A method for mining low-frequency information of anisotropic parameters of an HTI medium

Abstract

The application provides a low-frequency information mining method for anisotropy parameters of an HTI medium, and the mining method comprises the following steps: inputting azimuth time-domain seismic data and azimuth wavelet data of multiple angles; selecting a frequency band range omega and an attenuation factor sigma range; solving elastic impedance of a corresponding angle by using a least square method for seismic data of each angle to obtain low-frequency elastic impedance; and calculating an initial model of anisotropy parameters by using a strategy of azimuth elastic impedance difference. The low-frequency part of the seismic data is fully utilized, the low-frequency information of the anisotropy parameters can be mined to a greater extent, and a more accurate initial model is provided for anisotropy parameter inversion work.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and development, and in particular to a method for mining low-frequency information of anisotropic parameters of HTI media. Background Technology

[0002] Wide-azimuth seismic data contains abundant low-frequency, high-frequency, and wide-azimuth information, giving it high resolution and promising application prospects. However, the precise interpretation methods for wide-azimuth seismic data remain largely limited to the extension and application of conventional methods, with anisotropic parameter inversion exhibiting significant dependence on the initial anisotropic parameter model. Therefore, exploring the low-frequency responses inherent in seismic data and reducing the dependence of conventional anisotropic seismic inversion methods on the initial anisotropic parameter model is of great significance.

[0003] Existing methods for obtaining initial models of anisotropic parameters mainly involve using interpolation to extend the parameters of known wells into a three-dimensional data volume and then taking the low-frequency part as the initial model. The drawback is that the established initial model depends on the well and fails to make full use of the low-frequency information of the seismic data.

[0004] The drawback of the existing technology is that when establishing the initial model of anisotropic parameters, the anisotropic parameters are set to be related only to the anisotropic parameters and spatial location of the well. That is, the initial model of anisotropic parameters depends only on the anisotropic parameters and spatial location of the well, and does not utilize the rich low-frequency information in broadband seismic data. This makes the initial model of anisotropic parameters inconsistent with the actual situation, thereby affecting the reliability of pre-stack inversion of anisotropic parameters. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method for mining low-frequency information of anisotropic parameters of HTI media that overcomes or at least partially solves the above problems.

[0006] According to one aspect of the present invention, a method for mining low-frequency information of anisotropic parameters of HTI media is provided, the mining method comprising:

[0007] Input azimuth time-domain seismic data and azimuth wavelet data from multiple angles;

[0008] Select the frequency band range ω and the attenuation factor σ range;

[0009] The seismic data at each angle are used to solve the elastic impedance inversion objective function using the least squares method to obtain the elastic impedance at the corresponding angle, thus obtaining the low-frequency elastic impedance.

[0010] For low-frequency elastic impedance, an initial model of anisotropic parameters is calculated using a strategy of differentiating elastic impedances in different orientations.

[0011] Optionally, the plurality of angles are 30° azimuth angle and 4.5° incident angle, 30° azimuth angle and 13.5° incident angle, 30° azimuth angle and 22.5° incident angle, 150° azimuth angle and 4.5° incident angle, 150° azimuth angle and 13.5° incident angle, and 150° azimuth angle and 22.5° incident angle.

[0012] Optionally, the selected frequency band range ω and attenuation factor σ range include m attenuation factors and n frequencies, and the number of effective sampling points for each time-domain seismic data is N.

[0013] Optionally, the selected frequency band range ω can be selected from 0-10Hz as needed.

[0014] Optionally, the attenuation factor needs to be selected according to certain principles, specifically including:

[0015] Calculate seismic data in the transform domain;

[0016]

[0017]

[0018]

[0019] in, Let the incident angle be θ and the azimuth angle be... The time-domain seismic data e is the natural logarithm, Δt is the sampling interval, N is the sampling point, upright j represents the imaginary part, and italic i is the index of the selected frequency, and italic j is the index of the selected attenuation factor.

[0020] In the transform domain, seismic data represents the proportion of seismic data at a specific frequency and attenuation factor.

[0021] Plot the weight of different frequency components as a function of the attenuation factor, analyze the effect of the attenuation factor on the recovery of low-frequency components, and guide the selection of the attenuation factor.

[0022] Optionally, the seismic data at each angle are used to solve the elastic impedance inversion objective function using the least squares method to obtain the elastic impedance at the corresponding angle. Specifically, the low-frequency elastic impedance is obtained by: [expression omitted].

[0023] Where EI is the low-frequency elastic impedance, E is the unit vector, and m0 is the initial value of the elastic impedance. Let the angle of incidence be θ and the azimuth be... Transform domain seismic data, w s This indicates the proportion of seismic data in the inversion process. This indicates the proportion of the initial value in the inversion process;

[0024] G is the forward operator, and its expression is:

[0025] In equation (3), D is the difference matrix, which has the following form:

[0026]

[0027]

[0028]

[0029] In equation (5), Δt is the sampling interval, and N max σ represents the location of the point with the largest value in the wavelet data. j σ j+m-1 Let there be m attenuation factors, ω i ω i+n-1 There are n angular frequencies;

[0030] Wavelet matrix in the complex frequency domain

[0031]

[0032]

[0033]

[0034] In equation (6), Let the incident angle be θ and the azimuth angle be... Wavelet data.

[0035] Optionally, the sampling interval Δt is set to 2 ms.

[0036] Optionally, the initial value of the elastic impedance m0 is selected as a fixed value according to the actual working area conditions.

[0037] Optionally, the low-frequency elastic impedance, using a strategy of differentiating azimuth elastic impedances to calculate the initial model of anisotropic parameters, specifically includes:

[0038] The calculation formula is as follows:

[0039]

[0040]

[0041] In equation (8),

[0042]

[0043]

[0044]

[0045]

[0046] In equation (7), ε (V) δ (V) γ (V) Here, EI0 represents the anisotropic parameter in the HTI medium, and EI0 is the mean elastic impedance.

[0047] λ controls the weight of regularization, and E is the identity matrix;

[0048] The three HTI anisotropy parameters ε at the corresponding sampling point can be obtained by using the elastic impedance difference at the k-th sampling point. (V) δ (V) γ (V) ; r is the square of the ratio of transverse to longitudinal wave velocities;

[0049] Calculate the corresponding anisotropic parameter low-frequency model from the inverted low-frequency elastic impedance data.

[0050] Optionally, r is the square of the ratio of transverse to longitudinal wave velocities, which is selected according to the specific conditions of the work area, and r = 0.4286.

[0051] This invention provides a method for mining low-frequency information of anisotropic parameters in HTI media. The method includes: inputting azimuth time-domain seismic data and azimuth wavelet data from multiple angles; selecting the frequency band range ω and the attenuation factor σ range; using the least squares method to solve the elastic impedance inversion objective function for each angle to obtain the corresponding elastic impedance, thus obtaining the low-frequency elastic impedance; and using the low-frequency elastic impedance, calculating the initial model of anisotropic parameters using a strategy based on the difference in azimuth elastic impedance. This method fully utilizes the low-frequency portion of the seismic data, enabling greater mining of low-frequency information of anisotropic parameters and providing a more accurate initial model for anisotropic parameter inversion.

[0052] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1A flowchart of a method for mining low-frequency information of anisotropic parameters of HTI media provided in an embodiment of the present invention;

[0055] Figure 2 This is a schematic diagram illustrating the variation of low-frequency components with attenuation factor provided in an embodiment of the present invention;

[0056] Figure 3 A schematic diagram of the low-frequency elastic impedance inversion results from six angles provided in an embodiment of the present invention;

[0057] Figure 4 This is an initial model of anisotropic parameters provided in the embodiments of the present invention. Detailed Implementation

[0058] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0059] The terms "comprising" and "having," and any variations thereof, in the specification, embodiments, claims, and drawings of this invention are intended to cover non-exclusive inclusion, such as including a series of steps or units.

[0060] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0061] like Figure 1 As shown, the first step is to input azimuth time-domain seismic data and azimuth wavelet data for six angles. The six angles selected in this invention are azimuth angle 30° incident angle 4.5°, azimuth angle 30° incident angle 13.5°, azimuth angle 30° incident angle 22.5°, azimuth angle 150° incident angle 4.5°, azimuth angle 150° incident angle 13.5°, and azimuth angle 150° incident angle 22.5°.

[0062] Step 2: Select the frequency band range ω and the attenuation factor range σ (assuming that the selected range includes m attenuation factors and n frequencies, and assuming that the number of effective sampling points for each time-domain seismic data is N).

[0063] The frequency band can be selected from 0-10Hz as needed, and the attenuation factor should be selected according to the following principles:

[0064] First, calculate the seismic data in the transform domain.

[0065]

[0066]

[0067]

[0068] In equation (1), Let the incident angle be θ and the azimuth angle be... In the time-domain seismic data, e is the natural logarithm, Δt is the sampling interval, N is the number of sampling points, and upright j represents the imaginary part. Here, italic i represents the selected frequency index, and italic j represents the selected attenuation factor index. The seismic data in the transform domain represents the proportion of seismic data at a specific frequency and attenuation factor. By plotting the curves of the proportion of different frequency components versus the attenuation factor, the influence of the attenuation factor on the recovery of low-frequency components is analyzed, thereby guiding the selection of the attenuation factor.

[0069] from Figure 1 It can be seen that using an attenuation factor of σ = 3.8 in this invention helps in the recovery of low-frequency components of seismic data.

[0070] Step 3: For the seismic data at each angle, the least squares method is used to solve the elastic impedance inversion objective function to obtain the elastic impedance at the corresponding angle, thus realizing the mining of low-frequency information of elastic impedance. Its expression is:

[0071]

[0072] Where EI is the low-frequency elastic impedance, E is the unit vector, and m0 is the initial value of the elastic impedance, which is selected as a fixed value according to the actual working area conditions. Let the angle of incidence be θ and the azimuth be... Transform domain seismic data, w s This indicates the proportion of seismic data in the inversion process. This indicates the proportion of the initial value in the inversion process (its main function is regularization, which improves the stability of the inversion).

[0073] G is the forward operator, and its expression is:

[0074]

[0075] In equation (3), D is the difference matrix, which has the following form:

[0076]

[0077]

[0078]

[0079] In equation (5), Δt is the sampling interval, which is taken as 2ms here, and N max This represents the location of the point with the largest value in the wavelet data. σ j σj+m-1 Let there be m attenuation factors, ω i ω i+n-1 Let n be the angular frequencies and e be the natural logarithm.

[0080] Wavelet matrix in the complex frequency domain

[0081]

[0082]

[0083]

[0084] In equation (6), Let the incident angle be θ and the azimuth angle be... Wavelet data.

[0085] Step 4: Based on the azimuth low-frequency elastic impedances obtained in Step 3, calculate the initial model of anisotropic parameters using a strategy based on azimuth elastic impedance differences. The calculation formula is as follows:

[0086]

[0087]

[0088] In equation (8),

[0089]

[0090]

[0091]

[0092]

[0093] In equation (7), ε (V) δ (V) γ (V) Let ε be the anisotropic parameter in the HTI medium, and EI0 be the mean elastic impedance. λ controls the regularization weight to improve computational stability, and E is the identity matrix. This equation mainly expresses that the three HTI anisotropic parameters ε at the corresponding sampling point can be obtained by using the elastic impedance difference at the k-th sampling point. (V) δ (V) γ (V) r is the square of the transverse and longitudinal wave velocity ratio, which can be selected according to the specific conditions of the work area. In this case, r = 0.4286 is selected. Therefore, the corresponding anisotropic parameter low-frequency model can be calculated from the inverted low-frequency elastic impedance data based on this formula.

[0094] Figure 3 The low-frequency elastic impedance inversion profiles are shown from six angles.

[0095] (a) Low-frequency elastic impedance inversion results at an azimuth angle of 30° and an incident angle of 4.5°;

[0096] (b) Low-frequency elastic impedance inversion results at an azimuth angle of 30° and an incident angle of 13.5°;

[0097] (c) Low-frequency elastic impedance inversion results at an azimuth angle of 30° and an incident angle of 22.5°;

[0098] (d) Low-frequency elastic impedance inversion results with an azimuth angle of 150° and an incident angle of 4.5°;

[0099] (e) Low-frequency elastic impedance inversion results at an azimuth angle of 150° and an incident angle of 13.5°;

[0100] (f) Low-frequency elastic impedance inversion results with an azimuth angle of 150° and an incident angle of 22.5°.

[0101] Figure 4 To pass Figure 1 An initial model of anisotropic parameters calculated from six low-frequency elastic impedance data.

[0102] (a) Anisotropy parameter ε (V) Initial model;

[0103] (b) Anisotropy parameter δ (V) Initial model;

[0104] (c) Anisotropy parameter γ (V) Initial model.

[0105] This invention proposes a method for mining low-frequency information of anisotropic parameters in HTI media. Using this method, the initial model of anisotropic parameters can be estimated more accurately, and the dependence of anisotropic inversion on the initial model can be effectively reduced.

[0106] Beneficial effects: The low-frequency anisotropic parameter model determined by the method of this invention makes full use of the low-frequency part of the seismic data, and can extract the low-frequency information of the anisotropic parameters to a greater extent, providing a more accurate initial model for anisotropic parameter inversion work.

[0107] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for mining low-frequency information of anisotropic parameters in HTI media, characterized in that, The mining method includes: Input azimuth time-domain seismic data and azimuth wavelet data from multiple angles; Select the frequency band range ω and the attenuation factor σ range; The seismic data at each angle are used to solve the elastic impedance inversion objective function using the least squares method to obtain the elastic impedance at the corresponding angle, thus obtaining the low-frequency elastic impedance. For low-frequency elastic impedance, an initial model of anisotropic parameters is calculated using a strategy of differentiating elastic impedances in different orientations.

2. The method for mining low-frequency information of anisotropic parameters of HTI media according to claim 1, characterized in that, The various angles are 30° azimuth angle with an incident angle of 4.5°, 30° azimuth angle with an incident angle of 13.5°, 30° azimuth angle with an incident angle of 22.5°, 150° azimuth angle with an incident angle of 4.5°, 150° azimuth angle with an incident angle of 13.5°, and 150° azimuth angle with an incident angle of 22.5°.

3. The method for mining low-frequency information of anisotropic parameters of HTI media according to claim 1, characterized in that, The selected frequency band range ω and attenuation factor σ range include m attenuation factors and n frequencies, and the effective sampling number of each time-domain seismic data is N.

4. The method for mining low-frequency information of anisotropic parameters of HTI media according to claim 1, characterized in that, The selected frequency band range ω is chosen as needed, from 0 to 10 Hz.

5. The method for mining low-frequency information of anisotropic parameters of HTI media according to claim 1, characterized in that, The attenuation factor needs to be selected according to the following principles: Calculate seismic data in the transform domain; in, Let the incident angle be θ and the azimuth angle be... The time-domain seismic data is given by e, which is the natural logarithm, Δt is the sampling interval, N is the sampling point, and upright j represents the imaginary part. Here, italic i is the index of the selected frequency, and italic j is the index of the selected attenuation factor. In the transform domain, seismic data represents the proportion of seismic data at a specific frequency and attenuation factor. Plot the weight of different frequency components as a function of the attenuation factor, analyze the effect of the attenuation factor on the recovery of low-frequency components, and guide the selection of the attenuation factor.

6. The method for mining low-frequency information of anisotropic parameters of HTI media according to claim 1, characterized in that, The seismic data at each angle are used to solve the elastic impedance inversion objective function using the least squares method to obtain the elastic impedance at the corresponding angle. Specifically, obtaining the low-frequency elastic impedance includes: Its expression is: Where EI is the low-frequency elastic impedance, E is the unit vector, and m0 is the initial value of the elastic impedance. Let the angle of incidence be θ and the azimuth be... Transform domain seismic data, w s This indicates the proportion of seismic data in the inversion process. This indicates the proportion of the initial value in the inversion process; G is the forward operator, and its expression is: In equation (3), D is the difference matrix, which has the following form: In equation (5), Δt is the sampling interval, and N max σ represents the location of the point with the largest value in the wavelet data. j σ j+m-1 Let there be m attenuation factors, ω i ω i+n-1 There are n angular frequencies, and e is the natural logarithm; Wavelet matrix in the complex frequency domain In equation (6), Let the incident angle be θ and the azimuth angle be... Wavelet data.

7. The method for mining low-frequency information of anisotropic parameters of HTI media according to claim 6, characterized in that, The sampling interval Δt is 2ms.

8. The method for mining low-frequency information of anisotropic parameters of HTI media according to claim 6, characterized in that, The initial value of the elastic impedance m0 is selected as a fixed value based on the actual working area conditions.

9. The method for mining low-frequency information of anisotropic parameters of HTI media according to claim 1, characterized in that, The low-frequency elastic impedance, using a strategy of differentiating azimuth elastic impedances, calculates the initial model of anisotropic parameters, specifically including: The calculation formula is as follows: In equation (8), In equation (7), ε (V) δ (V) γ (V) Here, EI0 represents the anisotropic parameter in the HTI medium, and EI0 is the mean elastic impedance. λ controls the weight of regularization, and E is the identity matrix; The three HTI anisotropy parameters ε at the corresponding sampling point can be obtained by using the elastic impedance difference at the k-th sampling point. (V) δ (V) γ (V) ; r is the square of the ratio of transverse to longitudinal wave velocities; Calculate the corresponding anisotropic parameter low-frequency model from the inverted low-frequency elastic impedance data.

10. A method for mining low-frequency information of anisotropic parameters of HTI media according to claim 9, characterized in that, The value of r is the square of the ratio of transverse to longitudinal wave velocities, which is selected according to the specific conditions of the work area, and r = 0.4286.

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