Anisotropy parameter scanning method and device, computer device and storage medium

Abstract

The application relates to an anisotropy parameter scanning method and device based on an imaging gather, computer equipment and a storage medium. The method comprises the following steps: acquiring an imaging gather; classifying the imaging gather into near, middle and far offset gather sets according to effective imaging offset distances; determining a scanning speed according to the flattening degree of the imaging gather; respectively scanning the middle and far offset gather sets according to the determined scanning speed, and determining the flattening speed of the far offset distance and the flattening speed of the middle offset distance; determining the anisotropy parameter epsilon value according to the flattening speed Vp1 of the far offset distance; and determining the anisotropy parameter delta value according to the flattening speed Vp2 of the middle offset distance. The application determines the anisotropy parameter through scanning based on the relationship between the flattening condition and speed of the imaging gather and the anisotropy parameter. The method is fast and stable, can rapidly estimate the anisotropy parameter, has relatively high precision and efficiency, and has high resolution due to the layer scanning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geophysical exploration, in particular to an anisotropy parameter scanning method and device based on imaging gathers, computer equipment and storage medium. BACKGROUND

[0002] In seismic exploration, anisotropy is generally present. With the improvement of the fine degree of seismic exploration, the target horizon develops from the middle-deep layer to the deep layer and the super-deep layer, and the influence of anisotropy on seismic exploration is greater and greater. The propagation speed of seismic waves along different directions is different. For some large offset and wide-azimuth observation systems, if the underground medium is simply regarded as isotropic, it will lead to problems such as non-convergence of diffraction waves in the imaging process, incorrect horizon positioning, and reduced imaging quality.

[0003] For the estimation of anisotropy parameters (Vp0, ε, δ, θ0), there are double-parameter scanning, thickness ratio method and higher-precision tomographic inversion method. The anisotropy parameter model obtained by the double-parameter scanning and the thickness ratio method has low precision and low accuracy, and the initial model for tomographic inversion has poor effect and low convergence efficiency. SUMMARY

[0004] Therefore, it is necessary to provide an anisotropy parameter scanning method and device based on imaging gathers, computer equipment and storage medium, which has relatively high precision and relatively high determination process efficiency.

[0005] In a first aspect, the present application provides an anisotropy parameter scanning method based on imaging gathers, comprising the following steps:

[0006] Obtaining imaging gathers;

[0007] Classifying the imaging gathers into near-offset gather set, middle-offset gather set and far-offset gather set according to the effective imaging offset;

[0008] Determining the scanning speed according to the flattening degree of the imaging gathers;

[0009] According to the determined scanning speed, scanning the middle-offset gather set and the far-offset gather set respectively to determine the flattening speed Vp1 of the far-offset and the flattening speed Vp2 of the middle-offset;

[0010] Determining the anisotropy parameter ε value according to the flattening speed Vp1 of the far-offset, and determining the anisotropy parameter δ value according to the flattening speed Vp2 of the middle-offset.

[0011] In one of the embodiments, the imaging gathers are classified into the near-offset gather set, the middle-offset gather set and the far-offset gather set according to the effective imaging offset.

[0012] In one of the embodiments, the scanning speed is 60% to 140% of the isotropic speed, and the scanning interval is 0.5% of the isotropic speed.

[0013] In one of the embodiments, the anisotropy parameter ε value is determined according to the flattened velocity Vp1 of the far offset, and is determined by the following formula: Vp1=Vp0(1+2ε).

[0014] In one of the embodiments, the anisotropy parameter δ value is determined according to the flattened velocity Vp2 of the middle offset, and is determined by the following formula: Vp2=Vp0(1+2δ).

[0015] After the anisotropy parameter ε value is determined according to the flattened velocity Vp1 of the far offset and the anisotropy parameter δ value is determined according to the flattened velocity Vp2 of the middle offset, the method further comprises the following steps:

[0016] The anisotropy parameter δ value and the anisotropy parameter ε value are respectively determined for all the seismic gathers to obtain a global anisotropy parameter field.

[0017] After the anisotropy parameter ε value is determined according to the flattened velocity Vp1 of the far offset and the anisotropy parameter δ value is determined according to the flattened velocity Vp2 of the middle offset, the method further comprises the following steps:

[0018] The anisotropy parameter δ value and the anisotropy parameter ε value are respectively determined for the imaging gathers.

[0019] The global anisotropy parameter field of the imaging gathers is obtained by linear interpolation.

[0020] In a second aspect, the application provides an anisotropy parameter scanning device based on imaging gathers, which comprises:

[0021] An acquisition module is configured to acquire imaging gathers.

[0022] An imaging gather classification module is configured to classify the imaging gathers into near offset gathers, middle offset gathers and far offset gathers according to effective imaging offsets.

[0023] A scanning speed determination module is configured to determine a scanning speed according to a flattened degree of the imaging gathers.

[0024] A flattened velocity determination module is configured to respectively scan the middle offset gathers and the far offset gathers according to the determined scanning speed, to determine a flattened velocity Vp1 of the far offset and a flattened velocity Vp2 of the middle offset.

[0025] The anisotropy parameter determination module is configured to determine the anisotropy parameter epsilon value according to the near-offset flattening velocity Vp1, and determine the anisotropy parameter delta value according to the middle-offset flattening velocity Vp2.

[0026] In a third aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of the above embodiments when executing the program.

[0027] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, wherein the computer program is executable on a processor to implement the steps of the method according to any one of the above embodiments.

[0028] The above imaging gather-based anisotropy parameter scanning method classifies the imaging gathers into near-offset gather, middle-offset gather and far-offset gather according to the effective imaging offset; then selects a scanning velocity with the isotropic velocity as the intermediate value, and determines the final scanning velocity according to the degree of gather flattening, i.e., the more straight the gather is, the more accurate the scanning velocity used is; then scans the middle-offset gather and the far-offset gather to obtain the flattening velocities of the middle-offset gather and the far-offset gather, and then converts the two key anisotropy parameters epsilon and delta according to the relationship between the flattening velocity and the isotropic velocity, i.e., obtains the anisotropy parameters. Finally, the global anisotropy parameter field is obtained by scanning all seismic gathers. The present application provides an imaging gather-based anisotropy parameter estimation method. Compared with the prior art, the present application has the advantages that: the initial anisotropy parameter field is obtained more conveniently and quickly, and the anisotropy parameters are estimated based on the sensitivity difference between the imaging gather and the anisotropy parameter, which is more scientific and reasonable. The initial anisotropy parameter field obtained by the present application can be applied to anisotropy parameter inversion, which can effectively improve the iteration efficiency of the inversion. The present application provides an anisotropy parameter estimation method based on the flattening of the imaging gather and the relationship between the velocity and the anisotropy parameter, which is fast and stable, and can quickly estimate the anisotropy parameter to provide an initial model basis for subsequent more detailed modeling. The imaging gather-based anisotropy parameter scanning method provided by the present application has relatively high precision, high determination process efficiency, and high resolution due to the layer-by-layer scanning. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1 A step diagram of the imaging gather-based anisotropy parameter scanning method of an embodiment;

[0030] Figure 2-1 An imaging gather diagram in the imaging gather-based anisotropy parameter scanning method of an embodiment;

[0031] Figure 2-2 This is a trace map flattened after scanning in an anisotropic parameter scanning method based on imaging traces according to one embodiment;

[0032] Figure 2-3 This is an anisotropic parameter δ-field map scanned from a single imaging gather in an anisotropic parameter scanning method based on an imaging gather according to an embodiment.

[0033] Figure 2-4 An anisotropic parameter ε-field map scanned from a single imaging gather in an anisotropic parameter scanning method based on an imaging gather according to an embodiment;

[0034] Figure 3 This is a block diagram of an anisotropic parameter scanning device based on an imaging gather according to an embodiment;

[0035] Figure 4 This is a schematic diagram of the structure of a computer device according to one embodiment. Detailed Implementation

[0036] To facilitate understanding of this application and to make the aforementioned objectives, features, and advantages of this application more apparent, a detailed description of specific embodiments of this application is provided below in conjunction with the accompanying drawings. Numerous specific details are set forth in the following description to provide a thorough understanding of this application, and preferred embodiments are shown in the accompanying drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application. This application can be implemented in many other ways than those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application; therefore, this application is not limited to the specific embodiments disclosed below. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0037] Example 1

[0038] Firstly, this application provides an anisotropic parameter scanning method based on imaging gathers; please refer to [link to relevant documentation]. Figure 1 The anisotropic parameter scanning method based on imaging gathers includes the following steps:

[0039] S110: Acquire imaging gathers;

[0040] Seismic imaging gathers refer to a group of seismic records obtained after processing in seismic exploration, which come from the same reflection point underground and have the same underground offset. Through analysis and processing of these seismic records, information about the structure and physical properties of the underground strata can be obtained. In seismic exploration, multiple geophones are usually used to receive seismic waves from underground reflection points. Each geophone will record a seismic trace, so the records of multiple geophones constitute seismic imaging gathers. Through processing and interpretation of these seismic records, information about the structure and physical properties of the underground strata can be obtained, providing an important basis for the exploration and development of oil, gas and other resources.

[0041] In this embodiment, the imaging gathers are imaging gathers obtained by migration imaging using isotropic velocity. In an embodiment, the imaging gathers after conventional processing can also be used. The specific conventional processing is determined according to project requirements, including but not limited to conventional processing procedures such as denoising and multiple wave removal. For the specific process of obtaining imaging gathers, please refer to the prior art, which will not be described here.

[0042] S120: classifying the imaging gathers into near-offset gathers, middle-offset gathers and far-offset gathers according to the effective migration offset;

[0043] In this embodiment, the imaging gathers are classified into near-offset gathers, middle-offset gathers and far-offset gathers according to the effective migration offset, so as to facilitate the subsequent determination of the flattening velocity of each classified gather. Specifically, for example, the imaging gathers are classified into near-offset gathers, middle-offset gathers and far-offset gathers according to the average effective migration offset.

[0044] In one embodiment, the imaging gathers are classified into near-offset gathers, middle-offset gathers and far-offset gathers according to the average effective migration offset.

[0045] S130: determining the scanning velocity according to the flattening degree of the imaging gathers;

[0046] In this embodiment, the scanning velocity is determined according to the flattening degree of the imaging gathers, that is, the final scanning velocity is determined according to the flattening degree of the gathers. The flatter the gathers are, the more accurate the scanning velocity used is. In one embodiment, the scanning velocity is 60% to 140% of the isotropic velocity, and the scanning interval is 0.5% of the isotropic velocity. In this way, the applicant has found that the use of the above scanning velocity can better determine the two key parameters ε and δ of anisotropy.

[0047] S140: scanning the middle-offset gathers and the far-offset gathers respectively according to the determined scanning velocity, and determining the flattening velocity Vp1 of the far-offset and the flattening velocity Vp2 of the middle-offset;

[0048] In this embodiment, according to the determined scanning speed, the middle offset distance gather and the far offset distance gather are scanned respectively to determine the flattening speed Vp1 of the far offset distance and the middle offset distance flattening speed Vp2. Of course, in actual application, the speed is scanned from low speed to high speed, the shape and continuity of the reflection wave group are observed, and the speed that makes the reflection wave group flattest and the continuity best is found, that is, the flattening speed. The middle offset distance gather and the far offset distance gather are scanned respectively, the shape and continuity of the middle offset distance gather and the far offset distance gather are observed, and the speed that makes the reflection wave group flattest and the continuity best is found, that is, the flattening speed corresponding to the middle offset distance gather and the far offset distance gather. Of course, in other embodiments, the scanning speed can also be adjusted on the basis of constant speed scanning to find more accurate flattening speed.

[0049] S150: Determine the anisotropy parameter ε value according to the flattening speed Vp1 of the far offset distance; determine the anisotropy parameter δ value according to the middle offset distance flattening speed Vp2.

[0050] In this embodiment, the corresponding anisotropy parameters are determined according to the flattening speed. The middle offset distance is more sensitive to δ, so the anisotropy parameter δ value is determined by the middle offset distance flattening speed Vp2. The far offset distance is more sensitive to ε, so the anisotropy parameter ε value is determined by the flattening speed Vp1 of the far offset distance.

[0051] The imaging gather-based anisotropy parameter scanning method classifies the imaging gathers into near-offset gather, middle-offset gather and far-offset gather according to the effective imaging offset; then selects the scanning velocity with the isotropic velocity as the intermediate value, and determines the final scanning velocity according to the gather flattening degree, the more straight the gather is, the more accurate the scanning velocity used is; then scans the middle-offset gather and the far-offset gather to obtain the flattening velocity of the middle-offset gather and the far-offset gather, and then converts the two key parameters ε and δ of the anisotropy through the relationship between the flattening velocity and the isotropic velocity, that is, the anisotropy parameter is obtained. The global anisotropy parameter field can be obtained by scanning all seismic gathers. The imaging gather-based anisotropy parameter estimation method is provided. Compared with the prior art, the beneficial effects of the present application are that the initial anisotropy parameter field is obtained more conveniently and quickly, the anisotropy parameters are estimated based on the sensitivity difference between the imaging gather and the anisotropy parameter, and the estimation of the anisotropy parameters is more scientific and reasonable. The initial anisotropy parameter field obtained by the present application can be applied to anisotropy parameter inversion, and can effectively improve the iteration efficiency of the inversion. The present application provides an anisotropy parameter estimation method based on the flattening of the imaging gather and the relationship between the velocity and the anisotropy parameter, and the method is fast and stable, and can quickly estimate the anisotropy parameter, providing an initial model basis for subsequent more detailed modeling. The imaging gather-based anisotropy parameter scanning method provided by the present application has relatively high precision, high determination process efficiency, and high resolution due to the layer-by-layer scanning.

[0052] In order to better determine the anisotropy parameter ε value through the flattening velocity Vp1 of the far offset, in one embodiment, the anisotropy parameter ε value is determined according to the flattening velocity Vp1 of the far offset by using the following formula: Vp1=Vp0(1+2ε).

[0053] In this way, the anisotropy parameter ε value can be better determined according to the flattening velocity Vp1 of the far offset by using the above formula. Vp0 is the isotropic velocity, or the isotropic velocity of the imaging gather obtained by offset imaging using the isotropic velocity.

[0054] In order to better determine the anisotropy parameter δ value through the flattening velocity Vp2 of the middle offset, in one embodiment, the anisotropy parameter δ value is determined according to the flattening velocity Vp2 of the middle offset by using the following formula: Vp2=Vp0(1+2δ).

[0055] Thus, by using the above formula, the anisotropy parameter delta value can be determined according to the middle offset flattening velocity Vp2. Wherein Vp0 is the isotropic velocity, or in other words, it is the isotropic velocity of the imaging gather obtained by using the isotropic velocity for migration imaging.

[0056] In the embodiment, by using Vp2=Vp0(1+2delta) to determine the anisotropy parameter delta value and using Vp1=Vp0(1+2epsilon) to determine the anisotropy parameter epsilon value, the imaging gathers are classified into near offset gather, middle offset gather and far offset gather according to the effective imaging offset; then the scanning velocity is selected with the isotropic velocity as the middle value, and the final scanning velocity is determined according to the flattening degree of the gather, the more straight the gather is, the more accurate the scanning velocity used is; then the middle offset gather and the far offset gather are scanned to obtain the flattening velocity of the middle offset gather and the far offset gather, and then the two key anisotropy parameters epsilon and delta can be converted according to the relationship between the flattening velocity and the isotropic velocity, that is, the anisotropy parameter can be obtained. Then all the seismic gathers are scanned to obtain the global anisotropy parameter field. The application provides an anisotropy parameter estimation method based on imaging gathers. Compared with the prior art, the application has the beneficial effects that: the initial anisotropy parameter field can be obtained more conveniently and quickly, the anisotropy parameters are estimated based on the middle offset and the far offset according to the sensitivity difference between the imaging gather and the anisotropy parameter, which is more scientific and reasonable. The initial anisotropy parameter field obtained by the application can be applied to anisotropy parameter inversion, which can effectively improve the iteration efficiency of the inversion. The application provides an anisotropy parameter estimation method based on the flattening of the imaging gather and the relationship between the velocity and the anisotropy parameter, which is fast and stable, and can quickly estimate the anisotropy parameter to provide an initial model basis for subsequent more detailed modeling. The anisotropy parameter scanning method based on imaging gathers provided by the application has relatively high precision, high determination process efficiency, and high resolution because the scanning can be performed layer by layer.

[0057] In one of the embodiments, after the anisotropy parameter epsilon value is determined according to the far offset flattening velocity Vp1 and the anisotropy parameter delta value is determined according to the middle offset flattening velocity Vp2, the method further includes the following steps:

[0058] The corresponding anisotropy parameter delta value and anisotropy parameter epsilon value are determined for all the seismic gathers to obtain the global anisotropy parameter field.

[0059] In one of the embodiments, after the anisotropy parameter epsilon value is determined according to the far offset flattening velocity Vp1 and the anisotropy parameter delta value is determined according to the middle offset flattening velocity Vp2, the method further includes the following steps:

[0060] respectively, and the anisotropy parameter ε value and the anisotropy parameter δ value of each imaging gather are determined respectively;

[0061] The global anisotropy parameter field of the imaging gather is obtained by linear interpolation.

[0062] In this embodiment, the anisotropy parameter δ value and the anisotropy parameter ε value are determined based on the imaging gathers extracted respectively, and then the global anisotropy parameter field of the imaging gather is obtained by linear interpolation. In this embodiment, the global anisotropy parameter field of the imaging gather is obtained by linear interpolation based on the anisotropy parameter, which can be performed according to the following steps: collecting anisotropy parameters: first, the anisotropy parameters near each imaging point need to be collected, including longitudinal wave velocity, transverse wave velocity, density, etc. These parameters can be obtained by various methods such as seismic exploration and geological survey. Interpolation calculation: based on the collected anisotropy parameters, the global anisotropy parameters of each imaging point can be calculated by using linear interpolation method. The linear interpolation method can select different interpolation algorithms according to the actual situation, such as bilinear interpolation, trilinear interpolation, etc. Constructing the global anisotropy parameter field: combining the global anisotropy parameters of each imaging point together, the global anisotropy parameter field of the imaging gather can be constructed. This parameter field can reflect the overall characteristics of the underground medium in terms of anisotropy, and provide an important reference for subsequent seismic data processing and interpretation.

[0063] In this embodiment, the global anisotropy parameter field is obtained by scanning all seismic traces; or the seismic traces are extracted for scanning, and then the global anisotropy parameter field is obtained by linear interpolation.

[0064] In this embodiment, the scanning can be performed layer by layer, such as scanning once every 300 ms, so that the flattening velocity resolution is determined based on layer-by-layer scanning, and the process efficiency for determining the anisotropy parameters is also higher.

[0065] The anisotropy parameter scanning method based on the imaging gathers provided by the application has the advantages that: the initial anisotropy parameter field can be obtained more conveniently and quickly; the anisotropy parameters are estimated based on the sensitivity difference between the imaging gathers and the anisotropy parameters, and the estimation of the anisotropy parameters based on the middle offset gathers and the far offset gathers is more scientific and reasonable; the initial anisotropy parameter field obtained by the method can be applied to anisotropy parameter inversion, and the iteration efficiency of the inversion can be effectively improved; the method is quick and stable, and can quickly estimate the anisotropy parameters, thereby providing an initial model basis for subsequent more detailed modeling; the anisotropy parameter scanning method based on the imaging gathers has relatively high precision, high determination process efficiency, and high resolution because the scanning can be performed layer by layer.

[0066] Example 2

[0067] The embodiment continues to provide an anisotropy parameter scanning method based on imaging gathers. It should be noted that anisotropy is generally present in seismic exploration. With the improvement of the fine degree of seismic exploration, the target horizon develops from the medium-deep layer to the deep layer and the super-deep layer, and the influence of anisotropy on seismic exploration is greater and greater. The propagation speed of seismic waves in different directions is different. For some large offset and wide-azimuth observation systems, if the underground medium is simply regarded as isotropic, problems such as non-convergence of diffraction waves in the imaging process and incorrect horizon positioning will occur, and the quality of imaging is reduced. For the estimation of anisotropy parameters, there are double-parameter scanning, thickness ratio method and higher-precision tomographic inversion method. The anisotropy parameter model obtained by the double-parameter scanning and the thickness ratio method has low precision and low accuracy, and the effect of the initial model for tomographic inversion is poor, and the convergence efficiency is low. In view of the problem that the current anisotropy parameter estimation method cannot provide a better initial model for tomographic inversion, the method has unique advantages, can make up for the shortcomings of the above methods, and obtain a more adaptive and accurate anisotropy initial model. There is no corresponding research literature about the method. The purpose of the present application is to obtain a better anisotropy initial model by using migration gathers, and to establish a more accurate initial model for anisotropy medium tomographic inversion. Seismic exploration needs to consider anisotropy inversion to obtain more accurate velocity and anisotropy parameters. The anisotropy parameter estimation method based on imaging gathers can provide a more adaptive and reliable initial model, effectively improve the efficiency and accuracy of anisotropy tomographic inversion, and provide strong technical support for accurate modeling of anisotropy tomographic inversion. The present application is aimed at the initial model establishment of anisotropy parameter field. The method adopted is as follows: first, isotropic velocity is used for migration imaging to obtain imaging gathers. Then, the imaging gathers are divided into three parts, which are near-offset gather, middle-offset gather and far-offset gather. A series of velocities are selected with the isotropic velocity as the middle value, and the middle-offset gather and the far-offset gather are scanned respectively, and the gather is flattened to obtain the flattening velocity. The two key parameters of anisotropy, ε and δ, can be calculated through the relationship between the flattening velocity and the isotropic velocity, and the global anisotropy parameter field can be obtained by scanning all seismic gathers.

[0068] In the embodiment, the anisotropy parameter scanning method based on imaging gathers includes the following steps:

[0069] 1) Obtain the imaging gathers after conventional processing. The specific conventional processing is determined according to the project requirements, including but not limited to denoising, multiple wave removal and other conventional processing procedures.

[0070] 2) Classify the seismic gathers. Generally, the gathers can be divided into three parts according to the effective imaging offset, which are near-offset gather, middle-offset gather and far-offset gather.

[0071] 3) Determine the scan velocity range, generally 60%~140% of the isotropic velocity, and the scan interval is 0.5% of the isotropic velocity. The final scan velocity is determined according to the degree of trace flattening. The straighter the trace is, the more accurate the scan velocity used is;

[0072] 4) The scan of the middle offset and the far offset is completed by step 3), and the flattening velocity Vp2 of the middle offset and the flattening velocity Vp1 of the far offset are determined:

[0073] 5) The middle offset is more sensitive to delta, and therefore the relationship is:

[0074] Vp2 = Vp0 (1+2delta)

[0075] The value of delta is obtained;

[0076] The far offset is more sensitive to epsilon, and therefore the relationship is:

[0077] Vp1 = Vp0 (1+2epsilon)

[0078] The value of epsilon is obtained.

[0079] 6) The global anisotropy parameter field is obtained by scanning all seismic traces; or the seismic traces are extracted for scanning, and then the global anisotropy parameter field is obtained by linear interpolation.

[0080] The application provides an anisotropy parameter estimation method based on an imaging trace set. Compared with the prior art, the application has the beneficial effects that: the initial anisotropy parameter field is obtained more conveniently and quickly, the anisotropy parameters are estimated based on the sensitivity difference between the imaging trace set and the anisotropy parameters, and the anisotropy parameters are estimated for the middle offset and the far offset, which is more scientific and reasonable. The initial anisotropy parameter field obtained by the application can be applied to anisotropy parameter inversion, and the iteration efficiency of the inversion can be effectively improved. The application provides an anisotropy parameter estimation method based on the flattening condition of the imaging trace set and the relationship between the velocity and the anisotropy parameters, and the method is fast and stable, and the anisotropy parameters can be quickly estimated, which provides an initial model basis for subsequent more detailed modeling.

[0081] Embodiment 3

[0082] This embodiment further provides a specific verification process of the anisotropy parameter scanning method based on the imaging trace set of the application. To prove the correctness and effectiveness of the application, the actual data test is described below. Please refer to Figure 2-1 、 Figure 2-2 、 Figure 2-3 、 Figure 2-4 .

[0083] Figure 2-1For imaging trace gather, the input data of the application, the longitudinal direction is depth, unit m, and the transverse direction is offset, unit m;

[0084] Figure 2-2 For the trace gather after scanning and flattening, the longitudinal direction is depth, unit m, and the transverse direction is offset, unit m;

[0085] Figure 2-3 For the anisotropy parameter delta field scanned by the single imaging trace gather, the longitudinal direction is depth, and the transverse direction has no unit.

[0086] Figure 2-4 For the anisotropy parameter epsilon field scanned by the single imaging trace gather, the longitudinal direction is depth, and the transverse direction has no unit.

[0087] As shown in Figure 2-1 , it is an offset imaging trace gather obtained by a standard process, and the velocity used is isotropic velocity, and since the influence of the anisotropy parameter is not considered, the imaging trace gather is not flat enough.

[0088] As shown in Figure 2-2 , it is an imaging trace gather after scanning and flattening, and at this time, the program automatically selects a flattening velocity to flatten the trace gather;

[0089] As shown in Figure 2-3 , it is the single anisotropy parameter delta finally obtained.

[0090] As shown in Figure 2-4 , it is the single anisotropy parameter epsilon finally obtained, and the change trends of the two anisotropy parameters are similar, which conforms to the basic geological understanding.

[0091] Based on the flattening of the imaging trace gather and the relationship between the velocity and the anisotropy parameter, the application provides an anisotropy parameter estimation method through scanning, which is fast and stable, and can quickly estimate the anisotropy parameter, thereby providing an initial model basis for subsequent more detailed modeling.

[0092] Embodiment 4

[0093] In a second aspect, the application provides an anisotropy parameter scanning device based on imaging trace gather, please refer to Figure 2-1 , the device comprises an acquisition module, an imaging trace gather classification module, a scanning velocity determination module, a flattening velocity determination module and an anisotropy parameter determination module;

[0094] The acquisition module is configured to acquire an imaging gather. Specifically, the seismic imaging gather refers to a set of seismic records obtained after processing in seismic exploration. These records come from the same reflection point in the subsurface and have the same subsurface offset. By analyzing and processing these seismic records, information about the subsurface structure and physical properties can be obtained. In seismic exploration, multiple geophones are often used to receive seismic waves from subsurface reflection points. Each geophone records a seismic trace, so the records of multiple geophones constitute a seismic imaging gather. By processing and interpreting these seismic records, information about the subsurface structure and physical properties can be obtained, providing important basis for the exploration and development of oil, gas and other resources. In this embodiment, the imaging gather is an imaging gather obtained by migration imaging using isotropic velocity. In an embodiment, a conventionally processed imaging gather can also be used. The specific conventional processing is determined according to project requirements, including but not limited to conventional processing procedures such as denoising and multiple wave removal. For the specific process of obtaining an imaging gather, please refer to the prior art, which will not be described here.

[0095] The imaging gather classification module is configured to classify the imaging gather into near-offset gather, middle-offset gather and far-offset gather according to the effective migration offset. In this embodiment, the imaging gather is classified into near-offset gather, middle-offset gather and far-offset gather according to the effective migration offset, so as to facilitate subsequent determination of the flattening velocity of each classified gather. Specifically, for example, the imaging gather is classified into near-offset gather, middle-offset gather and far-offset gather according to the average effective migration offset. In one embodiment, the imaging gather classification module is configured to classify the imaging gather into near-offset gather, middle-offset gather and far-offset gather according to the average effective migration offset.

[0096] The scanning velocity determination module is configured to determine the scanning velocity according to the flattening degree of the imaging gather. In this embodiment, the scanning velocity is determined according to the flattening degree of the imaging gather, that is, the final scanning velocity is determined according to the flattening degree of the gather. The flatter the gather, the more accurate the scanning velocity used. In one embodiment, the scanning velocity is 60% to 140% of the isotropic velocity, and the scanning interval is 0.5% of the isotropic velocity. In this way, the applicant has found that the above scanning velocity can better determine the two key parameters ε and δ of anisotropy.

[0097] The flattening velocity determination module is configured to determine the flattening velocity Vp1 of the far offset and the flattening velocity Vp2 of the middle offset according to the determined scanning velocities, respectively. In this embodiment, the flattening velocity Vp1 of the far offset and the flattening velocity Vp2 of the middle offset are determined according to the determined scanning velocities, respectively. Of course, in actual application, the velocity is scanned from low speed to high speed, the shape and continuity of the reflection wave group are observed, and the velocity that makes the reflection wave group flattest and the continuity best is found, which is the flattening velocity. The shape and continuity of the middle offset gather and the far offset gather are observed by scanning the middle offset gather and the far offset gather, respectively, and the velocity that makes the reflection wave group flattest and the continuity best is found, which is the flattening velocity corresponding to the middle offset gather and the far offset gather. Of course, in other embodiments, the scanning velocity can be adjusted on the basis of the constant velocity scanning to find a more accurate flattening velocity.

[0098] The anisotropy parameter determination module is configured to determine the anisotropy parameter ε value according to the flattening velocity Vp1 of the far offset, and to determine the anisotropy parameter δ value according to the flattening velocity Vp2 of the middle offset. In this embodiment, the corresponding anisotropy parameters are determined according to the flattening velocities. The middle offset is more sensitive to δ, so the anisotropy parameter δ value is determined by the flattening velocity Vp2 of the middle offset. The far offset is more sensitive to ε, so the anisotropy parameter ε value is determined by the flattening velocity Vp1 of the far offset.

[0099] The anisotropy parameter scanning device based on the imaging gather comprises an acquisition module, an imaging gather classification module, a scanning speed determination module, a flattening speed determination module and an anisotropy parameter determination module; the imaging gather is classified into a near-offset gather, a middle-offset gather and a far-offset gather according to the effective imaging offset; then the scanning speed is selected with the isotropic speed as the intermediate value, and the final scanning speed is determined according to the flattening degree of the gather; the more straight the gather is, the more accurate the scanning speed used is; then the middle-offset gather and the far-offset gather are scanned to obtain the flattening speed of the middle-offset gather and the far-offset gather, and then the two key parameters ε and δ of the anisotropy can be converted according to the relationship between the flattening speed and the isotropic speed, that is, the anisotropy parameter can be obtained. The global anisotropy parameter field can be obtained by scanning all the seismic gathers. The anisotropy parameter estimation method based on the imaging gather is provided. Compared with the prior art, the beneficial effects of the present application are that the initial anisotropy parameter field can be obtained more conveniently and quickly, the anisotropy parameters are estimated according to the middle-offset and the far-offset based on the sensitivity difference between the imaging gather and the anisotropy parameter, and the method is more scientific and reasonable. The initial anisotropy parameter field obtained by the present application can be applied to anisotropy parameter inversion, and the iteration efficiency of the inversion can be effectively improved. The present application provides an anisotropy parameter estimation method based on the flattening of the imaging gather and the relationship between the speed and the anisotropy parameter, and the method is fast and stable, and the anisotropy parameter can be quickly estimated, which provides an initial model basis for subsequent more detailed modeling. The anisotropy parameter scanning method based on the imaging gather provided by the present application has relatively high precision, high determination process efficiency, and high resolution because the scanning can be performed layer by layer.

[0100] In order to better determine the anisotropy parameter ε value through the flattening speed Vp1 of the far-offset, in one embodiment, the anisotropy parameter determination module determines the anisotropy parameter ε value according to the flattening speed Vp1 of the far-offset by using the following formula:

[0101] Vp1 = Vp0 (1 + 2ε)

[0102] In this way, the anisotropy parameter ε value can be better determined according to the flattening speed Vp1 of the far-offset by using the above formula. Vp0 is the isotropic speed, or the isotropic speed of the imaging gather obtained by offset imaging using the isotropic speed.

[0103] In order to better determine the anisotropy parameter δ value through the flattening speed Vp2 of the middle-offset, in one embodiment, the anisotropy parameter determination module determines the anisotropy parameter δ value according to the flattening speed Vp2 of the middle-offset by using the following formula:

[0104] Vp2=Vp0(1+2δ)

[0105] Thus, by using the above formula, the anisotropy parameter δ value can be determined according to the middle offset flattening speed Vp2. Wherein Vp0 is the isotropic speed, or in other words, it is the isotropic speed when the imaging gathers obtained by using the isotropic speed for migration imaging.

[0106] In the embodiment, the anisotropy parameter determination module determines the anisotropy parameter δ value by using Vp2=Vp0(1+2δ) and determines the anisotropy parameter ε value by using Vp1=Vp0(1+2ε), respectively, the imaging gather classification module is used to classify the imaging gathers into near offset gather, middle offset gather and far offset gather according to the effective imaging offset, the scanning speed determination module then selects the scanning speed with the isotropic speed as the middle value, and determines the final scanning speed according to the gather flattening degree, the more straight the gather is, the more accurate the scanning speed used is, then the flattening speed determination module scans the middle offset gather and the far offset gather to obtain the flattening speed of the middle offset gather and the far offset gather, and then the anisotropy parameter determination module can convert the two key anisotropy parameters ε and δ through the relationship between the flattening speed and the isotropic speed, that is, the anisotropy parameters can be obtained. Then the global anisotropy parameter field can be obtained by scanning all seismic gathers. The application provides an imaging gather-based anisotropy parameter estimation method. Compared with the prior art, the application has the beneficial effects that: the initial anisotropy parameter field can be obtained more conveniently and quickly, the anisotropy parameters are estimated based on the sensitivity difference between the imaging gather and the anisotropy parameter, and the estimation of the anisotropy parameters based on the middle offset and the far offset is more scientific and reasonable. The initial anisotropy parameter field obtained by using the application can be applied to anisotropy parameter inversion, and the iteration efficiency of the inversion can be effectively improved. The application provides an anisotropy parameter estimation method based on the flattening of the imaging gather and the relationship between the speed and the anisotropy parameter, and the method is fast and stable, and the anisotropy parameters can be quickly estimated, which provides an initial model basis for subsequent more detailed modeling. The imaging gather-based anisotropy parameter scanning method provided by the application has relatively high precision, high determination process efficiency, and high resolution because the scanning can be performed layer by layer.

[0107] In one of the embodiments, the anisotropy parameter scanning device based on imaging gathers further comprises an anisotropy parameter field determining module connected with the acquisition module, the imaging gather classifying module, the scanning velocity determining module, the flattening velocity determining module and the anisotropy parameter determining module respectively; the anisotropy parameter field determining module is used to determine the corresponding anisotropy parameter δ value and anisotropy parameter ε value of all seismic gathers respectively through the acquisition module, the imaging gather classifying module, the scanning velocity determining module, the flattening velocity determining module and the anisotropy parameter determining module respectively to obtain a global anisotropy parameter field. In this embodiment, all seismic gathers are classified into near offset gather, middle offset gather and far offset gather according to the effective imaging offset of the imaging gathers, and then the scanning velocity is determined according to the flattening degree of the imaging gathers; the middle offset gather and the far offset gather are scanned respectively according to the determined scanning velocity to determine the flattening velocity Vp1 of the far offset and the flattening velocity Vp2 of the middle offset; the anisotropy parameter ε value is determined according to the flattening velocity Vp1 of the far offset; the anisotropy parameter δ value is determined according to the flattening velocity Vp2 of the middle offset to obtain the anisotropy parameter ε value and the anisotropy parameter δ value of all seismic gathers respectively. In this embodiment, all seismic gathers can also be called all seismic imaging gathers or all imaging gathers.

[0108] In one of the embodiments, the anisotropy parameter field determining module comprises:

[0109] The extraction and anisotropy parameter determining unit is used to extract the imaging gathers, and determine the corresponding anisotropy parameter δ value and anisotropy parameter ε value of all seismic gathers respectively through the acquisition module, the imaging gather classifying module, the scanning velocity determining module, the flattening velocity determining module and the anisotropy parameter determining module according to the extracted imaging gathers;

[0110] The anisotropy parameter field determining unit is used to obtain the global anisotropy parameter field of the imaging gathers through linear interpolation according to the corresponding anisotropy parameter δ value and anisotropy parameter ε value.

[0111] In this embodiment, the anisotropy parameter δ value and the anisotropy parameter ε value are determined based on the extracted imaging gathers respectively, and then the global anisotropy parameter field of the imaging gathers is obtained through linear interpolation. In this embodiment, the global anisotropy parameter field of the imaging gathers is obtained through linear interpolation based on the anisotropy parameter, which can be performed according to the following steps: collecting anisotropy parameters: first, the anisotropy parameters near each imaging point need to be collected, including P-wave velocity, S-wave velocity, density, etc. These parameters can be obtained through various ways such as seismic exploration and geological survey. Interpolation calculation: based on the collected anisotropy parameters, the global anisotropy parameters of each imaging point can be calculated using linear interpolation method. The linear interpolation method can select different interpolation algorithms according to the actual situation, such as bilinear interpolation, trilinear interpolation, etc. Constructing global anisotropy parameter field: combining the global anisotropy parameters of each imaging point together, the global anisotropy parameter field of the imaging gathers can be constructed. This parameter field can reflect the overall characteristics of the underground medium in terms of anisotropy, and provide an important reference for subsequent seismic data processing and interpretation.

[0112] In this embodiment, scanning all seismic traces can obtain the global anisotropy parameter field; or the seismic traces can be extracted for scanning, and then the global anisotropy parameter field is obtained through linear interpolation.

[0113] In this embodiment, the scanning can be layer scanning, such as scanning every 300 ms, so that the flattening velocity resolution is determined based on layer scanning, and the process efficiency of determining the anisotropy parameter is also higher.

[0114] The anisotropy parameter scanning device based on the imaging gather comprises an acquisition module, an imaging gather classification module, a scanning speed determination module, a flattening speed determination module and an anisotropy parameter determination module; the imaging gather is classified into near offset gather, middle offset gather and far offset gather according to the effective imaging offset; then the scanning speed is selected with the isotropic speed as the intermediate value, and the final scanning speed is determined according to the flattening degree of the gather; the more straight the gather is, the more accurate the scanning speed used is; then the middle offset gather and the far offset gather are scanned to obtain the flattening speed of the middle offset gather and the far offset gather, and then the two key parameters ε and δ of the anisotropy can be converted through the relationship between the flattening speed and the isotropic speed, that is, the anisotropy parameter can be obtained. The global anisotropy parameter field can be obtained by scanning all seismic gathers. The anisotropy parameter estimation method based on the imaging gather is provided. Compared with the prior art, the beneficial effects of the present application are that: the initial anisotropy parameter field can be obtained more conveniently and quickly, the anisotropy parameters are estimated based on the sensitivity difference between the imaging gather and the anisotropy parameter, and the estimation of the anisotropy parameters based on the middle offset and the far offset is more scientific and reasonable. The initial anisotropy parameter field obtained by the present application can be applied to anisotropy parameter inversion, and can effectively improve the iteration efficiency of the inversion. The present application provides an anisotropy parameter estimation method based on the flattening of the imaging gather and the relationship between the speed and the anisotropy parameter, and the method is fast and stable, and can quickly estimate the anisotropy parameter, thereby providing an initial model basis for subsequent more detailed modeling. The anisotropy parameter scanning method based on the imaging gather provided by the present application has relatively high precision, high determination process efficiency, and high resolution due to the layer scanning.

[0115] Example 5

[0116] In a third aspect, a computer device is provided, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor implements the steps of the method in any one of the above embodiments when executing the program.

[0117] In one embodiment, a computer device is provided, and the internal structure diagram of the computer device can be as shown in Figure 2-2As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The network interface of the computer device is used to communicate with the server through the network connection. The computer program is executed by the processor to implement an imaging trace set-based anisotropy parameter scanning method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0118] Those skilled in the art can understand that, Figure 2-3 Figure 2-4 Figure 3 Figure 4 Figure 4 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0119] In one embodiment, a computer device is provided, including a memory, a processor and a computer program stored on the memory and executable on the processor, and the processor executes the computer program to implement the following steps:

[0120] 1) Obtain an imaging trace set; the seismic imaging trace set refers to a set of seismic records obtained after processing in seismic exploration, which come from the same reflection point underground and have the same underground offset distance. By analyzing and processing these seismic records, the underground stratum structure and physical property information can be obtained. In seismic exploration, multiple geophones are usually used to receive seismic waves from underground reflection points. Each geophone records a seismic trace, so the records of multiple geophones constitute a seismic imaging trace set. By processing and interpreting these seismic records, the underground stratum structure and physical property information can be obtained, which provides an important basis for the exploration and development of oil, gas and other resources. In this embodiment, the imaging trace set is obtained by using isotropic velocity for migration imaging. In an embodiment, a conventional processed imaging trace set can also be used, and the specific conventional processing is determined according to the project requirements, including but not limited to conventional processing procedures such as denoising and multiple wave removal. For the specific process of obtaining the imaging trace set, please refer to the prior art, which will not be described here.

[0121] 2) classifying the imaging gathers into near offset gather, middle offset gather and far offset gather according to the effective imaging offset; in the embodiment, the imaging gathers are classified into near offset gather, middle offset gather and far offset gather according to the effective imaging offset, so as to facilitate the subsequent determination of the flattening velocity of each classified gather. Specifically, for example, the imaging gathers are classified into near offset gather, middle offset gather and far offset gather according to the average effective imaging offset. In one of the embodiments, the imaging gathers are classified into near offset gather, middle offset gather and far offset gather according to the average effective imaging offset.

[0122] 3) determining the scanning velocity according to the flattening degree of the imaging gather; in the embodiment, the scanning velocity is determined according to the flattening degree of the imaging gather, that is, the final scanning velocity is determined according to the flattening degree of the gather, and the more straight the gather is, the more accurate the scanning velocity used is. In one of the embodiments, the scanning velocity is 60% to 140% of the isotropic velocity, and the scanning interval is 0.5% of the isotropic velocity. In this way, the applicant has found that the two key parameters ε and δ of anisotropy can be better determined by using the above scanning velocity.

[0123] 4) respectively scanning the middle offset gather and the far offset gather according to the determined scanning velocity, and determining the flattening velocity Vp1 of the far offset and the flattening velocity Vp2 of the middle offset; in the embodiment, the middle offset gather and the far offset gather are respectively scanned according to the determined scanning velocity, and the flattening velocity Vp1 of the far offset and the flattening velocity Vp2 of the middle offset are determined. Of course, in actual application, the velocity is scanned from low speed to high speed, the shape and continuity of the reflection wave group are observed, and the velocity that makes the reflection wave group the flattest and the continuity the best is found, which is the flattening velocity. The middle offset gather and the far offset gather are respectively scanned, the shape and continuity of the middle offset gather and the far offset gather are observed, and the velocity that makes the reflection wave group the flattest and the continuity the best is found, which is the flattening velocity corresponding to the middle offset gather and the far offset gather. Of course, in other embodiments, the scanning velocity can also be adjusted on the basis of the constant speed scanning to find a more accurate flattening velocity.

[0124] 5) determining the anisotropy parameter ε value according to the flattening velocity Vp1 of the far offset, and determining the anisotropy parameter δ value according to the flattening velocity Vp2 of the middle offset; in the embodiment, the corresponding anisotropy parameters are determined according to the flattening velocity. The middle offset is more sensitive to δ, so the anisotropy parameter δ value is determined by the flattening velocity Vp2 of the middle offset. The far offset is more sensitive to ε, so the anisotropy parameter ε value is determined by the flattening velocity Vp1 of the far offset.

[0125] The computer device, when the processor executes the computer program, realizes the steps of the anisotropy parameter scanning method based on the imaging gather, classifies the imaging gather into near offset gather, middle offset gather and far offset gather according to the effective imaging offset distance; then selects the scanning speed with the isotropic speed as the intermediate value, and determines the final scanning speed according to the gather flattening degree, the more straight the gather is, the more accurate the scanning speed used is; then scans the middle offset gather and the far offset gather respectively to obtain the flattening speed of the middle offset gather and the far offset gather, and then converts the two key parameters ε and δ of the anisotropy through the relationship between the flattening speed and the isotropic speed, that is, the anisotropy parameter can be obtained. Then the global anisotropy parameter field can be obtained by scanning all seismic gathers. The application provides an anisotropy parameter estimation method based on the imaging gather. Compared with the prior art, the beneficial effects of the application are that: the initial anisotropy parameter field can be obtained more conveniently and quickly, the anisotropy parameters are estimated based on the sensitivity difference between the imaging gather and the anisotropy parameter, and the estimation of the anisotropy parameters based on the middle offset and the far offset is more scientific and reasonable. The initial anisotropy parameter field obtained by the application can be applied to anisotropy parameter inversion, and can effectively improve the iteration efficiency of the inversion. The application provides an anisotropy parameter estimation method based on the flattening of the imaging gather and the relationship between the speed and the anisotropy parameter, and the method is fast and stable, and can quickly estimate the anisotropy parameter, thereby providing an initial model basis for subsequent more detailed modeling. The anisotropy parameter scanning method based on the imaging gather provided by the application has relatively high precision, high determination process efficiency, and high resolution because the scanning can be performed layer by layer.

[0126] Embodiment 6

[0127] In a fourth aspect, the application provides a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of the above embodiments.

[0128] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0129] The technical features of the above-mentioned embodiments can be combined in any way. In order to make the description simple, all possible combinations of the technical features in the above-mentioned embodiments are not described, but as long as the combination of the technical features does not exist, it should be considered as the scope of the present application. It should be noted that the "in an embodiment of the present application", "for example", "such as" and the like are intended to illustrate the present application, but not to limit the present application. The above-mentioned embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it should not be understood as limiting the scope of the patent application. It should be noted that for those skilled in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are within the scope of the present application. Therefore, the scope of the patent protection of the present application should be subject to the appended claims.

Claims

1. A method for scanning anisotropic parameters based on imaging gathers, characterized in that, Includes the following steps: Acquire imaging gathers; Imaging gathers are classified into near-offset gathers, medium-offset gathers, and far-offset gathers based on the effective imaging offset. The scanning speed is determined based on the flattening of the imaging gathers. Based on the determined scanning speed, the mid-offset gather and the far-offset gather are scanned separately to determine the flattening speed for the far-offset gather. and center offset flattening speed The flattening speed is the speed at which the reflected wave group is flattest and has the best continuity during scanning; Based on the flattening speed of the far offset Determining anisotropic parameters with isotropic velocities Value; based on the center offset leveling speed Determining anisotropic parameters with isotropic velocities value.

2. The method according to claim 1, characterized in that, The imaging gathers are classified into near-offset gathers, medium-offset gathers, and far-offset gathers based on the effective imaging offset.

3. The method according to claim 1, characterized in that, In the process of determining the scanning speed based on the flattening of the imaging gather, the scanning speed is 60% to 140% of the isotropic speed, and the scanning interval is 0.5% of the isotropic speed.

4. The method according to claim 1, characterized in that, The leveling speed based on the far offset distance Determining anisotropic parameters with isotropic velocities The value is determined using the following formula: , The velocity is isotropic.

5. The method according to claim 1, characterized in that, The flattening speed based on the mid-offset distance Determining anisotropic parameters with isotropic velocities The value is determined using the following formula: , The velocity is isotropic.

6. The method according to any one of claims 1 to 5, characterized in that, The leveling speed based on the far offset distance Determine anisotropy parameters The value and the flattening speed based on the mid-offset distance Determine anisotropy parameters After the value is obtained, the method further includes the following steps: Determine the corresponding anisotropy parameters for each of the seismic gathers. Values ​​and anisotropy parameters The value is used to obtain the global anisotropic parameter field.

7. The method according to any one of claims 1 to 5, characterized in that, The leveling speed based on the far offset distance Determine anisotropy parameters The value and the flattening speed based on the mid-offset distance Determine anisotropy parameters After the value is obtained, the method further includes the following steps: Extract the imaging gathers separately and determine the corresponding anisotropy parameters for each. Values ​​and anisotropy parameters value; The global anisotropic parameter field of the imaging gather is obtained by linear interpolation.

8. An anisotropic parameter scanning device based on imaging gathers, characterized in that, The device includes: The acquisition module is used to acquire imaging gathers; The imaging gather classification module is used to classify imaging gathers into near-offset gathers, medium-offset gathers, and far-offset gathers according to the effective imaging offset. The scanning speed determination module is used to determine the scanning speed based on the flattening of the imaging gather; The flattening speed determination module is used to scan the mid-offset gather and the far-offset gather separately according to a determined scanning speed, and to determine the flattening speed for the far-offset gather. and center offset flattening speed The flattening speed is the speed at which the reflected wave group is flattest and has the best continuity during scanning; Anisotropy parameter determination module, used to determine the flattening speed based on the long offset distance. Determining anisotropic parameters with isotropic velocities Values; and the flattening speed based on the mid-offset distance. Determining anisotropic parameters with isotropic velocities value.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-7.

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