Underground distributed optical fiber anisotropic shale reservoir guided wave frequency dispersion curve inversion method

Abstract

The invention relates to an underground distributed optical fiber (DAS) anisotropic shale reservoir guided wave frequency dispersion curve inversion method and a medium, and the method comprises the steps: obtaining guided wave seismic data of a shale reservoir, calculating a guided wave frequency dispersion energy diagram according to the obtained guided wave seismic data, and extracting an observation guided wave frequency dispersion curve from the guided wave frequency dispersion energy diagram; establishing an initial anisotropic elastic parameter model of the shale reservoir; according to the initial or updated anisotropic elastic parameter model of the shale reservoir, performing forward modeling to obtain a theoretical guided wave frequency dispersion curve; constructing an objective function, and calculating and judging whether the objective function is converged or not according to a residual error between the theoretical guided wave frequency dispersion curve and the observation guided wave frequency dispersion curve; if the target function converges, outputting an anisotropic elastic parameter model of the current shale reservoir; if the target function is not converged, updating the anisotropic elastic parameter model by adopting a gradient algorithm until the target function is converged; and outputting the optimized anisotropic elastic parameter model of the shale reservoir.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, in particular to the field of seismic inversion technology, and is aimed at the application of downhole distributed optical fiber sensing technology in anisotropic shale reservoirs. Specifically, the present invention proposes a guided wave dispersion curve inversion method and medium for anisotropic shale reservoirs. Background Art

[0002] In geological exploration technology, inversion technology is a branch that uses observed physical phenomena to infer the spatial or structural information of the medium.

[0003] Shale often contains thin flaky particles rich in clay minerals and a certain amount of organic matter. Due to sedimentation and compaction, shale has a layered structure, which results in different elastic properties of shale in different directions, thus showing anisotropy.

[0004] In the existing inversion calculation methods of geological exploration, one type of algorithm usually assumes isotropy for the geological characteristics of some complex reservoirs, which obviously cannot accurately describe the geological characteristics of these complex layers. The underground structure model obtained by inversion based on the assumption of isotropic medium will deviate from the actual situation, affecting reservoir evaluation and prediction.

[0005] Another type of algorithm in the existing inversion method also takes anisotropy into account. However, the existing elastic anisotropic medium guided wave dispersion curve inversion method has low computational efficiency. For example, the Monte Carlo random inversion method requires a large number of random sampling of the model, resulting in a very large amount of calculation. Before finding the global optimal solution, multiple iterations are usually required, and the convergence speed is slow. Especially when the number of iterations is insufficient, the stability of the results is poor, making it difficult to achieve fast and high-precision imaging and characterization of shale layers. Summary of the invention

[0006] In view of the above problems, the purpose of the present invention is to provide a downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve inversion method and medium, which can calculate the structural information of the shale layer with high precision more quickly than the existing inversion methods.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a method for inverting a dispersion curve of an anisotropic shale reservoir guided wave using a distributed optical fiber downhole, the method comprising:

[0009] S1, obtaining guided wave seismic data of the shale reservoir, and calculating a guided wave dispersion energy map based on the obtained guided wave seismic data, and extracting an observed guided wave dispersion curve therefrom;

[0010] S2, establishing an initial anisotropic elastic parameter model of the shale reservoir;

[0011] S3, forward modeling the theoretical guided wave dispersion curve according to the initial or updated anisotropic parameter model of the shale reservoir;

[0012] S4, constructing an objective function, and calculating and judging whether the objective function converges according to the residual between the theoretical waveguide dispersion curve and the observed waveguide dispersion curve;

[0013] S5, if the objective function converges, the anisotropic elastic parameter model of the current shale reservoir is output; if the objective function does not converge, the anisotropic elastic parameter model is updated using a gradient algorithm, and returns to S3 and S4 until the objective function converges;

[0014] S6, output the optimized shale reservoir anisotropic elastic parameter model.

[0015] In one implementation, in S1, guided wave seismic data of the shale reservoir is collected through a downhole distributed optical fiber system.

[0016] In one implementation, in S1, a waveguide dispersion energy map is calculated based on the waveguide seismic data, and an observed waveguide dispersion curve is extracted from the waveguide dispersion energy map.

[0017] In one implementation, the calculation formula of the waveguide dispersion energy diagram is:

[0018]

[0019] Where N is the total number of DAS channels, Φ T,n is the phase shift, It is the guided wave seismic data in the space-frequency domain after amplitude normalization.

[0020] In one implementation, in S2, the anisotropic elastic parameter model of the shale reservoir is initialized according to geological information; the anisotropic elastic parameter model of the shale reservoir includes: vertical P-wave velocity, vertical S-wave velocity, density and Thomsen anisotropic parameters ε, δ;

[0021] In one implementation, in S3, the theoretical waveguide dispersion curve is solved by a dispersion equation;

[0022] The dispersion equation is specifically:

[0023]

[0024] in, is the generalized reflection coefficient related to the wave reflected from the j-1th interface to the jth layer of the medium, is the generalized reflection coefficient related to the wave reflected from the jth interface into the jth layer of the medium. The root of the dispersion equation solved for each layer is the theoretical guided wave dispersion curve corresponding to the current anisotropic elastic parameter model.

[0025] In one implementation, in S4, it includes:

[0026] The least square function of the difference between the observed dispersion curve and the theoretical dispersion curve is used as the objective function;

[0027] In one implementation, in S5, the specific method of updating the anisotropic elastic parameters using the gradient algorithm is:

[0028] The gradient of the objective function with respect to the vertical shear wave velocity is calculated, and then the gradient descent direction and the step size are determined by the Wolfe criterion. The linearized quasi-Newton method L-BFGS-B optimization method is used to update the vertical shear wave velocity.

[0029] Specifically, the calculation formula of the objective function is:

[0030]

[0031] Where ζ is the mode number of the observed dispersion curve, ξ η is the number of dispersion points of the ηth mode of the observed dispersion curve, is the phase velocity of the theoretical dispersion curve at the ηth mode frequency p, is the phase velocity of the observed dispersion curve at the pth mode frequency;

[0032] The formula for the objective function gradient is:

[0033]

[0034] in, k is the wave number, U is the group velocity, ρ is the density, V p0 is the vertical longitudinal wave velocity, V s0 is the vertical shear wave velocity, y1 and y2 are the amplitudes of the horizontal and vertical components of the harmonic solution, respectively;

[0035] The formula for calculating the gradient descent direction is:

[0036]

[0037] Where a is the number of iterations, Λ (a) is The approximate Hessian matrix at Ω (a) is the objective function The gradient of

[0038] The Wolfe criterion is:

[0039]

[0040] in, The objective function is The value at which b1,b2∈(0,1) is a constant, and b1 <b2;

[0041] The linearized quasi-Newton method L-BFGS-B optimization method updates the vertical shear wave velocity formula as follows:

[0042]

[0043] in, is the vertical shear wave velocity at the a+1th iteration, β is the update step size, is In the direction of gradient descent.

[0044] In one implementation, after S5, the method further includes: evaluating the credibility of the inversion result by using a sensitivity function. The calculation formula of the sensitivity function is:

[0045]

[0046] in, F ρ 、F ε and F δ are the sensitive functions of the guided wave dispersion curve to the vertical shear wave velocity, vertical longitudinal wave velocity, density, Thomsen parameters ε and δ respectively.

[0047] In a second aspect, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve inversion method described in the first aspect.

[0048] Compared with the prior art, the present invention is based on anisotropic elastic theory. Compared with the traditional isotropic inversion method, it takes into account the influence of formation anisotropy and can more accurately obtain the vertical shear wave velocity structure of the formation. Among them, the vertical shear wave velocity is a key parameter in the characterization of shale gas reservoirs, which helps to deeply understand the mechanical properties, stress state and fracture distribution of the reservoir, thereby improving the accuracy of reservoir evaluation and the rationality of development decisions. By introducing anisotropic inversion technology, the error caused by the isotropic assumption can be effectively reduced, thereby improving the success rate and economic benefits of hydraulic fracturing unconventional oil and gas development.

[0049] At the same time, the present invention adopts the linearized quasi-Newton method L-BFGS-B optimization method to invert the guided wave dispersion curve. Compared with the existing inversion methods, such as the Monte Carlo random inversion method, it can quickly determine the decreasing direction of the vertical shear wave velocity of the model, so that the objective function converges quickly to the local minimum, greatly improving the convergence speed and calculation efficiency, and realizing the rapid inversion of the vertical shear wave velocity structure of the shale layer. In the process of shale gas drilling and fracturing, when the operating parameters need to be adjusted in real time, the gradient inversion can quickly provide accurate reservoir parameter optimization results, which helps to improve the operating efficiency and safety.

[0050] At the same time, the present invention can analytically calculate the sensitivity functions of the guided wave dispersion curve to the formation density, vertical P- and S-wave velocities and anisotropy parameters. By analyzing the sensitivity of the guided wave dispersion curve to the vertical S-wave velocity, the credibility of the inversion results can be evaluated, which is helpful to interpret the inversion results and provide more accurate data support for shale gas development. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a flow chart of a method for inverting dispersion curves of downhole distributed optical fiber anisotropic shale reservoir guided waves in an embodiment of the present invention;

[0052] Figure 2 The guided wave seismic data stimulated by hydraulic fracturing perforation recorded by distributed optical fiber in horizontal wells simulated by anisotropic geological model in an embodiment of the present invention;

[0053] Figure 3 The following are the waveguide dispersion energy diagram and the extracted dispersion curve calculated by the phase shift method in the embodiment of the present invention;

[0054] Figure 4 This is a model result diagram of the gradient inversion of the anisotropic elastic medium guided wave dispersion curve in an embodiment of the present invention;

[0055] Figure 5 A dispersion curve result diagram of the gradient inversion of the anisotropic elastic medium guided wave dispersion curve in an embodiment of the present invention;

[0056] Figure 6 This is a dispersion curve result diagram based on the inversion of the isotropic elastic medium guided wave dispersion curve in the prior art.

[0057] Figure 7 is the optimized vertical shear wave velocity V of the anisotropic elastic medium guided wave dispersion curve in the embodiment of the present invention s0 Sensitivity function of

[0058] Figure 8 is the dispersion curve of the anisotropic elastic medium guided wave versus the initial vertical longitudinal wave velocity V in the embodiment of the present invention p0 Sensitivity function of

[0059] Fig. 9 is a sensitive function of the anisotropic elastic medium waveguide dispersion curve to the initial density ρ in an embodiment of the present invention;

[0060] Fig.10 is a sensitive function of the anisotropic elastic medium waveguide dispersion curve to the initial Thomsen anisotropy parameter ε in the embodiment of the present invention;

[0061] Fig.11 It is a sensitive function of the anisotropic elastic medium waveguide dispersion curve to the initial Thomsen anisotropy parameter δ in the embodiment of the present invention. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the embodiments of the present invention will be described clearly and completely in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, the present invention General technology in the field All other embodiments obtained by the personnel are within the scope of protection of the present invention.

[0063] In view of the problems of the prior art, the present invention provides a method for inverting the dispersion curve of anisotropic shale reservoir waveguide using an optical fiber downhole distribution method, the method comprising:

[0064] S1, obtaining guided wave seismic data of a shale reservoir, and calculating an observed guided wave dispersion curve based on the obtained guided wave seismic data;

[0065] Specifically, guided wave seismic data of shale reservoirs are collected through a downhole distributed optical fiber system; based on the guided wave seismic data, a guided wave dispersion energy map is calculated, and an observed guided wave dispersion curve is extracted from the guided wave dispersion energy map.

[0066] The shale layer is a low-speed layer sandwiched between high-speed surrounding rocks and is a waveguide structure. The longitudinal and transverse waves excited in the shale layer by hydraulic fracturing perforation or microseismic are confined to propagate in the shale layer, and constructive and destructive interference occurs to form guided waves. The normal vibration guided wave is divided into two modes, namely P-SV and SH mode, both of which have significant dispersion characteristics.

[0067] The embodiment of the present invention uses a distributed fiber optic acoustic wave sensing system for data acquisition. The demodulator of the fiber optic device transmits a series of optical signals that propagate along the optical fiber, and Rayleigh scattering occurs when encountering a point of uneven density in the optical fiber. The acoustic wave perturbs the optical fiber, causing a phase change in the backscattered optical signal. The demodulator calculates the phase change information using the principle of interferometry and converts it into the rate of change of strain. The frequency of the guided waves propagating in the shale reservoir caused by hydraulic fracturing is very high and has significant dispersion characteristics. The sensors deployed on the ground can only detect very weak guided wave signals. Therefore, downhole sensors are required to observe the guided waves at close range in the low-velocity layer. However, the existing data acquisition technology is not only expensive but also very difficult to deploy seismic detectors downhole. In addition, the frequency of the guided waves is very high, and traditional seismic detectors will produce false frequency interference when recording data. The high-precision sampling of distributed optical fibers in time and space can ensure the recording of high-frequency guided wave information without false frequency, which has great advantages in high-precision reservoir imaging.

[0068] The phase shift method is used to calculate the dispersion energy map of the guided wave seismic data observed by the downhole distributed optical fiber, and the observed guided wave dispersion curve is extracted from it, including: transforming the seismic data into the space-frequency domain by fast Fourier transform; for each given frequency, tilt stacking is performed along different speeds in the spatial direction, and the total number of DAS channels is normalized. The formula for calculating the observed guided wave dispersion energy map is:

[0069]

[0070] Where N is the total number of DAS channels, Φ T,n is the phase shift, It is the guided wave seismic data in the space-frequency domain after amplitude normalization.

[0071] S2, establishing an initial anisotropic elastic parameter model of the shale reservoir;

[0072] Specifically, an initial anisotropic elastic parameter model of the shale reservoir is established based on geological information, including vertical P-wave velocity, vertical S-wave velocity, density and Thomsen anisotropic parameters ε and δ.

[0073] S3, forward modeling the initial or updated anisotropic elastic parameter model of the shale reservoir to obtain a theoretical guided wave dispersion curve;

[0074] Specifically, the generalized reflection-transmission coefficient method is used to calculate the theoretical P-SV guided wave dispersion curve corresponding to the initial or updated anisotropic elastic parameter model. The dispersion equation corresponding to the generalized reflection-transmission coefficient method is expressed as:

[0075]

[0076] in, is the generalized reflection coefficient related to the wave reflected from the j-1th interface to the jth layer of the medium, is the generalized reflection coefficient related to the wave reflected from the jth interface into the jth layer of the medium;

[0077] Solving the root of the dispersion equation for each layer is the theoretical waveguide dispersion curve corresponding to the current structural information model.

[0078] S4, constructing an objective function, and calculating and judging whether the objective function converges according to the residual between the theoretical waveguide dispersion curve and the observed waveguide dispersion curve;

[0079] Specifically, the calculation formula of the objective function is:

[0080]

[0081] Where ζ is the mode number of the observed dispersion curve, ξ η is the number of dispersion points of the ηth mode of the observed dispersion curve, is the phase velocity of the theoretical dispersion curve at the ηth mode frequency p, is the phase velocity at frequency p of the ηth mode of the observed dispersion curve.

[0082] S5, if the objective function converges, the anisotropic elastic parameter model of the current shale reservoir is output; if the objective function does not converge, the anisotropic elastic parameter model is updated using a gradient algorithm, and returns to S3 and S4 until the objective function converges;

[0083] Specifically, the steps of updating the anisotropic elastic parameter model using the gradient algorithm are as follows: first, the gradient of the objective function with respect to the vertical shear wave velocity is calculated, then the gradient descent direction and the Wolfe criterion are calculated to determine the step size, and finally, the linearized quasi-Newton method L-BFGS-B optimization method is used to update the vertical shear wave velocity.

[0084] Among them, the formula of the objective function gradient is:

[0085]

[0086] in, k is the wave number, U is the group velocity, ρ is the density, V p0 is the vertical longitudinal wave velocity, V s0 is the vertical shear wave velocity, y1 and y2 are the amplitudes of the horizontal and vertical components of the harmonic solution, respectively;

[0087] The formula for calculating the gradient descent direction is:

[0088]

[0089] Where a is the number of iterations, Λ(a) is The approximate Hessian matrix at Ω (a) is the objective function The gradient of

[0090] The Wolfe criterion is:

[0091]

[0092] in, The objective function is The value at which b1,b2∈(0,1) is a constant, and b1 <b2;

[0093] The linearized quasi-Newton method L-BFGS-B optimization method updates the vertical shear wave velocity formula as follows:

[0094]

[0095] in, is the vertical shear wave velocity at the a+1th iteration, β is the update step size, is In the direction of gradient descent.

[0096] Furthermore, the sensitivity function of the guided wave dispersion curve to the optimized anisotropic elastic parameters is calculated, the influence of the anisotropic elastic parameter disturbance on the guided wave dispersion curve is analyzed, and the credibility of the inversion result is evaluated. Among them, the calculation formula of the sensitivity function of the guided wave dispersion curve to the anisotropic elastic parameters is:

[0097]

[0098] in, F ρ 、F ε and F δ are the sensitive functions of the guided wave dispersion curve to the vertical shear wave velocity, vertical longitudinal wave velocity, density, and Thomsen anisotropy parameters ε and δ, respectively.

[0099] S6, output the optimized shale reservoir anisotropic elastic parameter model.

[0100] In combination with more detailed embodiments of the present application and its accompanying drawings, the process of the method provided by the present application is explained in further examples, and its technical effects are explained.

[0101] Example 1 discloses a method for inverting the dispersion curve of downhole distributed optical fiber shale reservoir guided waves. Figure 1 As shown, the specific steps include:

[0102] Step 1: Use numerical simulation to obtain the guided wave seismic data of horizontal well DAS observation. Specifically, use the model shown in Table 1 to discretize the model into 550×2260 grid points, with a grid point spacing of 0.5 m and a time step of 4×10 -5 The source and the detector are arranged 12.5 meters below the interface between layer 1 and layer 2. The staggered grid finite difference method is used, the absorbing boundary is the CPML boundary, the source uses a vertical force source to simulate hydraulic fracturing perforation, the excitation function is a Ricker wavelet with a main frequency of 400 Hz, the shot distance is 100 meters, the detector spacing is 1 meter, a total of 1000 channels, the total simulation time is 1 second, and the time sampling interval is 4×10 -4 Seconds, perform simulation to obtain the horizontal velocity data of the geophone particle of the horizontal well waveguide, and then use the finite difference formula to convert the simulated horizontal velocity of the geophone particle into the DAS strain rate. The formula for converting the horizontal velocity of the geophone particle into the DAS strain rate is as follows:

[0103]

[0104] Where x is the distance from the DAS channel to the source, and L is the DAS gauge length. In this embodiment, L is set to 2 m. The guided wave seismic data of the horizontal well distributed optical fiber observation obtained by converting the simulated detector data is as follows: Figure 2 shown.

[0105]

[0106] Table 1

[0107] Step 2: Calculate the waveguide dispersion energy diagram using the phase shift method and extract the observed waveguide dispersion curve from it. Specifically, convert the seismic data Perform a one-dimensional Fourier transform along the time direction to obtain After the transformation of seismic data Normalize the amplitude to get Then, the given phase velocity and frequency are tilted and superimposed to obtain the guided wave dispersion energy map A. s (ω,c T ).like Figure 3 As shown, the background is the dispersion energy diagram, and the symbol “+” is the extracted observation Measuring guided wave dispersion The expression for calculating the waveguide dispersion energy diagram using the phase shift method is:

[0108]

[0109] Where N is the total number of DAS channels, Φ T,n is the phase shift, It is the space-frequency domain seismic data after amplitude normalization.

[0110] Step 3: The initial anisotropic elastic parameter model is established, including the thickness, density, vertical longitudinal wave velocity, vertical shear wave velocity and Thomsen anisotropic parameters ε and δ of each layer.

[0111] Step 4, use the generalized reflection-transmission coefficient method to calculate the theoretical dispersion curve, specifically: define stress and displacement vectors for each layer, use the relationship between the generalized reflection-transmission coefficient and the stress and displacement vector to transmit the wave field, starting from the upper half of the infinite space, by transmitting the generalized reflection-transmission coefficient layer by layer, applying the boundary conditions in the lower half of the space, that is, the wave decays to zero at infinity, and obtains the dispersion equation. Select the frequency range of the observed dispersion curve as the frequency range for calculating the theoretical dispersion curve, use the numerical method to solve the dispersion equation, and find the phase velocity corresponding to each frequency. The dispersion equation expression corresponding to the generalized reflection-transmission coefficient method is:

[0112]

[0113] in, is the generalized reflection coefficient related to the wave reflected from the j-1th interface to the jth layer of the medium, is the generalized reflection coefficient related to the wave reflected from the jth interface to the jth layer of the medium. The root of the dispersion equation solved for each layer is the waveguide theory dispersion curve of the corresponding model.

[0114] Step 5: Take the least square function of the difference between the observed dispersion curve and the theoretical dispersion curve as the objective function. Specifically, calculate the variance of the phase velocity under the corresponding mode and frequency of the observed dispersion curve and the theoretical dispersion curve, sum them up, and then take the average of the number of dispersion points and the number of modes respectively. The objective function expression is:

[0115]

[0116] Where ζ is the mode number of the observed dispersion curve, ξ η is the number of dispersion points of the ηth mode of the observed dispersion curve, is the phase velocity of the theoretical dispersion curve at the ηth mode frequency p, is the phase velocity at frequency p of the ηth mode of the observed dispersion curve.

[0117] Step 6: Calculate the objective function gradient. The objective function gradient expression is:

[0118]

[0119] in, k is the wave number, U is the group velocity, ρ is the density, V p0 is the vertical longitudinal wave velocity, V s0 is the vertical shear wave velocity, y1 and y2 are the horizontal and vertical component amplitudes of the harmonic solution, respectively.

[0120] Step 7: Determine whether the objective function or the objective function gradient satisfies the given convergence condition. If the convergence condition is satisfied, the vertical shear wave velocity is output; if the convergence condition is not satisfied, proceed to the next step.

[0121] Step 8: Use the linearized quasi-Newton method L-BFGS-B optimization method to update the vertical shear wave velocity. Specifically, the descent direction is calculated using a variant of the quasi-Newton method L-BFGS-B, and the step size is determined based on the Wolfe criterion. The expression for updating the vertical shear wave velocity using the linearized quasi-Newton method L-BFGS-B optimization method is:

[0122]

[0123] in, is the vertical shear wave velocity at the a+1th iteration, β is the update step size, is The gradient descent direction is calculated as:

[0124]

[0125] Among them, Λ (a) is The approximate Hessian matrix at Ω (a) is the objective function The gradient of . The step size β satisfies the Wolfe criterion, that is:

[0126]

[0127] in, The objective function is The value at which b1,b2∈(0,1) is a constant, and b1 <b2。

[0128] Step 9, repeating steps 4 to 7 until the objective function reaches a predetermined convergence standard. After the iteration is completed, the optimized vertical shear wave velocity is output. Figure 4 and Figure 5 The vertical shear wave velocity and dispersion curve results obtained by gradient inversion of the anisotropic elastic medium guided wave dispersion curve in the present invention are shown. It can be seen that the inversion model and data fit in this embodiment are both high. Figure 6 The inversion result based on the isotropic theory is improved by the present invention.

[0129] Step 10, calculate the sensitivity function of the guided wave dispersion curve to the anisotropic elastic parameters, such as Figure 7-Figure 11 As shown, Figure 7 is the sensitivity function of the anisotropic elastic medium wave dispersion curve to the optimized vertical shear wave velocity, Figure 8-Figure 11 is the sensitivity function of the anisotropic elastic medium wave dispersion curve to the initial vertical longitudinal wave velocity, density, Thomsen anisotropy parameters ε and δ. Figure 7 It can be seen that the guided wave dispersion curve is more sensitive to the vertical shear wave velocity of the upper and middle layers, and less sensitive to the vertical shear wave velocity of the lower layer. Therefore, the vertical shear wave velocity of the upper and middle layers obtained by inversion is more reliable, and the vertical shear wave velocity of the lower layer is less reliable.

[0130] The present invention also discloses a downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve inversion system, comprising:

[0131] An observation dispersion curve extraction module calculates the waveguide dispersion energy diagram by τ-p transformation, fk transformation or phase shift method, and extracts the observation waveguide dispersion curve from it;

[0132] Theoretical dispersion curve forward modeling module calculates theoretical guided wave dispersion curves by generalized reflection-transmission coefficient method and other methods;

[0133] The objective function judgment module calculates the objective function between the observed dispersion curve and the theoretical dispersion curve. If the objective function meets the convergence condition, the vertical shear wave velocity is output. If not, the next module is entered.

[0134] The objective function gradient calculation module calculates the gradient of the objective function with respect to the vertical shear wave velocity.

[0135] The vertical shear wave velocity update module calculates the step size and gradient descent direction, updates the vertical shear wave velocity through the linearized quasi-Newton method L-BFGS-B optimization method, calculates the theoretical dispersion curve corresponding to the updated model, recalculates the objective function, and determines whether it meets the convergence conditions until the objective function meets the convergence conditions.

[0136] The credibility evaluation module calculates the sensitivity function of the guided wave dispersion curve to the vertical shear wave velocity obtained by inversion, analyzes the sensitivity of the guided wave dispersion curve to the vertical shear wave velocity obtained by inversion, and evaluates the credibility of the vertical shear wave velocity obtained by inversion.

[0137] In the several embodiments provided by the present invention, it should be understood that the disclosed method can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0138] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the above-mentioned method in each embodiment of the present invention. The above-mentioned storage medium includes: a USB flash drive, a mobile hard disk, Read-only memory OnlyMemory,ROM), RandomAccessMemory, RAM), magnetic disks, or optical disks, etc.

[0139] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for inverting the dispersion curve of anisotropic shale reservoir waveguide using distributed optical fiber downhole, characterized in that: The method comprises: S1, obtaining guided wave seismic data of the shale reservoir, and calculating a guided wave dispersion energy map based on the obtained guided wave seismic data, and extracting an observed guided wave dispersion curve therefrom; S2, establishing an initial anisotropic elastic parameter model of the shale reservoir; S3, forward modeling the initial or updated anisotropic elastic parameter model of the shale reservoir to obtain a theoretical guided wave dispersion curve; S4, constructing an objective function, and calculating and judging whether the objective function converges according to the residual between the theoretical waveguide dispersion curve and the observed waveguide dispersion curve; S5, if the objective function converges, the anisotropic elastic parameter model of the current shale reservoir is output; if the objective function does not converge, the anisotropic elastic parameter model is updated using a gradient algorithm, and returns to S3 and S4 until the objective function converges; S6, output the optimized shale reservoir anisotropic elastic parameter model.

2. The method for inverting the dispersion curve of anisotropic shale reservoir waveguide using downhole distributed optical fiber according to claim 1, characterized in that: In S1, guided wave seismic data of the shale reservoir is collected through a downhole distributed optical fiber system.

3. The method for inversion of downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve according to claim 1, characterized in that: In S1, a waveguide dispersion energy map is calculated based on the waveguide seismic data, and an observed waveguide dispersion curve is extracted therefrom.

4. The method for inversion of downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve according to claim 1, characterized in that: The calculation formula of the guided wave dispersion energy diagram is: Where N is the total number of distributed fiber channels, Φ T,n is the phase shift, It is the guided wave seismic data in the space-frequency domain after amplitude normalization.

5. The method for inversion of downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve according to claim 1, characterized in that: In S2, an initial anisotropic elastic parameter model of the shale reservoir is constructed according to geological information; the anisotropic elastic parameter model of the shale reservoir includes: vertical P-wave velocity, vertical S-wave velocity, density and Thomsen anisotropic parameters ε and δ.

6. The method for inversion of downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve according to claim 1, characterized in that: In said S3, the theoretical waveguide dispersion curve is solved by the dispersion equation; The dispersion equation is specifically: in, is the generalized reflection coefficient related to the upgoing wave reflected from the j-1th interface into the jth layer of the medium, is the generalized reflection coefficient related to the wave reflected from the downlink wave through the jth interface into the jth layer of the medium; the root of the dispersion equation solved for each layer is the theoretical guided wave dispersion curve corresponding to the current anisotropic elastic parameter model.

7. The method for inversion of downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve according to claim 1, characterized in that: In the above S4, a least square function of the difference between the observed dispersion curve and the theoretical dispersion curve is used as the objective function.

8. The method for inversion of downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve according to claim 1, characterized in that: In S5, the specific method of updating the anisotropic elastic parameters using the gradient algorithm is: The gradient of the objective function with respect to the vertical shear wave velocity is calculated, and then the gradient descent direction and the step size are determined by the Wolfe criterion. The linearized quasi-Newton method L-BFGS-B optimization method is used to update the vertical shear wave velocity.

9. The method for inversion of downhole distributed optical fiber anisotropic shale reservoir guided wave dispersion curve according to claim 1, characterized in that: The calculation formula of the objective function is: Where ζ is the mode number of the observed dispersion curve, ξ η is the number of dispersion points of the ηth mode of the observed dispersion curve, is the phase velocity of the theoretical dispersion curve at the ηth mode frequency p, is the phase velocity of the observed dispersion curve at the pth mode frequency; The formula of the objective function gradient is: in, k is the wave number, I is the group velocity, ρ is the density, V p0 is the vertical longitudinal wave velocity, V s0 is the vertical shear wave velocity, y1 and y2 are the amplitudes of the horizontal and vertical components of the harmonic solution, respectively; The formula for calculating the gradient descent direction is: Where a is the number of iterations, Λ (a) is The approximate Hessian matrix at Ω (a) is the objective function for the current vertical shear wave velocity The gradient of The Wolfe criterion is: in, The objective function is The value at which b1,b2∈(0,1) is a constant, and b1 <b2; The linearized quasi-Newton method L-BFGS-B optimization method updates the vertical shear wave velocity formula as follows: in, is the vertical shear wave velocity at the a+1th iteration, β is the update step size, is In the direction of gradient descent.

10. The method for inverting the dispersion curve of anisotropic shale reservoir waveguide using downhole distributed optical fiber according to claim 1, characterized in that: After S5, the method further includes: evaluating the credibility of the inversion result by using a sensitivity function; wherein the calculation formula of the sensitivity function is: in, F ρ 、F ε and F δ are the sensitive functions of the guided wave dispersion curve to the vertical shear wave velocity, vertical longitudinal wave velocity, density, and Thomsen anisotropy parameters ε and δ, respectively.

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