CN109884691B - Strong single frequency and random noise suppression method and system for seismic signals with mining - Google Patents
Strong single frequency and random noise suppression method and system for seismic signals with mining Download PDFInfo
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Abstract
The invention relates to a strong single frequency and random noise suppression method and system for an acquired seismic signal. The method comprises the steps of firstly suppressing strong single-frequency noise of a reference channel; then, reducing single-frequency noise energy of all gathers by adopting a method based on a cross-correlation theory; and finally, suppressing random noise and residual single-frequency noise in a time-frequency domain by a self-adaptive threshold method to obtain the cross-correlation record of the mining-following earthquake with high signal-to-noise ratio. The method realizes the automatic identification of the frequency coordinates corresponding to the strong single frequency, and compared with a method for identifying the frequency coordinates of the single frequency noise based on experience or manual identification, the method has the advantages that the influence of manual intervention is less, and the calculation cost is saved; the method adopts a method based on the cross-correlation theory to suppress the strong single-frequency energy of all the gathers at one time, and has higher operation efficiency compared with a method for suppressing noise channel by channel; through the obtained cross-correlation with high signal-to-noise ratio and the acquisition of the seismic records, higher-quality basic data can be provided for later imaging processing, and the imaging precision is improved.
Description
Technical Field
The invention relates to a method and a system for suppressing noise of seismic signals along with mining, belongs to the technical field of seismic exploration, and particularly relates to a method and a system for suppressing strong single frequency and random noise of seismic signals along with mining.
Background
The method is characterized in that the method adopts the mining-following seismic exploration technology, namely, in the process of carrying out seismic exploration on a working face, the energy of a coal cutting rock body of a coal mining machine is used as a seismic source to replace an explosive seismic source, and the seismic exploration is synchronously carried out along with the operation of the coal mining machine. The technical innovation can not only solve the problems of various potential safety hazards caused by explosive excitation, but also achieve the purpose of instantly detecting catastrophe geologic bodies such as instantaneous ground stress change, fault activation and the like caused by coal and rock mass mining, and simultaneously does not interfere with the normal operation of a coal mine.
Although the seismic exploration technology along with mining has many advantages, because the vibration energy of the coal mining machine cutting coal rock mass is far less than the energy generated by the excitation of explosives, the effective signal energy acquired along with the mining exploration mode is also lower than that of the traditional exploration mode adopting explosives as seismic sources, and because of long-time continuous detection, environmental noise (such as single-frequency interference, mechanical vibration interference, random interference and the like) is introduced more, so that the signal-to-noise ratio of acquired data is reduced, and the processing precision of subsequent frequency dispersion analysis, inversion imaging and the like is seriously influenced. In summary, before the subsequent work is performed, the signal-to-noise analysis and noise attenuation processing must be performed on the original collected signal. The signal-noise analysis of the actual data collected at any time shows that the signal quality is seriously influenced by strong single frequency and random noise.
In the prior art, a suppression method for strong single frequency and random noise in the seismic signals with the mining does not exist, and the application of the suppression method for the strong single frequency and the random noise in the general seismic signals to the processing of the seismic signals with the mining has many problems.
In the prior art, the strong single-frequency noise processing in general seismic signals is to repeat the following processing for each trace of seismic signals acquired by each detector: the method comprises the steps of firstly converting original data into a frequency domain, carrying out spectrum analysis on the original data, then marking single-frequency noise from a frequency spectrum and carrying out energy suppression on the single-frequency noise, and then converting the data after noise suppression into a time domain from the frequency domain. As the single-frequency noise suppression pretreatment is also carried out by adopting a trace-by-trace method along with the acquisition of the seismic signals, the calculation cost is increased to a certain extent, and the process of selecting the single-frequency noise depends on human intervention.
In the prior art, a denoising method based on time-frequency analysis is widely adopted for random noise suppression, and the basic idea is to repeat the following processing channel by channel for seismic signals acquired by each detector: the method comprises the steps of firstly converting original data into a time-frequency domain through time-frequency transformation, then selecting a proper threshold value in the time-frequency domain to attenuate noise by utilizing the characteristic that signals and noise have coefficient difference in the time-frequency domain, and then inversely transforming the time-frequency coefficient after noise attenuation to the time domain. However, in general, strong single-frequency noise interference exists in the seismic environment, and when the processing mode is adopted, the time-frequency coefficients of signals and noise are basically not different, so that an ideal denoising effect cannot be achieved.
In summary, a method and a system for suppressing strong single frequency and random noise of an acquired seismic signal are provided to solve the above problems, which are urgent needs to be solved in the technical field of seismic exploration with acquisition.
Disclosure of Invention
In order to solve the problems in the prior art, the invention discloses a strong single frequency and random noise suppression method and system for a seismic signal along with acquisition. The method and the system firstly suppress strong single-frequency noise of a reference channel, and then reduce the single-frequency noise energy of all channel sets by adopting a method based on a cross-correlation theory; and finally, suppressing random noise and residual single-frequency noise in a time-frequency domain by a self-adaptive threshold method to obtain the cross-correlation record of the mining-following earthquake with high signal-to-noise ratio.
The purpose of the invention is realized by the following technical scheme:
a method for strong single frequency and random noise suppression of a production seismic signal comprising the steps of:
a reference channel single-frequency noise suppression step, namely converting a reference channel into a frequency domain signal, then calculating an envelope, carrying out median filtering on the envelope, comparing the envelope with an original envelope to calculate a frequency coordinate corresponding to strong single-frequency noise, replacing the amplitude value of the original signal of the frequency coordinate with the amplitude after the median filtering, and converting the obtained new reference channel back to a time domain;
a trace set single-frequency noise suppression step, wherein a method based on a cross-correlation theory is adopted to reduce the single-frequency noise energy of all trace sets;
and a random noise suppression step, wherein random noise and residual single-frequency noise are suppressed in a time-frequency domain by a self-adaptive threshold method.
In at least one embodiment of the present invention, the reference channel single frequency noise suppression step specifically includes:
step 101, transferring a reference channel signal into a frequency domain;
102, respectively obtaining real part envelopes and imaginary part envelopes of frequency domain complex numbers through reference channel Hilbert transform;
103, carrying out median filtering on the envelope obtained in the step 102, and calculating a frequency coordinate corresponding to the strong single-frequency noise through residual calculation with the original envelope;
step 104, replacing the amplitude value corresponding to the coordinate obtained in step 103 with the amplitude after median filtering;
and 105, converting the frequency domain coefficient of the new reference channel obtained in the step 104 back to a time domain through inverse Fourier transform.
In at least one embodiment of the present invention, in the trace gather single frequency noise suppression step, the method based on the cross-correlation theory is implemented by using formula 1 to reduce the single frequency noise energy of all trace gathers:
NCcs＝|W(s)|2G(rc,s)G*(rss), formula 1;
in the formula, G (r)cS) represents the seismic source s to the reference trace (reference detector) rcThe reference trace here is a new reference trace calculated in the step of single-frequency noise suppression of the reference trace, G (r)sS) Green's function representing the seismic source s to other detectors, G*Denotes the complex conjugate of G, W(s) denotes the seismic source response factor, where the seismic source is the energy of the shearer cutting the coal rock, NCcsRepresenting the cross-correlation result, i.e., the seismic record after the single frequency noise energy is reduced.
In at least one embodiment of the invention, the random noise suppression step comprises the sub-steps of:
step 301, solving the time-frequency coefficient of the seismic record processed in the trace set single-frequency noise suppression step;
and 302, performing random noise and residual single-frequency noise suppression on the time-frequency coefficient according to the determined threshold lambda.
In at least one embodiment of the present invention, the threshold λ in step 302 is calculated based on the following equation:
wherein σ ═ mean [ | V [ ]s-median(Vs)|]/0.618. where mean represents the median operation, VsAnd k represents the number of the time-frequency coefficients participating in calculation.
A strong single frequency and random noise suppression system for a production-dependent seismic signal, comprising the following modules:
the reference channel single-frequency noise suppression module is used for converting a reference channel into a frequency domain signal, then calculating an envelope, carrying out median filtering on the envelope, comparing the envelope with an original envelope to calculate a frequency coordinate corresponding to strong single-frequency noise, replacing the amplitude value of the original signal of the frequency coordinate with the amplitude value after the median filtering, and converting the obtained new reference channel back to a time domain;
the trace set single-frequency noise suppression module reduces the single-frequency noise energy of all trace sets by adopting a method based on a cross-correlation theory;
and the random noise suppression module suppresses random noise and residual single-frequency noise in a time-frequency domain by a self-adaptive threshold method.
In at least one embodiment of the present invention, the reference channel single frequency noise suppression module performs the following steps:
step 101, transferring a reference channel signal into a frequency domain;
102, respectively obtaining real part envelopes and imaginary part envelopes of frequency domain complex numbers through reference channel Hilbert transform;
103, carrying out median filtering on the envelope obtained in the step 102, and calculating a frequency coordinate corresponding to the strong single-frequency noise through residual calculation with the original envelope;
step 104, replacing the amplitude value corresponding to the coordinate obtained in step 103 with the amplitude after median filtering;
and 105, converting the frequency domain coefficient of the new reference channel obtained in the step 104 back to a time domain through inverse Fourier transform.
In at least one embodiment of the present invention, in the trace gather single-frequency noise suppression module, the method based on the cross-correlation theory is implemented by using formula 1 to reduce the single-frequency noise energy of all trace gathers:
NCcs＝|W(s)|2G(rc,s)G*(rss), formula 1;
in the formula, G (r)cS) represents the seismic source s to the reference trace (reference detector) rcThe reference trace here is a new reference trace calculated in the step of single-frequency noise suppression of the reference trace, G (r)sS) Green's function representing the seismic source s to other detectors, G*Denotes the complex conjugate of G, W(s) denotes the seismic source response factor, where the seismic source is the energy of the shearer cutting the coal rock, NCcsRepresenting the cross-correlation result, i.e., the seismic record after the single frequency noise energy is reduced.
In at least one embodiment of the invention, the random noise suppression module performs the following sub-steps:
step 301, solving the time-frequency coefficient of the seismic record processed in the trace set single-frequency noise suppression step;
and 302, performing random noise and residual single-frequency noise suppression on the time-frequency coefficient according to the determined threshold lambda.
In at least one embodiment of the present invention, the threshold λ in step 302 is calculated based on the following equation:
wherein σ ═ mean [ | V [ ]s-median(Vs)|]/0.618. where mean represents the median operation, VsAnd k represents the number of the time-frequency coefficients participating in calculation.
Therefore, the invention has the following advantages: (1) automatically identifying the frequency coordinates corresponding to the strong single frequency of the seismic signals along with the mining, and having small influence of human intervention; (2) when the conventional shot gather record is reconstructed along with the acquisition of the seismic signals, the strong single-frequency energy of all the gathers is synchronously suppressed by adopting a method based on a cross-correlation theory at one time, so that the operation efficiency is high; (3) by suppressing random noise and strong single-frequency noise, the cross-correlation along-acquisition seismic records with high signal-to-noise ratio can be obtained, and higher-quality basic data can be provided for later imaging processing.
Description of the drawings:
FIG. 1 is a flow chart of the method for suppressing random noise and strong single-frequency noise of an earthquake with mining according to the present invention;
FIG. 2 is a graph of a simulated noiseless signal;
FIG. 3a is a seismic record with the noise free data of FIG. 2 supplemented with random noise having a signal to noise ratio of 5, and data from lanes 6, 7 and 8 supplemented with single frequency noise at 50 Hz;
FIG. 3b is a time-frequency analysis diagram of the 6 th trace in FIG. 3 a;
FIG. 3c is a diagram of denoising effect only by using a time-frequency transform-based method;
FIG. 4a is a graph showing the effect of reducing the single frequency noise energy of the 6 th, 7 th and 8 th channels by using a method based on the cross-correlation theory;
FIG. 4b is a time-frequency analysis diagram of the 6 th trace in FIG. 4 a;
FIG. 4c is a diagram illustrating the effect of suppressing random noise and residual single-frequency noise using a time-frequency transform-based method;
FIG. 5a is a graph of cross-correlation results for raw seismic data with mining;
FIG. 5b is a graph of the effect of reducing the single frequency noise energy of all gathers using a method based on cross-correlation theory;
FIG. 5c is a diagram of denoising effect of suppressing random noise and residual single-frequency noise by using a time-frequency transform-based method.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
As shown in FIG. 1, the basic steps of the method and system for suppressing strong single frequency and random noise of a seismic signal with mining according to the present invention are as follows:
step 1: suppressing strong single-frequency noise of the reference channel;
step 2: reducing single-frequency noise energy of all gathers by adopting a method based on a cross-correlation theory;
and step 3: and suppressing random noise and residual single-frequency noise in a time-frequency domain by a self-adaptive threshold method.
The above steps are described in detail below:
suppressing strong single-frequency noise of the reference channel in the step 1:
the method comprises the following steps:
step 101, the reference track is transferred into the frequency domain by the formula (1),
in the formula, S (ω) is a reference track converted into a frequency domain, S (t) is an original reference track in a time domain, i and e are an imaginary unit and a natural constant respectively, ω is frequency, and t represents time.
Step 102, respectively obtaining envelopes of a real part and an imaginary part of the frequency domain signal by using the formula (2):
e (ω) ═ abs [ S (ω) H (ω) ] formula (2)
Wherein the content of the first and second substances,
in the formula (2), the formula in the square brackets represents the hilbert transform for obtaining the signal s, abs represents the modulus for obtaining the complex number, i is an imaginary unit, and sgn represents a sign function.
103, performing median filtering on the envelope obtained in the step 102, and calculating a frequency coordinate corresponding to the strong single-frequency noise by comparing the envelope with the original envelope, wherein the median filtering is realized by the following formula (3):
m (x) mean [ f (x-k), (k e wi) ] formula (3)
In the formula, wi is a one-dimensional filtering window, k is an element coordinate in the window, and mean represents that numerical values in the window are sorted, and a sorted middle value is used for replacing a window center value.
Step 104, replacing the amplitude value of the original signal corresponding to the coordinates obtained in step 103 with the amplitude after median filtering;
step 105, the new reference track obtained in step 104 is inversely transformed back to the time domain by the formula (4), i.e. s in the formulan(t)。
Step 2, the method based on the cross-correlation theory is adopted to reduce the single-frequency noise energy of all the gathers, and the method is realized by the following formula (5):
NCcs＝|W(s)|2G(rc,s)G*(rss) formula (5)
In contrast to conventional mutual theory, in the formula, G (r)cS) represents the seismic source s to the reference trace (reference detector) rcThe reference trace here is the new reference trace calculated in step 1, G (r)sS) Green's function representing the seismic source s to other detectors, G*Denotes the complex conjugate of G, W(s) denotes the seismic source response factor, where the seismic source is the energy of the shearer cutting the coal rock, NCcsRepresenting the cross-correlation result, i.e., the seismic record after the single frequency noise energy is reduced.
Step 3, suppressing random noise and residual single-frequency noise in the time-frequency domain by a self-adaptive threshold method, comprising the following substeps:
step 301, the earthquake record NC calculated in the step 2 is recordedcsAnd (3) solving a time-frequency coefficient by substituting formula (6):
in the formula, V (m, n) is a time-frequency coefficient (in this embodiment, an example of wavelet coefficients is adopted), ψ (τ) is called a mother wavelet, the mother wavelet generates a wavelet transform of the participating signal after corresponding to the wavelet base by different time shift parameters m and scale parameter n, ψ*(τ) is the complex conjugate of the mother wavelet.
And 302, solving a threshold lambda through the formula (7), then reserving the time-frequency coefficient which is calculated in the step 301 and is larger than the threshold, and finally returning to a time domain to complete the suppression of the random noise and the residual single-frequency noise.
Wherein the parameter sigma is calculated by equation (8),
σ＝median[|Vs-median(Vs)|]/0.618, formula (8)
Wherein, mean represents the median operation, VsAnd k represents the number of the time-frequency coefficients participating in calculation.
Thus, suppression of random noise and strong single-frequency noise in the seismic data along with acquisition is completed, and the seismic record with high signal-to-noise ratio can be calculated.
The invention has the following beneficial effects:
1) the method realizes the automatic identification of the frequency coordinates corresponding to the strong single frequency, and compared with a method for identifying the frequency coordinates of the single frequency noise based on experience or manual work, the method has the advantages that the influence of manual intervention is less, and the calculation cost is saved;
2) the method adopts a method based on the cross-correlation theory to suppress the strong single-frequency energy of all the gathers at one time, and has higher operation efficiency compared with a method for suppressing noise channel by channel;
3) through the obtained cross-correlation with high signal-to-noise ratio and the acquisition of the seismic records, higher-quality basic data can be provided for later imaging processing, and the imaging precision is improved.
The invention is verified below by means of the model and the actual data, respectively.
First, a numerical simulation was performed to carry out verification on the method of the present embodiment:
in order to verify the accuracy of the method, noiseless data is simulated firstly, the total number of the simulated data is 12, the sampling rate is 0.5 millisecond, and the acquisition time is 1000 milliseconds. As shown in fig. 2.
Fig. 3 is a diagram showing the effect of suppressing random noise and single-frequency noise on analog data by using a time-frequency analysis-based method, in which:
FIG. 3a is a seismic record with the noise free data of FIG. 2 supplemented with random noise having a signal to noise ratio of 5, and data from lanes 6, 7 and 8 supplemented with single frequency noise at 50 Hz;
FIG. 3b is the time-frequency analysis diagram of the 6 th trace in FIG. 3a, which shows that there is stronger energy at 50 Hz;
fig. 3c shows that a single-frequency interference noise still remains in the record only by using the denoising result based on the time-frequency transform method, and if the threshold coefficient is continuously increased to suppress the single-frequency noise, an effective signal is lost.
Fig. 4 is a diagram illustrating the effect of suppressing random noise and single-frequency noise on analog data by the method of the present invention, wherein:
FIG. 4a is a diagram illustrating the effect of the method for reducing the energy of the 6 th, 7 th and 8 th channels of single frequency noise by using the method based on the cross-correlation theory in this patent, and compared with FIG. 3a, the energy of the single frequency signal is suppressed to a great extent;
FIG. 4b is the time spectrum corresponding to trace 6 in FIG. 4a, from which it can be seen that the single frequency noise energy is greatly attenuated;
fig. 4c is an effect diagram of suppressing random noise and residual single-frequency noise by using a time-frequency transform-based method. As can be seen by comparing the noise-free data of fig. 2, the random noise and the strong single-frequency noise are substantially suppressed.
Secondly, the method designed by the embodiment is verified through actually acquired low signal-to-noise ratio data:
fig. 5 is a diagram of suppression effect of random noise and single-frequency noise of actual data with data, where:
FIG. 5a is the cross-correlation result of the original acquired seismic data, where it can be seen that the recorded signal-to-noise ratio is severely affected by random noise and strong single-frequency interference.
FIG. 5b is a diagram showing the effect of reducing the single-frequency noise energy of all gathers by the method based on the cross-correlation theory of the present invention, wherein compared with FIG. 5a, the single-frequency noise is suppressed to a large extent;
fig. 5c is a denoising result diagram for suppressing random noise and residual single-frequency noise by using a time-frequency transform-based method, and compared with fig. 5a, the signal-to-noise ratio recorded by cross-correlation is greatly improved, which proves the effect of the embodiment.
Finally, it should be noted that the above numerical simulation and actual data collection calculation examples provide further verification for the purpose, technical solution and advantages of the present invention, which only belong to the specific embodiment examples of the present invention, and are not intended to limit the scope of the present invention, and any modification, improvement or equivalent replacement made within the spirit and principle of the present invention should be within the scope of the present invention.
Claims (10)
1. A method for strong single frequency and random noise suppression of a production seismic signal comprising the steps of:
a reference channel single-frequency noise suppression step, namely converting a reference channel into a frequency domain signal, then calculating an envelope, carrying out median filtering on the envelope, comparing the envelope with an original envelope to calculate a frequency coordinate corresponding to strong single-frequency noise, replacing the amplitude value of the original signal of the frequency coordinate with the amplitude after the median filtering, and converting the obtained new reference channel back to a time domain;
a trace set single-frequency noise suppression step, wherein a method based on a cross-correlation theory is adopted to reduce the single-frequency noise energy of all trace sets;
and a random noise suppression step, wherein random noise and residual single-frequency noise are suppressed in a time-frequency domain by a self-adaptive threshold method.
2. The method according to claim 1, wherein the reference channel single frequency noise suppression step specifically comprises:
step 101, transferring a reference channel signal into a frequency domain;
102, respectively obtaining real part envelopes and imaginary part envelopes of frequency domain complex numbers through reference channel Hilbert transform;
103, carrying out median filtering on the envelope obtained in the step 102, and calculating a frequency coordinate corresponding to the strong single-frequency noise through residual calculation with the original envelope;
step 104, replacing the amplitude value corresponding to the coordinate obtained in step 103 with the amplitude after median filtering;
and 105, converting the frequency domain coefficient of the new reference channel obtained in the step 104 back to a time domain through inverse Fourier transform.
3. The method for strong single frequency and random noise suppression of seismic signals with mining according to claim 1, wherein in the trace gather single frequency noise suppression step, the method based on the cross-correlation theory is implemented to reduce the single frequency noise energy of all trace gathers by equation 1:
NCcs＝|W(s)|2G(rc,s)G*(rss) formula 1;
in the formula, G (r)cS) represents the seismic source s to the reference trace rcThe reference trace here is a new reference trace calculated in the step of single-frequency noise suppression of the reference trace, G (r)sS) Green's function representing the seismic source s to other detectors, G*Denotes the complex conjugate of G, W(s) denotes the seismic source response factor, where the seismic source is the energy of the shearer cutting the coal rock, NCcsRepresenting the cross-correlation result, i.e., the seismic record after the single frequency noise energy is reduced.
4. A method of strong single frequency and random noise suppression for a mined seismic signal according to claim 1, characterized in that the random noise suppression step comprises the substeps of:
step 301, solving the time-frequency coefficient of the seismic record processed in the trace set single-frequency noise suppression step;
and 302, performing random noise and residual single-frequency noise suppression on the time-frequency coefficient according to the determined threshold lambda.
5. A method of strong single frequency and random noise suppression for a mined seismic signal as claimed in claim 4 wherein the threshold λ in step 302 is calculated based on the equation:
in the formula, σ＝median[|Vs-median(Vs)|]/0.618, where mean represents the median operation, VsAnd k represents the number of the time-frequency coefficients participating in calculation.
6. A strong single frequency and random noise suppression system for a production-dependent seismic signal, comprising the following modules:
the reference channel single-frequency noise suppression module is used for converting a reference channel into a frequency domain signal, then calculating an envelope, carrying out median filtering on the envelope, comparing the envelope with an original envelope to calculate a frequency coordinate corresponding to strong single-frequency noise, replacing the amplitude value of the original signal of the frequency coordinate with the amplitude value after the median filtering, and converting the obtained new reference channel back to a time domain;
the trace set single-frequency noise suppression module reduces the single-frequency noise energy of all trace sets by adopting a method based on a cross-correlation theory;
and the random noise suppression module suppresses random noise and residual single-frequency noise in a time-frequency domain by a self-adaptive threshold method.
7. A strong single frequency and random noise suppression system for a mined seismic signal according to claim 6 wherein the reference channel single frequency noise suppression module performs the steps of:
step 101, transferring a reference channel signal into a frequency domain;
102, respectively obtaining real part envelopes and imaginary part envelopes of frequency domain complex numbers through reference channel Hilbert transform;
103, carrying out median filtering on the envelope obtained in the step 102, and calculating a frequency coordinate corresponding to the strong single-frequency noise through residual calculation with the original envelope;
step 104, replacing the amplitude value corresponding to the coordinate obtained in step 103 with the amplitude after median filtering;
and 105, converting the frequency domain coefficient of the new reference channel obtained in the step 104 back to a time domain through inverse Fourier transform.
8. The strong single frequency and random noise suppression system for seismic signals with mining according to claim 6, wherein in the gather single frequency noise suppression module, the single frequency noise energy of all gathers is reduced by a method based on the cross-correlation theory implemented by equation 1:
NCce＝|W(s)|2G(rc，s)G*(rss), formula 1;
in the formula, G (r)cS) represents the seismic source s to the reference trace rcThe reference trace here is a new reference trace calculated in the step of single-frequency noise suppression of the reference trace, G (r)sS) Green's function representing the seismic source s to other detectors, G*Denotes the complex conjugate of G, W(s) denotes the seismic source response factor, where the seismic source is the energy of the shearer cutting the coal rock, NCcsRepresenting the cross-correlation result, i.e., the seismic record after the single frequency noise energy is reduced.
9. A strong single frequency and random noise suppression system for a mined seismic signal according to claim 6 wherein the random noise suppression module performs the substeps of:
step 301, solving the time-frequency coefficient of the seismic record processed in the trace set single-frequency noise suppression step;
and 302, performing random noise and residual single-frequency noise suppression on the time-frequency coefficient according to the determined threshold lambda.
10. A strong single frequency and random noise suppression system for a mined seismic signal as claimed in claim 9 wherein the threshold λ in step 302 is calculated based on the equation:
wherein σ ═ mean [ | V [ ]s-median(Vs)|]/0.618, where mean represents the median operation, VsAnd k represents the number of the time-frequency coefficients participating in calculation.
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