CN117590470B - Surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation - Google Patents
Surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation Download PDFInfo
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Abstract
The invention discloses a surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation, which belongs to the technical field of earth detection and information, and comprises the following steps: the method comprises the steps of inputting seismic data, obtaining enhanced surface wave signals after gain, denoising and excision, carrying out multiple synchronous compression conversion on each channel of the surface wave data to a time-frequency domain, and merging time-frequency domain data of each channel to generate a three-dimensional time-frequency data body; extracting common-frequency slice data from the three-dimensional time-frequency data volume; calculating superposition energy of different speeds in the surface wave group velocity interval by adopting a similar coefficient method inclined scanning superposition mode for the common-frequency slice data; and combining the superposition energy of different surface wave group velocities with different frequencies to obtain a final surface wave dispersion energy diagram. The invention adopts the above-mentioned surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation, obviously improves the resolution and noise immunity of the surface wave group velocity dispersion spectrum, and has higher calculation efficiency.
Description
Technical Field
The invention relates to the technical field of earth detection and information, in particular to a surface wave group velocity dispersion energy imaging method based on multiple synchronous compression conversion.
Background
The shear wave velocity is a very important parameter for near-surface geotechnical engineering, and the accuracy of the shear wave velocity is very important for hydrogeology and engineering geology. Seismic surface waves are one of the important methods for non-destructive acquisition of near-surface shear wave velocities. The current seismic surface wave method is mainly obtained by utilizing phase velocity inversion calculation of Rayleigh waves, most researches are focused on the phase velocity dispersive energy imaging, and few researches are conducted on the group velocity dispersive energy imaging. In recent years, some experts at home and abroad have studied group velocity dispersion energy, and main methods include a multiple filtering method, a wavelet transformation method and a time-frequency analysis method based on S transformation. However, the methods have the defects of low resolution, poor robustness, large calculated amount and the like of the dispersion energy diagram.
The prior wave group velocity dispersion energy imaging method comprises a multiple filtering method, a wavelet transformation method and a time-frequency analysis method based on S transformation. However, the methods have the defects of low resolution, poor robustness, large calculated amount and the like of the dispersion energy diagram. Multiple filtering methods, as are currently more common, employ a series of bandpass filters on the seismic record and calculate the envelope of the resulting signal to estimate the group velocity. The method uses the center frequency of the band pass filter or the instantaneous frequency of the envelope as the frequency at which the group velocity is calculated. The method has the defects of poor energy focusing property and large group velocity calculation error at a low frequency end. The S-transformation-based time-frequency analysis method obtains higher time-frequency resolution and improves the accuracy of low-frequency band dispersion curve estimation by adjusting the width of a Gaussian time window, but in practice, the method is found to be poor in surface wave multi-mode time-frequency dispersion imaging effect, low in resolution and very difficult to adjust time window parameters.
Disclosure of Invention
The invention aims to provide a surface wave group velocity dispersion energy imaging method based on multiple synchronous compression conversion, which is mainly improved in two links compared with other methods: (1) The resolution of the surface wave group velocity spectrum is remarkably improved by adopting a multiple compression conversion method with greatly improved time spectrum and higher calculation efficiency from the time-frequency analysis link, and the method has higher calculation efficiency; (2) The similarity coefficient method is adopted in the common-frequency slice group velocity scanning link, so that the energy focusing performance of the dispersive imaging is further improved, and the anti-interference capability under the noise of a complex environment is improved.
In order to achieve the above object, the present invention provides a surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation, comprising the steps of:
s1, inputting seismic surface wave datas(t,x) And performing multiple synchronous compression conversion on each trace of the seismic surface wave data to a time-frequency domain, and combining the time-frequency domain data of each trace to generate a three-dimensional time-frequency data volumeTs(t, x, f)；
S2, for the three-dimensional time-frequency data body in the step S1Ts(t, x, f) Extracting the frequency along the frequency axis asf i Common frequency slice data at timeTs(t,x)；
S3, setting group velocity intervalv min ,v max ]The common frequency slice data obtained in step S2Ts(t,x) Calculating superposition energy of different speeds in the surface wave group velocity interval by adopting a similar coefficient method inclined scanning superposition mode;
s4, the frequency range is [f min ,f max ]Repeating the step S2 and the step S3, and combining the superposition energy of different frequencies and different surface wave group velocities to obtain a final surface wave dispersion energy diagram.
Preferably, in step S1, the following steps are included:
s11, firstly, performing amplitude gain, filtering and cutting treatment on the seismic surface wave data to strengthen the surface wave signals, and then performing short-time Fourier transformation on each channel of seismic surface wave data;
s12, setting the iteration times asN，And performing multiple synchronous compression transformation on the short-time Fourier transformation result.
Preferably, in step S11, wherein the single trace seismic signalss(t) Expressed as:
（1）
in the method, in the process of the invention,Kis the number of the single-component signals,tin order to be able to take time,xin order for the offset to be a distance,for instantaneous amplitude +.>For the instantaneous phase position,iis an imaginary unit;
the corresponding short-time fourier transform of the seismic signal is:
（2）
in the method, in the process of the invention,is a signals(t) Is used for the short-time fourier transform of (c),g(u-t) In order to be a time window of the time,ufor time shift factor, ++>Is the angular frequency.
Preferably, in step S12, the multiple synchronous compression conversion process is expressed as follows:
（3）
in the method, in the process of the invention,as a pulse function +.>Is the instantaneous frequency of the multiple iterative estimates,ηfor synchronizing the frequencies of the compression transformations.
Preferably, in step S3, the data is sliced for common frequencies of all frequency ranges of step S2Ts(t,x) At the intercept timeTAt the position of=0, the superposition energy at different surface wave group velocities is calculated by adopting a similar coefficient method inclined scanning superposition method, wherein the formula of the similar coefficient method inclined scanning superposition is as follows:
（4）
in the method, in the process of the invention,Scthe superposition energy calculated for the different group velocities,Lfor the number of seismic traces，MAs the intercept timeT=0~MIs used for the time window of (1),r i is offset fromxGroup velocity at timevWhen corresponding delay, i.er i =(x i /v)/Δt，aFor the sequence number of the seismic trace,bis the time sampling point sequence number.
Therefore, the invention adopts the above-mentioned surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation, adopts the method of rapidly obtaining high-quality and high-resolution dispersion images through multiple synchronous compression transformation, solves the defect of lower resolution of the surface wave dispersion energy of the traditional time-frequency analysis method, and adopts a similarity coefficient method analysis method to improve the robustness and resolution of the group velocity dispersion energy imaging under noise interference on the basis of frequency analysis. The method is simple and easy to implement, obviously improves the resolution and noise immunity of the surface wave group velocity dispersion spectrum, and has higher calculation efficiency.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
FIG. 1 is a flow chart of a method for surface wave group velocity dispersion energy imaging according to the present invention;
FIG. 2 is a conceptual diagram of a method for surface wave group velocity dispersion energy imaging according to the present invention;
FIG. 3 is a seismic surface wave data profile of an embodiment of the invention;
FIG. 4 is a time-frequency spectrum diagram of a 51 st data multi-synchronous compression transformation according to an embodiment of the present invention;
FIG. 5 is a common frequency slice diagram of a frequency of 10Hz according to an embodiment of the present invention;
FIG. 6 is a final group velocity surface wave dispersion imaging of an embodiment of the present invention;
fig. 7 is a graph of scattered energy imaging using generalized S-transform.
Detailed Description
The technical scheme of the invention is further described below through the attached drawings and the embodiments.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs.
Example 1
As shown in fig. 1, the invention provides a surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation, which comprises the following steps:
s1, inputting seismic surface wave datas(t,x) And carrying out multiple synchronous compression conversion on each line of the seismic surface wave data to generate a three-dimensional time-frequency data bodyTs(t, x, f) Comprising the following steps:
s11, carrying out short-time Fourier transform on each channel of seismic surface wave data, wherein seismic signalss(t) Represented as
（1）
In the method, in the process of the invention,tin order to be able to take time,xin order for the offset to be a distance,A k (t) For the instantaneous amplitude of the vibration,for the instantaneous phase position,kis the number of the single-component signals,iis an imaginary unit;
the corresponding short-time fourier transform of the seismic signal is:
（2）
in the method, in the process of the invention,is a signals(t) Is a short-time Fourier transform of->Is the angular frequency of the wave form,g(u) In order to be a time window of the time,iis an imaginary unit;
s12, for short-time Fourier transform resultMultiple synchronous compression transformations are employed. The multiple synchronous compression transformation performs multiple synchronous compression on spectrum data during the short-time Fourier transformation of the surface wave signal, and gradually improves the focusing property of the time spectrum energy. Meanwhile, the method adopts a function iteration mode to compare with the transmission modeThe calculation efficiency of the systematic high-order synchronous compression transformation is greatly improved. Therefore, the method is a high-resolution and high-efficiency time-frequency analysis method, and is very suitable for improving the velocity dispersion energy imaging of the seismic surface wave group.
For the seismic surface wave signal s (t), its synchronous compression transformation is expressed as:
（3）
based on the synchronous compression transformation result, iterative computation is carried out for a plurality of times, and the focusing property of spectrum energy is gradually improved. Assuming that the number of iterations isNThe multiple synchronous compression conversion process is expressed as follows:
（4）
in the method, in the process of the invention,is a short-time Fourier transform of the data of a certain channel of the face wave, < >>As a dirac function, +.>Is the instantaneous frequency of the multiple iterative estimates,ηfor synchronizing the frequencies of the compression transformations.
S2, extracting common-frequency slice data d (t, x) from the three-dimensional time-frequency data volume Ts (t, x, f) in the step S1 along a frequency axis;
s3, slicing the common frequency of all the frequency ranges in the step S2Ts(t,x) At the intercept timeTAnd (2) calculating the group velocity of the surface waves in a timing window width of the position=0 by adopting a similar coefficient method inclined scanning superposition mode, wherein the formula of the similar coefficient method inclined scanning superposition is as follows:
（4）
in the middle of，ScThe superposition energy calculated for the different group velocities,Lfor the number of seismic traces，MAs the intercept timeT=0~MIs used for the time window of (1),r i is offset fromxGroup velocity at timevWhen corresponding delay, i.er i =(x i /v)/Δt，aFor the sequence number of the seismic trace,bis the time sampling point sequence number.
And S4, combining the group velocities of the surface waves obtained in the step S3 together to serve as a final two-dimensional surface wave frequency-group velocity function.
Example two
The method flow of the first embodiment is described by taking the group velocity dispersion energy imaging of certain synthetic seismic surface wave data as an example, and the superiority and accuracy of the method are verified by comparing with the existing method.
1: and (3) inputting synthetic seismic surface wave data, and firstly carrying out preprocessing such as filtering, cutting, gain and the like on the surface wave data to improve the signal-to-noise ratio of the data. The data before and after pretreatment are shown in fig. 3.
2: and setting a Gaussian time window with the time window width of 200, and performing multiple synchronous compression transformation on each track of the preprocessed seismic data to obtain a time spectrum of each track, thereby forming a three-dimensional data volume Ts (t, x, f). The time spectrum after the multiple synchronous compression conversion is shown in fig. 4. From fig. 4, it can be known that the frequency spectrum will be more aggregated after 6 iterations, and meanwhile, the multiple iteration calculation process is converted into the iterative mode of the function, so that the SST is calculated only once, the calculation amount is greatly reduced, and the calculation efficiency is also greatly improved.
3: setting the frequency range to [10,50 ]]The speed scanning range is [100,1000]. Extracting co-frequency slice data along a frequency axis for a three-dimensional data volume Ts (t, x, f)Ts(t, x) as shown in FIG. 5, for a frequency range of [10,50]The frequency slice data corresponding to each frequency in the interval is calculated by using a similar coefficient method to obliquely scan, and the oblique superposition energy of each frequency at different speeds is used as a final scattered energy imaging diagram, as shown in fig. 6. FIG. 7 is a graph of a calculated dispersive energy image using a conventional surface wave group velocity dispersive energy imaging method based on generalized S-transform. Comparing the method frequency dispersion imaging result and the generalized S transformation result, the invention can show that the resolution of the method is greatly improved, the whole is less influenced by noise, and the method is very suitable for picking up the subsequent group velocity frequency dispersion curve.
Therefore, the invention adopts the above-mentioned surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation, obviously improves the resolution and noise immunity of the surface wave group velocity dispersion spectrum, and has higher calculation efficiency.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention and not for limiting it, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that: the technical scheme of the invention can be modified or replaced by the same, and the modified technical scheme cannot deviate from the spirit and scope of the technical scheme of the invention.
Claims (4)
1. The surface wave group velocity dispersion energy imaging method based on multiple synchronous compression transformation is characterized by comprising the following steps of:
s1, inputting seismic surface wave datas(t,x) And performing multiple synchronous compression conversion on each trace of the seismic surface wave data to a time-frequency domain, and combining the time-frequency domain data of each trace to generate a three-dimensional time-frequency data volumeTs(t, x,f)；
S2, for the three-dimensional time-frequency data body in the step S1Ts(t, x, f) Extracting the frequency along the frequency axis asf i Common frequency slice data at timeTs(t,x)；
S3, setting group velocity intervalv min ,v max ]The common frequency slice data obtained in step S2Ts(t,x) Calculating superposition energy of different speeds in the surface wave group velocity interval by adopting a similar coefficient method inclined scanning superposition mode;
s4, the frequency range is [f min ,f max ]Repeating the step S2 and the step S3, and combining the superposition energy of different frequencies and different surface wave group velocities to obtain a final surface wave dispersion energy diagram;
in step S3, the data is sliced for common frequencies of all frequency ranges of step S2Ts(t,x) At the intercept timeTAt the position of=0, the superposition energy at different surface wave group velocities is calculated by adopting a similar coefficient method inclined scanning superposition method, wherein the formula of the similar coefficient method inclined scanning superposition is as follows:
（4）
in the method, in the process of the invention,Scthe superposition energy calculated for the different group velocities,Lfor the number of seismic traces，MAs the intercept timeT=0~MIs used for the time window of (1),r i is offset fromxGroup velocity at timevWhen corresponding delay, i.er i =(x i /v)/Δt，aFor the sequence number of the seismic trace,bis the time sampling point sequence number.
2. The method of face velocity dispersion energy imaging based on multiple synchronous compression transformations according to claim 1, comprising the steps of, in step S1:
s11, firstly, performing amplitude gain, filtering and cutting treatment on the seismic surface wave data to strengthen the surface wave signals, and then performing short-time Fourier transformation on each channel of seismic surface wave data;
s12, setting the iteration times asN，And performing multiple synchronous compression transformation on the short-time Fourier transformation result.
3. The method of face velocity dispersion energy imaging based on multiple simultaneous compression transformation of claim 2, wherein in step S11, wherein the single trace seismic signals(t) Expressed as:
（1）
in the method, in the process of the invention,Kis the number of the single-component signals,tin order to be able to take time,xin order for the offset to be a distance,for instantaneous amplitude +.>For the instantaneous phase position,iis an imaginary unit;
the corresponding short-time fourier transform of the seismic signal is:
（2）
in the method, in the process of the invention,is a signals(t) Is used for the short-time fourier transform of (c),g(u-t) In order to be a time window of the time,ufor time shift factor, ++>Is the angular frequency.
4. A method of face velocity dispersion energy imaging based on multiple synchronous compression transformation according to claim 3, wherein in step S12, the multiple synchronous compression transformation procedure is expressed as follows:
（3）
in the method, in the process of the invention,as a pulse function +.>Is repeatedly overlappedInstead of the estimated instantaneous frequency,ηfor synchronizing the frequencies of the compression transformations.
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| WO2017223079A1 (en) * | 2016-06-22 | 2017-12-28 | University Of Houston System | Nonlinear signal comparison and high-resolution measurement of seismic or acoustic wave dispersion |
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| CN112285768A (en) * | 2020-10-15 | 2021-01-29 | 中国科学院地质与地球物理研究所 | High-frequency marine acoustic guided wave frequency dispersion analysis device and method |
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| WO2017223079A1 (en) * | 2016-06-22 | 2017-12-28 | University Of Houston System | Nonlinear signal comparison and high-resolution measurement of seismic or acoustic wave dispersion |
| CN111505707A (en) * | 2020-04-28 | 2020-08-07 | 西安交通大学 | Method for extracting dispersion curve from vertical seismic profile data |
| CN112285768A (en) * | 2020-10-15 | 2021-01-29 | 中国科学院地质与地球物理研究所 | High-frequency marine acoustic guided wave frequency dispersion analysis device and method |
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