A real-time monitoring and early warning system for stability of a coal underground gasification combustion void

Abstract

The present application relates to the field of combustion empty area stability monitoring, and relates to a coal underground gasification combustion empty area stability real-time monitoring and early warning system. The present application divides all fracture points in the inner wall of the surrounding rock of the combustion empty area in real time, obtains the real-time area of each risk area, calculates the area diffusion degree in combination with the area change amount of each risk area, determines the stress mutation point, carries out correlation analysis on the stress mutation point and the risk area, obtains the stress influence coefficient, calculates the risk coefficient in combination with the real-time area and the area diffusion degree of each risk area, obtains the stability grade of the gasification combustion empty area in combination with the spatial distribution density characteristic value and the correlation influence characteristic value of the risk coefficient of each risk area, and sends corresponding early warning signals according to different stability grades. Professionals can take differentiated prevention and control measures according to the early warning grades, effectively avoid safety accidents such as combustion empty area collapse, and protect the stability of the surface ecological environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of combustion space stability monitoring, and relates to a coal underground gasification combustion space stability real-time monitoring and early warning system. BACKGROUND

[0002] The combustion space refers to a complex underground space that is consumed, hollowed out and physically and chemically changed after coal is combusted in situ and converted into combustible gas through coal underground gasification technology in the underground coal seam. The existence of the combustion space will destroy the original stress balance of the underground rock mass, and risks such as surrounding rock rupture, deformation and even collapse are prone to occur. Therefore, real-time and accurate monitoring and early warning of the stability of the combustion space is a key requirement for ensuring the safe application of coal underground gasification technology.

[0003] However, the prior art has the following problems: the prior art mainly compares the stress values, displacement or stress mutation data of each point with the preset safety threshold to analyze the stability of the combustion space, without considering analyzing the risk area from the rupture which is the most essential factor affecting stability and analyzing the risk area area diffusion degree, and without analyzing the point-surface-space through the point-surface-space, which is difficult to meet the fine and forward-looking requirements of risk prediction in coal underground gasification engineering.

[0004] Even if the stress mutation is calculated, the prior art does not consider classifying the stress mutation points and analyzing the risk area with the existing risks, which deviates from the actual situation of the risk area actual safety state, and further reduces the reliability of the subsequent stability evaluation results. SUMMARY

[0005] In order to overcome the shortcomings of the prior art, the present application provides a coal underground gasification combustion space stability real-time monitoring and early warning system.

[0006] In order to achieve the above-mentioned purpose, the present application adopts the following technical solution: a coal underground gasification combustion space stability real-time monitoring and early warning system, comprising: a rupture point monitoring module, a risk area analysis module, a risk coefficient calculation module, a risk correlation analysis module, and a monitoring and early warning module. The connection relationship between the modules is: the rupture point monitoring module is connected with the risk area analysis module, the risk coefficient calculation module is connected with the risk area analysis module and the risk correlation analysis module, and the monitoring and early warning module is connected with the risk correlation analysis module.

[0007] The rupture point monitoring module: uniformly arranging a sensor group in the inner wall of the combustion space surrounding rock, receiving the seismic wave in the continuous time through the sensor group, and locating all the rupture point positions.

[0008] Risk area analysis module: the real-time area of each risk area is obtained by dividing adjacent fracture points, and the area diffusion degree is calculated by tracking the area change of each risk area.

[0009] Risk coefficient calculation module: stress mutation points are determined by real-time acquisition of stress data of the inner wall of surrounding rock, and the risk coefficient is calculated by combining the real-time area and the area diffusion degree of each risk area through the correlation analysis of the stress mutation points and the risk area.

[0010] Risk correlation analysis module: according to the spatial position of each risk area of the inner wall of the surrounding rock of the combustion air area, the spatial distribution density characteristic value and the correlation influence characteristic value of the combustion air area are obtained.

[0011] Monitoring and early warning module: the stability level of the combustion air area is analyzed by combining the risk coefficient of each risk area with the spatial distribution density characteristic value and the correlation influence characteristic value, and the corresponding early warning signal is sent according to different stability levels.

[0012] Compared with the prior art, the present application has the following beneficial effects: (1) the present application obtains the real-time area of each risk area by dividing adjacent fracture points, and calculates the area diffusion degree by tracking the area change of each risk area, which realizes the conversion of discrete fracture point monitoring into continuous and quantifiable risk area dynamic evaluation, and provides a data basis for subsequent analysis of the risk coefficient of the risk area.

[0013] (2) the present application determines stress mutation points by real-time acquisition of stress data of the inner wall of surrounding rock, and calculates the risk coefficient by combining the real-time area and the area diffusion degree of each risk area through the correlation analysis of the stress mutation points and the risk area, which considers the potential influence of the stress mutation points outside the area on the risk area, and improves the scientificity and pertinence of risk judgment.

[0014] (3) the present application obtains the spatial distribution density characteristic value and the correlation influence characteristic value of the combustion air area according to the spatial position of each risk area of the inner wall of the surrounding rock of the combustion air area, which considers the overall distribution of the risk area and the linkage influence between the risk areas, captures the potential correlation between risks, avoids sudden accidents caused by ignoring the coupling effect between areas, and provides core technical support for long-term safe and stable operation of the combustion air area.

[0015] (4) the present application analyzes the stability level of the combustion air area by combining the risk coefficient of each risk area with the spatial distribution density characteristic value and the correlation influence characteristic value, and sends the corresponding early warning signal according to different stability levels, which realizes comprehensive evaluation of the stability of the combustion air area, avoids resource waste caused by indiscriminate early warning, and improves the early warning efficiency. DETAILED DESCRIPTION

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description only some of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0017] Figure 1 The system module connection diagram of the present application.

[0018] Figure 2 The acquisition method flow diagram of the real-time area of each risk area in the present application.

[0019] Figure 3 The specific step flow diagram of the risk coefficient calculation module in the present application. DETAILED DESCRIPTION

[0020] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. Note that the relative arrangement, numerical expressions, and values of the components and steps set forth in these embodiments are not limiting to the scope of the present application unless otherwise specifically stated. At the same time, it should be understood that the sizes of the various parts shown in the drawings are not drawn in accordance with the actual proportional relationship for the convenience of description.

[0021] The following description of at least one example embodiment is merely illustrative in nature and is in no way limiting to the scope of the application and its applications or uses. Techniques, methods, and devices known to those of ordinary skill in the relevant art can not be discussed in detail, but should be considered part of the specification where appropriate.

[0022] In all examples shown and discussed herein, any specific values should be interpreted as merely illustrative, and not as a limitation. Thus, other examples of the example embodiments can have different values.

[0023] The present application obtains the real-time area of each risk area by dividing the adjacent fracture points of all fracture points in the surrounding rock of the combustion air zone, and calculates the area diffusion degree by tracking the area change of each risk area. By determining the stress mutation point, the stress mutation point is associated with the risk area for analysis to obtain the stress influence coefficient, and the risk coefficient is calculated by combining the real-time area and the area diffusion degree of each risk area. The risk coefficient of each risk area is combined with the spatial distribution density characteristic value and the associated influence characteristic value to obtain the stability grade of the gasification combustion air zone, and the corresponding warning signal is sent according to different stability grades. Professionals can take differentiated prevention and control measures according to the warning level to effectively avoid safety accidents such as combustion air zone collapse and protect the stability of the surface ecological environment.

[0024] Please refer to Figure 1As shown, the present application provides a coal underground gasification combustion empty area stability real-time monitoring and early warning system, comprising: a rupture point monitoring module, a risk area analysis module, a risk coefficient calculation module, a risk correlation analysis module, a monitoring and early warning module. The connection relationship between the modules is: the rupture point monitoring module is connected with the risk area analysis module, the risk coefficient calculation module is connected with the risk area analysis module and the risk correlation analysis module respectively, and the monitoring and early warning module is connected with the risk correlation analysis module.

[0025] The rupture point monitoring module: uniformly arrange a sensor group in the inner wall of the surrounding rock of the combustion empty area, receive the seismic wave in continuous time through the sensor group, and locate all the rupture point positions.

[0026] Considering that the rupture of the surrounding rock of the combustion empty area is essentially the process that the stored elastic potential energy is quickly released after the stress inside the rock mass exceeds its strength threshold, and this process will excite microseismic waves, the seismic wave is a real-time signal directly reflecting the rupture behavior, and the occurrence and position of the rupture can be traced back by capturing this signal. Considering that the rupture point is difficult to monitor in real time by naked eye observation or surface detection, therefore, microseismic sensors can be arranged in all planar surrounding rock areas of the combustion empty area to receive seismic waves to trace back the rupture point position.

[0027] Considering that the propagation speed of the longitudinal wave is faster than that of the transverse wave when the seismic wave propagates in the rock medium, therefore, the longitudinal wave signal first arrives at the microseismic sensor, so the present application analyzes the arrival time of the longitudinal wave of the microseismic wave.

[0028] Based on this, in one specific example of the present application, the specific content of the rupture point monitoring module includes: first, uniformly grid dividing all planar surrounding rock areas of the combustion empty area, taking each grid intersection as a monitoring point, and arranging a sensor group containing a microseismic sensor and a stress sensor on each monitoring point.

[0029] Secondly, recording the waveform signals appearing in continuous time from the microseismic sensor of each monitoring point.

[0030] Then, comparing the waveform shape features and the main frequencies in the waveform signals of each monitoring point with each other, taking the waveform signals with consistent waveform shape features and similar main frequencies as the same rupture point waveform signal, counting all the monitoring points same as each rupture point waveform signal, extracting the initial time of the longitudinal wave from the waveform signals of each monitoring point corresponding to each rupture point, grouping each monitoring point corresponding to each rupture point two by two to obtain each group of monitoring points, and calculating the initial time difference of the longitudinal wave corresponding to each group of monitoring points.

[0031] Wherein in a preferred example of the application, the waveform shape features include peak value and rising edge slope; the waveform signals with the same peak value and the same rising edge slope are recorded as the waveform shape features being consistent, and the waveform signals with the main frequency difference less than the set deviation threshold are recorded as the main frequency being similar.

[0032] Then, the distance difference of each group of monitoring points is calculated according to the difference between the first arrival time of the longitudinal wave of each group of monitoring points corresponding to each fracture point and the longitudinal wave velocity under the surrounding rock medium.

[0033] Wherein the propagation velocity of the longitudinal wave in the test surrounding rock can be calibrated by experiment, and the ultrasonic detector is used to emit ultrasonic longitudinal wave to the test surrounding rock.

[0034] Finally, the specific position of each fracture point is output by substituting the distance difference of each group of monitoring points of each fracture point and the position of each group of monitoring points into the Euclidean distance difference calculation formula.

[0035] The Euclidean distance difference calculation formula is: .

[0036] Wherein X, Y and Z coordinates of the specific position of the fracture point to be solved, And X, Y and Z coordinates of the position of two sensors, The distance difference between the fracture point and the position of two sensors.

[0037] Wherein The Euclidean distance between the fracture point to be solved and one of the sensors, The Euclidean distance between the fracture point to be solved and the other sensor.

[0038] The application can locate the positions of all fracture points by uniformly arranging sensor groups in the inner wall of the surrounding rock of the combustion air area, receiving seismic waves in continuous time through the sensor groups, and providing a basis for subsequent analysis of risk areas and reliable data anchor points for subsequent all risk analysis links, so as to ensure that the analysis results of the whole monitoring and early warning system are real and effective.

[0039] The risk area analysis module: the real-time area of each risk area is obtained by dividing adjacent fracture points, and the area diffusion degree is calculated by tracking the area change amount of each risk area.

[0040] Considering that the risk hidden danger of the combustion air area is directly related to the size of the fracture area, the larger the risk area is, the wider the surrounding rock fracture range is, the more serious the damage to the integrity of the rock mass structure is, and the larger the probability and influence range of subsequent deformation and collapse are. If the risk is only judged by the number of fracture points, the actual coverage range of the fracture area cannot be accurately reflected.

[0041] Based on this, as shown in the figure, the method for obtaining the area of each risk area is: W1, calculate the Euclidean distance between each fracture point and other fracture points, record two points with a distance less than a set distance threshold as adjacent points, take a fracture point as an initial fracture point, and include its adjacent points in the initial fracture point cluster. Figure 2

[0042] The set distance threshold is used to define the adjacent range of the fracture point, and in the present application, the value is 0.2 m, and the implementer can set other specific values.

[0043] W2, sequentially include the adjacent points of other fracture points in the initial fracture point cluster into the initial fracture point cluster until all adjacent points of the fracture points in the initial fracture point cluster are in the corresponding cluster.

[0044] W3, count all fracture point clusters, and record the minimum circumscribed polygon containing all points in each fracture point cluster as each risk area.

[0045] W4, calculate the product of the number of grids covered by each risk area and the area of a single grid to calculate the real-time area of each risk area.

[0046] Considering that the fracture of the surrounding rock of the combustion cavity has a dynamic evolution characteristic, the risk area does not exist statically, and the area diffusion degree directly reflects the development trend of the surrounding rock instability; at the same time, the area diffusion degree of the risk area is positively correlated with the stability risk of the combustion cavity, and the higher the area diffusion degree, the faster the propagation rate of the rock mass fracture, the higher the degree of stress imbalance, and the probability and harm range of subsequent induced surrounding rock collapse and deformation are also increased.

[0047] Therefore, the dynamic diffusion process of the risk area needs to be quantified as a specific index by calculating the area diffusion degree, so as to ensure that the evaluation of the risk of the combustion cavity conforms to the actual evolution law and avoids the lagging warning or misjudgment caused by ignoring the diffusion trend.

[0048] Based on this, the method for calculating the area diffusion degree of the risk area is: monitoring the area of each risk area after a set time period, calculating the difference between the area of each risk area after the set time period and the real-time area, and recording the ratio of the difference to the real-time area as the area diffusion degree.

[0049] The present application obtains the real-time area of each risk area by dividing the adjacent fracture points, calculates the area diffusion degree by tracking the area change of each risk area, realizes the conversion of discrete fracture point monitoring into continuous and quantifiable risk area dynamic evaluation, and provides a data basis for subsequent analysis of the risk coefficient of the risk area.

[0050] ​Risk coefficient calculation module: By collecting stress data of the inner wall of the surrounding rock in real time, the stress mutation point is determined, the stress mutation point is correlated with the risk area, and the risk coefficient is calculated by combining the real-time area and area diffusion of each risk area.

[0051] Given that changes in surrounding rock stress are an intrinsic cause of risk, and that sudden stress changes are a direct precursor to accelerated rock fracturing or even collapse, neglecting to consider sudden stress changes may lead to the overlooking of the collapse precursors they cause.

[0052] Based on this, such as Figure 3 As shown, the specific contents of the risk coefficient calculation module include: S1, extracting recent historical stress data for a set period from the historical stress data monitored by the stress sensors corresponding to each monitoring point, constructing a recent stress time series, comparing the stress at adjacent time points in the recent stress time series to obtain the stress change, and forming a recent stress change sequence based on the stress change.

[0053] S2. Based on the stress data of each monitoring point monitored in real time by the stress sensor, calculate the current stress change of each monitoring point, and analyze whether there is a stress mutation by combining the recent stress change sequence of each monitoring point. The monitoring point with stress mutation is taken as the stress mutation point.

[0054] In a preferred embodiment of the present invention, the method for determining the stress abrupt change point includes: firstly, calculating the recent standard deviation and recent average value of all stress changes in the recent stress change sequence of each monitoring point.

[0055] Secondly, a corresponding deviation threshold is set based on the recent standard deviation of the recent stress change sequence at each monitoring point. In this invention, the deviation threshold is based on... The principle is to use three times the recent standard deviation as the deviation threshold.

[0056] Finally, when the deviation between the current stress change at a certain monitoring point and the recent average value is greater than the corresponding deviation threshold, it is determined that there is a stress mutation at the monitoring point, and the monitoring point is recorded as a stress mutation point.

[0057] S3. Analyze the positional relationship between each stress mutation point and each risk area, and obtain the stress influence coefficient based on the positional relationship analysis.

[0058] Considering that stress abrupt changes are a direct manifestation of the imbalance in the mechanical equilibrium of the surrounding rock in the combustion zone, and that the impact of stress abrupt change points on the risk area is related to the number and spatial distance of these points, the more stress abrupt change points there are around the same risk area, the wider the area is affected by mechanical anomalies. Simultaneously, the closer the abrupt change point is to the risk area, the easier it is for the stress disturbance it induces to be transmitted to the risk area, accelerating the spread of the risk or rock mass instability. Therefore, the stress influence coefficient is an important indicator for analyzing risk levels.

[0059] Based on this, the calculation method of the stress influence coefficient includes: first, comparing the position of each stress mutation point with all risk areas, recording the stress mutation points in the risk area as internal mutation points, and counting the number of internal mutation points in each risk area.

[0060] Second, record the mutation points outside all risk areas as external mutation points, associate each external mutation point with the risk area with the shortest straight-line distance, and record the distance as the associated distance. The straight-line distance refers to the shortest distance from the external mutation point to the boundary of the risk area.

[0061] Then count the number of external mutation points associated with each risk area and the associated distance corresponding to each external mutation point.

[0062] Then record the ratio of the number of internal mutation points and the number of external mutation points in each risk area to the total number of stress mutation points in the combustion and empty area as the internal mutation point number ratio and the external mutation point number ratio.

[0063] Finally, the internal mutation point number ratio, the external mutation point number ratio, and the associated distance corresponding to the external mutation point are comprehensively analyzed to obtain the stress influence coefficient.

[0064] The calculation formula of the stress influence coefficient is as follows: .

[0065] Wherein, represents the stress influence coefficient, represents the internal mutation point number ratio, represents the external mutation point number ratio, represents the number of external mutation points, represents the number of each external mutation point, represents the associated distance corresponding to the th external mutation point, represents the maximum boundary distance of the plane where the risk area is located, , wherein respectively represent the weights corresponding to the internal mutation point and the external mutation point, and .

[0066] Among them, from the essence of rock mechanics, the influence of internal mutation points on risk areas is the most direct and intense, so the weight setting needs to meet The specific value can be determined by inviting experts to analyze the stability of the combustion and empty area, asking experts to submit their own weight settings, and calculating the mean value of the results through statistical analysis.

[0067] Wherein The impact term caused by the external stress mutation point is coupled with the correlation distance through the product of the external mutation point number ratio and the correlation distance expression, and the influence of the external stress mutation point on the risk area is based on the combined action of the quantity scale and the distance decay efficiency, The correlation distance expression is represented by the stress influence coefficient and the correlation distance, and the stress influence coefficient is inversely proportional to the correlation distance. The average value of the normalized correlation distance of each risk area is represented by adding 1 to the denominator to avoid zero.

[0068] S4, the risk coefficient of each risk area is obtained by comprehensively calculating the area of each risk area, the area diffusion degree and the stress influence coefficient.

[0069] Preferably, the area ratio of each risk area is obtained by ratio analysis of the risk area and the overall area of the surrounding rock inner wall of the combustion air zone, and the risk coefficient of each risk area is obtained by weighted summation of the area ratio, the area diffusion degree and the stress influence coefficient of each risk area.

[0070] The specific weights of the area ratio, the area diffusion degree and the stress influence coefficient can be extracted from the collapse history data of similar combustion air zones, and the area ratio, the diffusion degree, the stress influence coefficient and the corresponding risk coefficient are used as independent variables, and the risk coefficient is used as dependent variable, a multiple linear regression model is constructed for quantitative analysis, and the regression coefficients and constant terms of the area ratio, the diffusion degree and the stress influence coefficient are fitted, and the regression coefficients of the area ratio, the diffusion degree and the stress influence coefficient are normalized and added to 1, and the regression coefficients of the area ratio, the diffusion degree and the stress influence coefficient after normalization are used as the weights of each risk area.

[0071] The stress mutation point is determined by real-time acquisition of the stress data of the surrounding rock inner wall, the stress mutation point is associated with the risk area, the risk coefficient is calculated by combining the real-time area and the area diffusion degree of each risk area, and the potential influence of the external stress mutation point on the risk area is considered, thereby improving the scientificity and pertinence of risk judgment.

[0072] The risk correlation analysis module: according to the spatial position of each risk area of the surrounding rock inner wall of the combustion air zone, the spatial distribution density characteristic value and the correlation influence characteristic value of the combustion air zone are obtained.

[0073] Considering that the stability of the combustion air zone is not determined by the size of a single risk area, the spatial distribution of the risk area also significantly affects the overall structural stability. For example, when multiple risk areas are densely distributed, a through-breaking channel is easily formed, which greatly reduces the bearing capacity of the surrounding rock. The threat of scattered risk areas to the overall stability is relatively controllable. Therefore, by quantifying the spatial distribution characteristics of the risk area, the distribution density characteristic value can be obtained to supplement the evaluation dimension.

[0074] Based on this, the method for obtaining the spatial distribution density characteristic value comprises the following steps: determining all risk areas in each planar surrounding rock area according to the spatial positions of the risk areas in the inner wall of the surrounding rock of the combustion air zone, analyzing the ratio of the average distance between the geometric centers of all risk areas in each planar surrounding rock area to the maximum boundary distance of the corresponding planar area, and taking the ratio as the dispersion degree of each planar surrounding rock area.

[0075] The ratio of the sum of the areas of the risk areas in each planar surrounding rock area to the total area of the corresponding planar surrounding rock area is taken as the area coverage degree.

[0076] Considering that the larger the numerical value of the area coverage degree is, the more the risk area of each planar surrounding rock area covers the area, and the greater the distribution density is, the distribution density is proportional to the area coverage degree. Considering that the smaller the numerical value of the dispersion degree is, the closer the geometric centers of the risk areas in each planar surrounding rock area are, the more closely the risk areas are distributed, and the greater the distribution density is, the distribution density is inversely proportional to the dispersion degree. The ratio analysis of the two can accurately map the corresponding relationship between the planar risk level and the actual instability probability, and accurately reflect the synergistic effect of the risk space occupation and the aggregation effect.

[0077] Based on this, the ratio of the area coverage degree to the dispersion degree of each planar surrounding rock area is taken as the distribution density.

[0078] The distribution densities of all planar surrounding rock areas are weighted and summed to obtain the spatial distribution density characteristic value of the combustion air zone as a whole.

[0079] Considering that the distribution densities of the top surrounding rock, the bottom surrounding rock and the surrounding rock around the combustion air zone have different effects on the stability of the combustion air zone, different weights are set to reflect the overall density characteristics of the combustion air zone.

[0080] Considering that the surrounding rock around the combustion air zone plays a supporting role and its collapse has the highest impact on the overall stability, the weight corresponding to the surrounding rock around the combustion air zone should be the highest. The bottom surrounding rock has the lowest impact on the overall stability, so the weight corresponding to the bottom surrounding rock should be the lowest. The specific weight value can be set by the implementer, but the sum of the weights of all planes is 1.

[0081] Considering that the risk areas in the same plane are close to each other and may have a correlation impact, the fracture expansion of one area may conduct stress disturbance to the surrounding areas, accelerate the instability of adjacent risk areas, and thus increase the safety hazard of the overall structure of the combustion and empty area, thereby affecting the overall stability of the combustion and empty area, and ignoring the correlation impact may cause the subsequent risk value calculation to be low, and affect the judgment result of the overall stability of the combustion and empty area.

[0082] Therefore, the method for obtaining the correlation impact characteristic value comprises the following steps.

[0083] When other risk areas corresponding to the boundary shortest straight line distance of each risk area are less than the set boundary distance threshold, the correlation combination is performed to obtain the region correlation group.

[0084] The region boundary distance threshold can be obtained by extracting the collapse range of adjacent risk areas caused by each collapse risk area from the historical collapse events of the combustion and empty area, and taking the average of all the collapse ranges of the adjacent risk areas as the region boundary distance threshold.

[0085] Considering that the collapse risk of the combustion and empty area is not the result of the independent action of a single risk area, but is often caused by the mutual correlation and influence of multiple risk areas, and considering the improvement of the overall instability of the combustion and empty area, the essence is the result of the increase of the number of risk areas in the correlation group and the increase of the total number of such correlation groups, and if addition or other calculation is used, the amplification effect of the double influence will be weakened, and the multiplication calculation can avoid the misjudgment of the single dimension advantage offsetting the disadvantage of another dimension, and ensure the quantitative accuracy of the correlation impact.

[0086] Therefore, the sum of the number of risk areas in each region correlation group is calculated, and the product of the sum and the total number of the region correlation groups is taken as the correlation impact characteristic value.

[0087] The present application considers the overall distribution of the risk areas and the linkage effect between the risk areas, captures the potential correlation between the risks, avoids sudden accidents caused by ignoring the coupling effect between the areas, and provides core technical support for the long-term safe and stable operation of the combustion and empty area.

[0088] The monitoring and early warning module combines the risk coefficients of the risk areas with the spatial distribution density characteristic value and the correlation impact characteristic value, analyzes the stability level of the combustion and empty area, and sends corresponding early warning signals according to different stability levels.

[0089] In one preferred example of the present application, the specific method for analyzing the stability level of the gasification combustion and empty area comprises: normalizing the correlation impact characteristic value and the spatial distribution density characteristic value, respectively.

[0090] The normalization processing can extract the historical monitoring data of the combustion air zone from the combustion air zone monitoring database, and the maximum values of the correlation influence characteristic value and the spatial distribution density characteristic value are screened from the historical monitoring data, the correlation influence characteristic value and the spatial distribution density characteristic value are respectively compared with the corresponding maximum values, and when the ratio result is greater than 1, the normalization result is recorded as 1, so that the correlation influence characteristic value, the spatial distribution density characteristic value and the risk grade have the same dimension through the normalization processing.

[0091] The product of the correlation influence characteristic value, the spatial distribution density characteristic value and the maximum value in the risk coefficient of each risk area in the combustion air zone is taken as the risk value.

[0092] The correlation influence characteristic value, the spatial distribution density characteristic value and the risk coefficient of each risk area in the combustion air zone are not independent of the stability, but there is a risk transmission relationship, only through the product can the actual effect of the chain amplification be reflected: if other forms such as addition are used, the misjudgment of low risk items offsetting high risk items may occur, and the product can fully highlight the influence of any item, which conforms to the actual law of the instability of the combustion air zone.

[0093] The risk value is matched with the risk value range corresponding to each stability grade, and the stability grade corresponding to the combustion air zone is obtained.

[0094] The risk value is a value between 0 and 1, and the greater the value, the higher the risk and the lower the stability grade, in the specific example in the application, three stability grades of high, medium and low are set, wherein the risk value range of the high stability grade is [0, M1], the risk value range of the medium stability grade is (M1, M2], and the risk value range of the low stability grade is (M2, 1], the specific value range is obtained by extracting the collapse data corresponding to the collapse event from the combustion air zone monitoring database, tracing the risk value before each collapse event, considering that the stability grade of the combustion air zone is usually high in the months before the collapse, so in the application, the average value of the risk value in the three months before the collapse is recorded as the maximum value of the risk value range of the high stability grade, that is, M1, and considering that the closer to the collapse time, the lower the stability grade, so in the application, the average value of the risk value in the week before the collapse is recorded as the minimum value of the risk value range of the medium stability grade, that is, M2, wherein the specific time can also be set by the implementer.

[0095] The application analyzes the stability grade of the combustion air zone by combining the risk coefficient of each risk area with the spatial distribution density characteristic value and the correlation influence characteristic value, and issues corresponding warning signals according to different stability grades, so as to realize comprehensive evaluation of the stability of the combustion air zone, avoid resource waste caused by indiscriminate warning, and improve the warning efficiency.

[0096] The above-described embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented by software, the above-described embodiments can be implemented in whole or in part in the form of a computer program product.

[0097] Those skilled in the art can realize that the modules and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized 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 realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0098] In addition, each functional module in each embodiment of the present application can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0099] The above is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0100] Finally, the above is merely preferred embodiments of the present application, and is not intended to limit the present application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A real-time monitoring and early warning system for stability of a coal underground gasification combustion zone, characterized in that, Comprise: Rupture point monitoring module: evenly arrange sensor groups on the inner wall of the surrounding rock of the combustion and emptying area, receive seismic waves in continuous time through the sensor groups, and locate all rupture point positions; Risk area analysis module: divide adjacent rupture points to obtain the real-time area of each risk area, and calculate the area diffusion degree by tracking the area change of each risk area; Risk coefficient calculation module: determine the stress mutation point by real-time collection of stress data of the inner wall of the surrounding rock, perform correlation analysis on the stress mutation point and the risk area, and calculate the risk coefficient by combining the real-time area and the area diffusion degree of each risk area; Risk correlation analysis module: according to the spatial position of each risk area of the inner wall of the surrounding rock of the combustion and emptying area, obtain the spatial distribution density characteristic value and the correlation influence characteristic value of the combustion and emptying area; Monitoring and early warning module: combine the risk coefficient of each risk area with the spatial distribution density characteristic value and the correlation influence characteristic value to analyze the stability level of the combustion and emptying area, and send corresponding warning signals according to different stability levels; The specific content of the rupture point monitoring module includes: evenly dividing all planar surrounding rock areas of the combustion and emptying area into grids, taking each grid intersection as a monitoring point, and arranging a sensor group containing a microseismic sensor and a stress sensor on each monitoring point; The specific content of the risk coefficient calculation module includes: extracting stress data of a recent historical setting period from historical stress data monitored by the stress sensor of each monitoring point, constructing a recent stress time sequence, comparing the stresses of adjacent time points in the recent stress time sequence to obtain a stress change, and based on the stress change, a recent stress change sequence is formed; according to the stress data of each monitoring point monitored by the stress sensor in real time, the current stress change of each monitoring point is calculated, and whether there is a stress mutation is analyzed in combination with the recent stress change sequence of each monitoring point; the monitoring points with stress mutations are taken as stress mutation points; analyze the positional relationship between each stress mutation point and each risk area, and obtain the stress influence coefficient according to the positional relationship; and the risk coefficient of each risk area is obtained by weighted summation of the area, the area diffusion degree and the stress influence coefficient of each risk area; The calculation method of the stress influence coefficient includes: comparing the positions of each stress mutation point and all risk areas, recording the stress mutation points in the risk areas as regional mutation points, and counting the number of regional mutation points in each risk area; record the mutation points outside all risk areas as external mutation points, associate each external mutation point with the risk area with the shortest straight line distance from it, and record the distance as the associated distance; count the number of external mutation points associated with each risk area and the associated distance of each external mutation point; record the ratio of the number of regional mutation points and the number of external mutation points to the total number of stress mutation points in the combustion and emptying area as the regional mutation point number ratio and the external mutation point number ratio; and the stress influence coefficient is obtained by comprehensive analysis of the regional mutation point number ratio, the external mutation point number ratio and the associated distance of the external mutation point.

2. The real-time monitoring and early warning system for the stability of the combustion and emptying area of underground coal gasification according to claim 1, characterized in that, Record waveform signals appearing in continuous time from microseismic sensors of each monitoring point; Compare waveform shape features and dominant frequencies in waveform signals of each monitoring point with each other, take waveform signals with consistent waveform shape features and similar dominant frequencies as the same rupture point waveform signals, count all monitoring points with the same rupture point waveform signals, extract the first arrival time of the P wave from the waveform signals of each monitoring point corresponding to each rupture point, group each monitoring point corresponding to each rupture point in pairs to obtain each group of monitoring points, and calculate the difference in the first arrival time of the P wave corresponding to each group of monitoring points; According to the difference in the first arrival time of the P wave corresponding to each group of monitoring points of each rupture point, the velocity of the P wave under the surrounding rock medium is combined to calculate the distance difference of each group of monitoring points; Put the distance difference of each group of monitoring points of each rupture point and the position of each group of monitoring points into the Euclidean distance difference calculation formula, and output the specific position of each rupture point.

3. The real-time monitoring and early warning system for stability of the emptying zone of underground coal gasification according to claim 1, characterized in that, The real-time area acquisition method of the risk area comprises: Calculate the Euclidean distance between each rupture point and other rupture points, record two points with a distance less than a set distance threshold as adjacent points, take a rupture point as an initial rupture point, and include its adjacent points in the initial rupture point clustering cluster; In turn, include the adjacent points of other rupture points in the initial rupture point clustering cluster, until all adjacent points of the rupture points in the initial rupture point clustering cluster are in the corresponding clustering cluster; Count all rupture point clustering clusters, take the minimum circumscribed polygon containing all points in each rupture point clustering cluster as the real-time area of each risk area; Calculate the real-time area of each risk area by multiplying the number of grids covered by each risk area by the area of a single grid.

4. The real-time monitoring and early warning system for stability of the emptying zone of underground coal gasification according to claim 3, characterized in that, The area diffusion degree calculation method of the risk area is: Monitor the area of each risk area after a set period of time, calculate the difference between the area of each risk area after a set period of time and the real-time area, and take the ratio of the difference to the real-time area as the area diffusion degree.

5. The real-time monitoring and early warning system for stability of the emptying zone of underground coal gasification according to claim 1, characterized in that, The stress mutation point judgment method comprises: Calculate the recent standard deviation and recent average value of all stress changes in the recent stress change sequence of each monitoring point; Set the corresponding deviation threshold according to the recent standard deviation in the recent stress change sequence of each monitoring point; When the deviation of the current stress change amount of a monitoring point from the recent average value is greater than the corresponding deviation threshold, it is determined that the monitoring point has a stress mutation, and the monitoring point is recorded as a stress mutation point.

6. The real-time monitoring and early warning system for stability of the emptying zone of underground coal gasification according to claim 1, characterized in that, The acquisition method of the spatial distribution density characteristic value comprises: According to the spatial position of each risk area in the inner wall of the surrounding rock of the combustion air zone, determine all risk areas in each plane surrounding rock area, analyze the ratio of the average distance between the geometric centers of all risk areas in each plane surrounding rock area to the maximum boundary distance of the corresponding plane, and take the ratio as the dispersion degree of each plane surrounding rock area; Take the ratio of the sum of the areas of the risk areas in each plane surrounding rock area to the total area of the corresponding plane surrounding rock area as the area coverage degree; Take the ratio of the area coverage degree to the dispersion degree of each plane surrounding rock area as the distribution density; Weighted sum all the distribution densities of the plane surrounding rock areas to obtain the spatial distribution density characteristic value of the whole combustion air zone.

7. The real-time monitoring and early warning system for stability of the emptying zone of underground coal gasification according to claim 1, characterized in that, The acquisition method of the correlation influence characteristic value comprises: Obtain the shortest straight line distance between each risk area and other risk areas in each plane surrounding rock area; Screening other risk areas with a shortest straight line distance less than a set boundary distance threshold from the boundary of each risk area, and combining the risk areas to obtain a region association group; Summing the number of risk areas in each region association group, and taking the product of the sum and the total number of region association groups as an association influence characteristic value.

8. The real-time monitoring and early warning system for stability of the emptying zone of underground coal gasification according to claim 7, characterized in that, The specific method for analyzing the stability level of the fuel-air area includes: Normalizing the association influence characteristic value and the spatial distribution density characteristic value respectively; Taking the product of the association influence characteristic value, the spatial distribution density characteristic value, and the maximum value in the risk coefficient of each risk area in the fuel-air area as a risk value; Matching the risk value with a set risk value range corresponding to each stability level to obtain the stability level corresponding to the fuel-air area.

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