An automatic extraction method and system for crustal strain rate field anomalies

Abstract

The application discloses a kind of crustal strain rate field anomaly automatic extraction method and system, it is related to strain rate anomaly identification field, the method, comprising: obtaining the strain rate data of each position point in target area;Calculate principal strain rate standard deviation;The data of the principal strain rate standard deviation greater than the set multiple in principal strain rate data is extracted to obtain target data;From strain rate data, extract the surface strain rate of each principal strain rate anomaly point position;Determine the principal strain rate anomaly range circle based on the surface strain rate of principal strain rate anomaly point position;In target area, draw the surface strain rate contour line with 0 value as center, to determine surface strain rate anomaly range;Determine shear strain rate anomaly range based on the statistical histogram of shear strain rate;According to principal strain rate anomaly range circle, surface strain rate anomaly range and shear strain rate anomaly range, determine the crustal strain rate field anomaly area of target area.The application can improve the accuracy of crustal strain rate field anomaly area identification.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of strain rate anomaly identification, and in particular to a crustal strain rate field anomaly automatic extraction method and system. BACKGROUND

[0002] Long-term strain rate anomaly regions have a good corresponding relationship with regional historical earthquake events. For example, the earthquake risk regions determined by the alternating transformation of surface shrinkage and surface expansion and the maximum shear strain rate high-value regions and edge zones have good consistency with the distribution of historical earthquakes.

[0003] Currently, the identification of abnormal regions usually requires manual intervention. Although the identified strain rate anomaly regions have certain indicative significance for the determination of earthquake risk regions, different decision-makers with different experiences and backgrounds often interpret different abnormal regions. Therefore, there is a problem that the determination of the range of the risk region has a strong subjective factor. Lack of professional experience and personal emotions are the most common influencing factors in the process of strain rate anomaly identification. Whether it is lack of experience or personal emotions, rational thinking will be stifled during identification, which usually cannot accurately identify the strain rate anomaly region. SUMMARY

[0004] Therefore, the embodiments of the present application provide a crustal strain rate field anomaly automatic extraction method and system to improve the accuracy of the identification of the crustal strain rate field anomaly region.

[0005] To achieve the above object, the present application provides the following scheme:

[0006] A crustal strain rate field anomaly automatic extraction method, comprising:

[0007] Obtaining strain rate data of each position point in a target region; the strain rate data includes principal strain rate, surface strain rate and shear strain rate; the principal strain rate includes maximum principal strain rate and minimum principal strain rate;

[0008] Calculating the standard deviation of the principal strain rate; the standard deviation of the principal strain rate includes a first standard deviation and a second standard deviation; the first standard deviation is the standard deviation of the maximum principal strain rate of all position points; and the second standard deviation is the standard deviation of the minimum principal strain rate of all position points;

[0009] Extracting data greater than the set multiple of the standard deviation of the principal strain rate from the principal strain rate to obtain target data, and determining the position point corresponding to the target data as a principal strain rate anomaly point;

[0010] Extracting the surface strain rate of each principal strain rate anomaly point from the strain rate data;

[0011] determine a main strain rate anomaly range circle based on the plane strain rate of the main strain rate anomaly point and a first set range; the first set range is a region with the main strain rate anomaly point as the center and a first set distance as the diameter;

[0012] draw a plane strain rate contour centered on a 0 value in the target region, and determine a 0 value buffer zone in a second set range according to the plane strain rate contour using a buffer zone analysis method, and determine the 0 value buffer zone as a plane strain rate anomaly range;

[0013] calculate a statistical histogram of shear strain rates in the strain rate data;

[0014] determine a shear strain rate anomaly range based on the statistical histogram;

[0015] determine a crustal strain rate field anomaly region of the target region according to the main strain rate anomaly range circle, the plane strain rate anomaly range and the shear strain rate anomaly range.

[0016] Optionally, the main strain rate anomaly range circle is determined based on the plane strain rate of the main strain rate anomaly point and a first set range, and specifically includes:

[0017] determine a matching data set according to the plane strain rate; the matching data set includes each main strain rate anomaly point and a corresponding difference maximum point sequence number; the difference maximum point sequence number is a sequence number of a point with the largest difference in plane strain rate from the main strain rate anomaly point among adjacent points; the adjacent points are points adjacent to the main strain rate anomaly point within a first set range;

[0018] calculate an average longitude and an average latitude of all main strain rate anomaly points according to the matching data set;

[0019] determine a position with the average longitude and the average latitude as the center and the first set distance as the diameter to construct a main strain rate anomaly range circle.

[0020] Optionally, the shear strain rate anomaly range is determined based on the statistical histogram, and specifically includes:

[0021] determine a shear strain rate with the most occurrences in the statistical histogram as a background mean value;

[0022] calculate a shear strain rate standard deviation according to the background mean value;

[0023] determine a shear strain rate anomaly range according to the background mean value and the shear strain rate standard deviation.

[0024] Optionally, the determining the crust strain rate field anomaly region of the target region according to the principal strain rate anomaly range circle, the plane strain rate anomaly range and the shear strain rate anomaly range specifically comprises:

[0025] The principal strain rate anomaly range circle and the plane strain rate anomaly range are intersected to obtain an intersection region;

[0026] The crust strain rate field anomaly region of the target region is determined according to the intersection region and the shear strain rate anomaly range.

[0027] Optionally, the determining the shear strain rate anomaly range according to the background mean value and the shear strain rate standard deviation specifically comprises:

[0028] The shear strain rate anomaly point is determined according to the background mean value and the shear strain rate standard deviation; the shear strain rate anomaly point satisfies Shear abnorm > Shear mean + 2 * Shear std ; wherein, Shear abnorm represents the shear strain rate anomaly point; Shear mean represents the background mean value; Shear std represents the shear strain rate standard deviation.

[0029] The shear strain rate anomaly range is determined according to all shear strain rate anomaly points.

[0030] The application further provides a crust strain rate field anomaly automatic extraction system, comprising:

[0031] A strain data acquisition module is configured to acquire strain rate data of each position point in a target region; the strain rate data comprises principal strain rate, plane strain rate and shear strain rate; the principal strain rate comprises maximum principal strain rate and minimum principal strain rate;

[0032] A standard deviation calculation module is configured to calculate principal strain rate standard deviation; the principal strain rate standard deviation comprises first standard deviation and second standard deviation; the first standard deviation is the standard deviation of the maximum principal strain rate of all position points; the second standard deviation is the standard deviation of the minimum principal strain rate of all position points;

[0033] A principal strain rate anomaly point position determination module is configured to extract data greater than a set multiple of the principal strain rate standard deviation from the principal strain rate to obtain target data, and determine a position point corresponding to the target data as a principal strain rate anomaly point position;

[0034] A plane strain rate determination module is configured to extract the plane strain rate of each principal strain rate anomaly point position from the strain rate data;

[0035] The main strain rate anomaly range circle determination module is configured to determine a main strain rate anomaly range circle based on the surface strain rate of the main strain rate anomaly point and a first set range, wherein the first set range is a region with the main strain rate anomaly point as the center and a first set distance as the diameter.

[0036] The surface strain rate anomaly range determination module is configured to draw a surface strain rate contour with 0 as the center in the target region, and determine a 0-value buffer zone in a second set range according to the surface strain rate contour by using a buffer zone analysis method, and determine the 0-value buffer zone as a surface strain rate anomaly range.

[0037] The statistical histogram calculation module is configured to calculate a statistical histogram of shear strain rates in the strain rate data.

[0038] The shear strain rate anomaly range determination module is configured to determine a shear strain rate anomaly range based on the statistical histogram.

[0039] The anomaly region determination module is configured to determine a crustal strain rate field anomaly region of the target region according to the main strain rate anomaly range circle, the surface strain rate anomaly range and the shear strain rate anomaly range.

[0040] Optionally, the main strain rate anomaly range circle determination module specifically includes:

[0041] The matching data set determination unit is configured to determine a matching data set according to the surface strain rate, wherein the matching data set includes each main strain rate anomaly point and a corresponding difference maximum point sequence number, the difference maximum point sequence number is a sequence number of a point with the largest difference in surface strain rate from the main strain rate anomaly point among adjacent points, and the adjacent points are points adjacent to the main strain rate anomaly point within a first set range.

[0042] The latitude and longitude calculation unit is configured to calculate an average longitude and an average latitude of all main strain rate anomaly points according to the matching data set.

[0043] The main strain rate anomaly determination unit is configured to construct a main strain rate anomaly range circle with a position determined by the average longitude and the average latitude as the center and the first set distance as the diameter.

[0044] Optionally, the shear strain rate anomaly range determination module specifically includes:

[0045] The background mean value determination unit is configured to determine a shear strain rate with the largest number of occurrences in the statistical histogram as a background mean value.

[0046] The shear strain rate standard deviation calculation unit is configured to calculate a shear strain rate standard deviation according to the background mean value.

[0047] The shear strain rate anomaly determining unit is configured to determine a shear strain rate anomaly range according to the background mean value and the shear strain rate standard deviation.

[0048] Optionally, the anomaly region determining module specifically comprises:

[0049] The intersection unit is configured to intersect the main strain rate anomaly range circle and the surface strain rate anomaly range to obtain an intersection region.

[0050] The anomaly region determining unit is configured to determine a crustal strain rate field anomaly region of the target region according to the intersection region and the shear strain rate anomaly range.

[0051] Optionally, the shear strain rate anomaly determining unit specifically comprises:

[0052] The shear strain rate anomaly point determining subunit is configured to determine a shear strain rate anomaly point according to the background mean value and the shear strain rate standard deviation; the shear strain rate anomaly point satisfies Shear abnorm > Shear mean + 2 * Shear std ; wherein, Shear abnorm represents a shear strain rate anomaly point; Shear mean represents a background mean value; Shear std represents a shear strain rate standard deviation.

[0053] The anomaly range determining subunit is configured to determine a shear strain rate anomaly range according to all shear strain rate anomaly points.

[0054] Compared with the prior art, the method has the beneficial effects that:

[0055] The method for automatically extracting a crustal strain rate field anomaly region comprises the following steps: extracting target data from main strain rate data, which is greater than a set multiple of a main strain rate standard deviation; extracting surface strain rate of each main strain rate anomaly point from strain rate data; determining a main strain rate anomaly range circle based on the surface strain rate of the main strain rate anomaly point; drawing a surface strain rate contour line with 0 as the center in a target region to determine a surface strain rate anomaly range; determining a shear strain rate anomaly range based on a statistical histogram of shear strain rate in the strain rate data; and finally determining a crustal strain rate field anomaly region of the target region according to the main strain rate anomaly range circle, the surface strain rate anomaly range and the shear strain rate anomaly range. BRIEF DESCRIPTION OF DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings described below only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0057] Figure 1 The flow chart of the crustal strain rate field anomaly automatic extraction method provided by the embodiments of the present application is shown in the figure.

[0058] Figure 2 The strain rate field and the distribution of Ms≥5.0 earthquakes during the period calculated based on the GNSS continuous observation station data of Yunnan region from 2019 to 2022 are shown in the figure.

[0059] Figure 3 The strain rate field and the distribution of Ms≥5.0 earthquakes during the period calculated based on the GNSS continuous observation station data of Yunnan region from 2019 to 2022 are shown in the figure.

[0060] Figure 4 The strain rate field and the distribution of Ms≥5.0 earthquakes during the period calculated based on the GNSS continuous observation station data of Yunnan region from 2019 to 2022 are shown in the figure.

[0061] Figure 5 The strain rate field and the distribution of Ms≥5.0 earthquakes during the period calculated based on the GNSS continuous observation station data of Yunnan region from 2019 to 2022 are shown in the figure.

[0062] Figure 6 The strain rate field and the distribution of Ms≥5.0 earthquakes during the period calculated based on the GNSS continuous observation station data of Yunnan region from 2019 to 2022 are shown in the figure.

[0063] Figure 7 The structure diagram of the crustal strain rate field anomaly automatic extraction system provided by the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0065] The prior art method is often determined by human experience, and cannot accurately identify the strain rate anomaly. The computer and mathematics do not have emotion, so the model quantification eliminates the irrational factors, and the best probability distribution range of the dangerous area can be obtained through programmed calculation. Therefore, it is necessary to further replace the subjective judgment of human with a mathematical model to display the abnormal feature dangerous area. The strain rate field anomaly feature risk area is determined by a mathematical model, which can greatly reduce the influence of subjective judgment of human and more clearly display the strain rate field anomaly area.

[0066] In order to make the above-mentioned purposes, characteristics and advantages of the present application more apparent, obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0067] Figure 1 The flow chart of the crust strain rate field anomaly automatic extraction method provided by the embodiment of the present application is shown in Figure 1 The method is realized based on the numerical calculation of the principal strain rate, the surface strain rate and the maximum shear strain rate anomaly, and the method comprises the following steps:

[0068] Step 101: obtaining the strain rate data of each position point in the target area and calculating the principal strain rate standard deviation; the strain rate data comprises the principal strain rate, the surface strain rate and the shear strain rate; the principal strain rate comprises the maximum principal strain rate and the minimum principal strain rate. The principal strain rate standard deviation comprises a first standard deviation and a second standard deviation. The first standard deviation is the standard deviation of the maximum principal strain rate of all position points; the second standard deviation is the standard deviation of the minimum principal strain rate of all position points. Specifically:

[0069] The principal strain rate of each position point obtained by the strain rate model is taken as the input data, and the standard deviation P 1std of the maximum principal strain rate P1 of all position points in the target area is calculated, that is, the first standard deviation; the standard deviation P 2std of the minimum principal strain rate P2 of all position points in the target area is calculated, that is, the second standard deviation.

[0070] Step 102: extracting the data greater than the set multiple of the principal strain rate standard deviation in the principal strain rate to obtain target data, and determining the position point corresponding to the target data as the principal strain rate anomaly point. Specifically:

[0071] The maximum principal strain rate P1 and the minimum principal strain rate P2 are extracted respectively, and the absolute value of the maximum principal strain rate P1 and the minimum principal strain rate P2 is greater than 2 times the principal strain rate standard deviation (P 1std , P 2std ), to obtain the target data (P 1std_abnorm , P 2std_abnorm ).

[0072]

[0073] wherein std represents the standard deviation.

[0074] Step 103: extracting the surface strain rate of each of the principal strain rate anomaly point positions from the strain rate data. Specifically:

[0075] On the basis of the target data P 1std_abnorm , P 2std_abnorm , the maximum principal strain rate P std_abnorm and the minimum principal strain rate P 1i of the i-th principal strain rate anomaly point position in the data set P 2i are summed up to obtain the surface strain rate Δ i of the i-th principal strain rate anomaly point position.

[0076]

[0077] wherein n represents the number of principal strain rate anomaly point positions in the data set composed of target data, and Δ n represents the surface strain rate of the n-th principal strain rate anomaly point position.

[0078] Step 104: determining the principal strain rate anomaly range circle based on the surface strain rate of the principal strain rate anomaly point position and the first set range; the first set range is a region with the principal strain rate anomaly point position as the center and the first set distance as the diameter.

[0079] The step 104 specifically includes:

[0080] 1) determining the matching data set according to the surface strain rate; the matching data set includes each of the principal strain rate anomaly point positions and the corresponding maximum difference point position sequence number; the maximum difference point position sequence number is the sequence number of the point position with the maximum difference in surface strain rate from the principal strain rate anomaly point position among adjacent point positions; the adjacent point positions are the point positions adjacent to the principal strain rate anomaly point position within the first set range. Specifically:

[0081] The first set distance R is selected according to the strain rate data resolution, and the surface strain rate Δ std_abnorm of each principal strain rate anomaly point position i in the data set P i and the sequence number j of the point position with the maximum difference in surface strain rate from the adjacent point positions within the first set range of the point position with a distance R, i.e. the maximum difference point position sequence number, are counted respectively, so as to finally obtain the data set A corresponding to each of the principal strain rate anomaly point positions and the corresponding maximum difference point position sequence number, i.e. the matching data set.

[0082] 2) calculating the average longitude and the average latitude of all the principal strain rate anomaly point positions according to the matching data set. Specifically:

[0083] One principal strain rate anomaly point in the data set A corresponds to one difference maximum point position sequence number. Different principal strain rate anomaly points may correspond to the same difference maximum point position sequence number. Therefore, based on the one-to-one correspondence between n in the data set A and i and j, the data subset A is obtained by grouping according to the index j. j The data subset A j includes at least one pair of data pairs (i, j). If the data subset A j includes only one pair of data pairs, the difference maximum point position sequence number j corresponds to only one principal strain rate anomaly point (the value of i is unique). If the data subset A j includes multiple pairs of data pairs, the difference maximum point position sequence number j corresponds to multiple principal strain rate anomaly points (the value of i is not unique). The average latitude Lat mean and the average longitude Lon mean corresponding to the principal strain rate anomaly point are calculated according to the following formula:

[0084]

[0085]

[0086] Wherein, Lat i represents the latitude of the i th principal strain rate anomaly point; Lat j represents the latitude corresponding to the difference maximum point position sequence number j of the i th principal strain rate anomaly point; Lon i represents the longitude of the i th principal strain rate anomaly point; Lon j represents the longitude corresponding to the difference maximum point position sequence number j of the i th principal strain rate anomaly point; and m represents the number of i and j under the condition of A j .

[0087] 3) The position determined by the average latitude Lat mean and the average longitude Lon mean is taken as the center, and the first set distance R is taken as the diameter to construct a principal strain rate anomaly range circle.

[0088] Step 105: A surface strain rate contour centered on 0 value is drawn in the target area, and a 0 value buffer zone in a second set range is determined by using a buffer zone analysis method according to the surface strain rate contour. The 0 value buffer zone is determined as a surface strain rate anomaly range. The 0 value buffer zone is a region in which positive and negative values change alternately near the surface strain rate 0 value.

[0089] Step 106: A statistical histogram of shear strain rate in the strain rate data is calculated.

[0090] Step 107: A shear strain rate anomaly range is determined based on the statistical histogram.

[0091] The step 107 specifically includes:

[0092] 1) The mode of the statistical histogram is determined as the background mean value.

[0093] 2) The standard deviation of the shear strain rate is calculated according to the background mean value.

[0094] 3) The shear strain rate anomaly range is determined according to the background mean value and the standard deviation of the shear strain rate. Specifically:

[0095] The shear strain rate anomaly point is determined according to the background mean value and the standard deviation of the shear strain rate; the shear strain rate anomaly point satisfies Shear abnorm > Shear mean + 2 * Shear std ; wherein, Shear abnorm represents the shear strain rate anomaly point; Shear mean represents the background mean value; and Shear std represents the standard deviation of the shear strain rate.

[0096] The shear strain rate anomaly range, i.e. Shear abnorm , is determined according to all shear strain rate anomaly points; Shear abnorm represents the shear strain rate anomaly range.

[0097] Step 108: The crustal strain rate field anomaly region of the target region is determined according to the principal strain rate anomaly range circle, the surface strain rate anomaly range, and the shear strain rate anomaly range.

[0098] The step 108 specifically includes:

[0099] 1) The intersection region is obtained by intersecting the principal strain rate anomaly range circle and the surface strain rate anomaly range.

[0100] 2) The crustal strain rate field anomaly region of the target region is determined according to the intersection region and the shear strain rate anomaly range. The crustal strain rate field anomaly region is used to determine the quantitative risk region of earthquake occurrence.

[0101] The effectiveness of the method proposed in the embodiment is verified below.

[0102] The basic understanding of earthquake preparation at home and abroad at present is that the ductile layer in the lower crust is in a steady state of relative movement and is not locked for a long time, the brittle layer in the upper crust is hindered by the relative movement, leading to strain rate accumulation, and the elastic strain rate is released by coseismic rupture, so that the relative movement of the upper crust and the relative movement of the deep ductile layer tend to be consistent. As can be seen, studying the long-term elastic strain rate accumulation state of the crust is a way to determine the medium and long-term dangerous place of an earthquake.

[0103] Firstly, based on the strain rate field results of Yunnan regional GNSS continuous observation stations in 2019-2022 and GNSS mobile observation stations in 2015-2018, combined with Ms≥5.0 and Ms≥4.5 earthquakes occurred in Yunnan region during the period, the abnormal characteristics of the overall strain rate background field in Yunnan region were discussed.

[0104] Figure 2 The strain rate field calculated based on the data of Yunnan regional GNSS continuous observation stations in 2019-2022 and the distribution of Ms≥5.0 earthquakes during the period are shown, where the five-point star represents the location of the earthquake event, Figure 2 Part (a) of the figure is the plane strain rate and principal strain rate, Figure 2 Part (b) of the figure is the maximum shear strain rate. From the plane strain rate and principal strain rate, the plane strain rate in the Deqin town area of the Sichuan-Yunnan-Tibet junction, the Yongsheng Xiaguan area of northwest Yunnan, the left side of the Xiaojiang fault zone in Yuxi, the north of Qiaojia in northeast Yunnan and the intersection of the southern segment of the Xiaojiang fault zone and the Red River fault zone is positive, with a maximum value of 4.56×10 -8 / a, the Yanyuan area of the Sichuan-Yunnan junction, the Weixian Changning area east of small west Yunnan, the Luodian Huize area of northeast Yunnan and the middle segment of the Xiaojiang fault zone have negative plane strain rates, with a minimum value of -5.57×10 -8 / a. Overall, the plane strain rate shows alternating compression and tension, indicating the complex geological structure and earthquake preparation activities in Yunnan region. There are three relatively significant areas, including the east strip of northwest Yunnan, the southern part of the Xiaojiang fault zone and the junction of northeast Yunnan and Sichuan. From the historical earthquake data of Ms≥5.0 and above during the period, such as the Qiaojia Ms5.0 earthquake on May 18, 2020, the Yangpo Ms6.4 earthquake on May 21, 2021, the Shuangbai Ms5.1 earthquake on June 10, 2021 and the Ninglang Ms5.5 earthquake on January 2, 2022, most of them occurred between the inflation and compression areas of the plane strain rate, i.e. the intersection of normal and reverse faults.

[0105] From the maximum shear strain rate, there are several high-value areas of maximum shear strain rate, mainly along the Xiaojiang fault zone and along the east strip of northwest Yunnan. Among them, the northern and southern parts of the Xiaojiang fault zone, the Yongsheng-Ninglang area and the Yangpo-Weixian Changning area are more prominent, with a maximum value of 11.45×10 -8 / a. These areas are regions with more historical earthquakes in Yunnan, which is consistent with the fact that most earthquakes in Yunnan are caused by fault strike-slip motion. From the historical earthquakes during the period, it was found that most Ms≥5.0 and above earthquakes in Yunnan region occurred in high-value areas and marginal areas of the maximum shear strain rate.

[0106] Figure 3The strain rate field calculated based on the GNSS flow observation station data in Yunnan region from 2015 to 2018 and the distribution of Ms≥5.0 earthquakes during the period are shown, where the pentagram represents the location of the earthquake event, Figure 3 Part (a) is the plane strain rate and principal strain rate, Figure 3 Part (b) is the maximum shear strain rate. From the plane strain rate and the principal strain rate, similar to the results of the GNSS continuous observation station from 2019 to 2022, the same phenomenon of tension and compression alternation is presented, and it is also more significant in the eastern belt of northwest Yunnan, the southern part of Xiaojiang fault zone, and the border between northeast Yunnan and Sichuan. From the maximum shear strain rate, the high-value area is mainly along the Xiaojiang fault zone, the eastern belt of northwest Yunnan, and the Simao area in southwest Yunnan, with only partial differences. The similarity in spatial distribution of plane strain rate and maximum shear strain rate in different periods indicates that due to the relative stability and inheritance of tectonics and relative motion, the strain rate accumulation area may remain in the high-value abnormal area for a long time, and the easy rupture zone is likely to trigger a series of earthquakes, but it does not necessarily release all the energy, and the strain rate accumulation is still developing, i.e., the earthquake is still in gestation. In addition, by statistically analyzing the historical earthquakes in Yunnan region during the period, it is found that Ms≥5.0 earthquakes in Yunnan region tend to occur between the plane expansion area and the plane compression area, as well as in the high-value area of the maximum shear strain rate and the edge area. In addition, due to the more intensive distribution of GNSS flow observation stations than GNSS continuous observation stations, the strain rate results based on GNSS flow observation stations from 2015 to 2018 can scan more detailed information, and it is found that some Ms≥4.5 earthquakes during the period also conform to the above phenomenon, Figure 4 The strain rate field calculated based on the GNSS flow observation station data in Yunnan region from 2015 to 2018 and the distribution of Ms≥4.5 earthquakes during the period are shown, where the pentagram represents the location of the earthquake event, as shown in Figure 4 Figure 4 Part (a) is the plane strain rate and principal strain rate, Figure 4 Part (b) is the maximum shear strain rate.

[0107] In summary, the occurrence of strong earthquakes requires long-term strain rate accumulation and the strain rate accumulation tends to reach a limit state, and a long-term strain rate accumulation background with high strain rate is conducive to the occurrence of strong earthquakes. From the historical earthquakes that occurred during the statistical period, Ms≥5.0 earthquakes in Yunnan region mostly occurred between the plane expansion area and the plane compression area, as well as in the high shear strain rate area and the boundary of strain rate gradient. This conclusion is consistent with the understanding of strong earthquake risk areas by Jiang Zaisen and other scholars. Therefore, the determination of strain rate abnormal areas has certain indicative significance for identifying earthquake risk areas.

[0108] ​Based on the method proposed in the embodiment, the strain rate field anomaly characteristic regions of GNSS continuous observation stations from 2019 to 2022 and the strain rate field anomaly characteristic regions of GNSS flow observation stations from 2015 to 2018 mentioned above are calculated respectively, and the relevant earthquake focal mechanism solutions in the statistical time range are downloaded from GlobalCMT, and the results are as shown in Figure 5 and Figure 6 , wherein the contour lines are shear strain rate anomaly regions, and the dotted circular lines are the intersection ranges of the surface strain rate anomaly and the principal strain rate anomaly.

[0109] As can be seen from Figure 5 and Figure 6 , the risk region delineation model proposed in the embodiment according to the principal strain rate, the surface strain rate and the maximum shear strain rate anomaly region more clearly shows the earthquake risk region. The delineated region has a good corresponding relationship with most earthquakes in the period, and from the earthquake focal mechanism solution information, it can be seen that the earthquake rupture earthquake nature and the results of the method proposed in the embodiment match well. The shear strain rate anomaly region has a larger probability of occurring a strike-slip component earthquake, and the surface strain rate anomaly region also has a larger probability of occurring a normal fault or thrust component earthquake. The method enriches the determination method of the earthquake location and the earthquake focal mechanism.

[0110] The application further provides an automatic crustal strain rate field anomaly extraction system, which is shown in Figure 7 , and the system comprises:

[0111] A strain data acquisition module 701 is configured to acquire strain rate data of each position point in a target region; the strain rate data comprises a principal strain rate, a surface strain rate and a shear strain rate; the principal strain rate comprises a maximum principal strain rate and a minimum principal strain rate.

[0112] A standard deviation calculation module 702 is configured to calculate a principal strain rate standard deviation; the principal strain rate standard deviation comprises a first standard deviation and a second standard deviation; the first standard deviation is a standard deviation of the maximum principal strain rate of all position points; and the second standard deviation is a standard deviation of the minimum principal strain rate of all position points.

[0113] A principal strain rate anomaly point position determination module 703 is configured to extract data greater than a set multiple of the principal strain rate standard deviation from the principal strain rate to obtain target data, and determine a position point corresponding to the target data as a principal strain rate anomaly point position.

[0114] A surface strain rate determination module 704 is configured to extract a surface strain rate of each principal strain rate anomaly point position from the strain rate data.

[0115] The main strain rate anomaly range circle determination module 705 is configured to determine a main strain rate anomaly range circle based on the surface strain rate of the main strain rate anomaly point and a first set range. The first set range is a region with the main strain rate anomaly point as the center and a first set distance as the diameter.

[0116] The surface strain rate anomaly range determination module 706 is configured to draw a surface strain rate contour with 0 as the center in the target region, and determine a 0 value buffer zone in a second set range according to the surface strain rate contour by using a buffer zone analysis method. The 0 value buffer zone is determined as the surface strain rate anomaly range.

[0117] The statistical histogram calculation module 707 is configured to calculate a statistical histogram of the shear strain rate in the strain rate data.

[0118] The shear strain rate anomaly range determination module 708 is configured to determine a shear strain rate anomaly range based on the statistical histogram.

[0119] The anomaly region determination module 709 is configured to determine a crustal strain rate field anomaly region of the target region according to the main strain rate anomaly range circle, the surface strain rate anomaly range and the shear strain rate anomaly range.

[0120] In one example, the main strain rate anomaly range circle determination module 705 specifically includes:

[0121] The matching data set determination unit is configured to determine a matching data set according to the surface strain rate. The matching data set includes each main strain rate anomaly point and a corresponding difference maximum point sequence number. The difference maximum point sequence number is the sequence number of a point with the largest difference in surface strain rate from the main strain rate anomaly point among adjacent points. The adjacent points are points adjacent to the main strain rate anomaly point within the first set range.

[0122] The latitude and longitude calculation unit is configured to calculate the average longitude and the average latitude of all main strain rate anomaly points according to the matching data set.

[0123] The main strain rate anomaly determination unit is configured to construct a main strain rate anomaly range circle with the position determined by the average longitude and the average latitude as the center and the first set distance as the diameter.

[0124] In one example, the shear strain rate anomaly range determination module 708 specifically includes:

[0125] The background mean value determination unit is configured to determine the shear strain rate with the largest number of occurrences in the statistical histogram as the background mean value.

[0126] The shear strain rate standard deviation calculation unit is configured to calculate the shear strain rate standard deviation according to the background mean value.

[0127] The shear strain rate anomaly determining unit is configured to determine a shear strain rate anomaly range according to the background mean value and the shear strain rate standard deviation.

[0128] In one example, the anomaly region determining module 709 specifically comprises:

[0129] The intersection unit is configured to intersect the main strain rate anomaly range circle and the surface strain rate anomaly range to obtain an intersection region.

[0130] The anomaly region determining unit is configured to determine a crustal strain rate field anomaly region of the target region according to the intersection region and the shear strain rate anomaly range.

[0131] In one example, the shear strain rate anomaly determining unit specifically comprises:

[0132] The shear strain rate anomaly point determining subunit is configured to determine a shear strain rate anomaly point according to the background mean value and the shear strain rate standard deviation; the shear strain rate anomaly point satisfies Shear abnorm > Shear mean + 2 * Shear std ; wherein, Shear abnorm represents a shear strain rate anomaly point; Shear mean represents a background mean value; Shear std represents a shear strain rate standard deviation.

[0133] The anomaly range determining subunit is configured to determine a shear strain rate anomaly range according to all shear strain rate anomaly points.

[0134] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts between the various embodiments can be mutually referred to. For the system disclosed in the embodiments, the description is relatively simple because it corresponds to the method disclosed in the embodiments. The relevant parts can be referred to in the method part.

[0135] The principles and implementation manners of the present application are described by using specific examples in the present application. The above description of the embodiments is only used to help understand the method of the present application and its core idea; meanwhile, for the general technical personnel in the field, the specific implementation manners and application ranges will be changed according to the idea of the present application. In conclusion, the content of the specification should not be understood as the limitation of the present application.

Claims

1. A method for automatically extracting crustal strain rate field anomalies, characterized in that, include: Acquire strain rate data at various locations within the target area; The strain rate data includes principal strain rates, surface strain rates, and shear strain rates; the principal strain rates include the maximum principal strain rate and the minimum principal strain rate. Calculate the standard deviation of the principal strain rates; the standard deviation of the principal strain rates includes a first standard deviation and a second standard deviation; the first standard deviation is the standard deviation of the maximum principal strain rate at all locations; the second standard deviation is the standard deviation of the minimum principal strain rate at all locations. Extract the data of the principal strain rate standard deviation that is greater than a set multiple from the principal strain rate to obtain the target data, and determine the location point corresponding to the target data as the principal strain rate anomaly point; Extract the surface strain rate of each principal strain rate anomaly point from the strain rate data; The principal strain rate anomaly range circle is determined based on the surface strain rate at the principal strain rate anomaly point and a first set range; the first set range is the area with the principal strain rate anomaly point as the center and a first set distance as the diameter. Draw surface strain rate contour lines centered at 0 values ​​in the target area, and use the buffer analysis method based on the surface strain rate contour lines to determine the 0 value buffer within a second set range, and define the 0 value buffer as the surface strain rate anomaly range; Calculate the statistical histogram of shear strain rate in the strain rate data; The range of shear strain rate anomalies is determined based on the statistical histogram. The crustal strain rate field anomaly region of the target area is determined based on the principal strain rate anomaly range circle, the surface strain rate anomaly range, and the shear strain rate anomaly range.

2. The method for automatic extraction of crustal strain rate field anomalies according to claim 1, characterized in that, The determination of the principal strain rate anomaly range circle based on the surface strain rate at the principal strain rate anomaly point and the first predetermined range specifically includes: Based on the surface strain rate, a matching dataset is determined; the matching dataset includes each principal strain rate anomaly point and its corresponding maximum difference point number; the maximum difference point number is the number of the point with the largest surface strain rate difference from the principal strain rate anomaly point among the adjacent points; the adjacent points are the points adjacent to the principal strain rate anomaly point within a first set range. Based on the matching dataset, calculate the average longitude and average latitude of all principal strain rate anomaly points; Using the location determined by the average longitude and the average latitude as the center and the first set distance as the diameter, a circle is constructed to represent the range of main strain rate anomalies.

3. The method for automatic extraction of crustal strain rate field anomalies according to claim 1, characterized in that, The determination of the anomaly range of shear strain rate based on the statistical histogram specifically includes: The shear strain rate that appears most frequently in the statistical histogram is determined as the background mean. Calculate the standard deviation of shear strain rate based on the background mean; The range of shear strain rate anomalies is determined based on the background mean and the standard deviation of the shear strain rate.

4. The method for automatic extraction of crustal strain rate field anomalies according to claim 1, characterized in that, The step of determining the crustal strain rate field anomaly region of the target region based on the principal strain rate anomaly range circle, the surface strain rate anomaly range, and the shear strain rate anomaly range specifically includes: The intersection of the principal strain rate anomaly range circle and the surface strain rate anomaly range is obtained to obtain the intersection region; The crustal strain rate anomaly region of the target region is determined based on the intersection region and the shear strain rate anomaly range.

5. The method for automatic extraction of crustal strain rate field anomalies according to claim 3, characterized in that, The step of determining the anomaly range of shear strain rate based on the background mean and the standard deviation of shear strain rate specifically includes: Shear strain rate outliers are determined based on the background mean and the standard deviation of the shear strain rate; the shear strain rate outliers satisfy the Shear strain rate standard deviation. abnorm >Shear mean +2*Shear std Among them, Shear abnorm Indicates anomalies in shear strain rate; Shear mean Shear represents the background mean; std Indicates the standard deviation of shear strain rate; The range of shear strain rate anomalies is determined based on all the shear strain rate anomalies.

6. An automatic extraction system for crustal strain rate field anomalies, characterized in that, include: The strain data acquisition module is used to acquire strain rate data at various locations within the target area; The strain rate data includes principal strain rates, surface strain rates, and shear strain rates; the principal strain rates include the maximum principal strain rate and the minimum principal strain rate. The standard deviation calculation module is used to calculate the standard deviation of the principal strain rates; the standard deviation of the principal strain rates includes a first standard deviation and a second standard deviation; the first standard deviation is the standard deviation of the maximum principal strain rate at all locations; the second standard deviation is the standard deviation of the minimum principal strain rate at all locations. The principal strain rate anomaly point determination module is used to extract the data of the principal strain rate standard deviation that is greater than a set multiple from the principal strain rate, obtain the target data, and determine the location point corresponding to the target data as the principal strain rate anomaly point. A surface strain rate determination module is used to extract the surface strain rate of each of the main strain rate anomaly points from the strain rate data; The principal strain rate anomaly range circle determination module is used to determine the principal strain rate anomaly range circle based on the surface strain rate of the principal strain rate anomaly point and a first set range; the first set range is the area with the principal strain rate anomaly point as the center and a first set distance as the diameter; The surface strain rate anomaly range determination module is used to draw surface strain rate contour lines centered on 0 values ​​in the target area, and to determine a 0 value buffer zone within a second set range based on the surface strain rate contour lines using a buffer analysis method, and to determine the 0 value buffer zone as the surface strain rate anomaly range; The statistical histogram calculation module is used to calculate the statistical histogram of shear strain rate in the strain rate data; The shear strain rate anomaly range determination module is used to determine the shear strain rate anomaly range based on the statistical histogram. An anomalous region determination module is used to determine the crustal strain rate field anomalous region of the target region based on the principal strain rate anomalous range circle, the surface strain rate anomalous range, and the shear strain rate anomalous range.

7. The automatic extraction system for crustal strain rate field anomalies according to claim 6, characterized in that, The module for determining the circle of principal strain rate anomaly range specifically includes: A matching dataset determination unit is used to determine a matching dataset based on the surface strain rate; the matching dataset includes each principal strain rate anomaly point and its corresponding maximum difference point number; the maximum difference point number is the number of the point with the largest surface strain rate difference from the principal strain rate anomaly point among the adjacent points; the adjacent points are points adjacent to the principal strain rate anomaly point within a first set range. The latitude and longitude calculation unit is used to calculate the average longitude and average latitude of all principal strain rate anomaly points based on the matching dataset. The principal strain rate anomaly determination unit is used to construct a circle of principal strain rate anomaly range with the location determined by the average longitude and the average latitude as the center and the first set distance as the diameter.

8. The automatic extraction system for crustal strain rate field anomalies according to claim 6, characterized in that, The shear strain rate anomaly range determination module specifically includes: The background mean determination unit is used to determine the shear strain rate that appears most frequently in the statistical histogram as the background mean. A shear strain rate standard deviation calculation unit is used to calculate the shear strain rate standard deviation based on the background mean. The shear strain rate anomaly determination unit is used to determine the range of shear strain rate anomalies based on the background mean and the standard deviation of the shear strain rate.

9. The automatic extraction system for crustal strain rate field anomalies according to claim 6, characterized in that, The abnormal region determination module specifically includes: Intersection unit, used to find the intersection of the principal strain rate anomaly range circle and the surface strain rate anomaly range to obtain the intersection region; Anomaly region determination unit is used to determine the crustal strain rate field anomaly region of the target region based on the intersection region and the shear strain rate anomaly range.

10. The automatic extraction system for crustal strain rate field anomalies according to claim 8, characterized in that, The shear strain rate anomaly determination unit specifically includes: A shear strain rate anomaly determination subunit is used to determine shear strain rate anomalies based on the background mean and the standard deviation of the shear strain rate; the shear strain rate anomalies satisfy Shear rate... abnorm >Shear mean +2*Shear std Among them, Shear abnorm Indicates anomalies in shear strain rate; Shear mean Shear represents the background mean; std Indicates the standard deviation of shear strain rate; The anomaly range determination sub-unit is used to determine the anomaly range of shear strain rate based on all shear strain rate anomaly points.

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