CN110609324A - Method for screening rock burst early warning micro-seismic events of deep-buried tunnel - Google Patents
Method for screening rock burst early warning micro-seismic events of deep-buried tunnel Download PDFInfo
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Abstract
The invention provides a method for screening a deep-buried tunnel rock burst early warning micro-seismic event, and relates to the technical field of deep-buried hard rock tunnel rock burst early warning. Firstly, collecting microseismic monitoring information corresponding to each rock burst case from inoculation to occurrence, and extracting the release energy logarithm and the magnitude of each microseismic event in each rock burst case; drawing microseismic energy grading curves of different grades of rock burst cases, and further calculating release energy logarithm values corresponding to each particle size of the energy grading curves of different grades of rock bursts; drawing the variation conditions of the particle size values of different grades of rock burst in the same energy particle size curve chart, analyzing and obtaining the mean value of the logarithmic values of the released energy corresponding to the energy particle sizes when the energy particle size curves of the rock bursts of the different grades begin to have no cross and the subsequent trends are consistent; and taking the value as the minimum integrity energy threshold of the microseismic catalog, wherein the corresponding seismic magnitude is the minimum integrity seismic magnitude value, and further screening the microseismic event of rock burst early warning is realized.
Description
Technical Field
The invention relates to the technical field of deep-buried hard rock tunnel rock burst early warning, in particular to a method for screening deep-buried tunnel rock burst early warning micro-seismic events.
Background
Rock burst is a dynamic disaster phenomenon that under the condition of high stress, under the influence of excavation or other external disturbance, elastic deformation potential energy accumulated in a rock body is suddenly and violently released, so that the rock bursts and is ejected. With the continuous construction and development of deep-buried hard rock tunnel engineering in China, the rock burst disasters are more prominent. The sudden rockburst disaster not only seriously threatens the safety of constructors and equipment, but also delays the progress of the project to a great extent. Therefore, for deep-buried tunnel engineering with a rock burst tendency, a microseismic monitoring means is often adopted to predict and early warn the rock burst in the construction process. When the linear tunnel engineering carries out micro-seismic monitoring, the capability of the monitoring system for recording micro-seismic events can be changed along with the forward progress of the tunnel face and under the influence of factors such as a sensor array, the distance from the tunnel face, the monitoring quality of the sensor, the construction environment and the like. The adverse effect can possibly cause the microseismic activity parameters of part of rock burst cases to become discrete and irregular, and the adverse effect is generated on rock burst early warning. Therefore, in order to reduce and eliminate the influence of adverse factors on rock burst early warning to a certain extent and ensure that the rock burst is effectively early warned by using the microseismic characteristic parameter values on the basis of unified standard and relative fairness, the minimum integrity energy or the seismic magnitude which can effectively monitor and has no missed microseismic events needs to be reasonably established, and the microseismic events used for rock burst early warning are screened by taking the minimum integrity energy or the seismic magnitude as a lower limit threshold.
The process of establishing a minimum integrity energy or magnitude is referred to in seismology as seismic directory completeness analysis. The earthquake catalogue completeness analysis is an important basis for earthquake activity analysis, earthquake prediction and earthquake risk assessment. Therefore, when the deep-buried hard rock tunnel engineering carries out microseismic monitoring and rock burst early warning, the microseismic catalog completeness analysis is also necessary to be carried out so as to determine the lower limit threshold value of microseismic event screening for rock burst early warning and reduce or avoid the interference of part of adverse factors on the rock burst early warning. When the completeness of a seismic catalog is analyzed in seismology, the seismic level corresponding to the maximum frequency microseismic event is often selected as a completeness threshold value Mc. The difference from seismology is that different-energy microseismic events generated in the tunnel excavation process approximately follow normal distribution, and the microseismic events with smaller energy and larger energy are relatively less. If the microseismic catalog analysis standard in seismology is adopted, most microseismic events cannot be used for rock burst early warning. Therefore, the establishment of the microseismic catalog completeness analysis method for the screening of the deep tunnel rock burst early warning microseismic events has important significance.
At present, the microseismic event screening for rock burst early warning at home and abroad is mostly established by the experience of technicians, and has certain subjectivity. The invention discloses a microseismic multi-dimensional information comprehensive time sequence early warning method for rock burst, which is only applied to coal mines, and provides a method for screening microseismic events for early warning of rock burst by taking inflection point distribution of deviation of a high energy end and a low energy end of a Gurtenberg-Richter power rate curve from a power rate as upper and lower limit boundary lines of energy. However, for rock bursts of different grades in the same project, a uniform and fixed screening lower limit threshold value is lacked, and in addition, for the field of linear deep-buried tunnel engineering in which a sensor dynamically moves along with a tunnel face, the use of the method may have certain limitation. In addition, at present, a reasonable and effective microseismic catalog completeness analysis method for screening rock burst early warning microseismic events is not established in the construction of foreign deep-buried hard rock tunnel engineering, and no relevant literature report is found in China.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art, and provides a method for screening the rock burst early warning microseismic events of the deep-buried tunnel, so as to improve the accuracy of rock burst early warning (especially low-grade rock burst early warning) and ensure the safety and progress of tunnel construction.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a method for screening a deep-buried tunnel rock burst early warning microseismic event comprises the following steps:
step 1, carrying out microseismic monitoring in the process of excavating a deep-buried tunnel, and acquiring microseismic information of wall rock fracture in the process of excavating the tunnel;
step 2, respectively selecting rock burst cases with precursor micro-seismic characteristics aiming at the generated rock bursts of different grades, and collecting micro-seismic monitoring information corresponding to the rock burst cases from inoculation to generation by utilizing the micro-seismic information of the surrounding rock fracture obtained in the step 1;
the rock burst grade is no rock burst, slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst;
step 3, combining the selected microseismic events of all the rock-burst-free cases, and extracting the release energy logarithm and the seismic magnitude of each microseismic event in the rock-burst-free cases;
step 4, repeating the step 3, and respectively extracting the release energy logarithms and the magnitude of all microseismic events of the cases of slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst;
step 5, respectively drawing microseismic energy grading curves of different levels of rock burst cases;
step 5.1, sequencing all microseismic events without rock burst cases in ascending order according to the magnitude of the release energy logarithmic value, wherein the sequence is E1、E2、E3、…、EnWhere n is the number of microseismic events without a rockburst case, and E1＜E2＜E3＜…＜En；
Step 5.2, from E1At the beginning, press E1～EnRespectively counting that all microseismic events of the rockburst-free case are not more than EiCorresponding number N of microseismic events of microseismic release energy logarithm valuei，i＝1，2，…，n；
Step 5.3, respectively calculating a logarithmic value E of the release energy not greater than a certain logarithmic value EiNumber of microseismic events NiPercentage of total number of microseismic events N without rockburst case (N)i/N)％Taking the percentage as the logarithmic value of the release energy EiThe corresponding microseismic event cumulative percentage;
step 5.4, taking the logarithm of the release energy of the microseismic event as a horizontal axis, and taking the logarithm E of a certain release energyiThe accumulated percent of the microseismic events is a vertical axis, and a microseismic energy grading curve of a rock burst-free case is drawn;
step 5.5, repeating the step 5.1 to the step 5.4, and respectively drawing microseismic energy grading curves of the cases of slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst;
step 6, respectively calculating release energy logarithmic values corresponding to the particle sizes of the energy grading curves d10, d20, d30, … and d100 of the different grades of rock burst according to the microseismic energy grading curve;
step 7, respectively drawing the variation conditions of the particle size values of d10, d20, d30, … and d100 of the rockburst of each grade in the same energy particle size curve graph by taking different particle sizes of the microseismic energy grading curve as a horizontal axis and taking the corresponding release energy logarithmic value of the particle size as a vertical axis;
step 8, observing the spatial distribution condition of the rock burst energy particle size curves of different levels, and analyzing the energy particle size d corresponding to the rock burst energy particle size curves of different levels when the rock burst energy particle size curves begin to appear intercross and the subsequent trends are consistentc；
Step 9, solving the particle sizes d of different grades of rock burstcThe corresponding log value of the released energy is taken as the minimum integrity energy threshold value E of the microseismic cataloguecThe corresponding magnitude is the minimum integrity magnitude Mc；
Step 10, based on the determined EcValue or McScreening the microseismic events for rock burst early warning, and comparing the release energy of the microseismic events with a logarithmic value E > EcOr magnitude value M > McThe microseismic event of (a) is used as a microseismic event that can be used for rock burst warning.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in: the method for screening the early warning microseismic events of the deep tunnel rock burst reasonably establishes the minimum integrity of the microseismic events which can be effectively monitored and are free from missing through analyzing the completeness of the microseismic catalogEnergy and magnitude of earthquake, and according to the determined Ec value or Mc value, the microseismic event for rock burst early warning can be screened, and E is greater than EcOr M > McThe microseismic event of (a) is used as a microseismic event that can be used for rock burst warning. The influence of adverse factor interference on the rock burst early warning is eliminated or reduced, the accuracy of the rock burst early warning is effectively improved, the safety of tunnel construction is ensured, and the construction progress is accelerated.
Drawings
Fig. 1 is a flowchart of a method for screening a deep tunnel rockburst early warning microseismic event according to an embodiment of the present invention;
fig. 2 is a microseismic energy grading curve diagram of different grades of rockburst in a deep tunnel according to an embodiment of the present invention, where (a) is an energy grading curve diagram of no rockburst, (b) is a slight rockburst energy grading curve diagram, and (c) is a medium and above rockburst energy grading curve diagram;
FIG. 3 is a graph of energy particle size for different grades of rock bursts provided by an embodiment of the present invention;
fig. 4 is a calculation result of the number of microseismic events and the b value of a part of rock burst cases before screening the microseismic events, wherein (a) is the number of microseismic events of the part of rock burst cases before screening the microseismic events, and (b) is the calculation result of the b value before screening the microseismic events;
fig. 5 is a calculation result of the number of microseismic events and the value b of partial rockburst cases after the microseismic event screening according to the embodiment of the present invention, where (a) is the number of microseismic events of partial rockburst cases after the microseismic event screening, and (b) is the calculation result of the value b after the microseismic event screening.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In this embodiment, a deep-buried hard rock tunnel with a certain frequent rock burst is taken as an example, and the method of the present invention is adopted to perform microseismic event screening.
A method for analyzing completeness of a microseismic catalog for screening of a deep-buried tunnel rock burst early warning microseismic event is shown in figure 1 and comprises the following steps:
step 1, carrying out microseismic monitoring in the process of excavating a deep-buried tunnel, and acquiring microseismic information of wall rock fracture in the process of excavating the tunnel;
step 2, respectively selecting rock burst cases with precursor micro-seismic characteristics aiming at the generated rock bursts of different grades, and collecting micro-seismic monitoring information corresponding to the rock burst cases from inoculation to generation by utilizing the micro-seismic information of the surrounding rock fracture obtained in the step 1;
the rock burst grade is no rock burst, slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst;
in this embodiment, the rock burst level of the tunnel includes: strong rock burst, medium rock burst, slight rock burst and no rock burst are not generated, so that 3 strong rock bursts, 10 medium rock burst cases, 15 slight rock burst cases and 20 no rock burst cases are respectively selected, and microseismic monitoring information corresponding to the rock burst cases from inoculation to generation is collected;
step 3, combining the selected microseismic events of all the rock-burst-free cases, and extracting the release energy logarithm and the seismic magnitude of each microseismic event in the rock-burst-free cases;
in the embodiment, all the microseismic events of the selected 20 rockburst-free cases are combined, the number of the combined microseismic events is 2469, and the release energy logarithm and the seismic magnitude of the 2469 microseismic events are respectively extracted;
step 4, repeating the step 3, and respectively extracting the release energy logarithms and the magnitude of all microseismic events of the cases of slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst;
in the embodiment, because the number of strong rock burst cases is small, in order to ensure that the analysis result has reliability, the strong rock burst cases and the medium rock burst cases are combined and used as rock bursts above the medium rock burst to be jointly analyzed. According to the mode of the step 3, 2404 microseismic events after 15 slight rockburst cases are combined, 3185 microseismic events of more than 13 medium rockburst cases are combined, and the release energy logarithms and the magnitude of all the microseismic events of the slight rockburst cases and the rock burst cases above the medium rockburst cases are respectively extracted;
step 5, respectively drawing microseismic energy grading curves of different levels of rock burst cases, as shown in figure 2;
step 5.1, sequencing all microseismic events without rock burst cases in ascending order according to the magnitude of the release energy logarithmic value, wherein the sequence is E1、E2、E3、…、EnWhere n is the number of microseismic events without a rockburst case, and E1＜E2＜E3＜…＜En；
2469 microseismic events without rockburst cases are sorted in ascending order according to the magnitude of the release energy logarithmic value, and respectively are E1、E2、E3、…、E2469Wherein E is1Is-3.87, E2469Is 4.32;
step 5.2, from E1At the beginning, press E1～EnRespectively counting that all microseismic events of the rockburst-free case are not more than EiCorresponding number N of microseismic events of microseismic release energy logarithm valuei，i＝1，2，…，n；
Step 5.3, respectively calculating a logarithmic value E of the release energy not greater than a certain logarithmic value EiNumber of microseismic events NiPercentage of total number of microseismic events N without rockburst case (N)i/N)%, i.e. the percentage is taken as the logarithmic value of the release energy EiThe corresponding microseismic event cumulative percentage;
step 5.4, taking the logarithm of the release energy of the microseismic event as a horizontal axis, and taking the logarithm E of a certain release energyiThe accumulated percent of the microseismic events is a vertical axis, and a microseismic energy grading curve of a rock burst-free case is drawn;
step 5.5, repeating the step 5.1 to the step 5.4, and respectively drawing microseismic energy grading curves of the cases of slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst;
step 6, respectively calculating release energy logarithmic values corresponding to the particle sizes of the energy grading curves d10, d20, d30, … and d100 of the different grades of rock burst according to the microseismic energy grading curve;
step 7, respectively drawing the change conditions of d10, d20, d30, … and d100 values of the rockburst of each grade in the same energy particle size curve by taking different particle sizes of the microseismic energy grading curve as a horizontal axis and taking the corresponding release energy logarithmic value of the particle size as a vertical axis, as shown in fig. 3;
step 8, observing the spatial distribution condition of the rock burst energy particle size curves of different levels, and analyzing the energy particle size d corresponding to the rock burst energy particle size curves of different levels when the rock burst energy particle size curves begin to appear intercross and the subsequent trends are consistentc；
In this embodiment, the spatial distribution of the energy particle size curves of the different grades of rock bursts in fig. 3 is observed, and it can be seen from fig. 3 that the d 30-d 80 values of the different grades of rock bursts are substantially linear functions, and the energy value corresponding to the particle size is larger when the grade of the rock burst is higher, but when the microseismic energy is less than d30, the energy particle size functions of the different grades of rock bursts are curve segments, and particularly the d10 and d20 values of the slight rock burst and the rock bursts above the medium have obvious fluctuation and intersection, that is, when the energy particle size is d10 and d20 values, the energy particle size is obviouslycWhen d30, the rockburst energy particle size curves of all levels begin to have no intersection with each other, and the subsequent trends are consistent;
step 9, solving the energy particle size d of the rock burst of different gradescThe corresponding log value of the released energy is taken as the minimum integrity energy threshold value E of the microseismic cataloguecThe corresponding magnitude is the minimum integrity magnitude Mc；
In this embodiment, d30 values of no rock burst, light rock burst and medium or above rock burst are respectively calculated as-0.10, 0.43 and 0.58, and the average value is 0.30, that is, the minimum integrity energy threshold E of the microseismic catalogc0.30, the corresponding magnitude is the minimum integrity magnitude value Mc＝-2.6；
Step 10, based on the determined EcValue or McScreening the microseismic events for rock burst early warning, and comparing the release energy of the microseismic events with a logarithmic value E > EcOr magnitude value M > McThe microseismic event of (a) is used as a microseismic event that can be used for rock burst warning.
In this example, according to the established EcValue or McThe microseismic events used for rock burst early warning can be screened, and the microseismic events with E > 0.30 or M > -2.6 are used as the microseismic events used for rock burst early warning. The number of microseismic events and the b value calculation result of partial rock burst cases before and after screening are shown as a graph4. As shown in fig. 5. Comparing fig. 4 and fig. 5, it can be seen that, after partial slight rockburst and rockburst-free cases are screened, most of the cases of slight rockburst and rockburst-free can reach the early warning threshold value of the respective grade, and the interference on the early warning result is reduced to a certain extent by the minimum integrity energy or the seismic grade established by the microseismic catalog completeness analysis method for screening the microseismic event of the deep-buried tunnel rockburst early warning. By using Ec(d30) And E0(d80) The G-R graph drawn by the screened microseismic events is linear, the fitting degree is higher, and the solved b value is more reasonable.
Therefore, the embodiment and the application show that the microseismic catalog completeness analysis method for screening the rock burst early warning microseismic events of the deep-buried tunnel, which is established by the invention, is reasonable, has better use effect and value, and can make a contribution to improving the early warning accuracy of rock burst (particularly low-grade rock burst).
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.
Claims (2)
1. A method for screening a deep-buried tunnel rock burst early warning microseismic event is characterized by comprising the following steps: the method comprises the following steps:
step 1, carrying out microseismic monitoring in the process of excavating a deep-buried tunnel, and acquiring microseismic information of wall rock fracture in the process of excavating the tunnel;
step 2, respectively selecting rock burst cases with precursor micro-seismic characteristics aiming at the generated rock bursts of different grades, and collecting micro-seismic monitoring information corresponding to the rock burst cases from inoculation to generation by utilizing the micro-seismic information of the surrounding rock fracture obtained in the step 1;
the rock burst grade is no rock burst, slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst;
step 3, combining the selected microseismic events of all the rock-burst-free cases, and extracting the release energy logarithm and the seismic magnitude of each microseismic event in the rock-burst-free cases;
step 4, repeating the step 3, and respectively extracting the release energy logarithms and the magnitude of all microseismic events of the cases of slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst;
step 5, respectively drawing microseismic energy grading curves of different levels of rock burst cases;
step 6, respectively calculating release energy logarithmic values corresponding to the particle sizes of the energy grading curves d10, d20, d30, … and d100 of the different grades of rock burst according to the microseismic energy grading curve;
step 7, respectively drawing the variation conditions of the particle size values of d10, d20, d30, … and d100 of the rockburst of each grade in the same energy particle size curve graph by taking different particle sizes of the microseismic energy grading curve as a horizontal axis and taking the corresponding release energy logarithmic value of the particle size as a vertical axis;
step 8, observing the spatial distribution condition of the rock burst energy particle size curves of different levels, and analyzing the energy particle size d corresponding to the rock burst energy particle size curves of different levels when the rock burst energy particle size curves begin to appear intercross and the subsequent trends are consistentc；
Step 9, solving the particle sizes d of different grades of rock burstcThe corresponding log value of the released energy is taken as the minimum integrity energy threshold value E of the microseismic cataloguecThe corresponding magnitude is the minimum integrity magnitude Mc；
Step 10, based on the determined EcValue or McScreening the microseismic events for rock burst early warning, and comparing the release energy of the microseismic events with a logarithmic value E > EcOr magnitude value M > McThe microseismic event of (a) is used as a microseismic event that can be used for rock burst warning.
2. The method for screening the deep-buried tunnel rock burst early warning microseismic event according to claim 1, which is characterized in that: the specific method of the step 5 comprises the following steps:
step 5.1, all the microseisms without rockburst casesThe events are sorted in ascending order according to the magnitude of the release energy log, respectively E1、E2、E3、…、EnWhere n is the number of microseismic events without a rockburst case, and E1＜E2＜E3＜…＜En；
Step 5.2, from E1At the beginning, press E1～EnRespectively counting that all microseismic events of the rockburst-free case are not more than EiCorresponding number N of microseismic events of microseismic release energy logarithm valuei，i＝1，2，…，n；
Step 5.3, respectively calculating a logarithmic value E of the release energy not greater than a certain logarithmic value EiNumber of microseismic events NiPercentage of total number of microseismic events N without rockburst case (N)i/N)%, i.e. the percentage is taken as the logarithmic value of the release energy EiThe corresponding microseismic event cumulative percentage;
step 5.4, taking the logarithm of the release energy of the microseismic event as a horizontal axis, and taking the logarithm E of a certain release energyiThe accumulated percent of the microseismic events is a vertical axis, and a microseismic energy grading curve of a rock burst-free case is drawn;
and 5.5, repeating the steps 5.1-5.4, and respectively drawing microseismic energy grading curves of the cases of slight rock burst, medium rock burst, strong rock burst and extremely strong rock burst.
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| CN111123355A (en) * | 2020-01-07 | 2020-05-08 | 山东大学 | Rockburst prediction method and system based on microseismic monitoring data |
| US12020126B2 (en) | 2021-04-08 | 2024-06-25 | International Business Machines Corporation | Automated pressure level detection and correction |
| CN115526036A (en) * | 2022-09-19 | 2022-12-27 | 长安大学 | Method and system for judging rock burst scale grade |
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