Fracture sensitive parameter prediction method and device based on anisotropic gradient modeling

Abstract

The invention relates to a crack sensitive parameter prediction method and device based on anisotropic gradient modeling, and the method comprises the following steps: S1, obtaining the normal crack weakness and tangential crack weakness of a characterization crack based on a linear sliding model; s2, establishing an initial model of the fracture weakness by constructing a relationship between the fracture anisotropy gradient and the fracture weakness; s3, obtaining an azimuth difference longitudinal wave reflection coefficient equation based on the PP wave linear approximate reflection coefficient; and S4, estimating the tangential crack weakness according to the seismic azimuth amplitude difference, and constraining the data of the tangential crack weakness by using the initial model of the crack weakness. According to the technical scheme, the relationship between the fracture anisotropy gradient and the fracture weakness is constructed, the initial model of the fracture weakness is established, the model is reasonable and reliable, and the data of the tangential fracture weakness can be constrained and inverted, so that the seismic inversion precision of the fracture weakness is improved, and the seismic inversion accuracy of the fracture weakness is improved. The method can be used for reliable prediction of the carbonate reservoir fracture development area.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration, and in particular to a method and device for predicting fracture sensitivity parameters based on anisotropic gradient modeling. Background Art

[0002] At present, the initial model of fracture weakness in carbonate reservoirs is mainly established by establishing anisotropic rock physics equivalent models, that is, using logging interpretation results (mineral composition and content, porosity, fracture density, fluid type and saturation, etc.), and gradually calculating the mineral modulus of rocks, dry rock bulk modulus, dry rock bulk modulus containing dry cracks, and fluid-saturated fracture-type rock stiffness coefficient through various rock physics equivalent models, and then calculating fracture weakness. However, this method is suitable for the establishment of the initial model of fracture weakness at the wellbore position, and can be used to constrain the inversion of well bypass seismic data. However, when inverting fracture weakness in work areas without wells or where logging data is missing, the fracture weakness estimation based on the rock physics equivalent model cannot meet the requirements of the initial fracture weakness model required for the inversion of the entire work area.

[0003] In addition, the current seismic inversion of fracture weakness in oil and gas reservoirs is mainly based on the amplitude change of azimuthal seismic data (i.e., AVAZ characteristics) to carry out fracture weakness inversion, and the inversion strategy used is generally AVAZ direct inversion. Different from the pre-stack three-parameter inversion (P- and S-wave velocities and density) under the assumption of conventional isotropic media, AVAZ direct inversion requires the estimation of three anisotropic parameters or two fracture weakness parameters in addition to the three parameters. The solution of too many parameters and the correlation between the parameters will cause great uncertainty in the inversion method, resulting in low inversion accuracy.

[0004] Therefore, based on the azimuth difference of seismic wave reflection coefficient, the influence of the three parameters is removed, and only the influence of the fracture weakness parameter is retained. At this time, the required input data is the difference in seismic wave reflection amplitude at different azimuths. However, since the fracture weakness parameter mainly affects the seismic wave reflection amplitude at far offset and the influence of random noise, the signal-to-noise ratio of the input data itself is significantly reduced. In actual data processing, the effect of directly carrying out fracture weakness inversion using the azimuth difference of seismic wave reflection amplitude is not ideal. Summary of the invention

[0005] The purpose of the present invention is to propose a method and device for predicting fracture sensitivity parameters based on anisotropic gradient modeling, aiming to solve the technical problems that the prior art lacks a reasonable and reliable initial model of fracture weakness and the seismic inversion accuracy of oil and gas reservoir fracture weakness is not high.

[0006] To achieve the above object, the present invention proposes a method for predicting crack sensitivity parameters based on anisotropic gradient modeling, comprising the following steps:

[0007] S1: Based on the linear sliding model, the normal crack weakness and tangential crack weakness that characterize the crack are obtained;

[0008] S2: Establish an initial model of fracture weakness by constructing the relationship between fracture anisotropy gradient and fracture weakness;

[0009] S3: Based on the linear approximation reflection coefficient of PP wave, the azimuth difference longitudinal wave reflection coefficient equation for different incident angles and azimuths is obtained;

[0010] S4: Estimate the tangential fracture weakness based on the difference in seismic azimuth amplitude, and use the initial model of fracture weakness to constrain the data of tangential fracture weakness.

[0011] Furthermore, the step S2 comprises:

[0012] According to the incident angle and azimuth of the crack, the anisotropic gradient of the crack is obtained;

[0013] The anisotropic gradient is combined with the conversion relationship between normal fracture weakness and tangential fracture weakness to estimate the tangential fracture weakness.

[0014] The estimated tangential fracture weakness is subjected to Gaussian filtering to extract its low-frequency components and obtain the initial model of fracture weakness.

[0015] Furthermore, using the reflection coefficient R of the medium with vertical fractures PP According to the incident angle and azimuth of the crack, the anisotropic gradient of the crack is obtained.

[0016] Furthermore, the reflection coefficient R of the medium with vertical cracks is PP The expression is:

[0017] R PP (θ,φ)=P+(G iso +G ani cos 2 φ)sin 2 θ,

[0018] Where P is the AVO intercept, G iso is the AVO isotropic gradient, G ani is the AVO anisotropy gradient, θ and φ are the incident angle and azimuth of the crack, respectively.

[0019] Furthermore, according to the reflection coefficient R of the vertical fracture development medium PP The expression for the reflection coefficient R is given by an incident angle θ1 and two azimuth angles φ1 and φ2. PP You can get:

[0020]

[0021] The anisotropy gradient can be obtained:

[0022]

[0023] Furthermore, according to the rock physics equivalent model of fractured reservoirs, the normal weakness Δ related to the fracture density e is obtained: N and tangential weakness Δ T Expressions and the conversion relationship between them;

[0024] The anisotropic gradient is combined with the conversion relationship between the normal fracture weakness and the tangential fracture weakness to estimate the tangential fracture weakness; where the normal weakness Δ N and tangential weakness Δ T The expression is:

[0025]

[0026]

[0027] Among them, g is the ratio of the shear modulus to the longitudinal wave modulus of the isotropic background, and the conversion relationship between the normal crack weakness and the tangential crack weakness is:

[0028]

[0029] The expression for estimating the tangential fracture weakness is:

[0030]

[0031] Furthermore, the step S3 comprises:

[0032] Based on the PP wave linear approximation reflection coefficient, it is transformed into a form characterized by the azimuthal difference of the reflection coefficient and the tangential fracture weakness to obtain the azimuthal reflection coefficient difference.

[0033] Furthermore, the step S4 comprises:

[0034] Based on the azimuthal reflection coefficient differences and the convolution model, synthetic azimuthal seismic data differences are obtained;

[0035] Substitute the azimuth seismic data differences into seismic amplitude difference values ​​and transform them into a matrix form;

[0036] The damped least square method with model constraints is used to constrain the data of tangential fracture weakness through continuous iteration, and the final tangential weakness estimation value is obtained.

[0037] The present invention also proposes a device for predicting crack sensitivity parameters based on anisotropic gradient modeling, comprising:

[0038] A memory, a processor, and a crack sensitivity parameter prediction program stored in the memory and executable on the processor, wherein the crack sensitivity parameter prediction program is executed by the processor to perform the steps of the above-mentioned crack sensitivity parameter prediction method.

[0039] The present invention also proposes a computer-readable storage medium, on which a crack sensitivity parameter prediction program is stored. When the crack sensitivity parameter prediction program is executed by a processor, the steps of the above-mentioned crack sensitivity parameter prediction method are implemented.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] This technical solution establishes an initial model of fracture weakness by constructing the relationship between fracture anisotropy gradient and fracture weakness. This model is not only reasonable and reliable, but can also be used to constrain and invert the data of tangential fracture weakness, thereby improving the accuracy of seismic inversion of fracture weakness and serving the reliable prediction of fracture development areas in carbonate reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0043] Figure 1 A technical flow chart of the fracture weakness azimuth seismic difference inversion method based on AVO anisotropic gradient provided by the present invention;

[0044] Figure 2 The azimuth difference of actual seismic data in a carbonate rock work area;

[0045] Figure 3 An initial model diagram of fracture weakness established for the work area;

[0046] Figure 4 This is the crack weakness result diagram obtained by inversion in the work area. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in 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 embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0049] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features limited to "first" and "second" may explicitly or implicitly include at least one of the features. In addition, if "and / or" or "and / or" appears in the full text, its meaning includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, solution B, or solutions that satisfy both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0050] AVO (Amplitude variation with offset) technology is used to study the variation of seismic reflection amplitude with the distance between the shot point and the receiver, that is, the offset (or incident angle), to explore the variation of reflection coefficient response with the offset (or incident angle), and then determine the lithology and physical parameters of the media above and below the reflection interface. With the help of AVO analysis, the rock properties of oil and gas reservoirs can be better evaluated, including porosity, density, lithology and fluid content.

[0051] There are two major problems in the prior art:

[0052] First, in the current carbonate reservoir fracture prediction, for work areas without wells or missing logging data, the fracture weakness estimation based on the rock physics equivalent model cannot meet the requirements of the fracture weakness initial model required for the inversion of the entire work area;

[0053] Second, in addition to estimating three parameters, AVAZ direct inversion also requires estimating three anisotropy parameters or two fracture weakness parameters. The solution of too many parameters and the correlation between the parameters will cause great uncertainty in the inversion method. Due to these two major problems, it is not conducive to the prediction and interpretation of fracture weakness parameters in carbonate reservoirs.

[0054] In order to solve the above technical problems, the present technical solution provides a method for predicting crack sensitivity parameters based on anisotropic gradient modeling.

[0055] Figure 1 The technical flow chart of the fracture weakness azimuthal seismic difference inversion method based on AVO anisotropic gradient provided for the implementation of the present invention is shown, and the method comprises the following steps:

[0056] Step S1: Dry crack weakness correlation based on linear sliding model

[0057] First, according to the current research on the influence of cracks on rock properties, there are currently two main rock physics models of crack induction: the coin-shaped crack model proposed by Hudson (1980) and the linear sliding model proposed by Schoenberg (1980). Secondly, starting from the Schoenberg linear sliding model, the sensitive parameters for predicting the influence of cracks using seismic data are derived, namely two fracture weakness parameters: normal fracture weakness Δ N and the tangential crack weakness Δ T Finally, in the case of dry fractures in the reservoir, there is a strong correlation between the normal and tangential weaknesses. By using the mutual relationship between the fracture weaknesses, the mutual conversion of the two groups of fracture weaknesses can be achieved.

[0058] Specifically, according to the rock physics equivalent model applicable to fractured reservoirs, it is known that the normal Δ related to the dry fracture characteristics (fracture density e) N and tangential weakness Δ T The expression is:

[0059]

[0060]

[0061] Among them, g is the ratio of the shear modulus to the longitudinal modulus of the isotropic background. It can be seen that there is a strong correlation between the normal and tangential crack weaknesses, namely:

[0062]

[0063] Therefore, by using the mutual relationship between the fracture weaknesses, the mutual conversion between the two groups of fracture weaknesses can be achieved.

[0064] Step S2: Construction of initial fracture weakness model

[0065] Firstly, the approximate equation of PP wave reflection coefficient in HTI medium proposed by Ruger (1997) is rewritten into the form of AVO intercept and AVO gradient (isotropic gradient and anisotropic gradient).

[0066] Secondly, the pre-stack angle gathers at different azimuths in the actual fractured carbonate rock work area are processed to calculate the azimuth seismic amplitude difference, such as Figure 2As shown. The AVO gradient attributes in different directions are extracted to obtain the fracture azimuth, and then the anisotropic gradient attributes are extracted. Finally, according to the relationship between the anisotropic gradient and the tangential fracture weakness, the initial fracture weakness model is constructed, as shown in Figure 3 As shown, the purpose of constraining subsequent inversion and improving stability is achieved.

[0067] Specifically, the reflection coefficient R of the medium with vertical fractures is known to be PP It can be expressed as:

[0068] R PP (θ,φ)=P+(G iso +G ani cos 2 φ)sin 2 θ, (4)

[0069] Where P is the AVO intercept, G iso is the AVO isotropic gradient, G ani is the AVO anisotropic gradient, θ and φ are the incident angle and azimuth respectively. According to formula (4), it can be seen that the reflection coefficient R given an incident angle θ1 and two azimuth angles φ1 and φ2 is PP You can get:

[0070]

[0071] Therefore, the anisotropy gradient can be obtained:

[0072]

[0073] The approximate relationship between anisotropy gradient and fracture weakness is:

[0074] G ani =-g(1-2g)Δ N +gΔ T . (7)

[0075] Combining the correlation between normal and tangential weakness (Formula 3), the tangential fracture weakness can be preliminarily estimated as:

[0076]

[0077] The initially estimated tangential weakness is subjected to Gaussian filtering to extract its low-frequency components, which can be used as the initial model for subsequent inversion.

[0078] Step S3: Azimuth difference of PP wave reflection coefficient in HTI medium

[0079] In order to solve the problem that the extended Zoeppritz equation is too complicated and cumbersome to be suitable for practical application in anisotropic media, based on the linear approximate reflection coefficient of PP waves in HTI media derived by Chen (2017), it is rewritten in a form characterized by the azimuthal difference of the reflection coefficient and the tangential crack weakness, and a forward operator is constructed to extend the equation to N layers of media, and the azimuthal difference longitudinal wave reflection coefficient equation under different incident angles and azimuth angles is obtained.

[0080] Specifically, according to the existing reflection coefficient approximate formula applicable to reservoirs with vertical fractures, the azimuthal reflection coefficient difference can be written as:

[0081] R PP_ani (θ1,φ2,φ1)=exp[a(θ,φ2,φ1)δΔ T ], (9)

[0082] in,

[0083]

[0084] Assuming there are N incident angles and M azimuth angles, the azimuth difference of the reflection coefficient can be written as follows:

[0085]

[0086] Step S4: Fracture weakness inversion method based on Bayesian framework

[0087] Firstly, the azimuth seismic difference method based on the Bayesian framework is used to obtain the fracture weakness parameters. Among them, the likelihood function and the prior probability distribution use Gaussian distribution and Cauchy distribution respectively. In addition, the constraints of the estimated initial fracture weakness model are used to enhance stability. According to the Bayesian theory, the likelihood function, prior probability distribution and posterior probability distribution corresponding to the azimuth seismic amplitude difference data and the parameters to be solved are given. The iterative reweighted least squares method is used to solve the objective function to obtain the final tangential fracture weakness inversion result, as shown in Figure 1. Figure 4 shown.

[0088] Specifically, using the convolution model, the synthetic azimuthal seismic data differences are obtained:

[0089]

[0090] Where W represents the wavelet matrix.

[0091] Assuming there are two seismic amplitude difference values ​​at two incident angles θ1 and θ2, they can be represented in matrix form:

[0092] d=Gm, (13)

[0093] Where d represents the vector of azimuthal seismic amplitude differences; G is the forward operator matrix, which consists of the difference coefficients of the wavelet and PP wave reflection coefficients; m is the parameter to be inverted, i.e., the tangential fracture weakness Δ T .

[0094] In order to obtain the inversion result of the unknown parameter variable m, the present invention adopts the damped least squares method with model constraints, and obtains the final normal weakness and tangential weakness estimation values ​​through continuous iteration:

[0095] m i+1 =m i +(G T G) -1 G T (d-Gm i ) (14)

[0096] Where i=1:N, N is the number of iterations, and m1 is the initial fracture weakness model based on the AVO anisotropic gradient.

[0097] In addition, the present invention also proposes a crack sensitivity parameter prediction device based on anisotropic gradient modeling. The prediction device includes: a memory, a processor, and a crack sensitivity parameter prediction program stored in the memory and executable on the processor, and when the crack sensitivity parameter prediction program is executed by the processor, the steps of the crack sensitivity parameter prediction method in the above embodiment are implemented.

[0098] In addition, the present invention also proposes a computer-readable storage medium. The computer-readable storage medium of the present invention stores a crack sensitivity parameter prediction program, and when the crack sensitivity parameter prediction program is executed by a processor, the steps of the method for predicting crack sensitivity parameters described above are implemented. The method implemented when the crack sensitivity parameter prediction program running on the processor is executed can refer to the various embodiments of the method for predicting crack sensitivity parameters of the present invention, and will not be described in detail here.

[0099] Through the present invention, not only a reasonable and reliable initial model of carbonate reservoir fracture weakness parameters can be obtained, but also the established initial model constraints are used for subsequent inversion, which improves the accuracy of inversion and can serve for reliable prediction of carbonate reservoir fracture development areas.

[0100] The above descriptions are only optional embodiments of the present invention, and are not intended to limit the patent scope of the present invention. All equivalent structural changes made using the contents of the present invention's specification and drawings, or directly / indirectly applied in other related technical fields, are included in the patent protection scope of the present invention.

Claims

1. A method for predicting crack sensitivity parameters based on anisotropic gradient modeling, characterized in that: The steps include: S1: Based on the linear sliding model, the normal crack weakness and tangential crack weakness that characterize the crack are obtained; S2: Establish an initial model of fracture weakness by constructing the relationship between fracture anisotropy gradient and fracture weakness; S3: Based on the linear approximation reflection coefficient of PP wave, the azimuth difference longitudinal wave reflection coefficient equation for different incident angles and azimuths is obtained; S4: Estimate the tangential fracture weakness based on the difference in seismic azimuth amplitude, and use the initial model of fracture weakness to constrain the data of tangential fracture weakness.

2. The method for predicting crack sensitivity parameters based on anisotropic gradient modeling according to claim 1, characterized in that: The step S2 comprises: According to the incident angle and azimuth of the crack, the anisotropic gradient of the crack is obtained; The anisotropy gradient is combined with the conversion relationship between normal fracture weakness and tangential fracture weakness to estimate the tangential fracture weakness. The estimated tangential fracture weakness is subjected to Gaussian filtering to extract its low-frequency components and obtain the initial model of fracture weakness.

3. The method for predicting crack sensitivity parameters based on anisotropic gradient modeling according to claim 2, characterized in that: Using the reflection coefficient R of the medium with vertical fractures PP According to the incident angle and azimuth of the crack, the anisotropic gradient of the crack is obtained.

4. The method for predicting crack sensitivity parameters based on anisotropic gradient modeling according to claim 2, characterized in that: The reflection coefficient R of the medium with vertical cracks is PP The expression is: R PP (θ,φ)=P+(G iso +G ani cos 2 f)sin 2 I, Where P is the AVO intercept, G iso is the AVO isotropic gradient, G ani is the AVO anisotropy gradient, θ and φ are the incident angle and azimuth of the crack, respectively.

5. The method for predicting crack sensitivity parameters based on anisotropic gradient modeling according to claim 4 is characterized in that: According to the reflection coefficient R of the vertical crack development medium PP The expression for the reflection coefficient R is given by an incident angle θ1 and two azimuth angles φ1 and φ2. PP You can get: The anisotropy gradient can be obtained:

6. The method for predicting crack sensitivity parameters based on anisotropic gradient modeling according to claim 5, characterized in that: According to the rock physics equivalent model of fractured reservoirs, the normal weakness Δ related to the fracture density e is obtained: N and tangential weakness Δ T Expressions and the conversion relationship between them; The anisotropic gradient is combined with the conversion relationship between the normal fracture weakness and the tangential fracture weakness to estimate the tangential fracture weakness; where the normal weakness Δ N and tangential weakness Δ T The expression is: Among them, g is the ratio of the shear modulus to the longitudinal wave modulus of the isotropic background, and the conversion relationship between the normal crack weakness and the tangential crack weakness is: The expression for estimating the tangential fracture weakness is:

7. The method for predicting crack sensitivity parameters based on anisotropic gradient modeling according to claim 1, characterized in that: The step S3 comprises: Based on the PP wave linear approximation reflection coefficient, it is transformed into a form characterized by the azimuthal difference of the reflection coefficient and the tangential fracture weakness to obtain the azimuthal reflection coefficient difference.

8. The method for predicting crack sensitivity parameters based on anisotropic gradient modeling according to claim 7, characterized in that: The step S4 comprises: Based on the azimuthal reflection coefficient differences and the convolution model, synthetic azimuthal seismic data differences are obtained; Substitute the azimuth seismic data differences into seismic amplitude difference values ​​and transform them into a matrix form; The damped least square method with model constraints is used to constrain the data of tangential fracture weakness through continuous iteration, and the final tangential weakness estimation value is obtained.

9. A crack sensitivity parameter prediction device based on anisotropic gradient modeling, characterized in that: The prediction device includes: a memory, a processor, and a crack sensitivity parameter prediction program stored in the memory and executable on the processor. When the crack sensitivity parameter prediction program is executed by the processor, the steps of the crack sensitivity parameter prediction method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a crack sensitivity parameter prediction program, and when the crack sensitivity parameter prediction program is executed by a processor, the steps of the crack sensitivity parameter prediction method according to any one of claims 1 to 8 are implemented.

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