A method and device for early warning of gas eruptions from boreholes

Abstract

This invention relates to a method and device for early warning of borehole gas eruptions, belonging to the field of coal mine safety. It solves at least one of the problems in existing technologies, such as the inability to accurately predict and classify the degree of danger of eruptions, leading to untimely early warning responses and mismatches between response measures and the degree of danger. A method for early warning of borehole gas eruptions includes the following steps: constructing a borehole intensity classification model; data acquisition: acquiring time-series data of gas emission; classification determination: comparing the time-series data of gas emission with the borehole intensity classification model point by point; determining the current borehole intensity level based on the classification threshold range into which the gas emission falls; and early warning response: inputting the current borehole intensity level into a pre-constructed borehole early warning response model. This invention achieves accurate prediction and classified early warning of the degree of danger of boreholes, improving the safety of underground drilling operations.

Description

Technical Field

[0001] This invention relates to the field of coal mine safety technology, and in particular to a method and device for early warning of gas eruptions in boreholes. Background Technology

[0002] Gas eruptions are an extremely dangerous dynamic phenomenon during drilling operations in underground engineering projects such as coal mines and tunnels. They can lead to excessive gas concentrations, flying coal dust, and casualties, seriously hindering safe and efficient underground production.

[0003] To address the problem of borehole gas outbursts, various gas outburst prevention methods have been developed in existing technologies. However, in practical applications, the following shortcomings still exist: Existing early warning methods rely heavily on manual experience, such as roughly judging the degree of danger of an outburst based on the vibration of the gas drainage pipeline or the leakage at the connection of the negative pressure drainage pipeline. These methods lack intuitive, reliable, and quantifiable early warning indicators, resulting in a high rate of misjudgment and missed judgment. At the same time, existing technologies mainly rely on passive protection, only taking mechanical measures after an outburst occurs. They cannot accurately predict and classify the degree of danger of an outburst. Workers often only realize the danger and stop drilling when the outburst erupts violently, making it difficult to take effective avoidance measures in time, which can easily lead to gas over-limit accidents.

[0004] Therefore, how to accurately predict and classify the degree of danger of blowouts during underground drilling construction remains a technical problem that urgently needs to be solved. Summary of the Invention

[0005] In view of the above analysis, the present invention aims to provide a method and device for early warning of borehole gas eruptions, so as to solve at least one of the problems in the prior art, such as the inability to accurately predict and classify the degree of danger of the eruption, resulting in untimely early warning response and mismatch between response measures and degree of danger.

[0006] The objective of this invention is achieved through the following technical solution: This invention provides a method for early warning of gas eruptions in boreholes, comprising the following steps: Model construction: Obtain the basic mechanical parameters and geostress parameters of the coal body, wherein the basic mechanical parameters include: the cohesion c of the coal body and the residual cohesion. internal friction angle Cohesive softening modulus The shear modulus G and the influence coefficient b of the intermediate principal stress for coal body failure; the geostress parameters include: initial vertical stress σ 10 Initial minimum horizontal stress Based on a unified strength criterion and a roadway excavation model, and according to the obtained basic mechanical parameters and geostress parameters of the coal body, the influence coefficients t and g of the radius of the plastic zone and the radius of the failure zone of the coal body surrounding the borehole are constructed. Based on t, g, and the benchmark value W0 of borehole gas emission per unit time during normal drilling in the mining area, a blowout intensity grading model is constructed. The blowout intensity grading model includes multiple grading threshold intervals, and each grading threshold interval corresponds to a blowout intensity level. Data acquisition: Obtain time-series data on gas emission; Classification determination: The time series data of gas emission is compared point by point with the nozzle intensity classification model; the current nozzle intensity level is determined according to the classification threshold range into which the gas emission falls. Warning response: Input the current nozzle intensity level into the pre-built nozzle warning response model.

[0007] Furthermore, the nozzle early warning response model is pre-built through the following steps: establishing a mapping relationship between nozzle intensity level and early warning response strategy.

[0008] Furthermore, the mapping relationship between the nozzle intensity level and the early warning response strategy includes: The mild nozzle level is mapped to a three-level early warning response strategy, and the three-level early warning response strategy is configured to output a three-level early warning signal; The medium-level nozzle grade is mapped to a two-level early warning response strategy, and the two-level early warning response strategy is configured to output a two-level early warning signal; The severity of the jetting is mapped to a Level 1 warning response strategy, which is configured to output a Level 1 warning signal and simultaneously output a linkage control command.

[0009] Furthermore, the acquisition of gas emission time-series data includes: A gas emission monitoring unit installed in the exhaust channel of the blowout preventer continuously collects the gas emission rate W per unit time at fixed time intervals. t Generate time-series data of gas outflow arranged in chronological order.

[0010] Furthermore, the linkage control commands include commands to cut off the drilling rig power supply and commands to activate the blowout preventer locking mechanism.

[0011] Furthermore, the command to activate the blowout preventer locking mechanism includes: Send a start signal to the hydraulic slip clamping device to drive the slips to retract radially and clamp the drill pipe; Send a start signal to the electric control valve to open it to its maximum opening degree to introduce the high-pressure gas and pulverized coal mixture into the mine gas extraction system; A start signal is sent to the mechanical anti-backflow device to form a one-way flow in the diversion channel to prevent backflow of gas and pulverized coal.

[0012] Furthermore, the nozzle intensity grading model includes a mild nozzle threshold range, a moderate nozzle threshold range, and a severe nozzle threshold range; The threshold range for mild nozzles: W0≤W t ≤t 2 ×g 2 ×W0; The moderate nozzle threshold range: t 2 ×g 2 ×W0<W t ≤t 2 ×W0; The threshold range of the severe jet nozzle: t 2 ×W0<W t ; Among them, W t This refers to the amount of gas emitted per unit time.

[0013] Furthermore, the influence coefficient t of the plastic zone radius is constructed according to the following formula: .

[0014] Furthermore, the influence coefficient g of the radius of the damaged zone is constructed according to the following formula:

[0015] in, The value range is 1.3 to 1.5.

[0016] This invention provides a borehole gas eruption early warning device for performing the early warning method, comprising: The model building module is used to build the nozzle intensity grading model; The data acquisition module obtains time-series data on gas emission. The grading determination module compares the gas emission time series data with the nozzle intensity grading model point by point, and determines the current nozzle intensity level based on the grading threshold range into which the collected gas emission per unit time falls. The early warning response module inputs the current nozzle intensity level into a pre-built nozzle early warning response model and executes an early warning based on the early warning response strategy output by the nozzle early warning response model.

[0017] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects: (1) The early warning method and device provided by the present invention construct a blowout intensity classification model based on the influence coefficient t of the plastic zone radius of the coal body surrounding the borehole, the influence coefficient g of the radius of the damaged zone, and the benchmark value W0 of the borehole gas emission per unit time during normal drilling, thereby quantitatively correlating the gas emission with the degree of damage to the surrounding rock of the borehole. Among them, the influence coefficient t of the plastic zone radius is used as a dimensionless parameter characterizing the degree of expansion of the plastic zone, the influence coefficient g of the radius of the damaged zone is used as a dimensionless parameter characterizing the degree of expansion of the damaged zone relative to the plastic zone, and W0 represents the gas emission level under normal drilling conditions. Based on t, g, and W0, multiple classification threshold intervals are determined, realizing the scientific classification and accurate prediction of the degree of danger of the blowout, and solving the problems of existing technologies relying on manual experience, lacking quantitative indicators, and being unable to classify scientifically.

[0018] (2) The early warning method and device provided by the present invention compare the real-time collected gas emission time series data with the nozzle intensity grading model point by point, and determine the current nozzle intensity level according to the grading threshold range in which the gas emission per unit time falls. This point-by-point comparison method can realize continuous monitoring and dynamic analysis of gas emission, identify the danger level and determine the nozzle intensity in the early stage of nozzle development, so that operators can take corresponding risk avoidance measures in time before or in the early stage of nozzle occurrence, avoiding the problem of traditional methods relying on manual experience judgment, often only realizing the danger when the nozzle violently erupts and responding with lag.

[0019] (3) The early warning method and device provided by the present invention realize the execution of the corresponding early warning response strategy according to the current nozzle intensity level by inputting the determined current nozzle intensity level into the pre-constructed nozzle early warning response model, so that the early warning response measures are accurately matched with the nozzle danger level, avoiding the problems of untimely early warning response and mismatch between response measures and danger level (such as insufficient or excessive response) in the prior art.

[0020] (4) The early warning method and device provided in this embodiment of the invention achieve an accuracy rate of ≥90% and a false alarm rate of ≤10% when providing early warnings for gas eruption parameters and events during actual construction of more than 3 boreholes. The gas eruption parameters and events include the eruption intensity level, the number of eruptions, the time of eruption, and the duration of the eruption. The early warning method and device provided in this invention are significantly superior to traditional manual judgment methods and existing early warning devices for borehole gas eruption events, effectively improving the safety of downhole drilling construction.

[0021] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0022] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0023] Figure 1 This is a flowchart illustrating the borehole gas eruption early warning method provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of the blowout preventer body in the early warning device provided in the embodiment of the present invention; Figure 3 This is a schematic diagram of the loading of the true triaxial mechanical test in the borehole gas eruption early warning method provided in the embodiment of the present invention; Figure 4 This is a schematic diagram of drilling into the coal seam in an embodiment of the present invention; Figure label: 1-Solid-liquid-gas separator; 2-Guide pipe; 3-Extraction pipe; 4-Coal outlet trough; 5-Gas emission data output device. Detailed Implementation

[0024] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0025] Currently, widely used borehole gas blowout prevention measures are mainly designed based on the mechanical and physical principles of "sealing, guiding, and controlling." These measures can perform operations such as orifice sealing, pressure relief, and mechanical backflow prevention after a blowout occurs, providing a certain degree of passive protection. However, due to the lack of scientific early warning methods, existing blowout prevention measures still have the following shortcomings in practical applications: Firstly, they cannot accurately predict and classify the degree of danger of a blowout. Workers often only realize the danger and stop drilling when the blowout erupts violently, resulting in a delayed early warning response. Secondly, due to the lack of quantitative classification criteria, workers find it difficult to take timely avoidance measures that match the degree of danger of the blowout, easily leading to insufficient or excessive responses, causing gas exceedance accidents or affecting construction efficiency. Furthermore, existing blowout prevention measures cannot automatically record blowout parameters, making it difficult to provide data support for accurate assessment of gas geological conditions at the working face. Therefore, how to construct a scientific early warning method that enables existing blowout prevention measures to have the ability to accurately predict, classify, and respond precisely is a technical problem that urgently needs to be solved in the field of coal mine safety. However, constructing a scientific and reliable borehole gas blowout early warning method is no easy task. The geological conditions underground in coal mines are complex and variable. Different mines, different coal seams, and even different areas within the same working face exhibit significant differences in coal mechanics and geostress conditions. Directly employing empirical formulas or statistical laws to construct early warning methods is ill-suited to these complex and ever-changing underground conditions, leading to a significant reduction in the accuracy of early warnings. More importantly, any early warning method must be based on obtainable and operable parameters. However, the unique environment of coal mines limits the means of parameter acquisition. Ensuring the theoretical rigor of the early warning method while guaranteeing the effective measurement of the required parameters under field or laboratory conditions presents a major technical challenge for those skilled in the art.

[0026] To address the aforementioned problems, the inventors, through research, proposed a scientifically reliable and easily implemented early warning technology solution for borehole gas eruptions, as detailed below. This invention provides a method for early warning of gas eruptions in boreholes, comprising the following steps: Model construction: Obtain the basic mechanical parameters and geostress parameters of the coal body, wherein the basic mechanical parameters include: the cohesion c of the coal body and the residual cohesion. internal friction angle Cohesive softening modulus The shear modulus G and the influence coefficient b of the intermediate principal stress for coal body failure; the geostress parameters include: initial vertical stress σ 10 Initial minimum horizontal stress Based on a unified strength criterion and a roadway excavation model, and according to the obtained basic mechanical parameters and geostress parameters of the coal body, the influence coefficients t and g of the radius of the plastic zone and the radius of the failure zone of the coal body surrounding the borehole are constructed. Based on t, g, and the benchmark value W0 of borehole gas emission per unit time during normal drilling in the mining area, a blowout intensity grading model is constructed. The blowout intensity grading model includes multiple grading threshold intervals, and each grading threshold interval corresponds to a blowout intensity level. Data acquisition: Obtain time-series data on gas emission; Classification determination: The time series data of gas emission is compared point by point with the nozzle intensity classification model, and the current nozzle intensity level is determined according to the classification threshold range in which the collected gas emission per unit time falls. Warning response: Input the current nozzle intensity level into the pre-built nozzle warning response model; further, execute the corresponding warning response strategy.

[0027] Specifically, the multiple graded threshold ranges include a mild nozzle threshold range, a moderate nozzle threshold range, and a severe nozzle threshold range.

[0028] Preferably, the mild nozzle threshold range is composed of W0 and t 2 ×g 2 ×W0 defines the moderate nozzle threshold range, which is defined by t. 2 ×g 2 ×W0 and t 2 ×W0 defines the severe nozzle threshold range, which is defined by t. 2 ×W0 defines the boundary.

[0029] Specifically, the acquisition of gas emission time-series data includes: continuously collecting the gas emission rate W per unit time at fixed time intervals using a gas emission monitoring unit installed in the exhaust channel of the blowout preventer. t Generate time-series data of gas outflow arranged in chronological order.

[0030] For example, the fixed time interval is from 1 second to 60 minutes; for example, 10s, 30s, 1min, 5min, 10min, 20min, 30min, 45min.

[0031] For example, the gas emission monitoring unit is a gas concentration sensor or a gas flow meter.

[0032] For example, the gas emission monitoring unit is located between the solid-liquid-gas separation box and the extraction pipe of the blowout preventer body, or is located on the extraction pipe.

[0033] Preferably, after acquiring the time-series data of gas emission, the method further includes outlier removal processing of the time-series data. For example, the outlier removal processing includes: calculating the mean and standard deviation of gas emission within a preset time window; when the gas emission at the current moment deviates from the mean by more than three times the standard deviation, it is determined to be an outlier and removed. The removed outlier is replaced by the gas emission at the previous moment, the gas emission at the next moment, or a linear interpolation between the two moments.

[0034] Specifically, in the grading determination, the step of determining the current nozzle intensity level based on the grading threshold range into which the collected gas emission per unit time falls includes: The gas emission rate (W) per unit time at each sampling moment t Compare with the threshold ranges for mild, moderate, and severe nozzles, respectively; When the gas emission rate W per unit time t When the intensity falls within the threshold range of a minor nozzle, the current nozzle intensity level is determined to be a minor nozzle level. When the gas emission rate W per unit time t When the current nozzle intensity level falls within the medium nozzle threshold range, it is determined to be a medium nozzle level. When the gas emission rate W per unit time t When the current nozzle intensity level falls within the severe nozzle threshold range, it is determined to be a severe nozzle level.

[0035] Specifically, the point-by-point comparison is as follows: the gas emission per unit time collected at each collection moment is compared with each graded threshold interval (such as the threshold interval for mild nozzles, the threshold interval for moderate nozzles, and the threshold interval for severe nozzles) in chronological order.

[0036] Preferably, the classification determination further includes: recording nozzle events based on the changing trend of gas emission time-series data. When the gas emission rate W per unit time t From below the lower limit of the mild nozzle threshold range (as in some embodiments, W) t When <W0) enters the mild nozzle threshold range, record one mild nozzle event; When the gas emission rate W per unit time t W is below the lower limit of the moderate nozzle threshold range (as in some embodiments). t ≤t 2 ×g 2 When ×W0) enters the medium nozzle threshold range, record a medium nozzle event; When the gas emission rate W per unit time t From below the lower limit of the severe nozzle threshold range (as in some embodiments, W) t ≤t 2When ×W0) enters the severe nozzle threshold range, record one severe nozzle event; During the same nozzle process, when the gas emission rate W per unit time t When the number of nozzles at a given level fluctuates within the same threshold range, the number of nozzles at that level will not be recorded repeatedly.

[0037] Specifically, when the gas emission rate W per unit time t When the temperature drops below the lower limit of the mild nozzle threshold range, the nozzle process is considered to have ended, and the nozzle intensity level is stopped being output.

[0038] For example, the recorded nozzle event includes recording the nozzle occurrence time (the moment when it first enters the corresponding threshold range), the nozzle intensity level (such as mild / moderate / severe), and the nozzle duration (the duration from the moment it first enters the corresponding threshold range to the moment it leaves the range).

[0039] For example, the early warning method further includes: generating a blowout event database based on recorded blowout events for assessing the gas geological conditions of the working face and for disaster early warning.

[0040] Specifically, the nozzle early warning response model is pre-built through the following steps: establishing a mapping relationship between nozzle intensity level and early warning response strategy.

[0041] Specifically, the mapping relationship between the nozzle intensity level and the early warning response strategy includes: The mild nozzle level is mapped to a three-level early warning response strategy, and the three-level early warning response strategy is configured to output a three-level early warning signal; The medium-level nozzle grade is mapped to a two-level early warning response strategy, and the two-level early warning response strategy is configured to output a two-level early warning signal; The severity of the jetting is mapped to a Level 1 warning response strategy, which is configured to output a Level 1 warning signal and simultaneously output a linkage control command.

[0042] In some embodiments, the first-level warning signal, the second-level warning signal, and the third-level warning signal are audible and visual alarm signals of different colors or frequencies.

[0043] For example, the third-level warning signal is a yellow audible and visual warning signal, the second-level warning signal is an orange audible and visual warning signal, and the first-level warning signal is a red audible and visual warning signal.

[0044] For example, the first-level warning signal is also accompanied by a rapid beeping sound.

[0045] Specifically, the linkage control commands include commands to cut off the drilling rig power supply and commands to activate the blowout preventer locking mechanism.

[0046] For example, the command to cut off the drilling rig power is sent to the drilling rig power control circuit to immediately stop the drilling operation.

[0047] Preferably, the command to activate the blowout preventer locking mechanism is output synchronously with the first-level warning signal.

[0048] In some embodiments, the command to activate the blowout preventer locking mechanism includes: A start signal is sent to the hydraulic slip clamping device to drive the slips to retract radially and clamp the drill pipe; this achieves emergency braking of the drill pipe and enhances the orifice seal, preventing the drill pipe from being ejected and gas leakage; Send a start signal to the electric control valve to open it to its maximum opening degree to introduce the high-pressure gas and pulverized coal mixture into the mine gas extraction system; thus achieving emergency pressure relief. Send a start signal to the mechanical anti-backflow device to form a one-way flow in the diversion channel to prevent backflow of gas and pulverized coal, thus ensuring the safety of the work area.

[0049] Preferably, the time for the electric control valve to open to its maximum opening degree is on the order of milliseconds.

[0050] Specifically, when the gas emission rate W per unit time t When the temperature drops below the lower limit of the mild nozzle threshold range, the warning signal output stops, and the linkage control command remains in execution until manual reset confirmation. Manual reset confirmation includes: after on-site safety checks confirm safety, releasing the locked state via the manual reset button.

[0051] It is understood that the locked state refers to the safety lock state after the drilling rig is powered off, the slips are clamped, the valves are fully open, and the anti-backflow mechanism is activated after a violent jetting triggers the linkage response. It needs to be manually confirmed to be safe and then released by manually resetting the button.

[0052] In some preferred embodiments, the early warning method provided by the present invention includes a nozzle intensity grading model that includes a mild nozzle threshold range, a moderate nozzle threshold range, and a severe nozzle threshold range. The threshold range for mild nozzles: W0≤W t ≤t 2 ×g 2 ×W0; The moderate nozzle threshold range: t 2 ×g 2 ×W0<W t ≤t 2 ×W0; The threshold range of the severe jet nozzle: t 2 ×W0<W t ; Among them, W t This refers to the amount of gas emitted per unit time.

[0053] The nozzle intensity grading model described in this invention stems from the inventor's profound understanding of the intrinsic relationship between the zonal failure characteristics of the coal seam surrounding the borehole and the gas emission patterns. Specifically, based on the zonal failure characteristics of the coal seam surrounding the borehole, which sequentially forms a failure zone, a plastic zone, and an elastic zone from the borehole wall outwards, this invention introduces the influence coefficients t (radius of the plastic zone) and g (radius of the failure zone), and combines them with the benchmark value W0 of gas emission under normal drilling conditions to construct a mild nozzle (W0≤W...) grading model. t ≤t 2 ×g 2 ×W0), medium nozzle (t) 2 ×g 2 ×W0<W t ≤t 2 ×W0) and violent nozzle (t) 2 ×W0<W t Three graded threshold intervals, using the squared form (t) 2 t 2 ×g 2 This model maps the linear expansion of the radial pressure relief range of the borehole to a quadratic increase in the gas emission area, accurately depicting the physical law that the emission rate accelerates as the damage area expands. The scientific validity and rationality of this classification model lie in the following: in mild perforations, the fracturing of the coal in the damaged zone is the main factor in gas emission; in moderate perforations, deformation and damage of the coal in the plastic zone become the dominant factors; and in severe perforations, the stress release and sudden energy release of the coal in the elastic zone cause a sharp increase in gas emission. The three threshold intervals correspond to the gas emission levels at the boundaries of the damaged zone and the plastic zone, respectively, giving the classification thresholds clear physical and mechanical significance. Based on this classification model, this invention compares the continuous monitoring values ​​of gas emission rate with each threshold interval point by point. This allows for dynamic identification of the hazard level in the early stages of perforation development, enabling operators to take appropriate measures before or in the early stages of perforation. Simultaneously, point-by-point comparison achieves continuous monitoring and dynamic analysis, ensuring precise matching of early warning response with the perforation hazard level. This avoids problems such as insufficient or excessive response caused by existing technologies relying on manual experience and lacking quantitative classification basis.

[0054] See Figure 4 During drilling, the coal seam around the borehole forms a fracture zone, a plastic zone, and an elastic zone, whose W t The main factor is whether blowouts occur in the coal seam in the fractured area and plastic zone surrounding the borehole. During normal drilling, W t Originating only from coal seams within the borehole radius R1; when a slight blowout occurs in the borehole, W t Derived from the borehole radius R p Coal body within the range; when a moderate blowout occurs in the borehole, W t Derived from the borehole radius R s The coal seam within the range; when a violent blowout occurs in the borehole, Wt Originating from a borehole radius exceeding R s The influence range extends into the elastic zone of the coal body. The plastic zone radius influence coefficient t and the failure zone radius influence coefficient g of the coal body surrounding the borehole, constructed in this invention, are used to quantify the evolution characteristics of the plastic and failure zones of the borehole surrounding rock under a unified strength criterion.

[0055] In some preferred embodiments, the influence coefficient t of the plastic zone radius is constructed according to the following formula: .

[0056] It should be noted that, guided by the unified strength criterion and the roadway excavation model, and based on the above formula, determining the influence coefficient t of the plastic zone radius according to the formula, based on cohesion, internal friction angle, intermediate principal stress influence coefficient, and initial minimum horizontal stress, has the following advantages: First, this method is based on the unified strength criterion and the roadway excavation model, comprehensively considering the cohesive characteristics (c) and shear characteristics (c) of the coal body. (b) and the enhancement effect of intermediate principal stress under three-dimensional stress state, compared with the traditional single-parameter model based on the Mohr-Coulomb criterion, can more realistically reflect the mechanical response of coal under complex stress conditions and actual excavation disturbance; secondly, by introducing the initial minimum horizontal stress As a boundary condition for geostress, the t-value can quantitatively characterize the expansion range of the plastic zone after tunnel excavation under specific geological conditions in mining areas, realizing an organic connection from laboratory mechanical parameters to field engineering applications. Furthermore, as a dimensionless parameter characterizing the degree of expansion of the plastic zone, t transforms the abstract range of coal body damage around the borehole into a calculable and comparable specific value, providing a solid mechanical basis for the subsequent construction of the blowout intensity grading threshold. This effectively solves the technical problem of the lack of quantitative judgment standards for the hazard level of existing blowout prevention devices, thereby realizing the scientific prediction and accurate early warning of blowout hazards.

[0057] In some preferred embodiments, the influence coefficient g of the damaged zone radius is constructed according to the following formula:

[0058] in, The value range is 1.3 to 1.5.

[0059] For example, The values ​​are 1.3, 1.32, 1.35, 1.37, 1.38, 1.39, 1.40, 1.41, 1.42, 1.45, 1.47, and 1.50; the preferred values ​​are 1.38 to 1.42.

[0060] Specifically, cohesion c and residual cohesion The unit is MPa; the internal friction angle The units are °; shear modulus G and cohesive softening modulus. The unit is GPa; initial minimum horizontal stress and initial vertical stress The unit is MPa; the influence coefficient b of the intermediate principal stress is a dimensionless parameter.

[0061] It should be noted that, guided by the unified strength criterion and the tunnel excavation model, and based on the above formula, the cohesion c and residual cohesion are considered. internal friction angle Cohesive softening modulus Shear modulus G, intermediate principal stress influence coefficient b, initial minimum horizontal stress and initial vertical stress Determining the influence coefficient g of the radius of the damaged zone through the aforementioned specific quantitative relationship has the following advantages: First, this method breaks through the limitations of the traditional ideal elastoplastic model by introducing the cohesive softening modulus. and residual cohesion The model fully considers the strain softening characteristics of coal as it transitions from peak strength to residual strength. Within the framework of a unified strength criterion, it comprehensively reflects the enhancing effect of intermediate principal stress on the residual strength of the coal, enabling a more realistic depiction of the progressive deterioration process of the coal surrounding the borehole after failure. Secondly, the roadway excavation model provides a clear mechanical boundary for the construction of the g-coefficient by integrating the shear modulus G and the initial vertical stress. The parameter g comprehensively reflects the stiffness characteristics of the coal body and the influence of the maximum principal stress in the geostress field, accurately quantifying the extension depth of the plastic zone to the failure zone, and realizing the mechanical description of the zonal failure characteristics of the borehole surrounding rock. Furthermore, as a dimensionless parameter characterizing the degree of expansion of the failure zone relative to the plastic zone, g forms a progressive relationship with the t coefficient. In the evolution chain of "hole periphery stress redistribution - plastic zone formation - failure zone expansion" in the roadway excavation model, it jointly constructs a complete "elastic zone - plastic zone - failure zone" zonal failure evaluation system, enabling the blowout strength grading threshold to scientifically correspond to the gas emission law of different damage levels of the coal body. Finally, this multi-parameter coupled g value calculation method organically integrates the theoretical rigor of the unified strength criterion, the constitutive relationship of coal and rock mechanics, the characteristics of the geostress field, and the disturbance of borehole construction, significantly improving the accuracy and engineering applicability of blowout hazard level determination, and providing reliable technical support for graded early warning and active prevention and control of underground borehole construction.

[0062] Preferably, the method for determining the intermediate principal stress influence coefficient b includes the following steps: A rectangular coal sample was prepared, and a true triaxial mechanical test was conducted to set the minimum confining pressure. Second confining pressure ,and > Axial pressure was applied until the coal sample failed, and the axial pressure at failure was recorded. ; The influence coefficient of the intermediate principal stress is calculated using the following formula: .

[0063] It should be noted that this invention accurately determines the failure strength of coal samples under different stress paths through true triaxial mechanical tests, based on the axial compression at failure obtained from the tests. and the set minimum confining pressure Second confining pressure Based on the quantitative relationship, the intermediate principal stress influence coefficient *b* for coal body failure is determined. This coefficient quantitatively characterizes the contribution of the intermediate principal stress to the strength of the coal body. Under true triaxial stress conditions, the expansion initiation point, peak strength, and failure mode of coal and rock are all closely related to the intermediate principal stress coefficient *b* for coal body failure. Introducing the experimentally determined value of *b* into the key influencing factors *g* and *t* in the orifice grade determination can more realistically reflect the progressive failure process of coal body in three-dimensional stress space, overcome the limitation of traditional prediction methods that ignore the influence of intermediate principal stress, and significantly improve the prediction model's ability to identify coal and gas outburst risks under complex stress conditions, thus providing a more reliable basis for judgment and early warning for the prevention and control of coal mine dynamic disasters.

[0064] It is understood that the cuboid coal sample includes a cubic coal sample. For example, the length × width × height of the cuboid coal sample is (45~55) mm × (45~55) mm × (90~110) mm.

[0065] Specifically, the non-parallelism of the two end faces of the cuboid coal sample is ≤0.1mm, and the non-perpendicularity of adjacent planes is ≤0.1mm.

[0066] Specifically, during a true triaxial mechanical test, minimum confining pressure is applied symmetrically in two mutually perpendicular horizontal directions. Second confining pressure Up to the preset value; after the confining pressure stabilizes, maintain... and Constant, in the perpendicular and Axial pressure is applied vertically to the plane of the sample until it fails, and the axial pressure value at the point of failure is recorded. .

[0067] Specifically, when conducting a true triaxial mechanical test, the number of cuboid coal samples should be at least three, for example, three to five, and the arithmetic mean of the axial compression at failure of each coal sample should be taken. As Furthermore, if the destructive axial compression value of a coal sample deviates from the average value by more than ±15%, it is considered invalid data, and additional coal samples are prepared for retesting until the number of valid coal samples is no less than 3.

[0068] For example, in the true triaxial mechanical test, the minimum confining pressure Second confining pressure and axial compression See Figure 3 .

[0069] Preferably, in the true triaxial mechanical test: the minimum confining pressure Set to 5-15MPa, the second confining pressure Set to 10-25MPa, and and The difference is not less than 5 MPa. More preferably, and The difference is 5-10 MPa.

[0070] Preferably, in the true triaxial mechanical test, the loading rate of the applied axial pressure is 0.0001-0.0005 mm / min.

[0071] It should be noted that this invention controls the minimum confining pressure. Second confining pressure The difference in loading conditions ensures that the coal sample is under a significant stress difference, preventing the true influence of the intermediate principal stress from being masked by excessively close biaxial confining pressures. Simultaneously, employing a lower quasi-static loading rate eliminates the interference of kinetic effects on strength testing and ensures sufficient development of microcracks within the coal sample, resulting in more stable and reliable peak strength data. Furthermore, strict control over the coal sample processing precision (parallelism between two end faces ≤ 0.1 mm, perpendicularity between adjacent faces ≤ 0.1 mm) eliminates stress concentration errors caused by geometric deviations. This comprehensive control of loading conditions provides crucial assurance for obtaining a more accurate and repeatable intermediate principal stress coefficient, b.

[0072] Preferably, the residual cohesion The method for determining it includes the following steps: Cylindrical coal samples were prepared and conventional triaxial compression tests were conducted under different confining pressures. The axial pressure at the residual stage after the coal sample failed under load was recorded (i.e., the residual stage axial pressure). Scatter plots of axial compression at different confining pressures and residual stages were drawn and linearly fitted to obtain the slope of the fitted line. and intercept ; According to the slope and intercept The residual cohesion is calculated according to the following formula: .

[0073] It should be noted that this invention accurately determines the residual strength of coal samples under different confining pressures through conventional triaxial mechanical tests. Based on the residual stage axial pressure obtained from the tests and the set confining pressure, the slope and intercept are obtained according to a linear fitting relationship. The residual cohesion is then determined according to a quantitative formula. This parameter The residual shear capacity of the coal seam after failure was quantitatively characterized. During the evolution of coal and gas outburst disasters, the coal seam does not completely lose its bearing capacity after peak failure; its residual cohesion directly affects the expansion range of the outburst cavity and the stability of the surrounding rock of the roadway. The c determined by the experiment... t Introducing this value into the nozzle level determination model can effectively correct the shortcomings of traditional methods in not considering the mechanical behavior of coal after failure, making the prediction results more in line with actual working conditions, and providing key parameter support for the accurate early warning and scientific formulation of prevention and control measures for coal mine dynamic disasters.

[0074] Specifically, in a conventional triaxial compression test, at least three parallel coal samples are used in each confining pressure test, for example, three to five. The axial pressure of each parallel coal sample at the point of failure and subsequent residual stage is recorded. arithmetic mean As Furthermore, if the residual stage axial compression of a certain coal sample... Compared with the average If the deviation exceeds ±15%, it is considered invalid data, and additional coal samples are prepared for retesting until the number of valid coal samples is no less than 3.

[0075] Preferably, the cohesion and internal friction angle The methods for determining this include: Prepare cylindrical coal samples and conduct conventional triaxial compression tests. Record the axial pressure (i.e., failure axial pressure) at which the coal sample fails under each confining pressure. Scatter plots were drawn for different confining pressures and failure axial compressions, and linear fitting was performed to obtain the slope of the fitted line. and intercept ; Cohesion is calculated using the following formula. and internal friction angle : .

[0076] Specifically, in a conventional triaxial compression test, at least three parallel coal samples are used in each confining pressure test, for example, three to five. The axial pressure at failure of each parallel coal sample is recorded. arithmetic mean As Furthermore, if the axial compression at the time of failure of a certain coal sample... Compared with the average If the deviation exceeds ±15%, it is considered invalid data, and additional coal samples are prepared for retesting until the number of valid coal samples is no less than 3.

[0077] Preferably, the cohesive softening modulus The method for determining it includes the following steps: Stress-strain curves were obtained by performing conventional triaxial compression tests on a set of coal samples under a certain confining pressure to obtain the plastic strain at the point of failure of the coal samples. and plastic strain during the residual stage of loading ; binding cohesion With residual cohesion The cohesive softening modulus is calculated using the following formula: .

[0078] It should be noted that this invention obtains the stress-strain curves of coal samples through conventional triaxial compression tests. Based on the plastic strain at the point of failure and the plastic strain at the residual stage obtained from the tests, combined with cohesion and residual cohesion, the cohesion softening modulus is determined according to a quantitative formula. This parameter quantitatively characterizes the rate of mechanical property degradation of coal from peak strength to residual strength. In the evolution of coal and gas outburst disasters, the softening behavior of coal from peak failure to the residual stage directly affects the release intensity of outburst energy and the rate of pore expansion. Introducing the experimentally determined cohesion softening modulus into the nozzle grade determination model can more realistically reflect the gradual degradation process of coal after failure, overcoming the limitations of traditional methods that treat coal as an ideal elastic-plastic material and ignore strain softening characteristics. This significantly improves the predictive model's ability to characterize the dynamic evolution of coal and gas outbursts, thus providing a more reliable parameter basis for accurate early warning and prevention design of coal mine dynamic disasters.

[0079] Preferably, the confining pressure is 10~20MPa, for example 12MPa, 14MPa, 16MPa, or 18MPa.

[0080] Specifically, in a conventional triaxial compression test, at least three parallel coal samples are used in each confining pressure test, for example, three to five. The plastic strain of each parallel coal sample at failure is recorded. arithmetic mean As ; Take the plastic strain of each parallel coal sample when loaded to the residual stage arithmetic mean As Furthermore, if the plastic strain of a coal sample at failure under load... Compared with the average The deviation exceeds ±15%, or if the plastic strain of a coal sample is increased to the residual stage. Compared with the average If the deviation exceeds ±15%, it is considered invalid data, and additional coal samples are prepared for retesting until the number of valid coal samples is no less than 3.

[0081] Preferably, in the conventional triaxial compression test, the confining pressure is set to at least four different gradients within the range of 5-40 MPa, and the difference between adjacent confining pressures is not less than 3 MPa.

[0082] In some embodiments, during conventional triaxial compression tests, the difference between adjacent confining pressures is 5-10 MPa, with a gradient of 4-6. For example, the confining pressures σ3=σ2 of the five groups are set to 5 MPa, 10 MPa, 15 MPa, 20 MPa, and 30 MPa, respectively.

[0083] Preferably, in the conventional triaxial compression test, the loading rate of the applied axial pressure is 0.0001-0.0005 mm / min.

[0084] For example, the loading rate of the applied axial pressure is 0.0001 mm / min, 0.0002 mm / min, 0.0003 mm / min, 0.0004 mm / min, or 0.0005 mm / min; more preferably, it is 0.0001 to 0.0002 mm / min.

[0085] It is understood that the diameter × height of the cylindrical coal sample is (40~60) mm × (40~60) mm.

[0086] Specifically, the non-parallelism of the two end faces of the cylindrical coal sample is ≤0.1mm, and the non-perpendicularity between the end face and the central axis of the cylinder is ≤0.1mm.

[0087] Specifically, the shear modulus The determination method includes the following steps: preparing a cylindrical coal sample, conducting a uniaxial compression test, and determining the elastic modulus E and Poisson's ratio of the coal sample. Calculate the shear modulus according to the following formula. : .

[0088] Specifically, in a uniaxial compression test, the number of parallel coal samples should be at least three, for example, three to five. The arithmetic mean of the shear moduli of each parallel coal sample is taken as the shear modulus. .

[0089] Specifically, the initial vertical stress With initial minimum horizontal stress The stress in the original rock is determined by hydraulic fracturing. For example, the hydraulic fracturing test is performed according to the "Standard for Testing Ground Stress in Coal Mines" GB / T5886-2017.

[0090] Specifically, the borehole gas emission benchmark value W0 is defined as the borehole gas emission per unit time under normal drilling conditions in the mining area, when the borehole radius is R1.

[0091] It is understandable that the coal seam gas content W z It consists of four parts:

[0092] in, This refers to the amount of gas lost (gas that escapes during drilling and sampling). This refers to the actual measured analytical quantity underground (analyzed methane quantity measured on-site). This refers to the amount of gas released after crushing (the amount of gas released after crushing in the laboratory). This refers to the residual gas quantity (the final amount of gas remaining).

[0093] During normal drilling and perforation, the gas gushing out of the borehole is mainly composed of... and The sum is: .

[0094] For example, coal samples collected on-site are sealed and sent to a laboratory, and the amount of gas lost during drilling and sampling is calculated by back-calculating the desorption curve. .

[0095] For example, during normal drilling in a mining area, a representative borehole is selected. Under the condition of a borehole radius of R1, the amount of gas gushing out of the borehole per unit time is measured on-site using a gas desorption instrument or a gas flow meter to obtain the measured underground analytical volume. .

[0096] Preferably, at least three boreholes are selected for repeated measurements, and the arithmetic mean is taken as the W0 benchmark value under normal drilling conditions in the mining area to eliminate random errors from a single measurement.

[0097] The present invention also provides a borehole gas eruption early warning device for performing the borehole gas eruption early warning method, comprising: The model building module is used to execute the model building step in the borehole gas eruption early warning method to build the eruption intensity classification model; The data acquisition module is used to execute the data acquisition steps in the borehole gas eruption early warning method to obtain time-series data of gas emission volume; The classification and determination module is used to execute the classification and determination step in the borehole gas eruption early warning method, so as to compare the gas emission time series data with the eruption intensity classification model point by point, and determine the current eruption intensity level according to the classification threshold range into which the collected gas emission per unit time falls. The early warning response module is used to execute the early warning response step in the borehole gas eruption early warning method, so as to input the current eruption intensity level into the pre-built eruption early warning response model, and execute the early warning according to the early warning response strategy output by the eruption early warning response model.

[0098] Specifically, the model construction module includes: a storage unit for the influence coefficient t of the plastic zone radius; a storage unit for the influence coefficient g of the damage zone radius; a storage unit for the reference value W0 of gas emission; and a threshold interval calculation unit, used to calculate multiple graded threshold intervals based on t, g, and W0.

[0099] Specifically, the data acquisition module includes: The gas emission monitoring unit is installed in the exhaust channel of the blowout preventer body; The time-series data generation unit is used to generate time-series data by arranging the gas emission volume per unit time continuously collected by the gas emission volume monitoring unit at fixed time intervals in chronological order. For example, the gas emission volume monitoring unit is located between the solid-liquid-gas separation box and the extraction pipe of the blowout preventer body, or is located on the extraction pipe.

[0100] Preferably, the data acquisition module further includes an outlier removal unit, used to identify and remove outliers from the time-series data of gas outflow.

[0101] Specifically, the grading determination module includes: The real-time comparison unit is used to compare the gas emission per unit time at the time of collection with the threshold intervals of each level. The grade output unit is used to output the nozzle intensity grade corresponding to the threshold range in which the gas emission per unit time falls.

[0102] Preferably, the grading determination module further includes: a nozzle event recording unit, which is used to record the nozzle occurrence time, nozzle intensity level, and nozzle duration.

[0103] Furthermore, the nozzle event recording unit is connected to a nozzle event database storage unit for storing recorded nozzle event data.

[0104] Specifically, the early warning response module includes: The warning signal output unit is used to output a warning signal of the corresponding level according to the current nozzle intensity level; The linkage control command output unit is used to output linkage control commands at high nozzle levels.

[0105] Furthermore, the linkage control command output unit includes: The drilling rig power cut-off signal output terminal is used to connect to the drilling rig power control circuit; The blowout preventer's lockout signal output terminal is used to connect to the lockout mechanism of the blowout preventer body.

[0106] For example, the lockout signal output terminal of the blowout preventer includes: Hydraulic slip clamping device drive signal output terminal; Electric control valve drive signal output terminal; Mechanical anti-backflow device drives the signal output terminal.

[0107] In some embodiments, the warning device further includes: The display unit, connected to the grading determination module, is used to display the current nozzle intensity level in real time; An alarm unit, connected to the early warning response module, is used to issue audible and visual alarm signals.

[0108] Furthermore, the model building module, data acquisition module, hierarchical judgment module, and early warning response module are integrated into the same data terminal server.

[0109] For example, the data acquisition module (specifically the time-series data generation unit) is connected to the gas emission data output device 5 on the blowout preventer body via wired or wireless communication.

[0110] In some embodiments, the warning device further includes a blowout preventer body, the blowout preventer body comprising: Solid-liquid-gas separator 1; Guide pipe 2, one end of guide pipe 2 is connected to the borehole opening, and the other end of guide pipe 2 is connected to the inlet of solid-liquid-gas separation box 1; Extraction pipe 3, one end of extraction pipe 3 is connected to the gas outlet of solid-liquid-gas separator 1, and the other end of extraction pipe 3 is connected to the mine gas extraction system. Coal outlet 4 is located at the bottom or side of solid-liquid-gas separator 1. A gas emission data output device 5 is disposed between the solid-liquid-gas separator 1 and the extraction pipe 3 or on the extraction pipe 3. For example, the signal output terminal of the gas emission monitoring unit is connected to the gas emission data output device 5.

[0111] It is understood that the exhaust channel is formed by connecting the gas outlet of the solid-liquid-gas separation box 1 to the extraction pipe 3. The solid-liquid-gas separation box is used to receive the mixture of gas, coal dust and water that emerges during the drilling process, and to separate the solid, liquid and gas phases; the guide pipe is used to guide the mixture emerging from the borehole to the solid-liquid-gas separation box; the extraction pipe is used to extract the separated gas into the extraction pipeline network; and the coal outlet trough is used to discharge the separated coal dust and coal slime.

[0112] The technical solution of the present invention will be further described in detail below with reference to specific embodiments.

[0113] Example 1-1: This embodiment provides a method for early warning of gas eruptions from boreholes, including the following steps: S1: Model Building S11. Obtain the basic mechanical parameters and geostress parameters of the coal body, wherein the basic mechanical parameters include: the cohesion c of the coal body, the residual cohesion... internal friction angle Cohesive softening modulus The shear modulus G and the influence coefficient b of the intermediate principal stress for coal body failure; the geostress parameters include: initial vertical stress σ 10 Initial minimum horizontal stress ; (a) Cohesion c and internal friction angle Determination: Fifteen cylindrical coal samples were prepared (refer to GB / T 50266-2013). The diameter of the cylindrical coal sample was 50 mm ± 2 mm, the height was 50 mm ± 2 mm, the non-parallelism of the two end faces was ≤ 0.1 mm, and the non-perpendicularity of the end faces to the central axis of the cylinder was ≤ 0.1 mm. The 15 coal samples were randomly divided into 5 groups, with 3 parallel coal samples in each group. Conventional triaxial compression tests were performed on each group of coal samples using a rock mechanics testing machine. The confining pressure of the 5 groups was... = The pressure was set to 5 MPa, 10 MPa, 15 MPa, 20 MPa, and 30 MPa respectively; after the preset confining pressure was applied, axial pressure was applied at a loading rate of 0.0001 mm / min. Record the axial pressure at the time of failure of each coal sample group. Take three parallel coal samples from each group. mean ; Plot the relationship between different confining pressures σ3 and The scatter plot is then fitted with a linear model to obtain the slope of the fitted line. =3.2 and intercept =20.0; calculate cohesion according to the following formula. With internal friction angle : ; The internal friction angle was calculated. =32.0°, cohesion c=5.54MPa.

[0114] (b) Residual cohesion With cohesive softening modulus Determination: Record the axial pressure of the 5 groups of cylindrical coal samples in (a) above when they entered the residual stage of loading failure. Take three parallel coal samples from each group. mean ; Plot the relationship between different confining pressures σ3 and The scatter plot is then fitted with a linear model to obtain the slope of the fitted line. =1.52 and intercept =7.4; Calculate the residual cohesion according to the following formula. : ; The calculated residual cohesion =3.0MPa.

[0115] A set of stress-strain curves for coal samples with a confining pressure of 15 MPa were selected to obtain the plastic strain at the point of failure under loading. and plastic strain during the residual stage of loading Take the average of the three parallel coal samples in this group. =0.016、 =0.021; Calculate the cohesive softening modulus λ according to the following formula: ; Calculate and round to obtain the cohesive softening modulus. =500MPa=0.5GPa.

[0116] (c) Shear modulus Determination: Three cylindrical coal samples were prepared, each with a diameter of 50 mm ± 2 mm and a height of 50 mm ± 2 mm. The non-parallelism between the two end faces was ≤ 0.1 mm, and the non-perpendicularity between the end faces and the central axis of the cylinder was ≤ 0.1 mm. Uniaxial compression tests were performed on the coal samples using a rock mechanics testing machine to determine the elastic modulus E and Poisson's ratio. The average value of the three coal samples was taken as E=8.0 GPa. =0.22; Calculate the shear modulus G according to the following formula: ; The calculated shear modulus G = 3.3 GPa.

[0117] (d) Determination of the influence coefficient b of the intermediate principal stress: Three cuboid coal samples were prepared (refer to GB / T 9966.12—2021), with dimensions of 50 mm × 50 mm × 100 mm. The non-parallelism of the two end faces was ≤0.1 mm, and the non-perpendicularity of adjacent planes was ≤0.1 mm. A true triaxial mechanical testing machine was used, and the minimum confining pressure was set. =10MPa, second confining pressure =20MPa, minimum confining pressure is applied symmetrically in two mutually perpendicular horizontal directions. Second confining pressure Up to the preset value; after the confining pressure stabilizes, maintain... and A constant axial compressive force σ is applied at a loading rate of 0.0001 mm / min. 11 Record the axial pressure at the time of coal sample failure. Take the average of the three coal samples. =60MPa; Calculate the influence coefficient b of the intermediate principal stress according to the following formula: ; The calculation yields b = 0.2.

[0118] (e) Initial vertical stress With initial minimum horizontal stress Determination: According to the "Standard for Testing Ground Stress in Coal Mines" (GB / T 5886-2017), a suitable coal seam was selected, and the in-situ stress was tested using the hydraulic fracturing method to obtain the stress data of the mining area. =10MPa =5.54MPa.

[0119] S12. Based on the unified strength criterion and the roadway excavation model, according to the basic mechanical parameters and in-situ stress parameters of the coal body obtained in step S11, construct the influence coefficient t of the plastic zone radius and the influence coefficient g of the failure zone radius of the coal body around the borehole. Based on the parameters obtained in step S11, the influence coefficient t of the plastic zone radius is calculated according to the following formula:

[0120] The calculated value is t = 1.32; Based on the parameters obtained in step S1, the influence coefficient g of the radius of the damaged zone is calculated according to the following formula:

[0121] =1.4; The calculated value is g = 0.902.

[0122] S13. Obtaining the baseline value W0 for borehole gas emission; During normal drilling in the mining area, three representative boreholes were selected. With a borehole radius R1 = 42.00 mm, a gas desorption instrument was used to measure the gas emission per unit time on-site, obtaining the measured underground gas emission rate W2. Coal samples collected on-site were sealed and sent to the laboratory. The gas loss W1 was inferred from the desorption curve. The average measurement value of the three boreholes was taken, and W0 = W1 + W2 = 0.1 m was calculated. 3 / min.

[0123] S14. Based on the above t, g, and W0, the nozzle intensity grading model is constructed as follows: Mild nozzle threshold range: W0≤W t ≤t 2 ×g 2 ×W0, which is 0.1m 3 / min≤W t ≤0.142m 3 / min; Moderate nozzle threshold range: t 2 ×g 2 ×W0<W t ≤t 2 ×W0, which is 0.142m 3 / min<W t ≤0.174m 3 / min; Severe jet threshold range: t 2 ×W0<W t That is, W t >0.174m 3 / min; Among them, W t This refers to the amount of gas emitted per unit time.

[0124] S2: Data Acquisition A gas emission monitoring unit (located between the solid-liquid-gas separator 1 and the extraction pipe 3) installed in the exhaust channel of the blowout preventer continuously collects the gas emission rate W per unit time at fixed time intervals (e.g., 5 minutes). t Generate time-series data of gas emission volume arranged in chronological order; Outlier removal is performed on the time series data: the mean and standard deviation of gas emission within a preset time window (e.g., 30 min) are calculated. When the gas emission at the current moment deviates from the mean by more than three times the standard deviation, it is identified as an outlier and removed, and replaced by linear interpolation of the preceding and following moments.

[0125] S3: Grading Determination The time-series data of gas emission rate is compared point by point with the nozzle intensity grading model, based on the gas emission rate W per unit time. tThe current nozzle intensity level is determined by the grading threshold range into which it falls: When W t When the nozzle falls within the threshold range for minor nozzles, it is classified as a minor nozzle. When W t When it falls within the threshold range of medium-level nozzles, it is determined to be a medium-level nozzle. When W t When the jet falls within the severe jet threshold range, it is determined to be a severe jet level.

[0126] The point-by-point comparison involves sequentially comparing the gas emission W per unit time at each sampling moment. t By comparing with various threshold ranges (such as the threshold range for mild, moderate, and severe gas eruptions), continuous monitoring and dynamic analysis of gas emission can be achieved.

[0127] Furthermore, nozzle events are recorded based on the changing trends of gas emission time-series data: When the gas emission rate W per unit time t When a small nozzle enters the small nozzle threshold range from below the lower limit of the small nozzle threshold, a small nozzle event is recorded. When the gas emission rate W per unit time t When a nozzle enters the intermediate nozzle threshold range from below the lower limit of the intermediate nozzle threshold, a intermediate nozzle event is recorded. When the gas emission rate W per unit time t When the jet enters the severe jet threshold range from below the lower limit of the severe jet threshold, a severe jet event is recorded. During the same nozzle process, when the gas emission rate W per unit time t When the gas emission rate fluctuates within the same grading threshold range, the number of times that grade of nozzle is recorded is not repeated. When the gas emission rate W per unit time... t When the temperature drops below the lower limit of the mild nozzle threshold range, the nozzle process is considered to have ended, and the nozzle intensity level is stopped being output.

[0128] S4: Early Warning Response The current nozzle intensity level is input into the pre-built nozzle early warning response model, and an early warning is executed according to the pre-established mapping relationship between nozzle intensity level and early warning response strategy; Specifically, the mapping relationship between the nozzle intensity level and the early warning response strategy includes: a mild nozzle intensity level is mapped to a level three early warning response strategy, which is configured to output a level three early warning signal; a moderate nozzle intensity level is mapped to a level two early warning response strategy, which is configured to output a level two early warning signal; and a severe nozzle intensity level is mapped to a level one early warning response strategy, which is configured to output a level one early warning signal and simultaneously output a linkage control command. In this embodiment, the third-level warning signal is a yellow audible and visual warning signal, the second-level warning signal is an orange audible and visual warning signal, and the first-level warning signal is a red audible and visual warning signal accompanied by a rapid buzzing sound; Specifically, the linkage control commands include commands to cut off the drilling rig power and commands to activate the blowout preventer locking mechanism. The command to cut off the drilling rig power is sent to the drilling rig power control circuit to immediately stop drilling operations. The command to activate the blowout preventer locking mechanism is output synchronously with the first-level early warning signal, including: sending a start signal to the hydraulic slip clamping device to drive the slips to radially contract and clamp the drill rod, thereby achieving emergency braking of the drill rod and enhancing the orifice sealing to prevent drill rod ejection and gas leakage; sending a start signal to the electric control valve to open it to its maximum opening to introduce the high-pressure gas and coal powder mixture into the mine gas extraction system to achieve emergency pressure relief, with the duration of the electric control valve opening to its maximum opening being on the order of milliseconds; and sending a start signal to the mechanical anti-backflow device to form a unidirectional flow in the diversion channel to prevent gas and coal powder backflow and ensure the safety of the working area. When the gas emission rate W per unit time t When the temperature drops below the lower limit of the mild blowout threshold range, the warning signal output stops, and the linkage control command remains in execution until manual reset confirmation. Manual reset confirmation includes: after on-site safety inspection confirms safety, releasing the locked state via the manual reset button. The locked state refers to the safety lockout state after a severe blowout triggers the linkage response, with the drilling rig powered off, slips clamped, valves fully open, and anti-backflow activated.

[0129] Examples 1-2 This embodiment provides a borehole gas eruption early warning device, which is used to implement the early warning method described in Embodiment 1-1; the early warning device includes a model building module, a data acquisition module, a classification judgment module, and an early warning response module; The model building module is used to execute the model building steps in the early warning method described in Example 1-1, so as to build the nozzle intensity grading model described in Example 1-1; The data acquisition module is used to execute the data acquisition steps in the early warning method described in Embodiment 1-1 to obtain time-series data of gas emission. Specifically, the data acquisition module includes a gas emission monitoring unit and a time-series data generation unit. The gas emission monitoring unit is installed in the exhaust channel of the blowout preventer body, located between the solid-liquid-gas separator 1 and the extraction pipe 3, or located on the extraction pipe 3, and continuously collects the gas emission per unit time at fixed time intervals. The time-series data generation unit arranges the gas emission per unit time continuously collected by the gas emission monitoring unit at fixed time intervals in chronological order to generate time-series data. The data acquisition module also includes an outlier removal unit, used to identify and remove outliers in the gas emission time-series data. The grading determination module is used to execute the grading determination step in the early warning method described in Embodiment 1-1, to compare the gas emission time series data with the nozzle intensity grading model point by point, and to determine the current nozzle intensity level based on the grading threshold interval into which the collected gas emission per unit time falls; specifically, the grading determination module includes a real-time comparison unit and a level output unit; the real-time comparison unit compares the gas emission per unit time collected at the time of collection with each grading threshold interval; the level output unit outputs the nozzle intensity level corresponding to the threshold interval into which the gas emission per unit time falls; the grading determination module also includes a nozzle event recording unit, used to record the nozzle occurrence time, nozzle intensity level and nozzle duration, and is connected to a nozzle event database storage unit; The early warning response module is used to execute the early warning response steps in the early warning method described in Embodiment 1-1, to input the current nozzle intensity level into a pre-built nozzle early warning response model, and to execute an early warning according to the early warning response strategy output by the nozzle early warning response model; specifically, the early warning response module includes an early warning signal output unit and a linkage control command output unit; the early warning signal output unit outputs an early warning signal of the corresponding level according to the current nozzle intensity level; the linkage control command output unit outputs a linkage control command when the nozzle intensity level is severe; the linkage control command output unit includes a drilling rig power cut-off signal output terminal and a blowout preventer lock-up signal output terminal; the drilling rig power cut-off signal output terminal is used to connect to the drilling rig power control circuit; the blowout preventer lock-up signal output terminal includes a hydraulic slip clamping device drive signal output terminal, an electric control valve drive signal output terminal, and a mechanical anti-backflow device drive signal output terminal; The model building module, data acquisition module, grading judgment module, and early warning response module are integrated into the same data terminal server. The data acquisition module is connected to the gas emission data output device 5 on the blowout prevention device body via wired or wireless communication. The data terminal server is also connected to a display unit and an alarm unit. The display unit is connected to the grading judgment module and is used to display the current blowout intensity level in real time. It is an LCD screen that displays the gas emission monitoring value per unit time, the current blowout intensity level, and the historical blowout count in real time. The alarm unit is connected to the early warning response module and is used to issue audible and visual alarm signals, including yellow, orange, and red three-color indicator lights and a buzzer, corresponding to three early warning levels: mild blowout, moderate blowout, and severe blowout, respectively. The early warning device also includes a blowout preventer body, which is installed at the borehole opening to seal and guide gas and coal dust during drilling. The blowout preventer body includes a solid-liquid-gas separator 1, a guide pipe 2, an extraction pipe 3, a coal outlet trough 4, and a gas emission data output device 5. One end of the guide pipe 2 is connected to the borehole opening, and the other end is connected to the inlet of the solid-liquid-gas separator 1. One end of the extraction pipe 3 is connected to the gas outlet of the solid-liquid-gas separator 1, and the other end is connected to the mine gas extraction system. The coal outlet trough 4 is located at the bottom or side of the solid-liquid-gas separator 1. The gas emission data output device 5 is located between the solid-liquid-gas separation box 1 and the extraction pipe 3, or is located on the extraction pipe 3; the exhaust channel is formed by connecting the gas outlet of the solid-liquid-gas separation box 1 and the extraction pipe 3; the solid-liquid-gas separation box 1 is used to receive the mixture of gas, coal dust and water emitted during drilling and to separate the solid, liquid and gas phases; the guide pipe 2 is used to guide the mixture emitted from the borehole to the solid-liquid-gas separation box 1; the extraction pipe 3 is used to extract the separated gas into the extraction pipeline network; the coal outlet trough 4 is used to discharge the separated coal dust and coal slurry. The blowout preventer body also includes a locking mechanism, which is installed on the blowout preventer body and includes a hydraulic slip clamping device, an electric control valve, and a mechanical anti-backflow device. The hydraulic slip clamping device is installed at the borehole opening, with its slips facing the outer wall of the drill rod. The electric control valve is installed in the drainage channel of the blowout preventer body. The mechanical anti-backflow device is installed in the drainage channel. When the relevant module of the early warning device (including the grading judgment module) determines and outputs a severe blowout level signal, the linkage control command output unit sends a power-off signal to the drilling rig power control circuit to cut off the drilling rig power, sends a start signal to the hydraulic slip clamping device to clamp the drill rod, sends a start signal to the electric control valve to open to the maximum opening, and sends a start signal to the mechanical anti-backflow device to form unidirectional flow. The plastic zone radius influence coefficient t, the failure zone radius influence coefficient g, the gas emission benchmark value W0, and the nozzle intensity classification threshold are all obtained from the parameters and calculation results in the model construction step of the borehole gas nozzle early warning method described in Example 1-1. Using the early warning method described in Example 1-1 and the early warning device described in Example 1-2, the system issued a total of 12 early warnings during the construction of more than 3 boreholes, of which 1 was a false alarm. Examples 1-1 and 1-2 achieved a false alarm rate of ≤8.3% and an accuracy rate of ≥91.7% for borehole gas nozzle parameters and nozzle events (including nozzle intensity level, number of nozzles, nozzle occurrence time, and nozzle duration).

[0130] Example 2-1: This embodiment is the same as embodiment 1-1, except that... =1.3, and g = 0.893 is calculated. t and W0 are the same as in Example 1-1. Based on the aforementioned t, g, and W0, the nozzle intensity grading model is constructed as follows: Mild nozzle threshold range: W0≤W t ≤t 2 ×g 2 ×W0, which is 0.1m 3 / min≤W t ≤0.139m 3 / min; Moderate nozzle threshold range: t 2 ×g 2 ×W0<W t ≤t 2 ×W0, which is 0.139m 3 / min<W t ≤0.174m 3 / min; Severe jet threshold range: t 2 ×W0<W t That is, W t >0.174m 3 / min.

[0131] Example 2-2 This embodiment is the same as Embodiments 1-2, except that the plastic zone radius influence coefficient t, the failure zone radius influence coefficient g, the gas emission benchmark value W0, and the nozzle strength classification model all adopt the parameters and calculation results obtained in the model construction step of the borehole gas nozzle early warning method described in Embodiment 2-1.

[0132] Example 3-1: This embodiment is the same as embodiment 1-1, except that... =1.5, and g = 0.908 is calculated. t and W0 are the same as in Example 1-1. Based on the aforementioned t, g, and W0, the nozzle intensity grading model is constructed as follows: Mild nozzle threshold range: W0≤W t ≤t 2 ×g 2 ×W0, which is 0.1m 3 / min≤W t ≤0.144m 3 / min; Moderate nozzle threshold range: t 2 ×g 2 ×W0<W t ≤t 2 ×W0, which is 0.144m 3 / min<W t ≤0.174m3 / min; Severe jet threshold range: t 2 ×W0<W t That is, W t >0.174m 3 / min.

[0133] Example 3-2 This embodiment is the same as that of Embodiments 1-2, except that the plastic zone radius influence coefficient t, the failure zone radius influence coefficient g, the gas emission benchmark value W0, and the nozzle strength classification model are all obtained from the model construction steps in the borehole gas nozzle early warning method described in Embodiment 3-1.

[0134] The early warning method described in Example 2-1, the early warning device described in Example 2-2, the early warning method described in Example 3-1, and the early warning device described in Example 3-2 were used for drilling verification under the same mining area and geological conditions. The verification results show that although the early warning accuracy for borehole gas eruption parameters and eruption events (including eruption intensity level, number of eruptions, eruption occurrence time, and eruption duration) is slightly lower than that of Examples 1-1 and 1-2, the early warning accuracy for these parameters and events remains above 90%, with a false alarm rate controlled below 10%, significantly better than traditional manual judgment methods.

[0135] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for early warning of gas eruptions from boreholes, characterized in that, Includes the following steps: Model construction: Obtain the basic mechanical parameters and geostress parameters of the coal body, wherein the basic mechanical parameters include: the cohesion c of the coal body and the residual cohesion. internal friction angle Cohesive softening modulus The shear modulus G and the influence coefficient b of the intermediate principal stress for coal body failure; the geostress parameters include: initial vertical stress σ 10 Initial minimum horizontal stress Based on a unified strength criterion and a roadway excavation model, and according to the obtained basic mechanical parameters and geostress parameters of the coal body, the influence coefficients t and g of the radius of the plastic zone and the radius of the failure zone of the coal body surrounding the borehole are constructed. Based on t, g, and the benchmark value W0 of borehole gas emission per unit time during normal drilling in the mining area, a blowout intensity grading model is constructed. The blowout intensity grading model includes multiple grading threshold intervals, and each grading threshold interval corresponds to a blowout intensity level. Data acquisition: Obtain time-series data on gas emission; Classification determination: The time series data of gas emission is compared point by point with the nozzle intensity classification model; the current nozzle intensity level is determined according to the classification threshold range into which the collected gas emission per unit time falls. Warning response: Input the current nozzle intensity level into the pre-built nozzle warning response model.

2. The early warning method according to claim 1, characterized in that, The nozzle early warning response model is pre-built through the following steps: establishing a mapping relationship between nozzle intensity level and early warning response strategy.

3. The early warning method according to claim 2, characterized in that, The mapping relationship between the nozzle intensity level and the early warning response strategy includes: The mild nozzle level is mapped to a three-level early warning response strategy, and the three-level early warning response strategy is configured to output a three-level early warning signal; The medium-level nozzle grade is mapped to a two-level early warning response strategy, and the two-level early warning response strategy is configured to output a two-level early warning signal; The severity of the jetting is mapped to a Level 1 warning response strategy, which is configured to output a Level 1 warning signal and simultaneously output a linkage control command.

4. The early warning method according to claim 1, characterized in that, The acquisition of gas emission time-series data includes: A gas emission monitoring unit installed in the exhaust channel of the blowout preventer continuously collects the gas emission rate W per unit time at fixed time intervals. t Generate time-series data of gas outflow arranged in chronological order.

5. The early warning method according to claim 3, characterized in that, The linkage control commands include commands to cut off the drilling rig power supply and commands to activate the blowout preventer locking mechanism.

6. The early warning method according to claim 5, characterized in that, The command to activate the blowout preventer's locking mechanism includes: Send a start signal to the hydraulic slip clamping device to drive the slips to retract radially and clamp the drill pipe; Send a start signal to the electric control valve to open it to its maximum opening degree to introduce the high-pressure gas and pulverized coal mixture into the mine gas extraction system; A start signal is sent to the mechanical anti-backflow device to form a one-way flow in the diversion channel to prevent backflow of gas and pulverized coal.

7. The early warning method according to claim 1, characterized in that, The nozzle intensity grading model includes a mild nozzle threshold range, a moderate nozzle threshold range, and a severe nozzle threshold range. The threshold range for mild nozzles: W0≤W t ≤t 2 ×g 2 ×W0; The moderate nozzle threshold range: t 2 ×g 2 ×W0<W t ≤t 2 ×W0; The threshold range of the severe jet nozzle: t 2 ×W0<W t ; Among them, W t This refers to the amount of gas emitted per unit time.

8. The early warning method according to claim 1, characterized in that, The influence coefficient t of the plastic zone radius is constructed according to the following formula: 。 9. The early warning method according to claim 1, characterized in that, The influence coefficient g of the radius of the damaged zone is constructed according to the following formula: in, The value range is 1.3 to 1.

5.

10. A borehole gas eruption early warning device, used to execute the early warning method according to any one of claims 1 to 9, characterized in that, include: The model building module is used to build the nozzle intensity grading model; The data acquisition module obtains time-series data on gas emission. The grading determination module compares the gas emission time series data with the nozzle intensity grading model point by point, and determines the current nozzle intensity level based on the grading threshold range into which the collected gas emission per unit time falls. The early warning response module inputs the current nozzle intensity level into a pre-built nozzle early warning response model and executes an early warning based on the early warning response strategy output by the nozzle early warning response model.

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