TBM advanced detection method and system based on seismic waves from vibroseis and rock fragmentation seismic source

Abstract

A TBM advanced detection method based on seismic waves from a vibroseis and rock fragmentation seismic source, which method belongs to the technical field of tunnel boring. Acquired low-frequency-band vibroseis seismic data and high-frequency-band vibroseis seismic data after a TBM is shut down, and rock fragmentation seismic source seismic data during TBM boring are preprocessed; interference processing is performed on the preprocessed low-frequency-band vibroseis seismic data, high-frequency-band vibroseis seismic data and rock fragmentation seismic source seismic data and respective pilot sensing data, so as to obtain interference seismic data corresponding to each piece of seismic data; and a priori constraint is provided for vibroseis inversion by using a characteristic of the frequency of a rock fragmentation seismic source seismic record being low; a fine inversion wave velocity result is obtained by using multi-scale full-waveform inversion and by using the property of vibroseis interference data obtained by means of frequency division scanning having multiple frequency bands, and an imaging result of boundary depiction is obtained by using reverse time migration imaging. Therefore, a safety guarantee is provided for advanced detection of TBM-based tunnel construction. Further provided is a TBM advanced detection system based on seismic waves from a vibroseis and rock fragmentation seismic source.

Description

TBM controlled vibroseis-rock-breaking source seismic wave advance detection method and system

[0001] The present invention claims priority to a Chinese patent application filed with the Patent Office of China on September 11, 2023, with application number 202311166945.6 and invention name “TBM Controllable Vibrator-Rock-Breaking Source Seismic Wave Advance Detection Method and System”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] The present invention relates to the technical field of tunnel advance detection, and in particular to a method and system for advance detection of seismic waves of a TBM (Tunnel Burden Machine) controlled vibrator-rock-breaking source. Background Art

[0003] The statements in this section merely provide background art related to the present invention and do not necessarily constitute prior art.

[0004] With the rapid development of tunnel engineering, tunnel boring machines (TBMs) have become increasingly widespread. Compared to traditional drilling and blasting methods, TBMs offer significant advantages, such as high mechanization and rapid construction speed. During TBM tunnel excavation, unfavorable geological conditions pose a significant threat to construction safety. Encountering unfavorable geological conditions, such as karst caves and fractured zones, can easily lead to machine jams, sudden water and mud inrush, and even serious casualties. Due to the complexity and unique nature of TBM tunnel construction environments, advanced detection methods and technologies have long been a challenge in the field of tunnel advanced detection both domestically and internationally.

[0005] Among the many TBM tunnel in-hole detection methods, seismic wave detection can locate and characterize adverse geological structures from a distance, and is widely used in advance detection of TBM tunnels. Detection methods are classified according to the detection period, and there are currently two main detection methods:

[0006] (1) Detection methods during TBM tunnel shutdown;

[0007] Active source seismic exploration is often used during TBM downtime. Traditional manual hammering for seismic exploration is limited by manpower and results in a short signal propagation distance. Therefore, onboard active source equipment has emerged in TBM tunnels. Commonly used onboard active source detection equipment include hydraulic and pneumatic seismic sources. While these devices increase the seismic energy, they still suffer from uncontrollable resolution of effective long-distance reflected wave signals.

[0008] (2) Real-time detection method during TBM excavation;

[0009] The TBM rock-breaking source uses the vibration of the cutter breaking rock during TBM excavation as the excitation source, and realizes real-time detection by taking advantage of the nature of exploration as excavation progresses. Due to its high energy and low frequency characteristics, the detection distance is longer. However, the TBM rock-breaking source signal lacks high-frequency information, which makes the resolution of long-distance real-time detection method insufficient.

[0010] Summary of the Invention

[0011] In order to address the deficiencies of the prior art, the present invention provides a method and system for advanced detection of seismic waves using a TBM controllable vibrator-rock-breaking source, which fully utilizes the two periods of TBM shutdown and construction, combines the controllable vibrator and the rock-breaking source in the detection process and detection effect, utilizes the characteristic of the controllable vibrator that can excite high-frequency signals, and meets the demand for fine detection during shutdown. Utilizes the real-time detection capability of the TBM rock-breaking source during the TBM excavation process, and makes up for the deficiency that the controllable vibrator can only be used for detection during shutdown.

[0012] In order to achieve the above object, the present invention adopts the following technical solutions:

[0013] A first aspect of the present invention provides a method for advanced detection of seismic waves of a TBM controllable vibrator-rock-breaking source.

[0014] A method for advanced detection of seismic waves using a TBM vibroseis-rock-breaking source includes the following steps:

[0015] When the TBM is stopped, two segments of vibroseis seismic data are acquired through frequency division scanning: low-frequency vibroseis seismic data and high-frequency vibroseis seismic data. During the TBM excavation process, rock-breaking seismic data excited by the rock-breaking source are collected.

[0016] Preprocessing of low-frequency and high-frequency vibroseis seismic data acquired after TBM shutdown and rock-breaking source seismic data acquired during TBM excavation.

[0017] The pre-processed low-frequency vibroseis seismic data, high-frequency vibroseis seismic data and rock-breaking source seismic data are subjected to cross-correlation interference processing respectively as the leading sensing data to obtain the interference seismic data corresponding to each seismic data;

[0018] De-noising the acquired interferometric seismic data to obtain seismic interferometric data with random noise removed, analyzing the direct wave component of the seismic interferometric data to obtain the direct wave velocity;

[0019] Based on the direct wave velocity, an initial inversion velocity model is created. Based on the inversion initial velocity model, multi-scale joint inversion is performed to obtain the final inversion velocity model. Reverse time migration imaging is performed on the final inversion velocity model to obtain the final imaging result.

[0020] As a further limitation of the first aspect of the present invention, the principle of cross-correlation interference is:

[0021] Among them, f(t0) and g(t0) are two signals, R(t) is the interferometric seismic record generated by cross-correlation, and t is the time interval.

[0022] As an optional implementation of the first aspect of the present invention, preprocessing is performed on the low-frequency vibroseis seismic data and high-frequency vibroseis seismic data acquired after the TBM is shut down, and the rock-breaking source seismic data acquired during the TBM excavation process, including:

[0023] The low-frequency vibroseis seismic data, high-frequency vibroseis seismic data and rock-breaking source seismic data were processed to remove the mean and linear trend.

[0024] As an optional implementation of the first aspect of the present invention, noise removal is performed on the acquired interferometric seismic data, including:

[0025] Bandpass filtering is used to select the main frequency components of the seismic records, and spectral subtraction is used to remove random noise; Fourier transform is used to perform bandpass filtering, intercept the effective signal in the frequency domain, and the denoised interferometric seismic records are obtained through inverse Fourier transform.

[0026] As an optional implementation of the first aspect of the present invention, a multi-scale joint inversion based on vibroseis frequency division scanning is performed according to the inverted initial velocity model to obtain a final inversion velocity model, including:

[0027] The entire waveform information of the rock-breaking source interferometric seismic data is used as the fitting target. The simulated seismic data is obtained by applying the rock-breaking source wavelet signal to the inversion initial velocity model for forward simulation. The second norm of the difference between the simulated seismic record and the interferometric seismic record is used as the objective function. The minimum value of the objective function is continuously sought, and then the simulated seismic data and the actual interferometric seismic data are continuously fitted to obtain a velocity model based on the full waveform inversion of the rock-breaking source interferometric data. The obtained velocity model will be used as the initial model for multi-scale inversion. Since the inversion has multiple solutions, a good initial model will help improve the inversion accuracy.

[0028] In the present invention, the wave velocity model of the full waveform inversion of the rock-breaking source interference data is used as the initial model, the low-frequency band vibroseis interference data is scanned by the frequency-division signal to perform the full waveform inversion, the sub-wave function data of the autocorrelation of the vibroseis pilot signal is used as the source and applied to the initial model to obtain a set of seismic records of the vibroseis low-frequency band signal, the low-frequency band vibroseis interference data is used as the fitting object, and the second norm of the difference between the simulated seismic record and the interference seismic record is used as the target function of the inversion. On the basis of the formation model that is continuously inverted and iteratively updated, simulated data that is closer to the actual interference data will be obtained.

[0029] When the difference between the simulated data and the interferometric data is small enough, or the number of inversion iterations reaches an artificially set upper limit, the full waveform inversion of the low-frequency band is considered to be completed, and a velocity model based on the full waveform inversion of the low-frequency vibroseis interferometric data is obtained. The velocity model obtained at this time is more refined in its depiction of the stratigraphic structure than the velocity model of the rock-breaking source inversion. The nonlinearity and periodic jump phenomenon of the full waveform inversion lead to multiple extreme values ​​in the objective function. By inverting the low-frequency interferometric data with the vibroseis frequency division scanning, the full waveform inversion method can relatively improve the robustness of the inversion process and effectively reduce the multi-solution of the inversion.

[0030] The velocity model based on full waveform inversion of low-frequency vibroseis interferometry data is used as the initial model, and full waveform inversion is performed using high-frequency vibroseis interferometry data obtained by frequency division scanning. The wavelet data of the autocorrelation of the high-frequency vibroseis pilot signal is used as the source and added to the velocity initial model obtained by low-frequency signal inversion to obtain a set of simulated interference data. The second norm of the difference between the simulated record and the high-frequency interference data is used as the objective function, and the final inversion velocity model is obtained by iterative optimization. Based on the high-frequency vibroseis interferometry data of frequency division scanning, due to its high-frequency characteristics, the co-directional axis in the interference data will be narrower, and the information that can be fitted during inversion fitting will be richer, so that fine structural information can be obtained on the basis of the low-frequency inversion model.

[0031] As an optional implementation method of the first aspect of the present invention, the leading signals of the low-frequency controllable source seismic data, the high-frequency controllable source seismic data and the rock-breaking source seismic data are respectively subjected to autocorrelation processing to obtain the sub-wave signals corresponding to the low-frequency controllable source seismic data, the high-frequency controllable source seismic data and the rock-breaking source seismic data.

[0032] As an optional implementation method of the first aspect of the present invention, the direct wave components in the low-frequency controllable source seismic data, the high-frequency controllable source seismic data and the rock-breaking source seismic data are extracted, the direct wave information is used to calculate and obtain the surrounding rock wave velocity information, and the direct wave components are cut off. The surrounding rock wave velocity information and the previous exploration information are used to create an inversion initial velocity model.

[0033] As an optional implementation of the first aspect of the present invention, performing reverse time migration imaging on the final inversion velocity model to obtain a final imaging result includes:

[0034] Apply the autocorrelation wavelet data of the rock-breaking source leader signal at the rock-breaking source leader sensor position, apply the rock-breaking source seismic interferometer data in reverse time at the receiver position, save the wave fields of both, and obtain the rock-breaking source imaging result through correlation superposition;

[0035] Apply high-frequency vibroseis pilot signal autocorrelation wavelet data at the vibroseis pilot sensor position, apply high-frequency vibroseis seismic interferometry data in reverse time at the geophone position, save the wave fields of both, and obtain high-frequency vibroseis imaging results through correlation superposition;

[0036] Apply low-frequency vibroseis pilot signal autocorrelation wavelet data at the vibroseis pilot sensor position, apply low-frequency vibroseis seismic interferometry data in reverse time at the geophone position, save the wave fields of both, and obtain low-frequency vibroseis imaging results through correlation superposition;

[0037] The final imaging result is obtained by superimposing the rock-breaking source imaging results, the high-frequency controllable source imaging results and the low-frequency controllable source imaging results.

[0038] A second aspect of the present invention provides a TBM controllable source-rock-breaking source seismic wave advance detection system.

[0039] A TBM vibroseis-rock-breaking source seismic wave advance detection system, comprising:

[0040] The preprocessing module preprocesses the low-frequency and high-frequency vibroseis seismic data acquired after the TBM is shut down, as well as the rock-breaking source seismic data acquired during the TBM excavation process.

[0041] The interference processing module is configured to: perform interference processing on the pre-processed low-frequency vibroseis seismic data, high-frequency vibroseis seismic data and rock-breaking source seismic data respectively as the leading sensing data to obtain interference seismic data corresponding to each seismic data;

[0042] The initial inversion model is constructed by performing noise removal (using bandpass filtering and spectral subtraction) on the acquired interferometric seismic data based on low-frequency vibroseis interferometric seismic data, high-frequency vibroseis interferometric seismic data, and rock-breaking source interferometric seismic data, obtaining seismic interferometric data with random noise removed, obtaining direct wave velocity data of the seismic interferometric data, and creating an initial inversion velocity model based on the direct wave velocity data.

[0043] The multi-scale inversion imaging is configured to: perform multi-scale joint inversion based on the inverted initial velocity model to obtain a final inversion velocity model, and perform reverse time migration imaging on the final inversion velocity model to obtain a final imaging result.

[0044] A third aspect of the present invention provides a TBM controllable vibroseis-rock-breaking source seismic wave advance detection system.

[0045] A TBM vibroseis-rock-breaking source seismic wave advance detection system, comprising:

[0046] Includes: electromagnetic vibrator, three-component geophone, vibrator pilot sensor and rock-breaking vibrator pilot sensor;

[0047] The electromagnetic vibrator is fixed to the TBM's gripper shoe, the three-component geophone is fixed to both sides of the TBM working platform, the vibrator pilot sensor is fixed to the rock wall near the electromagnetic vibrator, and the rock-breaking source pilot sensor is located behind the TBM's upper cutterhead.

[0048] An electromagnetic controllable vibrator, comprising: an air bag, a blocking plate, a counterweight housing, a base plate, a guide rail, a moving component, an acceleration sensor and an excitation component;

[0049] The guide rail is arranged on the base plate, the counterweight housing is slidably connected to the guide rail through a moving component, the excitation component and the acceleration sensor are fixed on one side of the counterweight housing, a blocking plate is fixed on the base plate on the other side of the counterweight housing, and an airbag is fixed on the side of the blocking plate facing the counterweight housing;

[0050] It also includes a main control unit that communicates with the electromagnetic controllable source, the three-component detector, the controllable source pilot sensor and the rock-breaking source pilot sensor respectively. The main control unit is configured to: use the TBM controllable source-rock-breaking source seismic wave advance detection method described in any one of claims 1 to 6 for detection.

[0051] As an optional implementation method of the third aspect of the present invention, the three-component detector and the controllable seismic source pilot sensor start and begin to receive seismic records when the electromagnetic controllable seismic source excitation is detected. When the electromagnetic controllable seismic source excitation ends, the three-component detector stops working and saves the seismic records to the main control unit.

[0052] As an optional implementation method of the third aspect of the present invention, during the TBM excavation process, the main control unit controls the rock-breaking source leader sensor and the three-component detector to start at the same time to receive seismic records; when the detection is completed, the rock-breaking source leader sensor and the three-component detector are controlled to stop at the same time, and the seismic records are saved to the main control unit.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. In view of the complexity and particularity of the tunnel detection environment, the present invention innovatively proposes a tunnel boring machine controllable source-rock-breaking source advance detection system equipment. It fully utilizes the two periods of TBM downtime and construction, combines the controllable source and rock-breaking source in the detection process and detection effect, and overcomes the problems of the single detection method in traditional detection and the limitations of insufficient detection accuracy and detection coverage.

[0055] 2. The present invention innovatively proposes a method for processing controllable source and rock-breaking source data, which preliminarily removes noise through bandpass filtering, uses the cross-correlation method to remove random noise and obtain interferometric seismic records, providing a data basis for subsequent inversion and imaging.

[0056] 3. This invention innovatively proposes a joint inversion and imaging method for vibroseis and rock-breaking sources. A first full-waveform inversion is performed on the initial model using low-frequency rock-breaking source interferometric data to obtain a large-scale inversion result. This inversion result is then used as the initial model for a second full-waveform inversion using vibroseis interferometric data to obtain a more refined inversion velocity model. By comprehensively utilizing the two sets of interferometric seismic records, further structural information is obtained through reverse time migration imaging, greatly improving the accuracy of inversion imaging. By combining the low- and high-frequency characteristics of rock-breaking sources and vibroseis, the goal of fine-grained detection of TBM-constructed tunnels is achieved.

[0057] Advantages of additional aspects of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0059] FIG1 is a front view of an electromagnetic vibrator provided in Example 1 of the present invention;

[0060] FIG2 is a top view of the electromagnetic vibrator provided in Example 1 of the present invention;

[0061] FIG3 is a schematic diagram of a TBM vibroseis-rock-breaking source seismic wave advance detection system provided in Example 1 of the present invention;

[0062] FIG4 is a flow chart of a method for advanced detection of seismic waves using a TBM vibroseis-rock-breaking source, provided in Example 2 of the present invention;

[0063] Among them, 1. Excitation component; 2. Acceleration sensor; 3. Guide rail; 4. Moving component; 5. Counterweight shell; 6. Base plate; 7. Airbag; 8. Baffle plate; 9. TBM cutterhead; 10. Rock-breaking source pilot sensor; 11. Support shoe; 12. Electromagnetic controllable source; 13. Three-component detector; 14. Working platform; 15. Controllable source pilot sensor; 16. Mounting hole. DETAILED DESCRIPTION

[0064] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0065] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0066] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0067] Example 1:

[0068] Embodiment 1 of the present invention provides a TBM vibroseis-rock-breaking source seismic wave advance detection system, as shown in FIG1 , FIG2 and FIG3 , comprising:

[0069] It includes: an electromagnetic vibrator 12, a three-component detector 13, a vibrator pilot sensor 15 and a rock-breaking source pilot sensor 10;

[0070] The electromagnetic vibrator 12 is fixed to the TBM gripper 11, the three-component geophone 13 is fixed to both sides of the TBM working platform 14, the vibrator pilot sensor 15 is fixed to the rock wall near the electromagnetic vibrator 12 (specifically, the vibrator pilot sensor 15 is fixed to the rock wall separately from the TBM and is placed close to the vibrator pilot sensor 15). The rock-breaking vibrator pilot sensor 10 is located behind the TBM upper cutterhead 9.

[0071] The electromagnetic vibrator 12 includes an airbag 7, a blocking plate 8, a counterweight housing 5, a base plate 6, a guide rail 3, a moving component 4, an acceleration sensor 2, and an excitation component 1;

[0072] The guide rail 3 is arranged on the base plate 6. The counterweight housing 5 is slidably connected to the guide rail 3 through the moving component 4. The excitation component 1 and the acceleration sensor 2 are fixed to one side of the counterweight housing 5. A blocking plate 8 is fixed to the base plate 6 on the other side of the counterweight housing 5. The airbag 7 is fixed to the side of the blocking plate 8 facing the counterweight housing 5. The base plate 6 is fixedly connected to the gripper shoe 11 through the mounting hole 16.

[0073] It also includes a main control unit that communicates with the electromagnetic controllable source 12, the three-component detector 13, the controllable source pilot sensor 12 and the rock-breaking source pilot sensor 10 respectively, and the main control unit performs detection control and data analysis based on the acquired data.

[0074] Specifically, the working methods include:

[0075] S1: When the TBM is shut down, the main machine (i.e., main control unit) in the main control room controls the excitation parameters of the electromagnetic vibrator 12, including the excitation duration, waveform, and excitation force;

[0076] The airbag 7 of the electromagnetic vibrator 12 mounted on the gripper shoe 11 is inflated to ensure cushioning during the impact process, the excitation assembly 1 extends and presses against the rock wall, and the counterweight housing 5 is controlled to move forward and backward through the dynamic coil inside the vibrator to achieve the purpose of exciting vibration;

[0077] The three-component geophones 13 on both sides of the TBM working plane 14 and the pilot sensors 15 on the rock wall near the vibrator 12 are activated and begin to receive seismic records when the electromagnetic vibrator 12 is detected to be exciting;

[0078] The acceleration sensor 2 at the front end of the electromagnetic vibrator 12 can form a closed-loop control to accurately control the excitation duration, waveform and excitation force of the vibrator;

[0079] The electromagnetic vibrator 12 performs frequency division signal scanning to obtain two sets of signals, a low frequency band and a high frequency band (in this embodiment, the two frequency bands are relative concepts, for example, the low frequency band can be 10-200 Hz and the high frequency band can be 200-400 Hz, or the low frequency band can be 100 Hz-300 Hz and the high frequency band can be 300 Hz-400 Hz; the high and low frequency bands can also overlap, which will not be described in detail here). When the vibrator 12 finishes exciting, the three-component geophone 13 stops working and saves the seismic record to the host computer in the main control room;

[0080] S2: During TBM excavation, the host computer in the main control room can control the pilot sensor 10 and the three-component geophone 13 installed on the rear side of the cutterhead 9 to start simultaneously and receive seismic records;

[0081] When the detection is finished, the pilot sensor 10 and the three-component detector 13 are controlled to stop at the same time, and the earthquake record is saved in the host computer in the main control room.

[0082] Example 2:

[0083] As shown in FIG4 , embodiment 2 of the present invention provides a method for advanced detection of seismic waves of a TBM vibroseis-rock-breaking source, including the following steps:

[0084] S1: Data Processing

[0085] S1.1: Preprocessing of raw data

[0086] The rock-breaking source earthquake records, low-frequency controlled source earthquake records and high-frequency controlled source earthquake records were de-meaned and de-linearized.

[0087] S1.2: Interferometry processing is performed on the rock-breaking source seismic records and the vibroseis seismic records of the two frequency bands, and the direct wave velocity is obtained by analysis;

[0088] The cross-correlation calculation formula between the seismic record and the pilot sensor signal is as follows:

[0089] Where f(t0) and g(t0) are two signals, R(t) is the interferometric seismic record generated by cross-correlation, f(·) refers to the seismic record, and g(·) refers to the signal received by the lead sensor, which must be consistent with the seismic record component. t0 is the integral quantity used for full-time integration, and t is the independent variable of the function R(t), which is used to calculate the cross-correlation values ​​at different times.

[0090] Interference processing can be used to remove random noise and obtain interferometric seismic records. The leading signals of the rock-breaking source and the low- and high-frequency controllable source are subjected to autocorrelation processing to obtain their respective wavelet signals (autocorrelation processing is a kind of cross-correlation, which can also be calculated using formula (1). As long as the two signals f and g are the same signal, it is autocorrelation).

[0091] S1.3: De-noise the interferometric seismic data by using bandpass filtering and spectral subtraction to remove noise. Bandpass filtering uses Fourier transform to extract the main frequency information using a bandpass method, and then uses inverse Fourier transform to convert it back into seismic records:

[0092] Among them, f(t) is the time domain seismic record, and F(ω) is the frequency domain seismic record. The above processing can achieve the preliminary removal of the noise of rock-breaking source and controllable source seismic records.

[0093] S2: Multi-scale joint inversion

[0094] S2.1: Use the velocity model obtained in the data processing step as the initial model, use the waveform and arrival time (signal arrival time) of the rock-breaking source interferometric data as the fitting object, apply the rock-breaking source wavelet signal to the wave velocity model to perform forward simulation and obtain simulated seismic records, and continuously fit the simulated seismic records to the actual interferometric seismic records: E = ‖d obs -d mod ‖ 2 (4)

[0095] Where E is the error, dobs For observing earthquake records, d mod is the earthquake record obtained by forward modeling;

[0096] By taking advantage of the low frequency of rock-breaking earthquake source seismic records, large-scale inversion results are obtained, providing prior constraints for the fine inversion of controlled source seismic.

[0097] S2.2: Using the velocity model from the full waveform inversion of the rock-breaking source interferometry data as the initial model, perform full waveform inversion using the low-frequency vibroseis interferometry data, using the low-frequency vibroseis interferometry data as the fitting object, and using the wavelet record of the vibroseis leader signal autocorrelation as the source, repeat the inversion process of S2.1.

[0098] Through low-frequency controllable source interferometry data, combined with rock-breaking sources, large-scale structures are further outlined, providing inversion data supplement for distant structures, reducing the multi-solution problem of inversion using rock-breaking sources alone, and providing a better initial model for subsequent fine inversion.

[0099] S2.3: Use high-frequency vibroseis interferometry data to further invert the velocity model obtained in S2.2. Since high-frequency seismic records are better at depicting detailed structures, they can achieve the goal of fine detection.

[0100] Through multiple joint inversions of rock-breaking sources, low-frequency controllable sources and high-frequency controllable sources, the inversion results are gradually refined from the outline of large-scale structures to the characterization of detailed structures. The joint inversion method that integrates the three types of seismic records can improve the accuracy and precision of the inversion while reducing the multi-solution problem of the inversion.

[0101] S3: Reverse Time Migration Imaging

[0102] Based on the inversion velocity model obtained in S2.3, the autocorrelation wavelet record of the rock-breaking source leader signal is used as the source signal in the forward propagation process and applied at the rock-breaking source leader sensor location. The rock-breaking source seismic interferometry data is used as the source signal in the reverse propagation process and applied in reverse time at the geophone location. The wavefields of both are saved and the rock-breaking source imaging result is obtained through correlation superposition.

[0103] The wavefield cross-correlation results are calculated using the following formula:

[0104] Where I(x, y, z) is the imaging result, S(x, y, z, t) is the source wavefield record, R(x, y, z, t) is the detector wavefield record, T is the total duration, (x, y, z) is the three-dimensional coordinate of the source wave, and is the time t.

[0105] The vibroseis seismic records of the two frequency bands are imaged in the same way as the rock-breaking source to obtain the imaging results of the vibroseis, and the obtained imaging results are superimposed to obtain the final imaging result.

[0106] Example 3:

[0107] Embodiment 3 of the present invention provides a TBM vibroseis-rock-breaking source seismic wave advance detection system, comprising:

[0108] The preprocessing module preprocesses the low-frequency and high-frequency vibroseis seismic data acquired after the TBM is shut down, as well as the rock-breaking source seismic data acquired during the TBM excavation process.

[0109] The interference processing module is configured to: perform interference processing on the pre-processed low-frequency vibroseis seismic data, high-frequency vibroseis seismic data and rock-breaking source seismic data respectively as the leading sensing data to obtain interference seismic data corresponding to each seismic data;

[0110] The initial inversion model construction module is configured to: remove noise from the acquired interference seismic data based on the low-frequency vibroseis interferometric seismic data, the high-frequency vibroseis interferometric seismic data, and the rock-breaking source interferometric seismic data, obtain the seismic interferometric data with random noise removed, obtain direct wave velocity data of the seismic interferometric data, and create an inversion initial velocity model based on the direct wave velocity data;

[0111] The multi-scale inversion imaging module is configured to: perform multi-scale joint inversion based on the inverted initial velocity model to obtain a final inversion velocity model, and perform reverse time migration imaging on the final inversion velocity model to obtain a final imaging result.

[0112] The working method of the system is the same as the TBM vibroseis-rock-breaking source seismic wave advance detection method provided in Example 2, and will not be repeated here.

[0113] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for advanced detection of seismic waves of a TBM vibroseis-rock-breaking source, characterized in that: The process includes: Preprocess the low-frequency vibroseis seismic data, high-frequency vibroseis seismic data and rock-breaking seismic data acquired after the TBM is shut down, and the rock-breaking seismic data during the TBM excavation process; The pre-processed low-frequency controllable source seismic data, high-frequency controllable source seismic data and rock-breaking source seismic data are respectively subjected to interference processing by the leading sensing data to obtain the interference seismic data corresponding to each seismic data; According to the low-frequency vibroseis interference seismic data, the high-frequency vibroseis interference seismic data and the rock-breaking seismic source interference seismic data, the noise of the obtained interference seismic data is removed to obtain the seismic interference data with random noise removed, and the direct wave velocity data of the seismic interference data is obtained. According to the direct wave velocity data, an inversion initial velocity model is created; According to the inverted initial velocity model, multi-scale joint inversion is performed to obtain the final inversion velocity model, and reverse time migration imaging is performed on the final inversion velocity model to obtain the final imaging result.

2. The TBM vibroseis-rock-breaking source seismic wave advance detection method according to claim 1, characterized in that: The low-frequency vibroseis seismic data, high-frequency vibroseis seismic data and rock-breaking seismic data acquired after the TBM was shut down were de-noised, including: Bandpass filtering and spectral subtraction are used to remove noise from low-frequency controllable source seismic data, high-frequency controllable source seismic data and rock-breaking source seismic data; among them, bandpass filtering is to extract the main frequency information in the frequency domain through Fourier transform, and then use inverse Fourier transform to convert it back to seismic data.

3. The TBM vibroseis-rock-breaking source seismic wave advance detection method according to claim 1, characterized in that: According to the inverted initial velocity model, multi-scale joint inversion is performed to obtain the final inversion velocity model, including: The waveform and arrival time of rock-breaking source interference seismic data are used as fitting objects, and the wavelet signal of the rock-breaking source is applied to the inversion initial velocity model for forward simulation and simulated seismic data is obtained. The simulated seismic data and the actual interference seismic data are continuously fitted to obtain a wave velocity model based on the full waveform inversion of the rock-breaking source interference data. The velocity model of full waveform inversion of rock-breaking source interferometric data is used as the initial model, and the full waveform inversion is performed using low-frequency vibroseis interferometric data. The low-frequency vibroseis interferometric data is used as the fitting object, and the wavelet data of the autocorrelation of the vibroseis pilot signal is used as the source to obtain the velocity model based on the full waveform inversion of the low-frequency vibroseis interferometric data. The velocity model based on full waveform inversion of low-frequency vibroseis interference data is used as the initial model, and full waveform inversion is performed using high-frequency vibroseis interference data. The high-frequency vibroseis interference data is used as the fitting object, and the sub-wave data of the autocorrelation of the vibroseis pilot signal is used as the source to obtain the final inversion velocity model.

4. The TBM vibroseis-rock-breaking source seismic wave advance detection method according to claim 1, characterized in that: The leading signals of low-frequency controllable source seismic data, high-frequency controllable source seismic data and rock-breaking source seismic data are processed by autocorrelation respectively to obtain low-frequency controllable source seismic data, high-frequency controllable source seismic data and rock-breaking source seismic data. The wavelet signals corresponding to the source earthquake data.

5. The TBM vibroseis-rock-breaking source seismic wave advance detection method according to claim 1, characterized in that: The direct wave components in low-frequency vibroseis seismic data, high-frequency vibroseis seismic data and rock-breaking source seismic data are extracted, and the surrounding rock velocity information is calculated and obtained using the direct wave information. The direct wave components are cut off, and the inversion initial velocity model is created using the surrounding rock velocity information and previous exploration information.

6. The TBM vibroseis-rock-breaking source seismic wave advance detection method according to claim 1, characterized in that: Perform reverse time migration imaging on the final inversion velocity model to obtain the final imaging results, including: Apply the rock-breaking source leader signal autocorrelation wavelet data at the rock-breaking source leader sensor position, apply the rock-breaking source seismic interference data in reverse time at the detector position, save the wave fields of both, and obtain the rock-breaking source imaging result through correlation superposition; Apply high-frequency vibroseis pilot signal autocorrelation wavelet data at the vibroseis pilot sensor position, apply high-frequency vibroseis seismic interferometry data in reverse time at the geophone position, save the wave fields of both, and obtain high-frequency vibroseis imaging results through correlation superposition; Apply low-frequency vibroseis pilot signal autocorrelation wavelet data at the vibroseis pilot sensor position, apply low-frequency vibroseis seismic interferometry data in reverse time at the geophone position, save the wave fields of both, and obtain low-frequency vibroseis imaging results through correlation superposition; The final imaging result is obtained by superimposing the rock-breaking source imaging results, the high-frequency controllable source imaging results and the low-frequency controllable source imaging results.

7. A TBM vibroseis-rock-breaking source seismic wave advance detection system, characterized in that: include: A preprocessing module is used to preprocess the low-frequency vibrator seismic data and high-frequency vibrator seismic data acquired after the TBM is shut down, as well as the rock-breaking source seismic data acquired during the TBM excavation process; The interference processing module is configured to: perform interference processing on the pre-processed low-frequency controllable source seismic data, high-frequency controllable source seismic data and rock-breaking source seismic data respectively, and obtain interference seismic data corresponding to each seismic data; The initial inversion model building module is configured to: remove noise from the acquired interference seismic data according to the low-frequency vibroseis interference seismic data, the high-frequency vibroseis interference seismic data and the rock-breaking seismic source interference seismic data, obtain the seismic interference data with random noise removed, obtain the direct wave velocity data of the seismic interference data, and create an inversion initial velocity model according to the direct wave velocity data; The multi-scale inversion imaging module is configured to: perform multi-scale joint inversion according to the inverted initial velocity model to obtain a final inversion velocity model, perform reverse time migration imaging on the final inversion velocity model to obtain a final imaging result.

8. A TBM vibroseis-rock-breaking source seismic wave advance detection system, characterized in that: include: Including: electromagnetic vibrator, three-component detector, vibrator pilot sensor and rock-breaking vibrator pilot sensor; The electromagnetic vibrator is fixed on the TBM's gripper shoe, the three-component geophone is fixed on both sides of the TBM working platform, the vibrator pilot sensor is fixed on the rock wall near the electromagnetic vibrator, and the rock-breaking source pilot sensor is located at the rear side of the TBM upper cutterhead; An electromagnetic controllable vibrator, comprising: an air bag, a blocking plate, a counterweight housing, a base plate, a guide rail, a moving component, an acceleration sensor and an excitation component; The guide rail is arranged on the bottom plate, the counterweight shell is slidably connected to the guide rail through a moving component, the excitation component and the acceleration sensor are fixed on one side of the counterweight shell, a blocking plate is fixed on the bottom plate on the other side of the counterweight shell, and an airbag is fixed on the side of the blocking plate facing the counterweight shell; It also includes a main control unit that communicates with the electromagnetic controllable source, the three-component detector, the controllable source pilot sensor and the rock-breaking source pilot sensor respectively. The main control unit is configured to: use the TBM controllable source-rock-breaking source seismic wave advance detection method described in any one of claims 1-6 for detection.

9. The TBM vibroseis-rock-breaking source seismic wave advance detection system according to claim 8, characterized in that: The three-component geophone and vibrator pilot sensor start and begin to receive earthquake records when the electromagnetic vibrator excitation is detected. When the electromagnetic vibrator excitation ends, the three-component geophone stops working and saves the earthquake records to the main control unit.

10. The TBM vibroseis-rock-breaking source seismic wave advance detection system according to claim 8, characterized in that: During the TBM excavation process, the main control unit controls the rock-breaking source pilot sensor and the three-component geophone to start at the same time and receive seismic records; when the detection is completed, the rock-breaking source pilot sensor and the three-component geophone are controlled to stop at the same time, and the seismic records are saved to the main control unit.

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