Method, device, equipment and medium for automatically identifying and processing water and land inspection data

Abstract

The invention discloses a method, a device, equipment and a medium for automatically identifying and processing water and land inspection data, and belongs to the field of oil exploration data processing. The method comprises the following steps: firstly, setting a peak frequency threshold value, automatically identifying water and land detection data by using a high-low frequency energy spectrum ratio method, then carrying out integration processing on the water detection data, eliminating water and land detection frequency and phase difference, carrying out water and land detection cross-correlation processing on the basis, and solving a water and land detection calibration coefficient. And finally, using the calibration coefficient to obtain a water-land dual-detection merging result. The invention further provides a device for implementing the method, computer equipment and a computer readable storage medium. The method provided by the invention can automatically identify water and land detection information, comprehensively considers the amplitude, phase and frequency differences of water and land detection, and achieves a better dual-detection merging effect. The method can be applied to the water and land detection consistency processing technology.

Description

Technical Field

[0001] The invention belongs to the technical field of petroleum exploration, mining and development, and relates to a water and land inspection data merging and processing technology, specifically a method, device, equipment and medium for automatic identification and processing of water and land inspection data. Background Art

[0002] The surface conditions of shallow seas are complex, and the types of excitation and reception are complex. Data from the water-land transition zone and shallow sea areas are usually collected by alternating water and land detection or OBC collection. However, the seismic wavelets collected from water and land detection are very different. Therefore, consistency processing of water and land detection is the focus and difficulty of seismic data processing.

[0003] On the one hand, in the stage of acquiring and identifying water and land inspection data, SPS data or class report information is often relied upon. This method of acquiring and identifying data is prone to problems such as mismatches between water and land inspection identification and data, contradictions between SPS data and class report information, and incomplete records of SPS data and class report information, resulting in unsatisfactory consistency processing effects for water and land inspections. Distinguishing water and land inspections based solely on differences in the main frequency of the data is often greatly affected by acquisition conditions or noise interference, resulting in unreliable identification results.

[0004] On the other hand, when processing the consistency of water and land inspection, the phase of the water and land inspection data is generally matched, and the amplitude calibration coefficient is obtained on this basis to realize the merging of the two inspections. Due to the limitations of the method, the merging effect is often not ideal, and there are still obvious frequency differences after the water and land inspection processing, which affects the consistency processing effect. There are obvious differences in amplitude, phase and frequency between water and land inspection data. Only correcting one or two of the indicators cannot solve the consistency problem of water and land inspection well.

[0005] To sum up, how to correctly identify water inspection and land inspection data and solve the problems of amplitude, phase and frequency differences between water inspection data and land inspection data are the key to consistency processing. Summary of the invention

[0006] In order to solve the above deficiencies in the prior art, one purpose of the present invention is to provide a method for automatically identifying and processing water and land inspection data, so as to achieve the correct water and land inspection data identification of the collected data, and on this basis, to improve the double inspection consistency processing flow; another purpose of the present invention is to provide a device, a computer device and a computer-readable storage medium for running the above method. To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0007] A method for automatically identifying and processing water and land inspection data comprises the following steps performed in sequence:

[0008] S1. Automatic recognition of water and land inspection data

[0009] By first setting the peak frequency threshold and then using the high- and low-frequency energy spectrum ratio method, the water and land inspection data can be automatically identified;

[0010] S2. Water inspection data integration processing

[0011] Perform phase and frequency processing on the water inspection data identified in step S1;

[0012] S3. Cross-correlation processing of water and land inspection data

[0013] Performing cross-correlation operation on the water inspection data and the corresponding land inspection data processed in step S2, and picking up the amplitude ratio of water and land inspection from the output function;

[0014] S4. Calculate the water and land calibration coefficient

[0015] Obtaining the water and land inspection calibration coefficient according to the amplitude ratio of the water and land inspection obtained in step S3;

[0016] S5. Use the calibration coefficient of land and water inspection to realize the combination of double inspection

[0017] The water and land inspection calibration coefficients obtained in step S4 are used to realize dual inspection merging processing.

[0018] Furthermore, the specific operation of setting the peak frequency threshold in step S1 is: obtaining water and land inspection data with a time window greater than 500 milliseconds, setting the peak frequency threshold, and when the single-channel frequency in the water and land inspection data is greater than the peak frequency threshold, it is set to water inspection, and the remaining water and land inspection data are re-performed with water and land inspection identification based on the high- and low-frequency energy spectrum ratio method, wherein the peak frequency threshold range is: greater than the main frequency of a single gun for land inspection and less than the main frequency of a single gun for water inspection.

[0019] Furthermore, the operation of re-identifying the remaining water and land inspection data based on the high-low frequency energy spectrum ratio method is as follows: the low-frequency end and the high-frequency end of the remaining water and land inspection data are selected, and the root mean square amplitude values ​​of the two are calculated respectively, and the threshold value of the root mean square amplitude value of the low-frequency end frequency value / the root mean square amplitude value of the high-frequency end frequency value is set to A=30. When the ratio is less than A, it is set to water inspection, and when it is greater than or equal to A, it is set to land inspection, wherein,

[0020] The low frequency end range is: greater than 10Hz, less than the frequency value corresponding to 10db of the land inspection single-shot spectrum;

[0021] The high-frequency end range is: greater than the frequency value corresponding to 20db of the land inspection single-shot spectrum, and less than the frequency value corresponding to 20db of the water inspection single-shot spectrum.

[0022] Furthermore, in step S2, the water detection data identified in step S1 is integrated, and the acceleration information is converted into velocity information through integration processing, thereby realizing water detection phase and frequency processing.

[0023] Furthermore, step S10 is also included between step S1 and step S2. Step S10 is to perform pre-stack noise suppression processing on the water and land inspection data obtained in step S1, and perform water inspection data integration processing of step S2 on the water inspection data after the pre-stack noise suppression processing, wherein the pre-stack noise suppression processing only removes surface waves and abnormal amplitude interference, with the purpose of providing a better data basis for water inspection integration processing and obtaining the amplitude calibration coefficient of dual inspection data.

[0024] Furthermore, the cross-correlation processing of the water and land inspection data in step S3 is performed under the condition that it starts 50 milliseconds after the first arrival and the time window is greater than 1 second.

[0025] Furthermore, in step S4, the amplitude ratio of the water and land detection is subjected to Gauss-Seidel iterative decomposition calculation to obtain the water and land detection calibration coefficient;

[0026] In step S5, the formula for the dual-detection merging process is: Uplink wave U = V 陆检 +Scale*P 水检 .

[0027] The present invention also provides a device for automatically identifying and processing water and land inspection data, comprising:

[0028] Automatic identification unit for water and land inspection data: used to identify water and land inspection data by combining the setting of peak frequency threshold and high-low frequency energy spectrum ratio method;

[0029] Water inspection data integration processing unit: used to process the phase and frequency of the water inspection data identified by the water and land inspection data automatic identification unit;

[0030] Water and land inspection data cross-correlation processing unit: used to perform cross-correlation operation on each pair of land inspection data and water inspection data processed by the water inspection data integration processing unit, and pick up the amplitude ratio of water and land inspection from the output function;

[0031] Water and land inspection calibration coefficient determination unit: used to obtain the water and land inspection calibration coefficient by using the amplitude ratio of the water and land inspection obtained by the water and land inspection data cross-correlation processing unit;

[0032] Double inspection merging unit: used to realize double inspection merging processing of the water and land inspection calibration coefficients obtained by the water and land inspection calibration coefficient determination unit.

[0033] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for automatically identifying and processing water and land inspection data described in any one of the above items is implemented.

[0034] The present invention also provides a computer-readable storage medium, which stores a computer program for executing any of the above-mentioned methods for automatically identifying and processing water and land inspection data.

[0035] Due to the adoption of the above technical solution, the present invention has the following beneficial effects compared with the prior art:

[0036] (1) The method for automatic identification and processing of water and land inspection data proposed in the present invention innovatively applies the working principle of water and land inspection and spectrum difference. By setting the peak frequency threshold and combining the high-low frequency energy spectrum ratio method, a data-driven water and land inspection automatic identification method is proposed. The proportion of water inspection data identified is 96%, and the accuracy of water inspection identification is 100%, which provides an accurate data basis for subsequent water and land inspection data analysis and can verify the correctness of water and land inspection information identified by SPS data and class report information;

[0037] (2) The method for automatic identification and processing of water and land detection data proposed in the present invention optimizes the water detection data correction process, comprehensively considers the phase, frequency and amplitude differences of water and land detection, firstly integrates the water detection to eliminate the phase and frequency differences of water and land detection, and then obtains the amplitude matching coefficient with the land detection, thus realizing the matching of water and land detection and the merging of dual detection. The present invention solves the frequency difference problem existing in the previous methods, provides a better consistency processing technology, and significantly improves the consistency of sub-waves of data from different detector types;

[0038] (3) The device, computer equipment and computer-readable storage medium provided by the present invention can quickly and effectively realize automatic identification and processing of water and land inspection data. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0040] Figure 1 This is a schematic diagram of setting the peak frequency threshold in Example 1, wherein: Figure 1 a is the spectrum diagram of a single gun of land inspection, Figure 1 b is the spectrum diagram of a single shot of water inspection;

[0041] Figure 2 This is a typical spectrum diagram of a single land inspection gun in Example 1;

[0042] Figure 3 This is a typical spectrum diagram of a single shot of water inspection in Example 1;

[0043] Figure 4 This is a verification diagram of the automatic recognition effect of water and land inspection data in Example 1, where: Figure 4 a is the measured water inspection diagram, Figure 4 b is a water inspection map after automatic identification of water and land inspection data of the present invention;

[0044] Figure 5 This is a diagram for verifying the effect of water inspection data integration processing in Example 1, where: Figure 5 a is a single shot image collected alternately by water inspection and land inspection before water and land inspection matching processing. Figure 5 b is a single shot image collected alternately by water inspection and land inspection after water and land inspection matching;

[0045] Figure 6 This is a diagram for verifying the effect of double inspection merging in Example 1, where: Figure 6 a is a land inspection data map, Figure 6 b is the water inspection data map, Figure 6 c is the double inspection merged graph;

[0046] Figure 7 This is a water and land inspection consistency processing diagram before the water and land inspection matching processing in Example 1, where: Figure 7 a is the superimposed profile before water and land inspection matching processing. Figure 7 b is a schematic diagram of autocorrelation;

[0047] Figure 8 This is a diagram of the water and land inspection consistency processing using the conventional processing method in Example 1, wherein: Figure 8 a is the superimposed cross-section after conventional processing. Figure 8 b is a schematic diagram of autocorrelation;

[0048] Fig. 9 This is a diagram of the water and land inspection consistency processing using the method of the present invention in Example 1, wherein: Fig. 9 a is a superimposed cross-sectional view after being processed by the method of the present invention, Fig. 9 b is a schematic diagram of autocorrelation;

[0049] Fig.10 This is a diagram of the device for automatic identification and processing of water and land inspection data in Example 2, wherein: 1. a water and land inspection data automatic identification unit; 2. a water inspection data integration processing unit; 3. a water and land inspection data cross-correlation processing unit; 4. a water and land inspection calibration coefficient determination unit; 5. a double inspection merging unit. DETAILED DESCRIPTION

[0050] The present invention is further described in detail below through specific embodiments. It should be understood that the preferred embodiments described herein are only used to illustrate and understand the present invention, and are not used to limit the present invention.

[0051] Unless otherwise specified, the materials and reagents used in the examples of the present invention can be obtained from commercial sources. Experimental methods without specific conditions in the examples are usually carried out under conventional conditions or under conditions recommended by the manufacturer.

[0052] Example 1 A method for automatically identifying and processing water and land inspection data

[0053] This embodiment is a method for automatically identifying and processing water and land inspection data, including the following steps performed in sequence:

[0054] S1. Automatic recognition of water and land inspection data

[0055] Acquire water and land inspection data with a time window greater than 500 milliseconds. Set the peak frequency threshold according to the difference in peak frequencies of water and land inspection. In the data acquired in this embodiment, the main frequency of a single land inspection gun is about 40 Hz, and the main frequency of a single water inspection gun is about 65 Hz. Therefore, the peak frequency threshold is set to 55 Hz. Figure 1 As shown, Figure 1 The frequency corresponding to the vertical line in the middle is the set peak frequency threshold. Figure 1 The main frequency of the land inspection single gun shown in a is less than Figure 1 The main frequency of the single gun for water inspection shown in b;

[0056] When the frequency of a single channel in the water and land inspection data is greater than the set peak frequency threshold of 55Hz, it is set as water inspection. The remaining data is re-identified based on the high-low frequency energy spectrum ratio method. The low-frequency end and high-frequency end of the remaining data are selected. The low-frequency end range is: greater than 10Hz and less than 55Hz. Figure 2 As shown in the typical spectrum of a single land inspection gun, F1 is at 10Hz, F2 is the frequency value corresponding to 10db of the land inspection spectrum, and the frequency range between F1 and F2 is the low frequency end; the high frequency end range is: greater than 130Hz and less than 205Hz, such as Figure 2 Typical spectrum diagram of land inspection single gun and Figure 3 As shown in the typical spectrum of a single shot of water inspection, Figure 2 F3 is the frequency value corresponding to 20db of the land inspection spectrum. Figure 3 F4 is the frequency value corresponding to 20db of the water detection spectrum, and the frequency range between F3 and F4 is the high frequency end; according to The formula is used to calculate the root mean square amplitude of the two values ​​respectively. The threshold value is set as A=30, which is 10 times the root mean square amplitude of the low frequency end frequency value / the root mean square amplitude of the high frequency end frequency value. When the ratio is less than A, it is set to water detection. When it is greater than or equal to A, it is set to land detection.

[0057] S10. Prestack noise suppression processing

[0058] The water and land inspection data obtained in step S1 are subjected to pre-stack noise suppression processing, wherein the pre-stack noise suppression processing only removes surface waves and abnormal amplitude interference, with the purpose of providing a better data basis for water inspection integral processing and obtaining amplitude calibration coefficients of dual inspection data;

[0059] S2. Water inspection data integration processing

[0060] The water detection data after the pre-stack noise suppression process in step S10 is integrated, and the acceleration information is converted into velocity information through the following integral formula to realize the water detection phase and frequency processing.

[0061]

[0062] S3. Cross-correlation processing of water and land inspection data

[0063] Starting from 50 milliseconds after the first arrival, under the condition that the time window is greater than 1 second, a cross-correlation operation is performed on each pair of land detection data and the water detection data processed in step S2, and the amplitude ratio of the water and land detection is picked up from the output function, which is S ij =V ij / P ij ;

[0064] S4. Calculate the water and land calibration coefficient

[0065] According to the amplitude ratio of the water and land detection obtained in step S3, Gauss-Seidel iterative decomposition calculation is performed to obtain the water and land detection calibration coefficient Scale = V 陆检 / P 水检 ;

[0066] S5. Apply calibration coefficients to achieve dual inspection merging

[0067] The water and land calibration coefficients obtained in step S4 are used to realize the dual-inspection merging process, and the formula is: Upward wave U = V 陆检 +Scale*P 水检 .

[0068] Effect verification

[0069] The actual data of a domestic OBC work area were selected for effect verification. The surface conditions of the work area are complex. The terrain features are divided into three types of surfaces from north to south: coastal sand island land, tidal flats, and shallow sea. The land area of ​​the sand island is 21.19 km 2 , 79.38km of tidal flats 2 , trench and sea area 118.31km 2 , which is suitable for verifying the consistency of water and land detection sub-waves.

[0070] 1) Verification of the automatic recognition effect of water and land inspection data

[0071] The automatic identification method of water and land inspection data of the present invention is used to identify and distinguish water and land inspection data, and the effect is verified using the measured data of the OBC work area. The results are as follows: Figure 4 As shown, Figure 4 a is the measured water inspection diagram, Figure 4 b is the water inspection map after the water and land inspection data are automatically identified by the present invention. Figure 4It can be seen that the present invention can effectively identify water inspection data. According to: the water inspection data after the water and land inspection data are automatically identified by the present invention / the measured water inspection data, it can be obtained that the proportion of water inspection data identified is 96%, and the accuracy rate of water inspection identification is 100%.

[0072] II) Verification of the effect of water inspection data integration processing

[0073] The water detection data integration processing method of the present invention is used to perform consistency processing on the water and land detection phase and frequency, wherein:

[0074] Before the water and land inspection matching process, the water inspection and land inspection are alternately collected for single shots. Figure 5 As shown in a, Figure 5 In a, there are both water and land inspection data. The water inspection data has a high frequency, while the land inspection data has a low frequency. In addition, there is a phase difference between the water and land inspections, so there is an obvious boundary, which is manifested as the displacement of the event axis.

[0075] After the water and land inspections are matched, the water inspections and land inspections are alternately collected to collect single shots. Figure 5 As shown in b, after matching processing, the frequency of the water detection data has changed, becoming closer to that of the land detection data, and the phase has also changed, which is manifested in that the phase axis displacement phenomenon at the junction of the water and land detection is significantly improved, and the phase axis is more in line with the hyperbolic law;

[0076] In summary, the phase and frequency characteristics of the water inspection data after the water inspection integration processing of the present invention are consistent with those of the land inspection, which is suitable for consistency processing of data collected alternately by water and land inspections.

[0077] III) Verification of the effect of double inspection

[0078] Through the automatic identification of land and water inspection data in step S1 of this embodiment, land inspection data and water inspection data are obtained, respectively as follows: Figure 6 a and 6b, among which, the land inspection data is rich in low-frequency information, and the water inspection data is rich in high-frequency information;

[0079] And through steps S2 to S5 of this embodiment, firstly, the water detection phase and frequency matching are performed, and then the water and land detection amplitude calibration coefficients are obtained to realize the double detection merging. The obtained result is as follows: Figure 6 As shown in c, Figure 6 c It can be seen that after the merging process, the ringing interference of the stacked profile is effectively suppressed, and the autocorrelation shows that the consistency of the profile wavelet is significantly improved.

[0080] 4) Verification of the lateral consistency effect of the wavelet

[0081] After testing, it was found that within the selected OBC work area, there were obvious frequency and phase differences in the superimposed profiles of water and land inspection data, such as Figure 7 a The stacked sections before and after the water and land inspection matching process Figure 7 The autocorrelation of b is shown by Figure 7It can be seen that the autocorrelation shows obvious differences in the lateral consistency of the wavelets;

[0082] The conventional processing method only considers the phase difference between water and land detection. After the processing, there is still an obvious frequency difference. The conventional method of water detection phase shift 90 degrees and then amplitude matching is selected to compare the consistency processing of water and land detection. The results are as follows Figure 8 a conventional method to process the stacked sections and Figure 8 The autocorrelation of b is shown by Figure 8 It can be seen that the conventional method did not improve the lateral wavelet difference;

[0083] The method for automatically identifying and processing water and land inspection data of the present invention effectively solves the frequency and phase differences of water and land inspection data, such as Fig. 9 a The stacked sections after processing by the method of the present invention and Fig. 9 As shown in the autocorrelation diagram of b, Fig. 9 It can be seen that the lateral consistency of the wavelet is significantly improved after the processing.

[0084] Embodiment 2 A device for automatically identifying and processing water and land inspection data

[0085] Fig.10 FIG. 1 shows a device diagram for automatically identifying and processing water and land inspection data according to an embodiment of the present invention. Fig.10 As shown, the automatic identification and processing device for water and land inspection data includes:

[0086] Automatic identification unit 1 for water and land inspection data: used to identify water and land inspection data by combining the peak frequency threshold and the high-low frequency energy spectrum ratio method;

[0087] Water inspection data integration processing unit 2: used for performing phase and frequency processing on the water inspection data identified by the water and land inspection data automatic identification unit;

[0088] Water and land inspection data cross-correlation processing unit 3: used for performing cross-correlation operation on each pair of land inspection data and water inspection data processed by the water inspection data integration processing unit, and picking up the amplitude ratio of water and land inspection from the output function;

[0089] The water and land inspection calibration coefficient determination unit 4 is used to obtain the water and land inspection calibration coefficient by using the amplitude ratio of the water and land inspection obtained by the water and land inspection data cross-correlation processing unit;

[0090] The double inspection merging unit 5 is used to realize double inspection merging processing of the water and land inspection calibration coefficients obtained by the water and land inspection calibration coefficient determination unit.

[0091] Embodiment 3 A computer device

[0092] This embodiment provides a computer device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor to implement the above-mentioned method for automatic identification and processing of water and land inspection data.

[0093] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0094] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capability and / or instruction execution capability, and may control other components in the electronic device to perform desired functions. The processor is used to run the computer-readable instructions stored in the memory.

[0095] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0096] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0097] Embodiment 4 A computer readable storage medium

[0098] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for automatically identifying and processing water and land inspection data is implemented.

[0099] The computer-readable storage medium stores non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of various embodiments are executed.

[0100] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0101] It should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for automatically identifying and processing water and land inspection data, characterized in that: The method comprises the following steps in sequence: S1. Automatic recognition of water and land inspection data By first setting the peak frequency threshold and then using the high- and low-frequency energy spectrum ratio method, the water and land inspection data can be automatically identified; S2. Water inspection data integration processing Perform phase and frequency processing on the water inspection data identified in step S1; S3. Cross-correlation processing of water and land inspection data Performing cross-correlation operation on the water inspection data and the corresponding land inspection data processed in step S2, and picking up the amplitude ratio of water and land inspection from the output function; S4. Calculate the water and land calibration coefficient Obtaining the water and land inspection calibration coefficient according to the amplitude ratio of the water and land inspection obtained in step S3; S5. Use the calibration coefficient of land and water inspection to realize the combination of double inspection The water and land inspection calibration coefficients obtained in step S4 are used to realize dual inspection merging processing.

2. The method for automatic identification and processing of water and land inspection data as claimed in claim 1, characterized in that: The specific operation of setting the peak frequency threshold in step S1 is: obtaining water and land inspection data with a time window greater than 500 milliseconds, setting the peak frequency threshold, and when the single-channel frequency in the water and land inspection data is greater than the peak frequency threshold, it is set to water inspection, and the remaining water and land inspection data are re-performed with water and land inspection identification based on the high- and low-frequency energy spectrum ratio method; wherein the peak frequency threshold range is: greater than the main frequency of a single gun for land inspection and less than the main frequency of a single gun for water inspection.

3. The method for automatic identification and processing of water and land inspection data as claimed in claim 2, characterized in that: The operation of re-identifying the remaining water and land inspection data based on the high-low frequency energy spectrum ratio method is as follows: select the low-frequency end and the high-frequency end of the remaining water and land inspection data, calculate the root mean square amplitude values ​​of the two respectively, set: 10 times the root mean square amplitude value of the low-frequency end frequency value / the root mean square amplitude value of the high-frequency end frequency value The threshold value is A=30, when the ratio is less than A, it is set to water inspection, and when it is greater than or equal to A, it is set to land inspection; wherein, The low frequency end range is: greater than 10Hz, less than the frequency value corresponding to 10db of the land inspection single-shot spectrum; The high-frequency end range is: greater than the frequency value corresponding to 20db of the land inspection single-shot spectrum, and less than the frequency value corresponding to 20db of the water inspection single-shot spectrum.

4. The method for automatic identification and processing of water and land inspection data as claimed in claim 3, characterized in that: The step S2 is to perform channel integration on the water detection data identified in step S1 to achieve water detection phase and frequency processing.

5. The method for automatic identification and processing of water and land inspection data as claimed in claim 4, characterized in that: Step S10 is also included between step S1 and step S2. Step S10 is to perform pre-stack noise suppression processing on the water and land inspection data obtained in step S1, and perform water inspection data integration processing of step S2 on the water inspection data after the pre-stack noise suppression processing.

6. The method for automatic identification and processing of water and land inspection data as claimed in claim 5, characterized in that: The cross-correlation processing of the water and land inspection data in step S3 is performed under the condition that it starts 50 milliseconds after the first arrival and the time window is greater than 1 second.

7. The method for automatic identification and processing of water and land inspection data according to any one of claims 1 to 6, characterized in that: In the step S4, the amplitude ratio of the water and land detection is subjected to Gauss-Seidel iterative decomposition calculation to obtain the water and land detection calibration coefficient; In step S5, the formula for the dual-detection merging process is: Uplink wave U = V 陆检 +Scale*P 水检 .

8. A device for automatically identifying and processing water and land inspection data as claimed in any one of claims 1 to 7, characterized in that: include: Automatic identification unit for water and land inspection data: used to identify water and land inspection data by combining the setting of peak frequency threshold and high-low frequency energy spectrum ratio method; Water inspection data integration processing unit: used to process the phase and frequency of the water inspection data identified by the water and land inspection data automatic identification unit; Water and land inspection data cross-correlation processing unit: used to perform cross-correlation operation on each pair of land inspection data and water inspection data processed by the water inspection data integration processing unit, and pick up the amplitude ratio of water and land inspection from the output function; Water and land inspection calibration coefficient determination unit: used to obtain the water and land inspection calibration coefficient by using the amplitude ratio of the water and land inspection obtained by the water and land inspection data cross-correlation processing unit; Double inspection merging unit: used to realize double inspection merging processing of the water and land inspection calibration coefficients obtained by the water and land inspection calibration coefficient determination unit.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for automatically identifying and processing water and land inspection data according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for executing the method for automatically identifying and processing water and land inspection data according to any one of claims 1 to 7.

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