CN107045141B - 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
- Publication number
- CN107045141B CN107045141B CN201710101521.XA CN201710101521A CN107045141B CN 107045141 B CN107045141 B CN 107045141B CN 201710101521 A CN201710101521 A CN 201710101521A CN 107045141 B CN107045141 B CN 107045141B
- Authority
- CN
- China
- Prior art keywords
- focal point
- inverse
- inverse time
- arrival time
- time difference
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 42
- 239000011159 matrix material Substances 0.000 claims abstract description 32
- 238000004364 calculation method Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 2
- 238000012544 monitoring process Methods 0.000 abstract description 11
- 230000008569 process Effects 0.000 abstract description 4
- 230000007547 defect Effects 0.000 abstract description 2
- 238000013499 data model Methods 0.000 abstract 1
- 239000011435 rock Substances 0.000 description 15
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012804 iterative process Methods 0.000 description 2
- 230000004807 localization Effects 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000005065 mining Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000001994 activation Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000012942 design verification Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005553 drilling Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009440 infrastructure construction Methods 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Environmental & Geological Engineering (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Emergency Management (AREA)
- Business, Economics & Management (AREA)
- Acoustics & Sound (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
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 establishes geologic data model to monitoring region and carries out grid dividing, regards each grid node as feature focal point, by complicated rate pattern discretization, establishes slowness matrix to the inverse that each grid node assigns corresponding value of wave speed；With inverse time positioning principle, using each sensor position 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 to obtain inverse time arrival time difference database in order；Using Waveshape Collecting System, is extracted to the waveform signal that sensor receives the then time that focus wave reaches each sensor；Two sensors 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, and quickly positioning is realized to focus.It is this method accurate positioning, high-efficient, 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 technique
In recent years, with the continuous development of Chinese national economy, the speed of infrastructure construction is constantly accelerated, corresponding rock
Geotechnological journey safety problem also continuously emerges.Especially in the rock mass engineering fields such as mining, tunnel piercing and deep adit digging, 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 due to lacking 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 generate Elastic wave, this phenomenon is referred to as microseism.Due to micro-ly
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
Therefore Guan Xing is contained in microseism source signal and is largely destroyed about force-bearing of surrounding rock mass and Geological Defects activation process
Useful information, can infer whether the mechanical behavior of rock material, prediction surrounding rock structure destroy accordingly.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, is to rock
One of the most effective monitoring method of hazard predictions 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 the key that Microseismic monitoring system can play a role.
Traditional microseism localization method is related to iteratively solving the optimal value problem of the function of time mostly, but huge in data volume
In the case where, 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 assume that velocity of wave be constant or piecewise function,
But the velocity field under the conditions of real geology is often sufficiently complex, and rate pattern it is accurate whether directly determine microseism thing
The precision of part positioning.Based on this, the present invention proposes a kind of microseism focus based on the inverse time arrival time difference database quickly side of positioning
Method, the quick positioning suitable for complicated rate pattern.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of microseism/earthquake sources based on inverse time arrival time difference database
Method for rapidly positioning by carrying out numerical modeling and grid dividing to monitoring region in advance, and lays sensor, utilizes sensor
Inverse time, matrix established feature focal point inverse time arrival time difference database, was carried out using the Rapid matching feature of database to practical focus
Positioning, while by improving grid dividing density, it can reach quick, pinpoint purpose, and be suitable for complicated rate pattern.
The specific steps of the method for the present invention are as follows:
A. 1 or more sensor, T are laid in area to be monitoredi(i=1,2 ..., n) indicate 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 grid dividing, using each grid node as representing the position
The feature focal point S seti(i=1,2 ..., n), feature focal point SiPosition coordinates are (xoi,yoi,zoi)；
C. discretization rate pattern, take the inverse of each mesh point velocity of wave in step b establish 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 SiEstablish inverse time arrival time difference matrix F Ni, and then establish feature focal point SiInverse time
Arrival time difference database；
F. shape information acquisition system is utilized, focus wave is extracted to the waveform signal that sensor receives and reaches each sensing
The then time of device；
G. the arrival time difference for calculating any two sensors, establishes focus arrival time difference matrix, and with feature focal point SiInverse time
Arrival time difference database carries out matching search, is positioned real-time, quickly to focus.
Wherein, laid sensor is wave detector in the method for the present invention.
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, that is, feature focal point to duration u (x, y, z), adjacent node is taken to carry out to duration poor against the wind
Point, that is, meet following formula:
(a)+=max (a, 0)
Wherein:
Gaussian iteration solution is carried out for above formula, the number of iterations is more, and computational efficiency is low, therefore proposes 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 R3Optimal solution is calculated at grid node (most in secondary search
Small value)；
Specific difference algorithm:
1. enabling ux,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. grid dividings model, Gridding length h=dx=dy=dz.
2. enabling u*=W+r (x, y, z) * h, if u*≤ V, u*As iteration updated value, otherwise
3. if u*≤ U, u*As iteration updated value, otherwise
4. carrying out next iteration until meeting the condition of convergence.
In step e, inverse time arrival time difference database to establish principle as follows:
To sensor Ti, with inverse time positioning mode, calculate inverse time of each feature focal point in model then matrix Ni,
Then by n inverse time, then matrix mutually makes the difference to obtain in sequenceA inverse time arrival time difference matrix F Ni, by each feature focus
Point information and its corresponding inverse time arrival time difference fromA inverse time arrival time difference matrix extracts to form an ordered series of numbers input database,
Establish 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 is confirmed as the physical location of the focus.
The advantageous effects of the above technical solutions of the present invention are as follows:
The characteristics of the present invention is based on the search of database Rapid matching, in practical micro seismic monitoring engineering, according to sensor position
It sets, establishes feature focal point inverse time arrival time difference database in advance, without carrying out function optimization iterative solution to focus, therefore greatly
The time required to reducing seismic source location, meanwhile, using according to drilling, the complicated rate pattern calculating that the information such as prospecting are established is arrived
When, greatly improve positioning accuracy.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.
Detailed description of the invention
Fig. 1 is the microseism of the invention based on inverse time arrival time difference database/earthquake source method for rapidly positioning embodiment
Model schematic；
Fig. 2 is monitoring regional model grid dividing example, grid number 10*10*10, side length of element 1m；
Fig. 3 is rate pattern in monitoring region (by taking 10*10*10 grid exponential model as an example)；
Fig. 4 is position error comparison diagram under different mesh-densities；
Fig. 5 is that the method for the present invention calculates time-consuming comparison diagram under different mesh-densities.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached 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 includes the following steps:
A. 1 or more sensor, T are laid in area to be monitoredi(i=1,2 ..., n) indicate 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 grid dividing, using each grid node as representing the position
The feature focal point S seti(i=1,2 ..., n), feature focal point SiPosition coordinates are (xoi,yoi,zoi)；
C. discretization rate pattern, take the inverse of each mesh point velocity of wave in step b establish 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 SiEstablish inverse time arrival time difference matrix F Ni, and then establish feature focal point SiInverse time
Arrival time difference database；
F. shape information acquisition system is utilized, focus wave is extracted to the waveform signal that sensor receives and reaches each sensing
The then time of device；
G. the arrival time difference for calculating any two sensors, establishes focus arrival time difference matrix, and with feature focal point SiInverse time
Arrival time difference database carries out matching search, is positioned real-time, quickly to focus.
In the actual operation process, the specific steps are as follows:
It (1) is verifying effectiveness of the invention, design verification model is as shown in Figure 1, monitor region complexity rate pattern such as
Shown in Fig. 3, it is assumed that have 8 sensor T1, T2, T3, T4, T5, T6, T7, T8 is respectively arranged in eight vertex positions of cube, mould
Quasi- actual measurement focus P1, P2, P3, P4, P5, P6, various point locations coordinate are 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 grid dividing.
This example uses four kinds of mesh-density models altogether, by taking one of which as an example, as shown in Fig. 2, model partition grid is close
Degree is 10 × 10 × 10, side length of element 1m, and totally 1000 feature focal points can be with sensor Ti(i=1,2,3,4,5,6,7,
8) 8 inverse time then matrix is calculated with method for fast searching (FSM) for inverse time focal point.
(3) the inverse time arrival time difference matrix for calculating each feature focal point, establishes inverse time arrival time difference database.
In the case where there is 8 sensors, each feature focal point can be obtained altogetherA inverse time arrival time difference, and form
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 it arranges
Column, establish the inverse time arrival time difference database for characterizing this feature focal point arrival time difference information.
(4) shape information acquisition system is utilized, focus wave is extracted to the waveform signal that sensor receives and reaches each biography
The then time of sensor.
(5) the arrival time difference matrix of focus, and utilization similarity are surveyed in arrival time difference between calculating two sensors, foundation in order
It is subjected to matching search with feature focal point inverse time arrival time difference database with algorithm, it is fixed real-time, quickly to carry out to actual measurement focus
Position, can quickly seek its position coordinates, and worst error is not more than grid diagonal line length.
Under different mesh-densities, the comparison of the method for the present invention position error positions as shown in figure 4, as mesh-density increases
Precision is obviously improved.Conventional mapping methods are based on constant velocity model more and are positioned, and for complicated rate pattern, positioning accuracy is very
Difference even not can be carried out seismic source location, and the method for the present invention still maintains very high precision under complicated rate pattern.
Under different mesh-densities, the method for the present invention calculates time-consuming comparison as shown in figure 5, as shown in Figure 5, compare other biographies
System localization method, the method for the present invention computational efficiency is high, and as mesh-density increases, and it is little to calculate time-consuming increasing degree.
In conclusion in practical engineering applications, for the requirement for guaranteeing location accuracy, it is close necessarily to will increase grid search
Degree pre-establishes inverse time arrival time difference database due to eliminating a large amount of iterative process of conventional mapping methods, therefore the method for the present invention
Microseism seismic source location efficiency can be increased substantially, to cause the timely prediction of calamity Dynamic Loading to provide technology branch for rock mass engineering project
It holds.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principles of the present invention, several improvements and modifications can also be made, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (1)
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. 1 or more sensor, T are laid in area to be monitoredi(i=1,2, K, n) indicates i-th of sensor, sensor Ti's
Position coordinates are (xi,yi,zi)；
B. numerical modeling is carried out to area to be monitored, and carries out grid dividing, using each grid node as representing the position
Feature focal point Si(i=1,2 ..., n), feature focal point SiPosition coordinates are (xoi,yoi,zoi)；
C. discretization rate pattern takes the inverse of each mesh point velocity of wave in step b to establish 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 SiEstablish inverse time arrival time difference matrix F Ni, and then establish feature focal point SiInverse time then
Difference data library；
F. shape information acquisition system is utilized, focus wave is extracted to the waveform signal that sensor receives and reaches each sensor
The then time；
G. the arrival time difference for calculating any two sensors, establishes focus arrival time difference matrix, and with feature focal point SiInverse time arrival time difference
Database carries out matching search, is positioned real-time, quickly to focus；
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 R3Minimum value at grid node is calculated in secondary search, as optimal
Solution；
In the step e, inverse time arrival time difference database to establish principle as follows:
To sensor Ti, with inverse time positioning mode, calculate inverse time of each feature focal point in model then matrix Ni, then
By n inverse time, then matrix mutually makes the difference to obtain in sequenceA inverse time arrival time difference matrix F Ni, each feature focal point is believed
Breath and its corresponding inverse time arrival time difference fromA inverse time arrival time difference matrix extracts to form an ordered series of numbers input database, establishes special
Levy focal point SiInverse time arrival time difference database；
Sensor is wave detector in the step a；
Focus arrival time difference matrix and feature focal point S in step giInverse time arrival time difference database matching use similarity mode
Search method, the high feature focal point of similarity are confirmed as the physical location of the focus.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710101521.XA CN107045141B (en) | 2017-02-24 | 2017-02-24 | Microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710101521.XA CN107045141B (en) | 2017-02-24 | 2017-02-24 | Microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107045141A CN107045141A (en) | 2017-08-15 |
| CN107045141B true CN107045141B (en) | 2019-05-10 |
Family
ID=59545511
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710101521.XA Active CN107045141B (en) | 2017-02-24 | 2017-02-24 | Microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107045141B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108957404A (en) * | 2018-05-18 | 2018-12-07 | 中国科学技术大学 | A kind of method of earthquake locating, apparatus and system |
| CN109188515B (en) * | 2018-10-31 | 2021-02-26 | 中国石油化工股份有限公司 | Method and system for calculating position of seismic source of microseism monitoring crack |
| CN110907991B (en) * | 2019-12-11 | 2021-03-16 | 重庆大学 | Seismic source positioning method and system based on data field potential value and readable storage medium |
| CN112462415B (en) * | 2020-11-02 | 2023-07-21 | 中国电子科技集团公司第三研究所 | Method and device for positioning multiple vibration sources |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102495425A (en) * | 2011-11-14 | 2012-06-13 | 北京科技大学 | Energy-based method for automatically locating earthquake focus of microearthquake |
| CN103105624A (en) * | 2011-11-11 | 2013-05-15 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Longitudinal and transversal wave time difference positioning method based on base data technology |
| CN104076392A (en) * | 2014-05-28 | 2014-10-01 | 中国矿业大学(北京) | Microearthquake focus positioning combined inversion method based on grid search and Newton iteration |
| CN105510880A (en) * | 2014-09-23 | 2016-04-20 | 中国石油化工股份有限公司 | Microseism focus positioning method based on double-difference method |
| CN106094021A (en) * | 2016-06-01 | 2016-11-09 | 北京科技大学 | A kind of microseism focus method for rapidly positioning based on arrival time difference data base |
| CN106154334A (en) * | 2015-04-13 | 2016-11-23 | 中石化石油工程地球物理有限公司胜利分公司 | Down-hole based on grid search micro-seismic event real time inversion localization method |
| CN106199520A (en) * | 2015-05-30 | 2016-12-07 | 中国石油化工股份有限公司 | Microseism seismic source location method and apparatus |
| CN106249297A (en) * | 2015-06-08 | 2016-12-21 | 中国石油化工股份有限公司 | Fracturing microseism seismic source location method and system based on Signal estimation |
-
2017
- 2017-02-24 CN CN201710101521.XA patent/CN107045141B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103105624A (en) * | 2011-11-11 | 2013-05-15 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Longitudinal and transversal wave time difference positioning method based on base data technology |
| CN102495425A (en) * | 2011-11-14 | 2012-06-13 | 北京科技大学 | Energy-based method for automatically locating earthquake focus of microearthquake |
| CN104076392A (en) * | 2014-05-28 | 2014-10-01 | 中国矿业大学(北京) | Microearthquake focus positioning combined inversion method based on grid search and Newton iteration |
| CN105510880A (en) * | 2014-09-23 | 2016-04-20 | 中国石油化工股份有限公司 | Microseism focus positioning method based on double-difference method |
| CN106154334A (en) * | 2015-04-13 | 2016-11-23 | 中石化石油工程地球物理有限公司胜利分公司 | Down-hole based on grid search micro-seismic event real time inversion localization method |
| CN106199520A (en) * | 2015-05-30 | 2016-12-07 | 中国石油化工股份有限公司 | Microseism seismic source location method and apparatus |
| CN106249297A (en) * | 2015-06-08 | 2016-12-21 | 中国石油化工股份有限公司 | Fracturing microseism seismic source location method and system based on Signal estimation |
| CN106094021A (en) * | 2016-06-01 | 2016-11-09 | 北京科技大学 | A kind of microseism focus method for rapidly positioning based on arrival time difference data base |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107045141A (en) | 2017-08-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106094021B (en) | A kind of microseism focus method for rapidly positioning based on arrival time difference database | |
| CN107045141B (en) | Microseism based on inverse time arrival time difference database/earthquake source method for rapidly positioning | |
| Dong et al. | Velocity-free MS/AE source location method for three-dimensional hole-containing structures | |
| Feng et al. | Sectional velocity model for microseismic source location in tunnels | |
| Zhang et al. | Parameter prediction of hydraulic fracture for tight reservoir based on micro-seismic and history matching | |
| MX2015004001A (en) | Propagating fracture plane updates. | |
| CN102609982B (en) | Topology discovery method of space geological data based on unstructured mode | |
| Feng et al. | Performance and feasibility analysis of two microseismic location methods used in tunnel engineering | |
| CN109738940B (en) | Acoustic emission/microseismic event positioning method under condition of existing empty zone | |
| CN114035228B (en) | Tunnel seismic wave velocity inversion method and system based on deep learning | |
| CN103105624A (en) | Longitudinal and transversal wave time difference positioning method based on base data technology | |
| CN108845358B (en) | Tomography and the recognition methods of structural anomaly body and device | |
| CN109459787B (en) | coal mine underground structure imaging method and system based on seismic channel wave full-waveform inversion | |
| CN101719127A (en) | Quick systemic checking method of data quality of geological and mineral spatial database | |
| Wang et al. | An auto-detection network to provide an automated real-time early warning of rock engineering hazards using microseismic monitoring | |
| CN113189644B (en) | Microseismic source positioning method and system | |
| Ma et al. | Intelligent location of microseismic events based on a fully convolutional neural network (FCNN) | |
| Yin et al. | A novel tree-based algorithm for real-time prediction of rockburst risk using field microseismic monitoring | |
| CN108594299A (en) | High ferro intelligent early-warning method, apparatus and system | |
| CN103105622A (en) | Homomorphous wave time difference positioning method based on data base technology | |
| WO2018040592A1 (en) | Method and system for epicentre positioning in microseism monitoring | |
| Zhu et al. | The effect of P-and S-phase arrivals on the accuracy of microseismic source location | |
| CN109709602A (en) | A kind of remote detection sonic wave shift imaging method, apparatus and system | |
| CN104020508A (en) | Direct ray tracking algorithm for geological radar chromatography detecting | |
| CN107817524A (en) | The method and apparatus of three-dimensional seismic tomography |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |