A fiber breakage early warning method for horizontal well fracturing in hot dry rock reservoirs based on DAS monitoring

Abstract

The present invention discloses a fiber breakage warning method for horizontal well fracturing in hot dry rock reservoirs based on DAS monitoring. First, the vibration signal in the wellbore is collected by the DAS (distributed acoustic sensing) system, and the pre-processed signal data is obtained by wavelet threshold denoising, data segmentation and normalization processing. Secondly, the short-time Fourier transform analysis method is used to perform time-frequency analysis on the signal to identify the energy distribution of different frequency bands and visualize the high-energy area, thereby identifying abnormally wide frequency bands. Subsequently, phase wrapping detection is performed to verify whether the signal exceeds the dynamic range, and the strain rate and histogram characteristics of the phase signal are calculated. Finally, the standard deviation of the strain rate is evaluated through normal distribution modeling and maximum likelihood estimation. Once it exceeds the set threshold, a fiber breakage risk warning information is issued. This method effectively integrates signal processing and statistical analysis techniques, which not only improves the safety of fracturing operations, but also provides reliable technical support for the efficient development of hot dry rock reservoirs.

Description

Technical Field

[0001] The present invention belongs to the field of distributed fiber optic sensing (DFOS) for hydraulic fracturing of horizontal wells in hot dry rock reservoir development of an enhanced geothermal system (EGS), and specifically relates to a fiber breakage early warning method for hydraulic fracturing of horizontal wells in hot dry rock reservoirs based on DAS monitoring. Background Art

[0002] During hydraulic fracturing of horizontal wells in EGS hot dry rock reservoirs, permanent optical fibers are often installed outside the wellbore casing for real-time monitoring. DAS, a key distributed fiber optic sensing method, can acquire vibration information throughout the entire wellbore at a high sampling rate, helping operators assess hydraulic fracturing effectiveness, such as evaluating the geometric distribution and connectivity of interwell hydraulic fractures between injection and production wells. However, during hydraulic fracturing, if the optical fiber is exposed within the perforations, the high-velocity injection of fracturing fluid and / or proppant can directly erode the fiber, creating a high risk of fiber breakage due to the high-energy vibrations. Furthermore, if cementing quality is poor, high-velocity injection during hydraulic fracturing can cause cracking in the cement sheath, potentially breaking the fiber bonded to it. Fiber breakage not only results in significant economic losses but also compromises the ability to monitor subsequent production. Therefore, identifying and providing early warning of fiber breakage risks during hydraulic fracturing operations based on real-time DAS data is crucial. Summary of the Invention

[0003] To address the issue of strong in-well vibrations during hydraulic fracturing, which can lead to fiber breakage, as previously discussed, this invention provides a DAS-based early warning method for fiber breakage during horizontal well fracturing in hot dry rock reservoirs. This method is used to identify precursors to fiber breakage during hydraulic fracturing and issue timely warnings. Specifically, three characteristics—wideband signals, phase wrapping, and high amplitude (strain rate)—are proposed as precursors to fiber breakage. These characteristics can be used to help operators capture the corresponding warning signals before fiber breakage occurs, thereby rationally controlling pumping parameters and adjusting the fracturing operation plan, reducing the risk of fiber breakage.

[0004] In order to solve the technical problem, the technical solution of the present invention is:

[0005] A fiber breakage early warning method for horizontal well fracturing in hot dry rock reservoirs based on DAS monitoring, the method comprising:

[0006] S1: Obtain the original vibration signal collected by the DAS demodulator, perform wavelet threshold denoising, data segmentation and normalization processing to obtain the pre-processed DAS signal data;

[0007] S2: For the pre-processed DAS signal data, the short-time Fourier transform (STFT) is used to separate the energy distribution of different frequency bands. The output time-frequency spectrum is used to visually judge the high-energy area, identify the abnormally wide-band interval, and obtain the spectrum analysis results.

[0008] S3: First, perform phase wrapping detection on the pre-processed DAS signal data to determine the dynamic range of the DAS system. Detect whether phase wrapping occurs in signals outside the dynamic range. Calculate the phase signal histogram to observe whether abnormal peaks appear near the dynamic range. Then calculate the vibration amplitude, calculate the fiber strain and strain rate respectively, and determine whether wrapping occurs through histogram analysis to obtain the phase wrapping detection results and strain rate data.

[0009] S4: Input the phase wrapping test results obtained in step S3 and the calculated strain rate data, perform normal distribution modeling, maximum likelihood estimation and high amplitude detection, and output the amplitude detection results and the estimated strain rate standard deviation;

[0010] S5: Based on the spectrum analysis results, phase wrapping detection results, and amplitude detection results, fiber break precursor identification and warning information generation are performed.

[0011] Furthermore, the step S1 includes:

[0012] A permanently installed optical fiber outside the wellbore casing is connected to a DAS demodulator, which continuously records vibration signals at each location along the wellbore at a high time sampling rate. The original vibration signal along the entire length of the wellbore is obtained through the DAS demodulator. Wavelet threshold denoising is used to remove environmental noise and demodulator noise interference. The data is then segmented using 2-second time windows and spatial channels to form a three-dimensional data structure, namely time × depth × amplitude. Finally, normalization is performed to unify the data scales of different time windows and channels, and the preprocessed DAS signal data is output.

[0013] Furthermore, the step S3 includes:

[0014] S301: Dynamic Range and Phase Wrapping

[0015] The DAS system has an upper limit on its dynamic range. The phase signal of the fiber optic interrogator is usually limited to [-π, +π]. When the vibration energy exceeds this range, the measured phase signal will show phase wrapping, and high-frequency spikes or discontinuous jumps will appear in the histogram or data distribution.

[0016] S302: Vibration Amplitude

[0017] By comparing the vibration amplitude and distribution shape at different locations in the well section, the high-energy abnormal interval can be quickly located;

[0018] In order to quantitatively analyze the vibration amplitude, it is assumed that the phase signal after demodulation is recorded as If the optical fiber measurement gauge length is set to L, the strain can be obtained through the following approximate linear relationship:

[0019]

[0020] In DAS measurement, for the phase method DAS system, the measured phase φ(t) and strain rate Approximately regarded as a linear relationship:

[0021]

[0022] Where φ(t) is the phase value measured by the fiber optic sensor interrogator (unit: radians), defined in the range [-π, +π]; C is the proportionality constant determined by the fiber material properties and the internal modulation coefficient of the interrogator; ε(t) is the strain of the fiber; L is the gauge length in meters;

[0023] In actual hydraulic fracturing monitoring, the average strain rate within each time window Δt is defined as Then there is

[0024]

[0025] Among them, k is the normalization coefficient, including the aforementioned C and L, is the average strain rate in each time window;

[0026] S303: Phase wrapping and histogram characteristics when out of dynamic range

[0027] When the true φ(t) exceeds the range of [-π, +π], the phase measured by the demodulator will jump. At this time, the histogram will show the following characteristics: obvious peaks appear near -π and +π, and the probability distribution decreases in the middle area. This distribution feature can be regarded as reaching or exceeding the dynamic range limit of the DAS and can be regarded as a precursor to fiber breakage.

[0028] Furthermore, the step S4 specifically includes:

[0029] Assumed vibration strain rate In a certain time window, it obeys the normal distribution N(0,σ 2 ), that is, the mean is 0 and the standard deviation is σ;

[0030] For the phase measurement of the demodulator, if it does not exceed the dynamic range, it can be written as formula (2). If |φ|≤π, the phase measured by the demodulator is still the true value. However, if |φ|>π, wrapping will occur and the measurement result will fall back to [-π, +π], causing the histogram to pile up at ±π.

[0031] By fitting the statistical distribution of the histogram, the optimal estimate of σ is obtained. The inversion process is as follows:

[0032] Let f(φ) represent the probability distribution function PDF of the phase. If the dynamic range is not saturated, then:

[0033]

[0034] If there is phase wrapping, the measured phase φ m By φ m =φmod(2π) is mapped to [-π,+π], and f(φ m ) is represented by all such that φ k =φ m The sum of the superposition probabilities of +2πn;

[0035] By comparing the measured histogram with the theoretical distribution using the maximum likelihood method, we can finally obtain the optimal σ, from which we can deduce the average strain rate amplitude:

[0036]

[0037] in, is the standard deviation of the phase; and k·Δt is the proportional coefficient for converting the phase into the strain rate, thereby establishing a corresponding relationship between the magnitude of the microstrain rate με / s and the fiber amplitude safety threshold. If the value remains above a certain critical value A for a certain period of time, it is determined that there is a high risk of fiber breakage.

[0038] Compared with the prior art, the advantages of the present invention are:

[0039] For horizontal wells with permanently installed optical fibers deployed outside the casing, during the hydraulic fracturing process for EGS hot dry rock reservoir development, the present invention can be used to help operators capture corresponding early warning signals in a timely manner before the optical fiber breaks, thereby rationally controlling pumping parameters and adjusting the fracturing construction plan, significantly reducing the risk of optical fiber breakage and saving the additional cost of adopting remedial measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 , a technical roadmap of the present invention's method for early warning of fiber breakage during horizontal well fracturing in hot dry rock reservoirs based on DAS monitoring;

[0041] Figure 2 , schematic diagram of optical fiber deployment of the present invention;

[0042] Figure 3 ,DAS waterfall diagram (the black dotted line indicates the depth of 2661m, which is the fiber break depth);

[0043] Figure 4, DAS original signal time spectrum at a depth of 2661m;

[0044] Figure 5 ,DAS raw data phase value distribution histogram;

[0045] Figure 6 , comparative analysis of the DAS original signal amplitude value (strain rate) at the fiber break (2661m depth) and the normal fracturing (2625m depth). DETAILED DESCRIPTION

[0046] The specific implementation of the present invention is described below in conjunction with examples:

[0047] It should be noted that the structures, proportions, sizes, etc. shown in this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the conditions under which the present invention can be implemented. Any structural modification, change in proportional relationship or adjustment of size should still fall within the scope of the technical content disclosed in the present invention without affecting the efficacy and purpose that can be achieved by the present invention.

[0048] At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" quoted in this specification are only for the convenience of description and are not used to limit the scope of implementation of the present invention. Changes or adjustments to their relative relationships should be regarded as the scope of implementation of the present invention without substantially changing the technical content.

[0049] Definitions of Abbreviations and Key Terms:

[0050] DAS: Distributed Acoustic Sensing

[0051] DFOS: Distributed Fiber Optic Sensing

[0052] STFT: Short-Time Fourier Transform

[0053] PDF: Probability Distribution Function

[0054] Hydraulic fracturing: The engineering process of injecting high-pressure fluid into a formation to create cracks

[0055] Fiber breakage: The phenomenon of optical fiber breaking

[0056] Phase wrapping: The periodic jump phenomenon that occurs when the measured phase exceeds the range

[0057] Strain rate: the change in strain per unit time

[0058] Gauge length: the basic spatial unit length of fiber optic sensing measurement

[0059] Brillouin shift: the scattering effect of light in a medium

[0060] Rayleigh scattering: elastic scattering of light in a medium

[0061] Dynamic range: The maximum signal range that a DAS system can measure

[0062] Permanent fiber deployment: fiber cemented in cement casing

[0063] Demodulator: A device used to demodulate fiber optic sensor signals

[0064] Example 1:

[0065] To address the problem that strong in-well vibrations occurring during hydraulic fracturing may cause optical fiber breakage, the present invention provides a fiber breakage warning method based on DAS monitoring data. It proposes that three characteristics, namely broadband signals, phase wrapping, and high amplitude (strain rate), are precursors to fiber breakage. This method can be used to help operators capture corresponding warning signals in a timely manner before the fiber breaks, thereby rationally controlling pumping parameters and adjusting fracturing construction plans, reducing the risk of fiber breakage.

[0066] The present invention analyzes the spectrum, phase change and amplitude characteristics of each depth position over time during the hydraulic fracturing process based on DAS real-time data. The technical route of the present invention is as follows: Figure 1 As shown:

[0067] The key technical steps of this method are as follows:

[0068] 1. DAS signal acquisition and preprocessing

[0069] The permanent optical fiber deployed outside the wellbore casing is connected to the DAS demodulator to continuously record the vibration signal at each position along the wellbore at a high time sampling rate (10kHz). The optical fiber is deployed as follows Figure 2 Vibration information along the entire length of the wellbore is obtained through the DAS system.

[0070] The collected original DAS signal is subjected to preprocessing operations such as wavelet threshold denoising to remove the interference of environmental noise and demodulator noise.

[0071] Based on the known fiber deployment depth information, a time-depth two-dimensional matrix of the DAS signal is obtained.

[0072] The original DAS data is divided into time slices (every 2 seconds) and spatial channels (which vary with the depth of the fiber) to form three-dimensional data (time × depth × amplitude).

[0073] Normalization: Normalize the data of different channels and time windows numerically to facilitate subsequent unified processing.

[0074] 2. Spectrum Analysis

[0075] The preprocessed signal is subjected to time-frequency analysis based on short-time Fourier transform (STFT) to separate the energy distribution of different frequency bands.

[0076] High-energy areas can be visualized using time-frequency spectrograms and other methods to identify abnormally wide frequency bands. Under the interference of abnormal fiber break signals, the frequency band corresponding to the strong amplitude on the time-frequency spectrogram image contains low-frequency, medium-frequency, and high-frequency signals, forming a broadband, strong-amplitude feature.

[0077] 3. Phase Wrapping Detection

[0078] (1) Dynamic range and phase wrapping

[0079] DAS measurements have an upper limit on their dynamic range. The maximum measurable range of the optical phase by a demodulator is typically between -π and +π. Once the vibration energy exceeds this range, the measured phase signal will exhibit phase wrapping, resulting in high-frequency spikes or discontinuous transitions in the histogram or data distribution.

[0080] (2) Vibration amplitude (strain rate)

[0081] By comparing the vibration amplitude and distribution shape at different locations in the well section, the high-energy abnormal interval can be quickly located.

[0082] To quantitatively analyze the vibration amplitude, assume that the demodulated phase signal is recorded as φ(t). If the optical fiber measurement gauge length is set to L, the strain can be obtained by the following approximate linear relationship:

[0083] ε(t)=kφ(t) (1)

[0084] In DAS measurement, the optical fiber is affected by external vibrations, which will cause Brillouin frequency shift or phase change of Rayleigh scattering signal. Usually, for the phase method DAS system, the measured phase and strain rate (microstrain / second) is approximately considered a linear relationship:

[0085]

[0086] in:

[0087] It is the phase value measured by the fiber optic sensor interrogator (unit: radians), usually defined in the range of [-π, +π];

[0088] C is a proportional constant determined by the optical fiber material properties and the modulation coefficient inside the demodulator;

[0089] ε(t) is the strain of the optical fiber;

[0090] L is the gauge length, in meters.

[0091] In actual hydraulic fracturing monitoring, because the formation vibration is frequent and the vibration amplitude is uneven, the focus is often on "strain rate" rather than "strain". If the average strain rate within each time window Δt is defined as Then there is

[0092]

[0093] in:

[0094] k is the normalization coefficient, which includes the aforementioned C and L

[0095] is the average strain rate in each time window.

[0096] (3) Phase wrapping and its histogram characteristics when out of dynamic range

[0097] When the real When the range exceeds [-π, +π], the phase measured by the demodulator will jump (wrapping phenomenon), like a "sawtooth" going back and forth between ±π. At this time, the histogram will show the following characteristics

[0098] There are obvious peaks near -π and +π;

[0099] The probability distribution decreases in the middle region (such as near 0);

[0100] This distribution characteristic can be considered as reaching or exceeding the dynamic range limit of DAS and can be regarded as a precursor to fiber breakage.

[0101] 4. Amplitude detection

[0102] Assumed vibration strain rate In a certain time window, it obeys the normal distribution N(0,σ 2 ), that is, the mean is 0 (no net shift) and the standard deviation is σ.

[0103] For the phase measurement of the demodulator, if the dynamic range is not exceeded, it can be written as formula 2. When , the phase measured by the demodulator is still the true value. Wrapping will occur, and the measurement results will fall back to [-π, +π], causing the histogram to pile up at ±π.

[0104] Based on this, the present invention can obtain the optimal estimated value of σ by fitting the statistical distribution of the histogram. The inversion process is roughly as follows:

[0105] make represents the probability distribution function (PDF) of the phase. If the dynamic range is not saturated, then

[0106]

[0107] If phase wrapping exists, the measured phase Depend on (Here it means taking the remainder of 2pi) is mapped to [-π, +π]. Expressed as all such that The sum of the superposition probabilities (n is an integer).

[0108] By comparing the measured histogram with the theoretical distribution using the maximum likelihood method, the optimal σ is finally obtained. Once σ is determined, the average strain rate amplitude can be derived:

[0109]

[0110] in, is the standard deviation of the phase; and k·Δt is the proportional coefficient for converting the phase into the strain rate. Then, a corresponding relationship is established between the magnitude of the microstrain rate με / s and the fiber amplitude safety threshold. If If the value A remains above a certain critical value for a certain period of time (for example, 30 seconds or longer), it is determined that there is a high risk of fiber breakage.

[0111] 5. Fiber break risk warning

[0112] As mentioned above, real-time broadband signal recognition, phase wrapping analysis, and amplitude detection are performed on each slice of the DAS raw data. If the DAS data at a certain depth simultaneously exhibits the three characteristics of broadband, phase wrapping, and high amplitude (strain rate) within a certain period of time (for example, 600 seconds or longer), the data corresponding to that period and depth are considered to be precursors to fiber breakage. A fiber breakage warning message (including time and depth) can be issued in a timely manner to prompt fracturing operators to pay attention to the DAS response at that depth. Fracturing operators are also advised to reduce the displacement, fluid volume, or even suspend fracturing operations based on on-site fracturing parameters (such as pressure, displacement, proppant concentration, etc.) to avoid fiber breakage.

[0113] Example 2:

[0114] For example, fiber optic monitoring was used for hydraulic fracturing in a horizontal well in an EGS hot dry rock reservoir development project. A permanent fiber optic cable was deployed outside the casing, cemented into the cement sheath between the casing and the reservoir. During the hydraulic fracturing operation, the fiber was connected to a surface DAS demodulator, which recorded the fracturing vibration signal data for each section with a spatial sampling interval of 0.25m, a gauge length of 1m, and a temporal sampling frequency of 10kHz.

[0115] Figure 3 The waterfall plot shows the raw DAS data from the third stage of the well's fracturing, processed using this method. Fracturing begins around 1050 seconds, and the fiber breaks at 7050 seconds. The break is located at a depth of 2661 meters, indicated by the black dashed line. DAS data cannot be recorded beyond this depth after the fiber break. Furthermore, the normalized amplitude indicates that the vibration intensity remains high from the start of fracturing until the fiber break.

[0116] According to the method and process described in the present invention, time-frequency spectrum analysis is carried out to determine whether the bandwidth of the signal before the fiber break is wide, phase wrapping analysis is carried out to determine whether the signal before the fiber break has phase wrapping phenomenon, and whether the amplitude (strain rate) curve remains high before the fiber break. At the same time, the results of these three analyses can also be used to verify that the three characteristics described in the present invention can serve as precursors to fiber breakage and the basis for issuing fiber breakage warnings.

[0117] Figure 4 Yes Figure 3 A time-frequency spectrum generated by short-time Fourier transform (STFT) time-frequency analysis of the DAS raw signal (one-dimensional time series) at a depth of 2661m shows that before fracturing began 1000s ago, the DAS signal's strong amplitude was distributed within the 2000-5000Hz range. From around 3000s onward, during normal fracturing, the DAS signal's strong amplitude was distributed over a wide frequency band of 1000-5000Hz. In contrast, during the period just before a fiber break, such as 6000-7050s, the strong amplitude was distributed over a wide frequency band of 0-5000Hz. The bandwidths of the DAS signals in these three time periods are significantly different. Therefore, this broadband feature can serve as a precursor to a fiber break.

[0118] Figure 5 Yes Figure 3 A phase value distribution histogram generated by phase analysis of the DAS raw signal (one-dimensional time series) at a depth of 2661 m. As can be seen from the figure, due to the fiber break at 7050 s, the phase distribution of the DAS data no longer follows the normal distribution during fracturing. Instead, a large number of abnormal phases are present near -π and +π, indicating the presence of phase wrapping. Therefore, phase wrapping can be used as a precursor to fiber breakage.

[0119] Figure 6 yes Figure 3 Comparative analysis of the amplitude (strain rate) of the DAS raw signal (one-dimensional time series) at the fiber break (2661m depth) and the normal fracturing site (2625m depth). As can be seen from the figure, the normal fracturing site (2625m depth) maintained a relatively low amplitude throughout the fracturing operation. The first strong amplitude distribution appears between 3000 and 3500 seconds at the fiber break (2661 m depth), with a maximum strain rate of 1300.0 με / s (indicated by the black horizontal dashed line). This is relatively short-lived, indicating no fiber break. However, the amplitude at the fiber break (2661 m depth) remains high from 4000 to 7050 seconds, ultimately leading to fiber breakage at 7050 seconds (black vertical dashed line). The strain rate reaches a maximum of 2820.0 με / s at the time of breakage, indicated by the black horizontal dashed line. Furthermore, the strong amplitude between 7050 and 7500 seconds is due to the continued recording of strong vibrations caused by the fracture at the fiber end after the break. Therefore, the high amplitude (strain rate) curve before fiber breakage can serve as a precursor to fiber breakage.

[0120] In summary, during the real-time DAS monitoring process of hydraulic fracturing, real-time broadband signal recognition, phase wrapping analysis, and amplitude detection were performed on each slice of the DAS raw data. The DAS data at a depth of 2661 m, between 4000 and 7050 seconds after the start of fracturing, simultaneously exhibited three characteristics: broadband, phase wrapping, and high amplitude (strain rate). This indicated that the data corresponding to this time period and depth showed a precursor to fiber breakage. A fiber breakage warning message (including time and depth) was promptly issued to the fracturing operators, prompting them to pay attention to the DAS response at this depth. The operator was also advised to reduce the displacement, fluid volume, or even suspend fracturing operations based on on-site fracturing parameters (such as pressure, displacement, and proppant concentration), thereby successfully avoiding fiber breakage.

[0121] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0122] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0123] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0124] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0125] The preferred embodiments of the present invention are described in detail above, but the present invention is not limited to the above embodiments. Various changes can be made within the knowledge of ordinary technicians in this field without departing from the scope of the present invention.

[0126] Many other changes and modifications can be made without departing from the spirit and scope of the present invention. It should be understood that the present invention is not limited to the specific embodiments, and the scope of the present invention is defined by the appended claims.

Claims

1. A fiber breakage early warning method for horizontal well fracturing in hot dry rock reservoirs based on DAS monitoring, characterized in that: The method comprises: S1: Obtain the original vibration signal collected by the DAS demodulator, perform wavelet threshold denoising, data segmentation and normalization processing to obtain the pre-processed DAS signal data; S2: For the pre-processed DAS signal data, the short-time Fourier transform (STFT) is used to separate the energy distribution of different frequency bands. The output time-frequency spectrum is used to visually judge the high-energy area, identify the abnormally wide-band interval, and obtain the spectrum analysis results. S3: First, perform phase wrapping detection on the pre-processed DAS signal data to determine the dynamic range of the DAS system. Detect whether phase wrapping occurs in signals outside the dynamic range. Calculate the phase signal histogram to observe whether abnormal peaks appear near the dynamic range. Then calculate the vibration amplitude, calculate the fiber strain and strain rate respectively, and determine whether wrapping occurs through histogram analysis to obtain the phase wrapping detection results and strain rate data. S4: Input the phase wrapping test results obtained in step S3 and the calculated strain rate data, perform normal distribution modeling, maximum likelihood estimation and high amplitude detection, and output the amplitude detection results and the estimated strain rate standard deviation; S5: Based on the spectrum analysis results, phase wrapping detection results, and amplitude detection results, fiber break precursor identification and warning information generation are performed.

2. The method for early warning of fiber breakage during horizontal well fracturing in hot dry rock reservoirs based on DAS monitoring according to claim 1, characterized in that: The step S1 includes: A permanently installed optical fiber outside the wellbore casing is connected to a DAS demodulator, which continuously records vibration signals at each location along the wellbore at a high time sampling rate. The original vibration signal along the entire length of the wellbore is obtained through the DAS demodulator. Wavelet threshold denoising is used to remove environmental noise and demodulator noise interference. The data is then segmented using 2-second time windows and spatial channels to form a three-dimensional data structure, namely time × depth × amplitude. Finally, normalization is performed to unify the data scales of different time windows and channels, and the preprocessed DAS signal data is output.

3. The method for early warning of fiber breakage during horizontal well fracturing in hot dry rock reservoirs based on DAS monitoring according to claim 1, characterized in that: The step S3 includes: S301: Dynamic Range and Phase Wrapping The DAS system has an upper limit on its dynamic range. The phase signal of the fiber optic interrogator is usually limited to [-π, +π]. When the vibration energy exceeds this range, the measured phase signal will show phase wrapping, and high-frequency spikes or discontinuous jumps will appear in the histogram or data distribution. S302: Vibration Amplitude By comparing the vibration amplitude and distribution shape at different locations in the well section, the high-energy abnormal interval can be quickly located; In order to quantitatively analyze the vibration amplitude, it is assumed that the phase signal after demodulation is recorded as If the optical fiber measurement gauge length is set to L, the strain can be obtained through the following approximate linear relationship: In DAS measurement, for the phase method DAS system, the measured phase φ(t) and strain rate Approximately regarded as a linear relationship: in, is the phase value measured by the fiber optic sensor demodulator, defined in the range of [-π, +π]; C is the proportional constant determined by the fiber material properties and the internal modulation coefficient of the demodulator; ε(t) is the strain of the fiber; L is the gauge length in meters; In actual hydraulic fracturing monitoring, the average strain rate within each time window Δt is defined as Then there is Among them, k is the normalization coefficient, including the aforementioned C and L, is the average strain rate in each time window; S303: Phase wrapping and its histogram characteristics when out of dynamic range When the real When the phase measured by the demodulator exceeds the range of [-π, +π], a phase jump occurs. The histogram then exhibits the following characteristics: distinct peaks appear near -π and +π, and the probability distribution decreases in the middle region. This distribution characteristic can be considered to have reached or exceeded the dynamic range limit of the DAS and can be considered a precursor to fiber breakage.

4. The method for early warning of fiber breakage during horizontal well fracturing in hot dry rock reservoirs based on DAS monitoring according to claim 1, characterized in that: The step S4 specifically includes: Assumed vibration strain rate In a certain time window, it obeys the normal distribution N(0,σ 2 ), that is, the mean is 0 and the standard deviation is σ; For the phase measurement of the demodulator, if the dynamic range is not exceeded, it can be written as formula (2). ≤π, the phase measured by the demodulator is still the true value, but if >π, wrapping occurs and the measurement results fall back to [-π, +π], causing the histogram to pile up at ±π; By fitting the statistical distribution of the histogram, the optimal estimate of σ is obtained. The inversion process is as follows: Let f(φ) represent the probability distribution function PDF of the phase. If the dynamic range is not saturated, then: If phase wrapping exists, the measured phase Depend on = mod(2π) is mapped to [-π,+π], which can be Expressed as all such that = The sum of the superposition probabilities of +2πn; By comparing the measured histogram with the theoretical distribution using the maximum likelihood method, we can finally obtain the optimal σ, from which we can deduce the average strain rate amplitude: in, is the standard deviation of the phase; and k·Δt is the proportional coefficient for converting the phase into the strain rate, thereby establishing a corresponding relationship between the microstrain rate (in units of με / s) and the fiber amplitude safety threshold. If If the value remains above a certain critical value A for a certain period of time, it is determined that there is a high risk of fiber breakage.

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