CN116165700A - Diffraction wave imaging method, electronic equipment and medium - Google Patents

Abstract

The application discloses a diffraction wave imaging method, electronic equipment and a medium. The method includes: Step 1: For a receiving line data recorded by a single shot, calculate the imaging range of the receiving line, and perform the following steps for each imaging point in the imaging range: Step 101: Extract along the diffraction hyperbola for the imaging point The amplitude on each recording track on the receiving line; step 102: calculate the weight coefficient of the suppressed strong energy band corresponding to the imaging point; step 103: perform Kirchhoff time migration processing according to the weight coefficient; step 2: sequentially perform all single shot All recorded receiving line data are processed, and the migration results falling on the same imaging point are accumulated to obtain the final diffraction wave imaging result. The present invention locates the center position of the strong energy band by means of energy scanning, and determines the range of the strong energy band based on the principle of the Fresnel zone, and superimposes the remaining energy outside the strong energy band to suppress the reflected wave imaging, highlighting Diffraction wave imaging.

Description

Diffraction wave imaging method, electronic equipment and medium

technical field

The invention relates to the field of geophysical exploration, and more specifically, to a diffraction wave imaging method, electronic equipment and a medium.

Background technique

In exploration areas where carbonate fractured-vuggy reservoirs are the main target, it is necessary to finely describe geological targets such as faults, fractures, and cavities in the underground. The seismic response of these small-scale heterogeneous bodies is mainly represented by diffraction waves. Since the energy of diffraction waves is one to two orders of magnitude lower than that of reflected waves, the small-scale anomalies formed by diffraction waves in conventional imaging results The body is easily covered by a strong energy reflector. In order to avoid the interference of strong reflected energy and improve the ability to identify small-scale anomalies, it is necessary to separate the reflected wave from the diffracted wave and only image the diffracted wave. Diffraction wave imaging technology based on inverse-stable filtering uses an inverse-stable filter to separate the diffracted wave from the reflected wave under the framework of Kirchhoff migration. This technique needs to complete a conventional migration imaging calculation first, and then Estimate the reflection dip angle of each imaging point underground, and finally use the dip angle information to construct an anti-phase stabilization filter and perform a migration calculation. The calculation process of this technology is relatively cumbersome. When the underground structure is complex or the signal-to-noise ratio of the data is low, the underground reflection dip cannot be accurately calculated, and the imaging accuracy of diffracted waves is poor.

Therefore, it is necessary to develop a diffraction wave imaging method, electronic equipment and medium.

The information disclosed in the background of the present invention is only intended to deepen the understanding of the general background of the present invention, and should not be regarded as an acknowledgment or any form of suggestion that the information constitutes the prior art known to those skilled in the art.

Contents of the invention

The present invention proposes a diffracted wave imaging method, electronic equipment and medium, which can locate the center position of the strong energy band through energy scanning, and determine the range of the strong energy band according to the principle of the Fresnel zone. The superposition of the remaining energy outside the strong energy band can suppress the reflected wave imaging and highlight the diffracted wave imaging.

In a first aspect, an embodiment of the present disclosure provides a diffraction wave imaging method, including:

Step 1: For a receiving line data recorded by a single shot, calculate the imaging range of the receiving line according to the offset aperture, and perform the following steps for each imaging point within the imaging range:

Step 101: Extracting the amplitude of each recording track on the receiving line along the diffraction hyperbola for the imaging point;

Step 102: Calculate the weight coefficient of the suppressed strong energy band corresponding to the imaging point;

Step 103: performing Kirchhoff time offset processing according to the weight coefficient;

Step 2: Process all receiving line data recorded by all single shots in sequence, and accumulate the migration results falling on the same imaging point to obtain the final diffraction wave imaging result.

Preferably, determining the weight coefficient of the suppressed strong energy band corresponding to the receiving line includes:

Determine the center position and range of the strong energy band;

Determine the weight coefficient for suppressing the strong energy band according to the range of the strong energy band.

Preferably, determining the central position of the strong energy band includes:

Define a sliding window, perform sliding summation on the amplitudes extracted by the diffraction hyperbola, and obtain the sum W(j) of the amplitude values;

Calculate the number K(j) of amplitude values with the same polarity in each sliding window;

Determine the window in which the absolute value of W(j) is the largest and K(j) is greater than a preset value, and take the center sample point of the window as the center position of the strong energy band.

Preferably, the amplitude extracted by the diffraction hyperbola is slidingly summed by formula (1):

Among them, W(j) is the sum of N+1 amplitude values in the sliding window, A(i) is the amplitude value extracted from the diffraction hyperbola, i is the number of the amplitude sample point, and j is the number of the center sample point of the sliding window, j=N/2+1, N/2+2,...,NR-N/2, where NR is the total number of all amplitude values extracted by the diffraction hyperbola.

Preferably, the number of sample points with the same amplitude polarity in the sliding window is calculated by formula (2):

Among them, K(j) is the number of sample points with the same amplitude polarity in the sliding window, A(i) is the amplitude value extracted by the diffraction hyperbola, i is the number of the amplitude sample point, and j is the number of sample points in the center of the sliding window Serial number, j=N/2+1, N/2+2,...,NR-N/2, where NR is the total number of all amplitude values extracted by the diffraction hyperbola.

Preferably, the range of the strong energy band is:

|τ- _τd |≤T/4 (3)

Among them, τ _d is the travel time corresponding to the central position of the strong energy band, τ _d =t _s +t _rmax , r max is the receiver point position corresponding to the central position of the strong energy band, and τ is all the amplitudes extracted from the diffraction hyperbola corresponding to τ=t _s +t _r , t _s is the travel time from the shot point to the imaging point, t _r is the travel time from the receiver point to the imaging point, t _rmax is the travel time from the receiver point r max to the imaging point When traveling, T is the period of the seismic wavelet where the sampling point u(r max,τ _d ) is located in the record track of the receiver point r max.

Preferably, the weight coefficient is:

Among them, e(m, r) is the weight coefficient, and U(r max) is the spatial neighborhood centered on the detection point position r max.

Preferably, performing Kirchhoff time migration imaging according to the weight coefficient is:

Among them, V(m) is the migration result of imaging point m, e(m,r) is the weight coefficient, m is the imaging point, r is the detection point, ω(m,r) is used to compensate the energy caused by spherical diffusion Loss weight coefficient, u(r,t) is the seismic wave field amplitude.

As a specific implementation of the embodiments of the present disclosure,

In a second aspect, an embodiment of the present disclosure further provides an electronic device, and the electronic device includes:

a memory storing executable instructions;

A processor, the processor executes the executable instructions in the memory to implement the diffraction wave imaging method.

In a third aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and the computer program implements the diffraction wave imaging method when executed by a processor.

The method and apparatus of the present invention have other features and advantages which will be apparent from the accompanying drawings and the following detailed description, or which will be described in the accompanying drawings and the following description The detailed description is set forth in the detailed description, and together these drawings and detailed description serve to explain certain principles of the invention.

Description of drawings

The above and other objects, features and advantages of the present invention will become more apparent by describing the exemplary embodiments of the present invention in more detail with reference to the accompanying drawings, wherein, in the exemplary embodiments of the present invention, the same reference numerals generally represent same parts.

Fig. 1 shows a schematic diagram of amplitude values extracted from a diffraction curve when the imaging point is a point on a reflection interface according to an embodiment of the present invention.

Fig. 2 shows a schematic diagram of amplitude values extracted from a diffraction curve when the imaging point is a diffracting body according to an embodiment of the present invention.

Fig. 3 shows a flow chart of the steps of the diffraction wave imaging method according to one embodiment of the present invention.

Fig. 4 shows a schematic diagram of a SIGBEE2A model according to an embodiment of the present invention.

FIG. 5 shows a schematic diagram of a conventional Kirchhoff migration imaging section according to FIG. 4 .

FIG. 6 shows a schematic diagram of imaging sections processed according to the method of FIG. 4 .

FIG. 7 shows a schematic diagram of a conventional Kirchhoff migration imaging section according to an embodiment of the present invention.

FIG. 8 shows a schematic diagram of imaging sections processed by the method according to an embodiment of the present invention.

Detailed ways

Preferred embodiments of the present invention will be described in more detail below. Although preferred embodiments of the present invention are described below, it should be understood that the present invention can be embodied in various forms and should not be limited by the embodiments set forth herein.

When Kirchhoff migration performs imaging on a point, a diffraction curve (referred to as a diffraction hyperbola) is established by using the migration velocity, and then the amplitude is extracted along the diffraction curve for weighted superposition imaging. Formula (6) is the basic theoretical formula for Kirchhoff time migration imaging in the shot domain:

Among them, V(m) is the migration result of the imaging point m, r represents the position of the detection point, ω(m,r) represents the weight coefficient used to compensate for the energy loss caused by spherical diffusion, u(r,t) represents the detection point The record at r, t _s +t _r is the travel time of seismic wave propagation, t _s is the travel time from the shot point to the imaging point, t _r is the travel time from the receiver point to the imaging point, and the δ symbol represents Dirac δ function.

If the subsurface imaging point is a reflection point, there will be a strong energy band in the amplitude extracted by the diffraction hyperbola. The "reflected wave imaging" is mainly derived from the contribution of this "strong energy band", rather than all the amplitude values extracted by the diffraction hyperbola. However, if the point is a diffraction point, the amplitude energy extracted by the diffraction hyperbola is relatively uniform. The energy of diffraction wave imaging comes from all the amplitude values extracted by the diffraction hyperbola.

When performing Kirchhoff migration, if the diffraction hyperbola is located to extract the strong energy bands in all amplitudes and suppressed, the reflection imaging can be well suppressed and the diffraction imaging can be highlighted. This is because the contribution of reflected wave imaging mainly comes from the contribution of strong energy bands, and the removal of strong energy bands will greatly suppress reflected wave imaging. The contribution of the diffraction wave imaging comes from all the amplitudes extracted by the diffraction hyperbola, and the energy is relatively uniform, and the removal of the strong energy band has little effect on it.

The invention provides a diffraction wave imaging method, comprising:

Step 1: For a receiving line data recorded by a single shot, calculate the imaging range of the receiving line according to the offset aperture, and perform the following steps for each imaging point within the imaging range:

Step 101: Extracting the amplitude of each recording track on the receiving line along the diffraction hyperbola for the imaging point;

Step 102: Calculate the weight coefficient of the suppressed strong energy band corresponding to the imaging point;

Step 103: performing Kirchhoff time offset processing according to the weight coefficient;

Step 2: Process all receiving line data recorded by all single shots in sequence, and accumulate the migration results falling on the same imaging point to obtain the final diffraction wave imaging result.

In an example, determining the weight coefficient of the suppressing strong energy band corresponding to the receiving line includes:

Determine the center position and range of the strong energy band;

According to the range of the strong energy band, determine the weight coefficient for suppressing the strong energy band.

In one example, determining the center location of the band of intense energy includes:

Define a sliding window, perform sliding summation on the amplitudes extracted by the diffraction hyperbola, and obtain the sum W(j) of the amplitude values;

Calculate the number K(j) of amplitude values with the same polarity in each sliding window;

Determine the window in which the absolute value of W(j) is the largest and K(j) is greater than a preset value, and take the center sample point of the window as the center position of the strong energy band.

In one example, the amplitudes extracted by the diffraction hyperbola are slidingly summed by equation (1):

Among them, W(j) is the sum of N+1 amplitude values in the sliding window, A(i) is the amplitude value extracted from the diffraction hyperbola, i is the number of the amplitude sample point, and j is the number of the center sample point of the sliding window, j=N/2+1, N/2+2,...,NR-N/2, where NR is the total number of all amplitude values extracted by the diffraction hyperbola.

In one example, the number of samples with the same amplitude and polarity in the sliding window is calculated by formula (2):

Among them, K(j) is the number of sample points with the same amplitude polarity in the sliding window, A(i) is the amplitude value extracted by the diffraction hyperbola, i is the number of the amplitude sample point, and j is the number of sample points in the center of the sliding window Serial number, j=N/2+1, N/2+2,...,NR-N/2, where NR is the total number of all amplitude values extracted by the diffraction hyperbola.

In one example, the strong energy bands range from:

|τ- _τd |≤T/4 (3)

Among them, τ _d is the travel time corresponding to the central position of the strong energy band, τ _d =t _s +t _rmax , r max is the receiver point position corresponding to the central position of the strong energy band, and τ is all the amplitudes extracted from the diffraction hyperbola corresponding to τ=t _s +t _r , t _s is the travel time from the shot point to the imaging point, t _r is the travel time from the receiver point to the imaging point, t _rmax is the travel time from the receiver point r max to the imaging point When traveling, T is the period of the seismic wavelet where the sampling point u(r max,τ _d ) is located in the record track of the receiver point r max.

In one example, the weight coefficients are:

Among them, e(m, r) is the weight coefficient, and U(r max) is the spatial neighborhood centered on the detection point position r max.

In one example, Kirchhoff time-migrated imaging according to weight coefficients is:

Among them, V(m) is the migration result of imaging point m, e(m,r) is the weight coefficient, m is the imaging point, r is the detection point, ω(m,r) is used to compensate the energy caused by spherical diffusion Loss weight coefficient, u(r,t) is the seismic wave field amplitude.

Specifically, on the preprocessed single-shot seismic records, the data of a receiving line recorded by the single shot is processed, and a certain imaging point in the ground is subjected to Kirchhoff migration imaging, and the receiving line data is obtained by extracting along the diffraction hyperbola. The amplitude on each trace on the line. The specific implementation can refer to the basic formula of Kirchhoff time migration in the conventional shot field, that is, formula (6). The weighting process of compensation does not perform superposition calculation.

Fig. 1 shows a schematic diagram of amplitude values extracted from a diffraction curve when the imaging point is a point on a reflection interface according to an embodiment of the present invention.

Determine the extent of distribution of strong energy bands in the extracted amplitude data. If the subsurface imaging point is a point on the reflection interface, there will be a strong energy band in the extracted amplitude data, as shown in Figure 1, the energy of reflected wave imaging mainly comes from this strong energy band, rather than diffraction hyperbolic extraction All amplitude values of .

Fig. 2 shows a schematic diagram of amplitude values extracted from a diffraction curve when the imaging point is a diffracting body according to an embodiment of the present invention.

If the underground imaging point is a diffraction body similar to a small-scale cave, the energy of the extracted amplitude data is relatively uniform. As shown in Figure 2, the energy of the diffraction wave imaging comes from all the amplitude values extracted by the diffraction hyperbola.

From the above analysis, it can be deduced that when performing Kirchhoff migration, if the strong energy band in the extracted data is determined and suppressed, reflection imaging can be well suppressed and diffraction imaging can be highlighted. This is because the contribution of reflected wave imaging mainly comes from the contribution of strong energy bands, and the removal of strong energy bands will greatly suppress reflected wave imaging. The contribution of the diffraction wave imaging comes from all the amplitudes extracted by the diffraction hyperbola, and the energy is relatively uniform, and the removal of the strong energy band has little effect on it. To this end, it is necessary to determine the distribution range of the strong energy band. Because the strong energy band has two typical characteristics, one is strong energy, and the other is the same amplitude and polarity. Accordingly, the specific steps for determining a strong energy band are as follows:

Locate the center of the strong energy band. Define a sliding window with a width of N, perform sliding summation on the amplitude data extracted along the diffraction hyperbola by formula (1), and calculate the number of amplitude values with the same polarity in each sliding window by formula (2) .

Determine the window in which the absolute value of W(j) is the largest and K(j) is greater than a preset value, take the center sample point of the window as the center position of the strong energy band, and then determine the detection point corresponding to the center position of the strong energy band position r max, and then obtain the travel time τ _d =t _s +t _rmax corresponding to the sample point. In the above actual calculation, the parameter N is obtained through trial calculation.

Determine the range of strong energy bands. The generation of strong energy bands is mainly related to the Fresnel bands in the data domain. In the extracted amplitude data, in the spatial neighborhood centered on the detection point position r max , a set of amplitude values satisfying formula (3) during travel is The range of strong energy bands.

Diffraction wave separation imaging. By removing the determined strong energy bands and superimposing the remaining energy, the reflected wave imaging can be suppressed and the diffracted wave imaging can be highlighted. For this reason, the weight coefficient for cutting off the strong energy band is defined as formula (4), and the basic theoretical formula for diffraction wave separation imaging is formula (5).

The imaging range of the receiving line data is calculated according to the offset aperture, and the calculation of the above steps is completed for all imaging points within the imaging range, and the offset processing of one receiving line data is completed so far. Then, all the receiving line data recorded by all single shots are processed sequentially, and the migration results falling on the same imaging point are accumulated, and finally the diffraction wave imaging result is obtained.

The present invention also provides an electronic device, which includes: a memory storing executable instructions; and a processor running the executable instructions in the memory to realize the above-mentioned diffraction wave imaging method.

The present invention also provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the above-mentioned diffraction wave imaging method is realized.

In order to facilitate the understanding of the solutions and effects of the embodiments of the present invention, three specific application examples are given below. Those skilled in the art will understand that this example is only for the purpose of facilitating the understanding of the present invention, and any specific details thereof are not intended to limit the present invention in any way.

Example 1

Fig. 3 shows a flow chart of the steps of the diffraction wave imaging method according to one embodiment of the present invention.

As shown in Figure 3, the diffraction wave imaging method includes: Step 1, for a receiving line data recorded by a single shot, calculate the imaging range of the receiving line according to the offset aperture, and perform the following for each imaging point in the imaging range Step: step 101, extract the amplitude on each recording track on the receiving line for the imaging point along the diffraction hyperbola; step 102, calculate the weight coefficient of the suppressed strong energy band corresponding to the imaging point; Time migration processing; step 2, sequentially process all receiving line data recorded by all single shots, and accumulate the migration results falling on the same imaging point to obtain the final diffraction wave imaging result.

Fig. 4 shows a schematic diagram of the SIGBEE2A model according to an embodiment of the present invention, and the arrows indicate the tested target diffracters.

FIG. 5 shows a schematic diagram of a conventional Kirchhoff migration imaging section according to FIG. 4 .

FIG. 6 shows a schematic diagram of imaging sections processed according to the method of FIG. 4 .

This method is used to process part of the shot records of the SIGBEE2A model shown in Figure 4, and the method is tested, and the processing results are shown in Figures 5 and 6. By comparison, it can be seen that the reflected wave in Figure 6 is suppressed, and the diffracting body that was previously covered by the reflected wave and cannot be identified becomes clear and prominent.

FIG. 7 shows a schematic diagram of a conventional Kirchhoff migration imaging section according to an embodiment of the present invention.

FIG. 8 shows a schematic diagram of imaging sections processed by the method according to an embodiment of the present invention.

Apply this method to the actual data for trial calculation, and compare it with the conventional migration results, as shown in Figures 7 and 8, it can be seen that in the processing results of the present invention, the reflected waves are well suppressed, while the " Beaded" reflections are highlighted.

Example 2

The present disclosure provides an electronic device comprising: a memory storing executable instructions; and a processor running the executable instructions in the memory to implement the above diffraction wave imaging method.

An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

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

The processor may be a central processing unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is configured to execute the computer readable instructions stored in the memory.

Those skilled in the art should understand that in order to solve the technical problem of how to obtain a good user experience effect, this embodiment may also include known structures such as communication buses and interfaces, and these known structures should also be included in the protection scope of the present disclosure within.

For detailed descriptions of this embodiment, reference may be made to corresponding descriptions in the preceding embodiments, and details are not repeated here.

Example 3

An embodiment of the present disclosure provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and the computer program implements the diffraction wave imaging method when executed by a processor.

A computer-readable storage medium according to an embodiment of the present disclosure has non-transitory computer-readable instructions stored thereon. When the non-transitory computer-readable instructions are executed by the processor, all or part of the steps of the aforementioned methods in the various embodiments of the present disclosure are executed.

The above-mentioned computer-readable storage media include but are not limited to: optical storage media (such as: CD-ROM and DVD), magneto-optical storage media (such as: MO), magnetic storage media (such as: magnetic tape or mobile hard disk), with built-in Media that rewrites nonvolatile memory (eg: memory card) and media with built-in ROM (eg: ROM cartridge).

Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.

Having described various embodiments of the present invention, the foregoing description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and alterations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Claims (10)

1. A diffraction wave imaging method, characterized in that, comprising: Step 1: For a receiving line data recorded by a single shot, calculate the imaging range of the receiving line according to the offset aperture, and perform the following steps for each imaging point within the imaging range: Step 101: Extracting the amplitude of each recording track on the receiving line along the diffraction hyperbola for the imaging point; Step 102: Calculate the weight coefficient of the suppressed strong energy band corresponding to the imaging point; Step 103: performing Kirchhoff time offset processing according to the weight coefficient; Step 2: Process all receiving line data recorded by all single shots in sequence, and accumulate the migration results falling on the same imaging point to obtain the final diffraction wave imaging result. 2. The diffraction wave imaging method according to claim 1, wherein determining the weight coefficient of the corresponding suppressed strong energy band of the receiving line comprises: Determine the center position and range of the strong energy band; Determine the weight coefficient for suppressing the strong energy band according to the range of the strong energy band. 3. The diffraction wave imaging method according to claim 2, wherein determining the center position of the strong energy band comprises: Define a sliding window, perform sliding summation on the amplitudes extracted by the diffraction hyperbola, and obtain the sum W(j) of the amplitude values; Calculate the number K(j) of amplitude values with the same polarity in each sliding window; Determine the window in which the absolute value of W(j) is the largest and K(j) is greater than a preset value, and take the center sample point of the window as the center position of the strong energy band. 4. diffraction wave imaging method according to claim 3, wherein, carry out sliding summation to the amplitude that diffraction hyperbola extracts by formula (1):

Among them, W(j) is the sum of N+1 amplitude values in the sliding window, A(i) is the amplitude value extracted from the diffraction hyperbola, i is the number of the amplitude sample point, and j is the number of the center sample point of the sliding window, j=N/2+1, N/2+2,...,NR-N/2, where NR is the total number of all amplitude values extracted by the diffraction hyperbola. 5. diffracted wave imaging method according to claim 3, wherein, calculate the number of the same sample point of amplitude polarity in the sliding window by formula (2):

Among them, K(j) is the number of sample points with the same amplitude polarity in the sliding window, A(i) is the amplitude value extracted by the diffraction hyperbola, i is the number of the amplitude sample point, and j is the number of sample points in the center of the sliding window Serial number, j=N/2+1, N/2+2,...,NR-N/2, where NR is the total number of all amplitude values extracted by the diffraction hyperbola. 6. diffracted wave imaging method according to claim 2, wherein, the scope of described strong energy band is: |τ- _τd |≤T/4 (3) Among them, τ _d is the travel time corresponding to the central position of the strong energy band, τ _d =t _s +t _rmax , rmax is the detection point position corresponding to the central position of the strong energy band, and τ is the time corresponding to all the amplitudes extracted by the diffraction hyperbola Travel time, τ=t _s +t _r , t _s is the travel time from the shot point to the imaging point, t _r is the travel time from the receiver point to the imaging point, t _rmax is the travel time from the receiver point rmax to the imaging point , T is the period of the seismic wavelet where the sampling point u(rmax,τ _d ) is located in the trace of the receiver point rmax. 7. diffracted wave imaging method according to claim 1, wherein, described weight coefficient is:

Among them, e(m, r) is the weight coefficient, and U(rmax) is the spatial neighborhood centered on the detection point position rmax. 8. The diffraction wave imaging method according to claim 1, wherein performing Kirchhoff time migration imaging according to the weight coefficient is:

Among them, V(m) is the migration result of imaging point m, e(m,r) is the weight coefficient, m is the imaging point, r is the detection point, ω(m,r) is used to compensate the energy caused by spherical diffusion Loss weight coefficient, u(r,t) is the seismic wave field amplitude. 9. An electronic device, characterized in that the electronic device comprises: a memory storing executable instructions; A processor, the processor runs the executable instructions in the memory to implement the diffraction wave imaging method according to any one of claims 1-8. 10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the diffraction wave imaging according to any one of claims 1-8 is realized method.

Images