A method and system for low-frequency compensation seismic inversion of fracture weakness in HTI media

Abstract

The present invention discloses a low-frequency compensation seismic inversion method and system for fracture weakness in HTI medium, comprising: obtaining seismic data; obtaining fracture weakness parameters according to seismic data and fracture weakness parameter estimation model; wherein the process of obtaining the fracture weakness parameter estimation model is: establishing a forward initial model in Laplace-Fourier domain; adding the reflection coefficient equation of PP wave in HTI medium to the forward initial model to obtain the forward model in Laplace-Fourier domain; analyzing the forward model in Laplace-Fourier domain by Bayesian theory to obtain the target function to be inverted; solving the target function to be inverted to obtain the fracture weakness parameter estimation model. The stability and prediction accuracy of fracture weakness inversion are improved.

Description

Technical Field

[0001] The present invention relates to the field of seismic exploration technology, and in particular to a HTI medium fracture weakness low-frequency compensation seismic inversion method and system. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] Natural fractured reservoirs contain abundant oil and gas resources. Fractured reservoirs refer to reservoirs with fractures as the main storage space and seepage channels, which can increase effective porosity and generally have high permeability characteristics. The porosity and permeability of rocks are important parameters that reflect the ability of rocks to store and transport fluids, and fractured reservoirs have the characteristics of large porosity and high permeability. Therefore, fractures contribute to the high and stable production of oil and gas and play an important role in improving the porosity and permeability of sedimentary basins. The normal and tangential fracture weakness parameters are directly related to the anisotropy induced by fractures and can be used to characterize the fluid filling conditions in fractures. Low-frequency components play an important role in seismic inversion. Existing seismic inversions are highly dependent on low-frequency models. Due to the limitations of seismic acquisition conditions, the collected seismic data often lack low-frequency components, resulting in inaccurate seismic inversion results. Summary of the invention

[0004] In order to solve the above problems, the present disclosure proposes a seismic inversion method and system for low-frequency compensation of fracture weakness in HTI media.

[0005] To achieve the above objectives, the present disclosure adopts the following technical solutions:

[0006] First, a low-frequency compensation seismic inversion method for fracture weakness in HTI media is proposed, including:

[0007] Acquisition of seismic data;

[0008] According to the seismic data and the fracture weakness parameter estimation model, the fracture weakness parameters are obtained;

[0009] Among them, the process of obtaining the fracture weakness parameter estimation model is as follows: establish the forward initial model of the Laplace-Fourier domain; add the reflection coefficient equation of the PP wave in the HTI medium to the forward initial model to obtain the forward model of the Laplace-Fourier domain; analyze the forward model of the Laplace-Fourier domain through the Bayesian theory to obtain the objective function that needs to be inverted; solve the objective function that needs to be inverted to obtain the fracture weakness parameter estimation model.

[0010] Secondly, a low-frequency compensation seismic inversion system for HTI medium fracture weakness is proposed, including:

[0011] A data acquisition module, used for acquiring seismic data;

[0012] A fracture weakness parameter acquisition module is used to obtain fracture weakness parameters according to seismic data and a fracture weakness parameter estimation model;

[0013] Among them, the process of obtaining the fracture weakness parameter estimation model is as follows: establish the forward initial model of the Laplace-Fourier domain; add the reflection coefficient equation of the PP wave in the HTI medium to the forward initial model to obtain the forward model of the Laplace-Fourier domain; analyze the forward model of the Laplace-Fourier domain through the Bayesian theory to obtain the objective function that needs to be inverted; solve the objective function that needs to be inverted to obtain the fracture weakness parameter estimation model.

[0014] In a third aspect, an electronic device is proposed, comprising a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the steps described in a method for low-frequency compensation seismic inversion of fracture weakness in HTI media are completed.

[0015] In a fourth aspect, a computer-readable storage medium is proposed for storing computer instructions. When the computer instructions are executed by a processor, the steps described in a method for low-frequency compensation seismic inversion of fracture weakness in HTI media are completed.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] 1. Based on the Bayesian framework, this disclosure proposes a seismic inversion method in the Laplace-Fourier domain that is independent of the initial model, and adds a Cauchy constraint to reduce the uncertainty of the inversion results.

[0018] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings in the specification, which constitute a part of the present application, are used to provide further understanding of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute improper limitations on the present application.

[0020] Figure 1 This is a flow chart of the method disclosed in Example 1 of the present disclosure;

[0021] Figure 2 The synthetic seismic record gathers with different signal-to-noise ratios at azimuths of 15° and 45°;

[0022] Figure 3is the low-frequency component of the fracture weakness parameter estimated by the method disclosed in Example 1 under different signal-to-noise ratio conditions;

[0023] Figure 4 The final fracture weakness parameter inversion results obtained by the traditional inversion method and the method disclosed in Example 1 under different signal-to-noise ratio conditions are compared;

[0024] Figure 5 is a stacked seismic section;

[0025] Figure 6 is the low-frequency component of the estimated fracture weakness parameter;

[0026] Figure 7 is the final inversion result of normal fracture weakness parameters;

[0027] Figure 8 is the final inversion result of the tangential fracture weakness parameters;

[0028] Fig. 9 is the relative error of the estimated fracture weakness parameters. DETAILED DESCRIPTION

[0029] The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

[0030] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0031] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0032] Example 1

[0033] Low-frequency components play an important role in seismic inversion. However, due to the limitations of seismic acquisition conditions, the collected seismic data often lack low-frequency components. Many scholars have devoted themselves to studying the compensation of low-frequency components. One method is to use smooth model constraints, and the other is to use the damped wave field in the Laplace-Fourier domain. This embodiment is based on Bayesian theory and proposes a seismic inversion method for low-frequency compensation of fracture weakness in HTI media in the Laplace-Fourier domain. This method obtains the low-frequency component of the fracture weakness parameter, and finally obtains the inversion result of the fracture weakness parameter to solve the problem that seismic inversion is highly dependent on the initial model. Figure 1-9 As shown, including:

[0034] Acquisition of seismic data;

[0035] According to the seismic data and the fracture weakness parameter estimation model, the fracture weakness parameters are obtained;

[0036] Among them, the process of obtaining the fracture weakness parameter estimation model is as follows: establish the forward initial model of the Laplace-Fourier domain; add the reflection coefficient equation of the PP wave in the HTI medium to the forward initial model to obtain the forward model of the Laplace-Fourier domain; analyze the forward model of the Laplace-Fourier domain through the Bayesian theory to obtain the objective function that needs to be inverted; solve the objective function that needs to be inverted to obtain the fracture weakness parameter estimation model.

[0037] Furthermore, the process of establishing the forward initial model in the Laplace-Fourier domain is as follows:

[0038] A convolution model is established; Laplace transform is performed on the convolution model to obtain the forward initial model in the Laplace-Fourier domain.

[0039] Furthermore, the seismic data obtained include amplitude, longitudinal wave velocity, shear wave velocity, density, incident angle, and azimuth.

[0040] Furthermore, the fracture weakness parameter estimation model includes a normal fracture weakness parameter estimation model and a tangential fracture weakness parameter estimation model.

[0041] Furthermore, an iterative reweighted least squares algorithm is used to solve the objective function that needs to be inverted to obtain the fracture weakness parameter model.

[0042] Furthermore, the fracture weakness parameter estimation model is:

[0043] Δ N =LδΔ N

[0044] Δ T =LδΔT

[0045] Among them, Δ N , Δ T are the normal crack weakness parameter and the tangential crack weakness parameter, respectively.

[0046] Furthermore, the reflection coefficient equation of pp waves in HTI media is:

[0047]

[0048] in, and are longitudinal wave modulus, transverse wave modulus and density respectively; Δ N , Δ T are the normal and tangential crack weakness parameters, respectively.

[0049] A method for low-frequency compensation seismic inversion of HTI medium fracture weakness disclosed in this embodiment is described in detail.

[0050] A low-frequency compensation seismic inversion method for HTI medium fracture weakness, comprising:

[0051] Acquisition of seismic data;

[0052] The fracture weakness parameters are obtained according to the seismic data and the fracture weakness parameter estimation model.

[0053] Among them, the seismic data obtained include amplitude, longitudinal wave velocity, shear wave velocity, density, incident angle, and azimuth.

[0054] When obtaining fracture weakness parameters based on seismic data and fracture weakness parameter estimation model, the fracture medium with isotropic medium rock as background information is firstly equivalent to HTI medium, then the seismic data is imported and finally the fracture weakness parameters are obtained based on the fracture weakness parameter estimation model.

[0055] The specific process of obtaining the fracture weakness parameter estimation model is as follows:

[0056] S1: Construct a convolution model.

[0057] Robinson (1967) proposed the convolution model, that is, the seismic record can be approximated as the convolution of the wavelet and the reflection coefficient. The convolution expression, that is, the convolution model is:

[0058]

[0059] Among them, t represents the time domain, τ represents the time shift, s(t) is the seismic record, w(t) is the wavelet, and r(t) is the reflection coefficient.

[0060] S2: Perform Laplace transform on the convolution model to obtain the forward initial model in the Laplace-Fourier domain, specifically:

[0061] According to the Laplace transform principle, the seismic record expression in the Laplace-Fourier domain can be obtained from formula (1):

[0062]

[0063] Among them, S(σ+iω) is the seismic record after Laplace-Fourier transform, W(σ+iω) is the wavelet matrix in the Laplace-Fourier domain, r(τ) is the reflection coefficient, σ is the damping factor, ω is the circular frequency, and τ represents time.

[0064] Therefore, equation (2) can be written as the forward initial model in the Laplace-Fourier domain:

[0065] S ω =W ω ·C·E ω ·R (3)

[0066] Among them, S w is the Laplace amplitude spectrum when the frequency is ω, and R is the reflection coefficient.

[0067]

[0068]

[0069]

[0070] Where n is the number of sampling points and k is the number of damping factors.

[0071] S3: The reflection coefficient equation of PP waves in HTI media is added to the initial forward model to obtain the forward model in the Laplace-Fourier domain.

[0072] Specifically, the reflection coefficient R in the initial forward model of the Laplace-Fourier domain is used to adopt the reflection coefficient equation of the PP wave in the HTI medium derived based on the Born integral and the steady phase method. The reflection coefficient equation of the PP wave in the HTI medium is:

[0073]

[0074] Among them, θ and φ represent the incident angle and azimuth respectively, R PP (θ, φ) represents the reflection coefficient at different incident angles and azimuths, and are the longitudinal wave modulus, transverse wave modulus and density, δΔ N , δΔ T are the differences between the normal crack weakness parameter and the tangential crack weakness parameter,

[0075]

[0076] in, α and β are the longitudinal and shear wave velocities, respectively; θ and φ are the incident angle and azimuth, respectively.

[0077] Taking two azimuths and two incident angles as an example, the difference in reflection coefficients at two different azimuths can be obtained:

[0078]

[0079] Among them, ΔR pp (θ n ,t n ) is the difference in reflection coefficient at different azimuths,

[0080]

[0081] l(θ m ,t n )=2g n (sin 2 θ m (cos 2 φ2-cos 2 φ1)-sin 2 θ m tan 2 θ m (sin 2 φ2cos 2 φ2-sin 2 φ1cos 2 φ1)) (11)

[0082] Formula (9) can be written as:

[0083] ΔR pp =P·m (12)

[0084] Therefore, the preliminary forward model in the Laplace-Fourier domain can be obtained as follows:

[0085] d=G·m (13)

[0086] Among them, d is the Laplace spectrum difference at different azimuth angles, m is the model parameter,

[0087] G=W ω ·C·E ω ·P (14)

[0088] Considering the real and imaginary parts of the Laplace-Fourier domain, equation (13) can be written as:

[0089]

[0090] Therefore, the final Laplace-Fourier domain forward model is obtained as follows:

[0091] d ri =G ri ·m (16)

[0092] S4: The forward model in the Laplace-Fourier domain is analyzed by Bayesian theory to obtain the objective function that needs to be inverted.

[0093] According to the Bayesian theory, the forward model (16) in the Laplace-Fourier domain is analyzed and we can get:

[0094]

[0095] From this we can get the objective function that needs to be inverted:

[0096]

[0097] in, are the variances of the noise and model parameters, respectively.

[0098] S5: Solve the objective function that needs to be inverted to obtain a fracture weakness parameter estimation model.

[0099] According to the established objective function, the iterative reweighted least squares algorithm is used to solve equation (18), and then the following transformation is performed to obtain the fracture weakness parameter estimation model:

[0100] Δ N =LδΔ N (19)

[0101] Δ T =LδΔ T (20)

[0102] Where L represents the integral matrix, δΔ N , δΔ T are the differences between the normal fracture weakness parameter and the tangential fracture weakness parameter. The fracture weakness parameter estimation model obtained is used as the initial model to solve the acquired seismic data in the time domain to obtain the final fracture weakness parameter estimation result.

[0103] A set of synthetic logging data is used to invert fracture weakness parameters to verify the feasibility and robustness of the method disclosed in this embodiment.

[0104] Figure 2 The seismic traces with different signal-to-noise ratios are generated by convolution of the reflection coefficient calculated by logging data and 30Hz Ricker wavelet, where (a) is a synthetic seismic record without noise, (b) is a synthetic seismic record when SNR=5, and (c) is a synthetic seismic record when SNR=2. The synthetic seismic records with different azimuths and incident angles are extracted and inverted by the method disclosed in this embodiment to obtain Figure 3 The low-frequency components of the fracture weakness parameters shown in the figure, where (a) is the low-frequency components of the fracture weakness parameters estimated under noise-free conditions, (b) is the low-frequency components of the fracture weakness parameters estimated when SNR=5, and (c) is the low-frequency components of the fracture weakness parameters estimated when SNR=2. The dotted line represents the low-frequency components of the fracture weakness parameters obtained by seismic inversion in the Laplace-Fourier domain, the solid line is the original true fracture weakness parameter, and the dotted line is the initial linear fracture weakness parameter. The inversion results show that when the signal-to-noise ratio is greater than or equal to 2, the method proposed in this embodiment can better estimate the low-frequency components of the fracture weakness parameters.

[0105] The obtained fracture weakness parameter estimation model is used as the initial model, and Bayesian seismic inversion is performed in the time domain to obtain the final fracture weakness parameters. The inversion results are shown in Figure 4 As shown in (a)-(c), (a) is a comparison of the final fracture weakness parameter inversion results obtained by the traditional inversion method and the method proposed in this embodiment under noise-free conditions, (b) is a comparison of the final fracture weakness parameter inversion results obtained by the traditional inversion method and the method proposed in this embodiment when SNR=5, and (c) is a comparison of the final fracture weakness parameter inversion results obtained by the traditional inversion method and the method proposed in this embodiment when SNR=2. The dotted line represents the low-frequency component of the fracture weakness parameter in the Laplace-Fourier domain for seismic inversion, the solid line is the original true fracture weakness parameter, the dotted line represents the fracture weakness parameter inverted by the traditional time domain method, and the dotted line represents the fracture weakness parameter inverted by the method. The root mean square error of the fracture weakness parameter estimated by the traditional inversion method and the method proposed in this embodiment is shown in Table 1. It can be seen that the method proposed in this embodiment improves the stability and accuracy of seismic inversion, and verifies the feasibility of the method proposed in this embodiment.

[0106] Table 1. Root mean square error values ​​of different inversion methods

[0107] (a)Δ N The root mean square error of

[0108]

[0109] (b)Δ T The root mean square error of

[0110]

[0111] In order to prove the practicability of the method disclosed in this embodiment, a field data example is also proposed. The two inversion methods are applied to the field data of a gas-bearing fractured reservoir in China. Figure 5 Figure 1 is a superimposed seismic profile at a small incident angle and different azimuths, where (a) is a seismic profile at an incident angle of 18° and an azimuth of 40°, and (b) is a seismic profile at an incident angle of 18° and an azimuth of 130°. Since the difference in seismic amplitude at different azimuths can be used to estimate the fracture weakness parameters, in this embodiment, the difference in seismic amplitude at different azimuths is used to estimate the low-frequency component. Figure 6 is the estimated Δ N , Δ T Low frequency component, where (a) is Δ N The low-frequency component of (b) is Δ T In addition, the final fracture weakness parameters obtained by the traditional inversion method and the method proposed in this embodiment are as follows: Figure 7 and Figure 8 As shown, Figure 7 (a) is the Δ estimated by the traditional inversion method. N , (b) is the Δ estimated by the method proposed in this embodiment N , Figure 8 (a) is the Δ estimated by the traditional inversion method. T , (b) is the Δ estimated by the method proposed in this embodiment T Then, the relative error of the fracture weakness parameter at the well location is calculated, as Fig. 9 As shown. From these results, it can be seen that the relative error of the fracture weakness parameters is less than 20%. Compared with the traditional inversion method, the Laplace-Fourier domain inversion method proposed in this embodiment can more effectively recover the low-frequency components and has a better effect on the final estimated fracture weakness parameters. The Laplace-Fourier domain inversion method proposed in this embodiment can reduce the dependence on the initial model while ensuring the accuracy of seismic inversion, such as Figure 7 and Figure 8 The ellipse in .

[0112] Example 2

[0113] In this embodiment, a HTI medium fracture weakness low-frequency compensation seismic inversion system is disclosed, comprising:

[0114] A data acquisition module, used for acquiring seismic data;

[0115] A fracture weakness parameter acquisition module is used to obtain fracture weakness parameters according to seismic data and a fracture weakness parameter estimation model;

[0116] Among them, the process of obtaining the fracture weakness parameter estimation model is as follows: establish the forward initial model of the Laplace-Fourier domain; add the reflection coefficient equation of the PP wave in the HTI medium to the forward initial model to obtain the forward model of the Laplace-Fourier domain; analyze the forward model of the Laplace-Fourier domain through the Bayesian theory to obtain the objective function that needs to be inverted; solve the objective function that needs to be inverted to obtain the fracture weakness parameter estimation model.

[0117] Example 3

[0118] In this embodiment, an electronic device is disclosed, including a memory and a processor, and computer instructions stored in the memory and running on the processor. When the computer instructions are executed by the processor, the steps described in the HTI medium fracture weakness low-frequency compensation seismic inversion method disclosed in Example 1 are completed.

[0119] Example 4

[0120] In this embodiment, a computer-readable storage medium is disclosed for storing computer instructions. When the computer instructions are executed by a processor, the steps of a low-frequency compensation seismic inversion method for HTI medium fracture weakness disclosed in Example 1 are completed.

[0121] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A low-frequency compensation seismic inversion method for fracture weakness in HTI medium, characterized in that: include: Acquisition of seismic data; According to the seismic data and the fracture weakness parameter estimation model, the fracture weakness parameters are obtained; The process of obtaining the fracture weakness parameter estimation model is as follows: establish the initial forward model of the Laplace-Fourier domain; add the reflection coefficient equation of the PP wave in the HTI medium to the initial forward model to obtain the forward model of the Laplace-Fourier domain; analyze the forward model of the Laplace-Fourier domain by Bayesian theory to obtain the objective function that needs to be inverted; solve the objective function that needs to be inverted to obtain the fracture weakness parameter estimation model; The fracture weakness parameter estimation model is: in, , are the normal crack weakness parameter and the tangential crack weakness parameter respectively, L represents the integral matrix, , are the differences between the normal crack weakness parameter and the tangential crack weakness parameter; The reflection coefficient equation of PP wave in HTI medium is: in, represents the reflection coefficient at different incident angles and azimuths, , and are the longitudinal wave modulus, transverse wave modulus and density, respectively. , are the differences between the normal crack weakness parameter and the tangential crack weakness parameter, in, , are the longitudinal and shear wave velocities, are the incident angle and azimuth, respectively.

2. A low-frequency compensation seismic inversion method for fracture weakness in HTI medium as claimed in claim 1, characterized in that: The process of establishing the initial forward model of the Laplace-Fourier domain is as follows: A convolution model is established; Laplace transform is performed on the convolution model to obtain the forward initial model in the Laplace-Fourier domain.

3. A low-frequency compensation seismic inversion method for fracture weakness in HTI medium as claimed in claim 1, characterized in that: The seismic data obtained include amplitude, longitudinal wave velocity, shear wave velocity, density, incident angle, and azimuth.

4. A low-frequency compensation seismic inversion method for fracture weakness in HTI medium as claimed in claim 1, characterized in that: The fracture weakness parameter estimation model includes the normal fracture weakness parameter estimation model and the tangential fracture weakness parameter estimation model.

5. The method for low-frequency compensation seismic inversion of HTI medium fracture weakness according to claim 1, characterized in that: The iterative reweighted least squares algorithm is used to solve the objective function that needs to be inverted and obtain the fracture weakness parameter model.

6. A HTI medium fracture weakness low-frequency compensation seismic inversion system, characterized in that: include: A data acquisition module, used for acquiring seismic data; A fracture weakness parameter acquisition module is used to obtain fracture weakness parameters according to seismic data and a fracture weakness parameter estimation model; The process of obtaining the fracture weakness parameter estimation model is as follows: establish the initial forward model of the Laplace-Fourier domain; add the reflection coefficient equation of the PP wave in the HTI medium to the initial forward model to obtain the forward model of the Laplace-Fourier domain; analyze the forward model of the Laplace-Fourier domain by Bayesian theory to obtain the objective function that needs to be inverted; solve the objective function that needs to be inverted to obtain the fracture weakness parameter estimation model; The fracture weakness parameter estimation model is: in, , are the normal crack weakness parameter and the tangential crack weakness parameter respectively, L represents the integral matrix, , are the differences between the normal crack weakness parameter and the tangential crack weakness parameter; The reflection coefficient equation of PP wave in HTI medium is: in, represents the reflection coefficient at different incident angles and azimuths, , and are the longitudinal wave modulus, transverse wave modulus and density, respectively. , are the differences between the normal crack weakness parameter and the tangential crack weakness parameter, in, , are the longitudinal and shear wave velocities, are the incident angle and azimuth, respectively.

7. An electronic device, characterized in that: The method comprises a memory and a processor and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, the steps of a low-frequency compensation seismic inversion method for fracture weakness of HTI medium as claimed in any one of claims 1 to 5 are completed.

8. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of a HTI medium fracture weakness low-frequency compensation seismic inversion method as described in any one of claims 1 to 5.

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