CN107045141A - Microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning - Google Patents
Microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning Download PDFInfo
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- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
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Abstract
The present invention provides a kind of microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning, belongs to vibroseis positioning techniques field.This method sets up geologic data model to monitored area and carries out mesh generation, regards each grid node as feature focal point, and by complicated rate pattern discretization, slowness matrix is set up to the inverse that each grid node assigns corresponding value of wave speed；With inverse time positioning principle, using each sensing station as inverse time focal point, feature focal point inverse time then matrix is obtained with fast search process；By inverse time, then matrix makes the difference obtain inverse time arrival time difference database in order；Using Waveshape Collecting System, the waveform signal received to sensor extracts the then time that focus ripple reaches each sensor；Two sensorses arrival time difference is calculated in order and carries out matching search with inverse time arrival time difference database, obtains error minimal characteristic focal point, quick positioning is realized to focus.This method accurate positioning, efficiency high, overcome the defect of existing method.
Description
Technical field
The present invention relates to vibroseis positioning techniques field, particularly relate to a kind of microseism based on inverse time arrival time difference database/
Earthquake source method for rapidly positioning.
Background technology
In recent years, continuing to develop with Chinese national economy, the speed of infrastructure construction is constantly accelerated, corresponding rock
Geotechnological journey safety problem also continuously emerges.Especially in rock mass engineering fields such as mining, tunnel piercing and deep adit diggings, impact
The sudden dynamic disaster such as ground pressure, rock burst seriously threatens the security of the lives and property of the people.Although these accidental pollution events one
As have certain sign before generation, but be due to lack accurate prediction, often cause heavy losses to personnel's property.
In the rock mass engineering projects such as mine, tunnel piercing, deep adit digging, mining work activities can cause regional area in rock mass
Deformation or rupture, cause strain energy to discharge rapidly and produce Elastic wave, this phenomenon is referred to as microseism.Due to micro-
Shake is the attendant phenomenon of rock mass deformation, crack initiation and expansion process, and the mechanical behavior of it and surrounding rock structure has close phase
Guan Xing, therefore, contains substantial amounts of destroyed on force-bearing of surrounding rock mass and Geological Defects activation process in microseism source signal
Useful information, the mechanical behavior of rock material can be inferred accordingly, and whether prediction surrounding rock structure destroys.It is remote to country rock in recent years
The On Microseismic Monitoring Technique that field causes calamity Dynamic Loading to carry out Monitoring and forecasting system in real-time is widely used to rock mass engineering project field, and it is to rock
One of the maximally effective monitoring method of hazard prediction forecast such as collapse for quick-fried, bump and goaf.Microseism seismic source location is
The core of On Microseismic Monitoring Technique, can fast, accurately be positioned be key that Microseismic monitoring system can play a role.
Traditional microseism localization method is related to the optimal value problem of the iterative function of time mostly, but huge in data volume
In the case of, iterative process can waste the dynamic disaster prediction and warning times of a large amount of preciousnesses, therefore to focus it is quick, accurately ask
Solution is the striving direction of microseism location algorithm.Meanwhile, traditional Location Theory generally assumes that velocity of wave for constant or piecewise function,
But the velocity field under the conditions of real geology is often sufficiently complex, and the whether accurate of rate pattern directly determines microseism thing
The precision of part positioning.Based on this, the present invention proposes a kind of microseism focus based on inverse time arrival time difference database quickly side of positioning
Method, it is adaptable to the quick positioning of complicated rate pattern.
The content of the invention
The technical problem to be solved in the present invention is to provide a kind of microseism/earthquake source based on inverse time arrival time difference database
Method for rapidly positioning, by carrying out numerical modeling and mesh generation to monitored area in advance, and lays sensor, utilizes sensor
Inverse time, matrix set up feature focal point inverse time arrival time difference database, and actual focus is carried out using the Rapid matching feature of database
Positioning, while by improving mesh generation density, quick, pinpoint purpose is can reach, and suitable for complicated rate pattern.
The inventive method is concretely comprised the following steps：
A. the sensor of more than 1, T are laid in area to be monitoredi(i=1,2 ..., n) represent i-th of sensor, pass
Sensor TiPosition coordinates be (xi,yi,zi)；
B. numerical modeling is carried out to area to be monitored, and carries out mesh generation, using each grid node as representing the position
The feature focal point S puti(i=1,2 ..., n), feature focal point SiPosition coordinates is (xoi,yoi,zoi)；
C. discretization rate pattern, take each mesh point velocity of wave in step b inverse set up slowness model matrix r (x, y,
z)；
D. using each sensor as inverse time focal point, inverse time location Calculation feature focal point S is carried out with fast search processi
Inverse time then matrix Ni；
E. it is directed to each feature focal point SiSet up inverse time arrival time difference matrix F Ni, and then set up feature focal point SiInverse time
Arrival time difference database；
F. shape information acquisition system is utilized, the waveform signal received to sensor extracts focus ripple and reaches each sensing
The then time of device；
G. calculate the arrival time difference of any two sensorses, set up focus arrival time difference matrix, and with feature focal point SiInverse time
Arrival time difference database carries out matching search, and focus is positioned real-time.
Wherein, institute's laying sensor is wave detector in the inventive method.
In above-mentioned steps d, calculating inverse time with fast search process (FSM), then matrix is specific as follows：
This method is for solving the problems, such as elastic wave propagation, with eikonal equation (Eikonal Equation) by propagation path
Geometrization.Eikonal equation citation form is as follows：
| ▽ u (x) |=r (x), x ∈ Rn
u(x0)=0, x0∈Rn
Wherein, r (x) is dielectric model slowness；
u(x0)=0 is primary condition；
U (x)=φ (x) is boundary condition.
For any grid node be feature focal point to duration u (x, y, z), take adjacent node to duration carry out against the wind it is poor
Point, that is, meet equation below：
(a)+=max (a, 0)
Wherein：
Gaussian iteration solution is carried out for above formula, iterations is more, computational efficiency is low, therefore propose following algorithm：
(1) maximum is assigned to then u (x, y, z) at grid node；
(2) primary condition, boundary condition, rate pattern etc. are set；
(3) an iteration is carried out with contrary wind calculus of finite differences, pass through R3Secondary search calculating obtains at grid node optimal solution (most
Small value)；
Specific difference algorithm：
1. u is madex,min, uy,min, uz,minAccording to W≤V≤U is arranged as from big to small, then updated value is iteration posterior nodal point
u*, now only consider etc. mesh generation model, Gridding length h=dx=dy=dz.
2. u is made*=W+r (x, y, z) * h, if u*≤ V, u*As iteration updated value, otherwise
If 3. u*≤ U, u*As iteration updated value, otherwise
4. next iteration is carried out until meeting the condition of convergence.
In step e, inverse time arrival time difference database to set up principle as follows：
To sensor Ti, with inverse time positioning mode, calculate inverse time of the feature focal point of each in model then matrix Ni,
Then by n inverse time, then matrix mutually makes the difference obtain in sequenceIndividual inverse time arrival time difference matrix F Ni, by each feature focus
Point information and its corresponding inverse time arrival time difference fromIndividual inverse time arrival time difference matrix extracts to form an ordered series of numbers input database, builds
Vertical feature focal point SiInverse time arrival time difference database.
Focus arrival time difference matrix and feature focal point S in step giInverse time arrival time difference database matching use similarity
Search method is matched, the high feature focal point of similarity confirms as the physical location of the focus.
The above-mentioned technical proposal of the present invention has the beneficial effect that：
The characteristics of present invention is searched for based on database Rapid matching, in actual micro seismic monitoring engineering, according to sensor position
Put, feature focal point inverse time arrival time difference database is set up in advance, without carrying out function optimization iterative to focus, therefore greatly
The time required to reducing seismic source location, meanwhile, arrived using according to drilling, the complicated rate pattern that the information such as prospecting is set up is calculated
When, it is greatly enhanced positioning precision.Therefore rock mass engineering project dynamic disaster early warning can be quickly and efficiently carried out, to staff and set
It is standby that certain effective and safe guarantee is provided.
Brief description of the drawings
Fig. 1 is the microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning embodiment of the invention
Model schematic；
Fig. 2 is that monitored area model meshes divide example, and grid number is 10*10*10, and side length of element is 1m；
Fig. 3 is rate pattern in monitored area (by taking 10*10*10 grid exponential models as an example)；
Fig. 4 is position error comparison diagram under different mesh-densities；
Fig. 5 is the time-consuming comparison diagram of the inventive method calculating under different mesh-densities.
Embodiment
To make the technical problem to be solved in the present invention, technical scheme and advantage clearer, below in conjunction with accompanying drawing and tool
Body embodiment is described in detail.
The present invention provides a kind of microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning.
This method mainly comprises the following steps：
A. the sensor of more than 1, T are laid in area to be monitoredi(i=1,2 ..., n) represent i-th of sensor, pass
Sensor TiPosition coordinates be (xi,yi,zi)；
B. numerical modeling is carried out to area to be monitored, and carries out mesh generation, using each grid node as representing the position
The feature focal point S puti(i=1,2 ..., n), feature focal point SiPosition coordinates is (xoi,yoi,zoi)；
C. discretization rate pattern, take each mesh point velocity of wave in step b inverse set up slowness model matrix r (x, y,
z)；
D. using each sensor as inverse time focal point, inverse time location Calculation feature focal point S is carried out with fast search processi
Inverse time then matrix Ni；
E. it is directed to each feature focal point SiSet up inverse time arrival time difference matrix F Ni, and then set up feature focal point SiInverse time
Arrival time difference database；
F. shape information acquisition system is utilized, the waveform signal received to sensor extracts focus ripple and reaches each sensing
The then time of device；
G. calculate the arrival time difference of any two sensorses, set up focus arrival time difference matrix, and with feature focal point SiInverse time
Arrival time difference database carries out matching search, and focus is positioned real-time.
In actual mechanical process, comprise the following steps that：
(1) for checking effectiveness of the invention, design verification model as shown in figure 1, monitored area complexity rate pattern such as
Shown in Fig. 3, it is assumed that there are 8 sensors T1, T2, T3, T4, T5, T6, T7, T8 to be respectively arranged in eight vertex positions of cube, mould
Intend actual measurement focus P1, P2, P3, P4, P5, P6, various point locations coordinate is as shown in Table 1 and Table 2.
Table 1
| Sensor | X/m | Y/m | Z/m |
| T1 | 10 | 0 | 10 |
| T2 | 10 | 10 | 10 |
| T3 | 10 | 0 | 0 |
| T4 | 10 | 0 | 0 |
| T5 | 0 | 0 | 10 |
| T6 | 0 | 10 | 10 |
| T7 | 0 | 0 | 0 |
| T8 | 0 | 10 | 0 |
Table 2
| Survey focus | X/m | Y/m | Z/m |
| P1 | 8.3123 | 3.3635 | 7.2457 |
| P2 | 8.3256 | 4.3657 | 6.1251 |
| P3 | 1.1658 | 7.3479 | 9.1866 |
| P4 | 4.3746 | 2.1267 | 2.2543 |
| P5 | 5.3795 | 4.2587 | 1.1568 |
| P6 | 2.1964 | 8.1253 | 4.5894 |
(2) numerical modeling is carried out to micro seismic monitoring region, and carries out mesh generation.
This example is altogether using four kinds of mesh-density models, by taking one of which as an example, as shown in Fig. 2 model partition grid is close
Spend for 10 × 10 × 10, side length of element is 1m, totally 1000 feature focal points, can be with sensor Ti(i=1,2,3,4,5,6,7,
8) calculated for inverse time focal point with method for fast searching (FSM) and obtain 8 inverse time then matrix.
(3) the inverse time arrival time difference matrix of each feature focal point is calculated, inverse time arrival time difference database is set up.
In the case where there is 8 sensors, each feature focal point can obtain altogetherIndividual inverse time arrival time difference, and constitute
One inverse time arrival time difference matrix N comprising 56 datai, by inverse time arrival time difference matrix data according to feature focal point SiAgain arrange
Row, set up the inverse time arrival time difference database for characterizing this feature focal point arrival time difference information.
(4) shape information acquisition system is utilized, the waveform signal received to sensor extracts focus ripple and reaches each biography
The then time of sensor.
(5) arrival time difference between two sensorses is calculated in order, sets up the arrival time difference matrix of actual measurement focus, and utilize similarity
It is carried out matching search with feature focal point inverse time arrival time difference database with algorithm, it is fixed real-time to carry out actual measurement focus
Position, can quickly seek its position coordinates, its worst error is not more than grid diagonal line length.
Under different mesh-densities, the contrast of the inventive method position error is as shown in figure 4, as mesh-density increases, position
Precision is obviously improved.Positioned more than conventional mapping methods based on constant velocity model, for complicated rate pattern, positioning precision is very
Difference even can not carry out seismic source location, and the inventive method still maintains very high precision under complicated rate pattern.
Under different mesh-densities, the inventive method calculates time-consuming contrast as shown in figure 5, as shown in Figure 5, compare other biographies
System localization method, the inventive method computational efficiency is high, and as mesh-density increases, calculates time-consuming increasing degree little.
In summary, in practical engineering application, to ensure the requirement of location accuracy, grid search will necessarily be increased close
Degree, due to eliminating a large amount of iterative process of conventional mapping methods, pre-establishes inverse time arrival time difference database, therefore the inventive method
Microseism seismic source location efficiency can be increased substantially, so that the timely prediction for causing calamity Dynamic Loading for rock mass engineering project provides technology branch
Hold.
Described above is the preferred embodiment of the present invention, it is noted that for those skilled in the art
For, on the premise of principle of the present invention is not departed from, some improvements and modifications can also be made, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (5)
1. a kind of microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning, it is characterised in that：Including with
Lower step：
A. the sensor of more than 1, T are laid in area to be monitoredi(i=1,2 ..., n) represent i-th of sensor, sensor Ti
Position coordinates be (xi,yi,zi)；
B. numerical modeling is carried out to area to be monitored, and carries out mesh generation, using each grid node as representing the position
Feature focal point Si(i=1,2 ..., n), feature focal point SiPosition coordinates is (xoi,yoi,zoi)；
C. discretization rate pattern, takes the inverse of each mesh point velocity of wave in step b to set up slowness model matrix r (x, y, z)；
D. using each sensor as inverse time focal point, inverse time location Calculation feature focal point S is carried out with fast search processiInverse time
Then matrix Ni；
E. it is directed to each feature focal point SiSet up inverse time arrival time difference matrix F Ni, and then set up feature focal point SiInverse time then
Difference data storehouse；
F. shape information acquisition system is utilized, the waveform signal received to sensor extracts focus ripple and reaches each sensor
Then time；
G. calculate the arrival time difference of any two sensorses, set up focus arrival time difference matrix, and with feature focal point SiInverse time arrival time difference
Database carries out matching search, and focus is positioned real-time.
2. the microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning according to claim 1, its
It is characterised by：Sensor is wave detector in the step a.
3. the microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning according to claim 1, its
It is characterised by：In the step d, circular is as follows：
(1) maximum is assigned to then u (x, y, z) at grid node；
(2) primary condition, boundary condition, rate pattern are set；
(3) an iteration is carried out with contrary wind calculus of finite differences, pass through R3Secondary search calculating obtains minimum value at grid node, as optimal
Solution.
4. the microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning according to claim 1, its
It is characterised by：In the step e, inverse time arrival time difference database to set up principle as follows：
To sensor Ti, with inverse time positioning mode, calculate inverse time of the feature focal point of each in model then matrix Ni, then
By n inverse time, then matrix mutually makes the difference obtain in sequenceIndividual inverse time arrival time difference matrix F Ni, each feature focal point is believed
Breath and its corresponding inverse time arrival time difference fromIndividual inverse time arrival time difference matrix extracts to form an ordered series of numbers input database, sets up special
Levy focal point SiInverse time arrival time difference database.
5. the microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning according to claim 1, its
It is characterised by：Focus arrival time difference matrix and feature focal point S in the step giInverse time arrival time difference database matching use
Similarity mode search method, the high feature focal point of similarity confirms as the physical location of the focus.
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| CN110907991A (en) * | 2019-12-11 | 2020-03-24 | 重庆大学 | Seismic source positioning method and system based on data field potential value and readable storage medium |
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