pipe wave wavelength is long enough (assuming the wave velocity is 1500 m / s, and the wavelength of the pipe wave with a frequency of 5 Hz is 300 m), and the single-segment perforation length is less than 100 m. Different perforation clusters receive the same pressure wave because the pressure waves sensed by multiple clusters of fractures are the same. Therefore, multiple clusters of fractures can be equivalent to a single fracture. For a single fracture, the fluid mass conservation equation in the fracture can be expressed as: ; In the formula, is the density of the liquid in the fracture, kg / m 3 ; q is the fluid flow rate in the fracture, m 3 / s; is the porosity of the proppant in the fracturing fracture, dimensionless; A f is the cross-sectional area of the fluid in the fracture, m 2 ; t is the time, s; x is the length of the fluid cross-sectional area from the wellbore, m.

[0015] The propagation law of the pipe wave in the proppant placement layer of the fracture satisfies Darcy's formula: ; In the formula, 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 fracture, Pa.

[0016] According to the PKN model, assuming that the cross-section of the fracturing crack is elliptical and the width of the crack (in the order of millimeters to centimeters) is much smaller than the wavelength of the tube wave (in the order of hundreds of meters to kilometers), in the low-frequency range (≤5 Hz), it is obtained that the equivalent impedance of elliptical cracks can be expressed as: ; wherein, N is the number of clusters of fracturing cracks, dimensionless; G * is the shear modulus of the formation rock, Pa; i is the unit of the 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.

[0017] For the above model, it also has boundary conditions. In this embodiment, the boundary conditions are set as follows: Wellhead boundary condition: Assuming that the variation law of the injection flow rate at the wellhead satisfies the Gaussian function, and its spectrum is also a Gaussian function: ; wherein, is the amplitude of the Gaussian pulse function, m 3 / s; is the unit of the imaginary number; t is the time, s; t c is the central time of the Gaussian pulse signal, s; is the frequency-domain function of the Gaussian pulse flow rate at the wellhead.

[0018] In the embodiment of the present invention, the Gaussian function is used as the characteristic frequency, and the energy above this frequency is small. Other excitation functions are also applicable to the tube wave model of the wellbore-fracture system established herein.

[0019] Bottom-hole boundary condition: For the case of a completely sealed bottom hole, that is, after the bridge plug is set and before single-stage fracturing, the reflection coefficient of the bridge plug can be expressed as ; wherein, R b represents the reflection coefficient of the bridge plug.

[0020] In this step, the parameters for establishing the tube wave wellbore fracture model are the parameters of Dunham et al., (2017), and some of the parameters are shown in Table 1.

[0021] Table 1 Some parameters for establishing the tube wave wellbore fracture model

[0022] S2. Take the pre - fracturing excitation wave and the first echo before fracturing. Perform time - domain segmentation between the pre - fracturing excitation wave and the first echo before fracturing, and zero - pad the data after the segmentation point. Perform Fourier transform on the zero - padded data to obtain the spectral curve of the pre - fracturing excitation wave. Using the tube wave quality factor and the tube wave velocity as the inversion targets, substitute the spectral 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 correct the tube wave wellbore fracture model. It mainly includes the following sub - steps: Excite the tube wave before fracturing and record the time - domain curve of the tube wave before fracturing; Based on the time - domain curve of the tube wave before fracturing, obtain the pre - fracturing excitation wave and the first echo before fracturing. Select a stable point between the pre - fracturing excitation wave and the first echo before fracturing for time - domain segmentation, and zero - pad the data after the segmentation point including the first echo before fracturing. Perform Fourier transform on the zero - padded time - domain curve of the tube wave before fracturing to obtain the spectral curve of the pre - fracturing excitation wave; Substitute the spectral curve of the pre - fracturing excitation wave, the tube wave quality factor, and the tube wave velocity into the tube wave wellbore fracture model to obtain the time - domain curve of the first echo before fracturing, and calculate the eigenvalue of the first echo before fracturing 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; Change the tube wave quality factor and the tube wave velocity, repeat substituting into the tube wave wellbore fracture model and calculate the eigenvalue of the first echo before fracturing, simulate the error distribution of the eigenvalue of the first echo of the simulated data and the eigenvalue of the first echo of the measured data, find the optimal tube wave quality factor and the optimal tube wave velocity, and correct the tube wave wellbore fracture model based on the optimal tube wave quality factor and the optimal tube wave velocity.

[0023] In this embodiment, the tube wave velocity in the wellbore can be expressed in the following form: , where , in the formula: K e f f is the effective bulk elastic modulus, K is the bulk elastic modulus of the wellbore fluid, G is the shear modulus, E is the elastic modulus, e is the wall thickness of the casing, D is the casing diameter, c T is the tube wave velocity.

[0024] As can be seen from above, there are many factors affecting the tube wave velocity, including: wellbore fluid properties, wellbore geometry and elastic mechanics parameters, and formation attribute parameters. The factors that have the greatest impact on the tube wave velocity are the bulk modulus and density of the wellbore fluid, and these two factors are affected by pressure, temperature, gas content, and tube wave frequency. In pure water, when the liquid pressure is 13.79 - 68.95 MPa, the tube wave velocity is 1524 - 1645 m / s.

[0025] According to the characteristics of the tube wave echo time-domain curve, this paper proposes an inversion index for the tube wave velocity, that is: 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 is defined as the flight time of the tube wave, that is: the time for the tube wave to propagate from the wellhead to the bottom of the well and then reflect back to the wellhead. Analyzing the quantitative relationship between the flight time and wave velocity of different wave velocities, the flight time and wave velocity show an approximately linear negative correlation and are monotonically decreasing. From the above rules, it can be seen that as long as the flight time of the tube wave is picked up, the unique tube wave velocity can be found. This conclusion lays a theoretical foundation for the inversion of the tube wave velocity.

[0026] The tube wave is a mechanical wave and has the property of oscillator damping during the propagation in the wellbore. The rate 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 attenuation, and vice versa. According to the existing technology, the range of the tube wave quality factor in the wellbore - fracture system is about 10 - 100. Based on the established tube wave model of wellbore - fracture coupling, the time-domain characteristics of the wellbore echo are calculated under different tube wave quality factors. According to the simulation results, the tube wave quality factor mainly affects the amplitude of the wellbore echo. The larger the tube wave quality factor, the larger the amplitude of the wellhead echo; as time increases, the amplitude of the multiple echoes at the wellhead decays exponentially.

[0027] In this embodiment, a Gaussian pulse is used as the excitation signal at the wellhead, and finally the errors between different wave velocities and different tube wave quality factors and the true parameters are as Figure 1 shown. It can be seen from the figure that the optimal tube wave quality factor obtained by inversion is 29.2, and the optimal tube wave velocity is 1250.5 m / s, which is close to the true tube wave quality factor of 30 and the true tube wave velocity of 1250 m / s (the true value is determined by forward modeling) in this example, indicating that the inversion result is relatively accurate.

[0028] S3. Based on the pressure curve of the hydraulic shock during pump shutdown in fracturing, determine the depth of the main liquid injection point; Take the pressure curve of the hydraulic shock during pump shutdown for a single-stage fracturing, perform Fourier transform to obtain the frequency spectrum curve of the hydraulic shock curve during pump shutdown; Take the peak difference of the frequency spectrum curve of the hydraulic shock curve during pump shutdown and calculate the average value. Based on the average value, calculate the reflection period of the hydraulic shock wave to obtain the preliminary wave velocity of the hydraulic shock; In this embodiment, based on the simulation parameter data, combined with and based on the existing water hammer model of the wellbore-fracture coupling system (reference document "Filtering Method and Characteristic Analysis of Water Hammer Pressure Wave Signal during Fracturing Pump Shut-off", Hu Xiaodong), using the theoretical displacement data of the fracturing pump during shut-off, the shut-off water hammer signal is obtained. The specific shape of the curve is as shown in Figure 2 shown. As can be seen from Figure 2 , the simulated shut-off water hammer signal is clean and clear, with multiple oscillation periods, and lasts for a long time. The water hammer effect is obvious. This figure can provide initial data for subsequent calculations.

[0029] Based on the frequency difference method or the two-dimensional cepstrum method, calculate the depth of the main liquid injection point for single-stage fracturing.

[0030] Then, using the method of this embodiment and the two-dimensional cepstrum calculation method, a two-dimensional cepstrum interpretation diagram is obtained, as shown in Figure 3 shown. It can be seen from the figure that the shut-off time is 400 s, and the color is darker at 4500 m, indicating that the water hammer signal is strong; as time goes by, the color at this position gradually becomes lighter, indicating that the water hammer signal gradually weakens.

[0031] Take the specific numerical values at the two-dimensional cepstrum time points and change along the depth curve, as shown in Figure 4 shown. It can be seen from the figure that there is a local minimum at the liquid injection point position of 4500 m. Therefore, taking points on the two-dimensional cepstrum can effectively locate the depth of the main liquid injection point. In addition, periodic signals will appear on the two-dimensional cepstrum curve at the injection point. The odd-numbered signals are negative, and the even-numbered signals are positive, with positive and negative signals alternating.

[0032] S4. Take the post-fracture excitation wave and the first post-fracture echo after single-stage fracturing, perform time-domain segmentation between the post-fracture excitation wave and the first post-fracture echo, fill zeros for the data after the segmentation point, and perform Fourier transform on the zero-filled data to obtain the frequency spectrum curve of the post-fracture excitation wave; taking the fracture conductivity and fracture height as the inversion targets, substitute the frequency spectrum curve of the post-fracture excitation wave, the tube wave quality factor, the tube wave velocity, and the depth of the main liquid injection point into the tube wave wellbore fracture model for inversion to obtain.

[0033] Generally speaking, the inversion targets for post-fracture inversion are the depth, conductivity, and height of the main liquid injection point of the fracturing fracture. Since three parameters need to be inverted and it is difficult to mutually constrain the three parameters, there is strong multi-solution, and it is difficult to quickly and accurately carry out the inversion of fracturing fracture characteristics. However, the embodiment of the present invention determines the depth of the main liquid injection point, reduces one inversion parameter, reduces the uncertainty of fracture inversion, and at the same time greatly reduces the inversion difficulty and saves the inversion time.

[0034] This step includes the following sub-steps: Excite the tube wave after fracturing and record the time-domain curve of the post-fracture tube wave; Based on the post - pressure tube wave time - domain curve, obtain the post - pressure excitation wave and the post - pressure first echo. Between the post - pressure excitation wave and the post - pressure first echo, select a stable point for time - domain segmentation, and zero - pad the data after the segmentation point including the post - pressure first echo. Perform Fourier transform on the zero - padded post - pressure tube wave time - domain curve to obtain the frequency - spectrum curve of the post - pressure excitation wave; Substitute the frequency - spectrum curve of the post - pressure excitation wave, the tube wave quality factor, the tube wave velocity, and the depth of the main liquid - inlet point into the calibrated tube wave wellbore fracture model to obtain the time - domain curve of the post - pressure first echo, and calculate the eigenvalue of the post - pressure first echo 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. 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 existence of a certain baseline drift phenomenon in the tube wave sensor, while the tube wave echo of the inversion parameters is an ideal waveform with a baseline of 0. Therefore, in such a case, it will not only lead to a large amount of calculation, but also when the echo is weak, it is 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 calculates using the local extreme values of the first echo, can effectively overcome the problem of baseline drift of the actual echo signal, makes the forward - modeled echo waveform and the actual measured waveform fit well, and at the same time greatly reduces the calculation amount, saving time and computing power.

[0035] Based on the measured value of the first echo in the post - pressure tube wave time - domain curve, calculate and obtain the value of the second objective function in the simulated parameter space w and the measured value of the second objective function w The fracture conductivity and fracture height with the minimum error are obtained, and the inversion is completed; the minimum error here can be represented by the difference method, that is, the value of the second objective function in the simulated parameter space w and the measured value of the second objective function w The smaller the absolute value of the difference, the more accurate the result.

[0036] The final inversion result is as Figure 5 shown. From Figure 5 it can be seen that within the set range of conductivity and fracture height, the error function still has a global minimum (the position of the blue cross). Case analysis confirms that the tube wave - water hammer joint inversion algorithm proposed in this embodiment uses water hammer positioning to first constrain the depth of the main liquid - inlet point, and on this basis, can accurately invert the fracture conductivity and fracture height.

[0037] The above are only the preferred embodiments of the present invention, and do not impose any form of limitation on the present invention. Although the present invention is disclosed above in the preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can, within the scope of the technical solution of the present invention, make some changes or modifications to the above-disclosed technical content to obtain equivalent embodiments with equivalent changes. However, as long as the content does not depart from the technical solution of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A joint inversion method for near-wellbore characteristics of hydraulic fracture based on high-frequency tube waves and water hammer, characterized in that It includes the following steps: S1. Based on the excitation source parameters, wellbore parameters, and fracture parameters, establish a pipe wave wellbore fracture model; S2. Take the pre-fracture excitation wave and the first pre-fracture echo before single-stage fracturing. Perform time-domain segmentation between the pre-fracture excitation wave and the first pre-fracture echo, and zero-pad the data after the segmentation point. Perform Fourier transform on the zero-padded data to obtain the spectrum curve of the pre-fracture excitation wave. Using the pipe wave quality factor and the pipe wave velocity as the inversion targets, substitute the spectrum curve of the pre-fracture excitation wave, different pipe wave quality factors, and different pipe wave velocities into the pipe wave wellbore fracture model for inversion to obtain the optimal pipe wave quality factor and the optimal pipe wave velocity, and correct the pipe wave wellbore fracture model; S3. Based on the single-stage fracturing pump shut-off water hammer pressure curve, determine the depth of the main liquid injection point; S4. Take the post-fracture excitation wave and the first post-fracture echo after single-stage fracturing. Perform time-domain segmentation between the post-fracture excitation wave and the first post-fracture echo, and zero-pad the data after the segmentation point. Perform Fourier transform on the zero-padded data to obtain the spectrum curve of the post-fracture excitation wave. Using the fracture conductivity and the fracture height as the inversion targets, substitute the spectrum curve of the post-fracture excitation wave, the pipe wave quality factor, the pipe wave velocity, and the depth of the main liquid injection point into the pipe wave wellbore fracture model for inversion to obtain the results.

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

3. The method according to claim 1, wherein In S1, the pipe wave wellbore fracture model includes a pipe wave wellbore model and a pipe wave fracture model.

4. The method according to claim 1, wherein S2 includes the following sub-steps: Excite the pipe wave before fracturing and record the pre-fracture pipe wave time-domain curve; Based on the pre-fracture pipe wave time-domain curve, obtain the pre-fracture excitation wave and the first pre-fracture echo. Select a stable point between the pre-fracture excitation wave and the first pre-fracture echo for time-domain segmentation, and zero-pad the data after the segmentation point including the first pre-fracture echo. Perform Fourier transform on the zero-padded pre-fracture pipe wave time-domain curve to obtain the spectrum curve of the pre-fracture excitation wave; Substitute the spectral curve of the pre-pressure excitation wave, the tube wave quality factor, and the tube wave velocity into the tube wave wellbore fracture model to obtain the time-domain curve of the first echo before pressure, and calculate the value of (m) before pressure based on the first objective function. The first objective function is as follows: Φ (m) value, and 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 Φ (m) value, find the optimal tube wave quality factor and optimal tube wave velocity, and correct the tube wave wellbore fracture model based on the optimal tube wave quality factor and optimal tube wave velocity.

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

6. The method according to claim 1, wherein S4 includes the following sub-steps: Excite the pipe wave after single-stage fracturing and record the post-fracture pipe wave time-domain curve; Based on the post-fracture pipe wave time-domain curve, obtain the post-fracture excitation wave and the first post-fracture echo. Select a stable point between the post-fracture excitation wave and the first post-fracture echo for time-domain segmentation, and zero-pad the data after the segmentation point including the first post-fracture echo. Perform Fourier transform on the zero-padded post-fracture pipe wave time-domain curve to obtain the spectrum curve of the post-fracture excitation wave; Substitute the spectral curve of the post - pressure excitation wave, the tube wave quality factor, the tube wave velocity, and the depth of the main liquid injection point into the corrected tube wave wellbore fracture model to obtain the time - domain curve of the first echo after pressure, and calculate the eigenvalue of the first echo after pressure 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 value of the second objective function; Based on the measured value of the first echo in the time-domain curve of the post-pressurized tube wave, calculate and obtain the second objective function value within the simulated parameter space w The inversion is completed with the minimum fracture conductivity and fracture height obtained

Images