A method and system for processing earthquake event data based on improved triple seismic phase fitting method

Abstract

The present invention relates to the field of seismic data processing technology, and in particular to a method and system for processing seismic event data based on an improved triple phase fitting method. The present invention first uses P-wave arrival information including triple phases to determine the background velocity structure, and on this basis, based on the triple phase travel time near the interface, an adaptive partitioning algorithm is used to further constrain the interface position. The strategy of inverting the velocity and interface step by step can minimize the trade-off between the interface position and the velocity anomaly. Secondly, while retaining the advantage of the high vertical resolution of the traditional triple phase method, the method reduces the blindness and uncertainty of the model parameter setting in the trial and error method and the grid search method, and also improves the inversion efficiency and accuracy. In addition, the dual constraints of the triple phase arrival time and waveform information are realized, and the degree of waveform fitting can be provided with a quantitative evaluation, which is expected to provide new technical support for the detection of the velocity structure of the mantle transition zone.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic data processing, and in particular to a seismic event data processing method and system based on an improved triple seismic phase fitting method. Background Art

[0002] Existing seismological research results and global velocity models indicate that there are many seismic wave velocities in the Earth's interior.

[0003] Discontinuities provide important constraints on the Earth's internal structure. Generally speaking, velocity discontinuities in the crust and upper mantle include the 660 km discontinuity, 520 km discontinuity, 410 km discontinuity, 220 km discontinuity, lithosphere-asthenosphere interface, and the Moho. Globally, two distinct discontinuities exist at depths of approximately 410 km and 660 km: the 410 km discontinuity and the 660 km discontinuity. The 660 km discontinuity marks the boundary between the upper and lower mantle, and the region between 410 km and 660 km is called the mantle transition zone. Detecting the fluctuations of discontinuities in the mantle transition zone and seismic wave velocities, combined with high-temperature and high-pressure experimental results, is an important approach to estimating the water content of the mantle transition zone. This also provides a qualitative basis for determining the concentrations of the main chemical components in the mantle transition zone.

[0004] In the real earth medium, as the ray parameter decreases, the horizontal propagation distance of the ray increases. That is, the smaller the angle from the source, the greater the horizontal distance. In this case, , the travel time curve at this time is forward, if there is a sudden change in speed inside the earth, , the ray path deflects toward smaller epicentral distances, resulting in a backward traveltime curve. At certain epicentral distances, the same station may record multiple distinct seismic phases: return waves above and below the discontinuity, and reflection waves on the discontinuity. We call this phenomenon a triple phase. Research has shown that triple-phase waveform fitting is an effective method for studying discontinuities and velocity structures in the mantle transition zone. The closest existing technology ("Study of the Upper Mantle Velocity Structure in South China and the Qinghai-Tibet Plateau Based on P-Wave Triple Phases," Journal Library of Excellent Chinese Doctoral Dissertations, Lv Miaomiao") discloses a method for processing earthquake event data based on triple-phase fitting. This method uses a trial-and-error approach to process earthquake event data, which suffers from low efficiency, strong subjectivity, and difficulty in quantitatively evaluating and analyzing the degree of waveform fitting. Summary of the Invention

[0005] In light of this, the present invention proposes a seismic event data processing method and system based on an improved triple-phase fitting method, which processes seismic data using a progressive adaptive inversion of triple-phase arrival times. Travel time information is the most robust information extracted from seismic wave data. Using triple-phase travel time as inversion data can, to a certain extent, reduce the nonlinearity of direct inversion using waveform data while retaining the stability of traditional travel time imaging.

[0006] In order to achieve the above object, a method for processing earthquake event data based on an improved triple seismic phase fitting method is provided, the method comprising the following steps:

[0007] S1: Acquire earthquake event data;

[0008] S2: performing a preprocessing operation on the earthquake event data;

[0009] S3: Obtaining the focal depth and focal time function of the earthquake event data;

[0010] S4: Regional earthquake waveform fitting using the improved triple seismic phase fitting method;

[0011] The S4 is specifically:

[0012] S4.1: Extract P-wave arrival time information including triplet phases from earthquake event data profiles;

[0013] S4.2: Invert the background velocity field based on the picked P-wave arrival times;

[0014] S4.3: Refine the specific depth and velocity structure of the 410 km discontinuity and the 660 km discontinuity using an adaptive meshing algorithm;

[0015] S4.4: Based on the specific depth and velocity structure of the 410 km discontinuity and the 660 km discontinuity, synthesize the triple-phase waveform data and perform forward calculation, inversion sensitivity kernel calculation and iterative update of the velocity model to obtain the best fit model.

[0016] Preferably, the preprocessing operation includes: performing a data truncation operation on the seismic event data, and then resampling to 0.1 s; then performing a bandpass filtering operation, and finally, to ensure the waveform quality, manually removing waveform records with unclear P wave first arrival or low signal-to-noise ratio.

[0017] Preferably, the data interception operation on the seismic event data is specifically intercepting data from 30 seconds before to 60 seconds after the first arrival of the P wave.

[0018] Preferably, the filtering frequency band of the bandpass filter is 0.02-1 Hz.

[0019] Preferably, for teleseismic P-wave records, a time-domain iterative deconvolution technique is used to simultaneously invert the focal time function and focal depth.

[0020] Preferably, the method of using the time domain iterative deconvolution technique to simultaneously invert the focal time function and focal depth for the teleseismic P-wave record is specifically as follows:

[0021] For deep-focus earthquakes, the passive theoretical seismogram is deconvolved with the teleseismic P-wave vertical record to obtain the focal time function and focal depth;

[0022] For shallow earthquakes, the focal depth is continuously adjusted and the deconvolution operation is repeated until the actual passive seismogram is well fitted with the theoretical passive seismogram. This depth is the focal depth, and the corresponding duration is the focal time function.

[0023] Preferably, in said S4.1, said arrival time information includes the arrival time of the first arrival of the P wave and subsequent seismic phases.

[0024] Preferably, in S4.3, the adaptive subdivision algorithm uses ray distribution density or velocity variation as a judgment basis to achieve refinement of model parameters such as a specific depth and its nearby velocity structure.

[0025] According to another aspect of the present invention, a system for processing earthquake event data based on an improved triple seismic phase fitting method is provided. The system adopts the above-mentioned method for processing earthquake event data based on the improved triple seismic phase fitting method, wherein the system further comprises:

[0026] An earthquake event data acquisition module, used for acquiring earthquake event data;

[0027] A preprocessing module, configured to perform preprocessing operations on the earthquake event data;

[0028] A focal depth and focal time function acquisition module, configured to acquire the focal depth and focal time function of the earthquake event data;

[0029] The regional earthquake waveform fitting module is used to perform regional earthquake waveform fitting using an improved triple seismic phase fitting method.

[0030] The advantages and beneficial effects of the present invention are:

[0031] The present invention first uses the P-wave arrival time information including the triple seismic phase to determine the background velocity structure. On this basis, based on the triple seismic phase travel time near the interface, an adaptive segmentation algorithm is used to further constrain the interface position. The strategy of inverting the velocity and interface in steps can minimize the trade-off between the interface position and velocity anomaly. Secondly, while retaining the advantage of high vertical resolution of the traditional triple seismic phase method, this method reduces the blindness and uncertainty of the model parameter setting in the trial and error method and the grid search method, while also improving the inversion efficiency and accuracy. In addition, the dual constraints of the triple seismic phase arrival time and waveform information are realized, and the degree of waveform fitting can be provided with a quantitative evaluation, which is expected to provide new technical support for the detection of the velocity structure of the mantle transition zone. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the description of the present invention or the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0033] Figure 1 The flowchart of a method for processing earthquake event data based on an improved triple seismic phase fitting method is shown in FIG.

[0034] Figure 2 A triple seismic phase cross-section diagram provided by an embodiment of the present invention;

[0035] Figure 3 A flowchart of regional earthquake waveform fitting using an improved triple seismic phase fitting method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] As attached Figure 1 As shown, a method for processing earthquake event data based on an improved triple seismic phase fitting method comprises the following steps:

[0038] S1: Acquire earthquake event data;

[0039] In this embodiment, the selected earthquake time needs to meet the following basic conditions: (1) the epicenter distance covers the range of 10°-30°; (2) the magnitude is greater than or equal to 5.0; (3) there is corresponding focal mechanism solution information; then the seismic data of the above earthquake event is obtained; in this embodiment, earthquake event data 20130628235150 and earthquake event data 20110725171540 are selected as the earthquake event data for data processing in this embodiment.

[0040] S2: performing a preprocessing operation on the earthquake event data;

[0041] The preprocessing operation includes: performing a data truncation operation on the earthquake event data and then resampling it to 0.1 s; then performing a bandpass filtering operation; and finally, to ensure the waveform quality, manually removing waveform records with unclear P wave first arrival or low signal-to-noise ratio;

[0042] Furthermore, the data interception operation for the earthquake event data is specifically to intercept the data from 30 seconds before to 60 seconds after the first arrival of the P wave; the filtering frequency band of the bandpass filter is 0.02-1 Hz;

[0043] Taking earthquake event 20130628235150 as an example, the inflection point sampling of this event mainly covers the upper mantle of the Central Yangtze Craton and the part above the mantle transition zone of the Cathaysia Block, and is recorded in the azimuth range of 288°~318°. Figure 2 The figure shows a triplet seismic phase profile for this event, observed simultaneously from both the 410 km and 660 km discontinuities within an azimuth range of 312° to 318°. Event 20110725171540 fills a sampling gap in the transition zone of the Cathaysia Block, providing excellent data support for studying the lateral variations in the velocity structure of the upper mantle beneath the Yangtze Craton and Cathaysia Block. The comprehensive epicentral distance coverage and high-density data record mitigate or eliminate the influence of lateral inhomogeneities in the velocity structure beneath individual stations. Simultaneously fitting two sets of triplet seismic phases from the 410 km and 660 km discontinuities effectively constrains velocity models and improves resolution.

[0044] S3: Obtaining the focal depth and focal time function of the earthquake event data;

[0045] In this embodiment, the time domain iterative deconvolution technique is used to simultaneously invert the focal time function and focal depth for teleseismic P-wave records;

[0046] Specifically, the time domain iterative deconvolution technique is used to simultaneously invert the focal time function and focal depth of the teleseismic P-wave record as follows:

[0047] For deep earthquakes, the arrival time difference between the direct P wave and the deep earthquake phase is large enough, so the deep earthquake phase will not affect the determination of the focal time function; the source theoretical seismogram is deconvolved with the teleseismic P wave vertical record to obtain the focal time function and focal depth;

[0048] For shallow earthquakes, the deep earthquake phase and the direct P wave are mixed in the focal time window. Therefore, it is necessary to obtain an accurate focal depth to obtain a reliable focal time function. By continuously adjusting the focal depth and repeating the deconvolution operation until the actual passive seismogram and the theoretical passive seismogram are well fitted, this depth is the focal depth, and the corresponding duration is the focal time function.

[0049] S4: Regional earthquake waveform fitting using the improved triple seismic phase fitting method;

[0050] Triple-phase waveform fitting is an effective method for studying discontinuities and velocity structures in the mantle transition zone. Previous studies of triple-phase seismic data have mostly employed trial-and-error methods and grid search techniques. Traditional trial-and-error methods start with a one-dimensional velocity structure and continuously adjust and modify the velocity structure model until a good fit between the theoretical seismogram and the observed data is achieved. Due to inherent limitations, trial-and-error methods are inefficient, highly subjective, and difficult to quantitatively evaluate and analyze the degree of waveform fit. Recently developed grid search methods, based on an initial model, set a series of parameter combinations for discontinuity depth and velocity anomaly amplitude, define an error function and waveform fit cross-correlation coefficient, and search for the best-fitting model that minimizes the error and maximizes the cross-correlation coefficient. While this method overcomes the shortcomings of traditional trial-and-error methods, the non-uniqueness of the inversion results means that many local optima exist in the model space. The setting of model parameters is somewhat unpredictable and limited, and the inversion results may be dependent on the initial model. While parallel-based rapid search methods improve efficiency, they also suffer from the blindness and limitations of model parameter settings. The calculation of residuals during the inversion process relies on reference phases with large amplitudes, which may not be the triple phase itself. Furthermore, the trade-offs between velocity and interface, and between deep and shallow depths, remain unresolved.

[0051] In response to the problems existing in the above-mentioned method, this embodiment proposes an improved triple seismic phase fitting method for regional seismic waveform fitting; the triple seismic phase travel time is used as inversion data, and a progressive adaptive inversion algorithm is used to perform regional seismic waveform fitting; travel time information is the most robust information extracted from seismic wave data. Using the triple seismic phase travel time as inversion data can reduce the nonlinearity of directly using waveform data for inversion to a certain extent, while inheriting the stability of traditional travel time imaging.

[0052] Specifically, such as Figure 3 As shown, the S4 is specifically:

[0053] S4.1: First, extract the P-wave arrival time information including the triplet phase from the earthquake event data profile;

[0054] Specifically, the arrival time information includes the arrival time of the first arrival of the P wave and the subsequent seismic phases.

[0055] S4.2: Invert the background velocity field based on the picked P-wave arrival times;

[0056] S4.3: Refine the specific depth and velocity structure of the 410 km discontinuity and the 660 km discontinuity using an adaptive meshing algorithm;

[0057] Specifically, the adaptive subdivision algorithm uses the ray distribution density or velocity variation as a judgment basis to achieve the refinement of model parameters such as depth and velocity structure;

[0058] S4.4: Based on the specific depth and velocity structure of the 410 km discontinuity and the 660 km discontinuity, synthesize the triple-phase waveform data and perform forward calculation, inversion sensitivity kernel calculation and iterative update of the velocity model to obtain the best fit model.

[0059] The theoretical model is calculated using the focal depth and focal time function obtained by S3. The specific calculation process is based on existing technology and will not be discussed in detail here.

[0060] In this embodiment, the algorithm to be developed adopts a "progressive" scheme. First, the background velocity structure is determined using the P-wave arrival information including the triple phase. On this basis, an adaptive segmentation algorithm is used to further constrain the interface position based on the triple phase travel time near the interface. The strategy of inverting the velocity and interface step by step can minimize the trade-off between the interface position and velocity anomaly. Secondly, while retaining the advantage of high vertical resolution of the traditional triple phase method, this method reduces the blindness and uncertainty of the model parameter setting in the trial and error method and the grid search method, while also improving the inversion efficiency and accuracy. In addition, the dual constraints of the triple phase arrival time and waveform information are realized, and the degree of waveform fitting can be provided with a quantitative evaluation, which is expected to provide new technical support for the detection of velocity structure in the mantle transition zone.

[0061] Embodiment 2: This embodiment further includes a seismic event data processing system based on an improved triple seismic phase fitting method. The system adopts the seismic event data processing method based on the improved triple seismic phase fitting method of embodiment 1, wherein the system further includes:

[0062] An earthquake event data acquisition module, used for acquiring earthquake event data;

[0063] A preprocessing module, configured to perform preprocessing operations on the earthquake event data;

[0064] A focal depth and focal time function acquisition module, configured to acquire the focal depth and focal time function of the earthquake event data;

[0065] The regional earthquake waveform fitting module is used to perform regional earthquake waveform fitting using an improved triple seismic phase fitting method.

[0066] Embodiment 3: This embodiment includes a computer-readable storage medium on which a data processing program is stored. The data processing program is executed by a processor to implement the earthquake event data processing method based on the improved triple seismic phase fitting method of embodiment 1.

[0067] Those skilled in the art will appreciate that the embodiments herein may be provided as methods, apparatuses (devices), or computer program products. Therefore, the present invention may take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. These include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVDs) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery medium.

[0068] This document is described with reference to flowcharts and / or block diagrams of methods, apparatuses (devices), and computer program products according to the embodiments of this document. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0069] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1A step that specifies a function in one or more boxes.

[0070] The embodiments and / or implementation methods described above are only used to illustrate the preferred embodiments and / or implementation methods for realizing the technology of the present invention, and are not intended to impose any formal restrictions on the implementation methods of the technology of the present invention. Any person skilled in the art may make some changes or modifications to other equivalent embodiments without departing from the scope of the technical means disclosed in the content of the present invention, but they should still be regarded as technologies or embodiments that are essentially the same as the present invention. Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for processing earthquake event data based on an improved triple seismic phase fitting method, characterized in that: The method comprises the following steps: S1: Acquire earthquake event data; S2: performing a preprocessing operation on the earthquake event data; S3: Obtaining the focal depth and focal time function of the earthquake event data; S4: Regional earthquake waveform fitting using improved triple seismic phase fitting method; The S4 is specifically: S4.1: Extract the P-wave arrival time information including the triple phase in the earthquake event data profile; S4.2: Invert the background velocity field based on the picked P-wave arrival times; S4.3: Refine the specific depth and velocity structure of the 410 km discontinuity and 660 km discontinuity based on the adaptive subdivision algorithm; S4.4: Based on the specific depth and velocity structure of the 410 km discontinuity and the 660 km discontinuity, the triple seismic phase waveform data are synthesized to perform forward calculation, inversion sensitive kernel calculation and iterative update of the velocity model to obtain the best fitting model.

2. The earthquake event data processing method based on the improved triple seismic phase fitting method according to claim 1 is characterized in that: The preprocessing operation includes: performing a data interception operation on the seismic event data, and then resampling to 0.1s; then performing a bandpass filtering operation, and finally manually removing waveform records with low P wave first arrival signal-to-noise ratio to ensure waveform quality.

3. The earthquake event data processing method based on the improved triple seismic phase fitting method according to claim 2 is characterized in that: The data interception operation for the earthquake event data is specifically to intercept the data from 30 s before to 60 s after the first arrival of the P wave.

4. The earthquake event data processing method based on the improved triple seismic phase fitting method according to claim 2 is characterized in that: The filtering frequency band of the bandpass filter is 0.02-1 Hz.

5. The earthquake event data processing method based on the improved triple seismic phase fitting method according to claim 1, characterized in that: In S3, the time domain iterative deconvolution technique is used to simultaneously invert the focal time function and focal depth for the teleseismic P wave records.

6. The earthquake event data processing method based on the improved triple seismic phase fitting method according to claim 5, characterized in that: The specific method of using the time domain iterative deconvolution technique to simultaneously invert the focal time function and focal depth for the teleseismic P wave record is: For deep-focus earthquakes, the passive theoretical seismograms are deconvolved with the teleseismic P-wave vertical records to obtain the focal time function and focal depth; For shallow source earthquakes, the focal depth is continuously adjusted and the deconvolution operation is repeated until the actual passive seismogram fits the theoretical passive seismogram well. This depth is the focal depth, and the corresponding duration is the focal time function.

7. The earthquake event data processing method based on the improved triple seismic phase fitting method according to claim 1 is characterized in that: In S4.1, the arrival time information includes the arrival time of the first arrival of the P wave and the subsequent seismic phases.

8. The earthquake event data processing method based on the improved triple seismic phase fitting method according to claim 7 is characterized in that: In S4.3, the adaptive subdivision algorithm uses the ray distribution density or velocity change as a judgment basis to achieve the refinement of the depth and velocity structure.

9. A seismic event data processing system based on an improved triple seismic phase fitting method, the system adopts the seismic event data processing method based on an improved triple seismic phase fitting method according to any one of claims 1 to 8, characterized in that: The system further comprises: An earthquake event data acquisition module, used for acquiring earthquake event data; A preprocessing module, used for performing preprocessing operations on the earthquake event data; A focal depth and focal time function acquisition module, used to acquire the focal depth and focal time function of the earthquake event data; The regional earthquake waveform fitting module is used to fit the regional earthquake waveform using an improved triple seismic phase fitting method.

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