A waveform processing method, device, equipment and storage medium

Abstract

The present invention relates to the field of geological prospecting technology, and specifically to a waveform processing method, device, equipment and storage medium. The present invention first divides the collected original waveform into various segmented waveforms, selects waveforms that meet the characteristics of the diffuse field from the various segmented waveforms, performs cross-correlation analysis on the selected waveforms, obtains the amplitude cross-correlation function of each diffuse waveform, and analyzes the propagation characteristics of the original waveform in the geological structure based on the amplitude cross-correlation function. The present invention does not need to collect the original waveform that meets the diffusion condition within a long time range, but only needs to extract the segmented waveform that meets the diffusion condition from the original waveform, and then analyzes the propagation characteristics of the original waveform in the geological structure based on the cross-correlation function between the segmented waveforms. Therefore, the present invention can save the time required for analyzing the waveform propagation characteristics.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to a waveform processing method, device, equipment and storage medium. Background Art

[0002] The background noise cross-correlation technology performs cross-correlation analysis on multiple original waveforms (a signal is sent to the geological structure, and the geological structure reflects the signal to form a continuous waveform) to extract the surface wave dispersion curve composed of multiple continuous waveforms, and then extracts the propagation characteristics of the above continuous waveform in the geological structure from the surface wave dispersion curve. The propagation characteristics can be used for geological structure imaging. The premise of the above background noise cross-correlation technology is that multiple continuous waveforms are required to be collected under the condition that the vibration wave field of the geological structure is completely dispersed. That is, only when the multiple continuous waveforms collected under the condition that the vibration wave field of the geological structure is completely dispersed can the background noise cross-correlation technology be applied to obtain the propagation characteristics of the wave in the geological structure. The existing technology observes continuous waveforms for a long time to determine whether the vibration wave field meets the dispersion condition. This will cause two problems: first, it takes a long time to observe and collect continuous waveforms, and second, although it takes a long time to collect the continuous waveforms generated by the geological structure, the vibration wave field in the completely dispersed condition is still not captured, so the background cross-correlation technology cannot be used to calculate the propagation characteristics of the waveform in the geological structure.

[0003] In summary, existing technologies are time-consuming and difficult to analyze the propagation characteristics of waves in geological structures.

[0004] Therefore, the prior art still needs to be improved and enhanced. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a waveform processing method, device, equipment and storage medium, which solves the problem that the prior art is both time-consuming and difficult to analyze the propagation characteristics of waves in geological structures.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a waveform processing method, comprising:

[0008] Selecting waveforms that meet the diffuse field characteristics from each segmented waveform and recording them as each segmented diffuse waveform, wherein the segmented waveform is a waveform obtained by segmenting the original waveform;

[0009] Determining a cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform;

[0010] According to the cross-correlation function, the propagation characteristic information of the original waveform is obtained, and the propagation characteristic information is used to reflect the structural information of the geology, and the geology is the propagation medium of the original waveform.

[0011] In one implementation, the method for determining the fringing field characteristics includes:

[0012] Determining an expected value of the amplitude of the segmented waveform;

[0013] Determining an amplitude corresponding to one frequency and an amplitude corresponding to another frequency on the segmented waveform;

[0014] Determine the expected value of the product of the amplitude corresponding to one frequency and the amplitude corresponding to the other frequency;

[0015] Determine the product of the expectation of the square of the absolute value of the amplitude corresponding to one frequency and the expectation of the square of the absolute value of the amplitude corresponding to the other frequency;

[0016] Whether the segmented waveform satisfies the diffuse field characteristics is determined based on the amplitude expectation value, the amplitude product expectation value, and the expected product.

[0017] In one implementation, the determining of the cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform, includes:

[0018] Determine two of the diffusion waveforms in each of the diffusion waveforms, the two diffusion waveforms are respectively acquired by two detectors located on the geological surface, and the two diffusion waveforms are acquired at the same time;

[0019] A cross-correlation function between two segments of the diffusion waveform is determined.

[0020] In one implementation, obtaining the propagation characteristic information of the original waveform according to the cross-correlation function, wherein the propagation characteristic information is used to reflect the structural information of the geology, and the geology is the propagation medium of the original waveform, includes:

[0021] Applying inverse Fourier transform to the cross-correlation function to obtain a surface wave dispersion curve;

[0022] Each phase velocity in the propagation characteristic information of the original waveform is extracted from the surface wave dispersion curve, and each phase velocity corresponds to each frequency of the original waveform in the frequency domain.

[0023] In one implementation, the method further includes: obtaining the propagation characteristic information of the original waveform according to the cross-correlation function, wherein the propagation characteristic information is used to reflect the structural information of the geology, and the geology is the propagation medium of the original waveform;

[0024] Determining the amplitude of the waveform generated by the cross-correlation function, recorded as the corrected amplitude of the original waveform;

[0025] Determine the distance between the two detectors, recorded as the detector distance;

[0026] According to the detector distance, the corrected amplitude, the frequency of the original waveform in the frequency domain, and each phase velocity, an attenuation coefficient in the propagation characteristic information is obtained, and the attenuation coefficient is used to characterize the amplitude attenuation information of the original waveform.

[0027] In one implementation, the attenuation coefficient in the propagation characteristic information is obtained according to the detector distance, the corrected amplitude, the frequency of the original waveform in the frequency domain, and each of the phase velocities, and the attenuation coefficient is used to characterize the amplitude attenuation information of the original waveform, including:

[0028] Setting constants, the constants being related to noise sources in the geological environment and field effects of the geological environment;

[0029] Subtract the natural logarithm of the corrected amplitude from the natural logarithm of the constant to obtain a difference;

[0030] multiplying the difference by the phase velocity to obtain a first product;

[0031] multiplying the detector distance by the frequency by pi to obtain a second product, the frequency corresponding to the phase velocity;

[0032] The first product is divided by the second product to obtain an attenuation coefficient.

[0033] In one implementation, the segmented waveform is a waveform obtained by dividing the original waveform into equal time intervals.

[0034] In a second aspect, an embodiment of the present invention further provides a waveform processing device, wherein the device comprises the following components:

[0035] A diffusion waveform screening module is used to screen out waveforms that meet the diffusion field characteristics from each segmented waveform, which are recorded as each segmented diffusion waveform. The segmented waveform is a waveform obtained by segmenting the original waveform;

[0036] A cross-correlation function calculation module, used to determine the cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform;

[0037] The waveform characteristic calculation module is used to obtain the propagation characteristic information of the original waveform according to the cross-correlation function, wherein the propagation characteristic information is used to reflect the structural information of the geology, and the geology is the propagation medium of the original waveform.

[0038] In a third aspect, an embodiment of the present invention further provides a terminal device, wherein the terminal device includes a memory, a processor, and a waveform processing program stored in the memory and executable on the processor, and when the processor executes the waveform processing program, the steps of the above-mentioned waveform processing method are implemented.

[0039] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a waveform processing program is stored. When the waveform processing program is executed by a processor, the steps of the waveform processing method described above are implemented.

[0040] Beneficial effects: The present invention first divides the collected original waveform into various segmented waveforms, selects waveforms that meet the characteristics of the diffuse field from the various segmented waveforms, performs cross-correlation analysis on the selected waveforms (diffusion waveforms), obtains the amplitude cross-correlation function of each diffusion waveform, and analyzes the propagation characteristics of the original waveform in the geological structure based on the amplitude cross-correlation function. From the above analysis, it can be seen that the present invention does not need to collect the original waveform that meets the diffusion condition within a long time range, but only needs to extract the segmented waveform that meets the diffusion condition from the original waveform, and then analyze the propagation characteristics of the original waveform in the geological structure based on the cross-correlation function between the segmented waveforms. Therefore, the present invention can save the time required to analyze the propagation characteristics of the waveform. In addition, since the present invention does not require too many continuous original waveforms to analyze the propagation characteristics of the wave, the difficulty of analyzing the propagation characteristics of the wave is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is the overall flow chart of the present invention;

[0042] Figure 2 is a flow chart of geological structure imaging in an embodiment of the present invention;

[0043] Figure 3 is a waveform corresponding to the random noise signal in an embodiment of the present invention;

[0044] Figure 4 for Figure 3 A value distribution diagram corresponding to the waveform in;

[0045] Figure 5 for Figure 3 The B value distribution diagram corresponding to the waveform in;

[0046] Figure 6 for Figure 3The C value distribution diagram corresponding to the waveform in;

[0047] Figure 7 is a seismic waveform diagram in an embodiment of the present invention;

[0048] Figure 8 for Figure 7 A value distribution diagram corresponding to the waveform in;

[0049] Fig. 9 for Figure 7 The B value distribution diagram corresponding to the waveform in;

[0050] Fig.10 for Figure 7 The C value distribution diagram corresponding to the waveform in;

[0051] Fig.11 is a distribution diagram of optical fiber positions in an embodiment of the present invention;

[0052] Fig.12 Schematic diagram of waveforms in an embodiment of the present invention;

[0053] Fig.13 for Fig.12 The A value distribution diagram corresponding to the waveform in;

[0054] Fig.14 for Fig.12 The B value distribution diagram corresponding to the waveform in;

[0055] Fig.15 for Fig.12 The C value distribution diagram corresponding to the waveform in;

[0056] Fig.16 Schematic diagram of the cross-correlation function obtained using one hour of diffusion recording in an embodiment of the present invention;

[0057] Fig.17 This is a dispersion diagram obtained using a one-hour dispersion record in an embodiment of the present invention;

[0058] Fig.18 Schematic diagram of the cross-correlation function obtained using 20 seconds of diffusion recording in an embodiment of the present invention;

[0059] Fig.19 This is a dispersion diagram obtained using a 20-second diffusion record in an embodiment of the present invention;

[0060] Fig. 20 is a schematic diagram of the locations of various stations in an embodiment of the present invention;

[0061] Fig.21 This is a waveform diagram of a 60-second diffusion record in an embodiment of the present invention;

[0062] Fig. 22 for Fig.21 The A value distribution diagram corresponding to the waveform in;

[0063] Fig.23 for Fig.21 The B value distribution diagram corresponding to the waveform in;

[0064] Fig.24 for Fig.21 The C value distribution diagram corresponding to the waveform in;

[0065] Fig.25 is a relationship diagram between slowness and accumulated precipitation in an embodiment of the present invention;

[0066] Fig.26 is a relationship diagram between the attenuation coefficient and the daily precipitation in an embodiment of the present invention;

[0067] Fig. 27 This is a block diagram of the internal structure principle of the terminal device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The following is a clear and complete description of the technical solution of the present invention in combination with the embodiments and the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] Through research, it is found that the background noise cross-correlation technology extracts the surface wave dispersion curve composed of multiple continuous waveforms by cross-correlation analysis of multiple original waveforms (a signal is sent to the geological structure, and the geological structure reflects the signal to form a continuous waveform), and then extracts the propagation characteristics of the above continuous waveform in the geological structure from the surface wave dispersion curve. The propagation characteristics can be used for geological structure imaging. The premise of the above background noise cross-correlation technology is that multiple continuous waveforms are required to be collected under the condition that the vibration wave field of the geological structure is completely dispersed, that is, only when the multiple continuous waveforms collected under the condition that the vibration wave field of the geological structure is completely dispersed can the background noise cross-correlation technology be applied to obtain the propagation characteristics of the wave in the geological structure. The existing technology observes the continuous waveforms for a long time to determine whether the vibration wave field meets the dispersion condition. There are two problems in doing so: one is that it takes a long time to observe and collect the continuous waveforms, and the other is that although it takes a long time to collect the continuous waveforms generated by the geological structure, the vibration wave field in the completely dispersed condition is still not captured, so the background cross-correlation technology cannot be used to calculate the propagation characteristics of the waveform in the geological structure.

[0070] In order to solve the above technical problems, the existing technology is time-consuming and difficult to analyze the propagation characteristics of waves in geological structures. In specific implementation, the original waveform is first segmented to obtain each segmented waveform, and then the waveforms that meet the characteristics of the diffuse field are screened out from each segmented waveform (recorded as each segment of the diffuse waveform), and then the cross-correlation function of each segment of the diffuse waveform is determined. Finally, based on the cross-correlation function, the propagation characteristic information of the original waveform is obtained. The present invention can shorten the time required to analyze the characteristics of wave propagation.

[0071] For example, if you want to collect a geological structure image at a certain location, you need to do the following:

[0072] First, a seismic wave signal is sent to the location. After the seismic wave enters the geological structure, it is reflected by the geological structure. Several detectors located on the surface of the geological structure collect the original waveform formed by the seismic wave reflected by the geological structure. For example, three detectors A, B, and C collect three original waveforms w1, w2, and w3 respectively (the duration of the three original waveforms is five minutes). The original waveform collected by each detector is segmented at equal time intervals. For example, the original waveform w1 is segmented at equal intervals of sixty seconds to obtain segmented waveforms w11, w12, w13, w14, and w15; the original waveform w2 is segmented at equal intervals of sixty seconds to obtain segmented waveforms w21, w22, w23, w24, and w25; the original waveform w3 is segmented at equal intervals of sixty seconds to obtain segmented waveforms w31, w32, w33, w34, and w35. Among them, the segmented waveforms w13, w14 of detector A, w22, w23, w24, w25 of detector B, and w32, w33, w34 of detector C meet the characteristics of the diffuse field. Therefore, w13, w14 of detector A, w22, w23, w24, w25 of detector B, and w32, w33, w34 of detector C are regarded as diffuse waveforms.

[0073] Analyze the cross-correlation function of any two diffuse waveforms collected at the same time, that is, analyze the cross-correlation function between w13 of detector A and w23 of detector B Analyze the cross-correlation function between detector A's w13 and detector C's w33 Analyze the cross-correlation function between detector A's w14 and detector B's w24 Analyze the cross-correlation function between detector A's w14 and detector C's w34 Among them, w13, w23 and w33 are segmented waveforms collected at the third minute, and w14, w24 and w34 are segmented waveforms collected at the fourth minute.

[0074] According to the cross-correlation function Cross-correlation function Cross-correlation function Cross-correlation function The propagation characteristics of the original waveform w1 in the geological structure, the propagation characteristics of the original waveform w2 in the geological structure, and the propagation characteristics of the original waveform w3 in the geological structure are analyzed, and the geological structure of a certain location is analyzed based on the propagation characteristics of the above three original waveforms.

[0075] Exemplary Methods

[0076] The waveform processing method of this embodiment can be applied to a terminal device, and the terminal device can be a terminal product with a waveform acquisition function, such as a detector. Figure 1 As shown in , the waveform processing method specifically includes the following steps:

[0077] S100, selecting waveforms satisfying diffuse field characteristics from each segmented waveform and recording them as each segmented diffuse waveform, wherein the segmented waveform is a waveform obtained by segmenting the original waveform.

[0078] S200, determining a cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform.

[0079] S300, obtaining propagation characteristic information of the original waveform according to the cross-correlation function, wherein the propagation characteristic information is used to reflect geological structural information, and the geology is the propagation medium of the original waveform.

[0080] In one embodiment, if none of the segmented waveforms satisfies the diffuse field characteristics, the original waveforms containing the segmented waveforms cannot be used to reflect geological structural information.

[0081] In one embodiment, the overall process of steps S100, S200, and S300 is as follows: Figure 2 As shown,

[0082] The collected original waveform containing background noise data is divided into several waveform segments at equal time intervals, and each segmented waveform is analyzed to see whether it meets the diffusion condition. If it does not meet the diffusion condition, the waveform segment will not be used for geological structure imaging analysis; if it meets the diffusion condition, the waveform segment will be used for geological structure imaging analysis.

[0083] When using segmented waveforms that meet the diffusion conditions for geological structure imaging analysis, each segmented waveform is first analyzed with each other, and the information about the change of the phase velocity of the original waveform over time and the attenuation of the amplitude of the original waveform over time are determined based on the results of the cross-correlation analysis. Based on the information about the change of the phase velocity of the original waveform over time and the attenuation of the amplitude over time, the image of the geological structure is analyzed.

[0084] In this embodiment, the reason for selecting a segmented waveform that satisfies the diffusion condition is based on the following considerations:

[0085] The correct cross-correlation function cannot be calculated for the segmented waveforms that do not meet the dispersion conditions, and the phase velocity and attenuation cannot be obtained later. Therefore, it is necessary to select those that meet the dispersion conditions and discard those that do not meet them to ensure the accuracy of the final results.

[0086] In one embodiment, whether a segmented waveform satisfies the fringing field characteristic is determined through the following steps S101 to S105:

[0087] S101, determining the expected amplitude value E[Ψ F (w n )].

[0088] Ψ F (w n ) is the amplitude of the waveform in frequency domain, F represents the frequency domain, and the waveform in time domain is Fourier transformed to obtain the waveform in frequency domain (in a two-dimensional coordinate system, the horizontal axis is the frequency of the waveform, and the vertical axis is the amplitude of the waveform corresponding to the frequency). For example, the segmented waveform is frequency sampled to obtain 1HZ, 3HZ, 5HZ, 7HZ, and 9HZ, and the corresponding amplitudes are 2, 5, -2, -1, and 6 respectively. Amplitude expectation value

[0089]

[0090] In one embodiment, w n is the frequency corresponding to the nth-order mode. The segmented waveform includes different normal vibration modes of the earth.

[0091] S102, determining the amplitude Ψ corresponding to one of the frequencies on the segmented waveform F (w n ) and the amplitude Ψ corresponding to another frequency F (w m ).

[0092] S103, determining the expected value E[Ψ F (w m ) F (w n )].

[0093] S104, determining the product of the expectation of the square of the absolute value of the amplitude corresponding to one frequency and the expectation of the square of the absolute value of the amplitude corresponding to another frequency

[0094] S105, according to the expected value of amplitude E[Ψ F (w n)], expected value of amplitude product E[Ψ F (w m ) F (w n )], the expected product It is determined whether the segmented waveform satisfies the diffuse field characteristics.

[0095] This embodiment is achieved by E[Ψ F (w n )] and E[Ψ F (w m )] Construct three indicators mean(A), cond(B+I), and cond(C) to determine whether one of the segmented waveforms meets the diffusion condition, where mean(A) is the average value of vector A.

[0096] When one of the segmented waveforms satisfies mean(A)=0, cond(B+I)=1, and cond(C)=1, the segmented waveform satisfies the fringing field characteristic. Otherwise, the segmented waveform does not satisfy the fringing field characteristic.

[0097] Among them, the vector

[0098] cond(B+I)=||B+I||·||(B+I) -1 ||, where ||B+I|| is the norm of the matrix B+I, I is the identity matrix, (B+I) -1 is the inverse matrix of matrix B+I, ||(B+I) -1 || is the matrix (B+I) -1 The norm of .

[0099] in,

[0100]

[0101] Where * is a conjugate matrix.

[0102] In one embodiment, the specific process of step S200 is as follows: determining two segments of the diffusion waveform among the segments of the diffusion waveform, the two segments of the diffusion waveform are respectively collected by two detectors located on the geological surface, and the two segments of the diffusion waveform are collected at the same time; determining the cross-correlation function between the two segments of the diffusion waveform.

[0103] For example, there are two detectors A and B on the surface of the geological structure. Detector A records the waveform within three minutes, and detector B also records the waveform within three minutes transmitted from the inside of the geological structure. Both of these original waveforms are segmented, and the original waveform collected by A is divided into segmented waveform 1, segmented waveform 2, and segmented waveform 3, and the original waveform collected by B is divided into segmented waveform 1', segmented waveform 2', and segmented waveform 3'. Among them, segmented waveform 1, segmented waveform 2, segmented waveform 2', and segmented waveform 3' are all diffuse waveforms. Since only segmented waveform 2 and segmented waveform 2' are sent at the same time, it is only necessary to calculate the cross-correlation function of segmented waveform 2 and segmented waveform 2'. The cross-correlation function is used to reflect the degree of correlation between the amplitude of segmented waveform 2 and the amplitude of segmented waveform 2'.

[0104] In one embodiment, step S300 includes the following specific steps S301 to S308:

[0105] S301, applying inverse Fourier transform to the cross-correlation function to obtain a surface wave dispersion curve.

[0106] Step S200 determines the correlation function between two segmented waveforms recorded at the same time on every two detectors. Then, applying the inverse Fourier transform FJ to the correlation function of the two segmented waveforms can extract the surface wave dispersion curve.

[0107] S302, determining the amplitude of the waveform generated by the cross-correlation function, recorded as the corrected amplitude A of the original waveform correct .

[0108] Representing the cross-correlation function on the coordinate axis forms a waveform. Using a waveform to express the cross-correlation function is a prior art.

[0109] S303: Determine the distance between the two detectors, recorded as the detector distance r.

[0110] Two detectors are placed on the surface of the geological structure, and the detector distance r is the straight-line distance along the surface of the geological structure.

[0111] S304, setting a constant A0, wherein the constant is related to the noise source in the geological environment and the field effect of the geology.

[0112] A0 is the data of noise source and site effect, and A0 does not change with time.

[0113] S305, subtract the corrected amplitude A from the natural logarithm lnA0 of the constant A0 correct The natural logarithm of lnA correct , and get the difference lnA0-lnA correct .

[0114] S306, the difference lnA0-lnA correct Multiplying by the phase velocity c, the first product c(lnA0-lnA correct ).

[0115] S307 , multiplying the detector distance r by the frequency f by pi π to obtain a second product πrf, where the frequency corresponds to the phase velocity.

[0116] S308, the first product c(lnA0-lnA correct ) divided by the second product πrf, the attenuation coefficient Q is obtained -1 .

[0117]

[0118] Taking the waveform formed by random noise signals and the signal waveform formed by earthquakes as examples, it is explained that a signal waveform that satisfies the three conditions of mean(A)=0, cond(B+I)=1, and cond(C)=1 of the present invention can be determined as a diffuse waveform.

[0119] Figure 3 is the random noise signal waveform (this waveform satisfies the dispersion condition), Figure 4 is the corresponding relationship between frequency and A, Figure 4 The corresponding mean value of A, mean(A), is 0.0088. Figure 5 (both the horizontal and vertical axes are frequencies) The corresponding cond(B+I) value is 1.4821. Figure 6 (both the horizontal and vertical axes are frequencies) The corresponding cond(C) value is 1.5207. Since mean(A) is close to zero, cond(B+I) and cond(C) are both close to 1, so Figure 3 The random noise signal waveform approximately satisfies the three conditions of mean(A)=0, cond(B+I)=1, and cond(C=1, so it can be determined that Figure 3 The waveform satisfies the diffusion condition. This is consistent with the known Figure 3 The waveform meets the diffusion condition. Therefore, it can be explained that the present invention uses the three conditions of mean(A)=0, cond(B+I)=1, and cond(C)=1 to effectively determine whether the waveform meets the diffusion condition.

[0120] Figure 7 is the earthquake waveform ( Figure 7 The horizontal axis is time, and the vertical axis is amplitude. It is known that the earthquake waveform does not satisfy the diffuse field characteristics). Figure 8 (the horizontal axis is the frequency, the vertical axis is the amplitude value of A) is the corresponding relationship between frequency and A, Figure 8The corresponding mean value of A, mean(A), is 0.0483. Fig. 9 (both the horizontal and vertical axes are frequencies) The corresponding cond(B+I) value is 866.6486. Fig.10 (both the horizontal and vertical axes are frequency) The corresponding cond(C) value is 15134.6642. Since the mean(A) corresponding to the earthquake waveform is not close to zero, cond(B+I) and cond(C) are both much greater than 1, Figure 7 The earthquake waveform does not meet the three conditions of mean(A)=0,cond(B+I)=1,cond(C=1, so it can be determined that Figure 7 The seismic waveform does not satisfy the dispersion condition. Figure 7 Therefore, it can be shown that the present invention uses the three conditions of mean(A)=0, cond(B+I)=1, and cond(C)=1 to effectively determine whether the waveform meets the dispersion condition.

[0121] Fig.11 Optical fiber location distribution map, Fig.11 The white line in the middle is the location of the optical fiber, and the white ellipse is Fig.12 The location of the waveform shown. Fig.12 The waveform diagram is ( Fig.11 The waveform recorded at the middle ellipse position), Fig.13 The calculated value by the method of the present invention is Fig.12 The A value of the waveform, Fig.13 The mean(A) of each A value is 0.0175. Fig.14 express Fig.12 The waveform corresponding to cond(B+I)=2.4058, Fig.15 express Fig.12 The waveform corresponds to cond(C)=2.3953.

[0122] Fig.16 is the cross-correlation function obtained using one hour of diffusion record. The horizontal axis is time in seconds and the vertical axis is distance in meters.

[0123] Fig.17 This is a dispersion diagram obtained using a one-hour dispersion record. The horizontal axis is frequency in Hertz, and the vertical axis is phase velocity in Hertz.

[0124] Fig.18 is the cross-correlation function obtained using a 20-second diffusion record. The horizontal axis is time in seconds, and the vertical axis is distance in meters.

[0125] Fig.19This is a dispersion diagram obtained using a 20-second diffusion record. The horizontal axis is frequency in Hertz, and the vertical axis is phase velocity in Hertz.

[0126] By comparing Figures 16 to 19 It can be seen that by selecting a 20-second diffusion signal that meets the diffusion conditions, the surface wave dispersion curve was extracted, which is very consistent with the surface wave dispersion curve obtained using one hour of continuous waveform recording.

[0127] Fig. 20 The schematic diagram of the location of each station (detector) is shown in Figure 2. Fig. 20 The location of the middle triangle ▽ is the location of the station. Fig.21 This is a waveform diagram of a 60-second diffusion record (a waveform diagram that satisfies the diffusion characteristics, Fig. 20 The waveform recorded by the first station on the right in the figure). Fig. 22 (the horizontal axis is frequency, the vertical axis is amplitude) is Fig.21 The A value corresponding to the waveform. Fig. 22 The mean of all A values ​​in is mean(A)=0.0154. Fig.23 express Fig.21 The waveform corresponding to cond(B+I)=1.8767, Fig.24 express Fig.21 The waveform corresponds to cond(C)=2.0889.

[0128] If the surface wave phase velocity C and attenuation coefficient Q of a geological structure calculated by the method of the present invention -1 All of them change with time, so it is necessary to analyze what causes the above changes. In one embodiment, Fig.25 As shown in Figure 2, the relationship between slowness (the inverse of slowness is the surface wave phase velocity C) and accumulated precipitation is analyzed. Fig.26 As shown, the attenuation coefficient Q is analyzed -1 The relationship between the amount of daily precipitation.

[0129] In summary, the present invention first divides the collected original waveform into various segmented waveforms, selects waveforms that meet the characteristics of the diffuse field from each segmented waveform, performs cross-correlation analysis on each selected waveform (diffusion waveform), obtains the amplitude cross-correlation function of each diffusion waveform, and analyzes the propagation characteristics of the original waveform in the geological structure based on the amplitude cross-correlation function. From the above analysis, it can be seen that the present invention does not need to collect the original waveform that meets the diffusion condition within a long time range, but only needs to extract the segmented waveform that meets the diffusion condition from the original waveform, and then analyze the propagation characteristics of the original waveform in the geological structure based on the cross-correlation function between the segmented waveforms. Therefore, the present invention can save the time required to analyze the waveform propagation characteristics. In addition, since the present invention does not require too many continuous original waveforms to analyze the wave propagation characteristics, the difficulty of analyzing the wave propagation characteristics is reduced.

[0130] In addition, the present invention can extract surface wave dispersion and monitor the changes in velocity and attenuation by selecting ultra-short duration records that meet the dispersion conditions (segmented waveforms that meet the dispersion conditions) without preprocessing the original waveform by normalizing it in the time domain and whitening it in the frequency domain. The present invention can improve the time resolution of traditional background noise technology and monitor the changes in velocity and attenuation over time.

[0131] Exemplary Devices

[0132] This embodiment also provides a waveform processing device, which includes the following components:

[0133] A diffusion waveform screening module is used to screen out waveforms that meet the diffusion field characteristics from each segmented waveform, which are recorded as each segmented diffusion waveform. The segmented waveform is a waveform obtained by segmenting the original waveform;

[0134] A cross-correlation function calculation module, used to determine the cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform;

[0135] The waveform characteristic calculation module is used to obtain the propagation characteristic information of the original waveform according to the cross-correlation function, wherein the propagation characteristic information is used to reflect the structural information of the geology, and the geology is the propagation medium of the original waveform.

[0136] Based on the above embodiments, the present invention further provides a terminal device, whose principle block diagram can be shown as follows: Fig. 27As shown. The terminal device includes a processor, a memory, a network interface, a display screen, and a temperature sensor connected through a system bus. Among them, the processor of the terminal device is used to provide computing and control capabilities. The memory of the terminal device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the terminal device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a waveform processing method is implemented. The display screen of the terminal device can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the terminal device is pre-set inside the terminal device to detect the operating temperature of the internal device.

[0137] Those skilled in the art will understand that Fig. 27 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the terminal device to which the scheme of the present invention is applied. The specific terminal device may include more or less components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0138] In one embodiment, a terminal device is provided. The terminal device includes a memory, a processor, and a waveform processing program stored in the memory and executable on the processor. When the processor executes the waveform processing program, the following operation instructions are implemented:

[0139] Selecting waveforms that meet the diffuse field characteristics from each segmented waveform and recording them as each segmented diffuse waveform, wherein the segmented waveform is a waveform obtained by segmenting the original waveform;

[0140] Determining a cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform;

[0141] According to the cross-correlation function, the propagation characteristic information of the original waveform is obtained, and the propagation characteristic information is used to reflect the structural information of the geology, and the geology is the propagation medium of the original waveform.

[0142] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0143] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A waveform processing method, characterized in that: include: Selecting waveforms that meet the diffuse field characteristics from each segmented waveform and recording them as each segmented diffuse waveform, wherein the segmented waveform is a waveform obtained by segmenting the original waveform; Determining a cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform; According to the cross-correlation function, the propagation characteristic information of the original waveform is obtained, wherein the propagation characteristic information is used to reflect the structural information of the geology, and the geology is the propagation medium of the original waveform; The step of determining the cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform, includes: Determine two sections of the diffusion waveforms in each section of the diffusion waveform, the two sections of the diffusion waveforms are respectively acquired by two detectors located on the geological surface, and the two sections of the diffusion waveforms are acquired at the same time; A cross-correlation function between two segments of the diffusion waveform is determined.

2. The waveform processing method according to claim 1, characterized in that: The method for determining the characteristics of the diffuse field includes: Determining an expected value of the amplitude of the segmented waveform; Determining an amplitude corresponding to one frequency and an amplitude corresponding to another frequency on the segmented waveform; Determine the expected value of the product of the amplitude corresponding to one frequency and the amplitude corresponding to the other frequency; Determine the product of the expectation of the square of the absolute value of the amplitude corresponding to one frequency and the expectation of the square of the absolute value of the amplitude corresponding to the other frequency; Whether the segmented waveform satisfies the diffuse field characteristics is determined based on the amplitude expectation value, the amplitude product expectation value, and the expected product.

3. The waveform processing method according to claim 1, characterized in that: The method of obtaining the propagation characteristic information of the original waveform according to the cross-correlation function, wherein the propagation characteristic information is used to reflect the structural information of the geology, and the geology is the propagation medium of the original waveform, including: Applying inverse Fourier transform to the cross-correlation function to obtain a surface wave dispersion curve; Each phase velocity in the propagation characteristic information of the original waveform is extracted from the surface wave dispersion curve, and each phase velocity corresponds to each frequency of the original waveform in the frequency domain.

4. The waveform processing method according to claim 3, characterized in that: The method further comprises: obtaining propagation characteristic information of the original waveform according to the cross-correlation function, wherein the propagation characteristic information is used to reflect geological structural information, and the geology is a propagation medium of the original waveform; Determining the amplitude of the waveform generated by the cross-correlation function, recorded as the corrected amplitude of the original waveform; Determine the distance between the two detectors, recorded as the detector distance; According to the detector distance, the corrected amplitude, the frequency of the original waveform in the frequency domain, and each phase velocity, an attenuation coefficient in the propagation characteristic information is obtained, and the attenuation coefficient is used to characterize the amplitude attenuation information of the original waveform.

5. The waveform processing method according to claim 4, characterized in that: The attenuation coefficient in the propagation characteristic information is obtained according to the detector distance, the corrected amplitude, the frequency of the original waveform in the frequency domain, and each phase velocity, and the attenuation coefficient is used to characterize the amplitude attenuation information of the original waveform, including: Setting constants, the constants being related to noise sources in the geological environment and field effects of the geological environment; Subtract the natural logarithm of the corrected amplitude from the natural logarithm of the constant to obtain a difference; multiplying the difference by the phase velocity to obtain a first product; multiplying the detector distance by the frequency by pi to obtain a second product, the frequency corresponding to the phase velocity; The first product is divided by the second product to obtain an attenuation coefficient.

6. The waveform processing method according to any one of claims 1 to 5, characterized in that: The segmented waveform is a waveform obtained by dividing the original waveform into equal time intervals.

7. A waveform processing device, characterized in that: The device comprises the following components: A diffusion waveform screening module is used to screen out waveforms that meet the diffusion field characteristics from each segmented waveform, which are recorded as each segmented diffusion waveform. The segmented waveform is a waveform obtained by segmenting the original waveform; A cross-correlation function calculation module, used to determine the cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform; A waveform characteristic calculation module, used for obtaining propagation characteristic information of the original waveform according to the cross-correlation function, wherein the propagation characteristic information is used for reflecting geological structural information, and the geology is the propagation medium of the original waveform; The step of determining the cross-correlation function formed by each segment of the diffusion waveform, wherein the cross-correlation function is used to characterize the amplitude correlation degree of each segment of the diffusion waveform, includes: Determine two sections of the diffusion waveforms in each section of the diffusion waveform, the two sections of the diffusion waveforms are respectively acquired by two detectors located on the geological surface, and the two sections of the diffusion waveforms are acquired at the same time; A cross-correlation function between two segments of the diffusion waveform is determined.

8. A terminal device, characterized in that: The terminal device includes a memory, a processor, and a waveform processing program stored in the memory and executable on the processor. When the processor executes the waveform processing program, the steps of the waveform processing method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a waveform processing program, and when the waveform processing program is executed by the processor, the steps of the waveform processing method according to any one of claims 1 to 6 are implemented.

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