CN106918836A - Borehole strain data exception extraction method based on principal component analysis - Google Patents
Borehole strain data exception extraction method based on principal component analysis Download PDFInfo
- Publication number
- CN106918836A CN106918836A CN201710205283.7A CN201710205283A CN106918836A CN 106918836 A CN106918836 A CN 106918836A CN 201710205283 A CN201710205283 A CN 201710205283A CN 106918836 A CN106918836 A CN 106918836A
- Authority
- CN
- China
- Prior art keywords
- data
- principal component
- borehole strain
- borehole
- strain data
- 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.)
- Granted
Links
- 238000000513 principal component analysis Methods 0.000 title claims abstract description 17
- 238000000605 extraction Methods 0.000 title claims abstract description 12
- 239000011159 matrix material Substances 0.000 claims abstract description 28
- 238000006243 chemical reaction Methods 0.000 claims abstract description 9
- 238000010586 diagram Methods 0.000 claims description 4
- 239000002243 precursor Substances 0.000 abstract description 9
- 230000002159 abnormal effect Effects 0.000 abstract description 5
- 238000000034 method Methods 0.000 abstract description 5
- 230000003203 everyday effect Effects 0.000 abstract description 2
- 238000012360 testing method Methods 0.000 abstract description 2
- 238000004458 analytical method Methods 0.000 description 6
- 230000005856 abnormality Effects 0.000 description 5
- 241001269238 Data Species 0.000 description 3
- 238000000354 decomposition reaction Methods 0.000 description 3
- 238000005553 drilling Methods 0.000 description 3
- 230000002354 daily effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000011888 foil Substances 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000000737 periodic effect Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000010008 shearing Methods 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- GNFTZDOKVXKIBK-UHFFFAOYSA-N 3-(2-methoxyethoxy)benzohydrazide Chemical compound COCCOC1=CC=CC(C(=O)NN)=C1 GNFTZDOKVXKIBK-UHFFFAOYSA-N 0.000 description 1
- FGUUSXIOTUKUDN-IBGZPJMESA-N C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 Chemical compound C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 FGUUSXIOTUKUDN-IBGZPJMESA-N 0.000 description 1
- 208000033999 Device damage Diseases 0.000 description 1
- 206010033799 Paralysis Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 239000003822 epoxy resin Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000000116 mitigating effect Effects 0.000 description 1
- 229920000647 polyepoxide Polymers 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
- G01V1/01—Measuring or predicting earthquakes
Landscapes
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- Remote Sensing (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
First it is that the borehole strain data sequence of the same station is carried out into strain conversion the present invention relates to a kind of borehole strain data exception extraction method based on principal component analysis, the data after conversion is pre-processed；By pretreated borehole strain data configuration an into matrix；And the matrix to every day carries out principal component analysis, to obtain the characteristic value and characteristic vector of each matrix；The characteristic value that will be obtained is corresponding with seismic events with the characteristic vector angle calculated, to obtain abnormal testing result.Borehole strain data can be analyzed using the method for principal component analysis effectively by the present invention, the correlation of item is respectively surveyed according to borehole strain, possible Earthquake Precursor Anomalies are extracted.Borehole strain data exception extraction method of the present invention, is respectively characterized the faint change of the earth's crust using the characteristic value in principal component analysis and characteristic vector angle；Realize the accurate extraction to borehole strain data exception in the case where there are stronger ambient interferences.
Description
Technical field
The present invention relates to a kind of seismic precursor observation data method for detecting abnormality, and in particular to one kind is based on principal component analysis
Borehole strain data exception extraction method.
Background technology
Geoscience is a subject based on observation and survey data, and the constantly improve to observation system is development
Geoscience, the only way for mitigating disaster.Earth surface deform and the earth's crust inside tectonic movement and its generation variously
Matter disaster all acts on closely related with crustal stress, and the change of Crustal stress state is to cause fracture, fold or even generation earthquake
Most direct reason.Borehole strain observation is found by the fine observation changed according to Time Continuous to stratum internal strain state
Spatial and temporal distributions and development and change rule with being adjusted after (length) mid-term-short-term-imminent earthquake and shake for grasping earthquake strain omen, be
Important earthquake precursor observation means.Borehole strain observation is easy by high precision, strong antijamming capability, the observation of many survey items, instrument
Become the Precursor means for being only second to GPS observations the features such as safeguarding.
Principal component analytical method can know the signal of relative weak in primary signal from compared with strong jamming background in theory
Not out, earth's crust change small-signal is submerged in compared with strong jamming background in solving the problems, such as Borehole strain observation.
CN104390733A discloses a kind of determination method of crustal stress size and Orientation, in the epoxy resin of measurement stress
Peripherally disposed three strain rosettes on hollow inclusion, the angle of adjacent strain rosette is 120 °, there is four on each strain rosette
Foil gauge, the foil gauge on each strain rosette rotates 45 ° of settings successively；Using 12 different directions strain values on circumferencial direction,
Crustal stress and stress direction can accurately and effectively be calculated.
CN202452947U discloses a kind of Four component seismic technology observation system, including the data storage set on well
The component strain instrument of master four and the signal cable of connection underground that web-transporting device, underground are set, are also set including underground
The component strain instrument of auxiliary four.By setting a master, an auxiliary two four component strain instrument in observation system, system is increased
Reliability, it is to avoid because a device damages the situation for allowing for whole system paralysis.
Qiu Zehua etc. (analyzed with the small echo-rate that transfinites and extract Ningshan platform Wenchuan earthquake body strain exception, 2012) utilizes small echo
To aunt, our the component borehole strain data of the station four are studied with the improved rate analysis method that transfinites for decomposition, and trickle earthquake is different
Often change fine extracting.Chi Shunliang etc. (before the shake of Mount Lushan Ms7.0 earthquakes in 2013 and imminent earthquake strain abnormality, 2013) profits
With our component Borehole strain observation data of the station four of Mount Lushan BEFORE AND AFTER EARTHQUAKE aunt, earthquake is analyzed with shake signal.But to current
Untill, there is not yet borehole strain data are carried out with the report of anomaly extracting with the method for principal component analysis.
The content of the invention
The purpose of the present invention is that for above-mentioned the deficiencies in the prior art, there is provided a kind of drilling based on principal component analysis
Strain data abnormal extraction method.
The purpose of the present invention is achieved through the following technical solutions：
The present invention carries out anomaly extracting to borehole strain data using principal component analysis, is first by the drilling of the same station
Strain data sequence carries out strain conversion, and the data after conversion are pre-processed；By pretreated borehole strain data structure
Cause a matrix；And the matrix to every day carries out principal component analysis, to obtain the characteristic value and characteristic vector of each matrix；
The characteristic value that will be obtained is corresponding with seismic events with the characteristic vector angle calculated, to obtain abnormal testing result.
Borehole strain data can be analyzed using the method for principal component analysis effectively by the present invention, it is each according to borehole strain
The correlation of item is surveyed, possible Earthquake Precursor Anomalies are extracted.
A kind of borehole strain data exception extraction method based on principal component analysis, comprises the following steps：
A, typing borehole strain data, and the checking of data validity is carried out, "Yes" carries out next step；
B, strain conversion is carried out to borehole strain data；
C, data prediction；
D, making sample data；
E, the covariance matrix for seeking sample data；
F, the characteristic value and characteristic vector of obtaining covariance matrix；
G, the angle for obtaining feature value vector；
H, output characteristic value change curve；
I, output characteristic vector angle change curve and statistic histogram.
Step a, described typing borehole strain data are to choose a four component borehole strain numbers of the station from different places
According to, be fabricated to according to minute value sample time series.The checking of data validity is that, according to different components, data are represented by
S1,S2,S3,S4；It is right according to the circular hole radial deformation as derived from perforated flat plate elastic theory model and the relational expression of regional stress
Borehole strain data are carried out from being in harmony analysis, and its relational expression is：
S1+S3=k (S2+S4), (1)
It is selected from being in harmony data of the coefficient k more than 0.9 for valid data.
Step b, the described strain conversion that carried out to borehole strain data is to be seen four component borehole strains according to formula (2)
Survey data reduction into two shearing strain S13、S24With a face strain Sa,
Step c, described data prediction is to carry out harmonic analysis to data, for removing the periodic term of data；It is adjusted
And analytic functionExpression formula is：
Wherein, A0It is the DC component of time series, m is the number of times of harmonic wave, coefficient Am,BmIt is weight factor, represents each time
Contribution of the harmonic wave to total sequence；The cycle data that initial data subtracts after fitting is exactly data after the pretreatment that we want.
Step d, described making sample data is that the daily data of the station after pretreatment are expressed as into Z in temporal sequence1
=[Z1(1),Z1(2),...,Z1(1440)],…,Zn=[Zn(1),Zn(2),...,Zn(1440) sample matrix can], be obtained
Y=[Z1,Z2,Z3,...,Zn]T.The expression formula of sample matrix Y is：
Step e, sample data Y (n × 1440) its covariance matrix CYThe element γ of (n × n)pqCalculated by formula (5)
Arrive,
Wherein,WithRespectively the i-th row pth and q minute datas；WithIt is respectively the pth and q of N row data
The average of minute data.
Step f, the characteristic value for obtaining covariance matrix is the covariance matrix C to matrix YYCarry out Eigenvalues Decomposition,
CY=R ∧ RT, (6)
In formula, ∧ (n × n) is the characteristic value diagonal matrix of size descending arrangement；R (n × 1) is and characteristic value diagonal matrix
Corresponding eigenvectors matrix.The list of feature values is shown as λ1,λ2,...,λn(λ1＞ λ2＞ ... ＞ λn)。
Step g, the characteristic vector angle of obtaining is that to set characteristic vector be R=[V1 V2 ... Vn]T, as shown in Figure 2,
Characteristic vector angle is：
Compared with prior art, the beneficial effects of the present invention are：Borehole strain number of the present invention based on principal component analysis
According to abnormal extraction method, the faint change of the earth's crust is characterized respectively using the characteristic value in principal component analysis and characteristic vector angle
Out；Realize the accurate extraction to borehole strain data exception in the case where there are stronger ambient interferences.
Brief description of the drawings
Fig. 1 is the borehole strain data exception extraction method flow chart based on principal component analysis；
Fig. 2 is characterized vectorial angle schematic diagram；
Fig. 3 is our monitoring of earthquake precursors station of aunt and Lushan earthquake epicenter position view；
Fig. 4 is first principal component characteristic value change curve；
Fig. 5 is first principal component characteristic vector angle change schematic diagram；
Fig. 6 a are the characteristic vector angle stereogram of All Time section；
Fig. 6 b be without shake during characteristic vector angle stereogram；
Fig. 6 c are the characteristic vector angle stereogram for shaking preceding 5 months Earthquake Precursor Anomalies data；
Fig. 6 d are the characteristic vector angle stereogram of BEFORE AND AFTER EARTHQUAKE abnormal data.
Specific embodiment
With reference to embodiment, the present invention is described in detail.
For Lushan earthquake, by taking the borehole strain minute Value Data of our the monitoring of earthquake precursors station of Sichuan province aunt as an example.
Our station of aunt is as shown in Figure 3 with Lushan earthquake location.The data use YRY tetra- on December 31,1 day to 2013 January in 2012
Component drilling strain gauge is measured.
A, typing aunt our station on December 31,1 day to 2013 January in 2012 borehole strain minute value time series, according to
Data are designated as S by northern south component, thing component, east northeast component, the order of northwest (NW) component respectively1、S2、S3、S4；According to by with holes
Borehole strain data are carried out from being in harmony point by the relational expression of circular hole radial deformation derived from flat board elastic theory model and regional stress
Analyse, its relational expression is：
S1+S3=k (S2+S4), (1)
The k values for calculating, our station borehole strain of on December 31, of 1 day to 2013 January in 2012 of aunt is understood by k >=0.9
Minute Value Data is effective.
B, borehole strain data are carried out with strain conversion is by four component Borehole strain observation data reductions according to formula (2)
Into two shearing strain S13、S24With a face strain Sa；
C, data prediction, i.e., carry out harmonic analysis to the data after conversion, removes the periodic response of strain data；Reconcile
Analytic functionExpression formula is：
Wherein A0It is the DC component of time series, m is the number of times of harmonic wave, coefficient Am,BmIt is weight factor, represents each time
Contribution of the harmonic wave to total sequence.The cycle data that initial data subtracts after fitting is exactly data after the pretreatment that we want.
D, the daily data of pretreated borehole strain are expressed as
Zn=[Zn(1),Zn(2),...,Zn(1440)], n=1,2,3,
Sample matrix Y=[Z can be obtained1,Z2,Z3]T.The expression formula of sample matrix Y is：
E, the covariance matrix for seeking sample data Y, sample data Y (3 × 1440) its covariance matrix CYThe unit of (3 × 3)
Plain γpqIt is calculated by formula (5),
Wherein,WithThe pth and q minute datas of respectively the i-th row data；WithIt is respectively Nth row data
Pth and q minute datas average.
F, the covariance matrix C to matrix YYCarry out Eigenvalues Decomposition,
CY=R ∧ RT, (6)
In formula, the characteristic value diagonal matrix that ∧ (3 × 3) is arranged for size descending；R is corresponding with characteristic value diagonal matrix
Eigenvectors matrix, the list of feature values is shown as λ1,λ2,λ3(λ1＞ λ2＞ λ3)。
G, obtain characteristic vector angle；R is set by taking first principal component characteristic vector as an example1=[V1,V2,V3], according to Fig. 2 institutes
Show, obtained by formula (7)
Second, third principal component characteristic vector can similarly be asked.
H, characteristic value change curve is obtained, as shown in figure 4, in figure, solid line is first principal component characteristic value, --- dotted line is
At the Lushan earthquake moment, in rectangle frame is the earthquake relevant abnormalities extracted, it can be seen that characteristic value characterizes earthquake well
Relevant abnormalities.
I, characteristic vector angle change figure and statistic histogram, such as Fig. 5 are obtained, shown in Fig. 6 a- Fig. 6 d.Open circles in Fig. 5
Point is characterized vectorial angle, --- dotted line is the Lushan earthquake moment, and in rectangle frame is the earthquake relevant abnormalities extracted.Fig. 6 a-
Fig. 6 d are first principal component characteristic vector angle change stereogram, from Fig. 6 d can be seen that feature in unusual part to
Measuring angle has obvious clustering phenomena, and Earthquake Precursor Anomalies have been extracted well.
Claims (1)
1. a kind of borehole strain data exception extraction method based on principal component analysis, it is characterised in that comprise the following steps：
A, typing borehole strain data, and the checking of data validity is carried out, "Yes" carries out next step；
B, strain conversion is carried out to borehole strain data；
C, data prediction；
D, making sample data；
E, the covariance matrix for seeking sample data；
F, the characteristic value and characteristic vector of obtaining covariance matrix；
G, the angle for obtaining feature value vector；
H, output characteristic value variation diagram；
I, output characteristic vector angle variation diagram and statistic histogram.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710205283.7A CN106918836B (en) | 2017-03-31 | 2017-03-31 | Borehole strain data exception extraction method based on principal component analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710205283.7A CN106918836B (en) | 2017-03-31 | 2017-03-31 | Borehole strain data exception extraction method based on principal component analysis |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106918836A true CN106918836A (en) | 2017-07-04 |
| CN106918836B CN106918836B (en) | 2018-02-13 |
Family
ID=59461934
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710205283.7A Active CN106918836B (en) | 2017-03-31 | 2017-03-31 | Borehole strain data exception extraction method based on principal component analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106918836B (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109031403A (en) * | 2018-08-20 | 2018-12-18 | 吉林大学 | A kind of borehole strain data exception extraction method based on S-K feature |
| CN109101954A (en) * | 2018-09-11 | 2018-12-28 | 吉林大学 | Borehole strain data tidal strain component minimizing technology based on minimal noise separation |
| CN109406076A (en) * | 2018-11-19 | 2019-03-01 | 暨南大学 | A method of beam bridge structure damage reason location is carried out using the mobile principal component of displacement sensor array output |
| CN109740453A (en) * | 2018-12-19 | 2019-05-10 | 吉林大学 | A kind of satellite magnetic field data Earthquake Precursor Anomalies extracting method based on wavelet transformation |
| CN109738939A (en) * | 2019-03-21 | 2019-05-10 | 蔡寅 | A kind of Precursory Observational Data method for detecting abnormality |
| CN110068857A (en) * | 2019-04-02 | 2019-07-30 | 吉林大学 | Swarm double star magnetic field data Earthquake Precursor Anomalies extracting method based on principal component analysis |
| CN110618458A (en) * | 2019-08-20 | 2019-12-27 | 吉林大学 | ICA-RA-based multi-band cascade correction method for drilling strain data |
| CN115758089A (en) * | 2022-11-08 | 2023-03-07 | 海南师范大学 | Borehole strain data prediction method |
| CN116202570A (en) * | 2023-02-17 | 2023-06-02 | 中国地震局地震预测研究所 | Multi-frequency surface wave calibration method and device |
| CN116204760A (en) * | 2023-01-16 | 2023-06-02 | 海南师范大学 | Drilling strain data anomaly extraction method based on GRU network |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6601671B1 (en) * | 2000-07-10 | 2003-08-05 | Weatherford/Lamb, Inc. | Method and apparatus for seismically surveying an earth formation in relation to a borehole |
| CN1837858A (en) * | 2006-04-14 | 2006-09-27 | 钟融荣 | Multi-component borehole strain seismograph |
| JP2008003071A (en) * | 2006-06-23 | 2008-01-10 | Tsuneo Yamauchi | Method and program for early prediction of seismic magnitude based on deformation quantity of building during earthquake |
| US20130255394A1 (en) * | 2012-04-03 | 2013-10-03 | Public Interest Incorporated Foundations Association for the | Stress and Strain Sensing Device |
| CN103954228A (en) * | 2014-04-30 | 2014-07-30 | 中国科学院半导体研究所 | High-precision component type optical fiber drilling strain gauge |
| US20150308864A1 (en) * | 2014-04-24 | 2015-10-29 | Björn N. P. Paulsson | Vector Sensor for Seismic Application |
| CN105988133A (en) * | 2015-02-03 | 2016-10-05 | 中国地震局地震研究所 | Borehole strain observation full-frequency band data acquisition device |
-
2017
- 2017-03-31 CN CN201710205283.7A patent/CN106918836B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6601671B1 (en) * | 2000-07-10 | 2003-08-05 | Weatherford/Lamb, Inc. | Method and apparatus for seismically surveying an earth formation in relation to a borehole |
| CN1837858A (en) * | 2006-04-14 | 2006-09-27 | 钟融荣 | Multi-component borehole strain seismograph |
| JP2008003071A (en) * | 2006-06-23 | 2008-01-10 | Tsuneo Yamauchi | Method and program for early prediction of seismic magnitude based on deformation quantity of building during earthquake |
| US20130255394A1 (en) * | 2012-04-03 | 2013-10-03 | Public Interest Incorporated Foundations Association for the | Stress and Strain Sensing Device |
| US20150308864A1 (en) * | 2014-04-24 | 2015-10-29 | Björn N. P. Paulsson | Vector Sensor for Seismic Application |
| CN103954228A (en) * | 2014-04-30 | 2014-07-30 | 中国科学院半导体研究所 | High-precision component type optical fiber drilling strain gauge |
| CN105988133A (en) * | 2015-02-03 | 2016-10-05 | 中国地震局地震研究所 | Borehole strain observation full-frequency band data acquisition device |
Non-Patent Citations (3)
| Title |
|---|
| 李海亮等: "《钻孔应变观测现状与展望》", 《地质学报》 * |
| 杨少华等: "《姑咱台钻孔应变观测值年变化的数值模拟解释》", 《地震地质》 * |
| 邱泽华: "《关于用密集钻孔应变台网监测强震前兆的若干问题》", 《地震学报》 * |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109031403B (en) * | 2018-08-20 | 2019-07-26 | 吉林大学 | A kind of borehole strain data exception extraction method based on S-K feature |
| CN109031403A (en) * | 2018-08-20 | 2018-12-18 | 吉林大学 | A kind of borehole strain data exception extraction method based on S-K feature |
| CN109101954A (en) * | 2018-09-11 | 2018-12-28 | 吉林大学 | Borehole strain data tidal strain component minimizing technology based on minimal noise separation |
| CN109101954B (en) * | 2018-09-11 | 2020-11-27 | 吉林大学 | Method for removing tidal strain components of borehole strain data based on minimum noise separation |
| CN109406076A (en) * | 2018-11-19 | 2019-03-01 | 暨南大学 | A method of beam bridge structure damage reason location is carried out using the mobile principal component of displacement sensor array output |
| CN109740453B (en) * | 2018-12-19 | 2022-03-29 | 吉林大学 | Satellite magnetic field data earthquake precursor anomaly extraction method based on wavelet transformation |
| CN109740453A (en) * | 2018-12-19 | 2019-05-10 | 吉林大学 | A kind of satellite magnetic field data Earthquake Precursor Anomalies extracting method based on wavelet transformation |
| CN109738939A (en) * | 2019-03-21 | 2019-05-10 | 蔡寅 | A kind of Precursory Observational Data method for detecting abnormality |
| CN110068857A (en) * | 2019-04-02 | 2019-07-30 | 吉林大学 | Swarm double star magnetic field data Earthquake Precursor Anomalies extracting method based on principal component analysis |
| CN110618458A (en) * | 2019-08-20 | 2019-12-27 | 吉林大学 | ICA-RA-based multi-band cascade correction method for drilling strain data |
| CN115758089A (en) * | 2022-11-08 | 2023-03-07 | 海南师范大学 | Borehole strain data prediction method |
| CN116204760A (en) * | 2023-01-16 | 2023-06-02 | 海南师范大学 | Drilling strain data anomaly extraction method based on GRU network |
| CN116204760B (en) * | 2023-01-16 | 2023-10-24 | 海南师范大学 | Drilling strain data anomaly extraction method based on GRU network |
| CN116202570A (en) * | 2023-02-17 | 2023-06-02 | 中国地震局地震预测研究所 | Multi-frequency surface wave calibration method and device |
| CN116202570B (en) * | 2023-02-17 | 2023-09-05 | 中国地震局地震预测研究所 | Multi-frequency surface wave calibration method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106918836B (en) | 2018-02-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106918836B (en) | Borehole strain data exception extraction method based on principal component analysis | |
| Langbein et al. | High‐rate real‐time GPS network at Parkfield: Utility for detecting fault slip and seismic displacements | |
| Eaton et al. | 2b... or not 2b? Interpreting magnitude distributions from microseismic catalogs | |
| Fox et al. | Shallow seismic source parameter determination using intermediate-period surface wave amplitude spectra | |
| D’hour et al. | Detection of subtle hydromechanical medium changes caused by a small-magnitude earthquake swarm in NE Brazil | |
| Davi et al. | Moment tensor inversion of explosive long period events recorded on Arenal volcano, Costa Rica, constrained by synthetic tests | |
| Lyubushin | Connection of seismic noise properties in Japan and California with irregularity of Earth’s rotation | |
| Park | Monitoring resistivity changes prior to earthquakes in Parkfield, California, with telluric arrays | |
| He et al. | Comparison of regression methods to compute atmospheric pressure and earth tidal coefficients in water level associated with Wenchuan Earthquake of 12 May 2008 | |
| Li et al. | Real-time characterization of finite rupture and its implication for earthquake early warning: application of FinDer to existing and planned stations in Southwest China | |
| Johnson et al. | Learning the low frequency earthquake activity on the central San Andreas Fault | |
| Chi et al. | Detecting earthquake-related borehole strain data anomalies with variational mode decomposition and principal component analysis: A case study of the Wenchuan earthquake | |
| Tiwari et al. | Depth-dependent seismic anomalies and potential asperity linked to fluid-driven crustal structure in Garhwal region, NW Himalaya | |
| Yu et al. | Borehole strain observations based on a state-space model and apne analysis associated with the 2013 lushan earthquake | |
| Cauchie et al. | Probabilistic inversion of Rayleigh-wave dispersion data: an application to Mt. Etna, Italy | |
| Hong et al. | Short-impending earthquake anomaly index extraction of GNSS continuous observation data in Yunnan, Southwestern China | |
| Jones et al. | Quantifying the similarity of seismic polarizations | |
| Bataleva et al. | On the relationship of the extrema of lunar-solar tidal influences and seismic events | |
| Latto et al. | Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets–Part A: Event detection for cryoseismology | |
| Gossel et al. | Applications of time series analysis in geosciences: An overview of methods and sample applications | |
| CN112612045B (en) | GNSS earthquake earth surface displacement monitoring method considering multipath and homomorphic errors | |
| Okada et al. | Neural network learning: Crustal state estimation method from time-series data | |
| Gospe et al. | Supplementing shear wave velocity profile database with microtremor-based H/V spectral ratios | |
| Mahto et al. | December 01, 2020, Haridwar, Earthquake: Fault Plane Solution and Tectonic Implications | |
| Li et al. | Extraction of Pre-earthquake Anomalies in Borehole Strain Data Using Graph WaveNet: A Case Study of the Lushan Earthquake |
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 |