Automatic identification and suppression method of seismic surface waves

Abstract

The present invention provides a method for automatic identification and suppression of seismic surface waves, comprising: step 1, performing time-frequency analysis on seismic single-shot records of different offset distances by using modified S transform according to original seismic single-shot records; step 2, performing synchronous automatic identification of surface wave distribution time, distribution frequency, distribution range, and distribution energy in the time-frequency-offset domain spectrum; step 3, extracting single-band seismic single-shot records in the modified S transform time-frequency spectrum; step 4, performing radial trace transformation on single-band seismic single-shot records; step 5, performing variable frequency dynamic filtering on different single-band seismic single-shot records in the radial trace transformation domain; step 6, performing radial trace inverse transformation on surface wave noise extracted from all single-band seismic single-shot records. The method for automatic identification and suppression of seismic surface waves fully considers the characteristics of frequency, apparent velocity, dispersion characteristics, and energy change, so as to better extract surface wave noise.

Description

Technical Field

[0001] The invention relates to the field of oil and gas geophysical seismic data processing, and in particular to a method for automatically identifying and suppressing seismic surface waves. Background Art

[0002] With the continuous deepening of oil and gas exploration and development, higher requirements are placed on the signal-to-noise ratio and resolution of seismic data. As a regular interference, seismic surface waves are commonly found in onshore seismic data. They are characterized by low frequency, strong energy, and low speed. The surface wave energy is about ten times the energy of the effective signal. It is distributed approximately linearly on the shot set, and the surface waves and effective signals are intertwined and overlapped. Surface waves are mainly distributed near the shot offset of seismic records. The traditional detector combination receiving method is conducive to suppressing surface waves. However, with the promotion and application of single-point high-density seismic technology, surface waves have seriously reduced the signal-to-noise ratio of seismic data. The effective signals in the seismic data are submerged in the noise, which seriously affects the quality of the seismic data. Surface wave suppression is a crucial step in the processing of seismic data.

[0003] In view of the low frequency, strong energy and low apparent velocity of surface waves, domestic and foreign scholars have proposed a large number of surface wave noise suppression methods. The current surface wave suppression methods mainly include:

[0004] The bandpass filtering method based on frequency difference designs a high-pass filter according to the frequency distribution range of surface waves in seismic data, sets the low cutoff frequency of the filter, filters the seismic data, and filters out the components below the low cutoff frequency, thereby realizing surface wave processing. The bandpass filtering method is relatively simple, but it filters out all effective signals below the low cutoff frequency, resulting in the loss of low-frequency effective signals. The frequency-space domain coherent noise attenuation method is performed on data in the surface wave frequency range, and estimates the surface waves at each frequency based on the minimum square error criterion. The area where surface waves appear is restricted by the two parameters of velocity and frequency, which has little impact on seismic signals outside the range.

[0005] Based on the frequency-wavenumber domain method of suppressing surface waves based on apparent velocity differences, the seismic data is subjected to a two-dimensional Fourier transform to obtain a frequency-wavenumber spectrum. Since there is a difference in apparent velocity between surface waves and effective signals, the low-frequency surface waves and effective signals are separated in the frequency-wavenumber spectrum. The surface wave area is cut off, and then a two-dimensional Fourier inverse transform is performed to obtain the seismic data without surface waves.

[0006] The adaptive surface roll attenuation method based on frequency and apparent velocity transforms the seismic data into the time-frequency domain. According to the differences in frequency, energy and spatial distribution range between surface rolls and effective signals, the distribution range of surface rolls in time and space is first detected. Then, according to the frequency band range of surface rolls, frequency division and weighted suppression of surface rolls are performed.

[0007] Patent CN104345341A proposes a frequency-band energy seismic surface wave processing method based on regional constraints. It uses wavelet transform to perform frequency division processing on seismic data, calculates the average amplitude value in different time windows and different frequency bands, and uses the cumulative superposition statistical analysis method to set the amplitude threshold value. The new amplitude value calculated by the suppression factor formula replaces the original amplitude value, thereby achieving surface wave suppression.

[0008] Patent CN104614769B proposes a beam filtering method for suppressing seismic surface waves. The method analyzes the spatial, temporal, and amplitude distribution of each frequency of the Rayleigh surface waves recorded in the seismic record, obtains the propagation characteristics of the Rayleigh surface waves through methods such as dispersion curve extraction, and then estimates and merges the results of the Fourier transform of the pulse sequence of the surface waves. A surface wave beam filtering method is constructed using determined parameters, and the effective signal after filtering can be obtained by taking the inverse Fourier transform of the filtered output data.

[0009] Patent CN105319591A proposes an SVD adaptive surface roll suppression method based on radial trace transformation, that is, firstly, radial trace transformation is used to move the surface roll frequency band to a lower frequency range, then low-pass filtering is used to obtain low-frequency surface roll signals in the radial trace domain, and then the singular value decomposition method is used to separate the effective low-frequency signals in the surface roll, and finally the surface roll is subtracted from the original data. Patent CN104375185A proposes a method and device for removing surface rolls from seismic records, which uses wavelet frequency division to obtain seismic records of different frequency bands, performs radial trace transformation on seismic records containing surface rolls, and then performs high-pass filtering, and finally performs wavelet reconstruction to obtain seismic records with surface rolls removed.

[0010] At present, the surface wave suppression method has two main shortcomings. On the one hand, the surface wave identification is inaccurate, and the data without surface waves are also processed, destroying the effective signal; on the other hand, the surface wave suppression loses the low-frequency effective signal. In the process of suppressing surface waves, the method of drawing time windows in the time-offset domain seismic single shot records has the shortcomings of large workload of time window picking and large influence of human factors. Usually, all data are processed, and the data without surface waves loses the effective signal during the processing. Through the frequency band processing method, radial trace transformation method or frequency-wavenumber domain surface wave suppression method, the difference characteristics of surface waves and effective signals in frequency and apparent velocity can be brought into play, but the effective signal in the low-frequency band is still lost, which is not conducive to subsequent data interpretation and reservoir inversion.

[0011] The above existing technologies are greatly different from the present invention and fail to solve the technical problem we want to solve. For this reason, we have invented a new method for automatic identification and suppression of seismic surface waves. Summary of the invention

[0012] The purpose of the present invention is to provide a method for automatically identifying and suppressing seismic surface waves by fully considering the characteristics of frequency, apparent velocity, dispersion characteristics and energy change, so as to better extract surface wave noise.

[0013] The purpose of the present invention can be achieved by the following technical measures: a method for automatically identifying and suppressing seismic surface waves, the method comprising:

[0014] Step 1, based on the original seismic single shot records, the modified S transform is used to perform time-frequency analysis on the seismic single shot records of different offsets;

[0015] Step 2, synchronously and automatically identifying the surface wave distribution time, distribution frequency, distribution range, and distribution energy in the time-frequency-offset domain spectrum;

[0016] Step 3, extracting single-band seismic single-shot records from the modified S-transform time spectrum;

[0017] Step 4, performing radial trace transformation on the single-band seismic single-shot record;

[0018] Step 5, according to the dispersion characteristics and energy variation characteristics of the surface wave, dynamic frequency filtering is performed on different single-band seismic single-shot records in the radial trace transformation domain;

[0019] Step 6: Perform radial trace inverse transformation on the surface wave noise extracted from all single-band seismic single-shot records.

[0020] The purpose of the present invention can also be achieved by the following technical measures:

[0021] In step 1, based on the original seismic single shot record, the modified S transform is used to perform time-frequency analysis on the seismic single shot records with different offsets. The time-frequency-offset domain spectrum calculation formula of the seismic single shot record is as follows:

[0022]

[0023] Where: s(t,offset) is the imported original seismic single-shot record with different offsets, t is time in ms, offset is offset in m; ST(α,fre,offset) is the time-frequency-offset domain spectrum of s(t,offset), α is the time position of the window function in ms, fre is the frequency in Hz; parameters β and λ are the adjustment parameters of the modified S transform.

[0024] In step 2, the four-synchronous automatic identification formulas of surface wave distribution time, distribution frequency, distribution range, and distribution energy are as follows:

[0025]

[0026] Among them: R(t,fre,w,eng) is the result of four-synchronous recognition, t is time, unit ms, fre is frequency, unit Hz, w is range, unit m, eng is energy, dimensionless unit; when the energy difference |ST(t i ,fre,w)|-|ST(t i-1 ,fre,w)|When the recognition condition is met, t1=t i , i is the number of sampling points, t2 is the length of seismic single shot record, in ms; when the energy difference |ST(t,fre j ,w)|-|ST(t,fre j-1 ,w)|When the recognition condition is met, fre1 is the starting frequency value, fre2=fre j , j is the time-frequency spectrum sampling interval, unit Hz; when the energy difference |ST(t,fre,w k )|-|ST(t,fre,w k-1 )|When the recognition conditions are met, w1 is the starting offset, w2=w k , k is the offset interval, unit is m; eng1 and eng2 are the distribution energy recognition ranges, which are calculated based on the energy of surface waves and effective signals in seismic single shot records.

[0027] In step 2, the seismic single shot record is decomposed into data containing surface roll data and data not containing surface roll data, and noise suppression is performed only on the data within the surface roll distribution time, distribution frequency, distribution range, and distribution energy, thereby protecting the effective signal from loss.

[0028] In step 3, the dispersion characteristics and energy variation characteristics of the surface wave are fully considered. The apparent velocity and energy of the surface wave in different frequency bands are different. The single-band seismic single-shot record is extracted from the modified S-transform spectrum, that is, the seismic single-shot record is decomposed into N single-band seismic single-shot records s j (t, offset), j = 1, 2, ..., N, N is the maximum frequency value of the surface roll distribution, t is the time, the unit is ms, and offset is the offset distance, the unit is m.

[0029] In step 4, radial trace transformation is performed on the single-frequency seismic single-shot record. The radial trace transformation formula of the single-frequency seismic single-shot record is as follows:

[0030]

[0031] Where: RT[] is the radial track transformation, s j (t, offset) is a single-band seismic single-shot record, t is time, unit ms, offset is offset distance, unit m; It is the data after radial track transformation, t0 is the starting time, in ms, and offset0 is the starting offset, in m.

[0032] In step 5, according to the dispersion characteristics and energy change characteristics of the surface wave, the frequency-variable dynamic filtering is performed on different single-band seismic single-shot records in the radial trace transform domain, taking into full account the characteristics of frequency, apparent velocity, dispersion characteristics and energy change. The frequency-variable dynamic filtering formula is as follows:

[0033] φ i,j,k =fre(fre1,fre2)×vel(vel1,vel2)×fv(fv1,fv2)×eng(eng1,eng2)

[0034] Among them: fre is frequency, unit Hz. Since the amplitudes of different frequencies moving to the low frequency band after radial trace transformation are different, different filter frequency values ​​are set in the processing of different single-frequency seismic single-shot records to realize variable frequency processing; vel is apparent velocity, unit m / s. After radial trace transformation, time-apparent velocity domain data is obtained. The distribution ranges of different apparent velocities are different. The apparent velocities of surface waves in different single-frequency seismic single-shot records are also different. The filtering parameters are set according to the apparent velocity range of surface waves; fv is dispersion characteristic, dimensionless unit. The propagation velocities of different frequencies in surface waves are different. The dispersion characteristics of single-frequency seismic single-shot records have their own characteristics. The filtering parameters are set according to the dispersion characteristics of different single-frequency bands; eng is energy, dimensionless unit. The surface wave energy of different single-frequency seismic single-shot records is different. Dynamic filtering processing is performed according to the energy distribution range.

[0035] In step 5, all single-band seismic single-shot records are subjected to variable frequency dynamic filtering to extract surface wave noise.

[0036] In step 6, the surface wave noise extracted from all single-band seismic single-shot records is subjected to radial trace inverse transformation, and the surface wave noise is subtracted from the original seismic single-shot records, thereby realizing automatic identification and suppression of the surface wave noise.

[0037] The method for automatic identification and suppression of seismic surface waves in the present invention uses modified S transform to perform time-frequency analysis on seismic single-shot records of different offset distances, and performs synchronous automatic identification of surface wave distribution time, distribution frequency, distribution range, and distribution energy in the time-frequency-offset distance domain. Through the four-synchronous automatic identification processing of surface wave distribution time, distribution frequency, distribution range, and distribution energy, the seismic single-shot record is decomposed into data containing surface waves and data not containing surface waves. In the subsequent processing process, only noise suppression is performed on the data containing surface waves, and the data not containing surface waves is not processed, thereby protecting the effective signal from loss to the greatest extent. In the process of surface wave suppression, the dispersion characteristics and energy change characteristics of the surface wave are fully considered. The apparent velocity and energy of the surface wave in different frequency bands are different. Therefore, the single-band seismic single-shot record is extracted from the modified S-transform spectrum, that is, the seismic single-shot record is decomposed into N single-band seismic single-shot records, N is the maximum frequency value of the surface wave, and the single-band seismic single-shot record is subjected to radial trace transformation. The radial trace transformation makes the surface wave frequency move to a lower frequency band. According to the dispersion characteristics and energy change characteristics of the surface wave, the different single-band seismic single-shot records are subjected to variable frequency dynamic filtering in the radial trace transformation domain, and the characteristics of frequency, apparent velocity, dispersion characteristics and energy change are fully considered, so as to better extract the surface wave noise. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of a specific embodiment of the method for automatic identification and suppression of seismic surface waves of the present invention;

[0039] Figure 2 A schematic diagram of processing a pre-seismic single shot record in a specific embodiment of the present invention;

[0040] Figure 3 It is a schematic diagram of a two-dimensional time-frequency spectrum of a seismic single shot record in a specific embodiment of the present invention;

[0041] Figure 4 It is a schematic diagram of a 10 Hz single-frequency seismic single-shot recording in a specific embodiment of the present invention;

[0042] Figure 5 It is a schematic diagram of radial trace transformation of 10 Hz single-frequency seismic single-shot recording in a specific embodiment of the present invention;

[0043] Figure 6 It is a schematic diagram of the result of denoising of a single-shot seismic record of 10 Hz single frequency in radial channel in a specific embodiment of the present invention;

[0044] Figure 7 It is a schematic diagram of the surface waves suppressed after the denoising process of the radial channel 10 Hz single-frequency seismic single-shot record in a specific embodiment of the present invention;

[0045] Figure 8It is a schematic diagram of surface wave noise interference suppressed in radial channel domain in a specific embodiment of the present invention;

[0046] Fig. 9 A schematic diagram of suppressed surface wave noise interference in a specific embodiment of the present invention;

[0047] Fig.10 It is a schematic diagram of a seismic single shot record after suppressing surface waves in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0048] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0049] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations and / or combinations thereof.

[0050] The method for automatic identification and suppression of seismic surface waves of the present invention comprises the following steps: firstly, using modified S transform to perform time-frequency analysis on seismic single shot records of different offsets, and synchronously and automatically identifying the surface wave distribution time, distribution frequency, distribution range and distribution energy in the time-frequency-offset domain, and only performing noise suppression on the data in the surface wave distribution time, distribution frequency, distribution range and distribution energy, thereby protecting effective signals from loss; secondly, extracting single-frequency-band seismic single shot records from the modified S transform time spectrum, that is, decomposing the seismic single shot records into N single-frequency-band seismic single shot records, where N is the maximum frequency value of the surface wave; then, performing radial trace transformation on the single-frequency-band seismic single shot records, performing variable frequency dynamic filtering in the radial trace transformation domain, and processing all single-frequency-band seismic single shot records, thereby extracting surface wave noise; finally, performing radial trace inverse transformation on the surface wave noise extracted from all single-frequency-band seismic single shot records, and subtracting the surface wave noise from the original seismic single shot records, thereby realizing automatic identification and suppression of surface wave noise.

[0051] In a specific embodiment 1 of the present invention, Figure 1 As shown, the method for automatic identification and suppression of seismic surface waves of the present invention comprises the following steps:

[0052] Step 1: Import the original seismic single shot record ( Figure 2 ), using modified S transform to perform time-frequency analysis on seismic single shot records at different offsets ( Figure 3), the time-frequency-offset domain spectrum calculation formula of a single seismic shot record is as follows:

[0053]

[0054] Where: s(t,offset) is the imported original seismic single-shot record with different offsets, t is time in ms, offset is offset in m; ST(α,fre,offset) is the time-frequency-offset domain spectrum of s(t,offset), α is the time position of the window function in ms, fre is the frequency in Hz; parameters β and λ are the adjustment parameters of the modified S transform.

[0055] Step 2: Perform synchronous automatic identification of the surface roll distribution time, distribution frequency, distribution range, and distribution energy in the time-frequency-offset domain spectrum. The formula for the four synchronous automatic identification of the surface roll distribution time, distribution frequency, distribution range, and distribution energy is as follows:

[0056]

[0057] Among them: R(t,fre,w,eng) is the result of four-synchronous recognition, t is time, unit ms, fre is frequency, unit Hz, w is range, unit m, eng is energy, dimensionless unit; when the energy difference |ST(t i ,fre,w)|-|ST(t i-1 ,fre,w)|When the recognition condition is met, t1=t i , i is the number of sampling points, t2 is the length of seismic single shot record, in ms; when the energy difference |ST(t,fre j ,w)|-|ST(t,fre j-1 ,w)|When the recognition condition is met, fre1 is the starting frequency value, fre2=fre j , j is the time-frequency spectrum sampling interval, unit Hz; when the energy difference |ST(t,fre,w k )|-|ST(t,fre,w k-1 )|When the recognition conditions are met, w1 is the starting offset, w2=w k , k is the offset interval, unit is m; eng1 and eng2 are the distribution energy recognition ranges, which are calculated based on the energy of surface waves and effective signals in seismic single shot records.

[0058] The seismic single shot record is decomposed into data containing surface wave and data without surface wave, and noise suppression is performed only on the data within the surface wave distribution time, distribution frequency, distribution range and distribution energy, so as to protect the effective signal from loss.

[0059] Step 3: Fully consider the dispersion characteristics and energy variation characteristics of surface waves. The apparent velocity and energy of surface waves in different frequency bands are different. In the modified S transform, the single-band seismic single-shot record is extracted from the spectrum, that is, the seismic single-shot record is decomposed into N single-band seismic single-shot records s j (t, offset), j = 1, 2, ..., N, N is the maximum frequency value of the surface roll distribution, t is the time, the unit is ms, and offset is the offset distance, the unit is m. Figure 4 This is a 10Hz single-frequency seismic single-shot record. The processing of a 10Hz single-frequency seismic single-shot record is taken as an example.

[0060] Step 4: Perform radial trace transformation on the single-band seismic single-shot record. The radial trace transformation formula for the single-band seismic single-shot record is as follows:

[0061]

[0062] Where: RT[] is the radial track transformation, s j (t, offset) is a single-band seismic single-shot record, t is time, unit ms, offset is offset distance, unit m; It is the data after radial track transformation, t0 is the starting time, in ms, and offset0 is the starting offset, in m.

[0063] The radial channel transformation makes the surface wave frequency move to a lower frequency band, which is beneficial to the suppression of surface wave noise. Figure 5 It is the radial trace transformation of 10Hz single-frequency seismic single-shot record.

[0064] Step 5: According to the dispersion characteristics and energy change characteristics of the surface wave, the frequency-variable dynamic filtering is performed on different single-band seismic single-shot records in the radial trace transform domain, taking into full account the characteristics of frequency, apparent velocity, dispersion characteristics and energy change. The frequency-variable dynamic filtering formula is as follows:

[0065] φ i,j,k =fre(fre1,fre2)×vel(vel1,vel2)×fv(fv1,fv2)×eng(eng1,eng2)

[0066] Among them: fre is frequency, unit Hz. Since the amplitudes of different frequencies moving to the low frequency band after radial trace transformation are different, different filter frequency values ​​are set in the processing of different single-frequency seismic single-shot records to realize variable frequency processing; vel is apparent velocity, unit m / s. After radial trace transformation, time-apparent velocity domain data is obtained. The distribution ranges of different apparent velocities are different. The apparent velocities of surface waves in different single-frequency seismic single-shot records are also different. The filtering parameters are set according to the apparent velocity range of surface waves; fv is dispersion characteristic, dimensionless unit. The propagation velocities of different frequencies in surface waves are different. The dispersion characteristics of single-frequency seismic single-shot records have their own characteristics. The filtering parameters are set according to the dispersion characteristics of different single-frequency bands; eng is energy, dimensionless unit. The surface wave energy of different single-frequency seismic single-shot records is different. Dynamic filtering processing is performed according to the energy distribution range. Figure 6 This is the result of denoising the 10Hz single-frequency seismic single-shot record in the radial domain. Figure 7 It is the suppressed surface wave after denoising of the 10Hz single-frequency seismic single-shot record in the radial channel.

[0067] All single-band seismic single-shot records are processed with variable frequency dynamic filtering to better extract surface wave noise. Figure 8 It is the surface wave noise interference suppressed in the radial channel domain.

[0068] Step 6: Perform radial trace inverse transformation on the surface wave noise extracted from all single-band seismic single-shot records. Fig. 9 To suppress the surface wave noise interference, the surface wave noise is subtracted from the original seismic single shot record. Fig.10 It is a seismic single shot record after suppressing surface waves, thus realizing the automatic identification and suppression of surface wave noise.

[0069] Embodiment 2:

[0070] In the specific embodiment 2 of the present invention, the method for automatic identification and suppression of seismic surface waves of the present invention comprises the following steps:

[0071] Step 1: Import the original seismic single shot record, and use the modified S transform to perform time-frequency analysis on the seismic single shot records with different offsets. The time-frequency-offset domain spectrum calculation formula of the seismic single shot record is as follows:

[0072]

[0073] Where: s(t,offset) is the imported original seismic single-shot record with different offsets, t is time, unit is ms, offset is offset, unit is m; ST(α,fre,offset) is the time-frequency-offset domain spectrum of s(t,offset), α is the time position of the window function, unit is ms, fre is the frequency, unit is Hz; parameters β and λ are the adjustment parameters of the modified S transform. The corresponding adjustment parameter size can be set according to the characteristics of different seismic data. Here, the values ​​are β=2.0 and λ=1.0.

[0074] Step 2: Automatically and synchronously identify the surface wave distribution time, distribution frequency, distribution range, and distribution energy in the time-frequency-offset domain spectrum.

[0075] Step 3: Fully consider the dispersion characteristics and energy variation characteristics of surface waves. The apparent velocity and energy of surface waves in different frequency bands are different. In the modified S transform, the single-band seismic single-shot record is extracted from the spectrum, that is, the seismic single-shot record is decomposed into N single-band seismic single-shot records s j (t, offset), j = 1, 2, ..., N, N is the maximum frequency value of the surface wave distribution, t is the time, unit is ms, offset is the offset distance, unit is m. According to the distribution frequency range of the surface wave, N is taken as 15, that is, the seismic single shot record is decomposed into 15 single frequency band data, namely 1Hz, 2Hz, 3Hz, ..., 15Hz single frequency band seismic single shot records.

[0076] Step 4: Perform radial trace transformation on 15 single-frequency seismic single-shot records.

[0077] Step 5: Perform variable frequency dynamic filtering in the radial trace transform domain and process 15 single-band seismic single-shot records to extract the surface wave noise.

[0078] Step 6: Perform radial trace inverse transformation on the surface wave noise extracted from 15 single-band seismic single-shot records, and subtract the surface wave noise from the original seismic single-shot records, thereby realizing automatic identification and suppression of surface wave noise.

[0079] Embodiment 3:

[0080] In the specific embodiment 3 of the present invention, the method for automatic identification and suppression of seismic surface waves of the present invention comprises the following steps:

[0081] Step 1: Import the original seismic single shot records and use the modified S transform to perform time-frequency analysis on the seismic single shot records of different offset distances.

[0082] Step 2: Perform synchronous automatic identification of the surface roll distribution time, distribution frequency, distribution range, and distribution energy in the time-frequency-offset domain spectrum. The formula for the four synchronous automatic identification of the surface roll distribution time, distribution frequency, distribution range, and distribution energy is as follows:

[0083]

[0084] Among them: R (t, fre, w, eng) is the four-synchronous recognition result, t is time, unit ms, fre is frequency, unit Hz, w is range, unit m, eng is energy, dimensionless unit. Figure 2 For the original seismic single-shot record, the surface wave has the characteristics of low speed, low frequency and strong energy. The identification of distribution time is to analyze each data, starting from time 0, using the energy ratio method to identify the appearance time of the surface wave. When the energy difference meets the conditions, the appearance time of the surface wave is identified. The identification of distribution frequency is to identify the surface wave from the frequency domain. When the energy difference meets the conditions, the maximum frequency value of the surface wave is identified. The identification of distribution range is to identify the surface wave from the offset domain. The surface wave is mainly distributed in the near offset. When the energy difference meets the conditions, the maximum offset of the surface wave distribution is identified.

[0085] Step 3: Fully consider the dispersion characteristics and energy variation characteristics of surface waves. The apparent velocity and energy of surface waves are different in different frequency bands. Extract the single-band seismic single-shot record from the frequency spectrum during the modified S transform.

[0086] Step 4: Perform radial trace transformation on single-frequency seismic single-shot records.

[0087] Step 5: According to the dispersion characteristics and energy variation characteristics of the surface wave, dynamic frequency filtering is performed on different single-band seismic single-shot records in the radial trace transformation domain.

[0088] Step 6: Perform radial trace inverse transformation on the surface wave noise extracted from all single-band seismic single-shot records, thereby realizing automatic identification and suppression of surface wave noise.

[0089] The present invention has two advantages. On the one hand, the modified S transform is used to perform time-frequency analysis on seismic single-shot records of different offset distances, and the surface wave distribution time, distribution frequency, distribution range, and distribution energy are synchronously and automatically identified in the time-frequency-offset domain. Through the four-synchronous automatic identification processing of the surface wave distribution time, distribution frequency, distribution range, and distribution energy, the seismic single-shot record is decomposed into data containing surface wave data and data not containing surface wave data. In the subsequent processing process, only the data containing surface wave data is subjected to noise suppression, and the data not containing surface wave data is not processed, thereby protecting the effective signal from loss to the greatest extent. On the other hand, in the process of surface wave suppression, the dispersion characteristics and energy change characteristics of the surface wave are fully considered. The apparent velocity of the surface wave is different in different frequency bands. Therefore, the single-band seismic single-shot record is extracted from the modified S-transform spectrum, that is, the seismic single-shot record is decomposed into N single-band seismic single-shot records, N is the maximum frequency value of the surface wave, and the single-band seismic single-shot record is subjected to radial trace transformation. The radial trace transformation makes the surface wave frequency move to a lower frequency band. According to the dispersion characteristics and energy change characteristics of the surface wave, the different single-band seismic single-shot records are subjected to variable frequency dynamic filtering in the radial trace transformation domain, and the four characteristics of frequency, apparent velocity, dispersion characteristics and energy change are fully considered, so as to better extract the surface wave noise.

[0090] Finally, 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 has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein with 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.

[0091] Except for the technical features described in the specification, all other technical features are known technologies to those skilled in the art.

Claims

1. A method for automatically identifying and suppressing seismic surface waves, characterized in that: The method for automatic identification and suppression of seismic surface waves comprises: Step 1: Based on the original seismic single shot records, the modified S transform is used to perform time-frequency analysis on the seismic single shot records with different offsets. The time-frequency-offset domain spectrum calculation formula of the seismic single shot records is as follows: Where: s(t,offset) is the imported original seismic single shot record with different offsets, t is time, unit is ms, offset is offset, unit is m; ST(α,fre,offset) is the time-frequency-offset domain spectrum of s(t,offset), α is the time position of the window function, unit is ms, fre is the frequency, unit is Hz; parameters β and λ are the adjustment parameters of the modified S transform; Step 2, synchronously and automatically identifying the surface wave distribution time, distribution frequency, distribution range, and distribution energy in the time-frequency-offset domain spectrum; Step 3, extracting a single-band seismic single-shot record from the modified S-transform time spectrum; Step 4, performing radial trace transformation on the single-band seismic single-shot record; Step 5, according to the dispersion characteristics and energy variation characteristics of the surface wave, dynamic frequency filtering is performed on different single-band seismic single-shot records in the radial trace transformation domain; Step 6: Perform radial trace inverse transformation on the surface wave noise extracted from all single-band seismic single-shot records.

2. The method for automatic identification and suppression of seismic surface waves according to claim 1, characterized in that: In step 2, the four-synchronous automatic identification formulas of surface wave distribution time, distribution frequency, distribution range, and distribution energy are as follows: Among them: R(t,fre,w,eng) is the result of four-synchronous recognition, t is time, unit ms, fre is frequency, unit Hz, w is range, unit m, eng is energy, dimensionless unit; when the energy difference |ST(t i ,fre,w)-ST(t i-1 ,fre,w) meets the recognition condition, t1=t i , i is the number of sampling points, t2 is the length of seismic single shot record, in ms; when the energy difference |ST(t,fre j ,w)-ST(t,fre j-1 ,w) When the recognition condition is met, fre1 is the starting frequency value, fre2=fre j , j is the time-frequency spectrum sampling interval, unit Hz; when the energy difference |ST(t,fre,w k )-ST(t,fre,w k-1 ) When the recognition conditions are met, w1 is the starting offset, w2 = w k , k is the offset interval, unit is m; eng1 and eng2 are the distribution energy recognition ranges, which are calculated based on the energy of surface waves and effective signals in seismic single shot records.

3. The method for automatic identification and suppression of seismic surface waves according to claim 2, characterized in that: In step 2, the seismic single shot record is decomposed into data containing surface roll data and data not containing surface roll data, and noise suppression is performed only on the data within the surface roll distribution time, distribution frequency, distribution range, and distribution energy, thereby protecting the effective signal from loss.

4. The method for automatic identification and suppression of seismic surface waves according to claim 1, characterized in that: In step 3, the dispersion characteristics and energy variation characteristics of the surface wave are fully considered. The apparent velocity and energy of the surface wave in different frequency bands are different. The single-band seismic single-shot record is extracted from the modified S-transform spectrum, that is, the seismic single-shot record is decomposed into N single-band seismic single-shot records s j (t, offset), j = 1, 2, ", N, N is the maximum frequency value of the surface roll distribution, t is the time, the unit is ms, and offset is the offset distance, the unit is m.

5. The method for automatic identification and suppression of seismic surface waves according to claim 1, characterized in that: In step 4, radial trace transformation is performed on the single-frequency seismic single-shot record. The radial trace transformation formula of the single-frequency seismic single-shot record is as follows: Where: RT[] is the radial track transformation, s j (t, offset) is a single-band seismic single-shot record, t is time, unit ms, offset is offset distance, unit m; It is the data after radial track transformation, t0 is the starting time, in ms, and offset0 is the starting offset, in m.

6. The method for automatic identification and suppression of seismic surface waves according to claim 2, characterized in that: In step 5, according to the dispersion characteristics and energy change characteristics of the surface wave, the frequency-variable dynamic filtering is performed on different single-band seismic single-shot records in the radial trace transform domain, taking into full account the characteristics of frequency, apparent velocity, dispersion characteristics and energy change. The frequency-variable dynamic filtering formula is as follows: φ i,j,k =fre(fre1,fre2)×vel(vel1,vel2)×fv(fv1,fv2)×eng(eng1,eng2) Among them: fre is frequency, unit Hz. Since the amplitudes of different frequencies moving to the low frequency band after radial trace transformation are different, different filter frequency values ​​are set in the processing of different single-frequency seismic single-shot records to realize variable frequency processing; vel is apparent velocity, unit m / s. Time-apparent velocity domain data is obtained after radial trace transformation. The distribution ranges of different apparent velocities are different. The apparent velocities of surface waves in different single-frequency seismic single-shot records are also different. The filtering parameters are set according to the apparent velocity range of surface waves; fv is dispersion characteristic, dimensionless unit. The propagation velocities of different frequencies in surface waves are different. The dispersion characteristics of single-frequency seismic single-shot records have their own characteristics. The filtering parameters are set according to the dispersion characteristics of different single-frequency bands; eng is energy, dimensionless unit. The surface wave energy of different single-frequency seismic single-shot records is different. Dynamic filtering processing is performed according to the energy distribution range.

7. The method for automatic identification and suppression of seismic surface waves according to claim 6, characterized in that: In step 5, all single-band seismic single-shot records are subjected to variable frequency dynamic filtering to extract surface wave noise.

8. The method for automatic identification and suppression of seismic surface waves according to claim 1, characterized in that: In step 6, the surface wave noise extracted from all single-band seismic single-shot records is subjected to radial trace inverse transformation, and the surface wave noise is subtracted from the original seismic single-shot records, thereby realizing automatic identification and suppression of the surface wave noise.

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