HTI medium brittleness earthquake prediction stabilization method

Abstract

The invention provides an HTI medium brittleness earthquake prediction stabilization method. The stabilization method comprises the following steps: inputting azimuth time domain earthquake data of multiple angles, earthquake parameters and an initial model of three anisotropic parameters; an azimuth amplitude difference forward operator is constructed, an azimuth amplitude difference inversion objective function is established, and stable inversion of the three anisotropic parameters is realized; selecting seismic data of three incident angles in a certain direction, adopting an isotropic YPD equation to realize inversion of the seismic parameters, and calculating a brittleness indication factor of an isotropic hypothesis; and constructing display expressions among the brittleness indication factor of the isotropic hypothesis, the brittleness indication factor of the HTI hypothesis and the anisotropic parameters, and calculating the brittleness indication factor of the HTI medium. And the HTI medium brittleness indicator factor can be more stably predicted.

Description

Technical Field

[0001] The invention relates to the field of oil and gas exploration and development, and in particular to a method for predicting and stabilizing brittle earthquakes in HTI media. Background Art

[0002] The high-angle cracks developed in unconventional oil and gas reservoirs make them show weak azimuthal anisotropy in seismic data, which can generally be approximated as HTI media. The low natural production capacity requires fracturing of the reservoir for its development. Brittleness is one of the important indicators for evaluating the fracturability of reservoirs. In general, the ratio of Young's modulus to Poisson's ratio is often used as a brittleness indicator factor in seismic data. However, the current brittle seismic prediction for HTI media mainly remains in the extended application of conventional methods, and the stability of brittleness prediction is poor. Therefore, designing a more stable brittleness prediction method suitable for HTI media is of great significance for the evaluation of the fracturability of unconventional oil and gas reservoirs. This case proposes a stable method for brittle seismic prediction of HTI media to more reasonably estimate the brittleness indicator factor of HTI media.

[0003] The existing seismic prediction method for HTI medium brittleness is mainly based on the AVO inversion theory of HTI medium, using the anisotropic YPD equation to simultaneously invert six elastic and anisotropic parameters such as Young's modulus and Poisson's ratio, and finally calculating the brittleness indicator factor through the inversion results of Young's modulus and Poisson's ratio. Its disadvantages are that the six-parameter inversion has strong multi-solution and poor stability. When the signal-to-noise ratio of seismic data is low, the Young's modulus and Poisson's ratio obtained have large errors, which affects the prediction of brittleness. Different from this, this case constructs the display expression of the brittleness indicator factor based on the isotropic assumption and the brittleness indicator factor and anisotropic parameters of the HTI medium by comparing the similarity between the reflection coefficient equation of the HTI medium and the reflection coefficient equation of the isotropic medium. In this way, the three-parameter seismic inversion based on the isotropic YPD equation can be performed in a specific azimuth to obtain the Young's modulus and Poisson's ratio of the isotropic assumption, and then the three anisotropic parameters are obtained by inverting the azimuth amplitude difference, so as to achieve brittleness prediction.

[0004] The disadvantage of the existing technology is that when performing seismic inversion of HTI media, six parameters need to be inverted simultaneously, which will increase the condition number of the open-eye operator, increase the multiplicity of solutions of the inversion results, reduce the stability, and thus reduce the prediction accuracy of Young's modulus and Poisson's ratio, thereby affecting the reliability of brittleness prediction. Summary of the invention

[0005] In view of the above problems, the present invention is proposed to provide a HTI medium brittle earthquake prediction stability method that overcomes the above problems or at least partially solves the above problems.

[0006] According to one aspect of the present invention, a stabilization method for predicting brittle earthquakes in HTI media is provided, the stabilization method comprising:

[0007] Input azimuth time-domain seismic data at multiple angles, seismic parameters, and an initial model of three anisotropy parameters;

[0008] Construct the azimuth amplitude difference forward operator, establish the azimuth amplitude difference inversion objective function, and achieve stable inversion of three anisotropic parameters;

[0009] Selecting seismic data of three incident angles in a certain azimuth, using the isotropic YPD equation to implement the inversion of the seismic parameters, and calculating the brittleness indicator factor of the isotropic assumption;

[0010] The explicit expression between the brittleness indicator factor of the isotropic assumption and the brittleness indicator factor of the HTI assumption and the anisotropic parameters is constructed, and the brittleness indicator factor of the HTI medium is calculated.

[0011] Optionally, the seismic parameters specifically include: Young's modulus, Poisson's ratio, and density.

[0012] Optionally, the azimuth time domain seismic data of the multiple angles specifically include: azimuth 30° incident angle 4.5°, azimuth 30° incident angle 13.5°, azimuth 30° incident angle 22.5°, azimuth 150° incident angle 4.5°, azimuth 150° incident angle 13.5° and azimuth 150° incident angle 22.5°.

[0013] Optionally, the amplitude difference inversion objective function of the HTI medium is:

[0014] The objective function of HTI medium amplitude difference inversion is minJ = ||Gm-d||2+λ||m-m0||2(1)

[0015] Solving formula (1) gives the anisotropic parameter estimation result:

[0016]

[0017] λ is the model constraint weight, which is given according to the signal-to-noise ratio of seismic data. is the initial model of anisotropic parameters, m=(δ (V) ,ε (V) ,γ (V) ) T is the prediction result of anisotropic parameters, G is the azimuth amplitude difference forward operator, and d is the azimuth amplitude difference seismic data;

[0018]

[0019] θ i is the incident angle, is the azimuth, The incident angle is θ i , the azimuth is of earthquake data.

[0020] Optionally, the constructing of the azimuth amplitude difference forward operator specifically includes:

[0021] The azimuth amplitude difference forward operator is

[0022]

[0023] W is the wavelet matrix, I is the identity matrix, and D is the difference matrix

[0024]

[0025]

[0026]

[0027]

[0028] Where k is the square of the ratio of the transverse and longitudinal wave velocities.

[0029] Optionally, the seismic data of three incident angles in a certain azimuth are selected, and the isotropic YPD equation is used to implement the inversion of the seismic parameters, and specifically includes:

[0030] The isotropic YPD equation is as follows:

[0031]

[0032] The estimated result is

[0033]

[0034] In formula (6), d ISO is the seismic data of three incident angles in a certain azimuth, λ ISO are the model constraint weights for Young's modulus, Poisson's ratio, and density, is the initial model of Young's modulus, Poisson's ratio and density, G ISO is the forward operator, is the estimated result of Young's modulus assuming isotropy, is the Poisson's ratio estimation result under the isotropic assumption, ρ is the density estimation result under the isotropic assumption, and Δ is the difference, which represents the elastic parameters of the lower medium minus the elastic parameters of the upper medium.

[0035]

[0036]

[0037]

[0038]

[0039]

[0040] Where k is the square of the ratio of the transverse and longitudinal wave velocities.

[0041] Optionally, the calculation of the brittleness indicator factor of the isotropic assumption specifically includes:

[0042] The brittleness indicator factor for the isotropic assumption is

[0043] Optionally, the display expression between the brittleness indicator factor of the isotropic assumption and the brittleness indicator factor of the HTI assumption and the anisotropic parameter specifically includes:

[0044] Ignore the effect of anisotropy parameters at large angles and let the sin of the anisotropy parameter be 2 θtan 2 θ=0

[0045] YPD equation for HTI medium

[0046]

[0047] Further rearrangement of formula (10) yields

[0048]

[0049] in

[0050]

[0051]

[0052] Where k is the square of the ratio of the transverse and longitudinal wave velocities, E is the Young's modulus assumed by HTI, and σ is the Poisson's ratio assumed by HTI.

[0053] Optionally, the calculating of the brittleness indicator factor of the HTI medium specifically includes:

[0054]

[0055] Optionally, the initial model of the seismic parameters and the three anisotropic parameters further includes: wavelet data.

[0056] The present invention provides a stable method for predicting brittle earthquakes in HTI media, the stable method comprising: inputting azimuth time-domain seismic data of multiple angles, seismic parameters and initial models of three anisotropic parameters; constructing an azimuth amplitude difference forward operator, establishing an azimuth amplitude difference inversion objective function, and realizing stable inversion of three anisotropic parameters; selecting seismic data of three incident angles in a certain azimuth, using the isotropic YPD equation to realize the inversion of the seismic parameters, and calculating the brittle indicator factor of the isotropic assumption; constructing a display expression between the brittle indicator factor of the isotropic assumption and the brittle indicator factor and anisotropic parameters of the HTI assumption, and calculating the brittle indicator factor of the HTI media. A more stable prediction of the brittle indicator factor of the HTI media is achieved.

[0057] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0059] Figure 1 A flow chart of a method for predicting stability of brittle earthquakes in HTI media provided by an embodiment of the present invention;

[0060] Figure 2 A Young's modulus prediction result diagram of seismic data with an azimuth angle of 150° provided in an embodiment of the present invention;

[0061] Figure 3 A graph showing the Poisson's ratio prediction results for seismic data with an azimuth of 150° provided in an embodiment of the present invention;

[0062] Figure 4 The density prediction result of the seismic data with an azimuth angle of 150° provided in the embodiment of the present invention;

[0063] Figure 5 A brittleness indicator factor prediction result diagram of seismic data with an azimuth angle of 150° provided in an embodiment of the present invention;

[0064] Figure 6 This is a diagram of the prediction results of the HTI medium brittleness indicator factor provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0065] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0066] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0067] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0068] like Figure 1 As shown, the first step is to input the azimuth time-domain seismic data of six angles, Young's modulus, Poisson's ratio, density and three anisotropy parameters to obtain the initial model and wavelet data. The six angles selected this time are azimuth 30° incident angle 4.5°, azimuth 30° incident angle 13.5°, azimuth 30° incident angle 22.5°, azimuth 150° incident angle 4.5°, azimuth 150° incident angle 13.5° and azimuth 150° incident angle 22.5°.

[0069] Step 2: Construct the azimuth amplitude difference forward operator, establish the azimuth amplitude difference inversion objective function, and achieve stable inversion of the three anisotropic parameters.

[0070] The objective function of HTI medium amplitude difference inversion is:

[0071] minJ=||Gm-d||2+λ||m-m0||2 (1)

[0072] Solving (1) yields the anisotropic parameter estimation result:

[0073]

[0074] λ is the model constraint weight, which is given according to the signal-to-noise ratio of seismic data. is the initial model of anisotropic parameters, m=(δ (V) ,ε (V) ,γ (V) ) T is the prediction result of anisotropic parameters, G is the azimuth amplitude difference forward operator, and d is the azimuth amplitude difference seismic data

[0075]

[0076] θ i is the incident angle, is the azimuth, The incident angle is θ i , the azimuth is of earthquake data.

[0077] The azimuth amplitude difference forward operator is

[0078]

[0079] W is the wavelet matrix, I is the identity matrix, and D is the difference matrix

[0080]

[0081]

[0082]

[0083]

[0084] Where k is the square of the ratio of the transverse and longitudinal wave velocities.

[0085] Step 3: Select seismic data of three incident angles in a certain azimuth, use the isotropic YPD equation to realize the three-parameter inversion of Young's modulus, Poisson's ratio and density, and calculate the brittleness indicator factor of the isotropic assumption.

[0086] At this time, the isotropic YPD equation is as follows:

[0087]

[0088] The estimated result is

[0089]

[0090] In formula (6), d ISO is the seismic data of three incident angles in a certain azimuth, λ ISO are the model constraint weights for Young's modulus, Poisson's ratio, and density, is the initial model of Young's modulus, Poisson's ratio and density, G ISO is the forward operator, is the estimated result of Young's modulus assuming isotropy, is the Poisson's ratio estimation result assuming isotropy, is the density estimation result under the assumption of isotropy, and Δ is the difference, which represents the elastic parameters of the lower medium minus the elastic parameters of the upper medium.

[0091]

[0092]

[0093]

[0094]

[0095] Therefore, the brittleness indicator factor for the isotropic assumption is

[0096] Step 4: Construct a display expression between the brittleness indicator factor of the isotropic assumption and the brittleness indicator factor of the HTI assumption and anisotropic parameters, and calculate the brittleness indicator factor of the HTI medium.

[0097] The YPD equation for HTI medium can be written as

[0098]

[0099] Here, the influence of the anisotropic parameter at large angles is ignored, and the sin of the anisotropic parameter is 2 θtan 2 θ=0

[0100] So it becomes

[0101]

[0102] Further rearrangement of formula (10) yields

[0103]

[0104] in

[0105]

[0106]

[0107] so

[0108]

[0109] In this way, the brittleness indicator factor of the HTI medium can be calculated. Where k is the square of the ratio of the transverse and longitudinal wave velocities.

[0110] Figure 2-Figure 4 are the anisotropy parameters δ (V) , ε (V) and γ (V) The inversion result of Figure 5 is the brittleness indicator factor under the isotropic assumption predicted based on three seismic data with an azimuth of 150° Figure 6 This is the HTI medium brittleness indicator factor BI predicted by the method in this case.

[0111] Beneficial effects: The purpose of the present invention is to establish explicit expressions of the brittle indicator factor of the isotropic assumption and the brittle indicator factor of the HTI assumption and anisotropic parameters by utilizing the similarity between the YPD equation under the HTI assumption and the YPD equation under the isotropic assumption, thereby converting the conventional six-parameter inversion into two three-parameter inversions to avoid the instability caused by the six-parameter inversion. In order to improve the stability of the brittle indicator factor of the HTI medium, the present invention adopts the strategy of azimuth amplitude difference inversion to predict the three anisotropic parameters; then based on the YPD equation, the three-angle seismic data at a certain azimuth are used to realize the pre-stack three-parameter inversion, and the Young's modulus and Poisson's ratio are calculated to calculate the brittle indicator factor of the isotropic assumption; finally, the brittle indicator factor of the isotropic assumption and the brittle indicator factor of the anisotropic assumption and anisotropic parameters are established to obtain the brittle indicator factor of the HTI medium. The method of this case can more stably predict the brittle indicator factor of the HTI medium.

[0112] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods 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 in the scope of protection of the present invention.

Claims

1. A method for predicting stability of brittle earthquakes in HTI media, characterized in that: The stabilization method comprises: Input azimuth time-domain seismic data at multiple angles, seismic parameters, and an initial model of three anisotropy parameters; Construct the azimuth amplitude difference forward operator, establish the azimuth amplitude difference inversion objective function, and achieve stable inversion of three anisotropic parameters; Selecting seismic data of three incident angles in a certain azimuth, using the isotropic YPD equation to implement the inversion of the seismic parameters, and calculating the brittleness indicator factor of the isotropic assumption; The explicit expression between the brittleness indicator factor of the isotropic assumption and the brittleness indicator factor of the HTI assumption and the anisotropic parameters is constructed, and the brittleness indicator factor of the HTI medium is calculated.

2. A method for predicting stability of brittle earthquakes in HTI media according to claim 1, characterized in that: The seismic parameters specifically include: Young's modulus, Poisson's ratio, and density.

3. A method for predicting stability of brittle earthquakes in HTI media according to claim 1, characterized in that: The azimuth time domain seismic data at multiple angles specifically include: azimuth 30° incident angle 4.5°, azimuth 30° incident angle 13.5°, azimuth 30° incident angle 22.5°, azimuth 150° incident angle 4.5°, azimuth 150° incident angle 13.5° and azimuth 150° incident angle 22.5°.

4. A method for predicting stability of brittle earthquakes in HTI media according to claim 1, characterized in that: The amplitude difference inversion objective function of the HTI medium is: The objective function of HTI medium amplitude difference inversion is minJ = ||Gm-d||2+λ||m-m0||2(1) Solving formula (1) gives the anisotropic parameter estimation result: λ is the model constraint weight, which is given according to the signal-to-noise ratio of seismic data. is the initial model of anisotropic parameters, m=(δ (V) ,ε (V) ,γ (V) ) T is the prediction result of anisotropic parameters, G is the azimuth amplitude difference forward operator, and d is the azimuth amplitude difference seismic data; θ i is the incident angle, is the azimuth, The incident angle is θ i , the azimuth is of earthquake data.

5. A method for predicting stability of brittle earthquakes in HTI media according to claim 4, characterized in that: The construction of the azimuth amplitude difference forward operator specifically includes: The azimuth amplitude difference forward operator is W is the wavelet matrix, I is the identity matrix, and D is the difference matrix 6. A method for predicting stability of brittle earthquakes in HTI media according to claim 1, characterized in that: The seismic data of three incident angles in a certain azimuth are selected, and the isotropic YPD equation is used to realize the inversion of the seismic parameters, and specifically includes: The isotropic YPD equation is as follows: The estimated result is In formula (6), d ISO is the seismic data of three incident angles in a certain azimuth, λ ISO are the model constraint weights for Young's modulus, Poisson's ratio, and density, is the initial model of Young's modulus, Poisson's ratio and density, G ISO is the forward operator, is the estimated result of Young's modulus assuming isotropy, is the Poisson's ratio estimation result assuming isotropy, is the density estimation result under the assumption of isotropy, and Δ is the difference, which represents the elastic parameters of the lower medium minus the elastic parameters of the upper medium. Where k is the square of the ratio of the transverse and longitudinal wave velocities.

7. A method for predicting stability of brittle earthquakes in HTI media according to claim 6, characterized in that: The brittleness indicator factor for calculating the isotropic assumption specifically includes: The brittleness indicator factor for the isotropic assumption is 8. The method for predicting stability of brittle earthquakes in HTI media according to claim 1, characterized in that: The display expression between the brittleness indicator factor of the isotropic assumption and the brittleness indicator factor of the HTI assumption and the anisotropic parameters specifically includes: Ignore the effect of anisotropy parameters at large angles and let the sin of the anisotropy parameter be 2 θtan 2 θ=0 YPD equation for HTI medium Further rearrangement of formula (10) yields in Where k is the square of the ratio of the transverse and longitudinal wave velocities, E is the Young's modulus assumed by HTI, and σ is the Poisson's ratio assumed by HTI.

9. A method for predicting stability of brittle earthquakes in HTI media according to claim 7, characterized in that: The calculation of the brittleness indicator factor of the HTI medium specifically includes:

10. The method for predicting stability of brittle earthquakes in HTI media according to claim 1, characterized in that: The initial model of the seismic parameters and the three anisotropic parameters also includes: wavelet data.

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