Deep diffraction field velocity modeling method and device, electronic equipment and storage medium

Abstract

The application provides a deep diffraction field velocity modeling method and device, electronic equipment and storage medium, relates to the deep resource exploration field, and the method comprises the following steps: obtaining diffraction wave separation data, constructing a common diffraction point multi-aperture angle gather through angle migration based on an edge diffraction model and a scatterer physical model, and capturing the diffraction response in the multi-aperture; according to the angle gather, a correction relationship between the diffraction point dip angle and the migration velocity is established; then, according to the correction relationship, for each common diffraction point multi-aperture angle gather, the diffraction field velocity spectrum of each diffraction point is calculated based on the local similarity and the mixed weight of the difference boot-strap; the diffraction wave velocity value of the focused signal is picked up through human-computer interaction; and finally, the model is constructed through interpolation. The application can effectively capture the weak energy of deep diffraction bodies, improve the focusing quality of the velocity spectrum, construct a refined velocity model, and provide support for imaging of deep dry hot rock and other unconventional reservoirs.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of deep earth resource exploration, and particularly relates to a deep earth diffraction field velocity modeling method and device, electronic equipment and storage medium. BACKGROUND

[0002] In the processing and imaging of seismic data, a reasonable velocity model is crucial for high-precision imaging. In diffraction wave velocity modeling, most existing technologies are carried out on post-stack or migration gathers. The low signal-to-noise ratio characteristics of deep reservoir diffraction response pose challenges to migration velocity modeling. In diffraction wave velocity modeling research, most are carried out on post-stack or migration gathers, such as diffraction velocity analysis methods of velocity continuation and local maximum peak value, residual diffraction moveout velocity analysis method, etc. However, the current method still has the technical problems of low correlation degree of diffraction wave signals and poor accuracy of diffraction wave migration velocity. SUMMARY

[0003] The present application aims to provide a deep earth diffraction field velocity modeling method and device, electronic equipment and storage medium, which enhances the correlation of diffraction wave signals and improves the accuracy of diffraction wave migration velocity.

[0004] In a first aspect, the present application provides a deep earth diffraction field velocity modeling method, which comprises:

[0005] Obtaining diffraction wave separated data, based on an edge diffraction model and a scatterer physical model, constructing a common diffraction point multi-aperture angle gather through angle migration, and capturing diffraction response within the multi-aperture;

[0006] According to the common diffraction point multi-aperture angle gather, establishing a correction relationship between diffraction point dip angle and migration velocity;

[0007] According to the correction relationship between diffraction point dip angle and migration velocity, for each common diffraction point multi-aperture angle gather, calculating the diffraction field velocity spectrum of each diffraction point based on the hybrid weight of local similarity and difference boot-strap;

[0008] In the diffraction field velocity spectrum of each diffraction point, picking up the diffraction wave velocity value of the focused signal through a man-machine interactive mode;

[0009] Constructing a target diffraction field velocity model by interpolating the diffraction wave velocity value.

[0010] In an optional embodiment, obtaining diffraction wave separated data comprises:

[0011] Obtaining seismic data directly used for migration, removing reflection components from the seismic data to obtain diffraction wave separated data.

[0012] In optional embodiments, the common diffraction point multi-aperture angle gathers are constructed by angle migration, including:

[0013] For any imaging point in subsurface space, the angle gather data is generated by angle migration, and the diffraction incidence angle and diffraction emergence angle in the local position of the diffraction point are calculated by ray tracing:

[0014]

[0015] Wherein, α represents the included angle between the incident ray and the vertical axis, that is, the diffraction incidence angle; β represents the included angle between the emergence ray and the vertical axis, that is, the diffraction emergence angle;

[0016] The diffraction point dip angle is determined according to the included angle between the emergence ray and the vertical line of the local reflection interface:

[0017]

[0018] Wherein, θ is the diffraction point dip angle.

[0019] In optional embodiments, the multi-aperture internal diffraction response is captured, including:

[0020] Based on the three-dimensional angle domain migration framework, the first aperture internal diffraction energy of the scatterer model is selected by the imaging ray, and the second aperture internal diffraction main energy band is obtained by using the section dip angle field to control the ray beam.

[0021] In optional embodiments, the correction relationship between the diffraction point dip angle and the migration velocity, including:

[0022]

[0023] Wherein, τ(θ) is used to represent the travel time correction formula of the diffraction response in the migration dip angle domain, θ is the diffraction point dip angle, γ = υ m / υ, v m is the migration velocity, v is the original velocity, ξ = (x m -x d ) / z d , x m is the migration imaging point, x d , z d is the actual diffraction point position, τ0 is the two-layer travel time under the vertical incidence.

[0024] In optional embodiments, the mixed weight of local similarity and difference boot-strap is determined by the following formula:

[0025]

[0026] Wherein, w hyb (j,k) is the mixed weight, w swa weight function parameterized by a time-dependent parameter b(k); w νs is a local similarity weight function, κ[q(j, k), q r (k)] is a local similarity.

[0027] In a second aspect, the present application provides a deep diffraction field velocity modeling device, the device comprising:

[0028] A common diffraction point multi-aperture angle gather construction module is configured to obtain diffraction wave separation data, construct a common diffraction point multi-aperture angle gather through angle migration based on an edge diffraction model and a scatterer physical model, and capture diffraction responses within a multi-aperture;

[0029] A correction relationship establishment module is configured to establish a correction relationship between diffraction point dip angles and migration velocities based on the common diffraction point multi-aperture angle gather;

[0030] A calculation module is configured to calculate diffraction field velocity spectra of each diffraction point based on a hybrid weight of local similarity and differential boot-strap for each common diffraction point multi-aperture angle gather according to the correction relationship between diffraction point dip angles and migration velocities;

[0031] A picking module is configured to pick a diffraction wave velocity value of a focused signal in the diffraction field velocity spectrum of each diffraction point through a human-computer interaction mode;

[0032] A modeling module is configured to construct a target diffraction field velocity model by performing interpolation processing on the diffraction wave velocity value.

[0033] In an optional implementation, the common diffraction point multi-aperture angle gather construction module is further configured to:

[0034] Obtain seismic data directly used for migration, remove reflection components from the seismic data, and obtain diffraction wave separation data.

[0035] In a third aspect, the present application provides an electronic device comprising a processor and a memory, the memory storing computer executable instructions capable of being executed by the processor, and the processor executes the computer executable instructions to implement the deep diffraction field velocity modeling method of any one of the preceding embodiments.

[0036] In a fourth aspect, the present application provides a computer readable storage medium storing computer executable instructions, and the computer executable instructions, when invoked and executed by a processor, cause the processor to implement the deep diffraction field velocity modeling method of any one of the preceding embodiments.

[0037] The present application provides a method, device, electronic device, and storage medium for modeling deep earth diffraction field velocity. This application addresses deep unconventional reservoirs and, in order to fully utilize the wide illumination propagation law of diffraction waves, constructs a common diffraction point multi-aperture angle gather based on the Huygens principle. This gather has an ultra-high number of stacking times, can capture diffraction energy within multiple apertures, enhances the correlation of diffraction wave signals, and improves the accuracy of diffraction wave offset velocity. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0039] Figure 1 A flowchart of a method for modeling deep Earth diffraction field velocity provided in an embodiment of the present application;

[0040] Figure 2 A schematic diagram of constructing a common-incident point-to-point multi-aperture angle gather provided in an embodiment of the present application;

[0041] Figure 3 An interpolation schematic diagram provided in an embodiment of the present application;

[0042] Figure 4 A flowchart of a specific deep earth diffraction field velocity modeling method provided in an embodiment of the present application;

[0043] Figure 5 A structural diagram of a deep earth diffraction field velocity modeling device provided in an embodiment of the present application;

[0044] Figure 6 A structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0046] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative work are within the scope of protection of the present application.

[0047] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0048] A commonly used velocity processing method is stacking velocity spectrum analysis based on CMP gathers. To address the velocity spectrum problem in AVO, Ratcliffe and Adler (2000), Sarkar et al. (2001), Yan and Tsvankin (2008), and Fomel (2009) studied velocity analysis and modeling methods in the presence of complex waveforms and polarity reversals. In addition to stacking velocity, migration velocity analysis controls the quality of the final imaging, with the most commonly used being angle-domain migration velocity analysis. Biondi and Symes (2004) studied velocity analysis methods on angle-domain common imaging point gathers based on wavefield continuation. In addition to gather-based velocity analysis, Fomel (2003) implemented a migration velocity analysis method based on velocity continuation. Sava et al. (2005) improved the resolution and continuity of traditional methods by analyzing incompletely focused diffraction waves and incompletely migrated reflection waves. Fomel et al. (2007) proposed a method based on local maximum variance, which uses velocity extension and local peak technology to perform velocity analysis based on the diffraction after separation rather than the focusing degree of the reflected wave. By ray tracing the incompletely offset diffraction waves, Coimbra et al. (2013) used the residual diffraction time difference to update the offset velocity. Merzlikin and Fomel (2017) proposed a method for path summation imaging along the velocity dimension, avoiding the use of multiple velocities for offset and picking up velocity. Lin Peng (2020) combined the diffraction wave travel time correction formula and focusing method in the inclination domain for the separated diffraction waves, enhanced the correlation of the diffraction wave signal, and improved the accuracy of the diffraction wave migration velocity. Decker and Fomel (2021) based on the path integral idea, used the diffraction wave focusing spectrum to calculate the diffraction wave distribution probability and energy gradient distribution weight, and performed diffraction wave migration velocity analysis from a probabilistic perspective.

[0049] However, due to the low signal-to-noise ratio of the deep reservoir diffraction response, it is challenging to model the migration velocity. Based on this, the embodiments of the present application provide a deep diffraction field velocity modeling method, device, electronic equipment and storage medium, which enhances the correlation of the diffraction wave signal and improves the accuracy of the diffraction wave migration velocity.

[0050] The embodiments of the present application provide a deep diffraction field velocity modeling method, as shown in Figure 1 The method mainly includes the following steps:

[0051] In step S110, diffraction wave separation data is obtained, and based on the edge diffraction model and the scatterer physical model, a common diffraction point multi-aperture angle gather is constructed through angle migration to capture the diffraction response within the multi-aperture.

[0052] In an implementation, seismic data directly used for migration can be obtained, and a plane wave destruction filter is used on the seismic data to remove the reflection component to obtain the diffraction wave separation data.

[0053] When constructing the common diffraction point multi-aperture angle gather through angle migration, an angle domain migration method can be used, the position of the imaging ray perpendicular to the ground surface is used, the diffraction energy within the first Fresnel aperture is selected based on the scatterer model, in addition, based on the dip field of the underground reflection interface, the position of the ray exiting the ground surface is determined through ray tracing, and the main energy band within the second aperture is obtained. Figure 2 A common diffraction point multi-aperture angle gather construction schematic diagram is shown, wherein (a) is a three-dimensional wave front surface generated by single shot excitation, (b) is a multi-aperture diffraction energy selection method based on edge diffraction and scatterer model, (c) is the vertex energy and main energy band of the diffraction wave response, and (d) is the wave field characteristics of the common diffraction point multi-aperture angle gather.

[0054] The above common diffraction point multi-aperture angle gather is a storage form similar to a matrix, the row represents the depth position of the underground space, and the column represents the seismic amplitude value corresponding to each angle.

[0055] For the same imaging point, all signals based on angle migration and satisfying the diffraction wave kinematic imaging condition are projected into the dip angle-scattering angle-imaging point depth imaging space, the signals corresponding to different scattering angles are superimposed according to the scattering angle direction, and the dip angle is obtained, that is, the common diffraction point multi-aperture angle gather.

[0056] For each imaging point, the multi-aperture angle gather is the energy of the imaging point in the first dimension as the depth and the second dimension as the different migration dip angles.

[0057] In step S120, a correction relationship between the diffraction point dip angle and the migration velocity is established according to the common diffraction point multi-aperture angle gather.

[0058] Step S130, according to the correction relationship between the diffraction point dip angle and the migration velocity, for each common diffraction point multi-aperture angle gather, based on the hybrid weight of local similarity and difference boot-strap, the diffraction field velocity spectrum of each diffraction point is calculated.

[0059] In an embodiment, in the velocity field used for constructing the common diffraction point multi-aperture gather, a new time correction is calculated by using a series of different γ values for the constructed common diffraction point multi-aperture angle gather through the correction relationship between the diffraction point dip angle and the migration velocity, and the diffraction field velocity spectrum is obtained by applying the hybrid weight calculation of local similarity and difference boot-strap to the energy corresponding to the new correction.

[0060] The correction relationship between the diffraction point dip angle and the migration velocity can be represented by the following formula:

[0061]

[0062] Wherein, τ(θ) is used to represent the travel time correction formula of the diffraction response in the migration dip angle domain, θ is the diffraction point dip angle, γ = υ m / υ, v m is the migration velocity, v is the original velocity, ξ = (x m -x d ) / z d , x m is the migration imaging point, x d , z d is the actual diffraction point position, τ0 is the two-layer travel time under the vertical incidence.

[0063] Step S140, in the diffraction field velocity spectrum of each diffraction point, the diffraction wave velocity value of the focused signal is picked up through the man-machine interaction mode.

[0064] Step S150, the target diffraction field velocity model is constructed by interpolating the diffraction wave velocity value.

[0065] In an embodiment, the interpolation mode can include inverse distance weighting or Kriging, etc. For example, the interpolation function can be realized by the following interpolation function:

[0066]

[0067] Wherein, x, y are the coordinates to be interpolated, x1, y1, x2, y2 together constitute the four vertices of the coordinate region, Q is the velocity value corresponding to the four vertices, and the interpolation schematic diagram is shown in Figure 3 .

[0068] The finally constructed target diffraction field velocity model is a data matrix, wherein a row of the data matrix represents a depth, a column represents a lateral coordinate, and a value is a velocity value, and the data matrix can be displayed by software.

[0069] For the convenience of understanding, the following describes in detail the method for modeling the diffraction field velocity of the God of War provided in the embodiments of the present application.

[0070] In an optional embodiment, the diffraction wave separation data is acquired, and the seismic data directly used for migration can be acquired, and the reflection component is removed from the seismic data to obtain the diffraction wave separation data.

[0071] Specifically, the reflection component can be removed by performing reflection wave continuation non-stack transformation on the seismic data, and the reflection wave in the seismic data can be described by using a plane wave destruction filter:

[0072] D=S(I-C(p))

[0073] wherein D is the separated diffraction wave, S=[S1,S2,…S N ] T is the seismic data, I is a unit matrix, p=[p1,p2,…,p N-1 ] is an event slope, N is the number of traces of the seismic data, and C(p) is a plane wave destruction operator:

[0074]

[0075] C i,i+1 (p i ) represents a plane wave destruction filter for predicting the jth trace seismic data from the ith trace shot seismic data. The scalar form is:

[0076]

[0077] wherein Z t ,Z x represent Z transforms in the time direction and the space direction respectively.

[0078] In an optional embodiment, a common diffraction point multi-aperture angle gather is constructed by angle migration, comprising:

[0079] For any imaging point in the subsurface space, an angle gather data is generated by using angle migration, and a diffraction incident angle and a diffraction exit angle in the local diffraction point position are calculated by ray tracing:

[0080]

[0081] wherein α represents an included angle between an incident ray and a vertical axis, i.e., the diffraction incident angle; and β represents an included angle between an exit ray and the vertical axis, i.e., the diffraction exit angle.

[0082] The diffraction point dip angle is determined according to an included angle between an outgoing ray and a vertical line of a local reflection interface:

[0083]

[0084] wherein θ is the diffraction point dip angle.

[0085] In an optional embodiment, the multi-aperture in-diffraction response is captured, including:

[0086] Based on a three-dimensional angle domain migration framework, a first in-diffraction energy of a scatterer model is selected by an imaging ray, and a second in-diffraction main energy band is obtained by a ray beam controlled by a section dip angle field. In practical applications, an angle domain migration method can be used to select the first in-diffraction energy of the scatterer model based on the position of the imaging ray perpendicular to the outgoing ground surface, and then the position of the ray outgoing from the ground surface is determined based on the dip angle field of the underground reflection interface, so as to obtain the second in-diffraction main energy band.

[0087] In an optional embodiment, a hybrid weight of local similarity and differential boot-strap is determined by the following formula:

[0088]

[0089] wherein w hyb (j,k) is the hybrid weight, w sw is a weight function parameterized by a time-dependent parameter b(k); w νs is a weight function based on local similarity, κ[q(j,k),q r (k)] is the local similarity.

[0090] Figure 3 A specific deep diffraction field velocity modeling method is shown. The method constructs a common diffraction point multi-aperture angle gather with high superposition number by migration, generates a diffraction field velocity spectrum by using a migration velocity field and the multi-aperture angle gather, and establishes a diffraction field velocity model by interactively picking a focused velocity value of the velocity spectrum.

[0091] In summary, based on the edge diffraction and scatterer two physical models, the common diffraction point multi-aperture angle gather is constructed by following the Huygens principle, the super-high superposition number in-diffraction response energy can be captured, and the diffraction field velocity field modeling problem under the condition of low signal-to-noise ratio can be solved; the diffraction wave velocity spectrum is defined by the hybrid weight, the non-correlation signal interference effect can be eliminated, the focusing of the non-stationary signal diffraction velocity spectrum is improved, and the stability and accuracy of the calculation are enhanced.

[0092] The seismic diffraction response of unconventional reservoirs such as deep oil and gas and geothermal resources has a low signal-to-noise ratio, which poses a challenge to migration velocity modeling. To fully utilize the wide illumination propagation law of diffraction waves, this paper proposes a common diffraction point multi-aperture angular gather based on the Huygens principle. This common diffraction point multi-aperture angular gather has an ultra-high stacking number and can capture the diffraction energy within multiple apertures. By constructing a matching diffraction field velocity, it provides basic data for imaging deep complex media.

[0093] Based on the above method embodiment, the present application embodiment also provides a deep earth diffraction field velocity modeling device, see Figure 5 As shown, the device mainly includes the following parts:

[0094] The common diffraction point multi-aperture angular gather construction module 510 is used to obtain diffraction wave separation data. Based on the edge diffraction model and the scatterer physical model, the common diffraction point multi-aperture angular gather is constructed by angle offset to capture the diffraction response within the multi-aperture.

[0095] A correction relationship establishing module 520 is used to establish a correction relationship between the diffraction point inclination angle and the migration velocity based on the common diffraction point multi-aperture angle gather;

[0096] The calculation module 530 is used to calculate the diffraction field velocity spectrum of each diffraction point based on the correction relationship between the diffraction point inclination angle and the migration velocity, for each common diffraction point multi-aperture angle gather, based on the mixed weight of local similarity and differential bootstrap;

[0097] A picking module 540 is used to pick up the diffraction wave velocity value of the focus signal from the diffraction field velocity spectrum of each diffraction point through human-computer interaction;

[0098] The modeling module 550 is used to construct a target diffraction field velocity model by performing interpolation processing on the diffraction wave velocity values.

[0099] In a feasible implementation manner, the common diffraction point multi-aperture angle gather construction module 510 is further configured to:

[0100] Seismic data directly used for migration is acquired, and the reflection component is removed from the seismic data to obtain diffraction wave separation data.

[0101] In a feasible implementation manner, the common diffraction point multi-aperture angle gather construction module 510 is further configured to:

[0102] For any imaging point in the underground space, angle gather data is generated using angle offset, and the local diffraction incident angle and diffraction exit angle at the diffraction point are calculated by ray tracing:

[0103]

[0104] Among them, α represents the angle between the incident ray and the vertical axis, which is the diffraction incident angle; β represents the angle between the outgoing ray and the vertical axis, which is the diffraction outgoing angle;

[0105] The diffraction point inclination is determined by the angle between the outgoing ray and the perpendicular line of the local reflection interface:

[0106]

[0107] Where θ is the inclination angle of the diffraction point.

[0108] In a feasible implementation manner, the common diffraction point multi-aperture angle gather construction module 510 is further configured to:

[0109] Based on the three-dimensional angle domain migration framework, the diffraction energy in the first aperture of the scatterer model is selected by imaging rays, and the cross-sectional tilt field is used to control the ray beam to obtain the diffraction main energy band in the second aperture.

[0110] In a feasible implementation, the correction relationship between the diffraction point inclination angle and the migration velocity includes:

[0111]

[0112] Where τ(θ) is used to characterize the travel time correction formula of the diffraction response in the offset tilt domain, θ is the diffraction point tilt, and γ = υ m / υ,v m is the offset velocity, v is the original velocity, ξ=(x m -x d ) / z d , x m is the offset imaging point, x d ,z d is the actual diffraction point position, and τ0 is the double-layer travel time at vertical incidence.

[0113] In one feasible implementation, the mixed weight of local similarity and differential bootstrap is determined by the following formula:

[0114]

[0115] Among them, w hyb (j,k) is the mixing weight, w sw is a weight function parameterized by a time-dependent parameter b(k); w νs is a weight function based on local similarity, κ[q(j,k),q r (k)] is the local similarity.

[0116] The implementation principle and technical effects of the deep earth diffraction field velocity modeling device provided in the embodiments of the present application are the same as those of the aforementioned method embodiments. For the sake of brief description, any matters not mentioned in the embodiments of the deep earth diffraction field velocity modeling device may be referred to the corresponding contents in the aforementioned deep earth diffraction field velocity modeling method embodiments.

[0117] The present application also provides an electronic device, such as Figure 6 , which is a schematic structural diagram of the electronic device, wherein the electronic device 100 includes a processor 61 and a memory 60, wherein the memory 60 stores computer-executable instructions that can be executed by the processor 61, and the processor 61 executes the computer-executable instructions to implement any of the above-mentioned deep earth diffraction field velocity modeling methods.

[0118] exist Figure 6 In the illustrated embodiment, the electronic device further includes a bus 62 and a communication interface 63 , wherein the processor 61 , the communication interface 63 and the memory 60 are connected via the bus 62 .

[0119] Among them, the memory 60 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 63 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 62 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 62 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0120] The processor 61 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor 61 or by software instructions. The above processor 61 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor 61 reads the information in the memory and completes the steps of the deep earth diffraction field velocity modeling method of the aforementioned embodiment in combination with its hardware.

[0121] An embodiment of the present application further provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the above-mentioned deep earth diffraction field velocity modeling method. For specific implementation, please refer to the above-mentioned method embodiment and will not be repeated here.

[0122] The computer program product of the deep earth diffraction field velocity modeling method, device, electronic device, and storage medium provided in the embodiments of the present application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the previous method embodiments. For specific implementation, please refer to the method embodiments and will not be repeated here.

[0123] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0124] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for modeling deep earth diffraction velocity, characterized in that: The method comprises: Obtain diffraction wave separation data, and construct multi-aperture angular gathers of common diffraction points through angle offset based on the edge diffraction model and scatterer physical model to capture the diffraction response within the multi-aperture; Establishing a correction relationship between the diffraction point inclination angle and the migration velocity based on the common diffraction point multi-aperture angle gather; According to the correction relationship between the diffraction point inclination angle and the migration velocity, for each common diffraction point multi-aperture angle gather, the diffraction field velocity spectrum of each diffraction point is calculated based on the mixed weight of local similarity and differential boot-strap; In the diffraction field velocity spectrum of each diffraction point, the diffraction wave velocity value of the focused signal is picked up through human-computer interaction; Constructing a target diffraction field velocity model by interpolating the diffraction wave velocity values; Constructing common diffraction point multi-aperture angular gathers through angle migration, including: For any imaging point in the underground space, angle gather data is generated using angle offset, and the local diffraction incident angle and diffraction exit angle at the diffraction point are calculated by ray tracing: in, α It represents the angle between the incident ray and the vertical axis, which is the diffraction incident angle; β It represents the angle between the outgoing ray and the vertical axis, which is the diffraction outgoing angle; The diffraction point inclination is determined by the angle between the outgoing ray and the perpendicular line of the local reflection interface: in, θ is the diffraction point inclination angle.

2. The deep earth diffraction field velocity modeling method according to claim 1, wherein: Obtain diffraction wave separation data, including: Seismic data directly used for migration is acquired, and reflection components are removed from the seismic data to obtain diffraction wave separation data.

3. The deep earth diffraction field velocity modeling method according to claim 1, wherein: Captures diffraction responses within multiple apertures, including: Based on the three-dimensional angle domain migration framework, the diffraction energy in the first aperture of the scatterer model is selected by imaging rays, and the cross-sectional tilt field is used to control the ray beam to obtain the diffraction main energy band in the second aperture.

4. The deep earth diffraction field velocity modeling method according to claim 1, wherein: The correction relationship between the diffraction point inclination angle and the migration velocity includes: in, The travel time correction formula used to characterize the diffraction response in the offset tilt domain is: θ is the diffraction point inclination angle, , v m is the offset velocity, v is the original speed, , is the offset imaging point, is the actual diffraction point position, for double-layer travel at normal incidence.

5. The deep earth diffraction field velocity modeling method according to claim 1, wherein: The mixed weight of the local similarity and differential boot-strap is determined by the following formula: in, w hyb (j,k) is the mixing weight, A time-related parameter Parameterized weight function; is based on the local similarity weight function, is local similarity; is the amplitude, , , is the offset, It indicates the channel number and the time sampling point number.

6. A deep earth diffraction field velocity modeling device, characterized in that: For implementing the method according to claim 1, the apparatus comprises: The module for constructing multi-aperture angular gathers at common diffraction points is used to obtain diffraction wave separation data. Based on the edge diffraction model and the scatterer physical model, multi-aperture angular gathers at common diffraction points are constructed through angle offset to capture the diffraction response within multiple apertures. a correction relationship establishing module, configured to establish a correction relationship between the diffraction point inclination angle and the migration velocity based on the common diffraction point multi-aperture angle gather; A calculation module is used to calculate the diffraction field velocity spectrum of each diffraction point based on the correction relationship between the diffraction point inclination angle and the migration velocity, for each common diffraction point multi-aperture angle gather, based on the mixed weight of local similarity and differential boot-strap; A picking module is used to pick up the diffraction wave velocity value of the focused signal from the diffraction field velocity spectrum of each diffraction point through human-computer interaction; The modeling module is used to construct a target diffraction field velocity model by interpolating the diffraction wave velocity values.

7. The deep earth diffraction field velocity modeling device according to claim 6, characterized in that: The common diffraction point multi-aperture angle gather construction module is further used to: Seismic data directly used for migration is acquired, and reflection components are removed from the seismic data to obtain diffraction wave separation data.

8. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the deep earth diffraction field velocity modeling method according to any one of claims 1 to 5.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by the processor, the computer-executable instructions prompt the processor to implement the deep earth diffraction field velocity modeling method according to any one of claims 1 to 5.

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