CN116466396A - Nonlinear optimal positioning method for microseism focus - Google Patents
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- 238000004364 calculation method Methods 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 claims 1
- 238000005457 optimization Methods 0.000 abstract description 10
- 238000012544 monitoring process Methods 0.000 abstract description 8
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- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/288—Event detection in seismic signals, e.g. microseismics
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Abstract
The invention relates to the field of microseism monitoring and discloses a microseism focus nonlinear optimization positioning method. The method comprises the steps of collecting a microseismic vibration wave waveform file through a microseismic data collecting device, and transmitting the collected vibration wave waveform file to a built data processing system in a computer for data processing; after the microseismic signals to be positioned are processed, the microseismic shock wave first arrival time point is required to be picked up, and an improved M-AIC arrival time picking method is used for picking up the microseismic shock wave first arrival time point; after the end of the time-of-day pick-up, the positioning can be performed by using known parameters (time-of-day parameters and sensor coordinate parameters). The method improves the stability and the precision of positioning the microseism focus and greatly improves the working efficiency.
Description
Technical Field
The invention relates to the technical field of microseism monitoring, in particular to a nonlinear optimal positioning method for a microseism focus.
Background
Coal is one of the main energy sources in China, and meanwhile, the resource occurrence condition of the coal is complex. Along with the increase of coal mining depth and the improvement of mining intensity, the coal mining inevitably faces a plurality of scientific problems and technical problems such as roof disasters, rock burst, coal and gas outburst, water damage, gas efficient extraction and the like, and the microseismic monitoring technology is an answer for solving the problems.
Microseism focus positioning technology is a key core of microseism monitoring technology. However, because the monitoring environments of the projects such as coal mines, tunnels, side slopes and the like are complex, the propagation path and speed of microseism vibration waves are difficult to control, and the rock fracture signals are easily interfered by mechanical vibration, blasting vibration and natural noise, the microseism signals are difficult to pick up accurately in time, so that a plurality of positioning methods are difficult to position accurately. Therefore, an accurate and scientific microseismic positioning method becomes a key problem for realizing real-time disaster prevention by a microseismic monitoring technology. Therefore, the invention provides a microseism focus nonlinear optimization positioning method which can rapidly, accurately and scientifically perform focus positioning.
Disclosure of Invention
For the problems existing in the conventional microseism monitoring, the invention provides a microseism focus nonlinear optimization positioning method, and the method provides a microseism focus automatic positioning method based on a nonlinear optimization theory.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a nonlinear optimized positioning method of a microseism focus comprises the following steps:
step S1 (collected data-data processing): the microseism data acquisition device is utilized to acquire microseism vibration wave waveform files, the acquired vibration wave waveform files are transmitted to a built data processing system in a computer for data processing, and the data processing comprises: and screening and identifying the microseismic events and filtering microseismic data.
When the field operation environment is complex, the traditional positioning method cannot meet the positioning requirement, and the automatic positioning method of the microseism focus based on the nonlinear optimization theory is adopted, so that the positioning precision is high, the speed measurement is not required in advance, the accuracy and the stability are high, the stability of the traditional positioning method is poor, the effect of selecting different parameters and initial values is greatly affected, the sensitivity is low, the positioning effect is difficult to achieve the expected effect on microseism signals with low signal-to-noise ratio, and the method has the advantages that different microseism signals can be automatically processed by using a built data processing system: because the effective events of the microseism vibration waves are needed for positioning the needed events, the method detects whether the screened events are microseism events or not by using the STA/LTA microseism vibration waves in advance, and then carries out filtering processing on the detected microseism events by using a Kalman filtering algorithm.
Step S2 (to time point pickup): after the microseismic signals to be positioned are processed, the microseismic shock wave first arrival time point is required to be picked up, and the microseismic shock wave first arrival time point is picked up by using an improved M-AIC arrival time picking method.
When the microseism data is too long in trailing and has multiple arrivals, microseism pickup can generate errors, and a microseism event end point is easily picked up, so that final pickup is added into a limiting condition, and only the first arrival wave arrival time point of the calculated M-AIC characteristic value before the maximum value of the amplitude absolute value of the microseism waveform signal is picked up. The improved M-AIC arrival time pickup method can effectively pick up the arrival time of the first arrival of the microseismic shock wave, and the arrival time pickup method adopts the characteristic value calculation formula as follows:
M-AIC(k)＝klg(var(x[1，k]))+(N-k-1)lg(var(x[k+1，N]))
wherein x 1, k is the amplitude value of sampling points 1-k in the microseismic waveform data; n is the length of microseismic waveform data; var () is a variance function.
Step S3 (nonlinear optimized positioning): after the end of the time-of-day pick-up, the positioning can be performed by using known parameters (time-of-day parameters and sensor coordinate parameters).
The method does not need to carry out speed measurement in advance, and can effectively position by only inputting a group of iteration initial values before positioning; the method is based on the principle of nonlinear optimization, combines a mathematical algorithm with a microseismic positioning principle, introduces a hill-down factor in a Newton hill-down method, and strengthens the stability of the algorithm, so that an event that a local optimal solution can be generated in positioning can be effectively avoided; an iteration method is innovated, iteration parameters can be iterated freely in respective dimensions in positioning iteration, so that a positioning result is more scientific and accurate, errors in various directions in the positioning result can be effectively reduced, and a target function formula adopted by the positioning method is as follows:
f i ＝(x i -x 0 ) 2 +(y i -y 0 ) 2 +(z i -z 0 ) 2 -v 2 (t i -t) 2
wherein (x) 0 ，y 0 ，z 0 ) And (x) i ，y i ，z i ) V is a hypothetical velocity parameter (iterative velocity value) for the hypothetical microseismic source (iterative source value) and for the microseismic sensor coordinates, respectively.
The microseism event automatic positioning system is assembled in an industrial computer to ensure the system operation efficiency.
Compared with the prior art, the invention has the beneficial effects that:
the invention has high stability, is not easy to be interfered, and has strong applicability;
the invention improves the accuracy of microseism event positioning and the microseism monitoring effect;
the invention improves the working efficiency and the economic benefit on the whole.
Drawings
FIG. 1 is a diagram showing the comparison of the filtering front and back of microseism vibration waves by using a data processing system according to the microseism source nonlinear optimization positioning method;
FIG. 2 is a schematic diagram of the result of picking up time by using an improved time-to-time picking algorithm according to the method for nonlinear optimized positioning of microseism focus;
FIG. 3 is a schematic diagram of nonlinear optimized positioning results of a nonlinear optimized positioning method for a microseism focus according to the present invention;
FIG. 4 is a system operation flow chart of a microseism focus nonlinear optimization positioning method provided by the invention.
Detailed Description
The following description of the technical solutions in the embodiments of the present invention will be clear and complete, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments.
Example 1
A nonlinear optimized positioning method of a microseism focus comprises the following steps:
step S1: and (3) data processing: acquiring a microseism vibration wave waveform file by using a microseism data acquisition device, and transmitting the acquired vibration wave waveform file to a built data processing system in a computer for data processing;
step S2: picking up at the time point: after the microseismic signals to be positioned are processed, the microseismic shock wave first arrival time point is required to be picked up, and an improved M-AIC arrival time picking method is used for picking up the microseismic shock wave first arrival time point;
step S3: nonlinear optimized positioning: and after the picking-up is finished, positioning can be performed by using known parameters.
Example two
Referring to fig. 1-4, a method for nonlinear optimized positioning of a microseism focus includes the steps of:
step S1 (collected data-data processing): the microseism data acquisition device is utilized to acquire microseism vibration wave waveform files, the acquired vibration wave waveform files are transmitted to a built data processing system in a computer for data processing, and the data processing comprises: and screening and identifying the microseismic events and filtering microseismic data.
When the field operation environment is complex, the traditional positioning method cannot meet the positioning requirement, and the automatic positioning method of the microseism focus based on the nonlinear optimization theory is adopted, so that the positioning precision is high, the speed measurement is not required in advance, the accuracy and the stability are high, the stability of the traditional positioning method is poor, the effect of selecting different parameters and initial values is greatly affected, the sensitivity is low, the positioning effect is difficult to achieve the expected effect on microseism signals with low signal-to-noise ratio, and the method has the advantages that different microseism signals can be automatically processed by using a built data processing system: because the effective events of the microseism vibration waves are needed for positioning the needed events, the method detects whether the screened events are microseism events or not by using the STA/LTA microseism vibration waves in advance, and then carries out filtering processing on the detected microseism events by using a Kalman filtering algorithm.
Step S2 (to time point pickup): after the microseismic signals to be positioned are processed, the microseismic shock wave first arrival time point is required to be picked up, and the microseismic shock wave first arrival time point is picked up by using an improved M-AIC arrival time picking method.
When the microseism data is too long in trailing and has multiple arrivals, microseism pickup can generate errors, and a microseism event end point is easily picked up, so that final pickup is added into a limiting condition, and only the first arrival wave arrival time point of the calculated M-AIC characteristic value before the maximum value of the amplitude absolute value of the microseism waveform signal is picked up. The improved M-AIC arrival time pickup method can effectively pick up the arrival time of the first arrival of the microseismic shock wave, and the arrival time pickup method adopts the characteristic value calculation formula as follows:
M-AIC(k)＝klg(var(x[1，k]))+(N-k-1)lg(var(x[k+1，N]))
wherein x 1, k is the amplitude value of sampling points 1-k in the microseismic waveform data; n is the length of microseismic waveform data; var () is a variance function.
Step S3 (nonlinear optimized positioning): after the end of the time-of-day pick-up, the positioning can be performed by using known parameters (time-of-day parameters and sensor coordinate parameters).
The method does not need to carry out speed measurement in advance, and can effectively position by only inputting a group of iteration initial values before positioning; the method is based on the principle of nonlinear optimization, combines a mathematical algorithm with a microseismic positioning principle, introduces a hill-down factor in a Newton hill-down method, and strengthens the stability of the algorithm, so that an event that a local optimal solution can be generated in positioning can be effectively avoided; an iteration method is innovated, iteration parameters can be iterated freely in respective dimensions in positioning iteration, so that a positioning result is more scientific and accurate, errors in various directions in the positioning result can be effectively reduced, and a target function formula adopted by the positioning method is as follows:
f i ＝(x i -x 0 ) 2 +(y i -y 0 ) 2 +(z i -z 0 ) 2 -v 2 (t i -t) 2
wherein (x) 0 ，y 0 ，z 0 ) And (x) i ，y i ，z i ) V is a hypothetical velocity parameter (iterative velocity value) for the hypothetical microseismic source (iterative source value) and for the microseismic sensor coordinates, respectively.
The microseism event automatic positioning system is assembled in an industrial computer to ensure the system operation efficiency.
The invention is mainly a microseism automatic positioning technology, and the application flow of the invention is as follows:
step 1, transmitting a microseismic event shock wave into the system of the invention;
and 2, obtaining a microseism focus positioning result with higher precision through a microseism focus automatic positioning technology in the system.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (8)
1. A nonlinear optimized positioning method of a microseism focus is characterized by comprising the following steps:
step S1: and (3) data processing: acquiring a microseism vibration wave waveform file by using a microseism data acquisition device, and transmitting the acquired vibration wave waveform file to a built data processing system in a computer for data processing;
step S2: picking up at the time point: after the microseismic signals to be positioned are processed, the microseismic shock wave first arrival time point is required to be picked up, and an improved M-AIC arrival time picking method is used for picking up the microseismic shock wave first arrival time point;
step S3: nonlinear optimized positioning: and after the picking-up is finished, positioning can be performed by using known parameters.
2. The method for nonlinear optimized positioning of a microseismic source according to claim 1, wherein in step S1, the data processing includes: and screening and identifying the microseismic events and filtering microseismic data.
3. The method of claim 2, wherein the microseismic source selection and identification is specifically a STA/LTA microseismic shock wave detection selection and identification of whether the microseismic event is a microseismic event.
4. The method for nonlinear optimized positioning of a microseismic source according to claim 2, wherein the microseismic data filtering is specifically filtering the detected microseismic event by using a kalman filtering algorithm.
5. The method according to claim 1, wherein in the step S2, the final pick-up is added to the limiting condition, and only the first arrival time point of the calculated M-AIC eigenvalue before the maximum value of the absolute value of the amplitude of the microseism waveform signal is picked up; the characteristic value calculation formula adopted by the time-to-time pick-up method is as follows:
M-AIC(k)＝klg(var(x[1，k]))+(N-k-1)lg(var(x[k+1，N]))
wherein x 1, k is the amplitude value of sampling points 1-k in the microseismic waveform data; n is the length of microseismic waveform data; var () is a variance function.
6. The method for nonlinear optimized positioning of a microseismic source according to claim 1, wherein in the step S3, the objective function used in the positioning method is:
f i ＝(x i -x 0 ) 2 +(y i -y 0 ) 2 +(z i -z 0 ) 2 -y 2 (t i -t) 2
wherein (x) 0 ，y 0 ，z 0 ) And (x) i ，y i ，z i ) The coordinates of the assumed microseismic source and the microseismic sensor, respectively, v is the assumed velocity parameter.
7. The method of claim 6, wherein the microseismic source is assumed to be an iterative source value and the velocity parameter is assumed to be an iterative velocity value.
8. The method according to claim 1, wherein in the step S3, the known parameters are time-of-day parameters and sensor coordinate parameters.
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| CN117991349A (en) * | 2024-04-07 | 2024-05-07 | 吉林大学 | Microseism positioning method based on improved ant lion optimization algorithm |
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