On-site processing monitoring method suitable for controllable source frequency aliasing acquisition data

Abstract

The application provides a field processing monitoring method suitable for controllable source frequency division aliasing acquisition data, comprising: calculating low, medium and high frequency band field static correction amount; using the obtained field static correction amount to perform field static correction respectively; using the field static corrected data to perform denoising processing and surface consistency static correction on each frequency band respectively; using the processed and corrected wavelet to perform convolution processing on low, medium and high frequency band data; performing corresponding Q value compensation according to the time-frequency analysis of each frequency amount single shot; merging the processed frequency division data to obtain full frequency band data, using the full frequency band data to obtain a stack profile, and performing corresponding monitoring processing. The field processing monitoring method suitable for controllable source frequency division aliasing acquisition data can not only perform static correction, denoising, amplitude compensation and other conventional monitoring processes, but also solve the slope processing problem of the same frequency band junction after the merging of each frequency band.

Description

Technical Field

[0001] This invention relates to the field of oilfield seismic data processing technology, and in particular to a field processing and monitoring method suitable for controllable source frequency division and aliasing acquisition data. Background Technology

[0002] Currently, controlled-source efficient acquisition methods are receiving increasing attention and research as a way to achieve low-cost, high-density acquisition. Most of these methods rely on simultaneous excitation. However, due to the correlation of the simultaneously excited scanning signals, interference from adjacent shots and harmonic interference degrades the data quality. Therefore, a controlled-source frequency-division aliasing acquisition method is introduced. Utilizing the filtering characteristics of correlation algorithms, the target scanning signal is divided into several sub-scanning signals at different frequency bands. These sub-signals are independent in the frequency domain, and they are aliased and excited at any time. Correlation analysis yields precisely separated seismic single-shot data. Then, single shots from the same excitation point are superimposed to obtain full-band seismic single-shot data. Currently, there are no specific on-site processing and monitoring methods for this type of data.

[0003] Chinese patent application CN201410120974.3 discloses a method for processing seismic data based on VSP data. The method includes: compensating the amplitude of seismic data with reference to VSP data to obtain amplitude-compensated seismic data; using the downflow P-wave of the VSP data as a target wavelet and shaping the amplitude-compensated seismic data with reference to the target wavelet to obtain shaped seismic data; estimating the Q-values ​​of different layers using VSP data and statistically analyzing the Q-values ​​of different layers to obtain a global Q-value; applying inverse Q-filtering to the shaped seismic data using the global Q-value to obtain filtered seismic data; and performing zero-phase processing on the filtered seismic data through well matching to obtain zero-phase processed seismic data. This invention's method maintains amplitude fidelity and preserves the frequency of the seismic data during processing. The resulting processed seismic data profile clearly shows the wave group characteristics of each reflection layer, rich inter-layer information, and naturally stable waveforms.

[0004] Chinese patent application CN201410691159.2 discloses a method and system for determining seismic data acquisition parameters. The method includes: performing frequency-division scanning on raw seismic data to filter out effective seismic data time windows; obtaining the dominant seismic frequency band within the effective seismic data time window; calculating the correlation coefficient and linearity coefficient between the single-frequency wavelet spectrum and the theoretical wavelet spectrum of the corresponding frequency in the dominant seismic frequency band; and determining the seismic data acquisition parameters based on the correlation coefficient and linearity coefficient between the single-frequency wavelet spectrum and the theoretical wavelet spectrum of the corresponding frequency. This invention provides a method and system for determining seismic data acquisition parameters by quantitatively analyzing wavelet data and comprehensively comparing both correlation and linearity coefficients to determine the optimal seismic data acquisition parameters.

[0005] Chinese patent application CN201510272528.9 discloses a method for imaging controlled-source aliased data based on frequency-division dynamic coding. This method includes: Step 1, inputting the source and shot records; Step 2, reconstructing the source and receiver wavefields before coding by wavefield extension of the source and shot records; Step 3, inputting a frequency-division coding matrix; Step 4, encoding the source and receiver wavefields using the coding matrix; Step 5, imaging the encoded source and receiver wavefields; and Step 6, outputting the imaging results. This method for imaging controlled-source aliased data based on frequency-division dynamic coding can reduce crosstalk noise generated during aliased data migration and reduce the computational load of migration, thus improving efficiency.

[0006] The existing technologies described above are significantly different from the present invention and have failed to solve the technical problem we want to address. Therefore, we have invented a new on-site processing and monitoring method for controllable seismic source frequency division and aliasing acquisition data. Summary of the Invention

[0007] The purpose of this invention is to provide a field processing and monitoring method for controllable source frequency division and aliasing acquisition data that can perform conventional monitoring processes such as static correction, noise reduction, and amplitude compensation, and can also solve the slope handling problem at the boundary of the same frequency band after merging of various frequency bands.

[0008] The objective of this invention can be achieved through the following technical measures: a field processing and monitoring method for controllable source frequency-division aliasing acquisition data, comprising:

[0009] Step 1: Perform initial arrival picking using full-band data;

[0010] Step 2: Calculate the field static correction values ​​for low, medium, and high frequency bands using the acquired initial arrival values;

[0011] Step 3: Perform field static correction on the low-frequency data, medium-frequency data, and high-frequency data respectively using the obtained field static correction values;

[0012] Step 4: Using the statically corrected data from the field, perform noise reduction and surface uniformity static correction on each frequency band.

[0013] Step 5: Extract wavelets from each frequency-division data, perform wavelet processing, and use the processed and corrected wavelets to perform convolution processing on low, medium, and high frequency band data.

[0014] Step 6: Perform corresponding Q-value compensation based on the time-frequency analysis of each frequency division single shot;

[0015] Step 7: Merge the processed frequency-divided data to obtain full-band data, use the full-band data to obtain a superimposed profile, and perform corresponding monitoring processing.

[0016] The objective of this invention can also be achieved through the following technical measures:

[0017] The on-site processing and monitoring method applicable to controllable source frequency-division aliasing acquisition data also includes, before step 1, merging the low-frequency, medium-frequency, and high-frequency data acquired by the controllable source according to file number and channel number to obtain full-band data.

[0018] In step 1, when using full-band data to pick up the first arrival, a time window including the range of the first arrival is first drawn, and then the relevant picking parameters are set to pick up the first arrival. After picking up, manual intervention is used to modify any abnormal first arrivals.

[0019] In step 2, the field static correction amount is calculated using methods such as elevation static correction, refraction static correction, and tomographic static correction.

[0020] In step 2, static elevation correction is used for areas with flat terrain and little change in surface conditions; static refraction correction or static tomography correction is selected for areas with large changes in terrain elevation and large differences in surface velocity.

[0021] In step 4, when performing noise reduction, noise analysis is first performed on the low, medium, and high frequency band data respectively. Based on the noise characteristics of the low, medium, and high frequency band data, linear interference, external interference, and regional abnormal interference are attenuated in turn for each frequency band data.

[0022] In step 4, the linear interference attenuation uses the frequency-weighted denoising method. This method transforms the tx domain signal to the fx domain through Fourier transform. In the fx domain, weighted denoising is performed using the formula mix = velocity / (frequency * trace spacing). After denoising, the data is restored to the tx domain through inverse Fourier transform.

[0023] Where mix is ​​the weighting coefficient; velocity is the noise velocity; frequency is the noise frequency; and tracespacing is the track spacing.

[0024] In step 5, wavelets are extracted from each frequency-division data and processed. The processed and corrected wavelets are then used for convolution processing of low, medium, and high frequency band data. Wavelets are extracted from each frequency band data, and correlation processing is performed on the frequency of each frequency band wavelet signal to obtain the notch ratio range. A suitable value is calculated, and notch energy compensation is performed on the wavelet signals of the low, medium, and high frequency band data to obtain compensated wavelets. The compensated wavelets are then convolved with each frequency-division data to obtain the corrected wavelet data for each frequency band.

[0025] In step 6, Q-value compensation is performed based on the time-frequency analysis of each frequency division unit after processing, and energy loss in some frequency bands caused by defects in the acquired signal is compensated in a directional manner.

[0026] In step 7, the frequency and energy changes of the overall profile, the continuity and traceability of the phase axis of the target layer, and the identifiability in various structural interpretation processes are monitored.

[0027] The present invention provides a field processing and monitoring method for controlled-source frequency-division aliasing acquisition data. Utilizing the filtering characteristics of correlation algorithms, the target scanning signal is divided into several sub-scanning signals at different frequency bands. These sub-signals are independent in the frequency domain and are aliased and excited at any given time. Through correlation analysis, precisely separated seismic single-shot data can be obtained. Then, single-shot data from the same excitation point are superimposed to acquire full-band seismic single-shot data. This invention optimizes the processing of this seismic single-shot data, performing conventional procedures such as static correction, noise reduction, and amplitude compensation, while also addressing the slope problem at the boundaries of the same frequency bands after merging, resulting in an initial superposition monitoring profile that reflects the data quality. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a flowchart of a field processing and monitoring method for controllable seismic source frequency division and aliasing acquisition data in a specific embodiment of the present invention;

[0030] Figure 2This is a schematic diagram of low-frequency, mid-frequency, and high-frequency data obtained from controlled source frequency division and aliasing acquisition data, as well as the synthesized full-band data of the three frequency bands, in a specific embodiment of the present invention.

[0031] Figure 3 This is a comparison diagram of the superposition effects of full-band noise reduction and frequency-division noise reduction in a specific embodiment of the present invention;

[0032] Figure 4 This is a comparison diagram of the superimposed profile of full-band surface uniformity static correction and the superimposed effect of single-shot synthesis of frequency-division surface uniformity static correction in a specific embodiment of the present invention;

[0033] Figure 5 This is a schematic diagram of the synthesized wavelet waveform after wavelet correction and the synthesized wavelet waveform without wavelet correction obtained by extracting wavelets from data of each frequency band and performing wavelet processing on data of each frequency band in a specific embodiment of the present invention.

[0034] Figure 6 This is a schematic diagram comparing the superimposed spectrum of frequency-divided data obtained after wavelet correction and Q compensation processing with the superimposed spectrum of full-band acquired data in a specific embodiment of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In addition, the scope of protection of the present invention should not be limited to the specific steps described below.

[0036] This invention primarily addresses the acquisition method for controlled-source frequency-division aliasing data, as there is currently no specific on-site processing and monitoring method for this type of data. This frequency-division aliasing data differs from conventional on-site processed data; it exhibits a "notch" phenomenon when superimposing signals from different frequency bands. Therefore, this invention considers the slope handling problem at the intersection of different frequency bands. Furthermore, in on-site processing and monitoring, this invention performs corresponding processing on the data from each frequency band, optimizing the processing of this single-shot seismic data. This includes performing standard procedures such as static correction, noise reduction, and amplitude compensation, while also resolving the slope problem at the boundaries of the same frequency bands after merging, resulting in an initial superposition monitoring profile that reflects the data quality.

[0037] The following are several specific embodiments of the application of the present invention.

[0038] Example 1

[0039] In a specific embodiment 1 of the present invention, the on-site processing and monitoring method for controllable source frequency division aliasing acquisition data of the present invention may include:

[0040] (a) The low-frequency, mid-frequency, and high-frequency data acquired by the controllable seismic source are merged according to the file number and channel number to obtain full-band data;

[0041] (b) First arrival pickup using full-band data;

[0042] (c) Calculate the field static correction values ​​for low, medium and high frequency bands using the picked first arrivals;

[0043] (d) Perform field static correction on low-frequency data, medium-frequency data, and high-frequency data using the obtained field static correction values ​​respectively;

[0044] (e) Using the statically corrected data from the field, denoising is performed on each frequency band separately;

[0045] (f) Perform static surface consistency correction on each frequency band data after denoising;

[0046] (g) Extract wavelets from each frequency-division data, perform wavelet processing, and use the processed and corrected wavelets to perform convolution processing on low, medium, and high frequency band data.

[0047] (h) Perform corresponding Q-value compensation based on the time-frequency analysis of each frequency division single shot;

[0048] (i) The processed frequency-divided data are merged to obtain full-band data;

[0049] (j) Obtain overlay profiles using full-band data and perform corresponding monitoring and processing.

[0050] Using the full-band data obtained in step (a), when picking up the first arrival, first draw a time window that includes the range of the first arrival, then set the relevant picking parameters to pick up the first arrival. After picking up, manual intervention is used to modify any abnormal first arrivals.

[0051] The field static correction is obtained using the initial arrival data obtained in step (b). The optional methods for this step include elevation static correction, refraction static correction and tomographic static correction. Elevation static correction is used for areas with flat terrain and little change in surface conditions; refraction static correction or tomographic static correction is selected for areas with large changes in terrain elevation.

[0052] The steps for denoising the low, mid, and high frequency band data obtained in step (d) after field static correction may include: (e1) performing noise analysis on the low, mid, and high frequency band data respectively; (e2) based on the noise characteristics of the low, mid, and high frequency band data, attenuating linear interference, external interference, and regional anomaly interference in each frequency band in sequence. For linear interference attenuation, a frequency-weighted denoising method is used. This method transforms the tx-domain signal to the fx-domain using Fourier transform. In the fx-domain, weighted denoising is performed using the formula mix = velocity / (frequency * trace spacing). After denoising, the data is restored to the tx-domain using an inverse Fourier transform. Here, mix is ​​the weighting coefficient; velocity is the noise velocity; frequency is the noise frequency; and trace spacing is the trace spacing.

[0053] The data from each frequency band processed in step (f) is then convolved. The steps may include (g1) extracting wavelets from each frequency band data; (g2) performing correlation processing on the frequency of the wavelet signals in each frequency band to obtain the proportion range at the "notch"; (g3) calculating a suitable value based on the proportion range at the "notch" and performing energy compensation at the "notch" on the wavelet signals of the low, medium, and high frequency band data to obtain the compensated wavelets; and (g4) convolving the processed data with the data from each frequency band to obtain the wavelet-corrected data.

[0054] Example 2

[0055] In a specific embodiment 2 of the present invention, the present invention is applied. Figure 1 This is a flowchart of a field processing and monitoring method for controllable source frequency division aliasing acquisition data according to an embodiment of the present invention.

[0056] Reference Figure 1 In step 101, the low-frequency, mid-frequency, and high-frequency data acquired by the controllable seismic source are merged according to file number and channel number to obtain full-band data;

[0057] In step 102, first arrival picking is performed using full-band data. When picking the first arrival, a time window including the range of the first arrival is first drawn, and then the relevant picking parameters are set to pick the first arrival. After picking, manual intervention is used to modify any abnormal first arrivals.

[0058] In step 103, the low, medium and high frequency data are used to calculate the field static correction amount using the picked full-band first arrival. The calculation methods in this step include elevation static correction, refraction static correction and tomographic static correction. For areas with flat terrain and little change in surface conditions, elevation static correction is used; for areas with large changes in terrain elevation and large differences in surface velocity, refraction static correction or tomographic static correction method is selected.

[0059] In step 104, the low-frequency data, medium-frequency data, and high-frequency data are respectively subjected to field static correction using the obtained field static correction values;

[0060] In step 105, the noise reduction process is performed on each frequency band data after field static correction.

[0061] In step 105a, noise analysis is performed on the low, medium, and high frequency band data respectively;

[0062] In step 105b, based on the noise characteristics of the low, medium, and high frequency band data, noise attenuation is performed sequentially on each frequency band data, including linear interference, external interference, and regional anomaly interference. For linear interference attenuation, a frequency-weighted denoising method is used. This method transforms the tx-domain signal to the fx-domain using a Fourier transform. In the fx-domain, weighted denoising is performed using the formula mix = velocity / (frequency * trace spacing). After denoising, the data is restored to the tx-domain using an inverse Fourier transform. Here, mix represents the weighting coefficients; velocity represents the noise velocity; frequency represents the noise frequency; and trace spacing represents the channel spacing.

[0063] In step 106, surface consistency static correction is performed on each frequency band data after denoising;

[0064] In step 107, wavelets are extracted from each frequency-division data, and wavelet processing is performed. The processed and corrected wavelets are then used to perform convolution processing on the low, medium, and high frequency band data.

[0065] In step 107a, wavelets are extracted from the low, medium, and high frequency band data;

[0066] In step 107b, correlation processing is performed on the frequency of each frequency band wavelet signal to obtain the proportional range at the "notch" location;

[0067] In step 107c, a suitable value is calculated based on the proportion range at the "notch" location, and energy compensation is performed at the "notch" location on the low, medium, and high frequency band data wavelet signals to obtain the compensated wavelet.

[0068] In step 107d, the compensated wavelet is convolved with the data of each frequency band to obtain the corrected data of each frequency band wavelet.

[0069] In step 108, Q-value compensation is performed based on the time-frequency analysis of each frequency division single shot;

[0070] In step 109, the processed frequency-divided data are merged to obtain full-band data;

[0071] In step 110, a superimposed profile is obtained using full-band data, and corresponding monitoring and processing are performed. This includes monitoring the frequency and energy changes of the overall profile, the continuity and traceability of the phase axis of the target layer, and the identifiability in various structural interpretation processes.

[0072] Example 3

[0073] In a specific embodiment 3 of the present invention, according to the technical solution of the present invention, a field processing method for controllable source frequency division aliasing acquisition data includes the following steps:

[0074] In step 1, the low-frequency, mid-frequency, and high-frequency data acquired by the controllable seismic source are merged according to file number and channel number to obtain full-band data. Based on the characteristics of the source data, low-frequency data is affected by low-frequency noise, making first arrival difficult to identify; mid-frequency data has relatively good first arrival at near offsets, but far offsets are masked by noise; high-frequency data has weak energy, making first arrival barely identifiable at near offsets, while far offsets are completely mixed with background noise, making first arrival difficult to determine; however, the synthesized full-band data has relatively good first arrival records, which is beneficial for picking up first arrival information and providing accurate first arrival information for subsequent static correction problems. Therefore, first arrival picking should use synthesized full-band single-shot data from frequency-division aliasing data. Figure 2 ).

[0075] In step 2, first arrival picking is performed using full-band data. When picking the first arrival, a time window including the range of the first arrival is first drawn, and then the relevant picking parameters are set to pick the first arrival. After picking, manual intervention is used to modify any abnormal first arrivals.

[0076] In step 3, the field static correction amounts for low, medium, and high frequencies are calculated using the first arrival of the picked full-band frequencies. The calculation methods for this step include elevation static correction, refraction static correction, and tomographic static correction. For areas with flat terrain and little change in surface conditions, elevation static correction is used; for areas with large changes in terrain elevation and surface velocity, refraction static correction or tomographic static correction is selected.

[0077] In step 4, the low-frequency data, medium-frequency data, and high-frequency data are respectively subjected to field static correction using the obtained field static correction values;

[0078] In step 5, the noise reduction process is performed on the data of each frequency band after field static correction. First, noise analysis is performed on the low, medium and high frequency band data. Based on the noise characteristics of the low, medium and high frequency band data, noise such as linear interference, external interference and regional abnormal interference is attenuated on each frequency band data in turn. Figure 3 The image shows a comparison between the superposition effect after frequency division denoising and the superposition effect after full-band single-gun denoising using the proposed method. The comparison reveals that the superposition effect of synthesized single-gun after frequency division denoising is better than that of superposition after full-band single-gun denoising using the proposed method.

[0079] In step 6, surface consistency static correction is performed on each frequency band data after denoising; Figure 4 This image shows a comparison between the composite image of frequency-division single-shot data after static correction for surface consistency and the composite image of full-band single-shot data after static correction for surface consistency. The comparison shows that the composite image of frequency-division single-shot data after static correction for surface consistency is better than that of full-band single-shot data after static correction for surface consistency.

[0080] In step 7, wavelets are extracted from each frequency-division data and processed. The processed and corrected wavelets are then used for convolution processing of low, medium, and high frequency band data. Wavelets are extracted from each frequency band data, and correlation processing is performed on the frequency of each frequency band wavelet signal to obtain the proportion range at the "notch" location. A suitable value is calculated, and energy compensation is performed on the wavelet signals of the low, medium, and high frequency band data at the "notch" location to obtain the compensated wavelets. The compensated wavelets are then convolved with each frequency-division data to obtain the corrected wavelet data for each frequency band. Figure 5 In this embodiment of the invention, wavelets from data in each frequency band are extracted and processed to obtain a synthesized wavelet waveform after wavelet correction and an uncorrected synthesized wavelet waveform. The comparison shows that the synthesized wavelet waveform after wavelet correction is more stable than the uncorrected waveform, which is more beneficial for subsequent imaging processing.

[0081] In step 8, corresponding Q-value compensation is performed based on the time-frequency analysis of each frequency division single shot; corresponding Q-value compensation is performed based on the time-frequency analysis of each frequency division single shot after processing, and energy loss in some frequency bands caused by defects in the acquired signal is compensated in a directional manner. Figure 6 This diagram illustrates a comparison between the spectrum of the frequency-divided data stacked profile obtained after wavelet correction and Q-compensation processing and the spectrum of the full-band acquired data stacked profile. The comparison shows similar spectral analysis results, indicating that the notch filtering phenomenon has been resolved. The continuous short horizontal lines in the diagram represent the spectral analysis of the composite single-shot stacked profile of the controlled-source frequency-divided aliasing signal processing data; the continuous dotted lines represent the spectral analysis of the stacked profile of the controlled-source low-frequency, low-distortion signal full-band acquired data.

[0082] In step 9, the processed frequency-divided data are vertically superimposed to obtain full-band data;

[0083] In step 10, the overlay profile is obtained using full-band data and corresponding monitoring processing is performed.

[0084] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0085] Except for the technical features described in the specification, all other technologies are known to those skilled in the art.

Claims

1. A method for on-site processing and monitoring of data acquired by controlled-source frequency division and aliasing, characterized in that, The on-site processing and monitoring method applicable to controllable source frequency division and aliasing acquisition data includes: Step 1: Perform initial arrival picking using full-band data; Step 2: Calculate the field static correction values ​​for low, medium, and high frequency bands using the acquired initial arrival values; Step 3: Perform field static correction on the low-frequency data, medium-frequency data, and high-frequency data respectively using the obtained field static correction values; Step 4: Using the statically corrected data from the field, perform noise reduction and surface uniformity static correction on each frequency band. Step 5: Extract wavelets from each frequency-division data, perform wavelet processing, and use the processed and corrected wavelets to perform convolution processing on low, medium, and high frequency band data. Step 6: Perform corresponding Q-value compensation based on the time-frequency analysis of each frequency division single shot; Step 7: Merge the processed frequency-divided data to obtain full-band data, use the full-band data to obtain a superimposed profile, and perform corresponding monitoring processing.

2. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 1, characterized in that, The on-site processing and monitoring method applicable to controllable source frequency-division aliasing acquisition data also includes, before step 1, merging the low-frequency, medium-frequency, and high-frequency data acquired by the controllable source according to file number and channel number to obtain full-band data.

3. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 1, characterized in that, In step 1, when using full-band data to pick up the first arrival, a time window including the range of the first arrival is first drawn, and then the relevant picking parameters are set to pick up the first arrival. After picking up, manual intervention is used to modify any abnormal first arrivals.

4. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 1, characterized in that, In step 2, the field static correction amount is calculated using methods such as elevation static correction, refraction static correction, and tomographic static correction.

5. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 4, characterized in that, In step 2, static elevation correction is used for areas with flat terrain and little change in surface conditions; static refraction correction or static tomography correction is selected for areas with large changes in terrain elevation and large differences in surface velocity.

6. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 1, characterized in that, In step 4, when performing noise reduction, noise analysis is first performed on the low, medium, and high frequency band data respectively. Based on the noise characteristics of the low, medium, and high frequency band data, linear interference, external interference, and regional abnormal interference are attenuated in turn for each frequency band data.

7. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 6, characterized in that, In step 4, the linear interference attenuation uses the frequency-weighted denoising method. This method transforms the tx domain signal to the fx domain through Fourier transform. In the fx domain, weighted denoising is performed using the formula mix = velocity / (frequency * trace spacing). After denoising, the data is restored to the tx domain through inverse Fourier transform. Where mix is ​​the weighting coefficient; velocity is the noise velocity; frequency is the noise frequency; and trace spacing is the trace spacing.

8. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 1, characterized in that, In step 5, wavelets are extracted from each frequency-division data and processed. The processed and corrected wavelets are then used for convolution processing of low, medium, and high frequency band data. Wavelets are extracted from each frequency band data, and correlation processing is performed on the frequency of each frequency band wavelet signal to obtain the notch ratio range. A suitable value is calculated, and notch energy compensation is performed on the wavelet signals of the low, medium, and high frequency band data to obtain compensated wavelets. The compensated wavelets are then convolved with each frequency-division data to obtain the corrected wavelet data for each frequency band.

9. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 1, characterized in that, In step 6, Q-value compensation is performed based on the time-frequency analysis of each frequency division unit after processing, and energy loss in some frequency bands caused by defects in the acquired signal is compensated in a directional manner.

10. The on-site processing and monitoring method for controllable source frequency division and aliasing acquisition data according to claim 1, characterized in that, In step 7, the frequency and energy changes of the overall profile, the continuity and traceability of the phase axis of the target layer, and the identifiability in various structural interpretation processes are monitored.

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