A hydraulic fracturing roof cutting pressure relief method for a coal mine working face

Abstract

The application discloses a hydraulic fracturing roof cutting pressure relief method for a coal mine working face, relates to the technical field of hydraulic fracturing roof cutting pressure relief for a coal mine working face, and specifically comprises the following steps: analyzing fracturing operation dynamic information stored in a central monitoring system, and respectively generating a fracturing fluid evaporation coefficient, a fracture expansion coefficient and a pressure maintenance index; constructing a fracture expansion evaluation model based on the generated fracturing fluid evaporation coefficient, the fracture expansion coefficient and the pressure maintenance index, and generating a fracture expansion evaluation coefficient; determining a pre-set fracture expansion evaluation coefficient threshold, comparing the fracture expansion evaluation coefficient threshold with the generated fracture expansion evaluation coefficient after the determination, evaluating whether evaporation of the fracturing fluid in a high-temperature environment will affect a fracture expansion range, and respectively generating a normal signal and an abnormal signal according to an evaluation result. The application solves the problem that evaporation of the fracturing fluid in the high-temperature environment affects the fracture expansion, and ensures effective pressure maintenance and safe expansion.

Description

Technical Field

[0001] This invention relates to the field of hydraulic fracturing and roof cutting pressure relief technology in coal mine working faces, specifically to a hydraulic fracturing and roof cutting pressure relief method for coal mine working faces. Background Technology

[0002] A coal mine working face refers to the area where workers and equipment extract coal during underground coal mining. It is typically located in the middle of a coal seam and bears immense pressure from the overlying rock strata. As the working face advances, stress concentration in the overlying rock strata poses a threat to the safety of the working face, potentially leading to roof collapse, endangering worker lives, and impacting coal mining efficiency. Therefore, implementing reasonable roof pressure control in coal mine working faces is crucial. Hydraulic fracturing with roof cutting and pressure relief is a technique that uses hydraulic fracturing technology to directionally fracture the roof of a coal mine working face. By injecting high-pressure fluid into pre-drilled holes, fractures are created in the rock strata, releasing pressure in localized high-stress areas and reducing the threat posed by the roof to the working face. The core purpose of this technique is to release or redistribute roof stress through roof cutting and pressure relief, preventing sudden roof collapse and improving the stability and safety of the working face. The necessity of implementing this method lies in the fact that as the coal mine working face gradually expands during mining, the bearing capacity of the overlying rock strata continuously decreases, becoming unable to withstand greater pressure. Hydraulic fracturing can effectively address roof stress issues in advance, preventing sudden roof collapse accidents during mining and ensuring the continuity and safety of production. Therefore, hydraulic fracturing for roof cutting and pressure relief is not only a necessary means to ensure the safety of the working face during mining but also an important measure to improve the overall mining efficiency of coal mines.

[0003] Existing hydraulic fracturing technology for roof cutting and pressure relief in coal mine working faces is implemented through a series of steps. First, mine engineers conduct detailed exploration based on the geological conditions and roof pressure of the working face to identify high-stress areas and potential locations of roof instability. Next, based on the exploration results, hydraulic fracturing boreholes are designed and deployed. These boreholes are typically evenly distributed along the working face, with their depth and number determined by the specific pressure distribution to ensure effective coverage of the areas requiring pressure relief. Then, specialized hydraulic fracturing equipment injects high-pressure water into the pre-drilled boreholes. The water, through pressure, creates fractures in the rock strata, gradually expanding the fracture range, releasing concentrated stress in the rock strata, and cutting the pressure-bearing structure of the roof. Throughout the process, the fracturing operation is accompanied by real-time monitoring. By monitoring the expansion of fractures, pressure changes, and changes in roof stress, the effectiveness of the fracturing is assessed. Once the fractures have expanded to the designed range, the rock strata stress is fully released, thus completing the pressure relief operation. Subsequently, continuous monitoring of the fracturing roof is conducted to assess its stability, and adjustments to the support structure are made as necessary to ensure the safety of the working face. Throughout the process, hydraulic fracturing technology, through the directional generation and propagation of fractures, makes the roof, which might otherwise be unstable due to stress concentration, more stable, effectively preventing the risk of roof collapse and reducing the pressure on manual support.

[0004] The existing technology has the following shortcomings:

[0005] In coal mines located in deep, high-temperature rock formations, a problem arises where fracturing fluid partially evaporates during injection into the fractures. Due to the high temperature, the injected fracturing fluid cannot remain liquid; some evaporates rapidly, resulting in insufficient fluid entering the fracture and failing to generate enough pressure to propel it. This leads to ineffective pressure relief in high-stress areas, and current technologies lack effective control over fracturing fluid evaporation under high-temperature conditions, making it impossible to ensure fracture propagation to the predetermined depth and extent. Consequently, stress concentration problems in localized areas remain unresolved, increasing the risk of roof instability and localized collapse. Furthermore, poor fracturing results may necessitate repeated operations, increasing construction costs and time, and impacting the overall production progress and safety of the working face.

[0006] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to provide a hydraulic fracturing and roof-cutting depressurization method for coal mine working faces, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a hydraulic fracturing and roof-cutting depressurization method for coal mine working faces, specifically comprising the following steps:

[0009] At the coal mine working face in deep high-temperature rock strata, a sensor network is deployed to acquire dynamic information on fracturing operations in the coal mine working face environment, and the acquired dynamic information on fracturing operations in the coal mine working face environment is stored in the central monitoring system.

[0010] The dynamic information of fracturing operations stored in the central monitoring system is analyzed to generate fracturing fluid evaporation coefficient, fracture propagation coefficient and pressure maintenance index, respectively.

[0011] A fracture propagation assessment model was constructed based on the generated fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, and a fracture propagation assessment coefficient was generated.

[0012] Determine a pre-set threshold for the fracture propagation assessment coefficient, and compare it with the generated fracture propagation assessment coefficient after determination. Evaluate whether the evaporation of fracturing fluid under high temperature environment will affect the fracture propagation range, and generate normal and abnormal signals respectively based on the assessment results.

[0013] In the event of an abnormal signal, further dynamic information on fracturing operations in the coal mine working face environment is collected, and several subsequent fracture propagation assessment coefficients are generated. A comprehensive analysis is conducted to generate risk signals of corresponding levels, and corresponding adjustment measures are taken based on the generated risk signals of corresponding levels.

[0014] Preferably, the dynamic information of fracturing operations stored in the central monitoring system is analyzed to generate the fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, specifically including the following steps:

[0015] Preprocess the dynamic information of fracturing operations stored in the central monitoring system;

[0016] Extract dynamic information on thermal fluid evaporation, fracture morphology evolution, and stress persistence effectiveness from the pre-processed dynamic information of fracturing operations;

[0017] The extracted dynamic information on thermal fluid evaporation, fracture morphology evolution, and stress sustainability were analyzed to generate fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, respectively.

[0018] Preferably, the logic for obtaining the fracturing fluid evaporation coefficient is as follows:

[0019] The thermal fluid evaporation dynamics information is extracted from the pre-processed fracturing operation dynamics information. Specifically, this includes the rock layer temperature of the high-temperature rock strata at the coal mine face at different times over a period of time, the actual flow rate of the fracturing fluid, the actual temperature of the fracturing fluid, and the average pressure of the local environment at the coal mine face. These parameters are then denoted as TR. m QF m TF m and PE m m represents the number of the rock layer temperature, actual flow rate of fracturing fluid, actual temperature of fracturing fluid, and average pressure of the local environment at the coal mine working face at different times within a certain period of time, m = 1, 2, 3, ..., k, where k is a positive integer;

[0020] The specific formula for calculating the fracturing fluid evaporation coefficient is as follows:

[0021]

[0022] In the formula, FFEC is the fracturing fluid evaporation coefficient.

[0023] Preferably, the logic for obtaining the crack propagation coefficient is as follows:

[0024] Extract fracture morphology evolution information from the preprocessed dynamic information of fracturing operations, specifically including fracture length, fracturing fluid injection pressure, actual fracturing fluid flow rate, and actual rock hardness at the coal mine face at different times within a certain period. These parameters are then labeled as LFC. n YLP n YLL n H and n are the numbers of the fracture length, fracturing fluid injection pressure and actual flow rate of fracturing fluid at the coal mine working face at different times within a certain period of time, n = 1, 2, 3, ..., g, where g is a positive integer;

[0025] The crack propagation factor is calculated using the following formula:

[0026]

[0027] In the formula, FEC is the crack propagation coefficient.

[0028] Preferably, the logic for obtaining the pressure maintenance index is as follows:

[0029] Stress persistence performance information is extracted from the pre-processed dynamic information of fracturing operations. Specifically, this includes fracturing fluid injection pressure, fracture closure time, fracturing fluid pressure decay rate, and fracturing fluid viscosity at different times within a given period. These parameters are then denoted as YLZ. x LFB x YS x andYLN x x is the number of the fracturing fluid injection pressure, fracture closure time, fracturing fluid pressure decay rate and fracturing fluid viscosity at different times within a certain period of time, x = 1, 2, 3, ..., u, where u is a positive integer;

[0030] The pressure maintenance index is calculated using the following formula:

[0031]

[0032] In the formula, PMI is the pressure maintenance index.

[0033] Preferably, a fracture propagation assessment model is constructed based on the generated fracturing fluid evaporation coefficient FFEC, fracture propagation coefficient FEC, and pressure maintenance index PMI, and the fracture propagation assessment coefficient EC is generated by weighted summation.

[0034] Preferably, a pre-set crack propagation assessment coefficient threshold EC is determined. yuzhi After determination, it is compared with the generated fracture propagation assessment coefficient EC to evaluate whether the evaporation of fracturing fluid under high temperature environment will affect the fracture propagation range. Based on the assessment results, normal signals and abnormal signals are generated respectively. The specific comparison and analysis are as follows:

[0035] If EC <EC yuzhi The evaporation of fracturing fluid at high temperatures can affect the extent of fracture propagation and generate abnormal signals.

[0036] If EC≥EC yuzhi The evaporation of fracturing fluid under high temperature conditions does not affect the fracture propagation range and generates normal signals.

[0037] Preferably, in the event of an anomaly signal, further dynamic information on fracturing operations in the coal mine working face environment is obtained, and several subsequent fracture propagation evaluation coefficients are generated. These subsequently generated fracture propagation evaluation coefficients are then recalibrated to EC. i , i represents the number of several crack propagation evaluation coefficients subsequently generated under the condition of generating an abnormal signal, i = 1, 2, 3, ..., d, where d is a positive integer;

[0038] The average value of several crack propagation assessment coefficients is calibrated as EC. -,but:

[0039] The standard deviation of several crack propagation assessment coefficients is calibrated as EC. σ ,but:

[0040] Preferably, a preset average value and preset standard deviation of several crack propagation evaluation coefficients subsequently generated under the condition of generating an anomalous signal are obtained, and the preset average value and preset standard deviation of several crack propagation evaluation coefficients subsequently generated under the condition of generating an anomalous signal are respectively calibrated as follows: and The average value of several crack propagation evaluation coefficients generated subsequently under the condition of generating an anomalous signal, EC - and standard deviation EC σ Compared with the preset average value respectively and preset standard deviation Comparative analysis is conducted to generate risk signals of corresponding levels, and corresponding adjustment measures are taken based on the generated risk signals. The specific analysis is as follows:

[0041] like Once a high-risk level signal is generated, immediate emergency adjustment measures should be taken, including increasing the amount of fracturing fluid injected, increasing the viscosity of the fracturing fluid, and reducing the evaporation of the fracturing fluid by lowering the ambient temperature.

[0042] like and A medium-risk level signal is generated, and monitoring measures are taken, including continuous monitoring of fracturing operation parameters and adjustment of fracture closure time and pressure;

[0043] like and A low-risk level signal is generated; no adjustments are required, and the current operational status is maintained.

[0044] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0045] 1. This invention effectively solves the problem of existing technologies being unable to cope with fracturing fluid evaporation caused by high temperatures by precisely monitoring the dynamic information of fracturing operations under high-temperature environments, particularly the states of fracturing fluid evaporation, fracture propagation, and pressure maintenance. By acquiring key parameters of the fracturing fluid in real time through a sensor network and analyzing this data with the help of a central monitoring system, it ensures that the fracturing fluid maintains sufficient quantity and pressure under high-temperature conditions to drive fracture propagation to the expected range, thus resolving potential problems such as stress concentration and roof instability.

[0046] 2. This invention constructs a fracture propagation assessment model and generates multiple key coefficients, such as the fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, enabling dynamic evaluation of fracture propagation effectiveness. Compared to traditional methods, it incorporates a complex mathematical model and weighted algorithm, which not only generates comprehensive evaluation coefficients through calculation but also detects anomalies in a timely manner through a signal feedback mechanism, allowing for corresponding adjustment measures. This real-time feedback and control function significantly improves operational safety while reducing the risk of repeated operations.

[0047] 3. The anomaly handling mechanism in this invention significantly improves operational efficiency. When the system detects that crack propagation is affected by fracturing fluid evaporation under high-temperature conditions, it can automatically generate a risk signal and, combined with historical data and real-time monitoring, generate several new crack propagation assessment coefficients. By comparing the standard deviation and the average value, signals of different risk levels are generated, ensuring precise responses to different risks, reducing operational costs, and improving the safety and production efficiency of the coal mine working face. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0049] Figure 1 This is a schematic flowchart of a hydraulic fracturing and roof-cutting depressurization method for coal mine working faces according to the present invention. Detailed Implementation

[0050] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0051] This invention provides, for example Figure 1 The hydraulic fracturing roof cutting and pressure relief method for coal mine working faces, as shown, specifically includes the following steps:

[0052] At the coal mine working face in deep high-temperature rock strata, a sensor network is deployed to acquire dynamic information on fracturing operations in the coal mine working face environment, and the acquired dynamic information on fracturing operations in the coal mine working face environment is stored in the central monitoring system.

[0053] Deploying a sensor network to acquire dynamic information about fracturing operations in coal mine working faces located in deep, high-temperature rock strata can be achieved through the following methods. First, based on the geological conditions of the working face area and the scope of the fracturing operation, a sensor layout scheme is determined, including temperature sensors, pressure sensors, flow sensors, and fracture monitoring sensors. These sensors will be placed in key locations on the working face, such as around fracturing holes, fracture propagation areas, and high-temperature zones within the coal mine strata. The sensors are connected to a central monitoring system via wireless network or fiber optic communication to ensure reliable data transmission in high-temperature environments. Simultaneously, environmental factors must be considered during sensor installation, using high-temperature resistant materials for encapsulation and deploying a redundant sensor network to address potential sensor failures.

[0054] The deployed sensor network collects various dynamic data from the coal mine working face environment in real time, forming dynamic information on fracturing operations. Temperature sensors monitor real-time temperature changes in the working face rock strata, flow sensors record the flow rate and velocity of the fracturing fluid, pressure sensors monitor changes in injection pressure, and fracture monitoring sensors can record the length and direction of fracture propagation through acoustic monitoring or microseismic sensing technology. Each sensor in the network automatically collects data at set time intervals or triggered by mechanisms such as pressure or temperature changes exceeding set values, and the data is aggregated through local data collection nodes.

[0055] After acquiring dynamic information about fracturing operations, data can be transmitted from local sensor nodes to the central monitoring system via wireless communication technologies (such as LoRa, Wi-Fi, and 5G networks) or fiber optic transmission. The data collected by the sensors undergoes preliminary processing at the local nodes, including data filtering, noise reduction, and compression, before being encrypted to protect the security of data transmission. In the central monitoring system, the received data is automatically categorized and stored. Combined with a database management system, dynamic information is stored in a distributed database or cloud storage platform. The monitoring system software indexes and archives this data, ensuring it can be accessed at any time for real-time monitoring and historical data analysis.

[0056] The dynamic information of fracturing operations stored in the central monitoring system is analyzed to generate fracturing fluid evaporation coefficient, fracture propagation coefficient and pressure maintenance index, respectively.

[0057] In this embodiment, the dynamic information of fracturing operations stored in the central monitoring system is analyzed to generate the fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, specifically including the following steps:

[0058] Preprocess the dynamic information of fracturing operations stored in the central monitoring system;

[0059] Preprocessing the fracturing operation dynamics information stored in the central monitoring system is crucial for ensuring data accuracy and consistency, thus providing a reliable data foundation for subsequent analysis. The main objectives of preprocessing are noise removal, data completion (including filling in missing data), and data standardization from different sources. Specific operations include filtering out outliers from sensors using algorithms, completing missing data using interpolation methods, and normalizing data from different sensors to ensure all data is analyzed under the same standards. Through these preprocessing steps, the data can be used more efficiently and accurately for subsequent calculations of fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index.

[0060] Extract dynamic information on thermal fluid evaporation, fracture morphology evolution, and stress persistence effectiveness from the pre-processed dynamic information of fracturing operations;

[0061] Extracting dynamic information on thermal fluid evaporation, fracture morphology evolution, and stress sustaining effectiveness from preprocessed fracturing operation dynamics can be achieved through data classification and feature extraction algorithms in the software. First, the software classifies the preprocessed data according to its source and type, categorizing data such as temperature, flow rate, and pressure collected by different sensors into their corresponding information types. Then, using feature extraction technology, the software extracts specific datasets related to thermal fluid evaporation, fracture propagation, and stress sustaining from the classified data. Specific extraction methods can be based on the physical properties and time-series characteristics of the data, such as by setting specific threshold conditions or analyzing data fluctuation trends, to identify and extract key feature data related to the three types of information, ensuring that each type of information accurately reflects the actual state of the fracturing operation.

[0062] The extracted dynamic information on thermal fluid evaporation, fracture morphology evolution, and stress sustainability were analyzed to generate fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, respectively.

[0063] In this embodiment, the logic for obtaining the fracturing fluid evaporation coefficient is as follows:

[0064] The thermal fluid evaporation dynamics information is extracted from the pre-processed fracturing operation dynamics information. Specifically, this includes the rock layer temperature of the high-temperature rock strata at the coal mine face at different times over a period of time, the actual flow rate of the fracturing fluid, the actual temperature of the fracturing fluid, and the average pressure of the local environment at the coal mine face. These parameters are then denoted as TR. m QF m TF m and PE mm represents the number of the rock layer temperature, actual flow rate of fracturing fluid, actual temperature of fracturing fluid, and average pressure of the local environment at the coal mine working face at different times within a certain period of time, m = 1, 2, 3, ..., k, where k is a positive integer;

[0065] The system extracts dynamic information on thermal fluid evaporation from the pre-processed dynamic information of fracturing operations. First, temperature, flow rate, and pressure sensors are deployed in key areas of the coal mine face using a sensor network. Software acquires data from these sensors in real time. Rock strata temperature is collected by temperature sensors embedded at different depths within the rock strata. These sensors record temperature data at predetermined time intervals and transmit the data to a central monitoring system wirelessly or via wired connection. Fracturing fluid flow rate is monitored in real time by flow meters or differential pressure sensors installed near the pipeline or fracturing orifice. The software automatically correlates flow rate data with specific time points to ensure complete capture of dynamic changes in flow rate over time. Fracturing fluid temperature is monitored by flow temperature sensors installed in the fluid path, which record temperature changes as the fracturing fluid flows. Environmental pressure data is acquired by pressure sensors deployed locally at the coal mine face. The software smooths pressure fluctuations to ensure data accuracy. All this data is processed through the software's automatic acquisition and classification functions. The system integrates rock strata temperature, fracturing fluid flow rate, fracturing fluid temperature, and environmental pressure data at different times into dynamic information on thermal fluid evaporation for subsequent analysis.

[0066] The specific formula for calculating the fracturing fluid evaporation coefficient is as follows:

[0067]

[0068] In the formula, FFEC is the fracturing fluid evaporation coefficient.

[0069] The formula for calculating the fracturing fluid evaporation coefficient is designed in this form to comprehensively consider the influence of various factors on fracturing fluid evaporation. In the formula, TR... m -TF m This represents the temperature difference between the rock formation and the fracturing fluid at each time point m. A larger temperature difference corresponds to a higher evaporation rate; therefore, this difference plays a crucial role in evaporation calculations. PE m The denominator represents the local environmental pressure. Higher environmental pressure results in slower evaporation; therefore, the formula uses a fractional form to mitigate the inhibitory effect of pressure on evaporation. ln(1+QF) mThe formula reflects the effect of fracturing fluid velocity on evaporation. A higher fracturing fluid velocity means the fluid passes through the fracture faster, reducing fluid residence time and evaporation. A logarithmic function is used to handle the nonlinear effects of fracturing fluid velocity, allowing for a more reasonable modeling of the velocity's influence on evaporation. The entire formula obtains the average fracturing fluid evaporation coefficient by accumulating data from different time periods (from 1 to k), thus accurately reflecting the evaporation behavior of the fracturing fluid under high-temperature conditions throughout the entire time period.

[0070] The evaporation coefficient of fracturing fluid directly reflects its evaporation rate under high-temperature conditions, and this evaporation behavior significantly impacts fracture propagation. A higher evaporation coefficient means more fracturing fluid is lost during injection due to high-temperature evaporation, resulting in a reduced amount of fluid actually entering the fracture and consequently decreasing the fracture propagation pressure and extent. Conversely, a lower evaporation coefficient indicates that the fracturing fluid maintains good fluidity and volume under high-temperature conditions, allowing it to fully penetrate the fracture and apply sufficient pressure to propagate it. Therefore, the evaporation coefficient of fracturing fluid is closely related to the effectiveness of fracture propagation; an excessively high evaporation coefficient may lead to insufficient fracture propagation, thus affecting the overall effectiveness of the fracturing operation.

[0071] In this embodiment, the logic for obtaining the crack propagation coefficient is as follows:

[0072] Extract fracture morphology evolution information from the preprocessed dynamic information of fracturing operations, specifically including fracture length, fracturing fluid injection pressure, actual fracturing fluid flow rate, and actual rock hardness at the coal mine face at different times within a certain period. These parameters are then labeled as LFC. n YLP n YLL n H and n are the numbers of the fracture length, fracturing fluid injection pressure and actual flow rate of fracturing fluid at the coal mine working face at different times within a certain period of time, n = 1, 2, 3, ..., g, where g is a positive integer;

[0073] Extracting fracture morphology evolution information from pre-processed fracturing operation dynamics is primarily achieved through sensor networks and software analysis systems. Sensor networks deployed at the coal mine face collect key quantitative data in real time, including fracture length, fracturing fluid injection pressure, actual flow rate, and rock hardness. First, fracture length is detected using a microseismic monitoring system and acoustic sensors. The microseismic monitoring system captures acoustic signals during fracture formation and estimates the actual fracture length using a positioning algorithm. The software calculates the fracture expansion dynamics in real time based on the sensor data, generating time-series fracture length data. Second, the fracturing fluid injection pressure is monitored in real time by pressure sensors installed in the injection pipeline. These sensors record pressure changes at different times, and the software correlates this data with timestamps to ensure that the acquired pressure information is synchronized with the fracture length. The actual fracturing fluid flow rate is obtained through flow meters installed on the fracturing equipment's pipelines, which monitor the injection fluid rate in real time. The software automatically captures and records the flow velocity data and analyzes it in conjunction with other data. The actual rock hardness is obtained from prior geological exploration and is input into the system as fixed data, remaining constant over time. The software categorizes and summarizes all this data, extracts crack morphology evolution information at different time points, and uses it for subsequent crack propagation coefficient calculation.

[0074] The crack propagation factor is calculated using the following formula:

[0075]

[0076] In the formula, FEC is the crack propagation coefficient.

[0077] The formula for calculating the crack propagation coefficient is designed in this form to fully consider several key factors affecting crack propagation and to comprehensively calculate their average effect throughout the process. The LFC in the formula... n This represents the crack length at time n. A longer crack length indicates better crack propagation. YLP n YLL represents the fracturing fluid injection pressure at time n. The higher the pressure, the stronger the driving force for fracture propagation, and therefore it is positively correlated with fracture propagation. n The flow rate represents the actual flow rate of the fracturing fluid. Excessive flow rate reduces fracture propagation because rapid fluid flow through the fracture makes it difficult to maintain sufficient pressure for propagation. Therefore, this factor is included in the denominator of the formula to mitigate the negative impact of excessive flow rate. H represents the rock hardness; higher hardness makes fracture propagation more difficult. Therefore, hardness, as a denominator, constrains fracture propagation. Finally, by weighted averaging these factors, the fracture propagation effect over the entire time period can be comprehensively reflected, ensuring the scientific validity and accuracy of the calculation results.

[0078] The fracture propagation coefficient directly reflects the effectiveness of fracturing fluid in propagating fractures. However, at high temperatures, the evaporation of the fracturing fluid affects this coefficient. Specifically, when a large amount of fracturing fluid evaporates at high temperatures, the amount of fluid entering the fracture decreases, leading to a drop in injection pressure and consequently a decrease in the fracture propagation coefficient. A smaller fracture propagation coefficient means that the fracture's propagation range is limited because the fracturing fluid cannot maintain sufficient pressure to drive further fracture propagation. Therefore, the fracture propagation coefficient can be used to assess whether the evaporation of fracturing fluid under high-temperature conditions has an adverse effect on fracture propagation. A lower fracture propagation coefficient generally indicates that fluid loss due to evaporation has significantly impacted the effectiveness of fracture propagation.

[0079] In this embodiment, the logic for obtaining the pressure maintenance index is as follows:

[0080] Stress persistence performance information is extracted from the pre-processed dynamic information of fracturing operations. Specifically, this includes fracturing fluid injection pressure, fracture closure time, fracturing fluid pressure decay rate, and fracturing fluid viscosity at different times within a given period. These parameters are then denoted as YLZ. x LFB x YS x andYLN x x is the number of the fracturing fluid injection pressure, fracture closure time, fracturing fluid pressure decay rate and fracturing fluid viscosity at different times within a certain period of time, x = 1, 2, 3, ..., u, where u is a positive integer;

[0081] The extraction of stress persistence effectiveness information from pre-processed fracturing operation dynamics is primarily achieved through a sensor network and software analysis system. This information includes key data such as fracturing fluid injection pressure, fracture closure time, pressure decay rate, and fracturing fluid viscosity at different times. First, the fracturing fluid injection pressure is acquired in real-time by pressure sensors installed on the injection pipeline. The software automatically collects and calibrates the pressure data provided by the sensors, correlating the injection pressure data at different times with timestamps to ensure data timeliness. Fracture closure time is monitored using microseismic sensors or acoustic sensors. These sensors capture vibration signals generated during fracture formation, propagation, and closure. The software analyzes these vibration signals to determine the fracture closure time, forming time-series data. The pressure decay rate is calculated from the pressure change curve monitored by the pressure sensors. The software analyzes the change in injection pressure over time to calculate the pressure decay rate, extracting and recording decay data at different time points. The fracturing fluid viscosity is obtained through a fluid characteristic measuring instrument during fracturing fluid injection. The software calculates the viscosity based on the real-time flow liquid characteristics and a physical model, calibrating and recording the viscosity at different time points. Through the combination of these sensor networks and software systems, all data is collected, processed, and classified in real time, and finally extracted into stress persistence performance information at different times, ensuring the accuracy and real-time nature of the data, which facilitates subsequent analysis and calculation.

[0082] The pressure maintenance index is calculated using the following formula:

[0083]

[0084] In the formula, PMI is the pressure maintenance index.

[0085] The formula for calculating the pressure sustaining index is designed in this form to comprehensively consider several key factors of fracturing fluid during fracture propagation, in order to assess its ability to sustain pressure. YLZ in the formula... x This indicates the injection pressure of the fracturing fluid. Higher pressure helps maintain fracture propagation, hence it's included in the molecule. LFB x This represents the crack closure time. A longer crack duration indicates better crack propagation persistence, and a longer closure time signifies a more significant crack maintenance effect; therefore, it is also included in the molecule. YS x This represents the pressure decay rate. A higher decay rate results in a shorter pressure maintenance time and a faster crack closure rate. Therefore, it is used as a denominator to reduce its impact on maintaining pressure. YLN xThis refers to the viscosity of the fracturing fluid. Higher viscosity helps maintain pressure within the fracture, thus aiding in fracture propagation and is treated as a denominator term. By weighted averaging these factors, the formula reasonably reflects the overall pressure maintenance effect of the fracture over different time periods, ensuring an accurate reflection of the balance and dynamic changes of various influencing factors.

[0086] The pressure sustaining index directly reflects the fracturing fluid's ability to maintain sufficient pressure within the fracture, and this ability is closely related to the evaporation of the fracturing fluid under high-temperature conditions. A low pressure sustaining index indicates that the injected pressure of the fracturing fluid cannot be maintained for an extended period, resulting in a shorter fracture closure time and a faster pressure decay rate. This is typically due to severe evaporation of the fracturing fluid at high temperatures, leading to a reduction in fluid volume and viscosity, making it impossible to continuously apply sufficient pressure within the fracture, thus affecting the effective fracture propagation range. Conversely, a higher pressure sustaining index indicates that the fracturing fluid can maintain its pressure well at high temperatures, suggesting that evaporation has a smaller negative impact on fracture propagation. Therefore, the pressure sustaining index can effectively assess whether the evaporation of the fracturing fluid under high-temperature conditions significantly affects fracture propagation.

[0087] A fracture propagation assessment model was constructed based on the generated fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, and a fracture propagation assessment coefficient was generated.

[0088] In this embodiment, a fracture propagation assessment model is constructed based on the generated fracturing fluid evaporation coefficient FFEC, fracture propagation coefficient FEC, and pressure maintenance index PMI, and the fracture propagation assessment coefficient EC is generated by weighted summation.

[0089] A fracture propagation assessment model was constructed based on the generated fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index. Specifically, the fracture propagation assessment coefficient EC was generated through weighted summation. First, three weight coefficients δ1, δ2, and δ3 were assigned, corresponding to the fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, respectively. δ1 has a relatively small weight because fracturing fluid evaporation mainly affects fluid loss under high-temperature conditions. Although evaporation affects propagation, its impact on the overall fracture propagation process is relatively limited, and it is usually set to 0.2 to 0.3. δ2 corresponds to the fracture propagation coefficient and has a larger weight because the fracture propagation coefficient directly reflects the fracture length and propagation efficiency, which is crucial for fracture propagation. Therefore, δ2 is usually set to 0.4 to 0.5. δ3 corresponds to the pressure maintenance index, with a weight between the two, usually set to 0.3 to 0.4. This is because pressure maintenance also plays a crucial role in the continuous propagation of the fracture, but its impact is relatively stable and mainly related to the fluid's ability to maintain pressure. Finally, the crack propagation assessment coefficient EC is generated by weighted summing of the three parameters using the following formula: EC = δ1*FFEC + δ2*FEC + δ3*PMI. This coefficient comprehensively considers the different weights of various influencing factors, providing a comprehensive assessment of the crack propagation effect.

[0090] Determine a pre-set threshold for the fracture propagation assessment coefficient, and compare it with the generated fracture propagation assessment coefficient after determination. Evaluate whether the evaporation of fracturing fluid under high temperature environment will affect the fracture propagation range, and generate normal and abnormal signals respectively based on the assessment results.

[0091] In this embodiment, a pre-set crack propagation evaluation coefficient threshold EC is determined. yuzhi After determination, it is compared with the generated fracture propagation assessment coefficient EC to evaluate whether the evaporation of fracturing fluid under high temperature environment will affect the fracture propagation range. Based on the assessment results, normal signals and abnormal signals are generated respectively. The specific comparison and analysis are as follows:

[0092] If EC <EC yuzhi The evaporation of fracturing fluid at high temperatures can affect the extent of fracture propagation and generate abnormal signals.

[0093] This situation indicates that the fracture propagation assessment coefficient is below the preset threshold, suggesting excessive evaporation of the fracturing fluid under high-temperature conditions. This results in insufficient fluid entering the fracture, failing to maintain enough pressure to propel it further. This affects the fracture's propagation range, preventing it from reaching the expected depth and extent, thus hindering stress release in high-stress areas. Over time, this not only increases the risk of roof instability and collapse but may also necessitate repeated fracturing operations, leading to decreased construction efficiency, increased costs, and impacting production progress and overall mine safety.

[0094] If EC≥EC yuzhi The evaporation of fracturing fluid under high temperature conditions does not affect the fracture propagation range and generates normal signals.

[0095] This situation indicates that the fracture propagation assessment coefficient has reached or exceeded the preset threshold, suggesting that the evaporation of fracturing fluid under high-temperature conditions has little negative impact on fracture propagation. The fracturing fluid can effectively enter the fracture and maintain sufficient pressure, ensuring that the fracture propagates as expected. This situation means that the fracture can cover high-stress areas and effectively release stress, ensuring the stability of the roof and the safety of the coal mine face. Production can proceed normally without additional construction adjustments or repeated fracturing operations, saving time and costs while improving the efficiency and safety of fracturing operations.

[0096] Determining a pre-set threshold for fracture propagation assessment coefficients can be achieved through methods such as analyzing historical data, simulation experiments, and field testing. First, a retrospective analysis of extensive historical fracturing operation data can identify the range of assessment coefficients that successfully achieve fracture propagation. Combining this data, statistical methods can be used to determine the range of coefficients that can achieve the expected fracture propagation effect. Second, numerical simulation models can be established to simulate fracturing processes under different environments (such as temperature and pressure), thereby testing the fracture propagation assessment coefficients under different conditions. The optimal coefficient from the simulation results can be used as a threshold reference. Finally, field testing can be conducted to collect data such as fracturing fluid injection pressure, fracture propagation length, and fracturing fluid evaporation rate during actual operations. Real-time monitoring can be used to assess the fracture propagation effect, and the threshold can be dynamically adjusted and verified based on this data to ensure its accuracy and usability.

[0097] In the event of an abnormal signal, further dynamic information on fracturing operations in the coal mine working face environment is collected, and several subsequent fracture propagation assessment coefficients are generated. A comprehensive analysis is conducted to generate risk signals of corresponding levels, and corresponding adjustment measures are taken based on the generated risk signals of corresponding levels.

[0098] In this embodiment, when an abnormal signal is generated, the dynamic information of fracturing operations in the coal mine working face environment is further analyzed, and several subsequent fracture propagation evaluation coefficients are generated. These subsequently generated fracture propagation evaluation coefficients are then recalibrated to EC. i , i represents the number of several crack propagation evaluation coefficients subsequently generated under the condition of generating an abnormal signal, i = 1, 2, 3, ..., d, where d is a positive integer;

[0099] In the event of anomaly signals, further collection of dynamic information on fracturing operations in the coal mine working face environment can be achieved through the collaboration of sensor networks and software systems. First, sensors monitor key parameters such as temperature, pressure, and fracturing fluid flow rate within the working face in real time, transmitting this data to the central monitoring system via wireless or wired networks. The software system automatically identifies the moment the anomaly signal is triggered and begins collecting real-time data for subsequent time periods from that moment. Through the data acquisition module, the software aggregates and processes data from different times, updating the dynamic information of the fracturing operation. Then, based on the newly collected data, the software generates new fracture propagation evaluation coefficients for each time period using a built-in calculation model, calculates these coefficients, and uses the data analysis module to calculate the average and standard deviation of the generated evaluation coefficients. In this way, the software can automatically and continuously track the working conditions after anomalies and provide a basis for further adjustments to operational parameters.

[0100] The average value of several crack propagation assessment coefficients is calibrated as EC. - ,but:

[0101] The standard deviation of several crack propagation assessment coefficients is calibrated as EC. σ ,but:

[0102] In this embodiment, a preset average value and a preset standard deviation of several crack propagation evaluation coefficients subsequently generated under the condition of generating an abnormal signal are obtained, and the preset average value and preset standard deviation of several crack propagation evaluation coefficients subsequently generated under the condition of generating an abnormal signal are respectively calibrated as follows: and The average value of several crack propagation evaluation coefficients generated subsequently under the condition of generating an anomalous signal, EC - and standard deviation EC σ Compared with the preset average value respectively and preset standard deviation Comparative analysis is conducted to generate risk signals of corresponding levels, and corresponding adjustment measures are taken based on the generated risk signals. The specific analysis is as follows:

[0103] like Once a high-risk level signal is generated, immediate emergency adjustment measures should be taken, including increasing the amount of fracturing fluid injected, increasing the viscosity of the fracturing fluid, and reducing the evaporation of the fracturing fluid by lowering the ambient temperature.

[0104] This situation indicates that the evaporation of fracturing fluid has severely affected the fracture propagation range, preventing the fracture from extending to the expected depth and width, and hindering the adequate pressure relief of high-stress areas. The consequences include poor fracture propagation, increased risk of roof instability and collapse, and the potential need for repeated operations, leading to increased construction time and costs. To address this, the software system can automatically adjust fracturing operation parameters. Specifically, it monitors real-time injection pressure and flow rate through sensors and increases the injection volume of fracturing fluid through algorithms. It also monitors the viscosity of the fracturing fluid and increases it using regulators or fluid property adjustment modules. Furthermore, it can automatically control temperature control devices to lower the ambient temperature of the coal mine face, thereby reducing fracturing fluid evaporation. All these operations can be executed automatically by the software and adjusted in conjunction with the real-time monitored parameters.

[0105] like and A medium-risk level signal is generated, and monitoring measures are taken, including continuous monitoring of fracturing operation parameters and adjustment of fracture closure time and pressure;

[0106] This situation indicates that fracturing fluid evaporation has some impact on fracture propagation, but the situation is relatively controllable. Fracture propagation has not yet reached a point of serious impact, but operational parameters may fluctuate. In this case, fracture propagation may exhibit localized unevenness or weakened propagation effects, which, if not adjusted, could lead to further propagation difficulties. To address this situation, the software system can continuously monitor fracturing fluid injection parameters, such as injection pressure, flow rate, and fracture closure time, and adjust operational parameters in real time. Specifically, the software algorithm analyzes the relationship between fracture closure time and pressure, dynamically adjusting the injection pressure based on current monitoring data to ensure fracture propagation remains within a reasonable range. The software can also automatically generate optimization suggestions, prompting operators through the interface to fine-tune fracture propagation pressure and time.

[0107] like and A low-risk level signal is generated; no adjustments are required, and the current operational status is maintained.

[0108] This situation indicates that fracturing fluid evaporation has a minimal impact on fracture propagation, posing a low risk, and that current operating parameters are essentially stable. This suggests that fracturing operations are proceeding as expected, fracture propagation is within acceptable limits, and production is progressing smoothly. While this situation has minimal impact and will not affect current operations, continued monitoring of operating parameters is still necessary to ensure no sudden evaporation anomalies occur under high-temperature conditions. To address this, the software system can continue real-time data acquisition, automatically recording fracturing fluid flow rate, injection pressure, and temperature, and providing monitoring and early warnings based on preset thresholds. In this case, no adjustment of operating parameters is required; the software will maintain its current operating status, periodically updating and analyzing data to ensure successful operation.

[0109] In the event of an anomaly signal, to obtain the preset average and standard deviation of several subsequently generated fracture propagation assessment coefficients, the software first needs to automatically collect dynamic data of fracturing operations over a subsequent period, such as fracturing fluid injection pressure, flow rate, fracture length, and ambient temperature. The software system inputs this real-time data into the calculation model to generate a series of new fracture propagation assessment coefficients. Then, the software automatically calculates the preset average and standard deviation of these assessment coefficients through its built-in statistical analysis module. Specifically, the software collects and labels each generated assessment coefficient, classifies the data according to the time series, and uses an algorithm to sum and calculate the squared difference of all assessment coefficients, ultimately obtaining the average and standard deviation. These statistical results provide data support for subsequent risk level assessment and operational adjustments, ensuring the accuracy of real-time monitoring and analysis.

[0110] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0111] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0112] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0113] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0114] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0115] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0116] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0117] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A hydraulic fracturing roof cutting and pressure relief method for coal mine working faces, characterized in that, Specifically, the following steps are included: At the coal mine working face in deep high-temperature rock strata, a sensor network is deployed to acquire dynamic information on fracturing operations in the coal mine working face environment, and the acquired dynamic information on fracturing operations in the coal mine working face environment is stored in the central monitoring system. The dynamic information of fracturing operations stored in the central monitoring system is analyzed to generate fracturing fluid evaporation coefficient, fracture propagation coefficient and pressure maintenance index, respectively. Specifically, the following steps are included: Preprocess the dynamic information of fracturing operations stored in the central monitoring system; Extract dynamic information on thermal fluid evaporation, fracture morphology evolution, and stress persistence effectiveness from the pre-processed dynamic information of fracturing operations; The extracted dynamic information on thermal fluid evaporation, fracture morphology evolution, and stress sustainability were analyzed to generate fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, respectively. A fracture propagation assessment model was constructed based on the generated fracturing fluid evaporation coefficient, fracture propagation coefficient, and pressure maintenance index, and a fracture propagation assessment coefficient was generated. Determine a pre-set threshold for the fracture propagation assessment coefficient, and compare it with the generated fracture propagation assessment coefficient after determination. Evaluate whether the evaporation of fracturing fluid under high temperature environment will affect the fracture propagation range, and generate normal and abnormal signals respectively based on the assessment results. In the event of an abnormal signal, further dynamic information on fracturing operations in the coal mine working face environment is collected, and several subsequent fracture propagation assessment coefficients are generated. A comprehensive analysis is conducted to generate risk signals of corresponding levels, and corresponding adjustment measures are taken based on the generated risk signals of corresponding levels.

2. The hydraulic fracturing and roof-cutting depressurization method for coal mine working faces according to claim 1, characterized in that, The logic for obtaining the fracturing fluid evaporation coefficient is as follows: Extracting the thermal fluid evaporation dynamics information from the pre-processed fracturing operation dynamics data, specifically including the rock layer temperature of the high-temperature rock strata at the coal mine face at different times over a period of time, the actual flow rate of the fracturing fluid, the actual temperature of the fracturing fluid, and the average pressure of the local environment at the coal mine face, and labeling these parameters as follows: , , and , This refers to the numbering of the rock strata temperature, actual flow rate of fracturing fluid, actual temperature of fracturing fluid, and average pressure of the local environment at the coal mine working face at different times over a period of time. , It is a positive integer; The specific formula for calculating the fracturing fluid evaporation coefficient is as follows: In the formula, This represents the evaporation coefficient of the fracturing fluid.

3. The hydraulic fracturing and roof-cutting depressurization method for coal mine working faces according to claim 2, characterized in that, The logic for obtaining the crack propagation coefficient is as follows: Extract fracture morphology evolution information from the preprocessed dynamic information of fracturing operations, specifically including fracture length, fracturing fluid injection pressure, actual fracturing fluid flow rate, and actual rock hardness at the coal mine face at different times within a certain period. These parameters are then labeled as follows: , , and , This refers to the numbering of the fracture length, fracturing fluid injection pressure, and actual fracturing fluid flow rate at different times within a certain period of time at the coal mine working face. , It is a positive integer; The crack propagation factor is calculated using the following formula: In the formula, is the crack propagation coefficient.

4. A hydraulic fracturing and roof-cutting depressurization method for coal mine working faces according to claim 3, characterized in that, The logic for obtaining the pressure maintenance index is as follows: Stress persistence performance information is extracted from the pre-processed dynamic information of fracturing operations. Specifically, this includes fracturing fluid injection pressure, fracture closure time, fracturing fluid pressure decay rate, and fracturing fluid viscosity at different times within a given period. These parameters are then calibrated as follows: , , and , The fracturing fluid injection pressure, fracture closure time, fracturing fluid pressure decay rate, and fracturing fluid viscosity are numbered at different times within a certain period. , It is a positive integer; The pressure maintenance index is calculated using the following formula: In the formula, The pressure maintenance index.

5. A hydraulic fracturing and roof-cutting depressurization method for coal mine working faces according to claim 4, characterized in that, Evaporation coefficient of the generated fracturing fluid Crack propagation coefficient and pressure maintenance index Construct a crack propagation assessment model and generate crack propagation assessment coefficients through weighted summation. .

6. A hydraulic fracturing and roof-cutting depressurization method for coal mine working faces according to claim 5, characterized in that, Determine the pre-set threshold for crack propagation evaluation coefficient. And after determination, it is compared with the generated crack propagation evaluation coefficient. A comparison was conducted to assess whether the evaporation of fracturing fluid under high-temperature conditions would affect the fracture propagation range. Based on the assessment results, normal and abnormal signals were generated respectively. The specific comparative analysis is as follows: like The evaporation of fracturing fluid at high temperatures can affect the extent of fracture propagation and generate abnormal signals. like The evaporation of fracturing fluid under high temperature conditions does not affect the fracture propagation range and generates normal signals.

7. A hydraulic fracturing and roof-cutting depressurization method for coal mine working faces according to claim 6, characterized in that, In the event of anomaly signals, further dynamic information on fracturing operations in the coal mine working face environment is obtained, and several subsequent fracture propagation assessment coefficients are generated. These subsequently generated fracture propagation assessment coefficients are then recalibrated. , This indicates the number of several crack propagation evaluation coefficients subsequently generated when an anomalous signal is generated. , It is a positive integer; The average value of several crack propagation assessment coefficients is calibrated as follows: ,but: ; The standard deviation of several crack propagation evaluation coefficients is calibrated as follows: ,but: .

8. A hydraulic fracturing and roof-cutting depressurization method for coal mine working faces according to claim 7, characterized in that, Obtain the preset average value and preset standard deviation of several crack propagation evaluation coefficients subsequently generated under the condition of generating an anomalous signal. Define the preset average value and preset standard deviation of these coefficients as follows: and The average of several crack propagation evaluation coefficients generated subsequently in the event of an anomalous signal. and standard deviation Compared with the preset average value respectively and preset standard deviation Comparative analysis is conducted to generate risk signals of corresponding levels, and corresponding adjustment measures are taken based on the generated risk signals. The specific analysis is as follows: like A high-risk level signal is generated, and emergency adjustment measures are immediately taken, including increasing the amount of fracturing fluid injected, increasing the viscosity of the fracturing fluid, and reducing the evaporation of the fracturing fluid by lowering the ambient temperature; like and A medium-risk level signal is generated, and monitoring measures are taken, including continuous monitoring of fracturing operation parameters and adjustment of fracture closure time and pressure. like and It generates a low-risk level signal, requiring no adjustments and maintaining the current operational status.

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