A monitoring system and method for determining abnormal geologic bodies based on distributed fiber optic acoustic vibrations

Abstract

The application discloses a kind of monitoring system and method for determining abnormal geologic body based on distributed optical fiber acoustic wave vibration, it is related to distributed optical fiber acoustic wave detection technical field, including distributed optical fiber sensing unit, signal excitation unit, photoelectric demodulation unit, signal processing and analysis unit and result record and output unit etc., and distributed optical fiber is used to continuously collect stratum vibration response;Signal excitation unit applies controllable disturbance at known reference position, induces potential abnormal geologic body to generate non-active excitation response signal;Photoelectric demodulation unit carries out phase demodulation to backscattering light returned by optical fiber, forms distributed vibration measurement data;Signal processing and analysis unit filters noise reduction to data, establishes quantitative mathematical model of signal incidence angle and signal intensity, and is combined with propagation attenuation correction and least square inversion, obtains epicentral distance and incidence angle, calculates the spatial position of abnormal geologic body, and is suitable for mining and dangerous section identification and avoidance decision before construction.

Description

Technical Field

[0001] This invention belongs to the field of distributed optical fiber acoustic wave detection technology, and relates to distributed optical fiber acoustic wave vibration acquisition and formation vibration response location analysis, and particularly relates to a monitoring system and method for determining abnormal geological bodies based on distributed optical fiber acoustic wave vibration. Background Technology

[0002] As mineral resource exploration and mining continue to advance into deeper strata, and large-scale underground engineering projects (such as shafts, roadways, tunnels, and underground energy / gas storage spaces) are gradually implemented under conditions of high ground stress, high temperature, and heterogeneous surrounding rock, the demand for real-time assessment of strata stability and surrounding rock integrity at engineering sites has significantly increased. Common abnormal geological bodies in deep surrounding rock, such as weak interlayers, fracture zones, loosened zones, concealed fissure zones, and residual cavities in goaf areas, can suddenly become unstable under construction or mining disturbances, potentially triggering catastrophic events such as collapses, roof falls, water inrushes, or rock bursts. Therefore, identifying, locating, and risk-classifying potential abnormal geological bodies in the target area before mining or construction has become a crucial aspect of mine safety assessment and engineering geological hazard prevention.

[0003] Geological condition assessment is a crucial part of feasibility studies conducted before mining operations. Conventional geological assessment methods involve drilling and sampling the geological body, using rock quality indicators to comprehensively evaluate its integrity and other aspects. However, this method, due to its random sampling and inability to cover the entire area, often struggles to identify anomalous geological bodies in smaller areas or areas far from the sampling location. Furthermore, traditional seismic detectors face several technical bottlenecks in deep geological exploration: firstly, their large size makes deployment in narrow boreholes or shafts difficult; secondly, they are highly sensitive to environmental conditions such as temperature, humidity, and electromagnetic fields, exhibiting significant performance degradation or even failure in high-temperature or strong electromagnetic interference environments at depth; thirdly, the spatial resolution of point sensors is limited, requiring extensive deployment to achieve high monitoring density, leading to high system costs and complex construction; and fourthly, traditional detectors have weak anti-interference capabilities, with a significant decrease in signal-to-noise ratio in environments with strong interference, such as mechanical construction and blasting operations.

[0004] Distributed Acoustic Sensing (DAS) systems offer high stability, high signal quality, high sensitivity, and wide-coverage networking capabilities, enabling comprehensive, real-time monitoring of mining operations. However, in complex geological formations, vibration signal propagation is affected by multipath propagation, scattering, and anisotropic attenuation, leading to non-steady-state characteristics in amplitude and spectral morphology. Simultaneously, the coupling quality between the well and the formation, the coupling stiffness between the optical fiber and the soil / rock mass, the fixing method, and contact conditions directly impact observation sensitivity and response consistency. Effectively separating engineering disturbances, environmental noise, and the response of anomalous geological bodies in environments with strong background noise and non-stationary conditions remains a challenge for engineering applications.

[0005] In summary, existing geological exploration and anomaly detection technologies suffer from numerous shortcomings, including limited coverage, insufficient spatial resolution, poor environmental adaptability, and low positioning accuracy. Therefore, achieving high coverage and high signal-to-noise ratio continuous monitoring under complex deep geological conditions, and reliably, accurately, and engineering-usable spatial positioning and extent determination of potential anomalies, is an urgent problem to be solved. Summary of the Invention

[0006] (a) Purpose of the invention

[0007] In view of this, the present invention aims to provide a monitoring system and method for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration. By employing distributed optical fiber acoustic vibration sensing technology, high-density continuous signal acquisition is achieved using the Rayleigh scattering effect in optical fibers. Combined with a detection mechanism that actively excites vibration signals to induce responses in anomalous geological bodies, a mathematical relationship between signal intensity and spatial location is established by introducing signal incident angle parameters and a plane wave attenuation model. The spatial coordinates of anomalous geological bodies are accurately calculated through an inversion positioning algorithm. This allows for intelligent detection of the strata at the site before mining, construction, etc., to identify risky strata and avoid or specially treat anomalous geological strata during operations, ensuring safety before, during, and after operations.

[0008] (II) Technical Solution

[0009] To achieve the objective of this invention and solve its technical problems, the present invention adopts the following technical solution:

[0010] The first objective of this invention is to provide a monitoring system for identifying anomalous geological bodies based on distributed fiber optic acoustic vibration, used for identifying and locating anomalous geological bodies in target strata in scenarios such as mining and underground engineering construction, comprising at least:

[0011] The distributed optical fiber sensing unit includes a distributed optical fiber sensing medium that extends along the well or borehole wall of the target monitoring area and forms a mechanical transmission contact relationship with the corresponding stratum. It is used to continuously collect vibration signals generated by the surrounding rock or stratum under external disturbance and output the collected signals in the form of backscattered light signals transmitted back along the optical fiber.

[0012] The signal excitation unit is used to apply a controllable external disturbance to the target monitoring area to generate an active excitation vibration signal for calibrating the mechanical response characteristics of the target strata, induce potential anomalous geological bodies to undergo stress response or local rupture under the action of external disturbance and generate an identifiable non-active excitation response signal, wherein the excitation position of the active excitation vibration signal is a known reference position.

[0013] The photoelectric demodulation unit is connected to the optical signal of the distributed optical fiber sensing unit. It is used to inject probe laser into the distributed optical fiber sensing medium and perform photoelectric conversion and phase demodulation processing on the received backscattered light signal to extract the amplitude, frequency and phase information of the vibration signal. The demodulated vibration data is organized according to the optical fiber spatial position and time sequence to form distributed vibration measurement data.

[0014] The signal processing and analysis unit is electrically connected to the photoelectric demodulation unit and has a built-in inversion positioning algorithm for locating anomalous geological bodies. It is used to identify and locate anomalous geological bodies from the demodulated distributed vibration measurement data. The inversion positioning algorithm establishes a quantitative mathematical model of incident angle and signal intensity based on the active excitation vibration signal with known excitation location and corrects it according to medium attenuation. Based on the established quantitative mathematical model, it inverts the incident angle and epicentral distance of the non-active excitation response signal and combines the optical fiber layout geometry to obtain the spatial location of the anomalous geological body in the target monitoring area.

[0015] The result recording and output unit (preferred) is electrically connected to the signal processing and analysis unit. It is used to record, store and output the vibration response time series data, filtered signal, calibration model parameters, signal incident angle and epicentral distance solution results, and spatial location determination results of abnormal geological bodies obtained by signal processing and analysis, for subsequent risk assessment, early warning classification, engineering treatment and construction decision-making.

[0016] The distributed optical fiber sensing unit, signal excitation unit, signal demodulation unit, signal processing and analysis unit, and result recording and output unit work together to enable the monitoring system to obtain high spatial resolution distributed vibration response information under deep and complex surrounding rock conditions, and to quantitatively identify and spatially locate abnormal geological bodies based on the distributed vibration response information.

[0017] The second objective of this invention is to provide a monitoring method for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration. The monitoring system for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration, as described above, includes at least the following steps:

[0018] S100. Distributed Fiber Laying and System Initialization: Distributed fiber optic sensing media are laid in a manner parallel to the wall and conforming to constraints in a pre-set well or borehole in the target monitoring area. The spatial layout coordinate information of the fiber body is acquired and recorded to establish the correspondence between the spatial position of the fiber and the position of the stratum. The connection between each unit is completed, and the signal is debugged to ensure that the laser output and signal input are correct.

[0019] S200. Active excitation and response triggering: The signal excitation unit applies a controllable external disturbance to the target monitoring area, generates an active excitation vibration signal at a known reference location to calibrate the mechanical response characteristics of the target strata, induces potential anomalous geological bodies to undergo stress response or local fracturing under the action of external disturbance, and generates an identifiable non-active excitation response signal.

[0020] S300. Optical demodulation and measurement data formation: The photoelectric demodulation unit injects a probe laser into the optical fiber, receives the backscattered light signal transmitted along the optical fiber, and extracts the amplitude, frequency and phase information of the vibration signal through photoelectric conversion and phase demodulation. The demodulation results are organized according to the correspondence between the position along the optical fiber and the time series to form distributed vibration measurement data covering each sampling position segment.

[0021] S400. Data Preprocessing and Feature Extraction: Distributed vibration measurement data are filtered and denoised. Based on the amplitude square and frequency distribution characteristics of the vibration signal, the cutoff frequency, passband edge frequency and filter order are set to suppress background environmental noise and retain the effective vibration components related to the actual mechanical response of the strata. Actively excited vibration signals are distinguished from non-actively excited response signals generated by anomalous geological bodies, and the average peak amplitude, arrival time and propagation direction information of each sampling location segment are extracted.

[0022] S500. Construction of mathematical model for incident angle and signal intensity: The active excitation vibration signal at a known excitation position is used as the calibration signal. Based on the spatial geometric relationship between the excitation position and each sampling position segment, the angle between the vibration propagation direction and the fiber optic laying direction at each sampling position segment is determined as the signal incident angle. A quantitative mathematical model of the signal incident angle and signal intensity of the active excitation vibration signal source is established, and the signal intensity is attenuated and corrected.

[0023] S600. Inversion Solution and Location of Anomalous Geological Bodies: The characteristic parameters of the non-actively excited response signal are substituted into the mathematical model for signal analysis. The signal incident angle and epicentral distance are taken as unknowns to be solved. The optimal solution is obtained by least squares solution. The spatial location of the anomalous geological body in the target monitoring area is calculated by combining the geometric relationship of the fiber optic body. This enables the identification and location of the anomalous geological body.

[0024] (III) Technical Effects

[0025] Compared with existing technologies, the monitoring system and method for determining anomalous geological bodies based on distributed optical fiber acoustic vibration provided by this invention have the following advantages:

[0026] (1) This invention uses a distributed optical fiber sensing medium to generate an active excitation signal by drilling or deploying an excitation source at a known location in the well. Under controlled disturbance conditions, it induces stress response or local rupture in potential abnormal geological bodies (such as fracture zones, loose zones, and residual voids from mining), thereby generating a non-active excitation response signal. The location of the abnormal geological body is obtained by picking up and locating the response signal through optical fiber. Compared with traditional detectors, the distributed optical fiber acoustic vibration sensing system used in this invention has the advantages of flexible deployment, long-term online operation in deep and complex environments, strong anti-electromagnetic interference capability, high signal-to-noise ratio, and lower overall cost, and can realize continuous and wide-area structural anomaly detection.

[0027] (2) Conventional geological assessment using borehole sampling methods often fails to identify anomalous geological bodies in smaller areas and areas far from the sampling location due to the randomness of the sampling and the inability to cover all areas. This invention utilizes a distributed fiber optic acoustic vibration sensing system, where each meter is equivalent to a point sensor. It has advantages such as high spatial resolution, high sensitivity, and high coverage, enabling full-segment scanning detection of the target area and significantly improving the ability to detect potential anomalous geological bodies.

[0028] (3) This invention establishes a calculable physical correspondence between the measured fiber vibration response and the spatial location of the strata by constructing a quantitative mathematical model of the signal incident angle and signal intensity, and introducing a propagation distance attenuation term into the model. Furthermore, by combining the epicentral distance and incident angle obtained by least squares inversion, the location of the abnormal geological body can be quantitatively located, which can provide direct engineering input for subsequent risk classification, avoidance decision-making, and reinforcement and treatment, and improve the safety assurance capabilities before, during and after construction. Attached Figure Description

[0029] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 A block diagram of a monitoring system for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration.

[0031] Figure 2 A flowchart of a monitoring method for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration;

[0032] Figure 3 A schematic diagram illustrating the deployment of distributed optical fibers in a well and the establishment of a coordinate system.

[0033] Figure 4 This diagram illustrates the distributed optical fiber acoustic vibration monitoring signal data. Figure a shows the full-channel vibration response time series obtained after the distributed optical fiber was deployed along the shaft. The data is from a delayed blasting operation in the mine (a total of 7 blasts). The horizontal axis represents time (in ms), and the vertical axis represents the number of channels (dimensionless, each channel corresponds to an independent sampling position segment on the optical fiber). The color intensity indicates the phase magnitude. Figure b shows the vibration waveform of the sampling position segment corresponding to channel 1250 in a. The horizontal axis represents time (ms), and the vertical axis represents vibration intensity (rad / s), showing the actively excited vibration signal and the subsequent delayed high-amplitude response. Figure c shows the vibration waveform of the sampling position segment corresponding to channel 950 in a. The horizontal axis represents time (ms), and the vertical axis represents vibration intensity (rad / s). It can be seen that a secondary vibration signal with a significantly higher amplitude than the background noise appears about 5-6 seconds after the blast ends. This signal corresponds to the non-actively excited response of the anomalous geological body under active excitation. Figure d shows the vibration signal sequence generated by the 7 blasts, used to characterize the overall temporal characteristics of the active excitation event.

[0034] Figure 5 A schematic diagram of the fitting curve for the mathematical model;

[0035] Figure 6 This is a schematic diagram showing the location of the anomalous geological body.

[0036] Explanation of reference numerals in the attached figures: Distributed optical fiber sensing unit 10, signal excitation unit 20, signal demodulation unit 30, signal processing and analysis unit 40, result recording and output unit 50, surrounding rock or stratum 60. Detailed Implementation

[0037] This invention aims to provide a monitoring system and method for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration, used for identifying and locating anomalous geological bodies in target strata in scenarios such as mining and underground engineering construction. The technical solution of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0038] Example 1: Monitoring System

[0039] As a specific example, see Figure 1 As shown, the monitoring system for determining anomalous geological bodies based on distributed optical fiber acoustic vibration provided by this invention includes a distributed optical fiber sensing unit 10, a signal excitation unit 20, a photoelectric demodulation unit 30, a signal processing and analysis unit 40, and a result recording and output unit 50, etc., connected in sequence. The system is suitable for mine shafts or engineering borehole scenarios and operates according to the process of active excitation-distributed acquisition-demodulation-modeling-inversion positioning. Specifically:

[0040] The distributed optical fiber sensing unit 10 includes a distributed optical fiber sensing medium that extends along the well or borehole wall of the target monitoring area and forms a mechanical transmission contact relationship with the corresponding stratum position. It is used to continuously collect vibration signals generated by the surrounding rock or stratum 60 under external disturbance and output the collected signals in the form of backscattered light signals transmitted back along the optical fiber.

[0041] The signal excitation unit 20 is used to apply a controllable external disturbance to the target monitoring area to generate an active excitation vibration signal for calibrating the mechanical response characteristics of the target strata, induce potential abnormal geological bodies to undergo stress response or local rupture under the action of external disturbance and generate an identifiable non-active excitation response signal, wherein the excitation position of the active excitation vibration signal is a known reference position.

[0042] The photoelectric demodulation unit 30 is connected to the optical signal of the distributed optical fiber sensing unit. It is used to inject probe laser into the distributed optical fiber sensing medium and perform photoelectric conversion and phase demodulation processing on the received backscattered light signal to extract the amplitude, frequency and phase information of the vibration signal. The demodulated vibration data is organized according to the spatial position and time sequence of the optical fiber to form distributed vibration measurement data.

[0043] The signal processing and analysis unit 40 is electrically connected to the photoelectric demodulation unit 30. It has a built-in inversion positioning algorithm for locating anomalous geological bodies. It is used to identify and locate anomalous geological bodies from the demodulated distributed vibration measurement data. The inversion positioning algorithm establishes a quantitative mathematical model of the incident angle and signal intensity based on the active excitation vibration signal with known excitation location and corrects it according to the medium attenuation. Based on the established quantitative mathematical model, it inverts the incident angle and epicentral distance of the non-active excitation response signal and combines the optical fiber layout geometry to obtain the spatial position of the anomalous geological body in the target monitoring area.

[0044] The result recording and output unit 50 is electrically connected to the signal processing and analysis unit. It is used to record, store and output the vibration response time series data, filtered signal, calibration model parameters, signal incident angle and epicentral distance solution results, and spatial location determination results of abnormal geological bodies obtained by signal processing and analysis, so as to be used for subsequent risk assessment, early warning classification, engineering treatment and construction decision-making.

[0045] Among them, the distributed optical fiber sensing unit 10, the signal excitation unit 20, the signal demodulation unit 30, the signal processing and analysis unit 40, and the result recording and output unit 50 work together to enable the monitoring system to obtain distributed vibration response information with high spatial resolution under deep and complex surrounding rock conditions, and to quantitatively identify and spatially locate abnormal geological bodies based on the distributed vibration response information.

[0046] Preferably, the distributed optical fiber sensing medium is a continuous sensing medium used to continuously acquire vibration signals generated by the surrounding rock or formation 60 during monitoring. The optical fiber itself is fixed to the well wall or borehole wall of the target monitoring area through a tight fit and constraint method such as grouting, expansion anchoring, or mechanical clamping. A stable mechanical transmission contact relationship is formed between the optical fiber and the surrounding rock or formation 60 to improve the stability of vibration response transmission and signal acquisition sensitivity, ensuring that the vibration signal can be transmitted to the optical fiber body efficiently and with high fidelity. For smaller boreholes, it is not necessary to fix the optical fiber body. Furthermore, the optical fiber body has continuously arranged sampling position segments along its length, each corresponding to an independent monitoring point, enabling the optical fiber body to output vibration response information corresponding to each sampling position segment with high spatial resolution along its length.

[0047] Specifically, the distributed optical fiber sensing unit 10 in this invention utilizes Rayleigh scattering. When a laser beam is incident on the optical fiber, due to the presence of scatterers within the fiber, the incident laser is reflected back to the photoelectric demodulation unit 30. The photoelectric demodulation unit 30 receives and analyzes the reflected light. When the optical fiber is subjected to external disturbances, the spacing between the scatterers inside the fiber and the refractive index change, thereby altering various parameters of the reflected light. By demodulating the reflected light, the intensity of the external disturbance can be obtained.

[0048] Figure 3 The diagram illustrates the fiber optic cable deployment within the well and the establishment of the coordinate system. The fiber optic cable is vertically positioned close to the well wall. The coordinate system provides a reference for subsequent positioning. The distributed fiber optic sensing medium utilizes Rayleigh scattering to achieve distributed vibration monitoring. When external vibration disturbances affect the distributed fiber optic sensing medium, the spacing between scatterers and the refractive index within the fiber change, causing corresponding changes in the amplitude, frequency, and phase of the reflected light generated by the incident laser. This converts the mechanical vibration signal into an optical signal. The distributed fiber optic sensing unit 10 simultaneously receives actively excited vibration signals and passively excited signals generated by responses from anomalous geological bodies. Each meter of the distributed fiber optic sensing medium corresponds to an independent sensing point, enabling continuous monitoring with high spatial resolution.

[0049] Preferably, the signal excitation unit 20 in this embodiment of the invention is used to generate an active excitation vibration signal in the target stratum and to acquire the signal generated by the anomalous geological body, i.e., the non-active excitation signal, using the active excitation vibration signal. Specifically, the active excitation vibration signal is realized by at least one of a seismic source vehicle, a hydraulic seismic source, a pneumatic hammer, an electromagnetic vibrator, or a blasting excitation device. By actively exciting the vibration signal, the potential anomalous geological body is induced to produce a stress response or local rupture, thereby generating a non-active excitation signal from the anomalous geological body, which is used to locate the anomalous geological body. Furthermore, the signal excitation unit 20 has programmable control capabilities for excitation timing, amplitude, and main frequency, and is used to inject controllable mechanical impact energy or blasting impact energy into the target monitoring area to generate a repeatable and quantifiable active excitation vibration signal in the surrounding rock or stratum. By applying a controllable active excitation vibration signal at a known location, the vibration propagation characteristics and signal attenuation law under different stratum conditions can be calibrated, and the potential anomalous geological body can be induced to produce a stress response or local rupture, causing it to generate a non-active excitation response signal that is different from the active excitation signal. Furthermore, the signal excitation unit 20 is equipped with a depth encoder or positioning marker to record the excitation reference position, providing a geometric reference for subsequent incident angle calculation, epicentral distance estimation, and abnormal geological body location.

[0050] Preferably, the photoelectric demodulation unit 30 in this embodiment employs phase-sensitive optical time-domain reflectometry (OTDR) to inject a narrow-linewidth probe laser into the distributed optical fiber sensing medium and receive backscattered light caused by Rayleigh scattering. Through coherent detection and phase demodulation techniques, the backscattered light signal is photoelectrically converted and phase-demodulated based on the Rayleigh scattering echo returning along the optical fiber to extract distributed vibration measurement data containing amplitude, frequency, phase, and arrival time. The photoelectric demodulation unit maintains a one-to-one correspondence between the measurement data and the position along the optical fiber to achieve pinpoint acquisition of vibration responses at different depths. Finally, the demodulated vibration data is organized according to the spatial position and time sequence of the optical fiber to form distributed measurement data which is then transmitted to the signal processing and analysis unit 40.

[0051] As a preferred embodiment of the present invention, the signal processing and analysis unit 40 includes a preset inversion positioning method that uses the optical fiber incident angle for positioning. The inversion positioning method quantitatively analyzes the relationship between the signal incident angle and the signal strength and establishes a mathematical model of the signal incident angle and the signal strength. In establishing the relationship between the signal incident angle and the signal strength, the inversion positioning method introduces a plane wave attenuation model to reduce the positioning error caused by signal attenuation during transmission.

[0052] Specifically, the signal processing and analysis unit 40 includes a signal preprocessing module for filtering and denoising the distributed vibration measurement data to reduce background environmental noise and retain effective vibration components related to the actual mechanical response of the surrounding rock or subsurface. The filtering and denoising preprocessing is based on the square of the spectral amplitude X(ω) of the vibration signal at angular frequency ω, S(ω) = |X(ω)|. 2 As an energy characterization quantity, the frequency response transfer function |H(ω)| is used. 2 =1 / [1+(ω / ω c ) 2n ]=1 / [1+ε 2 ·(ω / ω p ) 2n Weighted suppression is applied to components of different frequencies, where ω c ω is the cutoff angular frequency and the position where the amplitude decays to -3dB. p Here, n is the passband edge frequency, n is the filter order used to control the high-frequency roll-off slope, and ε is a dimensionless parameter related to the amplitude attenuation at the passband edge, and when 1 / (1+ε) 2 )=|H(ω)| 2 This indicates that the device is at the edge of the passband.

[0053] Furthermore, when establishing and correcting the quantitative mathematical model of incident angle and signal intensity for locating anomalous geological bodies, the signal processing and analysis unit 40 first calculates the average peak amplitude, arrival time, and propagation direction information at each sampling location segment along the distributed optical fiber sensing medium based on the actively excited vibration signal at the known excitation location. Then, it determines the signal incident angle of each sampling location segment according to the spatial geometric relationship between the known excitation location and each sampling location segment. After that, it models the correlation between the signal incident angle θ and the corresponding average peak amplitude A, and introduces the distance attenuation characteristics of the formation medium on the propagation of vibration waves to correct the average peak amplitude according to the plane wave attenuation equation A(x)=A0·exp(-αx), where x is the epicentral distance, A0 is the initial amplitude, α is the attenuation coefficient caused by medium absorption and α=ω / (2Q·v)=π·f / (Q·v), ω=2πf is the angular frequency, f is the signal frequency, Q is the medium quality factor, and v is the P-wave velocity. The influence of propagation distance on signal intensity is eliminated through attenuation correction.

[0054] In addition, when the signal processing and analysis unit 40 locates and solves the non-actively excited response signal generated by the potential anomalous geological body, it substitutes the characterization parameters of the non-actively excited response signal into the quantitative mathematical model of the incident angle and signal intensity, and uses the signal incident angle θ and epicentral distance x as unknowns to be solved. The least squares method is used to solve for the optimal solution of the two. Then, combined with the geometric relationship of the distributed optical fiber sensing medium in the well or borehole, the spatial coordinates of the anomalous geological body in the target monitoring area are calculated based on the well or borehole coordinate system. The target location of the anomalous geological body is output in the form of well depth coordinates, mileage coordinates or section coordinates for engineering calibration, zoning control and construction avoidance.

[0055] Preferably, the result recording and output unit 50 in this embodiment of the invention is electrically connected to the signal processing and analysis unit 40. It is used to record, archive and output the filtered distributed vibration measurement data, calibration model parameters, signal incident angle and epicentral distance obtained by the least squares method, and spatial location determination results of abnormal geological bodies obtained by geometric inversion, and generate a location result dataset for subsequent risk assessment, early warning classification and reinforcement or avoidance decision-making.

[0056] It should be noted that this invention continuously collects vibration responses through distributed optical fiber sensing units, generates controllable active excitation vibration signals using signal excitation units to induce responses from potential anomalous geological bodies, acquires high spatial resolution distributed vibration measurement data based on photoelectric demodulation units, establishes a quantitative mathematical model of signal incident angle and signal intensity through signal processing and analysis units and introduces plane wave attenuation correction, and finally uses the least squares method to invert and solve for the epicentral distance and signal incident angle of the anomalous geological body. Combined with the geometric relationship of optical fiber deployment, it achieves accurate spatial positioning of the anomalous geological body, providing an effective technical means for the engineering deployment of geological disaster monitoring, risk identification, and construction decision-making under deep and complex geological conditions.

[0057] Example 2: Monitoring Method

[0058] Based on Embodiment 1 above, Embodiment 2 further discloses a monitoring method for determining anomalous geological bodies based on distributed optical fiber acoustic vibration, applying... Figure 1 The monitoring system shown is based on distributed fiber optic acoustic vibration to determine anomalous geological bodies, such as... Figure 2 As shown, the method mainly includes the following steps when implemented:

[0059] S100. Distributed Fiber Laying and System Initialization: Distributed fiber optic sensing media are laid in a manner parallel to the wall and conforming to constraints in a pre-set well or borehole in the target monitoring area. The spatial layout coordinate information of the fiber body is acquired and recorded to establish the correspondence between the spatial position of the fiber and the position of the stratum. The connection between each unit is completed, and the signal is debugged to ensure that the laser output and signal input are correct.

[0060] S200. Active excitation and response triggering: The signal excitation unit applies a controllable external disturbance to the target monitoring area, generates an active excitation vibration signal at a known reference location to calibrate the mechanical response characteristics of the target strata, induces potential anomalous geological bodies to undergo stress response or local fracturing under the action of external disturbance, and generates an identifiable non-active excitation response signal.

[0061] S300. Optical demodulation and measurement data formation: The photoelectric demodulation unit injects a probe laser into the optical fiber, receives the backscattered light signal transmitted along the optical fiber, and extracts the amplitude, frequency and phase information of the vibration signal through photoelectric conversion and phase demodulation. The demodulation results are organized according to the correspondence between the position along the optical fiber and the time series to form distributed vibration measurement data covering each sampling position segment.

[0062] S400. Data Preprocessing and Feature Extraction: Distributed vibration measurement data are filtered and denoised. Based on the amplitude square and frequency distribution characteristics of the vibration signal, the cutoff frequency, passband edge frequency and filter order are set to suppress background environmental noise and retain the effective vibration components related to the actual mechanical response of the strata. Actively excited vibration signals are distinguished from non-actively excited response signals generated by anomalous geological bodies, and the average peak amplitude, arrival time and propagation direction information of each sampling location segment are extracted.

[0063] S500. Construction of mathematical model for incident angle and signal intensity: The active excitation vibration signal at a known excitation position is used as the calibration signal. Based on the spatial geometric relationship between the excitation position and each sampling position segment, the angle between the vibration propagation direction and the fiber optic laying direction at each sampling position segment is determined as the signal incident angle. A quantitative mathematical model of the signal incident angle and signal intensity of the active excitation vibration signal source is established, and the signal intensity is attenuated and corrected.

[0064] S600. Inversion Solution and Location of Anomalous Geological Bodies: The characteristic parameters of the non-actively excited response signal are substituted into the learning model for signal analysis. The signal incident angle and epicentral distance are taken as unknowns to be solved. The optimal solution is obtained by least squares solution. Combined with the geometric relationship of the fiber optic cable layout, the spatial location of the anomalous geological body in the target monitoring area is calculated, so as to realize the identification and location of the anomalous geological body.

[0065] Preferably, the data preprocessing and feature extraction in step S400 includes the following sub-steps:

[0066] S401. Frequency Domain Filtering and Noise Reduction: Perform a frequency domain transformation on the original vibration signal x(t) to obtain the spectrum X(ω), where ω is the angular frequency, and calculate the power spectral density S(ω) = |X(ω)|. 2 The frequency distribution characteristics of the signal energy are identified, and filtering parameters are determined based on the energy distribution of S(ω). Noise suppression is then applied to the distributed vibration measurement data. The cutoff angular frequency ω is preset based on the dominant frequency range of the actively excited signal and the frequency characteristics of the geological body's response signal. c (Set at the upper limit of the effective signal frequency band), passband edge frequency ω p The filter order n (selected according to the required attenuation steepness, usually 4-8) and the passband edge attenuation parameter ε are used to construct the frequency response transfer function |H(ω)|. 2 =1 / [1+(ω / ω c ) 2n ]=1 / [1+ε 2 ·(ω / ω p ) 2n ], and with |H(ω)| 2 Suppress background noise;

[0067] S402. Event Separation and Feature Parameter Extraction: Based on signal arrival time, frequency characteristics, and amplitude characteristics, event separation is performed on the filtered distributed vibration measurement data to distinguish between actively excited vibration signals and inactively excited response signals generated by potential anomalous geological bodies. The arrival time and excitation time of actively excited vibration signals have a clear temporal correspondence, and their spectral characteristics are consistent with the set excitation parameters. Inactively excited response signals, on the other hand, are vibration events that occur randomly and whose spectral characteristics may differ from those of the excitation signals. For each sampling location segment, the average peak amplitude (as a parameter representing signal strength), arrival time (used to calculate propagation distance), and vibration propagation direction (used to calculate the incident angle) are extracted as feature parameters for subsequently constructing a mathematical model of the incident angle and signal strength.

[0068] Preferably, step S500 includes the following sub-steps when constructing the mathematical model of incident angle and signal strength:

[0069] S501. Average Peak Amplitude Statistics: The active excitation vibration signal is analyzed. For each sampling location segment along the main body of the optical fiber, the average peak amplitude of the active excitation vibration signal is extracted and statistically analyzed, which serves as the amplitude characteristic parameter characterizing the local formation response intensity of each sampling location segment.

[0070] S502. Signal incident angle calculation: Based on the known spatial geometric relationship between the excitation position and each sampling position segment, determine the vibration propagation direction vector from the excitation position to each sampling position segment, and define the angle between the vibration propagation direction and the fiber optic cable laying direction as the signal incident angle of the sampling position segment, which is used to characterize the directional characteristics of the vibration wave incident on the fiber optic cable.

[0071] S503. Propagation distance attenuation correction: The average peak amplitude of each sampling location segment is corrected for propagation distance attenuation to compensate for the amplitude attenuation of the vibration signal caused by energy dissipation in the medium. The correction form is A(x)=A0·exp(-αx), where x is the epicentral distance, A0 is the initial amplitude, α is the attenuation coefficient caused by medium absorption and α=ω / (2Q·v)=π·f / (Q·v), ω=2πf is the angular frequency, f is the signal frequency, Q is the medium quality factor and is used to characterize the energy dissipation characteristics of the medium, and v is the P-wave velocity and is used to characterize the energy attenuation characteristics of the medium.

[0072] S504. Establishment of mathematical model for incident angle and signal strength: The average peak amplitude A(x) after propagation distance attenuation correction is correlated with the signal incident angle of the corresponding sampling position segment, and a quantitative functional relationship model between the two is established by nonlinear curve fitting method.

[0073] Preferably, step S600 includes the following sub-steps when performing inversion solving and locating anomalous geological bodies:

[0074] S601. Statistical Analysis of Inactive Excitation Signal Amplitude: Analyze the inactive excitation response signals generated by potential anomalous geological bodies, and statistically analyze the average peak amplitude A at each sampling location along the fiber optic cable. 20 This is used as the amplitude characteristic parameter of the abnormal response event at each sampling location segment;

[0075] S602. Equation Substitution and Unknown Setting: Substitute the statistically obtained average peak amplitude A 20 Substituting the signal incident angle and signal intensity quantitative mathematical model constructed in step S500, and using the signal incident angle θ and epicentral distance x as unknowns to be determined, a model is formed based on A. 20 Solve a system of equations with known quantities and x and θ as unknowns;

[0076] S603. Least Squares Inversion Solution: The least squares method is used to solve the equation set to obtain the optimal solution for the epicentral distance x and the signal incident angle θ, which is used to characterize the propagation distance parameter and incident direction parameter of the anomalous geological body corresponding to the non-actively excited response signal;

[0077] S604. Spatial location of anomalous geological bodies: Based on the optimal solutions of x and θ, combined with the coordinate system of the distributed optical fiber sensing medium and the spatial geometric relationship of the monitoring area, the spatial coordinates of the anomalous geological bodies within the target monitoring area are calculated.

[0078] It should be noted that the monitoring method of the present invention induces potential anomalous geological bodies to generate identifiable non-active excitation response signals by deploying distributed optical fiber sensing media in the target monitoring area and applying controllable active excitation vibration signals. The distributed vibration measurement data is filtered, denoised, and feature extracted. A quantitative mathematical model of signal incident angle and signal intensity is established based on the active excitation vibration signal at the known excitation location, and a propagation distance attenuation correction is introduced. The non-active excitation response signal is substituted into the model and the least squares method is used to invert and solve for the epicentral distance and signal incident angle. The spatial location of the anomalous geological body is calculated by combining the geometric relationship of the optical fiber deployment. This method realizes the quantitative identification and precise positioning of anomalous geological bodies under deep and complex surrounding rock conditions.

[0079] Example 3: Application Case

[0080] Based on the above embodiments 1 and 2, this embodiment 3 provides a specific application case of a monitoring system and method for determining abnormal geological bodies based on distributed optical fiber acoustic vibration in actual engineering, in order to verify the effectiveness and practicality of the technical solution.

[0081] The monitoring system described in Example 1 has the following system composition: Figure 1 As shown, optical fiber serves as the distributed optical fiber sensing medium, employing the principle of phase-sensitive optical time-domain reflectometry (OTDR) and achieving continuous distributed vibration sensing based on Rayleigh scattering. The photoelectric demodulator corresponds to the photoelectric demodulation unit 30, responsible for laser injection, backscattered light reception, and phase demodulation. The computer integrates the functions of the signal processing and analysis unit 40 and the result recording and output unit 50, and includes a built-in inversion positioning algorithm program. (As shown...) Figure 3 As shown, optical fibers are deployed vertically in a granite mine shaft, parallel to the shaft wall. A specialized fixing device is used to secure the fibers tightly against the shaft wall, ensuring good coupling between the fibers and the surrounding rock, allowing rock vibrations to be effectively transmitted to the fibers and generate axial strain. Coordinate system establishment: A three-dimensional rectangular coordinate system is established with the shaft opening as the origin and the shaft axis as the positive Z-axis, providing a geometric reference for subsequent anomaly location.

[0082] Applying steps S200 and S300 of the method described in Example 2, a delayed blasting method is used as the signal excitation unit 20. Seven delayed blasts are performed at a known location near the wellhead, with an interval of approximately 200 ms between each blast. The excitation parameters are: explosive equivalent of 50 kg and dominant frequency of approximately 150 Hz. The actively excited vibration signal generated by the blast propagates into the deep formation. On the one hand, it generates observable vibration responses at each sampling point of the optical fiber, which are used to establish a quantitative calibration model. On the other hand, it applies stress disturbance to potential deep geological anomalies, inducing stress adjustment or local fracturing, thereby generating non-actively excited response signals. The distributed optical fiber sensing system continuously records vibration data at a spatial sampling interval of 1 meter and a time sampling frequency of 2 kHz. Figure 4 Figure a shows the received raw vibration signal data: the horizontal axis represents time (in milliseconds), the vertical axis represents the channel number (each channel corresponds to an independent sampling point 1 meter long on the optical fiber), and the color intensity represents the vibration phase intensity. The figure clearly shows the active excitation signals of 7 delayed blasts.

[0083] Data preprocessing is performed using step S400 as described in Example 2. Frequency domain filtering is used for noise reduction, and the cutoff frequency ω is set. c =100Hz, filter order n=6, frequency response transfer function is |H(ω)| 2 =1 / [1+(ω / ω c ) 2n It effectively suppresses high-frequency background noise. Figure 4 The b and c distributions in the figure show the vibration waveform after filtering in a certain channel. The horizontal axis represents time (ms), and the vertical axis represents vibration intensity (rad / s). In the 5000-6000ms period after the end of the 7 blasts, multiple optical fiber channels experienced another vibration event with an amplitude much higher than the background noise. The occurrence time of this signal did not correspond to the blasting sequence, and its spectral characteristics were slightly different from the actively excited signal. It was determined to be a non-actively excited response signal generated by an abnormal geological body under the disturbance of blasting. Figure 4 The data in the middle section comprehensively demonstrates the temporal characteristics of the vibration signals from the seven blasts.

[0084] Applying the S500 step described in Example 2, a quantitative mathematical model is established using seven active excitation signals. The average peak amplitude of each sampling location segment is statistically analyzed, and the signal incident angle θ is calculated based on the blasting location coordinates and the geometric relationship of the fiber optic cable layout. Considering vibration propagation attenuation, the plane wave attenuation equation A(x) = A0·exp(-αx) is used for correction, with an attenuation coefficient α = πf / (Qv). With a dominant frequency f = 150Hz, P-wave velocity v = 2.61 km / s, and granite quality factor Q = 100, α = 0.0018 is calculated. The corrected amplitude A0 is nonlinearly fitted to the incident angle θ using an Allometric model to establish a quantitative mathematical model, and the results are as follows. Figure 5 As shown.

[0085] Applying the S600 step described in Example 2, the average peak amplitude of the non-actively excited response signal is substituted into the established mathematical model, and the least squares method is used to simultaneously solve for the signal incident angle and epicentral distance. The optimal solution is obtained through iterative optimization calculations, and combined with the geometric relationship of the fiber optic cable layout, the spatial coordinates of the anomalous geological body are calculated. Figure 6 Showing the Figure 4 The two-dimensional positioning results of the non-actively excited signal source in the well successfully determined the depth and radial distance of the anomalous geological body relative to the well axis, with a positioning accuracy of meter level.

[0086] This application example verifies the effectiveness of the monitoring system and method, demonstrating the feasibility and accuracy of the technical approach of establishing a quantitative model through active excitation and inverting and locating non-active response signals under actual complex geological conditions, and providing a reliable technical means for monitoring abnormal geological bodies in deep engineering.

[0087] The objectives of this invention have been fully and effectively achieved through the above embodiments. Those skilled in the art will understand that this invention includes, but is not limited to, the contents described in the accompanying drawings and the specific embodiments described above. Although the invention has been described with reference to what is currently considered the most practical and preferred embodiments, it should be understood that the invention is not limited to the disclosed embodiments, and any modifications that do not depart from the functional and structural principles of the invention will be included within the scope of the claims.

Claims

1. A monitoring system for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration, characterized in that, At least including: The distributed optical fiber sensing unit includes a distributed optical fiber sensing medium that extends along the well or borehole wall of the target monitoring area and forms a mechanical transmission contact relationship with the corresponding stratum. It is used to continuously collect vibration signals generated by the surrounding rock or stratum under external disturbance and transmit back scattered light signals along the optical fiber. The signal excitation unit is used to apply controllable external disturbances to the target monitoring area to generate active excitation vibration signals for calibrating the mechanical response characteristics of the target strata. Its excitation location is a known reference location. It induces potential anomalous geological bodies to generate identifiable inactive excitation response signals through external disturbances. The photoelectric demodulation unit is signal-connected to the distributed optical fiber sensing unit. It is used to inject probe laser into the distributed optical fiber sensing medium and perform photoelectric demodulation on the received backscattered light signal. The demodulated vibration data is then organized into distributed vibration measurement data according to the optical fiber spatial position and time sequence. The signal processing and analysis unit, electrically connected to the photoelectric demodulation unit, is used to identify and locate abnormal geological bodies in the demodulated vibration measurement data. It establishes a quantitative mathematical model of the incident angle and signal intensity based on the actively excited vibration signal at a known excitation location, and corrects for media attenuation. Then, based on the model, it inverts the incident angle and epicentral distance from the non-actively excited response signal, and, combined with the fiber optic deployment geometry, determines the spatial location of the abnormal geological body within the target monitoring area. When establishing and correcting the quantitative mathematical model of incident angle and signal intensity for locating anomalous geological bodies, the signal processing and analysis unit first calculates the average peak amplitude, arrival time, and propagation direction information at each sampling location segment along the distributed optical fiber sensing medium based on the actively excited vibration signal at the known excitation location. Then, it determines the signal incident angle of each sampling location segment according to the spatial geometric relationship between the known excitation location and each sampling location segment. After that, it models the correlation between the signal incident angle θ and the corresponding average peak amplitude A, and introduces the distance attenuation characteristics of the formation medium on the propagation of vibration waves to correct the average peak amplitude according to the plane wave attenuation equation A(x)=A0·exp(-αx), where x is the epicentral distance, A0 is the initial amplitude, α is the attenuation coefficient caused by medium absorption and α=ω / (2Q·v)=π·f / (Q·v), ω=2πf is the angular frequency, f is the signal frequency, Q is the medium quality factor, and v is the P-wave velocity. The influence of propagation distance on signal intensity is eliminated through attenuation correction.

2. The monitoring system according to claim 1, characterized in that, The distributed optical fiber sensing medium is a continuous sensing medium. The optical fiber body is tightly attached to the well or borehole wall by grouting, expansion anchoring or mechanical clamping. A stable mechanical transmission contact relationship is formed between the optical fiber and the surrounding rock or stratum, and the sampling position segments are continuously arranged along the length of the optical fiber.

3. The monitoring system according to claim 1, characterized in that, The signal excitation unit includes at least one of a vibratory source vehicle, a hydraulic vibratory source, a pneumatic hammer, an electromagnetic vibrator, or a blasting excitation device, and has programmable control capabilities for excitation timing, amplitude, and main frequency. It is used to inject controllable mechanical impact or blasting impact energy into the target monitoring area to generate an active excitation vibration signal in the surrounding rock or stratum. The signal excitation unit is equipped with a depth encoder or positioning marker to record the excitation reference position.

4. The monitoring system according to claim 1, characterized in that, The photoelectric demodulation unit is configured to inject a narrow-linewidth probe laser into the distributed optical fiber sensing medium, and to perform photoelectric conversion and phase demodulation on the backscattered light signal based on the Rayleigh scattering echo returning along the optical fiber, thereby extracting distributed vibration measurement data containing amplitude, frequency, phase and arrival time. The photoelectric demodulation unit maintains a one-to-one correspondence between the measurement data and the position along the optical fiber.

5. The monitoring system according to claim 1, characterized in that, The signal processing and analysis unit includes a signal preprocessing module, used to perform filtering and noise reduction preprocessing on the distributed vibration measurement data, using the square of the spectral amplitude X(ω) of the vibration signal at angular frequency ω, S(ω) = |X(ω)|. 2 As an energy characterization quantity, the frequency response transfer function |H(ω)| is used. 2 =1 / [1+(ω / ω c ) 2n ]=1 / [1+ε 2 ·(ω / ω p ) 2n Weighted suppression is applied to components of different frequencies, where ω c ω is the cutoff angular frequency and the position where the amplitude decays to -3dB. p Here, n is the passband edge frequency, n is the filter order used to control the high-frequency roll-off slope, and ε is a dimensionless parameter related to the amplitude attenuation at the passband edge, and when 1 / (1+ε) 2 )=|H(ω)| 2 This indicates that the device is at the edge of the passband.

6. The monitoring system according to claim 1, characterized in that, When the signal processing and analysis unit locates and solves the inactive excitation response signal generated by the potential anomalous geological body, it substitutes the characterization parameters of the inactive excitation response signal into the quantitative mathematical model of incident angle and signal intensity, and uses the signal incident angle θ and epicentral distance x as unknowns to be solved. The least squares method is used to solve for the optimal solution of the two. Then, combined with the geometric relationship of the distributed optical fiber sensing medium in the well or borehole, the spatial coordinates of the anomalous geological body in the target monitoring area are calculated based on the well or borehole coordinate system, and the target location of the anomalous geological body is output in the form of well depth coordinates, mileage coordinates or section coordinates.

7. The monitoring system according to claim 1, characterized in that, It also includes a result recording and output unit, which is electrically connected to the signal processing and analysis unit, and is used to record, archive and output the filtered distributed vibration measurement data, calibration model parameters, signal incident angle and epicentral distance obtained by the least squares method, and spatial location determination results of abnormal geological bodies obtained by geometric inversion.

8. A monitoring method for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration, using the monitoring system for identifying anomalous geological bodies based on distributed optical fiber acoustic vibration as described in any one of claims 1 to 7, characterized in that, At least the following steps are included: S100. Distributed optical fiber sensing media are deployed in a pre-set well or borehole in the target monitoring area in a manner parallel to the wall and in close contact with the constraint, and the spatial deployment coordinate information of the optical fiber body is acquired and recorded. S200. Using a signal excitation unit, a controllable external disturbance is applied to the target monitoring area to generate an active excitation vibration signal at a known reference location, thereby inducing a potential anomalous geological body to generate an inactive excitation response signal. S300. Inject probe laser into the optical fiber and receive the backscattered light signal transmitted back along the optical fiber. Extract the amplitude, frequency and phase information of the vibration signal through photoelectric conversion and phase demodulation. Organize the demodulation results according to the correspondence between the position along the optical fiber and the time series to form distributed vibration measurement data. S400. The distributed vibration measurement data is filtered and denoised. Based on the amplitude square and frequency distribution characteristics of the vibration signal, the cutoff frequency, passband edge frequency and filter order are set to suppress background environmental noise. Actively excited vibration signals and non-actively excited response signals are distinguished, and the average peak amplitude, arrival time and propagation direction information of each sampling position segment are extracted. S500. Using the actively excited vibration signal as the calibration signal, based on the spatial geometric relationship between the excitation position and each sampling position segment, the angle between the vibration propagation direction and the fiber laying direction at each sampling position segment is determined as the signal incident angle, and a quantitative mathematical model of the signal incident angle and signal intensity of the actively excited vibration signal source is established. S600. Substitute the characteristic parameters of the non-actively excited response signal into the mathematical model for signal analysis. Take the signal incident angle and epicentral distance as unknowns to be solved. Obtain the optimal solution through least squares and combine it with the geometric relationship of the fiber optic body to calculate the spatial location of the abnormal geological body in the target monitoring area.

9. The monitoring method according to claim 8, characterized in that, The data preprocessing and feature extraction in step S400 shall include at least the following sub-steps: S401. Frequency Domain Filtering and Noise Reduction: Perform a frequency domain transformation on the original vibration signal x(t) to obtain the spectrum X(ω), where ω is the angular frequency, and calculate the power spectral density S(ω) = |X(ω)|. 2 The filtering parameters are determined based on the energy distribution of S(ω), and noise suppression is performed on the distributed vibration measurement data. This is based on the preset cutoff angular frequency ω. c , Passband edge frequency ω p Given the filter order n and the passband edge attenuation parameter ε, construct the frequency response transfer function |H(ω)|. 2 =1 / [1+(ω / ω c ) 2n ]=1 / [1+ε 2 ·(ω / ω p ) 2n ], and with |H(ω)| 2 Suppress background noise; S402. Event Separation and Feature Parameter Extraction: Perform event separation on the filtered distributed vibration measurement data to distinguish between actively excited vibration signals and non-actively excited response signals generated by potential anomalous geological bodies, and extract the average peak amplitude, arrival time and vibration propagation direction information for each sampling location segment.

10. The monitoring method according to claim 8, characterized in that, Step S500, in constructing the mathematical model of incident angle and signal strength, includes at least the following sub-steps: S501. Average Peak Amplitude Statistics: The active excitation vibration signal is analyzed. For each sampling location segment along the main body of the optical fiber, the average peak amplitude of the active excitation vibration signal is extracted and statistically analyzed, which serves as the amplitude characteristic parameter characterizing the local formation response intensity of each sampling location segment. S502. Signal incident angle calculation: Based on the known spatial geometric relationship between the excitation position and each sampling position segment, determine the vibration propagation direction vector from the excitation position to each sampling position segment, and define the angle between the vibration propagation direction and the fiber laying direction as the signal incident angle of the sampling position segment; S503. Propagation distance attenuation correction: The average peak amplitude of each sampling location segment is corrected for propagation distance attenuation. The correction form is A(x)=A0·exp(-αx), where x is the epicentral distance, A0 is the initial amplitude, α is the attenuation coefficient caused by medium absorption and α=ω / (2Q·v)=π·f / (Q·v), ω=2πf is the angular frequency, f is the signal frequency, Q is the medium quality factor, and v is the P-wave velocity of the formation. S504. Establishment of mathematical model for incident angle and signal strength: The average peak amplitude A(x) after propagation distance attenuation correction is correlated with the signal incident angle of the corresponding sampling position segment, and a quantitative functional relationship model between the two is established by nonlinear curve fitting method.

11. The monitoring method according to claim 8, characterized in that, Step S600, when performing inversion solving and locating anomalous geological bodies, includes at least the following sub-steps: S601. Statistical Analysis of Inactive Excitation Signal Amplitude: Analyze the inactive excitation response signals generated by potential anomalous geological bodies, and statistically analyze the average peak amplitude A at each sampling location along the fiber optic cable. 20 This is used as the amplitude characteristic parameter of the abnormal response event at each sampling location segment; S602. Equation Substitution and Unknown Setting: The average peak amplitude A... 20 Substituting the incident angle and signal intensity into a quantitative mathematical model, with the signal incident angle θ and epicentral distance x as unknowns, a model is formed based on A. 20 Solve a system of equations with x and θ as unknowns and known quantities, and obtain the optimal solution by least squares. S603. Spatial location of abnormal geological bodies: Based on the optimal solutions of x and θ, combined with the layout coordinate system of the distributed optical fiber sensing medium and the spatial geometric relationship of the monitoring area, the spatial coordinates of the abnormal geological body in the target monitoring area are calculated, and the target location of the abnormal geological body is output in the form of well depth, mileage or section coordinates.

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