An imaging method, apparatus, device, medium and product of seismic wave

Abstract

The application discloses an imaging method, device, equipment, medium and product of seismic waves. The method comprises the following steps: acquiring seismic data of a region to be imaged; performing amplitude compensation and Laplace filtering on an original reverse-time migration result to obtain a first target result; calculating a three-dimensional reflection coefficient of an original FWI velocity model and performing dip filtering to obtain a second target result; calculating a phase shift operator and an amplitude weighting coefficient according to the target results, and performing weighted processing on the target results to obtain a target imaging result corresponding to the region to be imaged. The original reverse-time migration result and the FWI calculation result are optimized and then weighted and superimposed, the energy of low wave numbers and high wave numbers in the seismic waves is enhanced, the frequency band range of conventional migration is expanded, the imaging result is more stereoscopic, the boundary line and the interface horizon change can be displayed, the full-bandwidth seismic data is mapped into a high-resolution seismic profile in the depth domain in the time domain, and the quality of the seismic wave imaging is improved.

Description

Technical Field

[0001] This invention relates to the field of earthquake data processing technology, and in particular to an imaging method, apparatus, device, medium, and product for seismic waves. Background Technology

[0002] Seismic wave imaging converts seismic data into a visual representation of subsurface structures. High-resolution seismic profile imaging is crucial for exploration and production, as it can not only avoid potential risks during drilling but also accurately identify potential reservoir locations, thereby improving the efficiency and safety of resource development.

[0003] In existing technologies, with the increasing complexity of geological structures, imaging algorithms based on ray and wave equations, due to their reliance on velocity models and lack of correction during migration, are prone to phase and frequency differences, thus reducing the quality of seismic wave imaging. Wave propagation attenuation, velocity errors, illumination compensation, signal differences between shot and receiver points, and limited data space sampling rates also reduce imaging resolution. Full Waveform Inversion (FWI), as a data-driven technique, may encounter inconsistencies or mismatches in various stages of the imaging process for highly complex terrains, making it difficult to provide high-resolution profiles in the highest frequency bands and further degrading the quality of seismic wave imaging. Summary of the Invention

[0004] This invention provides a method, apparatus, device, medium, and product for imaging seismic waves to solve the problems of low wavenumber resolution, low high beam resolution, and low imaging quality of seismic waves in seismic data.

[0005] According to one aspect of the present invention, a method for imaging seismic waves is provided, comprising:

[0006] Acquire seismic data for the region to be imaged; the seismic data for the region to be imaged includes the original full-waveform inversion FWI velocity model and the original reverse time migration results;

[0007] The original reverse time migration result is subjected to amplitude compensation and Laplace filtering to obtain the first target result;

[0008] For the original FWI velocity model, a three-dimensional reflection coefficient operator is calculated, and tilt filtering is performed using the three-dimensional reflection coefficient operator to obtain the second target result;

[0009] Based on the results of the first and second objectives, the phase shift operator and amplitude weighting coefficients are calculated.

[0010] The results for the first target and the second target are weighted using amplitude weighting coefficients and phase shift operators to obtain the target imaging result corresponding to the region to be imaged.

[0011] According to another aspect of the present invention, a seismic wave imaging apparatus is also provided, comprising:

[0012] The data acquisition module is used to acquire seismic data of the area to be imaged; the seismic data of the area to be imaged includes the original full waveform inversion FWI velocity model and the original reverse time migration results.

[0013] The first result acquisition module is used to perform amplitude compensation and Laplace filtering on the original reverse time offset result to obtain the first target result;

[0014] The second result acquisition module is used to calculate the three-dimensional reflection coefficient operator for the original FWI velocity model, and to perform tilt filtering using the three-dimensional reflection coefficient operator to obtain the second target result;

[0015] The parameter calculation module is used to calculate the phase shift operator and amplitude weighting coefficient based on the first target result and the second target result;

[0016] The target imaging acquisition module is used to perform weighted processing on the first target result and the second target result according to the amplitude weighting coefficient and the phase shift operator to obtain the target imaging result corresponding to the area to be imaged.

[0017] According to another aspect of the present invention, an electronic device is also provided, the electronic device comprising:

[0018] At least one processor; and

[0019] A memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the seismic wave imaging method according to any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the seismic wave imaging method according to any embodiment of the present invention.

[0022] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the method as described in any embodiment of the present invention.

[0023] The technical solution of this invention involves acquiring seismic data of the area to be imaged; performing amplitude compensation and Laplace filtering on the original reverse-time migration results to obtain a first target result; calculating a three-dimensional reflection coefficient operator on the original FWI velocity model and performing tilt filtering using the three-dimensional reflection coefficient operator to obtain a second target result; calculating a phase shift operator and amplitude weighting coefficients based on the first and second target results; and weighting the first and second target results based on the amplitude weighting coefficients and phase shift operator to obtain a target imaging result corresponding to the area to be imaged. By optimizing the original reverse-time migration results and FWI calculation results and performing weighted superposition, the energy of low and high wavenumbers in seismic waves is enhanced, the frequency band range of conventional migration is expanded, the imaging results are displayed in a more three-dimensional manner, and boundary lines and interface layer changes can be displayed. This achieves the mapping of full-bandwidth seismic data into a high-resolution seismic profile in the depth domain in the time domain, thereby improving the quality of seismic wave imaging.

[0024] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of a seismic wave imaging method according to Embodiment 1 of the present invention;

[0027] Figure 2 This is a flowchart of another seismic wave imaging method provided according to Embodiment 2 of the present invention;

[0028] Figure 3 This is a flowchart of an imaging algorithm for seismic waves applicable to an embodiment of the present invention;

[0029] Figure 4 This is a schematic diagram of a velocity field obtained by FWI, applicable to an embodiment of the present invention;

[0030] Figure 5 This is a reverse-time offset cross-sectional view applicable to the embodiments of the present invention;

[0031] Figure 6 This is a type of invention applicable to embodiments of the present invention. Figure 5 The corresponding wavenumber spectrum;

[0032] Figure 7 This is a schematic diagram of a reverse-time offset after three-dimensional filtering by the Laplacian operator, applicable to an embodiment of the present invention;

[0033] Figure 8 This is a type of invention applicable to embodiments of the present invention. Figure 7 The corresponding wavenumber spectrum;

[0034] Figure 9 This is a schematic diagram of three-dimensional reflection coefficients obtained from an FWI velocity field, applicable to an embodiment of the present invention;

[0035] Figure 10 This is a type of invention applicable to embodiments of the present invention. Figure 9 The corresponding wavenumber spectrum;

[0036] Figure 11 This is a schematic diagram of a time-phase matched superposition as applied in an embodiment of the present invention;

[0037] Figure 12 This is a type of invention applicable to embodiments of the present invention. Figure 11 The corresponding wavenumber spectrum;

[0038] Figure 13 This is a schematic diagram of the structure of a seismic wave imaging device according to Embodiment 3 of the present invention;

[0039] Figure 14 This is a schematic diagram of the structure of an electronic device that implements the seismic wave imaging method of this invention. Detailed Implementation

[0040] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0041] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0042] Example 1

[0043] Figure 1 This is a flowchart of a seismic wave imaging method provided in Embodiment 1 of the present invention. This embodiment is applicable to seismic wave imaging based on FWI velocity models and original reverse time migration results. The method can be executed by a seismic wave imaging device, which can be implemented in hardware and / or software and is generally configured in an electronic device. Figure 1 As shown, the method includes:

[0044] S110, Obtain seismic data for the area to be imaged.

[0045] The seismic data for the area to be imaged includes the original full-waveform inversion FWI velocity model and the original reverse time migration results.

[0046] In this embodiment of the invention, the seismic data of the area to be imaged can be specifically understood as: in the area to be imaged, the image data reflecting the underground structure generated by processing the seismic data collected through seismic exploration activities and the imaging algorithm, such as the original full waveform inversion FWI velocity model and the original reverse time migration result obtained by FWI technology and reverse time migration (RTM) technology, respectively.

[0047] The FWI velocity model is fundamental to understanding the propagation of seismic waves underground. FWI utilizes the full waveform information of seismic data to iteratively optimize the underground velocity model, minimizing the discrepancy between observed seismic data and forward modeling data based on the velocity model. The raw RTM result refers to the initial underground imaging result obtained by applying the reverse time migration algorithm to simulate the process of seismic waves propagating backward from the detector to the source. This result reflects the propagation characteristics of seismic waves underground and the geological structure.

[0048] S120. Perform amplitude compensation and Laplace filtering on the original reverse time offset result to obtain the first target result.

[0049] In this embodiment of the invention, the first target result can be specifically understood as: the result after optimizing the original reverse time migration result using amplitude compensation and Laplace filtering methods. When seismic waves propagate underground, their amplitude is affected by various factors, including geometric diffusion and absorption attenuation. By restoring the original amplitude of the seismic wave through amplitude compensation and reducing the impact of these factors causing the amplitude to decrease with increasing distance, the reliability of seismic data can be improved, thereby enhancing the imaging quality of the seismic wave. For example, for geometric diffusion, the compensation method can use a square root distance attenuation model, that is, multiplying the amplitude by an amplitude compensation factor to restore its original size. The amplitude compensation factor can be the square root of the distance from the seismic source to the receiving point.

[0050] Laplace filtering is an edge enhancement filter used to highlight high-frequency components in seismic data, such as geological features like faults and fractures. By combining amplitude compensation with the primary target output of Laplace filtering, the true amplitude of steep structures in the seismic data—that is, the energy of high-frequency components—can be preserved, improving the signal-to-noise ratio and resolution of the seismic data, thereby enhancing its imaging quality.

[0051] S130. For the original FWI velocity model, calculate the three-dimensional reflection coefficient operator, and use the three-dimensional reflection coefficient operator to perform tilt filtering to obtain the second target result.

[0052] In this embodiment of the invention, the second target result can be specifically understood as: the optimized result obtained by applying dip filtering to the original FWI velocity model using a three-dimensional reflection coefficient operator. The three-dimensional reflection coefficient operator is calculated based on the reflection characteristics of seismic waves at the formation interface; for example, the three-dimensional reflection coefficient operator can be: ik z |k / k z |. Where i is the imaginary unit, k z This represents the wave number in the vertical direction. |k / k z | is the wavenumber divided by the wavenumber in the vertical direction. k z |k / k z | represents the three-dimensional reflection coefficient at each point in the cross-section.

[0053] The specific calculation method for the three-dimensional reflection coefficient operator is as follows: First, the original FWI velocity model is transformed from the time domain to the wavenumber domain using a three-dimensional Fourier transform. The horizontal wavenumber is then low-pass filtered, for example, by multiplying the horizontal velocity field in the wavenumber domain by a low-pass filter (rectangular function or Gaussian function, etc.). The normal wavenumber is then band-pass filtered, by multiplying the normal velocity field in the wavenumber domain by a band-pass filter (rectangular function, etc.). This suppresses the steepest parts of the offset arc, reducing or eliminating the diffraction (also known as arcing or diffraction) effect caused by seismic waves propagating through complex geological structures. These effects manifest as steep anomalies or artifacts in the imaging results. Tilt filtering is a filtering technique used to suppress waves at a specific tilt angle (i.e., the angle between the wave propagation direction and the vertical direction), thereby reducing the influence of multiple waves, diffracted waves, or waves at other specific angles.

[0054] Then, high-steep energy is suppressed by defining tilt filtering. Specifically, tilt filtering can be performed as follows: for each wavenumber vector, calculate the angle between its wavenumber vector and the vertical direction, and design a corresponding filter based on the required tilt angle of the wave to be suppressed or enhanced. For example, if the goal is to suppress low-tilt waves (such as multiples), a high-pass filter can be designed that attenuates in the low-tilt range but allows passage in the high-tilt range; for suppressing high-tilt waves (such as diffracted waves), a low-pass filter can be designed that attenuates in the high-tilt range but allows passage in the low-tilt range; if it is necessary to retain waves within a specific tilt angle range while suppressing waves at other angles, a band-pass filter can be designed that allows passage only within the specific tilt angle range and attenuates in other ranges. The designed filter is then applied to the seismic data in the wavenumber domain, i.e., the wavenumber domain representation of the seismic data is multiplied by the filter. Finally, the velocity field in the wavenumber domain is subjected to a three-dimensional inverse Fourier transform, converting it back from the wavenumber domain to the time domain to obtain a three-dimensional reflection coefficient imaging profile, the corresponding data of which is the second target result. By using tilt filtering to suppress vertical artifacts in the FWI velocity model, low wavenumber energy is enhanced, improving the signal-to-noise ratio and resolution of seismic data, thereby improving the imaging quality of seismic data.

[0055] S140. Based on the first target result and the second target result, calculate the phase shift operator and amplitude weighting coefficient.

[0056] In this embodiment of the invention, the phase-shifting operator can be specifically understood as: the process of calculating the three-dimensional reflection coefficient, used to correct the phase difference in the second target result caused by velocity changes or other factors. The amplitude weighting coefficient can be specifically understood as: the weighting value used when adding the first target result and the second target result to optimize the final imaging result. The sum of the amplitude weighting coefficients of the first target result and the second target result is 1.

[0057] Based on the second objective result, the longitudinal amplitude value is normalized to eliminate the difference between different amplitude values, making the processing more uniform. Then, the normalized longitudinal amplitude value is multiplied by the depth amplitude gain to obtain the phase shift operator.

[0058] Depth amplitude gain is used to adjust the magnitude of the amplitude. After normalization, it is multiplied by a specific coefficient, which can be determined empirically or based on specific processing objectives. For example, if the goal is to enhance components within a specific frequency range in seismic data, such as enhancing high-frequency components to improve resolution, the coefficient can be set to amplify wavenumber domain data within that frequency range. In denoising, if experience shows that a certain frequency range is typically associated with noise, the coefficient can be set to attenuate the amplitude within that range to reduce the impact of noise.

[0059] The amplitude weighting coefficient can be determined based on the analysis of the first and second target results, and their performance under specific geological conditions. For example, when RTM results perform better in shallow layers and FWI results perform better in deep layers, the amplitude weighting coefficient can be set segmentally. In shallow layers (e.g., depth less than 1000 meters), more weight can be given to RTM results, such as 0.7, and correspondingly, the weight of FWI results is 0.3. In deep layers (e.g., depth greater than 1000 meters), more weight can be given to FWI results, such as 0.7, and correspondingly, the weight of RTM results is 0.3. Preferably, in transition layers (e.g., depth between 800 and 1000 meters), linear interpolation can be used to further refine the weighting values, and the weight of RTM results can be... The weights of the FWI results can be Where d is the depth.

[0060] S150. The results of the first target and the second target are weighted according to the amplitude weighting coefficient and the phase shift operator to obtain the target imaging result corresponding to the area to be imaged.

[0061] Specifically, the target imaging result corresponding to the area to be imaged = amplitude weighting coefficient of the second target result × phase shift operator × second target result + amplitude weighting coefficient of the first target result × first target result.

[0062] The technical solution of this invention involves acquiring seismic data of the area to be imaged; performing amplitude compensation and Laplace filtering on the original reverse-time migration results to obtain a first target result; calculating a three-dimensional reflection coefficient operator on the original FWI velocity model and performing tilt filtering using the three-dimensional reflection coefficient operator to obtain a second target result; calculating a phase shift operator and amplitude weighting coefficients based on the first and second target results; and weighting the first and second target results based on the amplitude weighting coefficients and phase shift operator to obtain a target imaging result corresponding to the area to be imaged. By optimizing the original reverse-time migration results and FWI calculation results and performing weighted superposition, the energy of low and high wavenumbers in seismic waves is enhanced, the frequency band range of conventional migration is expanded, the imaging results are displayed in a more three-dimensional manner, and boundary lines and interface layer changes can be displayed. This achieves the mapping of full-bandwidth seismic data into a high-resolution seismic profile in the depth domain in the time domain, thereby improving the quality of seismic wave imaging.

[0063] Optionally, based on the above embodiments, amplitude compensation and Laplace filtering are performed on the original reverse time migration result to obtain the first target result, which may include:

[0064] Multiply the original reverse time migration result by a power function of depth to obtain the target compensation result;

[0065] The target compensation result is subjected to three-dimensional Laplace filtering to obtain the first target result.

[0066] In this embodiment of the invention, the target compensation result can be specifically understood as: the result after amplitude compensation of the original reverse time offset result.

[0067] Specifically, amplitude compensation for the original reverse-time migration result can be achieved using the following formula:

[0068] A = A0 × D n

[0069] Where A0 represents the initial amplitude, D is the depth at that location, n is the power, and A is the target compensation result. The power needs to be determined based on the characteristics of the original reverse-time migration result. For example, by analyzing the amplitude attenuation result of the original reverse-time migration, an amplitude attenuation model can be established (which can be a geometric diffusion attenuation model or an absorption attenuation model, etc.). Based on the model, the power of amplitude compensation is determined so that the compensated amplitude is more balanced at different depths, thereby achieving longitudinal energy balance.

[0070] A three-dimensional Fourier transform is performed on the target compensation result to convert it from the time domain to the wavenumber domain. A Laplace operator is designed (for example, the square of the Laplace operator can be: the square of the horizontal wavenumber vector + the square of the vertical wavenumber vector), and the data is multiplied by the Laplace operator for filtering to enhance or suppress specific frequency components in the seismic data. Then, a three-dimensional inverse Fourier transform is performed to convert the data from the wavenumber domain back to the time domain. The parameters of the Laplace operator can be adjusted as needed to optimize the filtering effect. Although one-dimensional filtering methods can attenuate migration arc noise, they also suppress the amplitude of steep structures. Compared with the longitudinal one-dimensional filtering method, the three-dimensional filtering method (Lappland operator) in this embodiment can not only filter out low wavenumber noise, remove undercurrent energy, and attenuate migration arc noise, but also protect the true amplitude of steep structures, thus improving the imaging quality of the first target result.

[0071] Optionally, based on the above embodiments, the step of using the three-dimensional reflection coefficient operator for tilt filtering to obtain the second target result may include:

[0072] The original FWI velocity model is converted to the wavenumber domain to obtain the wavenumber domain FWI velocity model;

[0073] The horizontal wavenumber of the wavenumber domain FWI velocity model is low-pass filtered and the normal wavenumber is band-pass filtered to obtain the first FWI velocity model.

[0074] Using three-dimensional periodic boundary conditions, tilt filtering is performed on the singularity where the vertical wavenumber is 0 in the three-dimensional reflection coefficient operator of the first FWI velocity model, and the filtered result is converted back to the time domain to obtain the second target result.

[0075] In this embodiment of the invention, the wavenumber domain FWI velocity model can be specifically understood as: the original FWI velocity model is transformed from the time domain to the wavenumber domain using a three-dimensional Fourier transform, resulting in the model. Based on this, a low-pass filter is applied to the horizontal wavenumber of the model, and a band-pass filter is applied to the normal wavenumber to obtain the first FWI velocity model. The three-dimensional periodic boundary condition can be specifically understood as: under the three-dimensional periodic boundary condition, the boundaries of the model are assumed to be periodic, meaning that seismic waves on the boundaries will repeat with the same value. This implies that fluctuations on one boundary of the model will continue in the same form on the opposite boundary. This boundary condition helps to simulate infinite or semi-infinite geological media while reducing the influence of boundary effects on the simulation results.

[0076] By utilizing three-dimensional periodic boundary conditions to eliminate the reflecting surface, tilt filtering is applied to the singularities where the vertical wavenumber is 0 in the three-dimensional reflection coefficient operator of the first FWI velocity model, in order to suppress vertical multiples or high-tilt noise. The singularity where the vertical wavenumber is 0, i.e., k...z The singularity at 0 represents a wave in the vertical direction with a tilt angle close to 90 degrees. Multiplying the wave at this singularity by a filter factor close to 0 suppresses the vertical wave. For waves at other tilt angles, multiplying by a higher transfer function value preserves or enhances them. Converting the filtered result back to the time domain yields the second target result. Tilt filters, by limiting the angle, filter out wavenumbers exceeding a certain angle, suppressing high-steep energy, especially vertical artifact noise, and enhancing low-wavenumber energy in the data, thereby improving image quality.

[0077] Example 2

[0078] Figure 2 This is a flowchart of another seismic wave imaging method provided in Embodiment 2 of the present invention. This embodiment is a refinement of the operation of "calculating the phase shift operator and amplitude weighting coefficient based on the first target result and the second target result" in the above embodiment. Specifically, it includes: normalizing the longitudinal amplitude value and multiplying it by the depth amplitude gain based on the second target result to calculate the phase shift operator; calculating the target time difference, target phase difference and target amplitude ratio between the first target result and the second target result; and calculating the amplitude weighting coefficient that minimizes the difference between the first target result and the second target result based on the target time difference, target phase difference and target amplitude ratio.

[0079] Correspondingly, such as Figure 2 As shown, the method includes:

[0080] S210. Obtain seismic data for the area to be imaged.

[0081] The seismic data for the area to be imaged includes the original full-waveform inversion FWI velocity model and the original reverse time migration results.

[0082] S220. Perform amplitude compensation and Laplace filtering on the original reverse time offset result to obtain the first target result.

[0083] S230. For the original FWI velocity model, calculate the three-dimensional reflection coefficient operator, and use the three-dimensional reflection coefficient operator to perform tilt filtering to obtain the second target result.

[0084] S240. Based on the second objective result, normalize the longitudinal amplitude value and multiply it by the depth amplitude gain to calculate the phase shift operator.

[0085] S250. Calculate the target time difference, target phase difference, and target amplitude ratio between the first target result and the second target result.

[0086] In this embodiment of the invention, the target time difference can be specifically understood as the difference in seismic wave propagation time between the first target result and the second target result caused by factors such as inaccuracy in the velocity model or differences in seismic wave propagation paths. Using time alignment techniques such as cross-correlation, the first target result and the second target result are aligned in time. Then, for each seismic event, the peak positions or characteristic points of the two results are compared to calculate the target time difference between the first target result and the second target result.

[0087] The target phase difference can be specifically understood as the phase difference between the first target result and the second target result caused by factors such as inaccuracies in the velocity model or differences in the seismic wave propagation path. Phase alignment techniques, such as phase correction (e.g., phase rotation or phase-matched filtering), are used to align the first and second target results in phase. Then, for each seismic event, the phase spectra of the two results are compared, or phase difference techniques are used to calculate the target phase difference between the first and second target results.

[0088] The target amplitude ratio can be specifically understood as the proportional relationship in amplitude between the first target result and the second target result, caused by factors such as inaccuracies in the velocity model or differences in seismic wave propagation paths. Amplitude alignment techniques, such as amplitude correction (e.g., geometric diffusion correction, absorption attenuation correction, or amplitude compensation filtering), are used to align the first and second target results in amplitude. Then, for each seismic event, the amplitude spectra of the two results are compared, or the target amplitude ratio technique is used to calculate the target amplitude ratio between the first and second target results.

[0089] Alignment techniques are used to eliminate differences caused by non-geological factors (such as differences in seismic data acquisition parameters and processing procedures) to ensure that the target time difference, target phase difference, and target amplitude ratio reflect the true geological changes.

[0090] S260. Based on the target time difference, target phase difference, and target amplitude ratio, calculate the amplitude weighting coefficient that minimizes the difference between the first target result and the second target result.

[0091] Specifically, an objective function can be constructed that comprehensively considers the differences among the target time difference, target phase difference, and target amplitude ratio. For example, the objective function could be a weighted sum of these differences, where the weights reflect the importance of each difference. Then, the optimal weighting coefficients, i.e., the amplitude weighting coefficients, are found using gradient descent, least squares, or other optimization algorithms. Minimizing the differences does not simply mean making the target time difference, target phase difference, and target amplitude ratio each zero, but rather minimizing the overall error that comprehensively considers these differences. For example, when the weighting coefficients represent the weights of the first objective result, and correspondingly, the 1-weighting coefficients represent the weights of the second objective result, if the amplitude ratio of the first objective result is closer to reality in some regions, but the phase of the second objective result is more accurate, then the weighting coefficients will reflect this difference, assigning higher weights to the amplitude ratio and lower weights to the phase difference.

[0092] S270. The results of the first target and the second target are weighted according to the amplitude weighting coefficient and the phase shift operator to obtain the target imaging result corresponding to the area to be imaged.

[0093] The technical solution of this invention involves acquiring seismic data of the area to be imaged; performing amplitude compensation and Laplace filtering on the original reverse time migration results to obtain a first target result; calculating a three-dimensional reflection coefficient operator on the original FWI velocity model and performing tilt filtering using the three-dimensional reflection coefficient operator to obtain a second target result; normalizing the longitudinal amplitude value based on the second target result and multiplying it by the depth amplitude gain to calculate a phase shift operator; calculating the target time difference, target phase difference, and target amplitude ratio between the first and second target results; calculating the amplitude weighting coefficient that minimizes the difference between the first and second target results based on the target time difference, target phase difference, and target amplitude ratio; and weighting the first and second target results based on the amplitude weighting coefficient and the phase shift operator to obtain a target imaging result corresponding to the area to be imaged. By minimizing the differences in target time difference, target phase difference, and target amplitude ratio between the first and second target results, the optimized FWI and RTM results are weighted and superimposed to enhance the energy of low and high wavenumbers in seismic waves, expand the frequency band range of conventional migration, and display more three-dimensional imaging results. This allows for the display of boundary lines and interface layer changes, enabling the mapping of full-bandwidth seismic data into high-resolution seismic profiles in the depth domain in the time domain, thereby improving the quality of seismic wave imaging.

[0094] Optionally, based on the above embodiments, the first target result and the second target result are weighted according to the amplitude weighting coefficient and the phase shift operator to obtain the target imaging result corresponding to the region to be imaged. Specifically, this may include:

[0095] Through formula The optimized target imaging result is calculated; where FWI is the original full waveform inversion calculation result, image is the original image, FWI-image is the final optimized image, w is the amplitude weighting coefficient, S is the phase shift operator, and v FWI This refers to the velocity at each position in the original FWI velocity model, I RTM That is the primary objective.

[0096] In this embodiment of the invention, S is the phase shift operator, which is equivalent to the process of calculating the three-dimensional reflection coefficient, v FWI This refers to the velocity at each location in the FWI plot. This refers to converting the velocity field into a wavenumber spectrum using a Fourier transform. This refers to the output result after optimizing the FWI velocity model. In other words, the target imaging result is obtained by weighted summing the output result optimized by the FWI velocity model and the output result optimized by the original reverse time migration result. This can improve imaging quality, reduce noise, enhance geological features, and improve the reliability of seismic imaging.

[0097] Specific application scenarios

[0098] The quality of seismic imaging is mainly affected by three key factors: First, low wavenumber resolution, which depends primarily on the low-frequency signal components in the seismic record; second, high wavenumber resolution, which depends primarily on the high-frequency signal components and the spatial distribution density of the seismic source (shot point) and seismic wave receiver (detector), determining the longitudinal and lateral resolution of the imaging; and finally, by using appropriate low and high wavenumbers and integrating low and high frequency information, an accurate velocity model can be constructed, transforming the full-band seismic data from the time domain to the depth domain, thereby generating accurate seismic profile maps.

[0099] However, as the complexity of geological structures increases, traditional imaging algorithms based on ray and wave equations have limitations. They are both highly dependent on velocity models, and without correcting for these limitations, the migration process can lead to phase and frequency discrepancies. Furthermore, illumination compensation, residuals, and migration arcs can introduce noise into the migration results, reducing the signal-to-noise ratio and resolution of the image, and ultimately lowering the quality of seismic wave imaging.

[0100] To address the above problems, this invention proposes a method for imaging seismic waves. Figure 3 This is a flowchart of a seismic wave imaging algorithm applicable to an embodiment of the present invention. The method may include:

[0101] 1. Input the FWI velocity model and the original reverse time migration results.

[0102] Figure 4This is a schematic diagram of a velocity field obtained by FWI, applicable to an embodiment of the present invention. Figure 5 This is a reverse time migration profile applicable to an embodiment of the present invention. The horizontal axis of the two images represents the lateral distance, and the vertical axis represents the depth from the Earth's surface. The input FWI velocity model and the original reverse time migration results are shown below. Figure 4 and Figure 5 As shown.

[0103] Figure 6 This is a type of invention applicable to embodiments of the present invention. Figure 5 The corresponding wavenumber spectrum, with the horizontal axis representing frequency and the vertical axis representing energy, revealed excessively strong low wavenumbers and a significant difference between the energy spectrum and the seismic wavelet morphology. This is mainly due to:

[0104] 1) Uncutting of energy at large incident angles and energy of creeping waves (dynamic stretching effect)

[0105] High-angle-of-incidence energy refers to seismic waves that strike the geological interface at a large angle, corresponding to high-frequency waves, while creeping waves are waves that propagate along the bottom of the formation, corresponding to low-frequency waves. If these energies are not properly processed, they can cause misestimation of travel time during dynamic calibration, leading to incorrect stretching or compression of seismic events in the imaging, reducing the resolution and reliability of the images. Therefore, failure to remove high-angle-of-incidence energy and creeping wave energy can result in dynamic calibration stretching effects, thus affecting the imaging quality of seismic data.

[0106] 2) The imaging conditions omitted the second-order time derivative factor; the amplitude of the reverse time migration result decayed too quickly, which was due to the lack of illumination compensation, transmission loss compensation, etc.

[0107] In reverse time migration imaging, the second time derivative is related to the high-frequency components of seismic waves, which carry information about details of the subsurface structure. Omitting this factor may result in the loss of high-frequency information in the imaging results, thereby reducing the imaging resolution.

[0108] Furthermore, illumination compensation corrects for amplitude attenuation caused by geometric diffusion of seismic waves, while transmission loss compensation corrects for energy loss due to absorption and scattering as waves propagate in different media. Without illumination and transmission loss compensation, amplitude attenuation will be too rapid, affecting the accuracy of imaging results.

[0109] 2. Optimize the reverse offset results

[0110] Amplitude compensation (i.e., multiplying by a power function of depth) and Laplace filtering are applied to the original reverse-time migration results. While one-dimensional longitudinal filtering (using the second-order depth derivative) suppresses the amplitude of steep structures, it also attenuates migration arc noise. Therefore, a three-dimensional filtering method (using the Laplace operator) is employed to filter out low wavenumbers (i.e., remove undercurrent wave energy). Figure 7 This is a schematic diagram of a reverse-time offset after three-dimensional filtering using the Laplacian operator, applicable to an embodiment of the present invention. The horizontal axis represents the lateral distance, and the vertical axis represents the depth from the ground surface. Figure 7 As shown, it can preserve the true amplitude of high-steep structures, enhance high-wavenumber energy, and compensate for the suppression of high-steep structure amplitude by one-dimensional filtering (second-order depth derivative), but it also has the limitation of attenuating offset arc noise. Figure 8 This is a type of invention applicable to embodiments of the present invention. Figure 7 The corresponding wavenumber spectrum, with the horizontal axis representing frequency and the vertical axis representing energy, such as... Figure 8 As shown, after the above processing, the wavenumber spectrum should exhibit the shape of a seismic wavelet.

[0111] 3. Optimize FWI results

[0112] The corresponding three-dimensional reflection coefficients are calculated using the FWI velocity field. The operator for calculating the three-dimensional reflection coefficients is ik. z |k / k z |,k z This represents the wave number in the vertical direction. |k / k z | is the wavenumber divided by the wavenumber in the vertical direction. k z |k / k z | represents the three-dimensional reflection coefficient at each point in the profile. The FWI velocity field is converted to the wavenumber domain using a three-dimensional Fourier transform. The horizontal wavenumber is low-pass filtered, and the normal wavenumber is band-pass filtered, thereby suppressing the steep parts of the offset arc.

[0113] The boundary reflection surface is eliminated by utilizing three-dimensional periodic boundary conditions. By defining a tilt angle filter, the reflection surface is suppressed by the operator at k. z The singularity at 0 causes a vertical artifact; the amplitude weighting value, i.e., the phase shift operator, is obtained by normalizing the amplitude and using the corresponding depth amplitude gain. The three-dimensional reflectance coefficient imaging profile is obtained by converting from the wavenumber domain back to the time domain. Figure 9 This is a schematic diagram of three-dimensional reflection coefficients obtained from an FWI velocity field, applicable to an embodiment of the present invention. The horizontal axis represents the lateral distance, and the vertical axis represents the depth from the ground surface. Figure 10 This is a type of invention applicable to embodiments of the present invention. Figure 9 The corresponding wavenumber spectrum, with the horizontal axis representing frequency and the vertical axis representing energy level. For example... Figure 10 As shown, after the above processing, wavenumber spectrum analysis shows that the energy is stronger at low wavenumbers.

[0114] 4. After steps 2 and 3, the time and phase of the three-dimensional reflection coefficient obtained by the reverse time migration result and the full waveform inversion calculation may differ.

[0115] The input data volume can be either two-dimensional or three-dimensional. When the input data volume is two-dimensional, the original reverse-time migration result is not zero-phase due to the lack of two-dimensional to three-dimensional correction. Two-dimensional to three-dimensional correction refers to the fact that, although the software processes actual two-dimensional data during migration, the expected input should simulate the propagation of a wave field in three-dimensional space, and its corresponding Green's function should be zero-phase. However, when the data provided in this embodiment is based on sampling of a wave field in two-dimensional space, its corresponding Green's function has a 45-degree phase shift. Therefore, appropriate correction should be performed before or during migration processing. In addition, factors such as wavelets can also cause time or phase deviations.

[0116] Therefore, the matching summation module is used to superimpose the outputs of steps 2 and 3 to obtain the output of this process. This module calculates the time difference, phase difference, and amplitude ratio between the two inputs to obtain the corresponding amplitude weighting coefficients that minimize these parameters. The two optimized results are then corrected and summed to obtain the final output. The formula for overall full-waveform inversion imaging is summarized as follows:

[0117]

[0118] Where FWI is the original full waveform inversion calculation result, image is the original image, FWI-image is the final optimized target imaging result, w is the amplitude weighting coefficient, S is the phase shift operator, which is equivalent to the process of calculating the three-dimensional reflection coefficient, and v FWI This refers to the velocity at each location in the FWI plot. This refers to converting the velocity field into a wavenumber spectrum using a Fourier transform. RTM This refers to the output result after optimizing the original reverse time offset result.

[0119] Figure 11 This is a schematic diagram of a time-phase matched overlay used in an embodiment of the present invention. The horizontal axis represents the lateral distance, and the vertical axis represents the depth from the Earth's surface. Figure 11 As shown, when the same color represents a single layer, the cross-sectional display results are more three-dimensional. Not only can the boundary lines be clearly seen, but the layer changes within the interface can also be displayed in greater depth. Compared to traditional imaging results, the display adds low-frequency information, as if directly showing the layers rather than just the interface. Figure 12 This is a type of invention applicable to embodiments of the present invention. Figure 11 The corresponding wavenumber spectrum, with the horizontal axis representing frequency and the vertical axis representing energy, such as... Figure 12 As shown, the wavenumber spectrum results show that the energy is enhanced at both low and high wavenumbers.

[0120] The technical solution proposed in this invention, based on obtaining high-precision velocity through FWI inversion, performs reflection coefficient conversion, spatial filtering, and phase matching, and then quantitatively fuses it with the results of reverse time migration to achieve FWI imaging. This enhances the energy of low and high wavenumbers in seismic waves, effectively expands the frequency band range of conventional migration, and displays more three-dimensional imaging results. It can show boundary lines and interface layer changes, and realizes the mapping of full-bandwidth seismic data into high-resolution seismic profile maps in the depth domain in the time domain, thereby improving the quality of seismic wave imaging.

[0121] Example 3

[0122] Figure 13 This is a schematic diagram of the structure of a seismic wave imaging device provided in Embodiment 3 of the present invention. Figure 13 As shown, the device includes: a data acquisition module 1310, a first result acquisition module 1320, a second result acquisition module 1330, a parameter calculation module 1340, and a target imaging acquisition module 1350.

[0123] The data acquisition module 1310 is used to acquire seismic data of the area to be imaged; wherein, the seismic data of the area to be imaged includes the original full waveform inversion FWI velocity model and the original reverse time migration results;

[0124] The first result acquisition module 1320 is used to perform amplitude compensation and Laplace filtering on the original reverse time offset result to obtain the first target result;

[0125] The second result acquisition module 1330 is used to calculate the three-dimensional reflection coefficient operator for the original FWI velocity model, and to perform tilt filtering using the three-dimensional reflection coefficient operator to obtain the second target result;

[0126] The parameter calculation module 1340 is used to calculate the phase shift operator and amplitude weighting coefficient based on the first target result and the second target result;

[0127] The target imaging acquisition module 1350 is used to perform weighted processing on the first target result and the second target result according to the amplitude weighting coefficient and the phase shift operator to obtain the target imaging result corresponding to the area to be imaged.

[0128] The technical solution of this invention involves acquiring seismic data of the area to be imaged; performing amplitude compensation and Laplace filtering on the original reverse-time migration results to obtain a first target result; calculating a three-dimensional reflection coefficient operator on the original FWI velocity model and performing tilt filtering using the three-dimensional reflection coefficient operator to obtain a second target result; calculating a phase shift operator and amplitude weighting coefficients based on the first and second target results; and weighting the first and second target results based on the amplitude weighting coefficients and phase shift operator to obtain a target imaging result corresponding to the area to be imaged. By optimizing the original reverse-time migration results and FWI calculation results and performing weighted superposition, the energy of low and high wavenumbers in seismic waves is enhanced, the frequency band range of conventional migration is expanded, the imaging results are displayed in a more three-dimensional manner, and boundary lines and interface layer changes can be displayed. This achieves the mapping of full-bandwidth seismic data into a high-resolution seismic profile in the depth domain in the time domain, thereby improving the quality of seismic wave imaging.

[0129] Based on the above embodiments, the first result acquisition module 1320 is specifically used for:

[0130] Multiply the original reverse time migration result by a power function of depth to obtain the target compensation result;

[0131] The target compensation result is subjected to three-dimensional Laplace filtering to obtain the first target result.

[0132] Based on the above embodiments, the second result acquisition module 1330 is specifically used for:

[0133] The original FWI velocity model is converted to the wavenumber domain to obtain the wavenumber domain FWI velocity model;

[0134] The horizontal wavenumber of the wavenumber domain FWI velocity model is low-pass filtered and the normal wavenumber is band-pass filtered to obtain the first FWI velocity model.

[0135] Using three-dimensional periodic boundary conditions, tilt filtering is performed on the singularity where the vertical wavenumber is 0 in the three-dimensional reflection coefficient operator of the first FWI velocity model, and the filtered result is converted back to the time domain to obtain the second target result.

[0136] Based on the above embodiments, the parameter calculation module 1340 is specifically used for:

[0137] Based on the second objective result, the longitudinal amplitude value is normalized and multiplied by the depth amplitude gain to calculate the phase shift operator;

[0138] Calculate the target time difference, target phase difference, and target amplitude ratio between the first target result and the second target result;

[0139] Based on the target time difference, target phase difference, and target amplitude ratio, the amplitude weighting coefficient that minimizes the difference between the first target result and the second target result is calculated.

[0140] Based on the above embodiments, the target imaging acquisition module 1350 is specifically used for:

[0141] Through formula The optimized target imaging result is calculated; where FWI is the original full waveform inversion calculation result, image is the original image, FWI-image is the final optimized target imaging result, w is the amplitude weighting coefficient, S is the phase shift operator, and v FWI This refers to the velocity at each position in the original FWI velocity model, I RTM That is the primary objective.

[0142] The seismic wave imaging device provided in this embodiment of the invention can execute the seismic wave imaging method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0143] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0144] Example 4

[0145] Figure 14 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0146] like Figure 14As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0147] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0148] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as seismic wave imaging methods, i.e.:

[0149] Acquire seismic data for the region to be imaged; the seismic data for the region to be imaged includes the original full-waveform inversion FWI velocity model and the original reverse time migration results;

[0150] The original reverse time migration result is subjected to amplitude compensation and Laplace filtering to obtain the first target result;

[0151] For the original FWI velocity model, a three-dimensional reflection coefficient operator is calculated, and tilt filtering is performed using the three-dimensional reflection coefficient operator to obtain the second target result;

[0152] Based on the results of the first and second objectives, the phase shift operator and amplitude weighting coefficients are calculated.

[0153] The results for the first target and the second target are weighted using amplitude weighting coefficients and phase shift operators to obtain the target imaging result corresponding to the region to be imaged.

[0154] In some embodiments, the seismic wave imaging method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the seismic wave imaging method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the seismic wave imaging method by any other suitable means (e.g., by means of firmware).

[0155] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0156] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0157] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0158] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0159] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0160] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0161] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0162] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for imaging seismic waves, characterized in that, include: Acquire seismic data for the region to be imaged; the seismic data for the region to be imaged includes the original full-waveform inversion FWI velocity model and the original reverse time migration results; The original reverse time migration result is subjected to amplitude compensation and Laplace filtering to obtain the first target result; For the original FWI velocity model, a three-dimensional reflection coefficient operator is calculated, and tilt filtering is performed using the three-dimensional reflection coefficient operator to obtain the second target result; Based on the results of the first and second objectives, the phase shift operator and amplitude weighting coefficients are calculated. The results for the first target and the second target are weighted using amplitude weighting coefficients and phase shift operators to obtain the target imaging result corresponding to the region to be imaged.

2. The method according to claim 1, characterized in that, The original reverse time migration result is subjected to amplitude compensation and Laplace filtering to obtain the first target result, including: Multiply the original reverse time migration result by a power function of depth to obtain the target compensation result; The target compensation result is subjected to three-dimensional Laplace filtering to obtain the first target result.

3. The method according to claim 1, characterized in that, The process of using a three-dimensional reflection coefficient operator for tilt filtering to obtain the second target result includes: The original FWI velocity model is converted to the wavenumber domain to obtain the wavenumber domain FWI velocity model; The horizontal wavenumber of the wavenumber domain FWI velocity model is low-pass filtered and the normal wavenumber is band-pass filtered to obtain the first FWI velocity model. Using three-dimensional periodic boundary conditions, tilt filtering is performed on the singularity where the vertical wavenumber is 0 in the three-dimensional reflection coefficient operator of the first FWI velocity model, and the filtered result is converted back to the time domain to obtain the second target result.

4. The method according to claim 1, characterized in that, Based on the results of the first and second objectives, the phase shift operator and amplitude weighting coefficients are calculated, including: Based on the second objective result, the longitudinal amplitude value is normalized and multiplied by the depth amplitude gain to calculate the phase shift operator; Calculate the target time difference, target phase difference, and target amplitude ratio between the first target result and the second target result; Based on the target time difference, target phase difference, and target amplitude ratio, the amplitude weighting coefficient that minimizes the difference between the first target result and the second target result is calculated.

5. The method according to claim 1, characterized in that, The results for the first and second targets are weighted using amplitude weighting coefficients and phase shift operators to obtain the target imaging results corresponding to the region to be imaged, specifically including: Through formula The optimized target imaging result is calculated; where FWI is the original full waveform inversion calculation result, image is the original image, FWI-image is the final optimized target imaging result, w is the amplitude weighting coefficient, S is the phase shift operator, and v FWI This refers to the velocity at each position in the original FWI velocity model, I RTM That is the primary objective.

6. An imaging device for seismic waves, characterized in that, include: The data acquisition module is used to acquire seismic data of the area to be imaged; the seismic data of the area to be imaged includes the original full waveform inversion FWI velocity model and the original reverse time migration results. The first result acquisition module is used to perform amplitude compensation and Laplace filtering on the original reverse time offset result to obtain the first target result; The second result acquisition module is used to calculate the three-dimensional reflection coefficient operator for the original FWI velocity model, and to perform tilt filtering using the three-dimensional reflection coefficient operator to obtain the second target result; The parameter calculation module is used to calculate the phase shift operator and amplitude weighting coefficient based on the first target result and the second target result; The target imaging acquisition module is used to perform weighted processing on the first target result and the second target result according to the amplitude weighting coefficient and the phase shift operator to obtain the target imaging result corresponding to the area to be imaged.

7. The apparatus according to claim 6, characterized in that, The first result acquisition module is specifically used for: Multiply the original reverse time migration result by a power function of depth to obtain the target compensation result; The target compensation result is subjected to three-dimensional Laplace filtering to obtain the first target result.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the seismic wave imaging method according to any one of claims 1-5.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the imaging method for seismic waves according to any one of claims 1-5.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the seismic wave imaging method according to any one of claims 1-5.

Images