Crack quantitative prediction method and device based on pre-stack anisotropy inversion

Abstract

The invention relates to the field of oil-gas exploration and geophysical logging, and particularly discloses a fracture quantitative prediction method and device based on pre-stack anisotropic inversion, and the method comprises the steps: carrying out the pre-stack AVAZ inversion based on an optimized omnibearing OVT gather or angle domain ES360 gather, and obtaining an inversion result; and performing ellipse fitting on the inversion result to obtain the fracture development density and the fracture orientation. According to the crack quantitative prediction method based on pre-stack anisotropic inversion provided by the invention, pre-stack AVAZ direct inversion is carried out by utilizing an omnibearing OVT domain gather or an angle domain ES360 gather, the gather does not need to be subjected to azimuth superposition processing work, ellipse fitting is carried out on an inversion result, the crack development density and the crack azimuth are obtained, and the crack prediction precision is improved.

Description

Technical Field

[0001] The invention relates to the field of oil and gas exploration and geophysical logging, and in particular to a method and device for quantitatively predicting fractures based on prestack anisotropy inversion. Background Art

[0002] As an important place for oil and gas storage, fractures have become one of the key reservoir types in current exploration. Fractures are mainly developed in various reservoirs such as shale, carbonate rock, volcanic rock, etc. How to accurately predict the fracture development zone in the reservoir has become a hot topic and key issue in current research.

[0003] At present, the prediction methods for fractures can use core drilling, imaging logging and other methods to obtain more accurate fracture information in logging, but these methods are difficult to judge fracture information outside the wellhead. The post-stack attribute method in seismic exploration can identify fault-related fractures and characterize the distribution characteristics of the fault plane, thereby qualitatively predicting the development of fractures. However, since this method is mainly based on full stack data, it ignores the azimuthal anisotropy caused by fracture development.

[0004] In order to fully obtain the azimuth information in seismic data and quantitatively characterize the intensity and direction of fracture development, the fracture prediction method has gradually moved from post-stack to pre-stack. The pre-stack fracture prediction method is mainly realized by using the azimuthal anisotropy of longitudinal waves. The commonly used ellipse fitting method is mainly to fit the anisotropic ellipse to the selected sensitive azimuth seismic attributes, and use the fitted flattening and major (minor) axis to indicate the density and direction of fracture development. The calculation process of this method is mainly based on the azimuth stacking data volume, which is more susceptible to factors such as the aspect ratio of seismic data, unreasonable azimuth angle division scheme, and uneven azimuth stacking coverage, thereby affecting the prediction accuracy of fractures.

[0005] Based on this technical background, the present invention studies a method and device for quantitative prediction of fractures based on prestack anisotropic inversion. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a method and device for quantitative prediction of fractures based on pre-stack anisotropic inversion. The method uses omnidirectional OVT domain gathers or angle domain ES360 gathers to carry out pre-stack AVAZ direct inversion, does not require azimuth stacking processing of the gathers, and performs ellipse fitting on the inversion results to obtain fracture development density and fracture azimuth, thereby improving the accuracy of fracture prediction.

[0007] In order to achieve the above object, a first aspect of the present invention provides a method for quantitatively predicting fractures based on prestack anisotropic inversion, comprising:

[0008] The inversion results are obtained by performing prestack AVAZ inversion based on the optimized omnidirectional OVT gathers or angle domain ES360 gathers.

[0009] The inversion results are subjected to ellipse fitting to obtain the fracture development density and fracture orientation.

[0010] A second aspect of the present invention provides a fracture quantitative prediction device based on prestack anisotropic inversion, comprising:

[0011] Prestack AVAZ inversion module, used to perform prestack AVAZ inversion based on optimized omnidirectional OVT gathers or angle domain ES360 gathers to obtain inversion results;

[0012] The ellipse fitting module is used to perform ellipse fitting on the inversion result to obtain the fracture development density and fracture orientation.

[0013] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0014] A memory storing executable instructions;

[0015] A processor runs the executable instructions in the memory to implement the quantitative fracture prediction method based on prestack anisotropic inversion described in the first aspect.

[0016] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for quantitative fracture prediction based on prestack anisotropic inversion as described in the first aspect.

[0017] The beneficial effects of the present invention include:

[0018] (1) The quantitative fracture prediction method based on prestack anisotropic inversion proposed in the present invention uses omnidirectional OVT domain gathers or angle domain ES360 gathers to carry out prestack AVAZ direct inversion. It does not require azimuth stacking processing of the gathers, and performs ellipse fitting on the inversion results to obtain fracture development density and fracture orientation, thereby improving the fracture prediction accuracy.

[0019] (2) The quantitative fracture prediction method based on pre-stack anisotropic inversion proposed in the present invention uses logging data to carry out anisotropic forward modeling to clarify the relationship between fracture density and anisotropic gradient, and uses the optimized full-scale OVT data set to carry out pre-stack AVAZ inversion. The azimuthal anisotropy gradient of the inversion result is further ellipse fitted to obtain the fracture development density and fracture azimuth, thereby avoiding the problem that the existing post-stack fracture prediction method ignores the azimuthal anisotropy of the fracture and the conventional pre-stack ellipse fitting method is affected by various factors, resulting in insufficient fracture prediction accuracy.

[0020] (3) The quantitative fracture prediction method based on pre-stack anisotropic inversion proposed in the present invention is based on logging data and uses the Ruger equation at close offset to perform anisotropic forward modeling to obtain pre-stack traces. The fracture segment data of the pre-stack traces are further analyzed to obtain the relationship between the fracture development density and the anisotropic gradient. This not only verifies the effectiveness and rationality of the method, but also provides a theoretical guarantee for the subsequent pre-stack AVAZ inversion.

[0021] (4) Compared with other methods, the quantitative fracture prediction method based on prestack anisotropy inversion proposed in the present invention can fully exploit the azimuthal anisotropy information of OVT domain data sets and improve the fracture prediction accuracy of deep-layer low signal-to-noise ratio volcanic rocks.

[0022] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings.

[0024] Figure 1 The present invention provides a flowchart of a method for quantitatively predicting fractures based on prestack anisotropic inversion.

[0025] Figure 2 These are the anisotropic forward model parameters in the quantitative fracture prediction method based on prestack anisotropic inversion proposed by the present invention.

[0026] Figure 3 This is a curve diagram of the accuracy analysis of the near-offset Ruger equation in the quantitative fracture prediction method based on prestack anisotropic inversion proposed in the present invention.

[0027] Figure 4 Schematic diagram of the well logging curve of the target layer of Well W in Example 1 of the present invention.

[0028] Figure 5 Schematic diagram of anisotropic forward modeling results of different fracture sections of Well W in Example 1 of the present invention.

[0029] Figure 6 It is a schematic diagram for comparing the OVT gather optimization processing in the first embodiment of the present invention.

[0030] Figure 7 Schematic diagram of AVO and AVAZ characteristic curves of seismic fracture layer ① in Example 1 of the present invention.

[0031] Figure 8 Schematic diagram of the fracture density profile of Well W in Example 1 of the present invention.

[0032] Fig. 9Schematic diagram of fracture development vectors of the target layer in Example 1 of the present invention. DETAILED DESCRIPTION

[0033] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0034] The present invention provides a method for quantitatively predicting fractures based on prestack anisotropic inversion, such as Figure 1-Figure 3 As shown, including:

[0035] The inversion results are obtained by performing prestack AVAZ inversion based on the optimized omnidirectional OVT gathers or angle domain ES360 gathers.

[0036] The inversion results are fitted with an ellipse to obtain the fracture density and fracture orientation.

[0037] In the present invention, the pre-stack AVAZ direct inversion is carried out using the omnidirectional OVT domain gather or the angle domain ES360 gather, without the need to perform azimuth stacking processing on the gather, and the inversion results are fitted with an ellipse to obtain the fracture development density and fracture azimuth, thereby improving the fracture prediction accuracy.

[0038] According to the present invention, it also includes:

[0039] Before prestack AVAZ inversion, the exact Ruger equation is simplified to the Ruger equation at close offset under the assumption of close incidence angle;

[0040] Based on the logging data, the Ruger equation is used to perform anisotropic forward modeling at close offset to obtain pre-stack gathers.

[0041] The relationship between fracture density and anisotropy gradient is obtained by analyzing the fracture segment data of pre-stack gathers.

[0042] If the fracture density is proportional to the anisotropy gradient, the inversion results can be obtained by performing prestack AVAZ inversion using the Ruger equation at close offset based on the optimized omnidirectional OVT gathers or angle domain ES360 gathers.

[0043] Preferably, the exact Ruger equation is as follows:

[0044]

[0045] Among them, θ and φ are the incident angle and azimuth of the seismic wave, α and β are the longitudinal and transverse wave velocities, Z is the longitudinal wave impedance, G is the vertical transverse wave shear modulus, Δ and - are the difference and average of the upper and lower interfaces, respectively, and ε (V) ,δ(V) ,γ are Thomsen anisotropy parameters in HTI medium, and Z and G are calculated by the following formulas:

[0046] Z=αρ,G=ρβ 2 ;

[0047] Where ρ is the density elasticity;

[0048] The Ruger equation at close offset is as follows:

[0049] R(θ,φ)=A+[B iso +B ain cos 2 (φ-φ0)]sin 2 θ;

[0050] Among them, A is the intercept, B iso , B ani are isotropic gradient and anisotropic gradient respectively, φ0 is the azimuth angle, A, B iso , B ani They are calculated by the following formulas:

[0051]

[0052]

[0053] According to the present invention, based on the well logging data, the pre-stack gathers obtained by anisotropic forward modeling using the Ruger equation at close offset include:

[0054] Based on the logging data, the reflection coefficient related to the incident angle and azimuth is calculated using the Ruger equation at close offset. The reflection coefficient is convolved with the wavelet to obtain the pre-stack gathers with different incident angles and azimuths.

[0055] Preferably, the logging data include P-wave velocity, S-wave velocity, density elastic parameters, and δ, ε, γ anisotropy parameters.

[0056] According to the present invention, the optimization is to sequentially perform anisotropic correction, denoising, and super gather processing on the omnidirectional OVT gathers;

[0057] The inversion results include isotropic gradient, anisotropic gradient, and azimuth.

[0058] In the present invention, in order to ensure the inversion accuracy, the accuracy of the Ruger equation at close offset is first analyzed, and the theoretical model parameters are selected as follows: Figure 2 As shown in the figure, the model is forward modeled using the Ruger equation for HTI media under anisotropy and the Ruger equation under close offset to obtain the corresponding reflection coefficient, as shown in Figure 3As shown in the figure, the calculation accuracy of the Ruger equation at close offset is comparable to that of the exact Ruger equation at small incident angles. Therefore, when the effective seismic incident angle is within 35°, the error between the reflection coefficient and the exact solution can be basically ignored. The Ruger equation under the assumption of close offset can be used to carry out fracture prediction research.

[0059] In the present invention, anisotropy forward modeling is carried out using logging data to clarify the relationship between fracture density and anisotropy gradient, and pre-stack AVAZ inversion is carried out using the optimized omnidirectional OVT gathers. The azimuthal anisotropy gradient of the inversion result is further ellipse fitted to obtain the fracture development density and fracture azimuth, thereby avoiding the problem that the existing post-stack fracture prediction method ignores the azimuthal anisotropy of the fracture and the conventional pre-stack ellipse fitting method is affected by multiple factors, resulting in insufficient fracture prediction accuracy.

[0060] In the present invention, based on the logging data, the Ruger equation is used for anisotropic forward modeling at close offset to obtain the pre-stack gathers, and the fracture segment data of the pre-stack gathers are further analyzed to obtain the relationship between the fracture development density and the anisotropic gradient, which not only verifies the effectiveness and rationality of the method, but also provides a theoretical guarantee for the subsequent pre-stack AVAZ inversion.

[0061] In the present invention, in order to verify the applicability and rationality of the method, it is necessary to carry out single well anisotropy forward modeling to better analyze the azimuthal anisotropy of the fractures in the study area, clarify the relationship between the fracture density and the anisotropy intensity, and use the longitudinal wave velocity, shear wave velocity, density elastic parameter curve and the δ, ε, γ anisotropy three-parameter curve of the logging data to substitute into the Ruger equation at the near offset to calculate the reflection coefficient related to the incident angle and azimuth angle, and convolve with the sub-wave to obtain the pre-stack gathers with different incident angles and azimuth angles, and carry out azimuthal anisotropy analysis on the fracture section of the forward gathers to clarify the relationship between the fracture development density and the anisotropy gradient. The greater the fracture density, the stronger the azimuthal anisotropy of the amplitude, and the fracture density is proportional to the anisotropy gradient. Therefore, the anisotropy parameters obtained by pre-stack AVAZ inversion are used to fit the azimuthal ellipse, which can be used to characterize the fracture development density in the study area.

[0062] Preferably, the formula used for ellipse fitting is:

[0063] R(θ,φ)=A+[B1sin 2 (φ-φ0)+B2cos 2 (φ-φ0)]sin 2 θ;

[0064] Where B1 is the minor axis of the ellipse fitting, and B1 = B iso , B2 is the major axis of the ellipse fitting, and B2=B ani +B iso ;

[0065] The flattening obtained by ellipse fitting is the fracture development density, and the direction of the major axis is the fracture orientation.

[0066] Compared with other methods, this method can fully exploit the azimuthal anisotropy information of OVT domain gathers and improve the fracture prediction accuracy of deep low signal-to-noise ratio volcanic rocks.

[0067] The present invention will be described in more detail below by way of examples.

[0068] Embodiment 1:

[0069] This example selects a deep volcanic rock target reservoir in a block of the Songnan fault depression in the Songliao Basin. The main target layer has multiple stages of volcanic rocks, and according to previous knowledge, the internal fractures of the reservoir are well developed, forming a good reservoir space. Post-stack coherence, curvature and other methods can only identify large-scale fractures, and cannot quantitatively predict the density of small-scale fracture development. Therefore, the pre-stack fracture prediction method based on pre-stack anisotropic inversion of this example is used to carry out pre-stack fracture prediction of volcanic rocks.

[0070] Well W in the study area, which has relatively complete logging curves and imaging logging and fracture density curves, was selected for anisotropic forward modeling. Figure 4 As shown in Figure 1, imaging logging of Well W shows that fractures are well developed in the target layer Huoshiling Formation around the well as a whole, and four sets of fracture zones are mainly developed vertically, including high-conductivity fractures, induced fractures and high-resistance fractures. The fracture trend rose diagram shows that the trend of the three types of fractures is nearly south-north, approximately perpendicular to the direction of the maximum horizontal principal stress.

[0071] Anisotropic forward modeling was performed on the four fracture-developed layers of Well W, and amplitude azimuth anisotropy analysis was performed on the forward modeled gathers. Figure 5 It can be seen that the ①-④ fracture layers all show the characteristic that the amplitude value decreases with the increase of the incident angle, and the amplitude attenuation gradient gradually increases with the azimuth angle from 0° to 90°, indicating that the four fracture development layers all have azimuthal anisotropy; from the comparison of the four characteristics, the attenuation gradient of the amplitude with the azimuth angle of the ① and ② layers is larger than that of the ③ and ④ layers, indicating that the greater the fracture density, the stronger the azimuthal anisotropy of the amplitude, and the fracture density is proportional to the anisotropy gradient. The above forward analysis shows that the method of this embodiment is applicable in this study area, and the azimuthal ellipse fitting using the anisotropy gradient obtained by prestack AVAZ inversion can be used to characterize the fracture development density in the study area.

[0072] The three-dimensional wide-azimuth and high-precision OVT gathers in the study area are as follows: Figure 6 As shown, Figure 6a is the original OVT gather data without anisotropic time difference correction. As the offset increases, the gather azimuth angles are arranged in a periodic manner. Due to the velocity azimuth anisotropy, the gathers have azimuth time difference. Affected by the time difference, the amplitude has a more obvious jitter phenomenon with the azimuth angle. The AVAZ inversion method is based on the azimuth amplitude, and it is necessary to eliminate the influence of anisotropic time difference, that is, Figure 6 As shown in b, the amplitude jitter phenomenon disappears after the anisotropic time difference correction, and the anisotropic gradient can be calculated by using the principle that the amplitude changes with the azimuth.

[0073] The corrected OVT gathers are subjected to optimization processing such as denoising and super gathers, and are converted into common azimuth-incident angle gathers using prestack migration velocity. The AVO and AVAZ characteristics of the fracture layer ① in the actual seismic gathers are analyzed. Figure 7 In a, the horizontal axis is the offset distance, and the vertical axis is the amplitude value. Curves of different colors represent the AVO changes under different azimuths. It can be seen that the amplitude decreases with the increase of the offset distance, and the larger the azimuth, the faster the amplitude decays, that is, the larger the AVO attenuation gradient. This feature is consistent with the amplitude change law of the forward modeling gathers in the fracture layer of Well W①, which further illustrates the effectiveness of the method. Figure 7 In b, the horizontal axis is the azimuth, and the vertical axis is the amplitude value. Curves of different colors represent the change of amplitude with azimuth at different incident angles. It can be seen that the amplitude changes with the azimuth in a cosine manner with a period of 180°. The larger the incident angle, the more obvious the periodic law of the amplitude changing with the azimuth. Through the above analysis of the actual wellside gather, the OVT gather data has rich azimuthal anisotropy information and can meet the requirements of prestack AVAZ inversion.

[0074] The anisotropically corrected OVT gathers were used to carry out prestack AVAZ inversion and fracture prediction in the study area. The isotropic gradient B was obtained by prestack AVAZ inversion. iso , anisotropic gradient B ani and azimuth φ, and further transform B iso , B ani Converted to B1 and B2 and ellipse fitting was performed to obtain the density and direction of fracture development. Figure 8 The figure shows the fracture density profile through Well W. It can be seen that the fracture density obtained by the prestack AVAZ inversion method is consistent with the fracture density curve on the well. The vertical ①-④ fractured layers of the target layer Huoshiling Formation show strong anisotropy in the inversion results, representing the fracture development area.

[0075] like Fig. 9 The figure shows the fracture development vector diagram along the target layer. The color represents the fracture development density, and the direction of the vector bar represents the predicted fracture direction. Fig. 9The prediction results of medium fractures show that the distribution of fractures and faults is well correlated, and the fracture development directions are mainly near north-south and north-northwest. Figure 4 The results of imaging logging in Well W are consistent with those in the previous study, indicating that the fracture prediction results of the present invention have high reliability.

[0076] Embodiment 2:

[0077] This embodiment provides a quantitative fracture prediction method based on prestack anisotropic inversion, such as Figure 1-Figure 3 As shown, including:

[0078] The inversion results are obtained by performing prestack AVAZ inversion based on the optimized omnidirectional OVT gathers or angle domain ES360 gathers.

[0079] Perform ellipse fitting on the inversion results to obtain the fracture density and fracture orientation;

[0080] Before prestack AVAZ inversion, the exact Ruger equation is simplified to the Ruger equation at close offset under the assumption of close incidence angle;

[0081] Based on the logging data, the Ruger equation is used to perform anisotropic forward modeling at close offset to obtain pre-stack gathers.

[0082] The relationship between fracture density and anisotropy gradient is obtained by analyzing the fracture segment data of pre-stack gathers.

[0083] If the fracture density is proportional to the anisotropy gradient, the inversion results can be obtained by performing prestack AVAZ inversion using the Ruger equation at close offset based on the optimized full-scale OVT gathers or angle-domain ES360 gathers.

[0084] The exact Ruger equation is as follows:

[0085]

[0086] Among them, θ and φ are the incident angle and azimuth of the seismic wave, α and β are the longitudinal and transverse wave velocities, Z is the longitudinal wave impedance, G is the vertical transverse wave shear modulus, Δ and - are the difference and average of the upper and lower interfaces, respectively, and ε (V) ,δ (V) ,γ are Thomsen anisotropy parameters in HTI medium, and Z and G are calculated by the following formulas:

[0087] Z=αρ,G=ρβ 2 ;

[0088] Where ρ is the density elasticity;

[0089] The Ruger equation at close offset is as follows:

[0090] R(θ,φ)=A+[B iso +B ani cos 2 (φ-φ0)]sin 2 θ;

[0091] Among them, A is the intercept, B iso , B ani are isotropic gradient and anisotropic gradient respectively, φ0 is the azimuth angle, A, B iso , B ani They are calculated by the following formulas:

[0092]

[0093]

[0094] Based on the logging data, the anisotropic forward modeling of Ruger equation at close offset is used to obtain the pre-stack gathers including:

[0095] Based on the logging data, the reflection coefficient related to the incident angle and azimuth is calculated using the Ruger equation at close offset, and the pre-stack gathers with different incident angles and azimuths are obtained by convolving the reflection coefficient with the wavelet.

[0096] Well logging data include P-wave velocity, S-wave velocity, density elastic parameters, and δ, ε, and γ anisotropy parameters;

[0097] The optimization is to perform anisotropy correction, denoising, and super gather processing on the full-range OVT gathers in sequence;

[0098] The inversion results include isotropic gradient, anisotropic gradient, and azimuth;

[0099] The formula used for ellipse fitting is:

[0100] R(θ,φ)=A+[B1sin 2 (φ-φ0)+B2cos 2 (φ-φ0)]sin 2 θ;

[0101] Where B1 is the minor axis of the ellipse fitting, and B1 = B iso , B2 is the major axis of the ellipse fitting, and B2=B ani +B iso ;

[0102] The flattening obtained by ellipse fitting is the fracture development density, and the direction of the major axis is the fracture orientation.

[0103] Embodiment three:

[0104] This embodiment provides a fracture quantitative prediction device based on prestack anisotropic inversion, including:

[0105] Prestack AVAZ inversion module, used to perform prestack AVAZ inversion based on optimized omnidirectional OVT gathers or angle domain ES360 gathers to obtain inversion results;

[0106] The ellipse fitting module is used to perform ellipse fitting on the inversion results to obtain the fracture development density and fracture orientation;

[0107] Before prestack AVAZ inversion, the exact Ruger equation is simplified to the Ruger equation at close offset under the assumption of close incidence angle;

[0108] Based on the logging data, the Ruger equation is used to perform anisotropic forward modeling at close offset to obtain pre-stack gathers.

[0109] The relationship between fracture density and anisotropy gradient is obtained by analyzing the fracture segment data of pre-stack gathers.

[0110] If the fracture density is proportional to the anisotropy gradient, the inversion results can be obtained by performing prestack AVAZ inversion using the Ruger equation at close offset based on the optimized full-scale OVT gathers or angle-domain ES360 gathers.

[0111] The exact Ruger equation is as follows:

[0112]

[0113] Among them, θ and φ are the incident angle and azimuth of the seismic wave, α and β are the longitudinal and transverse wave velocities, Z is the longitudinal wave impedance, G is the vertical transverse wave shear modulus, Δ and - are the difference and average of the upper and lower interfaces, respectively, and ε (V) ,δ (V) ,γ are Thomsen anisotropy parameters in HTI medium, and Z and G are calculated by the following formulas:

[0114] Z=αρ,G=ρβ 2 ;

[0115] Where ρ is the density elasticity;

[0116] The Ruger equation at close offset is as follows:

[0117] R(θ,φ)=A+B iso +B ani cos 2 (φ-φ0)]sin 2 θ;

[0118] Among them, A is the intercept, B iso , B ani are isotropic gradient and anisotropic gradient respectively, φ0 is the azimuth angle, A, B iso , B ani They are calculated by the following formulas:

[0119]

[0120]

[0121] Based on the logging data, the anisotropic forward modeling of Ruger equation at close offset is used to obtain the pre-stack gathers including:

[0122] Based on the logging data, the reflection coefficient related to the incident angle and azimuth is calculated using the Ruger equation at close offset, and the pre-stack gathers with different incident angles and azimuths are obtained by convolving the reflection coefficient with the wavelet.

[0123] Well logging data include P-wave velocity, S-wave velocity, density elastic parameters, and δ, ε, and γ anisotropy parameters;

[0124] The optimization is to perform anisotropy correction, denoising, and super gather processing on the full-range OVT gathers in sequence;

[0125] The inversion results include isotropic gradient, anisotropic gradient, and azimuth;

[0126] The formula used for ellipse fitting is:

[0127] R(θ,φ)=A+[B1sin 2 (φ-φ0)+B2cos 2 (φ-φ0)sin 2 θ;

[0128] Where B1 is the minor axis of the ellipse fitting, and B1 = B iso , B2 is the major axis of the ellipse fitting, and B2=B ani +B iso ;

[0129] The flattening obtained by ellipse fitting is the fracture development density, and the direction of the major axis is the fracture orientation.

[0130] Embodiment 4:

[0131] An embodiment of the present invention provides an electronic device including a memory and a processor.

[0132] A memory storing executable instructions;

[0133] The processor runs the executable instructions in the memory to implement a quantitative fracture prediction method based on prestack anisotropic inversion.

[0134] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0135] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present invention, the processor is used to run the computer-readable instructions stored in the memory.

[0136] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present invention.

[0137] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0138] Embodiment five:

[0139] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, a quantitative fracture prediction method based on prestack anisotropic inversion is implemented.

[0140] The computer-readable storage medium according to the embodiment of the present invention stores non-transitory computer-readable instructions, and when the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of the embodiments of the present invention are executed.

[0141] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0142] The embodiment of the present invention proposes a method for quantitative prediction of fractures based on pre-stack anisotropic inversion, which uses omnidirectional OVT domain gathers or angle domain ES360 gathers to carry out pre-stack AVAZ direct inversion. It does not require azimuth stacking processing of the gathers, and performs ellipse fitting on the inversion results to obtain fracture development density and fracture azimuth, thereby improving the accuracy of fracture prediction.

[0143] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for quantitative prediction of fractures based on prestack anisotropic inversion, characterized in that: include: The inversion results are obtained by performing prestack AVAZ inversion based on the optimized omnidirectional OVT gathers or angle domain ES360 gathers. The inversion results are subjected to ellipse fitting to obtain the fracture development density and fracture orientation.

2. The prediction method according to claim 1, characterized in that: Also includes: Before performing the prestack AVAZ inversion, the exact Ruger equation is simplified to the Ruger equation at close offset under the assumption of close incidence angle; Based on the logging data, the Ruger equation at the near offset is used to perform anisotropic forward modeling to obtain pre-stack gathers; Analyzing the fracture segment data of the pre-stack gather to obtain the relationship between fracture development density and anisotropy gradient; If the fracture density is proportional to the anisotropy gradient, based on the optimized omnidirectional OVT gather or angle domain ES360 gather, the Ruger equation at the close offset is used to perform prestack AVAZ inversion to obtain the inversion result.

3. The prediction method according to claim 2, characterized in that: The exact Ruger equation is as follows: Among them, θ and φ are the incident angle and azimuth of the seismic wave, α and β are the longitudinal and transverse wave velocities, Z is the longitudinal wave impedance, G is the vertical transverse wave shear modulus, Δ and - are the difference and average of the upper and lower interfaces, respectively, and ε (V) ,δ (V) ,γ are Thomsen anisotropy parameters in HTI medium, and Z and G are calculated by the following formulas: Z=ar, G=rv 2 ; Where ρ is the density elasticity; The Ruger equation at close offset is as follows: R(θ,φ)=A+[B iso +B ani cos 2 (φ-φ0)]sin 2 I; Among them, A is the intercept, B iso , B ani are isotropic gradient and anisotropic gradient respectively, φ0 is the azimuth angle, A, B iso , B ani They are calculated by the following formulas:

4. The prediction method according to claim 3, characterized in that: Based on the logging data, the anisotropic forward modeling using the Ruger equation at the near offset is performed to obtain the pre-stack gathers including: Based on the logging data, the reflection coefficient related to the incident angle and azimuth is calculated using the Ruger equation at the near offset, and the reflection coefficient is convolved with the wavelet to obtain pre-stack gathers with different incident angles and azimuths.

5. The prediction method according to claim 4, characterized in that: The logging data include P-wave velocity, S-wave velocity, density elastic parameters, and δ, ε, γ anisotropy parameters.

6. The prediction method according to claim 3, characterized in that: The optimization is to sequentially perform anisotropy correction, denoising, and super gather processing on the omnidirectional OVT gather; The inversion results include isotropic gradient, anisotropic gradient, and azimuth.

7. The prediction method according to claim 6, characterized in that: The formula used for the ellipse fitting is: R(θ,φ)=A+[B1sin 2 (φ-φ0)+B2cos 2 (φ-φ0)]sin 2 I; Where B1 is the minor axis of the ellipse fitting, and B1 = B iso , B2 is the major axis of the ellipse fitting, and B2=B ani +B iso ; The flattening obtained by ellipse fitting is the fracture development density, and the direction of the major axis is the fracture orientation.

8. A fracture quantitative prediction device based on prestack anisotropic inversion, characterized in that: include: Prestack AVAZ inversion module, used to perform prestack AVAZ inversion based on optimized omnidirectional OVT gathers or angle domain ES360 gathers to obtain inversion results; The ellipse fitting module is used to perform ellipse fitting on the inversion result to obtain the fracture development density and fracture orientation.

9. An electronic device, characterized in that: The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the quantitative fracture prediction method based on prestack anisotropic inversion according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for quantitatively predicting fractures based on prestack anisotropic inversion described in any one of claims 1 to 7 is implemented.

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