An underground structure imaging method based on background noise surface wave double-wave bunching
By using the dual-wave beamforming method, phase velocity and azimuth anisotropy information can be directly extracted from seismic data, solving the problems of ray theory assumptions and medium homogeneity limitations in traditional methods, and achieving more accurate imaging of underground structures.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTHERN UNIVERSITY OF SCIENCE AND TECHNOLOGY
- Filing Date
- 2022-10-19
- Publication Date
- 2026-04-21
AI Technical Summary
Traditional background noise tomography methods suffer from limitations in the inversion process due to the assumptions of ray theory and dependence on transversely homogeneous media, resulting in inaccurate imaging results of underground structures.
A dual-wave beamforming method based on background noise surface waves is adopted. By acquiring raw seismic data, calculating the cross-correlation function between station pairs, selecting dual-wave beamforming calculation parameters, setting the search range for local phase velocity and azimuth angle, generating phase velocity maps and azimuth anisotropy information, and directly extracting subsurface structure information.
This improved the signal-to-noise ratio, reduced the impact of non-diffuse noise, and yielded more accurate imaging results of underground structures, avoiding errors found in traditional methods.
Smart Images
Figure CN116165706B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of underground structure imaging technology, and more specifically, to an underground structure imaging method based on background noise surface wave dual-wave focusing. Background Technology
[0002] Traditional background noise tomography utilizes the dispersion characteristics of surface waves to extract dispersion curves within a certain period range through time-frequency analysis techniques, and then performs inversion calculations. The inversion process generally adopts a two-step method: (1) Based on the assumption of ray theory, the phase (group) velocity measurements related to the period are inverted to obtain a two-dimensional phase (group) velocity map; (2) The local dispersion curves extracted from the two-dimensional phase (group) velocity map at the grid points are subjected to one-dimensional linear inversion to obtain a one-dimensional shear wave velocity model, and then the final three-dimensional shear wave velocity model is constructed. However, the traditional two-step inversion method of background noise tomography has two basic limitations: (1) The use of ray theory is assumed in most cases that seismic waves propagate along a great circular arc path, and it is believed that the travel time of surface waves is only sensitive to the medium structure with zero width in the propagation path. This assumption is only applicable to high-frequency approximation conditions, requiring the heterogeneous scale of the medium to be much larger than the seismic wavelength; (2) When performing point-by-point one-dimensional shear wave velocity structure inversion, it is only applicable to transversely homogeneous media. Considering that there is strong heterogeneity in underground structures in most cases, this basic limitation may lead to non-negligible errors. Therefore, the traditional background noise tomography method is not effective and the results are not accurate enough. Summary of the Invention
[0003] To address the problems existing in the first step of the inversion process, this application provides a method for imaging underground structures based on background noise surface wave dual-wave focusing.
[0004] In a first aspect, embodiments of this application provide a method for imaging underground structures based on background noise surface wave dual-wave focusing, the method comprising:
[0005] The raw seismic data is acquired, and after preprocessing, the cross-correlation function between station pairs is calculated based on the preprocessed raw seismic data.
[0006] Based on the cross-correlation function, dual-wavelength beamforming calculation parameters are selected, and source beamforming and receiving beamforming are determined based on the dual-wavelength beamforming calculation parameters. The dual-wavelength beamforming calculation parameters include the beamforming center point and the beamforming width.
[0007] Set the local phase velocity and azimuth search range, correct the cross-correlation waveforms located in the source beam and receiver beam and superimpose them onto the beam center point, and search for the optimal measurement result corresponding to the maximum energy spectrum of the envelope of the superimposed waveform. The optimal measurement result includes the optimal phase velocity and the optimal incident azimuth.
[0008] The source beam and the receiving beam are moved to obtain multiple sets of optimal measurement results. A phase velocity map is generated based on each optimal measurement result, and azimuth anisotropy information is generated by fitting the weakly anisotropic medium.
[0009] Subsurface structure information is generated based on the phase velocity map and azimuth anisotropy information.
[0010] Preferably, the preprocessing of the raw seismic data includes:
[0011] The original seismic data were sequentially subjected to instrument response removal, trend removal, and mean removal.
[0012] Preferably, the step of selecting dual-wavelength beamforming calculation parameters based on the cross-correlation function includes:
[0013] Based on the spatial distribution of each station, a first preset number of beam-focusing center points are selected, and the beam-focusing center points are distributed at equal intervals.
[0014] Select a beamwidth such that a second preset number of the cross-correlation functions can be superimposed within the beamwidth.
[0015] Preferably, the setting of the local phase velocity and azimuth angle search range includes:
[0016] Determine the relative position and relative azimuth angle of each of the station pairs in the source and receiving beams relative to the center point of the beams;
[0017] The local phase velocity and azimuth search range are set based on the relative position and relative azimuth angle.
[0018] Preferably, generating the phase velocity map based on each of the optimal measurement results includes:
[0019] The final phase velocity value is obtained by averaging the values of the optimal phase velocities described above.
[0020] A phase velocity map is generated based on the final phase velocity value.
[0021] Preferably, the step of generating azimuth anisotropy information by fitting the weakly anisotropic medium includes:
[0022] Each time the optimal phase velocity is obtained, the propagation incident angle of the seismic wave at the beam center point is determined, and the average phase velocity within a preset angle range is statistically analyzed.
[0023] Based on the weak anisotropy fitting of the average propagation incident angle and phase velocity, azimuth anisotropy information is generated.
[0024] Secondly, embodiments of this application provide an underground structure imaging device based on background noise surface wave dual-wave focusing, the device comprising:
[0025] The acquisition module is used to acquire raw seismic data, preprocess the raw seismic data, and calculate the cross-correlation function between station pairs based on the preprocessed raw seismic data.
[0026] The selection module is used to select dual-wave beamforming calculation parameters based on the cross-correlation function, and to determine the source beam and the receiving beam based on the dual-wave beamforming calculation parameters. The dual-wave beamforming calculation parameters include the beam center point and the beam width.
[0027] The setting module is used to set the local phase velocity and azimuth angle search range, correct and superimpose the cross-correlation waveforms located in the source beam and the receiver beam onto the center point of the beam, and search for the optimal measurement result corresponding to the maximum energy spectrum of the envelope of the superimposed waveform. The optimal measurement result includes the optimal phase velocity and the optimal incident azimuth angle.
[0028] The determination module is used to move the source beam and the receiving beam to obtain multiple sets of optimal measurement results, generate a phase velocity map based on each optimal measurement result, and generate azimuth anisotropy information by fitting the weakly anisotropic medium.
[0029] The generation module is used to generate underground structure information based on the phase velocity map and azimuth anisotropy information.
[0030] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method provided as in the first aspect or any possible implementation of the first aspect.
[0031] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method provided as in the first aspect or any possible implementation thereof.
[0032] The beneficial effects of this invention are as follows: 1. By superimposing the energy coherence portion of the cross-correlation signal between two seismic arrays, the reconstruction of weak surface wave signals is completed, thereby improving the signal-to-noise ratio. This effectively addresses the challenges posed by non-diffused noise (scattering and reflection signals, etc.) in the background noise field. In other words, the dual-wave beamforming method acts as a spatial filter between two seismic arrays.
[0033] 2. By searching the azimuth angle, we can obtain local azimuth anisotropy information in a well-distributed seismic array, which also helps to establish a more realistic ray path.
[0034] 3. Traditional background noise imaging methods based on ray theory generally indirectly extract single-point dispersion curves by measuring phase velocity. Due to the uncertainty of the inherent phase, deviations may occur during the calculation process. However, this invention does not need to consider the background noise surface wave imaging inversion problem, thus avoiding the errors caused by various assumptions and intermediate processes in traditional imaging. Attached Figure Description
[0035] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0036] Figure 1 A flowchart illustrating an underground structure imaging method based on background noise surface wave dual-wave focusing, provided for an embodiment of this application;
[0037] Figure 2 A schematic diagram of the structure of an underground structure imaging device based on background noise surface wave dual-wave focusing provided in an embodiment of this application;
[0038] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0039] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.
[0040] In the following description, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The following description provides multiple embodiments of this application, which can be substituted or combined with each other. Therefore, this application can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more other possible combinations of A, B, C, and D, even if such embodiments are not explicitly described in the following text.
[0041] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this application. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
[0042] See Figure 1 , Figure 1 This is a schematic flowchart illustrating a method for imaging underground structures based on background noise surface wave dual-wave focusing, according to an embodiment of this application. In this embodiment, the method includes:
[0043] S101. Obtain raw seismic data, preprocess the raw seismic data, and calculate the cross-correlation function between station pairs based on the preprocessed raw seismic data.
[0044] The entity executing this application may be a cloud server.
[0045] In this embodiment of the application, the original seismic data contains background noise. After preprocessing the original seismic data, cross-correlation calculation is performed using the background noise to obtain the cross-correlation function between each station pair.
[0046] In one possible implementation, the preprocessing of the raw seismic data includes:
[0047] The original seismic data were sequentially subjected to instrument response removal, trend removal, and mean removal.
[0048] In this embodiment, to ensure the accuracy of subsequent calculations and eliminate interference from other factors, the original seismic data will be preprocessed. Specifically, instrument response, trend removal, and mean removal will be performed.
[0049] S102. Select dual-wavelength beamforming calculation parameters based on the cross-correlation function, and determine the source beamforming and the receiving beamforming based on the dual-wavelength beamforming calculation parameters. The dual-wavelength beamforming calculation parameters include the beamforming center point and the beamforming width.
[0050] In this embodiment, dual-wave beamforming relies on source beamforming and receiver beamforming. Therefore, it is first necessary to select the dual-wave beamforming calculation parameters based on the cross-correlation function according to the actual test environment, that is, to select the beamforming center point and beamforming width, thereby determining the source beamforming and receiver beamforming. In addition, the cross-correlation of the target frequency band during dual-wave beamforming also needs to be processed by narrowband filtering.
[0051] In one possible implementation, selecting dual-wavelength beamforming calculation parameters based on the cross-correlation function includes:
[0052] Based on the spatial distribution of each station, a first preset number of beam-focusing center points are selected, and the beam-focusing center points are distributed at equal intervals.
[0053] Select a beamwidth such that a second preset number of the cross-correlation functions can be superimposed within the beamwidth.
[0054] In this embodiment of the application, firstly, an appropriate number of equally spaced clustering centers are selected based on the spatial distribution of stations in the study area. The spacing between clustering points can be set with reference to the average spacing between stations in a dense array. Then, the clustering width is selected, which generally varies depending on the period, but it is necessary to ensure that the number of superimposed cross-correlation points is appropriate, neither too many nor too few.
[0055] S103. Set the local phase velocity and azimuth angle search range, correct the cross-correlation waveforms located in the source beam and the receiver beam and superimpose them onto the center point of the beam, and search for the optimal measurement result corresponding to the maximum energy spectrum of the envelope of the superimposed waveform. The optimal measurement result includes the optimal phase velocity and the optimal incident azimuth angle.
[0056] In this embodiment, after determining the source and receiver beams, a local phase velocity and azimuth angle search range is set to superimpose the cross-correlation waveforms within the source and receiver beams, ultimately searching for the optimal phase velocity and optimal incident azimuth angle. The search process is iterative, performing a velocity search followed by an azimuth angle search. Each search employs a two-step method: coarse and fine mesh, which significantly saves computation time and improves computational efficiency. In the time domain, the waveforms of the superimposed cross-correlation functions within the source and receiver beams are... It can be represented as follows:
[0057]
[0058] in, The cross-correlation function lies within a source-receiver beam. and This indicates the number of stations included in a pair of beams. The correction time for the cross-correlation source (receiver) stations relative to the source (receiver) beam center point. and A spatial vector representing relative distance. and Source (receiver) beam center point Local phase velocity and incident azimuth angle, x and y are the horizontal and vertical coordinates of the cross-correlation source (receiving) stations. The calculation formula is as follows:
[0059]
[0060] In practice, the time correction process for dual-wave beamforming is completed in the frequency domain to avoid errors caused by the accuracy limitations of the time domain sampling rate. It is then converted to the time domain to extract the maximum energy value of the superimposed cross-correlation waveform; the corresponding velocity and azimuth angle represent the optimal local velocity and angle.
[0061] In one possible implementation, setting the local phase velocity and azimuth angle search range includes:
[0062] Determine the relative position and relative azimuth angle of each of the station pairs in the source and receiving beams relative to the center point of the beams;
[0063] The local phase velocity and azimuth search range are set based on the relative position and relative azimuth angle.
[0064] In this embodiment, the local phase velocity and azimuth angle search range will be determined based on the relative position and azimuth angle settings of each station in the source and receiver beams relative to the beam center reference point.
[0065] S104. Move the source beam and the receiving beam to obtain multiple sets of optimal measurement results, generate a phase velocity map based on each optimal measurement result, and generate azimuth anisotropy information by fitting the weakly anisotropic medium.
[0066] In this embodiment, for the same focusing point, there will be multiple search results from different directions. Therefore, by continuously moving the source and receiver focusing beams, multiple sets of optimal measurement results can be obtained, thereby generating a phase velocity map. Furthermore, azimuth anisotropy information will be generated by fitting the weakly anisotropic medium. It is evident that by using dual-wave focusing, it is not necessary to extract the phase (group) velocity dispersion curve; the phase velocity and azimuth anisotropy information of each reference point can be directly extracted solely through local phase velocity and azimuth angle searches.
[0067] In one possible implementation, generating the phase velocity map based on each of the optimal measurement results includes:
[0068] The final phase velocity value is obtained by averaging the values of the optimal phase velocities described above.
[0069] A phase velocity map is generated based on the final phase velocity value.
[0070] In the embodiments of this application, slowness is relative to phase velocity and is the reciprocal of phase velocity. Phase velocity is one of the key parameters of seismic signals.
[0071] The final phase velocity value is calculated using the following formula:
[0072]
[0073] The phase velocity uncertainty is calculated using the following formula:
[0074]
[0075] in, This represents the average slowness value at that point. and This indicates that the center point of a cluster is at the th... The phase velocity and its slowness value are obtained in each measurement, where n represents the number of effective measurements.
[0076] Ultimately, the phase velocity map is obtained directly by searching the local phase velocity at each cluster center point, without the need for an inversion process.
[0077] In one possible implementation, the step of generating azimuth anisotropy information by fitting the weakly anisotropic medium includes:
[0078] Each time the optimal phase velocity is obtained, the propagation incident angle of the seismic wave at the beam center point is determined, and the average phase velocity within a preset angle range is statistically analyzed.
[0079] Based on the weak anisotropy fitting of the average propagation incident angle and phase velocity, azimuth anisotropy information is generated.
[0080] In this embodiment, after each phase velocity measurement, the propagation incident angle of the seismic wave at each pair of beam centers is approximately estimated and determined. The phase velocities in all azimuths are statistically analyzed within a preset angle range (e.g., 20°), and the average value is extracted. Finally, the average values are differentiated according to the weak anisotropic medium, and then the azimuth anisotropy is fitted. Because of the azimuth anisotropy of Rayleigh waves... Since the term is dominant, anisotropy can be expressed by the following formula:
[0081]
[0082] in, This represents the measured azimuth distribution. The amplitude represents the anisotropy. for The direction of the fast axis of anisotropy.
[0083] S105. Generate underground structure information based on the phase velocity map and azimuth anisotropy information.
[0084] In this embodiment, the traditional ray tracing, matrix construction and inversion process is transformed into local phase velocity search, azimuth angle search and anisotropy fitting. Finally, the underground structure information can be generated based on the phase velocity map and directional anisotropy information, thus realizing the acquisition of underground structure information.
[0085] The following will be combined with the appendix Figure 2 This paper provides a detailed description of the underground structure imaging device based on background noise surface wave dual-wave focusing provided in the embodiments of this application. It should be noted that the appendix... Figure 2 The underground structure imaging device based on background noise surface wave dual-wave focusing shown is used to perform the functions described in this application. Figure 1 The methods shown in the embodiments are for illustrative purposes only, illustrating the parts relevant to the embodiments of this application. For specific technical details not disclosed, please refer to this application. Figure 1 The example shown.
[0086] Please see Figure 2 , Figure 2 This is a schematic diagram of an underground structure imaging device based on background noise surface wave dual-wave focusing, provided in an embodiment of this application. Figure 2 As shown, the device includes:
[0087] The acquisition module 201 is used to acquire raw seismic data, preprocess the raw seismic data, and calculate the cross-correlation function between station pairs based on the preprocessed raw seismic data.
[0088] The selection module 202 is used to select dual-wave beamforming calculation parameters based on the cross-correlation function, and to determine the source beamforming and the receiving beamforming based on the dual-wave beamforming calculation parameters. The dual-wave beamforming calculation parameters include the beamforming center point and the beamforming width.
[0089] The setting module 203 is used to set the local phase velocity and azimuth angle search range, correct the cross-correlation waveforms located in the source beam and the receiver beam and superimpose them onto the beam center point, and search for the optimal measurement result corresponding to the maximum energy spectrum of the envelope of the superimposed waveform. The optimal measurement result includes the optimal phase velocity and the optimal incident azimuth angle.
[0090] The determination module 204 is used to move the source beam and the receiving beam to obtain multiple sets of optimal measurement results, generate a phase velocity map based on each optimal measurement result, and generate azimuth anisotropy information by fitting the weakly anisotropic medium.
[0091] The generation module 205 is used to generate underground structure information based on the phase velocity map and azimuth anisotropy information.
[0092] In one possible implementation, the acquisition module 201 includes:
[0093] The preprocessing unit is used to sequentially remove instrument response, trend, and average values from the raw seismic data.
[0094] In one possible implementation, the selection module 202 includes:
[0095] The first selection unit is used to select a first preset number of beam-focusing center points based on the spatial distribution of each station, wherein the beam-focusing center points are distributed at equal intervals.
[0096] The second selection unit is used to select the beamwidth so that a second preset number of the cross-correlation functions can be superimposed within the beamwidth.
[0097] In one possible implementation, the setting module 203 includes:
[0098] The first determining unit is used to determine the relative position and relative azimuth angle of each of the station pairs in the source beam and the receiving beam relative to the center point of the beam;
[0099] The setting unit is used to set the local phase velocity and azimuth search range based on the relative position and relative azimuth angle.
[0100] In one possible implementation, the determining module 204 includes:
[0101] The average value calculation unit is used to average the optimal phase velocities to obtain the final phase velocity value.
[0102] The first generation unit is used to generate a phase velocity map based on the final phase velocity value.
[0103] In one possible implementation, the determining module 204 further includes:
[0104] The second determining unit is used to determine the propagation incident angle of the seismic wave at the beam center point whenever the optimal phase velocity is obtained, and to calculate the average phase velocity within a preset angle range.
[0105] The generation unit is used to generate azimuth anisotropy information by fitting the average value of the propagation incident angle and phase velocity based on weak anisotropy.
[0106] Those skilled in the art will clearly understand that the technical solutions of the embodiments of this application can be implemented by means of software and / or hardware. In this specification, "unit" and "module" refer to software and / or hardware that can independently complete or cooperate with other components to complete a specific function, wherein the hardware may be, for example, a field-programmable gate array (FPGA), an integrated circuit (IC), etc.
[0107] Each processing unit and / or module in the embodiments of this application can be implemented by an analog circuit that implements the functions described in the embodiments of this application, or by software that executes the functions described in the embodiments of this application.
[0108] See Figure 3 It shows a schematic diagram of the structure of an electronic device according to an embodiment of this application, which can be used to implement... Figure 1 The method in the illustrated embodiment. (As shown) Figure 3 As shown, the electronic device 300 may include: at least one central processing unit 301, at least one network interface 304, user interface 303, memory 305, and at least one communication bus 302.
[0109] The communication bus 302 is used to enable communication between these components.
[0110] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.
[0111] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).
[0112] The central processing unit 301 may include one or more processing cores. The central processing unit 301 connects to various parts within the electronic device 300 using various interfaces and lines. It executes various functions of the terminal 300 and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling data stored in the memory 305. Optionally, the central processing unit 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The central processing unit 301 may integrate one or more of the following: a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the central processing unit 301.
[0113] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned central processing unit 301. Figure 3 As shown, the memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.
[0114] exist Figure 3 In the illustrated electronic device 300, the user interface 303 is mainly used to provide an input interface for the user and to acquire user input data; while the central processing unit 301 can be used to call the underground structure imaging application based on background noise surface wave dual-wave beam focusing stored in the memory 305, and specifically perform the following operations:
[0115] The raw seismic data is acquired, and after preprocessing, the cross-correlation function between station pairs is calculated based on the preprocessed raw seismic data.
[0116] Based on the cross-correlation function, dual-wavelength beamforming calculation parameters are selected, and source beamforming and receiving beamforming are determined based on the dual-wavelength beamforming calculation parameters. The dual-wavelength beamforming calculation parameters include the beamforming center point and the beamforming width.
[0117] Set the local phase velocity and azimuth search range, correct the cross-correlation waveforms located in the source beam and receiver beam and superimpose them onto the beam center point, and search for the optimal measurement result corresponding to the maximum energy spectrum of the envelope of the superimposed waveform. The optimal measurement result includes the optimal phase velocity and the optimal incident azimuth.
[0118] The source beam and the receiving beam are moved to obtain multiple sets of optimal measurement results. A phase velocity map is generated based on each optimal measurement result, and azimuth anisotropy information is generated by fitting the weakly anisotropic medium.
[0119] Subsurface structure information is generated based on the phase velocity map and azimuth anisotropy information.
[0120] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.
[0121] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.
[0122] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.
[0123] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.
[0124] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0125] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0126] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.
[0127] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.
[0128] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.
Claims
1. A method for imaging subsurface structures based on background noise surface wave double wave beamforming, characterized by, The method includes: The raw seismic data is acquired, and after preprocessing, the cross-correlation function between station pairs is calculated based on the preprocessed raw seismic data. Based on the cross-correlation function, dual-wavelength beamforming calculation parameters are selected, and source beamforming and receiving beamforming are determined based on the dual-wavelength beamforming calculation parameters. The dual-wavelength beamforming calculation parameters include the beamforming center point and the beamforming width. Set the local phase velocity and azimuth search range, correct the cross-correlation waveforms located in the source beam and receiver beam and superimpose them onto the beam center point, and search for the optimal measurement result corresponding to the maximum energy spectrum of the envelope of the superimposed waveform. The optimal measurement result includes the optimal phase velocity and the optimal incident azimuth. The source beam and the receiver beam are moved to obtain multiple sets of optimal measurement results. A phase velocity map is generated based on each optimal measurement result. Whenever the optimal phase velocity is obtained, the propagation incident angle of the seismic wave at the center point of the beam is determined, and the average phase velocity within a preset angle range is statistically analyzed. Based on the weak anisotropy, the propagation incident angle and the average phase velocity are fitted to generate azimuth anisotropy information. Subsurface structure information is generated based on the phase velocity map and azimuth anisotropy information.
2. The method of claim 1, wherein, The preprocessing of the raw seismic data includes: The original seismic data were sequentially subjected to instrument response removal, trend removal, and mean removal.
3. The method of claim 1, wherein, The selection of dual-wavelength beamforming calculation parameters based on the cross-correlation function includes: Based on the spatial distribution of each station, a first preset number of beam-focusing center points are selected, and the beam-focusing center points are distributed at equal intervals. Select a beamwidth such that a second preset number of the cross-correlation functions can be superimposed within the beamwidth.
4. The method of claim 1, wherein, The setting of the local phase velocity and azimuth angle search range includes: Determine the relative position and relative azimuth angle of each of the station pairs in the source and receiving beams relative to the center point of the beams; The local phase velocity and azimuth search range are set based on the relative position and relative azimuth angle.
5. The method of claim 1, wherein, The generation of the phase velocity map based on each of the optimal measurement results includes: The final phase velocity value is obtained by averaging the optimal measurement results described above. A phase velocity map is generated based on the final phase velocity value.
6. An apparatus for imaging subsurface structures based on background noise surface wave double wave beamforming, characterized by The device includes: The acquisition module is used to acquire raw seismic data, preprocess the raw seismic data, and calculate the cross-correlation function between station pairs based on the preprocessed raw seismic data. The selection module is used to select dual-wave beamforming calculation parameters based on the cross-correlation function, and to determine the source beam and the receiving beam based on the dual-wave beamforming calculation parameters. The dual-wave beamforming calculation parameters include the beam center point and the beam width. The setting module is used to set the local phase velocity and azimuth angle search range, correct and superimpose the cross-correlation waveforms located in the source beam and the receiver beam onto the center point of the beam, and search for the optimal measurement result corresponding to the maximum energy spectrum of the envelope of the superimposed waveform. The optimal measurement result includes the optimal phase velocity and the optimal incident azimuth angle. The determination module is used to move the source beam and the receiving beam to obtain multiple sets of optimal measurement results, generate a phase velocity map based on each optimal measurement result, and determine the propagation incident angle of the seismic wave at the center point of the beam whenever the optimal phase velocity is obtained, and calculate the average phase velocity within a preset angle range; and generate azimuth anisotropy information by fitting the propagation incident angle and the average phase velocity based on weak anisotropy. The generation module is used to generate underground structure information based on the phase velocity map and azimuth anisotropy information.
7. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-5.
8. A computer-readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-5.