Method and system for judging rock burst grade based on multi-element micro-seismic monitoring information

Abstract

The invention provides a method for judging a rock burst grade based on multi-element micro-seismic monitoring information. The method comprises the following steps: acquiring micro-seismic monitoring data of a micro-seismic energy event; calculating the maximum energy activity according to the micro-seismic monitoring data; performing data testing on the rock stratum generating the maximum energy per day to obtain a stress concentration coefficient; obtaining the position of an advanced working face according to the stress concentration coefficient and the spatial distribution of the micro-seismic energy event; grading the micro-seismic energy events according to the micro-seismic energy ratio, the maximum energy activity and the position of the advanced working face; and executing different work contents according to a grading result. According to the method, the rock burst grade is judged through the multi-element micro-seismic monitoring information, different countermeasures are executed according to the rock burst grade, the influence of the rock burst on the mine is prevented, and the production safety is improved.

Description

Technical Field

[0001] The present invention relates to the field of rock burst technology, and in particular to a method and system for determining rock burst levels based on multi-element microseismic monitoring information. Background Art

[0002] As the depth of coal mining continues to increase, the frequency of geological dynamic disasters in coal mines and the hazards of rock burst are also increasing rapidly. Rock burst has a serious impact on the safe production of mines, including tunnel shrinkage and deformation, support damage, equipment damage, gas and coal dust explosions and other serious consequences. In order to effectively prevent and control rock burst, coal mines generally install microseismic monitoring systems to obtain real-time information on surrounding rock fractures in the mining area, and then predict potential disaster risks.

[0003] At present, the monitoring of microseismic data is basically divided into two categories. One category focuses on considering the formation mechanism of rock burst, conducting mathematical and statistical analysis on the mechanical characteristics of coal-rock instability destruction, and analyzing the law and trend of microseismic energy changes and the range of temporal and spatial destruction with the help of conventional statistical parameters and comprehensive processing parameters. The other category focuses on the establishment of prediction models, including fitting prediction and identification prediction. Fitting prediction generally uses statistical methods such as correlation coefficients and multivariate linear regression to establish prediction models for variable statistics and time series.

[0004] However, due to the high dimensionality, discreteness, complexity, and temporal and spatial correlation of microseismic data, it is still challenging to mine and understand the useful information in it. Therefore, it is necessary to design a method and system for judging the rock burst level based on multivariate microseismic monitoring information. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for determining the rock burst level based on multivariate microseismic monitoring information, by which the rock burst level is determined and different response measures are implemented according to the rock burst level, so as to prevent the impact of rock burst on mines and improve production safety.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A method for determining rock burst level based on multivariate microseismic monitoring information comprises the following steps:

[0008] Obtain microseismic monitoring data of microseismic energy events; microseismic monitoring data include microseismic energy proportion, number of microseismic energy occurrences, maximum energy per day, and average energy per day;

[0009] The maximum energy activity is calculated based on the microseismic monitoring data;

[0010] Conduct data testing on the rock formation that produces the maximum energy in a single day and obtain the stress concentration factor;

[0011] The position of the advanced working face is obtained according to the spatial distribution of stress concentration factor and microseismic energy events;

[0012] Microseismic energy events are graded according to the proportion of microseismic energy, maximum energy activity and the position of the advanced working face;

[0013] Perform different work contents according to the results of grade division.

[0014] Optionally, the microseismic energy ratio includes: a first energy ratio and a second energy ratio; the first energy ratio is when the microseismic energy is greater than 10 3 The number of microseismic energy events of J accounts for more than 30% of the total number; the second energy proportion is the microseismic energy greater than 10 3 The number of microseismic energy events in J did not exceed 30% of the total number.

[0015] Optionally, the maximum energy activity is calculated as: Among them, P is the maximum energy activity, m is the number of occurrences, E p is the average energy of the day, E max The maximum energy per day.

[0016] Optionally, the maximum energy activity includes: a first activity and a second activity; when the maximum energy activity is greater than or equal to 8, the maximum energy activity is used as the first activity; when the maximum energy activity is greater than or equal to 1 and less than 8, the maximum energy activity is used as the second activity.

[0017] Optionally, the calculation formula for the position of the advance working surface is: Where S is the height of the advance working surface, h max is the maximum height of the microseismic energy event, h min The minimum height of a microseismic energy event, K is the stress concentration factor.

[0018] Optionally, the advance working surface position includes: a first position and a second position; when a microseismic event occurs at the advance working surface position, the advance working surface position is taken as the first position; when no microseismic energy event occurs at the advance working surface position, the advance working surface position is taken as the second position.

[0019] Optionally, microseismic energy events are graded according to the proportion of microseismic energy, maximum energy activity and advance working surface position, specifically: corresponding weighted values ​​are assigned to the proportion of microseismic energy, maximum energy activity and advance working surface position, and the microseismic energy events are graded according to the sum of the weighted values.

[0020] Optionally, the weighted values ​​of microseismic energy proportion, maximum energy activity and advance working face position are 0.4, 0.4 and 0.2 respectively; the weighted values ​​of the first energy proportion and the second energy proportion are 0.32 and 0.08 respectively; the weighted values ​​of the first activity and the second activity are 0.32 and 0.08 respectively; the weighted values ​​of the first position and the second position are 0.12 and 0.08 respectively.

[0021] Optionally, the microseismic energy events are graded according to the sum of weighted values, including:

[0022] When the sum of the weighted values ​​is 0.76, the microseismic energy event is determined to be the first level;

[0023] When the sum of the weighted values ​​is 0.72, the microseismic energy event is determined to be the second level;

[0024] When the sum of the weighted values ​​is 0.52, the microseismic energy event is determined to be the third level;

[0025] When the sum of the weighted values ​​is 0.48, the microseismic energy event is determined to be the fourth level;

[0026] When the sum of the weighted values ​​is 0.28 or 0.24, the microseismic energy event is determined to be the fifth level.

[0027] A system for determining rock burst levels based on multivariate microseismic monitoring information, comprising:

[0028] The data acquisition module is used to obtain the microseismic monitoring data of microseismic energy events; the microseismic monitoring data includes the microseismic energy proportion, the number of microseismic energy occurrences, the maximum energy per day and the average energy per day;

[0029] An information processing module is used to calculate the maximum energy activity according to the microseismic monitoring data and to obtain the position of the leading working face according to the stress concentration factor and the spatial distribution of the microseismic energy events;

[0030] A classification module is used to classify microseismic energy events according to the proportion of microseismic energy, maximum energy activity and advanced working face position;

[0031] The instruction generation module is used to generate different work instructions according to the results of grade division.

[0032] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: the method provided by the present invention for judging the impact ground pressure level based on multivariate microseismic monitoring information, the method comprising: obtaining microseismic monitoring data of microseismic energy events; calculating the maximum energy activity according to the microseismic monitoring data; performing data testing on the rock formation that produces the maximum energy in a single day to obtain the stress concentration factor; obtaining the advance working face position according to the stress concentration factor and the spatial distribution of microseismic energy events; classifying the microseismic energy events according to the proportion of microseismic energy, the maximum energy activity and the advance working face position; and executing different work contents according to the results of the classification. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0034] Figure 1 The present invention is a flow chart of the method for determining rock burst level. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and understandable, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0037] like Figure 1 As shown, the present invention provides a method for determining the rock burst level based on multivariate microseismic monitoring information, comprising the following steps:

[0038] Step 100: Acquire microseismic monitoring data of microseismic energy events; the microseismic monitoring data includes microseismic energy proportion b, number of microseismic energy occurrences m, and maximum energy per day E. max and the average energy E of the day p ;

[0039] Specifically, the microseismic energy ratio includes: a first energy ratio b1 and a second energy ratio b2; when the microseismic energy is greater than 10 3When the number of microseismic energy events of J exceeds 30% of the total number, b is recorded as the first energy proportion b1; when the microseismic energy is greater than 10 3 When the proportion of the occurrence of microseismic energy events of J does not exceed 30% of the total number, b is recorded as the second energy proportion b2.

[0040] Furthermore, according to the height distribution h of the microseismic energy event in the spatial position, the maximum height h of the microseismic energy event is obtained. max and minimum height h min .

[0041] Step 200: Calculate the maximum energy activity P according to the microseismic monitoring data;

[0042] Specifically, the calculation formula for the maximum energy activity P is:

[0043]

[0044] Among them, P is the maximum energy activity, m is the number of occurrences, E p is the average energy of the day, E max The maximum energy per day.

[0045] More specifically, the maximum energy activity includes: a first activity P1 and a second activity P2; when the maximum energy activity is greater than or equal to 8, that is, P>8, the maximum energy activity P is recorded as the first activity P1; when the maximum energy activity is greater than or equal to 1 and less than 8, that is, 1≤P<8, the maximum energy activity P is recorded as the second activity P2.

[0046] Step 300: Perform data testing on the rock formation that generates the maximum energy in a single day to obtain the stress concentration factor K;

[0047] Step 400: obtaining the position of the leading working surface according to the stress concentration factor and the spatial distribution of microseismic energy events;

[0048] Specifically, the calculation formula at the advance working surface S meters is:

[0049]

[0050] Among them, h max is the maximum height of the microseismic energy event, h min The minimum height of a microseismic energy event, K is the stress concentration factor.

[0051] More specifically, the position of the advance working face includes: a first position S1 and a second position S2; when a microseismic event occurs at S meters from the advance working face, the position S meters from the advance working face is recorded as the first position S1; when no microseismic energy event occurs at S meters from the advance working face, the position S meters from the advance working face is recorded as the second position S2.

[0052] Step 500: classifying microseismic energy events according to microseismic energy proportion, maximum energy activity and advanced working face position;

[0053] Specifically, the corresponding weighted values ​​are assigned to the proportion of microseismic energy, the maximum energy activity and the position of the advanced working surface. The weighted values ​​of the proportion of microseismic energy, the maximum energy activity and the position of the advanced working surface are 0.4, 0.4 and 0.2 respectively. For the b value, the weights of b1 and b2 for the b value are 0.8 and 0.2 respectively; for the P value, the weights of P1 and P2 for the P value are 0.8 and 0.2 respectively; for the S value, the weights of S1 and S2 for the S value are 0.6 and 0.4 respectively.

[0054] Generally speaking, the weighted values ​​of the first energy proportion b1, the second energy proportion b2, the first activity level P1, the second activity level P2, the first position S1 and the second position S2 are 0.32, 0.08, 0.32, 0.08, 0.12 and 0.08 respectively.

[0055] More specifically, microseismic energy events are classified according to the sum of weighted values, including:

[0056] When the sum of the weighted values ​​is 0.76, the microseismic energy event is judged as level A, which is a strong danger level;

[0057] When the sum of the weighted values ​​is 0.72, the microseismic energy event is judged as level B, which is a medium-risk level;

[0058] When the sum of the weighted values ​​is 0.52, the microseismic energy event is judged as level C, which is a general danger level;

[0059] When the sum of the weighted values ​​is 0.48, the microseismic energy event is judged as level D, which is a weak danger level;

[0060] When the sum of the weighted values ​​is 0.28 or 0.24, the microseismic energy event is judged as E level, that is, no danger level. The specific classification content is shown in Table 1:

[0061] Table 1 Classification table

[0062] type b-value P-value S value Weighted sum grade 1 <![CDATA[b1]]> <![CDATA[P1]]> <![CDATA[S1]]> 0.76 A 2 <![CDATA[b1]]> <![CDATA[P1]]> <![CDATA[S2]]> 0.72 B 3 <![CDATA[b1]]> <![CDATA[P2]]> <![CDATA[S1]]> 0.52 C 4 <![CDATA[b1]]> <![CDATA[P2]]> <![CDATA[S2]]> 0.48 D 5 <![CDATA[b2]]> <![CDATA[P1]]> <![CDATA[S1]]> 0.52 C 6 <![CDATA[b2]]> <![CDATA[P1]]> <![CDATA[S2]]> 0.48 D 7 <![CDATA[b2]]> <![CDATA[P2]]> <![CDATA[S1]]> 0.28 E 8 <![CDATA[b2]]> <![CDATA[P2]]> <![CDATA[S2]]> 0.24 E

[0063] Step 600: Execute different work contents according to the result of the level division.

[0064] Specifically, if the risk level is high, the mining operation is stopped so that no personnel are required to evacuate the mine, and effective pressure relief is achieved through surface fracturing.

[0065] If the danger level is medium, mining operations and prevention work are carried out simultaneously, and prediction and forecasting are used to ensure that the danger level does not rise again. The pressure relief method is directional long drilling;

[0066] If it is a general danger level, mining operations and prevention work are carried out simultaneously, and supervision is strengthened, and the operation form is handled by blasting and pressure relief;

[0067] If the risk level is low, mining operations will proceed normally, and hydraulic fracturing will be used as a pressure relief method;

[0068] If it is a non-hazardous level, no intervention measures are taken, only strengthened supervision is required.

[0069] The present invention also provides a system for determining rock burst level based on multivariate microseismic monitoring information, comprising:

[0070] The data acquisition module is used to obtain the microseismic monitoring data of microseismic energy events; the microseismic monitoring data includes the microseismic energy proportion, the number of microseismic energy occurrences, the maximum energy per day and the average energy per day;

[0071] An information processing module is used to calculate the maximum energy activity according to the microseismic monitoring data and to obtain the position of the leading working face according to the stress concentration factor and the spatial distribution of the microseismic energy events;

[0072] A classification module is used to classify microseismic energy events according to the proportion of microseismic energy, maximum energy activity and advanced working face position;

[0073] The instruction generation module is used to generate different work instructions according to the results of grade division.

[0074] The present invention takes the data of a coal mine in Shanxi Province on March 25, 2024 as an example. Its microseismic energy is greater than 10 3 The number of microseismic events in J does not exceed 30%, with a specific number of occurrences m = 13 times and a maximum energy of E per day. max =2.44E+5 (scientific notation), the average energy of the day E p =1.98E+4 (scientific notation), the maximum height of microseismic energy events h max = 30 m and minimum height h min =-10 meters, maximum energy activity The stress concentration factor K=2 obtained through data testing, the leading working surface at S meters is And no microseismic events occurred at S.

[0075] According to the microseismic monitoring data of the coal mine, the classification conditions are b2, P2, and S2, and the sum of the total weights is 0.24, which belongs to the non-hazardous level and does not require any intervention measures, only strengthened supervision.

[0076] The beneficial effects of the present invention are as follows:

[0077] 1) Through the processing of multi-element microseismic monitoring information, accurate classification of rock burst levels and safety warning are achieved;

[0078] 2) By determining the rock burst level, corresponding countermeasures can be implemented in a timely manner, avoiding the danger caused by rock burst, making mine production safer and more reliable, and greatly improving economic benefits.

[0079] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0080] The present invention uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for determining rock burst level based on multivariate microseismic monitoring information, characterized in that: The steps include: Acquire microseismic monitoring data of microseismic energy events; the microseismic monitoring data includes microseismic energy proportion, number of microseismic energy occurrences, maximum energy per day, and average energy per day; Calculating the maximum energy activity according to the microseismic monitoring data; Conducting data testing on the rock formation that generates the maximum energy in a single day to obtain a stress concentration factor; Obtaining the position of the leading working face according to the stress concentration factor and the spatial distribution of the microseismic energy events; Classifying the microseismic energy events according to the microseismic energy proportion, the maximum energy activity and the advanced working face position; Different work contents are performed according to the result of the classification.

2. The method for determining rock burst level based on multivariate microseismic monitoring information according to claim 1 is characterized in that: The microseismic energy ratio includes: a first energy ratio and a second energy ratio; the first energy ratio is when the microseismic energy is greater than 10 3 The proportion of the number of microseismic energy events of J exceeds 30% of the total number; the second energy proportion is the number of microseismic energy events greater than 10 3 The number of microseismic energy events of J does not exceed 30% of the total number of events.

3. The method for determining rock burst level based on multivariate microseismic monitoring information according to claim 1 is characterized in that: The calculation formula of the maximum energy activity is: Among them, P is the maximum energy activity, m is the number of occurrences, E p is the average energy of the day, E max The maximum energy per day.

4. The method for determining rock burst level based on multivariate microseismic monitoring information according to claim 2 is characterized in that: The maximum energy activity includes: a first activity and a second activity; when the maximum energy activity is greater than or equal to 8, the maximum energy activity is used as the first activity; when the maximum energy activity is greater than or equal to 1 and less than 8, the maximum energy activity is used as the second activity.

5. The method for determining rock burst level based on multivariate microseismic monitoring information according to claim 1 is characterized in that: The calculation formula of the advanced working surface position is: Where S is the height of the advance working surface, h max is the maximum height of the microseismic energy event, h min The minimum height of a microseismic energy event, K is the stress concentration factor.

6. The method for determining rock burst level based on multivariate microseismic monitoring information according to claim 4 is characterized in that: The advance working surface position includes: a first position and a second position; when the microseismic event occurs at the advance working surface position, the advance working surface position is used as the first position; when the microseismic energy event does not occur at the advance working surface position, the advance working surface position is used as the second position.

7. The method for determining rock burst level based on multivariate microseismic monitoring information according to claim 6 is characterized in that: The microseismic energy events are graded according to the microseismic energy proportion, the maximum energy activity and the advance working surface position. Specifically, corresponding weighted values ​​are assigned to the microseismic energy proportion, the maximum energy activity and the advance working surface position, respectively, and the microseismic energy events are graded according to the sum of the weighted values.

8. The method for determining rock burst level based on multivariate microseismic monitoring information according to claim 7 is characterized in that: The weighted values ​​of the microseismic energy proportion, the maximum energy activity and the advance working face position are 0.4, 0.4 and 0.2 respectively; the weighted values ​​of the first energy proportion and the second energy proportion are 0.32 and 0.08 respectively; the weighted values ​​of the first activity and the second activity are 0.32 and 0.08 respectively; the weighted values ​​of the first position and the second position are 0.12 and 0.08 respectively.

9. The method for determining rock burst level based on multivariate microseismic monitoring information according to claim 7, characterized in that: The microseismic energy events are classified according to the sum of the weighted values, including: When the sum of the weighted values ​​is 0.76, the microseismic energy event is determined to be the first level; When the sum of the weighted values ​​is 0.72, the microseismic energy event is determined to be the second level; When the sum of the weighted values ​​is 0.52, the microseismic energy event is determined to be the third level; When the sum of the weighted values ​​is 0.48, the microseismic energy event is determined to be at the fourth level; When the sum of the weighted values ​​is 0.28 or 0.24, the microseismic energy event is determined to be at the fifth level.

10. A system for determining rock burst level based on multivariate microseismic monitoring information, characterized in that: include: A data acquisition module, used to obtain microseismic monitoring data of microseismic energy events; The microseismic monitoring data include the microseismic energy proportion, the number of microseismic energy occurrences, the maximum energy per day and the average energy per day; An information processing module, used to calculate the maximum energy activity according to the microseismic monitoring data and to obtain the position of the leading working face according to the stress concentration factor and the spatial distribution of microseismic energy events; A classification module, used for classifying the microseismic energy events according to the microseismic energy proportion, the maximum energy activity and the advanced working face position; The instruction generation module is used to generate different work instructions according to the result of the grade division.

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