First arrival seismic wave anomaly data filtering method, system, medium and device

Abstract

Embodiments of the present application provide a method, system, medium and device for filtering abnormal data of first arrival seismic wave, the method comprising: determining a signal-to-noise ratio value of a target region according to geological data of the target region; in a case where the signal-to-noise ratio value is less than or equal to a set threshold, adjusting an abnormal enhancement parameter to perform abnormal enhancement processing on first arrival seismic wave data, and adjusting an abnormal filtering parameter to filter abnormal data in the first arrival seismic wave data after the abnormal enhancement processing; and performing filtering processing on the first arrival seismic wave data corresponding to the target region based on the adjusted abnormal enhancement parameter and the abnormal filtering parameter to obtain filtered target first arrival seismic wave data. The method of the present application solves the problem of abnormal data in the first arrival seismic wave data.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration, and more specifically, to a method, system, medium, and device for filtering first-arrival seismic wave anomaly data. Background Technology

[0002] Due to the crisscrossing gullies, dramatic surface undulations, and dense distribution of surface obstacles in the Loess Mountain region, coupled with the influence of the thick topsoil, the initial arrival data obtained when collecting seismic data in the Loess Mountain region using traditional methods is severely distorted. Therefore, it is necessary to further improve the accuracy of initial arrival picking.

[0003] Existing methods for improving first arrival picking accuracy typically employ KL-FBPicker software and set automatic picking parameters. However, this method, by using fixed parameters, results in significant variations in first arrival picking accuracy. Furthermore, due to the influence of parameters and low signal-to-noise ratio data, large areas of anomalous data often appear in the acquired first arrival seismic wave data, and these anomalous data are difficult to delete during first arrival seismic wave editing. Summary of the Invention

[0004] This application aims to provide a method, system, medium, and device for filtering first-arrival seismic wave anomaly data, in order to solve the problem of anomaly data appearing in first-arrival seismic wave data.

[0005] A first aspect of this application provides a method for filtering first-arrival seismic wave anomaly data, the method comprising: Determine the signal-to-noise ratio value of the target area based on the geological data of the target area; When the signal-to-noise ratio is less than or equal to a set threshold, the anomaly enhancement parameter is adjusted to perform anomaly enhancement processing on the first arrival seismic wave data, and the anomaly filtering parameter is adjusted to filter out abnormal data in the first arrival seismic wave data after anomaly enhancement processing. Based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, the first arrival seismic wave data corresponding to the target area is filtered to obtain the filtered target first arrival seismic wave data.

[0006] Optionally, if the signal-to-noise ratio is less than or equal to a set threshold, the anomaly enhancement parameters are adjusted to perform anomaly enhancement processing on the first-arrival seismic wave data, including: When the signal-to-noise ratio value is less than or equal to a set threshold, determine the amount of reduction in the computation length and the amount of reduction in the energy threshold value corresponding to the signal-to-noise ratio value. Based on the reduction in computation length, the initial value of computation length in the anomaly enhancement parameters is reduced to obtain the target value of computation length. Based on the reduction amount of the energy threshold value, the initial value of the energy threshold value in the abnormal enhancement parameters is reduced to obtain the target value of the energy threshold value.

[0007] Optionally, adjusting the anomaly filtering parameters includes: When the signal-to-noise ratio value is less than or equal to a set threshold, determine the increase in the evaluation threshold value corresponding to the signal-to-noise ratio value and the decrease in the time difference between adjacent channels. Based on the increase in the evaluation threshold value, the initial value of the evaluation threshold value in the anomaly filtering parameter is increased to obtain the target value of the evaluation threshold value. Based on the reduction in the adjacent channel time difference, the initial value of the adjacent channel time difference in the anomaly filtering parameters is reduced to obtain the target value of the adjacent channel time difference.

[0008] Optionally, the method further includes: Determine the dispersion of outlier distributions in the first arrival seismic wave data of the target; The outlier distribution dispersion is compared with a preset dispersion value to obtain the comparison result; Based on the comparison results, it is determined whether the target's first arrival seismic wave data is qualified.

[0009] Optionally, based on the comparison results, it is determined whether the target's first arrival seismic wave data is qualified, including: When the comparison result shows that the dispersion of the outlier distribution is greater than the preset dispersion value, the target first arrival seismic wave data is determined to be unqualified, and the anomaly enhancement parameters and anomaly filtering parameters are adjusted again. When the comparison result shows that the dispersion of the outlier distribution is less than or equal to the preset dispersion value, the target first arrival seismic wave data is determined to be qualified, and the target first arrival seismic wave data is used for static correction processing.

[0010] Optionally, before determining the signal-to-noise ratio of the target area based on geological data of the target area, the method further includes: Determine the medium and low signal-to-noise ratio ranges where the signal-to-noise ratio values ​​are less than or equal to a set threshold range; Establish mapping relationships between the signal-to-noise ratio range and the reduction in computation length and energy threshold in the anomaly enhancement parameters, respectively, as well as between the increase in evaluation threshold and the reduction in adjacent channel time difference in the anomaly filtering parameters, respectively. Establish mapping relationships between the low signal-to-noise ratio range and the reduction in computation length and energy threshold in the anomaly enhancement parameters, respectively, as well as between the increase in evaluation threshold and the reduction in adjacent channel time difference in the anomaly filtering parameters, respectively.

[0011] Optionally, based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, the first-arrival seismic wave data corresponding to the target area is filtered to obtain filtered target first-arrival seismic wave data, including: Based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, the first arrival seismic wave data of the target area is filtered to obtain the filtered first arrival seismic wave data to be filled. The first arrival seismic wave data to be filled is processed based on the data corresponding to adjacent seismic traces to obtain the corresponding target first arrival seismic wave data.

[0012] The second aspect of this embodiment provides a filtering system for first-arrival seismic wave anomaly data, the system comprising: The signal-to-noise ratio determination module is used to determine the signal-to-noise ratio value of the target area based on the geological data of the target area. The parameter adjustment module is used to adjust the anomaly enhancement parameter to perform anomaly enhancement processing on the first arrival seismic wave data when the signal-to-noise ratio value is less than or equal to a set threshold, and to adjust the anomaly filtering parameter to filter out abnormal data in the first arrival seismic wave data after anomaly enhancement processing. The data determination module is used to filter the first-arrival seismic wave data corresponding to the target area based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, so as to obtain the filtered target first-arrival seismic wave data.

[0013] The third aspect of this embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the method for filtering first-arrival seismic wave anomaly data as described in any of the first aspects.

[0014] The fourth aspect of this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the filtering method for first-arrival seismic wave anomaly data as described in any of the first aspects.

[0015] Beneficial effects: This application provides a method for filtering first-arrival seismic wave anomaly data. The method includes: determining the signal-to-noise ratio (SNR) value of the target area based on geological data of the target area; adjusting anomaly enhancement parameters to perform anomaly enhancement processing on the first-arrival seismic wave data when the SNR value is less than or equal to a set threshold; adjusting anomaly filtering parameters to filter out anomalous data in the anomaly-enhanced first-arrival seismic wave data; and filtering the first-arrival seismic wave data of the target area based on the adjusted anomaly enhancement parameters and anomaly filtering parameters to obtain filtered target first-arrival seismic wave data.

[0016] This application determines whether to adjust the anomaly enhancement and anomaly filtering parameters based on the signal-to-noise ratio (SNR) of the target area. When the SNR is low, the anomaly enhancement parameters are adjusted to amplify anomalous data in the first-arrival seismic wave data, making the anomalies more prominent and easier to locate. Then, the anomaly filtering parameters are adjusted to filter out clearly anomalous data. The first-arrival seismic wave anomaly filtering method provided in this application significantly reduces anomalous data in the first-arrival seismic wave data, resulting in more accurate data. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the steps of a method for filtering first-arrival seismic wave anomaly data according to an embodiment of this application; Figure 2 This is a first arrival time cross-sectional view provided in an embodiment of this application; Figure 3 This is a data effect diagram corresponding to a calculated length provided in one embodiment of this application; Figure 4 This is a data effect diagram corresponding to an energy threshold value provided in one embodiment of this application; Figure 5 This is a data effect diagram corresponding to an evaluation threshold value provided in one embodiment of this application; Figure 6 This is a data effect diagram corresponding to the time difference between adjacent channels provided in an embodiment of this application; Figure 7 This is a schematic diagram of a static correction section provided in an embodiment of this application; Figure 8 This is a schematic diagram of a filtering system for first-arrival seismic wave anomaly data provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] Existing methods for acquiring first-arrival seismic wave data involve first acquiring the data based on fixed parameters, and then manually removing outliers. This method is time-consuming. Therefore, existing technologies have proposed a parameter-based outlier removal method. This method acquires first-arrival seismic wave data based on set parameters, where the parameters aim to reduce the generation of outliers and remove them. However, this method may fail to remove some less obvious outliers. To address this, this application provides a method for filtering outlier data in first-arrival seismic waves. This method takes the opposite approach: first, it adjusts the anomaly enhancement parameters to amplify the outliers, making them more prominent and clearly distinguishable from normal data; then, it adjusts the anomaly filtering parameters to filter out these prominent outliers, thus removing all outliers from the first-arrival seismic wave data.

[0021] This application proposes a method for filtering first-arrival seismic wave anomaly data, such as... Figure 1 As shown, this application also provides a step diagram of a method for filtering first-arrival seismic wave anomaly data; specifically, the method includes: S11: Determine the signal-to-noise ratio of the target area based on the geological data of the target area.

[0022] In this embodiment, the area where first-arrival seismic wave data is to be acquired is defined as the target area. First-arrival seismic waves refer to the wave signals that arrive first when the seismic waves reach the detector. After geological exploration of the target area, corresponding geological data is obtained. The signal-to-noise ratio (SNR) of the target area can be determined by quality analysis of the geological data. The SNR refers to the relationship between the energy of the effective signal and the background noise; a high SNR indicates strong effective signal energy, while a low SNR indicates strong background noise energy. Due to the inherent geological properties and the intensity of environmental interference in the surrounding area, different target areas have different SNR values. Generally, target areas with simple layered strata and no large-scale technical construction in the surrounding environment have higher SNR values. Conversely, target areas with fault zones or fracture zones and surrounding industrial interference have lower SNR values.

[0023] S12: When the signal-to-noise ratio is less than or equal to a set threshold, adjust the anomaly enhancement parameter to perform anomaly enhancement processing on the first arrival seismic wave data, and adjust the anomaly filtering parameter to filter out abnormal data in the anomaly enhancement processed first arrival seismic wave data.

[0024] Since the accuracy of the first arrival seismic wave data obtained when picking up the first arrival of the target area is affected by the signal-to-noise ratio of the target area, the first arrival seismic wave obtained when the signal-to-noise ratio is high is of good quality and the result is accurate. When the signal-to-noise ratio is low, the accuracy of the first arrival seismic wave obtained is low, and there may even be abnormal data in the data. Therefore, for areas with low signal-to-noise ratio, this embodiment adjusts the parameters in the software to make the obtained first arrival seismic wave data accurate before acquiring the first arrival seismic wave data of the area.

[0025] Specifically, the signal-to-noise ratio (SNR) of the target area is compared with a set threshold to determine if the SNR of the target area is less than or equal to the set threshold. If it is, it indicates that the SNR of the target area is low, and the parameters of the software used to acquire first-arrival seismic wave data need to be adjusted. The set threshold is determined by the staff.

[0026] In this embodiment, the software used to acquire first-arrival seismic wave data includes anomaly enhancement parameters and anomaly filtering parameters. When the signal-to-noise ratio (SNR) of the target area is less than or equal to a set threshold, the anomaly enhancement parameters are adjusted according to a preset adjustment method to enhance the anomalous data in the first-arrival seismic wave data, making the anomalous data clearly distinguishable. Then, the anomaly filtering parameters are adjusted according to a preset adjustment method, and the adjusted anomaly filtering parameters can completely filter out the anomalous data that has undergone anomaly enhancement processing.

[0027] S13: Based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, the first arrival seismic wave data corresponding to the target area is filtered to obtain the filtered target first arrival seismic wave data.

[0028] Specifically, after adjusting the parameters of the software used to acquire first-arrival seismic wave data, the first-arrival seismic wave data of the target area is acquired based on the adjusted anomaly enhancement and anomaly filtering parameters. During the acquisition process, anomaly data in the first-arrival seismic wave data is filtered to obtain the corresponding target first-arrival seismic wave data without anomalies. The target first-arrival seismic wave data can be illustrated using a first-arrival time profile. The filtered first-arrival time profile will not contain any "flying points" representing anomalies, such as... Figure 2 As shown in the figure, this embodiment also provides a first arrival time profile.

[0029] In this application, anomalous data in the first-arrival seismic wave data are first highlighted by adjusting the anomaly enhancement parameters, and then these enhanced anomalous data are filtered out using anomaly filtering parameters. This allows for the precise removal of anomalous data from the first-arrival seismic wave data, resulting in accurate target first-arrival seismic wave data. Furthermore, this method of removing anomalous data by adjusting parameters saves a significant amount of time compared to manual anomaly removal.

[0030] In conjunction with the above embodiments, in one implementation, the present invention also provides a method for filtering first-arrival seismic wave anomaly data. In this method for filtering first-arrival seismic wave anomaly data, step S12 includes steps S21 to S23: S21: When the signal-to-noise ratio value is less than or equal to a set threshold, determine the amount of reduction in the calculation length and the amount of reduction in the energy threshold value corresponding to the signal-to-noise ratio value.

[0031] S22: Based on the reduction in computation length, the initial value of computation length in the anomaly enhancement parameter is reduced to obtain the target value of computation length.

[0032] S23: Based on the amount of reduction in the energy threshold value, the initial value of the energy threshold value in the abnormal enhancement parameter is reduced to obtain the target value of the energy threshold value.

[0033] In this embodiment, the anomaly enhancement parameters include computation length and energy threshold value. The computation length refers to the sliding window length of the capacity ratio within the computation window, and is a parameter used to determine the starting position of the first-arrival seismic wave. The energy threshold value is a threshold used to determine whether a certain time point of the first-arrival seismic wave represents the first-arrival energy.

[0034] If the signal-to-noise ratio (SNR) value in the target area is less than or equal to a set threshold, it is determined that the anomaly enhancement parameters need to be adjusted. Since the parameters in the software used to pick up first-arrival seismic wave data in this embodiment already have corresponding parameter values, after determining that the parameters need to be adjusted, this embodiment also needs to determine the adjustment amount corresponding to these parameters based on the specific SNR value, that is, the amount by which the parameter value is reduced or the amount by which the parameter value is increased.

[0035] Because this embodiment requires amplification of abnormal data, and because a smaller sliding window means the algorithm can only analyze signals over a very short period, if local noise exists within that time period, this noise might be identified as first-arrival seismic wave data, leading to more discrete first-arrival seismic wave data in the picking results. Figure 3 The diagram shown in this embodiment illustrates the data effect corresponding to the calculated length. In this diagram, as the calculated length decreases, the first-arrival seismic wave data becomes more discrete. The red dots within the green area represent the first-arrival seismic wave data, and the data within the blue box represents discrete anomaly data. Therefore, this embodiment reduces the conventional calculated length. After determining the amount of reduction in calculated length based on the signal-to-noise ratio, the calculated length is reduced according to this amount to obtain the target value for the calculated length.

[0036] Setting the energy threshold too low makes it easier to misinterpret background noise in the target area as first-arrival seismic wave data, leading to flying spots in the acquired first-arrival time profile. However, setting the energy threshold too high will cause normal seismic wave data to be filtered out because it does not meet the threshold, resulting in incomplete and inaccurate first-arrival seismic wave data. Figure 4 The diagram shown in this embodiment illustrates the data effect corresponding to an energy threshold value. In this diagram, the red dots within the green area represent first-arrival seismic wave data. Therefore, this embodiment reduces the energy threshold value. Even if background noise is picked up, the integrity of the data is ensured as much as possible. Finally, anomaly filtering parameters filter out this picked-up noise. After determining the amount of energy threshold reduction based on the signal-to-noise ratio, the energy threshold value is reduced according to the reduction amount to obtain the target value of the corresponding energy threshold value.

[0037] In conjunction with the above embodiments, in one implementation, the present invention also provides a method for filtering first-arrival seismic wave anomaly data. In this method for filtering first-arrival seismic wave anomaly data, step S12 includes steps S31 to S33: S31: When the signal-to-noise ratio value is less than or equal to a set threshold, determine the increase in the evaluation threshold value corresponding to the signal-to-noise ratio value and the decrease in the time difference between adjacent channels.

[0038] S32: Based on the increase in the evaluation threshold value, the initial value of the evaluation threshold value in the anomaly filtering parameter is increased to obtain the target value of the evaluation threshold value.

[0039] S33: Based on the reduction amount of the adjacent channel time difference, the initial value of the adjacent channel time difference in the anomaly filtering parameters is reduced to obtain the target value of the adjacent channel time difference.

[0040] In this embodiment, the anomaly filtering parameters include at least an evaluation threshold and adjacent trace time difference. The evaluation threshold is a threshold set to determine whether the data in the first-arrival seismic wave data is reasonable. The adjacent trace time difference is the first-arrival time difference between adjacent seismic traces.

[0041] After determining that anomalous data should be augmented, the anomaly filtering parameters are adjusted to filter out the anomalous data. Specifically, since the anomalous data in this embodiment has undergone anomalous augmentation, this embodiment increases the evaluation threshold value. Data points that still exceed the evaluation threshold value are identified as augmented anomalous data and deleted. The amount of increase in the energy threshold value is determined by the signal-to-noise ratio of the target region. After increasing the energy threshold value by the specified amount, the target value of the evaluation threshold value is obtained. Figure 5As shown in the figure, the red dots within the green area represent the first arrival seismic wave data. This embodiment also provides a data effect diagram corresponding to the evaluation threshold value. In this diagram, the number of "flying points" in the diagram corresponding to the high evaluation threshold value is significantly reduced.

[0042] Since the adjacent channel time difference reflects the first arrival time difference between adjacent seismic channels, reducing the adjacent channel time difference narrows the time range and filters out more fly-bysits. For example, if three people, A, B, and C, are relaying a message, and A's message to B takes 2 seconds, while B's message to C takes 6 seconds, and the original time difference is 7 seconds, then both A's and B's messages are valid. However, if the time difference is reduced to 4 seconds, B's message will be invalid, indicating an abnormal message relay. The amount of reduction in the adjacent channel time difference is determined by the signal-to-noise ratio (SNR) of the target area. After reducing the adjacent channel time difference, the target value for that adjacent channel time difference is obtained, such as... Figure 6 As shown in the figure, this embodiment also provides a data effect diagram corresponding to the time difference between adjacent channels. In this diagram, the number of "flying points" in the diagram corresponding to the low time difference between adjacent channels is significantly reduced. In this diagram, the red dots in the green area represent the first arrival seismic wave data.

[0043] In addition, the anomaly filtering parameters in this embodiment may also include correction parameters. The correction parameters reflect the tolerance for anomalous data in the first arrival seismic wave data. Lowering the correction parameters means that the tolerance is reduced, and more anomalous data will be filtered out.

[0044] In conjunction with the above embodiments, in one implementation, the present invention also provides a method for filtering first-arrival seismic wave anomaly data. This method further includes steps S41 to S43: S41: Determine the dispersion of outlier distribution in the first arrival seismic wave data of the target.

[0045] S42: Compare the outlier distribution dispersion with a preset dispersion value to obtain a comparison result.

[0046] S43: Based on the comparison results, determine whether the target first arrival seismic wave data is qualified.

[0047] After obtaining the filtered first-arrival seismic wave data, to further verify whether the data is acceptable, i.e., whether there are still a large number of outliers, this embodiment also determines the outlier distribution dispersion of the first-arrival seismic wave data. Specifically, the Z-score method can be used to calculate the standard deviation multiple of a data point in the first-arrival seismic wave data from the mean to determine whether the data point is an outlier, thereby determining the outlier distribution dispersion of the entire first-arrival seismic wave data. Then, the outlier distribution dispersion corresponding to the first-arrival seismic wave data is compared with a preset dispersion value set by the staff to determine whether the outlier distribution dispersion is less than the preset dispersion value, and the corresponding comparison result is obtained. Based on this comparison result, it is determined whether the outliers in the first-arrival seismic wave data have been filtered out and whether the data is acceptable.

[0048] In conjunction with the above embodiments, in one implementation, the present invention also provides a method for filtering first-arrival seismic wave anomaly data. In this method for filtering first-arrival seismic wave anomaly data, step S43 further includes steps S51 to S52: S51: When the comparison result shows that the dispersion of the outlier distribution is greater than the preset dispersion value, the target first arrival seismic wave data is determined to be unqualified, and the outlier enhancement parameter and outlier filtering parameter are adjusted again.

[0049] S52: When the comparison result shows that the dispersion of the outlier distribution is less than or equal to the preset dispersion value, the target first arrival seismic wave data is determined to be qualified, and the target first arrival seismic wave data is used for static correction processing.

[0050] Specifically, if the comparison result shows that the dispersion of outlier distribution in the target first-arrival seismic wave data is greater than the preset dispersion value, it indicates that the target first-arrival seismic wave data is unqualified and contains a large number of outliers. In order to obtain qualified target first-arrival seismic wave data, this embodiment further adjusts the anomaly enhancement parameters and anomaly filtering parameters so that the adjusted parameters can effectively filter out the outliers in the first-arrival seismic wave data, thereby obtaining qualified target first-arrival seismic wave data.

[0051] If the comparison result shows that the outlier distribution dispersion of the target first-arrival seismic wave data is less than or equal to the preset dispersion value, it indicates that the target first-arrival seismic wave data is qualified, the result is accurate, and the data contains few or no outliers. At this point, the target first-arrival seismic wave data can be used for subsequent static correction processing. Data after static correction can be used for tasks such as shot deviation checks, single-shot analysis and evaluation. Static correction processing refers to the data processing procedure that corrects the time of seismic waves received by different detectors to a unified reference surface. Figure 7As shown in the figure, this embodiment provides a schematic diagram of a static correction profile. Calculating the static correction using accurate first-arrival seismic wave data allows the error to be controlled within milliseconds, resulting in a more precise static correction effect, which is beneficial for personnel conducting shot deviation checks. Conversely, when inaccurate first-arrival seismic wave data leads to a poor static correction effect, it becomes difficult to determine whether the shot point has deviated, and it also fails to meet the needs of on-site data evaluation.

[0052] In conjunction with the above embodiments, in one implementation, the present invention also provides a method for filtering first-arrival seismic wave anomaly data. In this method for filtering first-arrival seismic wave anomaly data, steps S61 to S63 are included before step S11: S61: Determine the medium and low signal-to-noise ratio ranges where the signal-to-noise ratio value is less than or equal to the set threshold range.

[0053] S62: Establish the mapping relationship between the signal-to-noise ratio range and the reduction in computation length and energy threshold value in the anomaly enhancement parameters, respectively, and the mapping relationship between the increase in evaluation threshold value and the reduction in adjacent channel time difference in the anomaly filtering parameters, respectively.

[0054] S63: Establish mapping relationships between the low signal-to-noise ratio range and the reduction in computation length and energy threshold in the anomaly enhancement parameters, respectively, as well as mapping relationships between the increase in evaluation threshold and the reduction in adjacent channel time difference in the anomaly filtering parameters, respectively.

[0055] Specifically, different signal-to-noise ratio (SNR) values ​​in the target area have different effects on the acquired first-arrival seismic wave data. Therefore, this embodiment further divides the SNR values ​​that are less than or equal to a set threshold range. This embodiment sets a range threshold value, which is less than the set threshold value. The range between the range threshold value and the set threshold value is defined as the medium SNR range, and the range with SNR values ​​less than the range threshold value is defined as the low SNR range.

[0056] After determining the signal-to-noise ratio (SNR) range, the reduction amounts corresponding to the computation length and energy threshold values ​​in the anomaly enhancement parameters within this range are determined, and a corresponding mapping relationship is established. In this mapping relationship, the SNR range corresponds to the reduction amounts of computation length and energy threshold values. Similarly, the increase amounts of the evaluation threshold value and the reduction amounts of adjacent channel time difference in the anomaly filtering parameters are also determined, and a corresponding mapping relationship is established. In this mapping relationship, the SNR range corresponds to the increase amounts of the evaluation threshold value and the reduction amounts of adjacent channel time difference. For example, when the threshold is set to 1.5 and the range critical value is 0.6, the SNR range is determined to be 0.6-1.5, and the corresponding reduction amounts of computation length, energy threshold value, evaluation threshold value, and adjacent channel time difference within this range are determined to be 0-20, 0.2-0.5, 5-15, and 90.

[0057] After determining the low signal-to-noise ratio (SNR) range, the reduction amounts corresponding to the computation length and energy threshold values ​​in the anomaly enhancement parameters within this range can be determined based on historical seismic data or parameter algorithm formulas. A corresponding mapping relationship can then be established, where the SNR range corresponds to the reduction in computation length and energy threshold value. Similarly, the increase in the evaluation threshold value and the reduction in adjacent trace time difference in the anomaly filtering parameters can be established, and a corresponding mapping relationship can be established, where the SNR range corresponds to the increase in the evaluation threshold value and the reduction in adjacent trace time difference. For example, using the above example, the low SNR range is determined to be less than 0.6, and the corresponding reduction amounts for computation length, energy threshold, evaluation threshold, and adjacent trace time difference within this range are determined to be 20, 0.5, 15, and 90.

[0058] In conjunction with the above embodiments, in one implementation, the present invention also provides a method for filtering first-arrival seismic wave anomaly data. In this method for filtering first-arrival seismic wave anomaly data, step S13 includes steps S71 to S72: S71: Based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, the first arrival seismic wave data of the target area is filtered to obtain the filtered first arrival seismic wave data to be filled.

[0059] S72: Based on the data corresponding to adjacent seismic traces, perform filling processing on the first arrival seismic wave data to be filled to obtain the corresponding target first arrival seismic wave data.

[0060] Because the anomaly filtering parameters filter out anomalous data in the first-arrival seismic wave data, data gaps may exist in the filtered data. Therefore, this embodiment performs data filling to address these gaps. Specifically, based on adjusted anomaly enhancement and filtering parameters, the first-arrival seismic wave data undergoes anomaly enhancement and filtering to obtain the missing data to be filled. This embodiment then determines adjacent seismic traces based on the seismic traces corresponding to the missing data. The data corresponding to these adjacent traces are then used to calculate reasonable values ​​for the missing data using waveform similarity calculations, thus filling in the missing data and obtaining more complete target first-arrival seismic wave data.

[0061] Based on the same inventive concept, one embodiment of this application provides a filtering system for first-arrival seismic wave anomaly data, such as... Figure 8 This is a schematic diagram of a first-arrival seismic wave anomaly data filtering system 800 provided in this embodiment. The system includes: The signal-to-noise ratio determination module 801 is used to determine the signal-to-noise ratio value of the target area based on the geological data of the target area. The parameter adjustment module 802 is used to adjust the anomaly enhancement parameter to perform anomaly enhancement processing on the first arrival seismic wave data when the signal-to-noise ratio value is less than or equal to a set threshold, and to adjust the anomaly filtering parameter to filter out abnormal data in the first arrival seismic wave data after anomaly enhancement processing. The data determination module 803 is used to filter the first arrival seismic wave data corresponding to the target area based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, so as to obtain the filtered target first arrival seismic wave data.

[0062] Optionally, the parameter adjustment module 802 includes: The first adjustment amount determination module is used to determine the amount of reduction in the calculation length and the amount of reduction in the energy threshold value corresponding to the signal-to-noise ratio value when the signal-to-noise ratio value is less than or equal to a set threshold value. The first anomaly enhancement module is used to reduce the initial value of the computation length in the anomaly enhancement parameters based on the amount of reduction in the computation length, so as to obtain the target value of the computation length. The second anomaly enhancement module is used to reduce the initial value of the energy threshold value in the anomaly enhancement parameters based on the amount of reduction of the energy threshold value, so as to obtain the target value of the energy threshold value.

[0063] Optionally, the parameter adjustment module 802 includes: The second adjustment amount determination module is used to determine the increase in the evaluation threshold value corresponding to the signal-to-noise ratio value and the decrease in the adjacent channel time difference when the signal-to-noise ratio value is less than or equal to a set threshold value. The first anomaly filtering module is used to increase the initial value of the evaluation threshold value in the anomaly filtering parameters based on the increase amount of the evaluation threshold value, so as to obtain the target value of the evaluation threshold value. The second anomaly filtering module is used to reduce the initial value of the adjacent channel time difference in the anomaly filtering parameters based on the reduction amount of the adjacent channel time difference, so as to obtain the target value of the adjacent channel time difference.

[0064] Optionally, the filtering system for the first-arrival seismic wave anomaly data further includes: The dispersion determination module is used to determine the dispersion of outlier distribution in the first arrival seismic wave data of the target. The comparison module is used to compare the outlier distribution dispersion with a preset dispersion value to obtain a comparison result; The qualification determination module is used to determine whether the target first arrival seismic wave data is qualified based on the comparison results.

[0065] Optionally, the pass / fail determination module includes: The first submodule for qualification determination is used to determine that the target first arrival seismic wave data is unqualified when the comparison result shows that the dispersion of the outlier distribution is greater than the preset dispersion value, and to readjust the outlier enhancement parameters and outlier filtering parameters. The second sub-module for qualification determination is used to determine that the target first arrival seismic wave data is qualified when the comparison result shows that the dispersion of the outlier distribution is less than or equal to the preset dispersion value, and to use the target first arrival seismic wave data for static correction processing.

[0066] Optionally, the filtering system for the first-arrival seismic wave anomaly data further includes: The range determination module is used to determine the medium signal-to-noise ratio range and the low signal-to-noise ratio range where the signal-to-noise ratio value is less than or equal to a set threshold range; The signal-to-noise ratio (SNR) adjustment amount determination module is used to establish the mapping relationship between the SNR range and the reduction of the calculation length and the energy threshold value in the anomaly enhancement parameters, respectively, as well as the mapping relationship between the increase of the evaluation threshold value and the reduction of the adjacent channel time difference in the anomaly filtering parameters, respectively. The low signal-to-noise ratio adjustment amount determination module is used to establish mapping relationships between the low signal-to-noise ratio range and the reduction in the computation length and energy threshold value in the anomaly enhancement parameters, respectively, as well as mapping relationships between the increase in the evaluation threshold value and the reduction in the adjacent channel time difference in the anomaly filtering parameters, respectively.

[0067] Optionally, the data determination module 803 includes: The first filling module is used to filter the first arrival seismic wave data of the target area based on the adjusted anomaly enhancement parameters and anomaly filtering parameters to obtain the filtered first arrival seismic wave data to be filled. The second filling module is used to fill the first arrival seismic wave data to be filled based on the data corresponding to adjacent seismic traces, so as to obtain the corresponding target first arrival seismic wave data.

[0068] Based on the same inventive concept, another embodiment of this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in any of the methods for filtering first-arrival seismic wave anomaly data.

[0069] Based on the same inventive concept, another embodiment of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the filtering method for first-arrival seismic wave anomaly data described in any of the above embodiments.

[0070] In the first-arrival seismic wave anomaly data filtering method provided in this application embodiment, by adjusting the anomaly enhancement parameters in the first-arrival seismic wave data picking software, the integrity of the first-arrival seismic wave data is ensured while making the anomalies in the first-arrival seismic wave data obvious, facilitating the subsequent removal of these anomalies. Furthermore, by adjusting the anomaly filtering parameters, these enhanced anomalies are accurately filtered out, ensuring the accuracy of the remaining first-arrival seismic wave data. At the same time, this embodiment removes anomalies by adjusting parameters, saving a significant amount of time compared to manually removing anomalies from first-arrival seismic wave data.

[0071] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0072] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0073] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0074] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes that element.

[0075] The above provides a detailed description of the filtering method, system, medium, and equipment for first-arrival seismic wave anomaly data provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for filtering first-arrival seismic wave anomaly data, characterized in that, The method includes: Determine the signal-to-noise ratio value of the target area based on the geological data of the target area; When the signal-to-noise ratio is less than or equal to a set threshold, the anomaly enhancement parameter is adjusted to perform anomaly enhancement processing on the first arrival seismic wave data, and the anomaly filtering parameter is adjusted to filter out abnormal data in the first arrival seismic wave data after anomaly enhancement processing. Based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, the first arrival seismic wave data corresponding to the target area is filtered to obtain the filtered target first arrival seismic wave data.

2. The method for filtering first-arrival seismic wave anomaly data according to claim 1, characterized in that, When the signal-to-noise ratio is less than or equal to a set threshold, the anomaly enhancement parameters are adjusted to perform anomaly enhancement processing on the first-arrival seismic wave data, including: When the signal-to-noise ratio value is less than or equal to a set threshold, determine the amount of reduction in the computation length and the amount of reduction in the energy threshold value corresponding to the signal-to-noise ratio value. Based on the reduction in computation length, the initial value of computation length in the anomaly enhancement parameters is reduced to obtain the target value of computation length. Based on the reduction amount of the energy threshold value, the initial value of the energy threshold value in the abnormal enhancement parameters is reduced to obtain the target value of the energy threshold value.

3. The method for filtering first-arrival seismic wave anomaly data according to claim 2, characterized in that, Adjusting the anomaly filtering parameters includes: When the signal-to-noise ratio value is less than or equal to a set threshold, determine the increase in the evaluation threshold value corresponding to the signal-to-noise ratio value and the decrease in the time difference between adjacent channels. Based on the increase in the evaluation threshold value, the initial value of the evaluation threshold value in the anomaly filtering parameter is increased to obtain the target value of the evaluation threshold value. Based on the reduction in the adjacent channel time difference, the initial value of the adjacent channel time difference in the anomaly filtering parameters is reduced to obtain the target value of the adjacent channel time difference.

4. The method for filtering first-arrival seismic wave anomaly data according to claim 1, characterized in that, The method further includes: Determine the dispersion of outlier distributions in the first arrival seismic wave data of the target; The outlier distribution dispersion is compared with a preset dispersion value to obtain the comparison result; Based on the comparison results, it is determined whether the target's first arrival seismic wave data is qualified.

5. The method for filtering first-arrival seismic wave anomaly data according to claim 4, characterized in that, Based on the comparison results, determine whether the target's first arrival seismic wave data is qualified, including: When the comparison result shows that the dispersion of the outlier distribution is greater than the preset dispersion value, the target first arrival seismic wave data is determined to be unqualified, and the anomaly enhancement parameters and anomaly filtering parameters are adjusted again. When the comparison result shows that the dispersion of the outlier distribution is less than or equal to the preset dispersion value, the target first arrival seismic wave data is determined to be qualified, and the target first arrival seismic wave data is used for static correction processing.

6. The method for filtering first-arrival seismic wave anomaly data according to claim 3, characterized in that, Before determining the signal-to-noise ratio of the target area based on its geological data, the method further includes: Determine the medium and low signal-to-noise ratio ranges where the signal-to-noise ratio values ​​are less than or equal to a set threshold range; Establish mapping relationships between the signal-to-noise ratio range and the reduction in computation length and energy threshold in the anomaly enhancement parameters, respectively, as well as between the increase in evaluation threshold and the reduction in adjacent channel time difference in the anomaly filtering parameters, respectively. Establish mapping relationships between the low signal-to-noise ratio range and the reduction in computation length and energy threshold in the anomaly enhancement parameters, respectively, as well as between the increase in evaluation threshold and the reduction in adjacent channel time difference in the anomaly filtering parameters, respectively.

7. The method for filtering first-arrival seismic wave anomaly data according to claim 1, characterized in that, Based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, the first-arrival seismic wave data corresponding to the target area are filtered to obtain filtered target first-arrival seismic wave data, including: Based on the adjusted anomaly enhancement parameters and anomaly filtering parameters, the first arrival seismic wave data of the target area is filtered to obtain the filtered first arrival seismic wave data to be filled. The first arrival seismic wave data to be filled is processed based on the data corresponding to adjacent seismic traces to obtain the corresponding target first arrival seismic wave data.

8. A filtering system for first-arrival seismic wave anomaly data, characterized in that, The system includes: The signal-to-noise ratio determination module is used to determine the signal-to-noise ratio value of the target area based on the geological data of the target area. The parameter adjustment module is used to adjust the anomaly enhancement parameter to perform anomaly enhancement processing on the first arrival seismic wave data when the signal-to-noise ratio value is less than or equal to a set threshold, and to adjust the anomaly filtering parameter to filter out abnormal data in the first arrival seismic wave data after anomaly enhancement processing. The data determination module is used to filter the first-arrival seismic wave data of the target area based on the adjusted anomaly enhancement parameters and anomaly filtering parameters to obtain the filtered target first-arrival seismic wave data.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps in the method for filtering first-arrival seismic wave anomaly data as described in any one of claims 1 to 7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the filtering method for first-arrival seismic wave anomaly data as described in any one of claims 1 to 7.

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