CN112926189B - An information extraction method of earthquake precursory anomalies based on unfiltered maximum shear strain - Google Patents
An information extraction method of earthquake precursory anomalies based on unfiltered maximum shear strain Download PDFInfo
- Publication number
- CN112926189B CN112926189B CN202110116597.6A CN202110116597A CN112926189B CN 112926189 B CN112926189 B CN 112926189B CN 202110116597 A CN202110116597 A CN 202110116597A CN 112926189 B CN112926189 B CN 112926189B
- Authority
- CN
- China
- Prior art keywords
- earthquake
- maximum shear
- shear strain
- data
- grace
- 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.)
- Expired - Fee Related
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Remote Sensing (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- Quality & Reliability (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
本发明公开了一种基于无滤波最大切应变的地震前兆异常信息提取方法，包括以下步骤：通过目标地区的GLDAS水文数据，获得水文球谐展开系数，将目标地区的GRACE球谐系数与水文球谐展开系数做差，获得去除水文因素影响的GRACE月重力场数据；基于相邻月的GRACE月重力场数据，获得月差分重力场数据；基于左手系局部指北坐标系，通过拉格朗日重力应变张量，获得最大切应变，通过设置偏移指数，构建异常信息提取模型；基于构建的异常信息提取模型，对目标地区进行分析，在震前半年内提取到目标地区的异常信息，对地震预测具有参考指示意义，本发明所述方法能够探测到6级及以上地震震前异常信息。
The invention discloses a method for extracting abnormal information of earthquake precursors based on unfiltered maximum shear strain. Harmonic expansion coefficients are calculated to obtain the GRACE monthly gravity field data without the influence of hydrological factors; monthly differential gravity field data are obtained based on the GRACE monthly gravity field data of adjacent months; Gravity strain tensor, obtain the maximum shear strain, and build an anomaly information extraction model by setting the offset index; Prediction has reference meaning, and the method of the present invention can detect abnormal information before earthquakes of magnitude 6 and above.
Description
Technical Field
The invention belongs to the technical field of earthquake prediction, and relates to an earthquake precursor abnormal information extraction method based on the maximum shear strain without filtering.
Background
Earthquake is one of the sudden natural disasters with the strongest destructiveness and the largest harm in the modern society. The junctures of European and Asia seismic zones and three plates in continental places of China are areas with frequent shallow source earthquakes and can generate extremely destructive strong earthquakes, so the junctures become one of the most serious countries of earthquake disasters. Currently, the world is facing a new earthquake active period, and destructive earthquakes can cause losses to national economic construction and people's life and property safety, so how to effectively extract the earthquake-ahead abnormal information is very important. For the inversion of the gravity field in a large area, the conventional means such as acquiring gravity anomaly data by using a gravimeter or a pendulum instrument cannot meet the inversion requirement of the gravity field, in order to improve inversion accuracy, resolution and the like, the satellite gravity technology is rapidly developed in the new century, a novel space measurement technology using a gravity satellite as a carrier becomes a main measurement technology of the large-area gravity field, as the GRACE gravity satellite has higher accuracy in a medium-long wave part, and the earth time-varying gravity field and the gravity anomaly change calculated by using the GRACE gravity satellite play more and more important roles in atmospheric monitoring, glacier movement and underground water change, more and more geodess use the GRACE gravity satellite to explore the changes of earth surface and underground substances.
Many scientific institutions have studied earth gravitational field models. Time-varying gravity field models were successfully established by using kinetic methods by international agencies such as the German geological research Center GFZ (GeoForschung Zentrum), the American Texas University Austin Center for Space research in Austin, CSR (the University of Texas at Austin Center for Space research) and the American astronaut jet power laboratory JPL (jet Propulsion laboratory), and the time-varying gravity field models were also successfully obtained by the Holland University of Times engineering using acceleration methods. Sun & Okubo is obtained through parameter inversion of the seismic fault model and by combining with the GRACE observation precision characteristics and other comprehensive analysis: theoretically, the GRACE gravity satellite can detect the homoseismal deformation signal (including the ground level surface change signal and the gravity change signal) of a fracture type earthquake larger than mw7.5 or a shear type earthquake larger than mw9.0, and the theory is verified by researchers by using GRACE gravity satellite time-varying gravity field model data to research on the earthquake occurring in recent years; han et al studied Sumenyan earthquake in 2004 based on GRACE gravity satellite CSR RL04Level-1 data, and obtained the first result of the same-earthquake gravity change in the world, which was obtained by gravity satellite data detection. Since their successful detection by the GRACE gravity satellite in 2004, the scholars used the GRACE gravity satellite to study major earthquakes occurring in the last 15 years (somnophila mw9.3 earthquake in 2004, indonesia mw8.6 earthquake in 2005, venterna mw7.8 earthquake in 2008, chile mw8.8 earthquake in 2010, mw9.0 earthquake in japan in 2011, mw8.6 earthquake in somnophila in 2012, and nipaler mw8.0 earthquake in 2015) using different data processing strategies and research methods.
The method for extracting the isoseismal gravity anomaly information is based on earth-moon gravity field model data, after the lower-order term replacement, average gravity field removal, hydrological factor influence removal, filtering and the like are carried out on the isoseismal gravity field model data, the gravity change before and after the earthquake happens is directly contrasted and analyzed, the gravity gradient tensor is rarely obtained through processing, the maximum shear strain information is not further extracted, and the extraseismic anomaly information is further detected.
Disclosure of Invention
In order to solve the problems, the invention provides a method for extracting seismic precursor abnormal information based on the maximum shear strain without filtering, which comprises the following steps:
s1, acquiring a hydrological spherical harmonic coefficient through GLDAS hydrological data of a target area, making a difference between the GRACE spherical harmonic coefficient of the target area and the GLDAS spherical harmonic coefficient, separating non-structural factors such as hydrological influences from the GRACE data of the target area, and acquiring the target GRACE spherical harmonic coefficient after removing hydrological factors;
s2, constructing a gravity field of a target area through a target GRACE spherical harmonic coefficient and according to a bit coefficient theory based on the earth radius, the complementary latitude, the longitude and a regularized Legendre function;
s3, acquiring a lunar difference data model through a gravity field based on GRACE month gravity field data of adjacent months, wherein the lunar difference data model comprises a first spherical harmonic coefficient and a second spherical harmonic coefficient;
s4, obtaining a corresponding gravitational potential of the lunar difference data model through a first spherical harmonic coefficient and a second spherical harmonic coefficient based on the lunar difference data model, obtaining a Lagrange gravitational strain tensor based on a left-hand system local north-pointing coordinate system through a second-order gradient of the gravitational potential, and constructing a maximum shear strain time sequence through the Lagrange gravitational strain tensor;
s5, based on the maximum shear strain time sequence and the average value and standard deviation of the maximum shear strain time sequence, extracting first abnormal information on a time domain of the maximum shear strain time sequence through a 'k sigma' criterion for a characteristic point of the maximum shear strain time sequence, based on each cell in a space range, extracting second abnormal information on the space domain of the maximum shear strain time sequence through setting an offset index, based on the first abnormal information and the second abnormal information, constructing an abnormal data extraction model on a space-time scale, and based on GRACE data through the abnormal data extraction model, performing GRACE data analysis on a target area, wherein the GRACE data analysis is used for extracting pre-earthquake abnormal information of the target area through the GRACE data analysis.
Preferably, S1 includes obtaining target GRACE spherical harmonic coefficients with hydrographic effects removed by a hydrographic data model of the global land data assimilation system based on the GRACE spherical harmonic coefficients.
Preferably, the grid spacing of the hydrological data model is 1 ° × 1 °;
hydrological data models, including snow water and subsurface 0-2m soil water content.
Preferably, the order of the GRACE spherical harmonic coefficients after removing the hydrologic factors is 96 orders.
Preferably, the lunar difference data model includes, pre-earthquake two-year data.
Preferably, S4, includes constructing a maximum shear strain time sequence based on the maximum eigenvalue and the minimum eigenvalue of the lagrangian gravitational strain tensor.
Preferably, the "k σ" criterion is a criterion for abnormality recognition in the feature point time series, and the k value of the "k σ" criterion is set to 3.2.
Preferably, the spatial range is 5 ° × 5 °;
and obtaining a deviation index through the mean value and the standard deviation of the maximum shear strain time series based on each unit cell in the space range.
Preferably, the formula for the shift index is:
wherein K is the offset index, MSH is the maximum shear strain value, muMSHIs the mean value of the maximum shear strain time series, σMSHThe maximum shear strain time series standard deviation.
Preferably, S5 further includes drawing a seismic example feature map of the target region through the abnormal data extraction model based on the migration index, obtaining the maximum shear strain anomaly information before earthquake based on the time feature and the spatial feature of the seismic example feature map and the abnormal data extraction model based on the abnormal data extraction model, constructing a correlation model of the migration index and the geological structure activity of the target region by comparing the migration index of the seismic year and the earthquake-free period of the target region, and making an early warning on whether the seismic precursor gravity anomaly exists in the target region based on the migration index through the correlation model.
The positive progress effects of the invention are as follows:
the invention provides a method for extracting maximum shear strain earthquake precursor abnormal information based on no filtering, which avoids the problems that high-order information is seriously suppressed, middle-order and high-order information is lost and the spatial resolution is reduced due to filtering processing. The maximum shear strain is essentially a second-order gradient of gravity, so that the error of a north-south strip is effectively inhibited, and the weakening of a real signal is avoided. Meanwhile, the maximum shear strain contains information such as deformation of the earth crust surface and the like, and has clear physical significance. The method of the invention utilizes GRACE gravity data to detect the abnormal information of the earthquake with the level of 6 and above before earthquake.
Drawings
FIG. 1 is a flow chart of the extraction of pre-earthquake anomaly information according to the present invention;
FIG. 2 is a schematic diagram illustrating the extraction of pre-earthquake abnormal information according to the present invention;
FIG. 3 is a time series plot of maximum shear strain according to the present invention;
FIG. 4 is a schematic diagram of the time series of maximum shear strain based on the "k σ" criterion according to the present invention;
FIG. 5 is a schematic diagram of the spatial domain variation of the shift index according to the present invention;
FIG. 6 shows an example of the present invention in a field seismic mode: (a) the gravity anomaly of the feature points extracted after the Gaussian filtering and smoothing are carried out and the radius is 250 meters; (b) the gravity anomaly of the feature points extracted after the Gaussian filtering smoothing with the radius of 300 meters is processed; (c) the gravity anomaly of the feature points extracted after the Gaussian filtering smoothing with the radius of 500 meters is processed; (d) the gravity anomaly of the feature points extracted after the Gaussian filtering smoothing radius is 300 meters and the decorrelation filtering processing is carried out; (e) abnormal information extracted by the invention;
FIG. 7 is a Yaan earthquake magnitude diagram of the present invention, wherein (a) the gravity anomaly of the feature points extracted after Gaussian filtering and smoothing with radius of 250 m; (b) the gravity anomaly of the feature points extracted after the Gaussian filtering smoothing with the radius of 300 meters is processed; (c) the gravity anomaly of the feature points extracted after the Gaussian filtering smoothing with the radius of 500 meters is processed; (d) the gravity anomaly of the feature points extracted after the Gaussian filtering smoothing radius is 300 meters and the decorrelation filtering processing is carried out; (e) abnormal information extracted by the invention;
FIG. 8 is a comparison of the shockless period of the shocking examples in the field of the present invention: (a) after Gaussian filtering and smoothing, processing the seismic center characteristic points with radius of 250 meters, and extracting seismic period-free gravity anomaly time sequence; (b) after being processed by Gaussian filtering and smoothing with radius of 300 meters, extracting seismic center characteristic points of the gravity anomaly time sequence without the seismic period; (c) after Gaussian filtering and smoothing with the radius of 500 m, extracting seismic center characteristic points of the gravity anomaly time sequence without the seismic period; (d) the seismographic feature points extracted after Gaussian filtering smoothing radius of 300 meters and decorrelation filtering processing have no seismographic period gravity anomaly time sequence; (e) the seismic center characteristic points extracted by the method have no seismic period abnormal information time sequence;
FIG. 9 is a comparison of the Yaan seismic examples without the seismic period of the invention: (a) after Gaussian filtering and smoothing, processing the seismic center characteristic points with radius of 250 meters, and extracting seismic period-free gravity anomaly time sequence; (b) after being processed by Gaussian filtering and smoothing with radius of 300 meters, extracting seismic center characteristic points of the gravity anomaly time sequence without the seismic period; (c) after Gaussian filtering and smoothing with the radius of 500 m, extracting seismic center characteristic points of the gravity anomaly time sequence without the seismic period; (d) the seismographic feature points extracted after Gaussian filtering smoothing radius of 300 meters and decorrelation filtering processing have no seismographic period gravity anomaly time sequence; (e) the seismic center characteristic points extracted by the method have no seismic period abnormal information time sequence;
fig. 10 shows the time-space variation of the pre-earthquake migration index in the field and the results of the comparison between the pre-earthquake migration index and the non-earthquake period, wherein the image data in each period are calculated according to the present invention from the gravity field model data of the Grace month in the adjacent 3 months, the images (1) to (4) show the variation of the pre-earthquake migration index in the field, and the images (5) to (8) show the results of the comparison between the non-earthquake periods and the same periods;
fig. 11 is the time-space change of the yaan earthquake pre-earthquake migration index and the non-earthquake period comparison result thereof, wherein image data of each period are calculated according to the invention from the GRACE month gravity field model data of 3 adjacent months, fig. 1 to 4 are the change of the yaan earthquake pre-earthquake migration index, and fig. 5 to 8 are the non-earthquake period synchronization comparison results thereof.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
In the existing method for extracting the pre-earthquake gravity anomaly based on filtering processing, the pre-earthquake anomaly information can be well extracted for a huge earthquake, but the anomaly information is difficult to extract by using the existing method for a strong earthquake with the level of 7.5 or below. Meanwhile, in the process of using the filtering method, not only is useful information lost, but also new noise is brought, for example, for a gaussian smooth filtering with a filtering radius of 400km, the high-order bit coefficient after 60 orders is seriously suppressed, although the method can effectively reduce the noise, the method can lose the gravity field information with the high-order bit coefficient to a certain extent, so that the spatial resolution is reduced, the magnitude of the final result is reduced, the reliability of the gravity field obtained by final processing is reduced, and the sensitivity of the earthquake gravity field abnormal information is reduced.
Aiming at the defects of the existing GRACE information extraction technology, the invention provides a maximum shear strain earthquake abnormal information extraction method based on no filtering processing. The invention adopts a non-filtering mode, avoids the loss and error of data brought by filtering processing, but considers the stripe error of the original data, if a gravity abnormal value is directly extracted, useful information is annihilated in the stripe error, the maximum shear strain is the second-order gradient of gravity, the method has obvious filtering effect on the stripe error, and the maximum shear strain contains information such as crust surface deformation and the like, and has clear physical significance, so the method uses the maximum shear strain to describe the information related to the structure. The maximum shear strain is sensitive to the pre-earthquake abnormal information, the abnormal change of the characteristic point time sequence can be effectively extracted by combining the rule based on 'K sigma', and meanwhile, the maximum shear strain abnormal information is further extracted in a space domain by calculating the offset index K, so that the strain state of a fault can be described on a space-time scale. The method for extracting the maximum shear strain abnormal information based on the non-filtering provided by the invention not only can effectively extract huge earthquake pre-earthquake abnormal information, but also can extract pre-earthquake abnormal information of strong earthquakes with the level of more than 6 and less than 7.5, and therefore, the method has a better indication effect on medium and strong earthquakes with higher occurrence frequency, and therefore, the patented technology has very important significance on prediction of medium and short impending earthquakes. The method is a place which is difficult to be achieved by the technology of extracting the pre-earthquake gravity anomaly by using the traditional classical filtering method.
As shown in fig. 1 to 11, the invention provides a method for extracting seismic precursor anomaly information based on filter-free maximum shear strain, which comprises the following steps:
s1, acquiring a hydrological spherical harmonic coefficient through GLDAS hydrological data of a target area, making a difference between the GRACE spherical harmonic coefficient of the target area and the GLDAS spherical harmonic coefficient, separating non-structural factors such as hydrological influences from the GRACE data of the target area, and acquiring the target GRACE spherical harmonic coefficient after removing hydrological factors;
s2, constructing a gravity field of a target area through a target GRACE spherical harmonic coefficient and according to a bit coefficient theory based on the earth radius, the complementary latitude, the longitude and a regularized Legendre function;
s3, acquiring a lunar difference data model through a gravity field based on GRACE month gravity field data of adjacent months, wherein the lunar difference data model comprises a first spherical harmonic coefficient and a second spherical harmonic coefficient;
s4, obtaining a corresponding gravitational potential of the lunar difference data model through a first spherical harmonic coefficient and a second spherical harmonic coefficient based on the lunar difference data model, obtaining a Lagrange gravitational strain tensor based on a left-hand system local north-pointing coordinate system through a second-order gradient of the gravitational potential, and constructing a maximum shear strain time sequence through the Lagrange gravitational strain tensor;
s5, based on the maximum shear strain time sequence and the average value and standard deviation of the maximum shear strain time sequence, extracting first abnormal information on a time domain of the maximum shear strain time sequence through a 'k sigma' criterion for a characteristic point of the maximum shear strain time sequence, based on each cell in a space range, extracting second abnormal information on the space domain of the maximum shear strain time sequence through setting an offset index, based on the first abnormal information and the second abnormal information, constructing an abnormal data extraction model on a space-time scale, and based on GRACE data through the abnormal data extraction model, performing GRACE data analysis on a target area, wherein the GRACE data analysis is used for extracting pre-earthquake abnormal information of the target area through the GRACE data analysis.
S1 includes obtaining target GRACE spherical harmonic coefficients without hydrologic influence through a hydrologic data model of the global land data assimilation system based on the GRACE spherical harmonic coefficients.
The grid spacing of the hydrological data model is 1 ° × 1 °; hydrological data models, including snow water and subsurface 0-2m soil water content.
The order is 96.
The lunar difference data model includes, the first two years worth of data.
And S4, constructing a maximum shear strain time sequence based on the maximum eigenvalue and the minimum eigenvalue of the Lagrange gravitational strain tensor.
The "k σ" criterion is a criterion for abnormality recognition in the feature point time series, and the k value of the "k σ" criterion is set to 3.2. The spatial range is 5 ° × 5 °;
and obtaining a deviation index through the mean value and the standard deviation of the maximum shear strain time series based on each unit cell in the space range.
The formula for the shift index is:
wherein K is the deviation index, MSH is the maximum shear strain value, muMSHIs the mean value of the maximum shear strain time series, σMSHThe maximum shear strain time series standard deviation.
S5 further comprises the steps of drawing a seismic example feature map of the target area through an abnormal data extraction model based on the migration index, obtaining the maximum shear strain abnormal information before earthquake based on the time feature and the space feature of the seismic example feature map and the abnormal data extraction model based on the abnormal data, establishing a correlation model of the migration index and the geological structure activity of the target area through comparing the migration index of the earthquake year and the earthquake-free period of the target area, and giving an early warning to the target area whether the earthquake precursor gravity abnormality exists or not through the correlation model and based on the migration index.
The technical process of the present invention is explained below by means of specific embodiments
1. Hydrologic factor influence removal and lunar difference image calculation on original gravity field model data
And the step of removing hydrologic factor influence on the original gravity field model data comprises the spherical harmonic coefficient expansion of the hydrologic data and the removal of the hydrologic factor from the GRACE data. The GRACE gravity satellite observation data comprises a plurality of substance change information inside and on the earth, and when the earth gravity satellite monthly gravity field model data is used for researching earthquakes, non-structural factors such as hydrological factor influence and the like need to be separated. The invention selects a hydrological data model with a Global Land Data Assimilation System (GLDAS) grid interval of 1 degree multiplied by 1 degree, the used products comprise snow water and underground 0-2m soil water content, the spherical harmonic coefficient expansion is carried out on the model and the model is cut off to 96 orders (same order as GRCACE), and the hydrological spherical harmonic coefficient C is obtainedgldasAnd Sgldas。
The spherical harmonic coefficient C, S of GRACE data and the hydrographic spherical harmonic coefficient Cgldas、SgldasAre respectively provided withAnd (5) performing difference making, as shown in a formula (7), to obtain the spherical harmonic coefficient after removing the hydrological factors.
And (4) obtaining the gravity field model without the influence of the hydrological factors according to the formula (8).
Wherein R, theta and lambda are the earth radius, the remaining latitude and the longitude respectively; n and m are the order of the spherical harmonic expansion; pnm(cos θ) is the regularized Legendre function.
GRACE data is published in a month unit, the month change of a gravity field can provide fine dynamic change process information, and the data of two years before earthquake are selected when the information before earthquake is extracted. After the hydrologic step is removed, difference processing is carried out on adjacent months of the GRACE month gravity field model to obtain month difference data, and as shown in a formula (8), regional local effect can be highlighted, and more comprehensive information can be provided for researching regional gravity field change.
In the formula (I), the compound is shown in the specification,
and
to time-sequentially order the spherical harmonics in the previous month,
and
the spherical harmonic coefficient for the next month in the sequence.
2. Derivation of gravitational strain tensor
Is C'correct、S′correctAnd C ″)correct、S″correctAnd respectively obtaining corresponding gravitational potential T, T according to the formula (8) for the differentiated adjacent lunar difference data, namely the first spherical harmonic coefficient and the second spherical harmonic coefficient. And taking any observation point on the earth surface as an origin O, wherein the X axis points to the north, the Y axis points to the east, the Z axis is vertical to the XOY plane and upwards forms a local north-pointing coordinate system of a left-handed system, and the Lagrange gravitational strain tensor is shown as a formula (10).
Wherein B and B are the second order gradients corresponding to the gravitational potential T, T, respectively, i.e.
3. Calculation of maximum shear strain
The maximum shear strain (MSH) is calculated according to equation (10):
MSH＝λmax-λmin (11)
in the formula, λmaxAnd λminThe maximum eigenvalue and the minimum eigenvalue of the lagrange gravitational strain tensor E are respectively.
17 hours and 19 minutes in 2 and 12 months in 2014, M7.3 earthquake (field 7.3 grade earthquake for short) occurs in county in Uygur autonomous region of Xinjiang and the field area, and the microscopic epicenter measured by the earthquake table net in the Uygur autonomous region of Xinjiang is 36.10 degrees N and 82.50 degrees E. Taking field earthquake as an example, the maximum shear strain of the epicenter position of the feature point is calculated according to the method above by using the month gravity field model data (part of month data is missing) of 38 months in 2 months to 2016 months (two years before earthquake and two years after earthquake) in 2012, and the 36-stage data result is obtained, and the result is shown in fig. 3.
4. Extraction of extraepicentral abnormal information based on 'k sigma' criterion
And taking the 'k sigma' criterion as a discrimination standard of the abnormality identification, and determining an abnormal value according to empirical statistics. The basic principle is as follows:
in the formula, xiIn order to be able to take the value of the observation,
and σ is the mean and standard deviation, respectively, of the observed sequences. The present invention sets the k value to 3.2, and when the observed value satisfies the above equation, the value is defined as abnormal data.
As shown in fig. 4, the maximum shear strain value in stage 17 is an abnormal value, the maximum shear strain calculated from the difference between months 12 and 11 in 2013 and months 1 and 12 in 2013 in 2014 in stage 7.3 earthquake in field occurs in month 2 in 2014, and the abnormal phenomenon occurs in three months before earthquake and is an earthquake-related abnormal phenomenon.
5. Extraction of pre-earthquake space-time abnormal information based on offset index K
The part is based on the step 4, namely a time series maximum shear strain extraction method, and adds a spatial domain anomaly extraction process. In order to retain the original data characteristics and highlight abnormal signals, the invention further calculates the offset index K of the characteristic points, takes the offset index K as a measurement index for describing the abnormality, and the offset index implementation formula is as follows:
wherein K is the deviation index, MSH is the maximum shear strain value calculated according to the method of the invention, muMSHThe mean value, sigma, of the MSH observation time series of the maximum shear strain value of the characteristic pointMSHAnd (4) observing the standard deviation of the time series for the maximum shear strain value MSH of the characteristic point. It should be noted that the calculation of the shift index is directed to the variation of each feature point in its time sequence, independent of other feature points in the spatial domain, that is, the shift index of each feature pointThe values are independent of the choice of spatial domain range.
According to the offset index, a rapid mapping can be realized, the invention selects an area range which takes the epicenter as the center and is 5 degrees multiplied by 5 degrees as a space scale, the range size of the unit cell in each image is 0.5 degrees multiplied by 0.5 degrees, the offset index of the central point of each unit cell is respectively obtained according to the formula, and the value of the offset index is used as the offset index of the unit cell. And extracting the maximum shear strain abnormal information before earthquake by combining the time and space characteristics of the earthquake case, and then further comparing the earthquake year with the earthquake-free period migration index K to obtain the related condition of the migration index change and the geological structure activity. In the present invention, a value satisfying the condition K ≧ 3.2 is defined as an abnormal value, so that analysis in a spatial domain is facilitated for avoiding interference, and a value satisfying the condition K <3.2 is set to 0 in drawing, in consideration of the fact that the maximum shear strain is a value greater than 0 and there is no negative abnormal value phenomenon.
As shown in fig. 5, the experimental result image is calculated by calculating the difference between adjacent 3 months of the gravity data of the GRACE month, i.e., the data of 11 months, 12 months and 1 month of 2014 in 2013, the difference data of the months, i.e., the difference data of 12 months to 11 months (denoted by T) in 2013 and 12 months (denoted by T) in 2014 to 12 months (denoted by T) in 2014 is obtained according to the method of step 2 and step 3, and then the shift index in the 5 ° × 5 ° region centered on the seismic center of the field is further obtained from T and T. From a time point of view, the experimental result image actually shows the strain state of the region in three months, i.e. corresponding to stage 16 in fig. 4; spatially, the value of the cell (0.5 ° × 0.5 °) in the epicenter in fig. 5 corresponds to the data of phase 16 in fig. 4.
Aiming at the defects of the prior art, the invention provides a method for extracting the maximum shear strain earthquake precursor abnormal information based on no filtering, which avoids the problems that high-order information is seriously suppressed, middle-order and high-order information is lost and the spatial resolution is reduced due to filtering processing. The maximum shear strain is essentially a second-order gradient of gravity, so that the error of a north-south strip can be effectively inhibited, and the weakening of a real signal is avoided. Meanwhile, the maximum shear strain contains information such as deformation of the earth crust surface and the like, and has clear physical significance. The method can detect the abnormal information before earthquake of 6 grades and above by using GRACE gravity data, and is not limited to 7.5 grades and above 8 grades of huge earthquakes. The method has better indication effect on the medium and strong earthquakes just because the method is more sensitive to the motion response of the earthquake structure.
In order to show the advantages of the method, the method is compared with a gravity anomaly extraction method based on various traditional GRACE data filtering processing technologies. The conventional method comprises the following steps: and smoothing and denoising the GRACE data by using Gaussian filtering smoothing radii of 250 meters, 300 meters and 500 meters and decorrelation filtering, and extracting characteristic point gravity anomaly information. In order to ensure the reliability and feasibility of the method, four seismic cases are selected for comparative analysis.
The earthquake center position of each earthquake case is taken as a characteristic point, the information change conditions of the earthquake center position of the earthquake case after the earthquake is two years are respectively obtained by using the method and the filtering method based on GRACE tradition, and the extraction results of the abnormal information before the earthquake are compared and analyzed.
In the field, the earthquake occurs at 17 hours at 12 days 12 months 12 days in 2014 for 19 minutes, the magnitude of the earthquake is M7.3, the depth of the earthquake source is 12km, and the microscopic epicenter measured by the earthquake table net in the Uygur autonomous region in Xinjiang is 36.10 degrees N and 82.50 degrees E. The gravity data are filtered by using Gaussian filtering with smooth radiuses of 250 meters, 300 meters and 500 meters and by combining decorrelation filtering with the Gaussian filtering with smooth radius of 300 meters, so that the time sequence gravity change of the epicenter characteristic points is obtained. As is evident from the experimental results, no abnormality was found before earthquake in the conventional method (the abnormality is defined in the foregoing, and the variation value is larger (or smaller)
(or
) I.e., is abnormal). The abnormal information before earthquake in the field is successfully extracted by using the method, the abnormal value occurs in the data of the 17 th stage, and the data is the maximum cut obtained by calculating the difference between 12 months and 11 months in 2013 and the difference between 1 month in 2014 and 12 months in 2013Strain, which can be found one month before earthquake occurs.
The Qingchuan earthquake occurs in Qingchuan county of Sichuan province in 2008 at 8/5, the earthquake center positions published by the American earthquake Bureau are 32.756 degrees N and 105.494 degrees E, the earthquake magnitude is 6.0, and the earthquake source depth is 6 km. It can be obviously seen from the experimental results that the gravity change obtained by the traditional filtering processing method does not obtain earthquake abnormal information of epicenter characteristic points, the maximum shear strain obtained by the processing method of the invention has an abnormal phenomenon before earthquake, the abnormal value occurs in the 19 th data, and the maximum shear strain is obtained by calculating the difference between month 3 and month 2 in 2008 and the difference between month 4 and month 3 in 2008, namely the maximum shear strain occurs in the first four months of the earthquake.
Wenchuan earthquake occurred in Wenchuan at 2008, 5, 12 and published earthquake locations of 31.002 degrees N and 103.322 degrees E, the magnitude of earthquake was 7.9, and the depth of the earthquake source was 19 km. It is obvious from the experimental results that the results obtained by the gaussian smoothing radius of 250 m and 300 m processing have no abnormal information defined herein, but have larger change in the fourth month before the onset than the adjacent months, and the larger change disappears in the results obtained by the gaussian smoothing radius of 500 m processing and the gaussian smoothing radius of 300 m processing combined with the decorrelation filtering method, and the preliminary analysis is that the change disappears due to the increase of the filtering radius. And abnormal information is extracted before earthquake by using the method, abnormal values occur in data of 9 th and 24 th, namely, the maximum shear strain obtained by difference between 2 month and 1 month in 2007 and difference between 3 month and 2 month in 2007, and the maximum shear strain obtained by difference between 4 month and 3 month in 2008 and difference between 5 month and 4 month in 2008, namely, the abnormal values are extracted before earthquake occurs in one year, and the abnormal values are also found in the calculation results of the current month and two months before earthquake occurs.
An Yaan earthquake occurs in 20 days 4 months in 2013, the epicenter positions published by the Chinese earthquake table net are 30.52 degrees N and 102.79 degrees E, the earthquake magnitude is 7.1, and the earthquake source depth is 11 km. Abnormal information is not extracted from the gravity change data obtained by the traditional filtering processing before the earthquake occurs. The pre-earthquake abnormal information is extracted from the change of the characteristic points extracted by the invention, namely, the 16 th stage is the maximum shear stress change obtained by calculating the difference between the month 11 and the month 9 in 2012 (data missing at the month 10) and the difference between the month 12 in 2012 and the month 11, and the abnormal phenomenon can be found in the four months before earthquake.
The experimental result shows that for the earthquakes with the level of 6 to below and the level of 7.5, the gravity data obtained after the traditional Gaussian filtering and decorrelation filtering processing does not show abnormal phenomena before the earthquake, but the method can effectively extract the abnormal information before the earthquake, so the method is superior to the traditional gravity abnormal extraction technology based on the filtering method.
The invention shows the comparison condition of the extraventricular abnormal information extraction results of part of experimental seismographs obtained by using the method and the GRACE-based traditional filtering method. FIG. 6 shows the information change of the characteristic points in the field earthquake center after two years before and after earthquake, and FIG. 7 shows the information change comparison of the characteristic points in the Yaan earthquake center after two years before and after earthquake.
In the four experimental earthquake cases, the invention can be used for extracting abnormal information appearing in the epicenter position in the year before the earthquake occurs, for example, abnormal phenomena appear in the month before the field earthquake occurs, obvious abnormal phenomena appear in the first four months before the Qingchuan earthquake occurs, abnormal phenomena appear in Wenchuan earthquake not only in the year before the earthquake occurs, but also in the calculation results of the month when the earthquake occurs and the two months before the earthquake occurs, and abnormal phenomena are also found in the fourth month before the Yaan earthquake occurs. In order to further prove the reliability of the method, the non-seismic periods are respectively selected for time series detection based on the epicenter characteristic points of the four seismic cases, so that the method can be tested that the false alarm rate can not occur in the non-seismic periods. When selecting the shockless period, the following considerations need to be combined: 1) counting whether strong earthquake of 6 grades or above occurs within the range of 10 degrees multiplied by 10 degrees with the epicenter position as the central point, and ensuring that no earthquake of 6 grades or above exists within the selected earthquake-free period within the space range; 2) considering the migration phenomenon of the materials inside the earth crust, the selected range of the no-earthquake period should be the contemporaneous data of the corresponding earthquake example, that is, the earthquake occurs in month 2 of 2014, the time range of the earthquake before the earthquake is from month 1 of 2013 to month 2 of 2014, and the selected time span of the no-earthquake period should be from month 1 of the previous year to month 2 of the next year.
According to the non-seismic period selection method described above, the non-seismic period at the seismic center position of the field is selected from 1 month 2010 to 2 months 2011, the non-seismic period at the seismic center position of Qingchuan is selected from 7 months 2013 to 8 months 2014, the non-seismic period at the seismic center position of Wenchuan is selected from 4 months 2010 to 5 months 2011, and the non-seismic period at the seismic center position of Yaan earthquake is selected from 3 months 2005 to 4 months 2006. After the selection of the seismological period is finished, the change information of the seismological position in the seismological period is extracted by respectively utilizing a classical filtering method and the method. If the gravity abnormal information is extracted in the non-earthquake-period detection of each earthquake, the gravity abnormal information can generate certain interference on the early warning work of the strong earthquake, so that the reliability of the detection method is reduced, and in the process of detecting the non-earthquake-period time sequence change of the four earthquake-period positions, the information extraction method does not find abnormal information, and the experimental result further verifies the reliability and feasibility of extracting the pre-earthquake abnormal information of 6 grades or more.
The present invention shows the time sequence variation process obtained by the method of the present invention and the filtering method based on GRACE tradition in the non-earthquake period of the earthquake of field earthquake and Yaan earthquake at the epicenter position, as shown in FIG. 8 and FIG. 9.
Fig. 6-9 are time series change information extracted at feature points — epicenter locations using the present invention. In consideration of time and space characteristics, the method uses the offset index K, increases the spatial domain anomaly extraction process, and further extracts the pre-earthquake space-time anomaly change information of the maximum shear strain. The invention selects the area range of 5 degrees multiplied by 5 degrees with the epicenter as the center as the spatial scale, and takes the first half year to the moment of origin as the time scale, and respectively performs the experiments on the four earthquake cases of the field earthquake, the Qingchuan earthquake, the Wenchuan earthquake and the Yaan earthquake, and performs the comparison experiment of the migration index K of the earthquake period and the earthquake-free period on the spatial domain by utilizing the selected earthquake-free period.
In the results of the half-year shift index change of the field before earthquake and the comparative experiment with the same earthquake-free period, it was found that, in 3 months before earthquake, large-scale abnormality occurred within about 60 km around the epicenter, the shift indexes were all 5 or more, the maximum value reached 5.8, and the position was located at the south end of the alpha gold fracture zone, as shown in fig. 10 (3). Before this time period, as shown in fig. 10(1) and (2), the above-mentioned abnormality did not appear in the vicinity of the alpha fracture zone, as shown in fig. 10(4), no abnormality was found during one month after the shock before the shock occurred (data missing in 2 months of the shock occurred). Fig. 10(5) to (8) show the variation of the displacement index values of the same period of the non-earthquake period, wherein the displacement index values are all 0, and compared with the result of the non-earthquake period, the obvious abnormal phenomenon occurs in the field within the range of about 60 km around the earthquake-center position in 3 months before the earthquake.
The seismic center of Qingchuan earthquake is located at the boundary junction of Gansu, Shaanxi and Sichuan. In the change of the migration index of the Qingchuan earthquake in the first half year before the earthquake, the obvious abnormal change is found in the experimental results of other time periods between 4 months and 6 months before the earthquake, namely, the abnormal positions at the junction of the three provinces and in the Sichuan province are rapidly increased, and the obvious observation shows that the larger abnormal values are distributed at the junction of the three provinces, namely, around 100 kilometers near the earthquake center position, wherein the migration index value reaches about 6, the maximum value is 6.9, and the effect of larger stress on the junction of the three provinces is shown. The values in the shockless period are all 0, and no abnormal phenomenon occurs. Through the comparison of the non-earthquake period experiments, the abnormal phenomenon of the earthquake-center position of Qingchuan and the area near the earthquake-center position of Qingchuan between 4 months and 6 months before the earthquake is further highlighted.
Wenchuan earthquake epicenter is located in the Longshan fracture zone. In the case of the deflection index change of Wenchuan earthquake in the first half year of earthquake, it can be found that the abnormal values are symmetrically distributed about the Longshan fracture zone, the epicenter is positioned near the central point of the connecting line of the abnormal points on the two sides, and the deflection index value is mostly close to 6. And the values of the deflection indexes in the non-earthquake period synchronization are all 0, and no abnormal phenomenon is found, so that the abnormal phenomenon of the Wenchuan earthquake midsummer position and the area nearby the Wenchuan earthquake midsummer position in the 6 months before the earthquake is further highlighted.
The Yaan earthquake center is positioned at a fracture zone of the Longmen mountain. The gantry fracture zone is obviously different from other time periods between 9 and 12 months in 2012, two abnormal cells appear, the deviation indexes are respectively 4.7 and 5.1, and the epicenter position is positioned in one abnormal cell, which indicates that the fracture zone near the epicenter position is subjected to larger stress. The offset index values of the Longshan fracture zones in the non-earthquake period are all 0, and the abnormal phenomenon does not occur, so that the abnormal phenomenon occurring in the vicinity of the Yaan earthquake in the period from 4 months to 6 months before the earthquake is further highlighted.
The present invention shows the variation of the field earthquake and the yaan earthquake in the first half year of the earthquake and the comparison experiment result with the no-earthquake period, as shown in fig. 10 and 11, the range of the cell in each image is 0.5 degree multiplied by 0.5 degree, and the value of the central point of each cell represents the value of the cell.
The experimental result shows that in the first half year of the earthquake, the abnormality of a large degree occurs near the epicenter positions of four earthquakes, the deviation index values are all close to 6, the deviation index values in the non-earthquake period are all 0, no abnormality occurs, and the phenomenon of the abnormality before the earthquake occurs in each earthquake case is further highlighted through the comparison experiment of the earthquake period and the corresponding non-earthquake period. And the abnormal phenomena occur in the epicenter position and the area near the epicenter position in a concentrated mode, so that the method has good reference indication significance for earthquake epicenter position prediction.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the present invention in its spirit and scope. Are intended to be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. The method for extracting the seismic precursor abnormal information based on the non-filtering maximum shear strain is characterized by comprising the following steps of:
s1, acquiring a hydrological spherical harmonic coefficient through GLDAS hydrological data of a target area, subtracting the GRACE spherical harmonic coefficient of the target area from the GLDAS spherical harmonic coefficient, separating hydrological influence non-structural factors from the GRACE data of the target area, and acquiring the target GRACE spherical harmonic coefficient after removing the hydrological factors;
s2, constructing a gravity field of the target area through the target GRACE spherical harmonic coefficient and according to a bit coefficient theory based on the earth radius, the remaining latitude, the longitude and a regularized Legendre function;
s3, obtaining a lunar difference data model through the gravity field based on GRACE month gravity field data of adjacent months, wherein the lunar difference data model comprises a first spherical harmonic coefficient and a second spherical harmonic coefficient;
s4, obtaining a corresponding gravitational position of the lunar differential data model through the first spherical harmonic coefficient and the second spherical harmonic coefficient based on the lunar differential data model, obtaining a Lagrange gravity strain tensor based on a left-hand system local north-pointing coordinate system through a second-order gradient of the gravitational position, and constructing a maximum shear strain time sequence through the Lagrange gravity strain tensor;
s5, based on the maximum shear strain time sequence and the average value and standard deviation of the maximum shear strain time sequence, extracting first abnormal information on a time domain of the maximum shear strain time sequence through a 'k sigma' criterion for a characteristic point of the maximum shear strain time sequence, based on each unit cell in a space range, extracting second abnormal information on the space domain of the maximum shear strain time sequence through setting an offset index, based on the first abnormal information and the second abnormal information, constructing an abnormal data extraction model on a space-time scale, and based on GRACE data through the abnormal data extraction model, performing GRACE data analysis on the target area based on the GRACE data, so as to extract the pre-earthquake abnormal information of the target area through the GRACE data analysis.
2. The method of claim 1, wherein the seismic precursor anomaly information extraction method based on the unfiltered maximum shear strain,
and the step S1 includes that the target GRACE spherical harmonic coefficient without hydrologic influence is obtained through a hydrologic data model of a global land data assimilation system based on the GRACE spherical harmonic coefficient.
3. The method of claim 2, wherein the seismic precursor anomaly information extraction method based on the unfiltered maximum shear strain,
the grid interval of the hydrological data model is 1 degree multiplied by 1 degree;
the hydrological data model comprises snow water and underground 0-2m soil water content.
4. The method of claim 2, wherein the seismic precursor anomaly information extraction method based on the unfiltered maximum shear strain,
the order of the GRACE spherical harmonic coefficient after the hydrographic factors are removed is 96 orders.
5. The method of claim 1, wherein the seismic precursor anomaly information extraction method based on the unfiltered maximum shear strain,
the lunar difference data model comprises data of two years before earthquake.
6. The method of claim 1, wherein the seismic precursor anomaly information extraction method based on the unfiltered maximum shear strain,
the S4 includes constructing the maximum shear strain time series based on the maximum eigenvalue and the minimum eigenvalue of the lagrangian gravitational strain tensor.
7. The method of claim 1, wherein the seismic precursor anomaly information extraction method based on the unfiltered maximum shear strain,
the "k σ" criterion is a criterion for identifying an abnormality in the feature point time series, and the k value of the "k σ" criterion is set to 3.2.
8. The method of claim 1, wherein the seismic precursor anomaly information extraction method based on the unfiltered maximum shear strain,
the spatial range is 5 ° × 5 °;
and obtaining the deviation index through the mean value and the standard deviation of the maximum shear strain time series based on each unit cell in the space range.
9. The method of claim 1, wherein the seismic precursor anomaly information extraction method based on the unfiltered maximum shear strain,
the formula of the shift index is:
wherein K is the offset index, MSH is the maximum shear strain value, muMSHIs the mean value of the maximum shear strain time series, σMSHThe maximum shear strain time series standard deviation.
10. The method as claimed in claim 1, wherein the S5 further includes, based on the migration index, drawing a seismic example feature map of the target area through the abnormal data extraction model, based on the time feature and the space feature of the seismic example feature map, obtaining the earthquake-front maximum shear anomaly information through the abnormal data extraction model, comparing the migration index of the earthquake year and the earthquake-free period of the target area, constructing a correlation model of the migration index and the geological structure activity of the target area, and based on the migration index, pre-warning whether the target area has earthquake-front gravity anomaly.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110116597.6A CN112926189B (en) | 2021-01-28 | 2021-01-28 | An information extraction method of earthquake precursory anomalies based on unfiltered maximum shear strain |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110116597.6A CN112926189B (en) | 2021-01-28 | 2021-01-28 | An information extraction method of earthquake precursory anomalies based on unfiltered maximum shear strain |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112926189A CN112926189A (en) | 2021-06-08 |
| CN112926189B true CN112926189B (en) | 2022-03-11 |
Family
ID=76168333
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110116597.6A Expired - Fee Related CN112926189B (en) | 2021-01-28 | 2021-01-28 | An information extraction method of earthquake precursory anomalies based on unfiltered maximum shear strain |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112926189B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114238301B (en) * | 2021-12-23 | 2025-03-25 | 国家石油天然气管网集团有限公司 | A method and system for eliminating invalid data for stress monitoring |
| CN118364229B (en) * | 2024-06-19 | 2024-10-15 | 中国船舶集团有限公司第七〇七研究所 | Denoising method for measurement data of relative gravimeter |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6675097B2 (en) * | 1999-04-02 | 2004-01-06 | Conoco Inc. | Nonlinear constrained inversion method to determine base of salt interface from gravity and gravity tensor data |
-
2021
- 2021-01-28 CN CN202110116597.6A patent/CN112926189B/en not_active Expired - Fee Related
Non-Patent Citations (1)
| Title |
|---|
| 汶川地震前后的重力异常变化特征分析;鲁勇波;《测绘工程》;20181123;第7卷(第12期);第4-7页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112926189A (en) | 2021-06-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Liu et al. | The high-resolution community velocity model V2. 0 of southwest China, constructed by joint body and surface wave tomography of data recorded at temporary dense arrays | |
| Dong et al. | Detection and displacement characterization of landslides using multi-temporal satellite SAR interferometry: A case study of Danba County in the Dadu River Basin | |
| CN103824133B (en) | A kind of granite type U-ore field prospective area Comprehensive Prediction Method | |
| Jordan et al. | Inland extent of the Weddell Sea Rift imaged by new aerogeophysical data | |
| CN112926189B (en) | An information extraction method of earthquake precursory anomalies based on unfiltered maximum shear strain | |
| Sarjan et al. | Delineation of upper crustal structure beneath the island of Lombok, Indonesia, using ambient seismic noise tomography | |
| Paoletti et al. | The Ischia volcanic island (Southern Italy): inferences from potential field data interpretation | |
| Wu et al. | High‐Resolution Velocity and Seismic Anisotropy Structures of the 2021 M s 6.0 Luxian Earthquake Zone in Sichuan Basin | |
| Ganas et al. | Left-lateral shear inside the North Gulf of Evia Rift, Central Greece, evidenced by relocated earthquake sequences and moment tensor inversion | |
| De Ritis et al. | High resolution magnetic anomalies, volcanism and tectonics of the active “La Fossa” vulcanic system (Vulcano island) and Lipari Island (South Italy) | |
| Strollo et al. | The uppermost crust structure of Ischia (southern Italy) from ambient noise Rayleigh waves | |
| Dai et al. | Generalization of PhaseNet in Shandong and its application to the Changqing M4. 1 earthquake sequence | |
| Yonghai et al. | Extraction of two tsunamis signals generated by earthquakes around the Pacific rim | |
| Wang et al. | A method for extracting the preseismic gravity anomalies over the Tibetan Plateau based on the maximum shear strain using GRACE data | |
| Adeniyia et al. | Qualitative and quantitative interpretations of high-resolution aeromagnetic data of Saki-East area, for basement and structural framework | |
| Mala et al. | Earthquake Microzonation Study on Batubesi Dam of Nuha, East Luwu, South Sulawesi, Indonesia | |
| Kokowski et al. | Epicenter accuracy for seismic events recorded on the LUMINEOS network in Legnica-Głogów Copper District, Poland | |
| Zhu et al. | Surface Deformation Monitoring in Shiyan Based on Multi-Temporal Insar Technology | |
| Sayyid et al. | The 25 november 2018 Mw 6.3 Iraq-Iran border earthquake by using InSAR technique | |
| CN115166846B (en) | Regional ground gravity change continuous monitoring method based on load deformation | |
| CN114926509B (en) | Ground stress blocking display area remote sensing tracking method based on satellite microwave brightness temperature | |
| Badarch et al. | Estimation of tectonic fault systems of mongolian territory using geomagnetic anomaly data | |
| Ventura et al. | Monitoring and structural significance of ground deformations at Campi Flegrei supervolcano (Italy) from the combined 2D and 3D analysis of PS-InSAR, geophysical, geological and structural data | |
| Huigui et al. | Shallow crustal velocity structure and tectonic significance beneath Fildes Peninsula, West Antarctica | |
| Cho et al. | Ionospheric Irregularities Signature Correlation on ROT Variation for Earthquake Detection and Epicenter Estimation: Case Study of Tohoku (2011) & Turkey-Syria (2023) Earthquakes |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20220311 |