Method and device for processing seismic image data of air hammer seismic source

Abstract

The invention discloses a seismic image data processing method for an air hammer seismic source, and the method comprises the steps: enabling an air hammer to be connected with a plurality of moving-coil detectors, enabling the air hammer to hammer the ground in a single-shot manner, collecting and storing seismic image recording data through the moving-coil detectors, enabling one moving-coil detector to serve as a triggering channel, and enabling the other moving-coil detector to serve as a vibration channel; taking the rest moving-coil detectors as effective recording channels; the excitation waveform of the air hammer recorded by the trigger channel is voltage data, the voltage data is regarded as speed data, and the voltage data is derived to obtain an acceleration waveform; the length of front and rear time windows is set, the take-off moment of the acceleration is detected according to the acceleration waveform through the front and rear time window method, and the moment is used as the landing triggering moment of the air hammer body; cutting and aligning the seismic image record data of the rest effective record channels by taking the trigger moment as a reference to obtain a seismic image section; and performing spectral analysis on the seismic image section, determining a noise peak frequency, and then performing low-pass filtering to obtain the seismic image section with significantly reduced noise.

Description

Technical Field

[0001] The present invention relates to the field of exploration seismic data processing, in particular to a method and device for processing seismic image data of a pneumatic hammer source. Background Art

[0002] Seismic data acquisition and processing is a traditional geophysical method, primarily used in the exploration of oil and gas resources. In recent years, the frequent occurrence of urban road collapses and the high risk of road collapses have led to a rapid increase in the demand for detection of potential road collapse hazards.

[0003] At present, the main methods for detecting road collapse include ground penetrating radar and seismic imaging. Among them, ground penetrating radar has a shallow detection depth of less than 7m, while seismic imaging has a relatively deep detection depth of about 3-15m.

[0004] Ground penetrating radar achieves its collection purpose by emitting and collecting high-frequency electromagnetic waves. Both the transmitting and collecting antennas have the ability to continuously excite and receive electromagnetic wave signals. Therefore, ground penetrating radar has the ability to continuously collect data and has high data collection efficiency. The seismic imaging method is a single excitation and single reception method. It does not have the ability to continuously collect data and has low data collection efficiency. Therefore, an air hammer that can be electrically and automatically controlled is developed as a seismic source to improve collection efficiency.

[0005] At present, the application of seismic imaging in road collapse detection at home and abroad mainly relies on artificial seismic sources and traditional data processing methods, which are inefficient; or some adopt air hammer seismic sources, but still use traditional data processing methods, with low accuracy and precision (the traditional method synchronizes the source excitation and the detector receiving the seismic signal, while the air hammer source detector is not synchronized with the source excitation). Summary of the Invention

[0006] The purpose of the present invention is to overcome the deficiencies in the prior art, solve the delay characteristics of air hammer source data acquisition, and provide a method and device for processing seismic imaging data of air hammer sources, so as to realize accurate processing of air hammer source data when detecting ground collapse by seismic imaging method.

[0007] The purpose of the present invention is achieved through the following technical solutions:

[0008] A method for processing seismic imaging data of an air hammer source, comprising:

[0009] S1. Connect a pneumatic hammer to several moving-coil geophones. The hammer strikes the ground with a single shot, collecting and storing seismic image data through the moving-coil geophones. One of the moving-coil geophones is used as a trigger channel to record the hammer's excitation waveform for analysis of the moment the hammer hits the ground. The remaining moving-coil geophones are used as active recording channels, corresponding to the seismic image data detected by the moving-coil geophones.

[0010] S2. The excitation waveform of the air hammer recorded by the trigger channel is voltage data. This voltage data is considered as velocity data and its derivative is used to obtain the acceleration waveform.

[0011] S3. Set the length of the front and back time window, based on the acceleration waveform and the use of the front and back time window method to detect the acceleration take-off moment, and use this moment as the trigger moment for the hammer to land;

[0012] S4. Based on the trigger time, the remaining effective recording channels of the seismic image data are cut and aligned to obtain a seismic image profile;

[0013] S5. Performing spectrum analysis on the seismic image profile to determine the noise peak frequency, and then performing low-pass filtering to obtain a seismic image profile with significantly reduced noise.

[0014] Furthermore, the calculation formula for the characteristic value h(t) of the front and back time windows in step S3 is:

[0015]

[0016] Where w is the length of the previous and next time windows, x[n] represents the time series, and h(t) is the eigenvalue at time t when the previous and next time windows slide on the data axis.

[0017] Furthermore, in step S3, the sampling rate is 2000 Hz, the full-wave width is 32 sampling points, corresponding to a duration of 16 ms, and the length of the front and rear time windows w=16 ms.

[0018] Furthermore, the cutoff frequency of the low-pass filtering in step S5 is 120 Hz to 160 Hz to adapt to the noise characteristics under different geological conditions.

[0019] The present invention also provides a seismic image data processing device for an air hammer source, comprising:

[0020] The data acquisition unit is used to connect the air hammer to several moving coil geophones. The air hammer strikes the ground in a single shot and collects and stores seismic image recording data through the moving coil geophones. One of the moving coil geophones is used as a trigger channel to record the excitation waveform of the air hammer for analyzing the moment when the air hammer body hits the ground. The remaining moving coil geophones are used as effective recording channels, corresponding to the seismic image recording data detected by the moving coil geophones.

[0021] The acceleration calculation unit is used to convert the excitation waveform of the air hammer recorded by the trigger channel into voltage data, regard the voltage data as velocity data, and obtain the acceleration waveform by taking its derivative;

[0022] The trigger moment calculation unit is used to set the length of the front and back time windows, detect the acceleration take-off moment according to the acceleration waveform and the front and back time window method, and use this moment as the trigger moment of the hammer body landing;

[0023] The seismic image section unit is used to cut and align the seismic image recording data of the remaining effective recording channels using the triggering moment as a reference to obtain a seismic image section;

[0024] The output unit is used to perform spectrum analysis on the seismic image section to determine the noise peak frequency, and then perform low-pass filtering to obtain a seismic image section with significantly reduced noise.

[0025] The present invention also provides an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for processing seismic image data of an air hammer source when executing the program.

[0026] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the seismic image data processing method of the air hammer source are implemented.

[0027] Compared with the prior art, the beneficial effects brought about by the technical solution of the present invention are:

[0028] 1. Accurately extract the trigger moment of the air hammer: By differentiating the velocity-type moving-coil detector signal on the trigger channel to obtain acceleration and using the forward and backward time window method to accurately detect the trigger moment, the timing deviation caused by the traditional method of using the valve power-on moment as the starting point is avoided, thereby ensuring high consistency of the data of each shot during cutting alignment. This technical feature significantly improves the accuracy of subsequent channel value stacking and phase axis identification.

[0029] 2. Automated and efficient data segmentation and alignment: Each data channel is automatically segmented and aligned based on the calculated true landing time, eliminating the need for manual labeling or correction. This significantly improves the efficiency and stability of seismic image data processing and reduces human error.

[0030] 3. Effectively remove high-frequency noise: Based on spectrum analysis, invalid noise peaks such as 140Hz and 400Hz are identified, and low-pass filtering (cutoff at approximately 140Hz) is used to suppress high-frequency interference, significantly improving the signal-to-noise ratio. The hyperbolic phase axis and weak reflection interface are clearer, which is conducive to accurately locating underground collapse or weak layers.

[0031] 4. Enhanced data reliability and applicability: The method of the present invention can adapt to different sampling rates (only the time window length w needs to be recalculated according to the actual sampling rate) and the noise characteristics of different geological environments (the cutoff frequency can be adjusted). It has good scalability and is suitable for various shallow seismic imaging scenarios such as urban road collapse.

[0032] 5. The present invention is the first seismic imaging method to use an automatically controllable air hammer source; and the 12-channel detector device meets the full coverage of a single lane, realizing three-dimensional detection; the data processing method of the present invention is the only newly proposed method that can better solve the problem of air hammer source data processing. Traditional data processing methods are not applicable to this device and method. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic flow diagram of the method of the present invention.

[0034] Figure 2 It is the original seismic image recording data using an air hammer source.

[0035] Figure 3 It is the excitation waveform detected by the trigger channel.

[0036] Figure 4 It is a schematic diagram of the trigger channel acceleration waveform.

[0037] Figure 5 This is an enlarged schematic diagram of the first peak waveform in the acceleration waveform.

[0038] Figure 6 It is the characteristic waveform of the time window before and after acceleration.

[0039] Figure 7 It is the cross-sectional view of the trigger path at the hammering moment t1.

[0040] Figure 8 It is the waveform diagram of acceleration, velocity and displacement.

[0041] Figure 9 It is a seismic imaging profile.

[0042] Figure 10 is the unfiltered grayscale image of the seismic image profile.

[0043] Figure 11 This is the frequency filtering interface diagram.

[0044] Figure 12 and Figure 13 It is a seismic image profile after low-pass filtering.

[0045] Figure 14 It is the seismic image recording data obtained by a single excitation of an air hammer source in the high groundwater level area of ​​Jinnan District, Tianjin.

[0046] Figure 15 This is a cross-section of seismic imaging multi-shot data records in the high groundwater level area of ​​Jinnan District, Tianjin.

[0047] Figure 16 is Figure 15On the basis of the conventional seismic image data processing (filtering, etc.), the geological profile is obtained. DETAILED DESCRIPTION

[0048] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0049] like Figure 1 As shown, this embodiment provides a method for processing seismic image data of an air hammer source, which is specifically as follows:

[0050] S1. Connect a pneumatic hammer to several moving-coil geophones. The hammer strikes the ground with a single shot, collecting and storing seismic image data through the moving-coil geophones. One of the moving-coil geophones is used as a trigger channel to record the hammer's excitation waveform for analyzing the moment the hammer hits the ground. The remaining moving-coil geophones are used as active recording channels, corresponding to the seismic image data detected by the moving-coil geophones.

[0051] After the seismic image data is collected, it is stored in a single shot format. The data start time is the moment when the air hammer valve is energized, not the moment when the hammer body hits the ground. The moment when the hammer body hits the ground needs to be further extracted.

[0052] The collected seismic image data is as follows Figure 2 , Figure 2 Track 1 is the trigger channel, which records the excitation waveform of the air hammer and is used to analyze the triggering moment of the air hammer's impact. Tracks 2 through 11 are valid recording channels, corresponding to the seismic image waveforms of geophones 2 through 11, respectively. Track 12 is not connected to a geophone and is an invalid recording channel.

[0053] S2. The excitation waveform of the air hammer recorded by the trigger channel is voltage data. The voltage data is regarded as velocity data and its derivative is used to obtain the acceleration waveform. Specifically:

[0054] In order to extract the triggering moment of the hammer body falling to the ground, the trigger channel signal must be analyzed first. The triggering moment of the hammer body falling to the ground is obtained from the trigger channel, and the trigger waveform detection and frequency domain normalization are performed at the same time, as follows:

[0055] See Figure 3 This trigger trace shows the voltage data from a moving-coil detector connected to the air hammer. Since moving-coil detectors are velocity detectors, this trace can be considered velocity data. This velocity waveform has multiple peaks. While the first peak is distinct, it lacks clear physical meaning, making it difficult to directly determine the actual impact time of the air hammer from this trace.

[0056] When the hammer head of an air hammer strikes the ground, it will be subjected to a significant upward force from the ground, which will appear as a sudden change in acceleration in the vibration data. According to this physical law, deriving the velocity data into acceleration data can give the waveform data a clear physical meaning while highlighting high-frequency signals. The acceleration formula is:

[0057]

[0058] After calculation, the acceleration waveform is shown in Figure 4 , Figure 4 The first acceleration peak corresponds to the maximum support force of the air hammer on the ground.

[0059] S3. Set the length of the front and back time windows, detect the acceleration start time according to the acceleration waveform and use the front and back time window method, and use this time as the trigger time for the hammer body to fall to the ground; specifically:

[0060] In order to detect the moment when the hammer head just touches the ground, that is, the moment when the acceleration begins to increase significantly, the front and back time window method is used to detect the take-off moment of the acceleration waveform. The formula is as follows:

[0061]

[0062] Where w is the time window length, x[n] represents the time series, and h(t) is the eigenvalue at time t. As the forward and backward time windows slide along the data axis, the eigenvalues ​​h for the forward and backward time windows corresponding to the entire data can be calculated.

[0063] To determine the time window length w, the first peak of the acceleration data is amplified and the Figure 5 ,Depend on Figure 5 As can be seen from the figure, the half-wave width of the peak is 16 sampling points, that is, the full-wave width is 32 sampling points. The current data sampling rate is 2000Hz, so the full-wave width is calculated by the following formula:

[0064]

[0065] The full wave width is 16ms. Therefore, in this embodiment, w is set to 16ms to match the first wave feature of the trigger waveform. In practical applications, the value range of w can be 10ms to 20ms.

[0066] After substituting w=16ms into the front and back time window formula, the acceleration waveform is processed to obtain the characteristic waveform of the front and back time window of acceleration. Figure 6 : Figure 6 The characteristic peak in is very clear and completely coincides with the take-off position at 534 milliseconds in the acceleration waveform, indicating that the selection of w is very reasonable. Therefore, this method can accurately extract the hammering moment t1 when the hammer head contacts the ground.

[0067] The trigger time is t1, when the hammer head of the air hammer touches the ground. The trigger channel data is cut to obtain the trigger channel profile. Figure 7 .

[0068] After alignment at t1, a distinct event axis consisting of troughs appears in the trigger path. To determine its specific physical significance, the instantaneous operating state of the air hammer needs to be analyzed. After the air hammer head contacts the ground, its impact force on the ground continues to increase, but the ground's reaction force simultaneously pushes the hammer body upward, eventually causing it to move away from the ground. The ground's reaction force then begins to decrease to its lowest point, manifesting as a trough following the peak in the acceleration waveform. To more vividly illustrate this process, according to the displacement integral formula:

[0069] d=∫vdt

[0070] The displacement waveform can be calculated from the original velocity waveform. The acceleration, velocity and displacement waveforms are displayed simultaneously on Figure 8 middle, Figure 8 The middle blue curve represents the acceleration, the red represents the velocity, and the yellow represents the displacement. As can be seen, after the hammer's acceleration reaches its maximum, it begins to decrease while continuing its upward displacement. When the acceleration drops below zero, the hammer begins to decelerate. After the acceleration reaches its lowest point, the hammer stops rising and begins its downward descent. This data fully explains the hammer's various instantaneous operating states, and the acceleration trough, t2, is determined as the time when the hammer ends its impact with the ground.

[0071] In summary, t1 to t2 is the hammering time of the air hammer. Taking the midpoint time as an example, it is:

[0072]

[0073] t3 is the moment when the hammer body of the air hammer falls to the ground and is triggered.

[0074] S4. Based on the trigger time t3, the seismic image data of the remaining valid recording channels are cut and aligned to obtain a seismic image profile; see the seismic image profile. Figure 9 , the unfiltered seismic image profile grayscale image is shown in 10.

[0075] S5. Perform spectrum analysis on the seismic image profile to determine the noise peak frequency, and then perform low-pass filtering to obtain a seismic image profile with significantly reduced noise.

[0076] Specifically, in the seismic trace, there is obvious high-frequency signal interference. To remove the high-frequency noise, a low-pass filter is used to filter the data. First, the data is subjected to spectrum analysis to obtain the frequency filter interface diagram, see Figure 11 ;

[0077] according to Figure 11As shown in Figure 1, the main frequency peaks are distributed at 30, 140, and 400 Hz. Seismic wavelets are generally unimodal, so the 140 and 400 Hz peaks are invalid noise interference and should be filtered out. The cutoff frequency is set to 140H to adapt to the noise characteristics under different geological conditions. The results after filtering are shown in Figure 1. Figure 12 .

[0078] After filtering, the data noise is reduced and obvious hyperbolic phase axes can be observed. In the grayscale display mode (see Figure 13 ), its phase axis is more obvious and easy to distinguish, and the data processing is completed.

[0079] Specifically, take the seismic image data obtained by excitation of a pneumatic hammer source in the high groundwater level area of ​​Jinnan District, Tianjin as an example, see Figure 14 The seismic image profile obtained after the above method is shown in Figure 15 Finally, the filtering is eliminated and the seismic image profile in grayscale display mode is shown in Figure 16 .

[0080] Based on the same inventive concept, the embodiments of the present application also provide a seismic image data processing device for a pneumatic hammer source, which can be used to implement the method described in the above embodiments, as described in the following embodiments. Since the principle of solving the problem by the seismic image data processing device for a pneumatic hammer source is similar to that of the seismic image data processing method for a pneumatic hammer source, the implementation of the seismic image data processing device for a pneumatic hammer source can refer to the implementation of the seismic image data processing method for a pneumatic hammer source, and the repeated parts will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceived.

[0081] The embodiment of the present invention provides a specific implementation of a pneumatic hammer source seismic image data processing device capable of implementing a pneumatic hammer source seismic image data processing method, including:

[0082] The data acquisition unit is used to connect the air hammer to several moving coil geophones. The air hammer strikes the ground in a single shot and collects and stores seismic image recording data through the moving coil geophones. One of the moving coil geophones is used as a trigger channel to record the excitation waveform of the air hammer for analyzing the moment when the air hammer body hits the ground. The remaining moving coil geophones are used as effective recording channels, corresponding to the seismic image recording data detected by the moving coil geophones.

[0083] The acceleration calculation unit is used to convert the excitation waveform of the air hammer recorded by the trigger channel into voltage data, regard the voltage data as velocity data, and obtain the acceleration waveform by taking its derivative;

[0084] The trigger moment calculation unit is used to set the length of the front and back time windows, detect the acceleration take-off moment according to the acceleration waveform and the front and back time window method, and use this moment as the trigger moment of the hammer body landing;

[0085] The seismic image section unit is used to cut and align the seismic image recording data of the remaining effective recording channels using the triggering moment as a reference to obtain a seismic image section;

[0086] The output unit is used to perform spectrum analysis on the seismic image section to determine the noise peak frequency, and then perform low-pass filtering to obtain a seismic image section with significantly reduced noise.

[0087] Preferably, the embodiments of the present application further provide a specific implementation of an electronic device capable of implementing all steps of the method for processing seismic image data of a pneumatic hammer source in the above embodiment, wherein the electronic device specifically includes the following contents:

[0088] Processor, memory, communications interface, and bus;

[0089] Among them, the processor, memory, and communication interface communicate with each other through the bus; the communication interface is used to realize information transmission between related devices such as server-side devices, metering devices, and user-side devices.

[0090] The processor is used to call the computer program in the memory, and when the processor executes the computer program, all the steps of the seismic image data processing method of the air hammer source in the above embodiment are implemented.

[0091] An embodiment of the present application also provides a computer-readable storage medium capable of implementing all steps in the method for processing seismic imaging data of a pneumatic hammer source in the above-mentioned embodiment. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements all steps in the method for processing seismic imaging data of a pneumatic hammer source in the above-mentioned embodiment.

[0092] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences between the other embodiments. In particular, the hardware + program embodiments are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, refer to the description of the method embodiments.

[0093] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0094] Although the present application provides method operation steps such as embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-creative work. The order of steps listed in the embodiments is only one way of executing the steps among many steps and does not represent the only execution order. When an actual device or client product is executed, it can be executed in the order shown in the embodiments or the drawings or in parallel (for example, in a parallel processor or multi-threaded processing environment).

[0095] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0097] The present invention is not limited to the embodiments described above. The above description of the specific embodiments is intended to describe and illustrate the technical solutions of the present invention. The above specific embodiments are merely illustrative and not restrictive. Without departing from the scope of the present invention and the scope of protection of the claims, those skilled in the art may make various specific modifications based on the teachings of the present invention, all of which fall within the scope of protection of the present invention.

Claims

1. A method for processing seismic imaging data of an air hammer source, characterized in that: include: S1. Connect a pneumatic hammer to several moving-coil geophones. The hammer strikes the ground with a single shot, collecting and storing seismic image data through the moving-coil geophones. One of the moving-coil geophones is used as a trigger channel to record the hammer's excitation waveform for analysis of the moment the hammer hits the ground. The remaining moving-coil geophones are used as active recording channels, corresponding to the seismic image data detected by the moving-coil geophones. S2. The excitation waveform of the air hammer recorded by the trigger channel is voltage data. This voltage data is considered as velocity data and its derivative is used to obtain the acceleration waveform. S3. Set the length of the front and back time window, based on the acceleration waveform and the use of the front and back time window method to detect the acceleration take-off moment, and use this moment as the trigger moment for the hammer to land; S4. Based on the trigger time, the remaining effective recording channels of the seismic image data are cut and aligned to obtain a seismic image profile; S5. Performing spectrum analysis on the seismic image profile to determine the noise peak frequency, and then performing low-pass filtering to obtain a seismic image profile with significantly reduced noise.

2. The method for processing seismic image data of an air hammer source according to claim 1, characterized in that: In step S3, the calculation formula of the characteristic value h(t) of the front and back time windows is: Where w is the length of the previous and next time windows, x[n] represents the time series, and h(t) is the eigenvalue at time t when the previous and next time windows slide on the data axis.

3. The method for processing seismic image data of an air hammer source according to claim 1, characterized in that: In step S3 , the sampling rate is 2000 Hz, the full-wave width is 32 sampling points, corresponding to a duration of 16 ms, and the length of the front and rear time windows is w=16 ms.

4. The method for processing seismic image data of an air hammer source according to claim 1, characterized in that: The cutoff frequency of the low-pass filtering in step S5 is 120 Hz to 160 Hz to adapt to the noise characteristics under different geological conditions.

5. A seismic imaging data processing device for an air hammer source, characterized in that: include: The data acquisition unit is used to connect the air hammer to several moving coil geophones. The air hammer strikes the ground in a single shot and collects and stores seismic image recording data through the moving coil geophones. One of the moving coil geophones is used as a trigger channel to record the excitation waveform of the air hammer for analyzing the moment when the air hammer body hits the ground. The remaining moving coil geophones are used as effective recording channels, corresponding to the seismic image recording data detected by the moving coil geophones. The acceleration calculation unit is used to convert the excitation waveform of the air hammer recorded by the trigger channel into voltage data, regard the voltage data as velocity data, and obtain the acceleration waveform by taking its derivative; The trigger moment calculation unit is used to set the length of the front and back time windows, detect the acceleration take-off moment according to the acceleration waveform and the front and back time window method, and use this moment as the trigger moment of the hammer body landing; The seismic image section unit is used to cut and align the seismic image recording data of the remaining effective recording channels using the triggering moment as a reference to obtain a seismic image section; The output unit is used to perform spectrum analysis on the seismic image section to determine the noise peak frequency, and then perform low-pass filtering to obtain a seismic image section with significantly reduced noise.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for processing seismic image data of an air hammer source according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for processing seismic image data of an air hammer source according to any one of claims 1 to 4 are implemented.

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