Noise source positioning method and device, electronic equipment and storage medium

Abstract

The invention provides a noise source positioning method and device, electronic equipment and a storage medium. The noise source positioning method comprises the following steps: carrying out de-coding processing on a seismic exploration original record to obtain seismic wave data; carrying out coordinate loading on the observation point and the seismic source according to the seismic wave data to obtain a coordinate loading result; acquiring noise source data according to the seismic wave data; and positioning the noise source on the coordinate loading result according to the noise source data. According to the noise positioning method provided by the invention, the noise source can be marked in the coordinate system where the observation point and the seismic source are located, so that a user can quickly determine the position of the noise source according to the known specific positions of the seismic source and the observation point, the user does not need to visit and find the noise source on site, and the exploration efficiency of seismic exploration is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a noise source localization method, device, electronic device and storage medium. Background Art

[0002] Underground oil and gas exploration and development often requires seismic exploration of the underground environment. By artificially creating crustal vibrations, the propagation of seismic waves in the strata is recorded, so as to study the underground geological structure characteristics and the lithological characteristics of the bottom layer, and thus find mineral resources such as oil and natural gas that can be developed. However, when there are a large number of urban gatherings, industrial production and other human activities in the area where seismic exploration is carried out, the noise generated by human activities affects the signal-to-noise ratio of seismic data, so seismic exploration data is mainly stimulated and collected at night. However, uncertain interference such as industrial production and vehicle operation still exists at night, and the seismic waves generated by such interference sources have strong energy and wide frequency band, which seriously reduces the signal-to-noise ratio of seismic exploration data and affects the quality of seismic exploration data.

[0003] In view of the above problems, the existing seismic exploration construction needs to use instruments to monitor the surrounding noise interference, and the areas with serious noise interference need to be searched on site by on-site personnel to stop the work, which seriously reduces the efficiency of seismic exploration. Summary of the invention

[0004] The embodiments of the present application provide a noise source positioning method, device, electronic device and storage medium. Since the noise positioning method provided by the present application can mark the noise source in the coordinate system where the observation point and the earthquake source are located, the user can quickly determine the location of the noise source based on the known specific location of the earthquake source and the observation point, and no longer needs to visit the site to find the noise source, which effectively improves the exploration efficiency of seismic exploration.

[0005] In order to solve the above technical problems, the present application provides a noise source positioning method, comprising:

[0006] Decode and process the original records of seismic exploration to obtain seismic wave data;

[0007] Coordinate loading is performed on observation points and seismic sources according to seismic wave data to obtain coordinate loading results;

[0008] Acquire noise source data based on seismic wave data;

[0009] According to the noise source data, the noise source is located on the coordinate loading results.

[0010] Optionally, the noise source locating method provided by the present application further includes:

[0011] Performing energy scanning according to the seismic wave data to acquire first energy spectrum data;

[0012] Perform noise source gather on the first energy spectrum data to extract first gather data.

[0013] Optionally, the noise source locating method provided by the present application further includes:

[0014] The first energy spectrum data is screened according to a preset threshold to obtain screened first energy spectrum data whose energy spectrum is higher than the threshold.

[0015] Optionally, the noise source locating method provided by the present application further includes:

[0016] The threshold is determined based on the signal-to-noise ratio of the seismic data and the quality of the environmental data.

[0017] Optionally, the noise source locating method provided by the present application further includes:

[0018] Eliminate the seismic wave data related to the filtered first energy spectrum data from the seismic wave data to obtain the eliminated seismic wave data;

[0019] Performing energy scanning on the eliminated seismic wave data to obtain second energy spectrum data;

[0020] Performing noise source gather on the second energy spectrum data to extract second gather data;

[0021] Combining the first track gather data and the second track gather data to obtain a noise source track gather data set;

[0022] Combining the first energy spectrum data and the second energy spectrum data to obtain a noise source energy spectrum data set;

[0023] The noise source is located based on the coordinate loading result according to the noise source energy spectrum data set and the noise source gather data set.

[0024] Optionally, the noise source locating method provided by the present application further includes:

[0025] Preliminarily locating the first noise source according to the first energy spectrum data and the first gather data;

[0026] Positioning the second noise source around the first noise source according to the energy spectrum spatial distribution of the first energy spectrum data;

[0027] Determine whether the second noise source and the first noise source are of the same source according to a preset correlation judgment criterion;

[0028] The first noise source and the second noise source are located according to the result of the correlation determination.

[0029] Optionally, the noise source locating method provided by the present application further includes:

[0030] Comparing the noise source with a preset template noise source for correlation;

[0031] The noise sources are classified according to the correlation comparison result.

[0032] The present application also provides a noise source locating device, comprising:

[0033] A seismic wave data acquisition module is used to decode and process the original seismic exploration records to obtain seismic wave data;

[0034] A coordinate loading module, used to perform coordinate loading on the observation point and the seismic source according to the seismic wave data to obtain a coordinate loading result;

[0035] A noise source acquisition module, used for acquiring noise source data according to the seismic wave data;

[0036] The first positioning module is used to locate the noise source on the coordinate loading result according to the noise source data.

[0037] The present application also provides an electronic device, including:

[0038] at least one processor; and,

[0039] a memory communicatively connected to at least one processor; wherein,

[0040] The memory stores instructions that can be executed by at least one processor. The instructions are executed by the at least one processor so that the at least one processor can implement the noise source localization method described above.

[0041] The present application also provides a computer-readable storage medium storing a computer program, which can implement the above-mentioned noise source locating method when executed by a processor.

[0042] Since the noise locating method provided in the present application can mark the noise source in the coordinate system where the observation point and the earthquake source are located, the user can quickly determine the location of the noise source based on the known specific locations of the earthquake source and the observation point, and no longer needs to conduct field visits to search for the noise source, thereby effectively improving the exploration efficiency of seismic exploration.

[0043] The above description is only an overview of the technical solution provided by the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0045] Figure 1 This is one of the schematic diagrams of the noise source locating method provided in the embodiment of the present application;

[0046] Figure 2 This is the second schematic diagram of the noise source locating method provided in the embodiment of the present application;

[0047] Figure 3 This is the third schematic diagram of the noise source location method provided in the embodiment of the present application;

[0048] Figure 4 This is the fourth schematic diagram of the noise source locating method provided in the embodiment of the present application;

[0049] Figure 5 This is the fifth schematic diagram of the noise source locating method provided in the embodiment of the present application;

[0050] Figure 6 This is the sixth schematic diagram of the noise source locating method provided in the embodiment of the present application;

[0051] Figure 7 This is the seventh schematic diagram of the noise source locating method provided in the embodiment of the present application;

[0052] Figure 8 This is a noise source location process diagram provided by this application;

[0053] Fig. 9 It is one of the schematic diagrams of the noise source locating device provided in the embodiment of the present application;

[0054] Fig.10 This is the second schematic diagram of the noise source locating device provided in the embodiment of the present application;

[0055] Fig.11 This is the third schematic diagram of the noise source locating device provided in the embodiment of the present application;

[0056] Fig.12 This is the fourth schematic diagram of the noise source locating device provided in the embodiment of the present application;

[0057] Fig.13 This is the fifth schematic diagram of the noise source locating device provided in the embodiment of the present application;

[0058] Fig.14 This is the sixth schematic diagram of the noise source locating device provided in the embodiment of the present application;

[0059] Fig.15This is the seventh schematic diagram of the noise source locating device provided in the embodiment of the present application;

[0060] Fig.16 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0062] It should be emphasized that the noise source positioning method provided in this application is summarized, and the noise source includes various vibration interferences in two-dimensional or three-dimensional seismic exploration and other interferences that affect the seismic exploration process.

[0063] Many existing seismic exploration areas have a large number of urban clusters and dense populations, and their production and living activities are frequent, which brings a lot of interference to seismic exploration. Specifically, the seismic waves generated by artificial production and life have strong energy and wide bandwidth, which seriously affects the signal-to-noise ratio of seismic exploration data. Even if seismic exploration is carried out at night when the activity frequency is relatively low, it is inevitable that these uncertain interferences will affect the original records of seismic exploration, and even cause some single-shot records of seismic exploration to become waste. In response to the above problems, the existing seismic exploration process is often monitored by instruments. In the areas with strong noise interference, users are required to find the interference source on the spot and stop the interference, so as to eliminate the influence of the interference source on seismic exploration. However, the interference source is often far away from the seismic source and the observation point. Users often need to find the interference source within a few square kilometers, which takes a long time. The original records of seismic exploration before eliminating the interference source will be affected, which reduces the work efficiency and exploration quality of seismic exploration.

[0064] The present application provides a noise source locating method, which marks the noise source in the coordinate system where the observation point and the earthquake source are located. The user can quickly determine the location of the noise source based on the known specific locations of the earthquake source and the observation point, and no longer needs to conduct on-site visits to find the noise source. Automatic analysis of the noise source can be achieved, thereby improving the efficiency of finding noise sources in seismic exploration and improving the quality of seismic exploration data.

[0065] The first embodiment of the present application provides a noise source positioning method, such as Figure 1 As shown, including:

[0066] Step 101, decode the original seismic exploration records to obtain seismic wave data;

[0067] Step 102: coordinate loading is performed on the observation point and the seismic source according to the seismic wave data to obtain the coordinate loading result;

[0068] Step 103, obtaining noise source data according to seismic wave data;

[0069] Step 104: According to the noise source data, locate the noise source on the coordinate loading result.

[0070] Specifically, the noise source provided in this application first needs to decode the original records of seismic exploration, such as the artillery records and background noise records summarized in the seismic data acquisition process, to obtain seismic wave data. s The kth component band data S of the seismic wave obtained by the i-th observation point i，k (x R，i , t), then the data set obtained from N observation points is as shown in Formula 1:

[0071] S k (x s )=[S 1，k (x R，1 , t),…,S i，k (x R，i , t),…,S N，k (x R，N , t)] (1)

[0072] Among them, S 1，k (x R，1 , t) is the observation point located at χ R，1 The kth component of the seismic P wave band data is obtained in m, cm, mm or μm; S i，k (x R，i , t) is the observation point located at χ R，i The kth component of the seismic P wave band data, in units of m, cm, mm or μm; S N，k (x R，N , t) is the observation point located at χ R，N The k-th component of the seismic P-wave band data is obtained in m, cm, mm or μm.

[0073] Secondly, the observation coordinates are loaded according to the decoded seismic wave data, and the coordinate system is constructed and the earthquake source χ s and observation point χ R，i The coordinates are loaded into the system applying the noise source location method of the present application.

[0074] Subsequently, the decoded seismic wave data is subjected to energy scanning processing to obtain noise source data, and the noise source data is located in the constructed coordinate system according to the noise source data.

[0075] Since the noise locating method provided in the present application can mark the noise source in the coordinate system where the observation point and the earthquake source are located, the user can quickly determine the location of the noise source based on the known specific locations of the earthquake source and the observation point, and no longer needs to conduct field visits to search for the noise source, thereby effectively improving the exploration efficiency of seismic exploration.

[0076] Based on the above implementation, Figure 2 As shown, the noise source data includes the first energy spectrum data and the first track gather data. In the noise source positioning method provided in the present application, step 103 includes:

[0077] Step 131, performing energy scanning according to the seismic wave data to obtain first energy spectrum data;

[0078] Step 132: Perform noise source gather on the first energy spectrum data to extract first gather data.

[0079] Specifically, the noise source data includes first energy spectrum data and first track data. The present application also provides a specific method for obtaining noise source data. First, energy scanning is performed on the seismic wave data to obtain the first energy spectrum data. For example, the method for obtaining the first energy spectrum data in the noise source positioning method provided in the present application is shown in Formula 2:

[0080]

[0081] In the formula, E(χ S , i) is the energy spectrum data of the i-th channel, t i，1 is the starting time of the ith track, t i，2 is the end time of the ith track.

[0082] The average value of the N to energy spectrum data in formula (2) is calculated as shown in formula 3:

[0083]

[0084] Then, the noise source gather is extracted from the first energy spectrum data to extract the first gather data corresponding to the strong noise source in the energy spectrum data.

[0085] Finally, the noise source is located according to the first energy spectrum data and the first channel gather data. For example, the number of noise sources can be determined by the first channel gather data to achieve the preliminary location of the noise source, and then the preliminary location result of the noise source is calibrated by the spatial distribution in the first energy spectrum data. These positionings are all realized in a system with a pre-established coordinate system. The noise source is quickly determined by comparing the distance difference between the noise source and the known seismic wave coordinates and the known observation point coordinates.

[0086] On the basis of the above implementation mode, noise source data such as the first energy spectrum data and the first track gather data are obtained according to the seismic wave data, and the noise source data can be quickly located according to the noise source data, thereby improving the working efficiency of the noise source location method.

[0087] Based on the above implementation, Figure 3 As shown, after step 131 and before step 132, the noise source localization method provided by the present application also includes:

[0088] Step 133: Screening the first energy spectrum data according to a preset threshold to obtain screened first energy spectrum data having an energy spectrum higher than the threshold.

[0089] Specifically, energy spectra with energy intensities greater than a preset threshold are extracted from the first energy spectrum data, and the energy spectra are subsequently processed to locate corresponding noise sources. The energy spectrum Ratio of the preset threshold is shown in Formula 4.

[0090] Ratio=E(χ S , i) / E Ave (x S ) (4)

[0091] The energy spectrum Ratio of the preset threshold is the same as the threshold Threshold mentioned in the above embodiment.

[0092] On the basis of the above implementation mode, by adding a threshold, the noise intensity in the first energy spectrum data is too low, and the noise source that will not substantially affect the seismic exploration is excluded, thereby reducing the workload required for locating the noise source and improving the work efficiency of seismic exploration while ensuring the quality of seismic exploration.

[0093] Based on the above implementation, Figure 4 As shown, in the noise source locating method provided by the present application, before step 133, the method further includes:

[0094] Step 134: Determine the threshold according to the signal-to-noise ratio of the seismic data and the quality of the environmental data.

[0095] Specifically, in the noise source locating method provided by the present application, the threshold is pre-set by the user according to the signal-to-noise ratio of the seismic data and the quality of the environmental data, for example, 2. When the signal-to-noise ratio of the seismic data obtained by the user contains too much noise and the quality of the environmental data is poor, the threshold can be raised to 2.5 to exclude more weak noise, study the strong noise, and improve the efficiency of seismic exploration; when the signal-to-noise ratio of the seismic data obtained by the user contains very little noise and the quality of the environmental data is good, the threshold can be lowered to 1.5 to enhance the monitoring of noise sources with relatively weak noise, thereby further improving the quality of seismic exploration.

[0096] On the basis of the above implementation mode, the threshold is determined according to the signal-to-noise ratio of the seismic data and the quality of the environmental data, and is used to screen the first energy spectrum. The user can adjust the threshold according to their own needs, and a suitable screening method can be provided for a variety of occasions and needs. The versatility of the noise source locating method provided in this application is enhanced.

[0097] Based on the above implementation, Figure 5 As shown, in the noise source locating method provided by the present application, after step 132, the following further includes:

[0098] Step 135, removing the seismic wave data related to the filtered first energy spectrum data from the seismic wave data, and obtaining the removed seismic wave data;

[0099] Step 136, performing energy scanning on the eliminated seismic wave data to obtain second energy spectrum data;

[0100] Step 137, performing noise source gather on the second energy spectrum data to extract second gather data;

[0101] Step 138, merging the first track gather data and the second track gather data to obtain a noise source track gather data set;

[0102] Step 139: combining the first energy spectrum data and the second energy spectrum data to obtain a noise source energy spectrum data set;

[0103] Step 140: According to the noise source energy spectrum data set and the noise source gather data set, locate the noise source based on the coordinate loading result.

[0104] Specifically, the energy scan in the noise source location method provided in the present application is a multi-channel energy scan. First, multiple first energy spectrum data in the seismic wave data are used to generate an original energy spectrum data set, and then the first energy spectrum data in the original energy spectrum data set whose energy intensity is greater than a preset threshold is subjected to a first energy scan to obtain the corresponding first channel set data. Subsequently, the first energy spectrum data in the original energy spectrum data set is eliminated to obtain the eliminated original energy spectrum data set, and the eliminated original energy spectrum data set is subjected to an energy scan to obtain the corresponding second channel set data. When the channel set energy spectrum ratio of the second energy spectrum data is greater than the threshold, the second energy spectrum data is eliminated, and the energy scan is repeated until the channel set energy spectrum ratios of all remaining energy spectrum data are less than the threshold, and the energy scan is terminated.

[0105] The first energy spectrum data set is shown in Equation 5:

[0106] E M (X S )=[E(X S , 1),…,E(X S , j), …, E(X S,M)] (5)

[0107] Where E M (X S ) is the first energy spectrum data set, E(X S , 1) is the first energy spectrum data corresponding to the first band newly generated, E(X S , j) is the first energy spectrum data corresponding to the newly generated j-th band, E(X S , M) is the first energy spectrum data corresponding to the newly generated Mth band, and M is the total number of identified noise sources.

[0108] The first trace data set is shown in Equation 6:

[0109] S M (x S )=[S 1，k , (χ R，1 , t), ..., S m，k (x R，m , t), ..., S M，k (x R，M , t), t 0 ] (6)

[0110] Where S M (X S ) is the first set of data, S 1，k , (χ R，1 , t) is E(X S , 1) The corresponding first channel data, S m，k (x R，m , t) is E(X S , j) the corresponding first channel data, S M，k (x R，M , t) is E(X S , M) corresponds to the first channel set data.

[0111] Subsequently, the eliminated first energy spectrum data and the second energy spectrum data are merged to obtain a noise source energy spectrum data set, and the first channel gather data and the second channel gather data are merged to obtain a noise source channel gather data set. Finally, the noise source is located based on the noise source energy spectrum data set and the noise source channel gather data set.

[0112] The original energy spectrum data set after elimination is shown in Formula 7:

[0113] E N-M (X S )=[E(X S , 1),…,E(X S , j), …, E(X S ,NM)] (7)

[0114] Where EN-M (X S ) is the original energy spectrum data set after removing the j-th energy scan.

[0115] The gather data set corresponding to the original energy spectrum data set after elimination is shown in Formula 8:

[0116] S N-M (x S )=[S 1，k (x R，1 , t), ..., S i，k (x R，i , t), ..., S N-M，k (x R，N-M , t), t 0 ] (8)

[0117] Where s N-M (X S ) is the gather data set corresponding to the original energy spectrum data set after removing the j-th energy scan.

[0118] In addition, the present application also provides an example. First, a first energy scan is performed based on multiple first energy spectrum data in the seismic wave data to obtain multiple first track gather data, and corresponding original energy spectrum data sets and original track gather data sets are generated based on the multiple energy spectrum data and the multiple track gather data, respectively. The track gather energy spectrum ratios in the original energy spectrum data set and the original track gather data set that are greater than a preset threshold are eliminated, and energy scanning is performed again based on the eliminated original energy spectrum data set to generate a new track gather data set, and the elimination action is repeated until all energy spectrum data with track gather energy spectrum ratios greater than the threshold are eliminated and then the action is terminated.

[0119] On the basis of the above implementation, multiple energy scans are set until the energy spectrum gather ratios of all remaining energy spectrum data are less than a threshold, thus ending the energy scan and avoiding omission problems during the collection of energy spectrum gather data sets.

[0120] Based on the above implementation, Figure 6 As shown, the noise sources corresponding to the original earthquake records provided by the present application include a first noise source and a second noise source. In the noise source positioning method provided by the present application, step 104 includes:

[0121] Step 141: Preliminarily locate the first noise source according to the first energy spectrum data and the first gather data;

[0122] Step 142: locating the second noise source around the first noise source according to the energy spectrum spatial distribution of the first energy spectrum data;

[0123] Step 143: determining whether the second noise source and the first noise source are of the same source according to a preset correlation judgment criterion;

[0124] Step 144: locate the first noise source and the second noise source according to the result of the correlation determination.

[0125] Specifically, in the noise source positioning method provided in the present application, positioning can be performed by initially positioning and then judging the relationship between multiple adjacent noise sources according to the spatial distribution of the energy spectrum, and re-positioning the noise belonging to the same source. First, the noise source is preliminarily positioned in the generated coordinate system according to the first energy spectrum data and the first channel collection data. When there are multiple first energy spectrum and first channel collection data, each noise source in the energy spectrum data set and the channel collection data set is preliminarily positioned. Then, the spatial distribution in the first energy spectrum data is used to judge the correlation of the second noise source adjacent to the first noise source. When it is judged that the second noise source around the first noise source is the same source as the first noise source, the first noise source and the second noise source are re-positioned. The correlation judgment is shown in Formulas 9-11:

[0126] E i (X S )>E j (X S ) (9)

[0127]

[0128] |ji|=1 (11)

[0129] E in formula 8-10 i (X S ) is the first energy spectrum set E M (X S ) in which the i-th initially located noise source S i (X S )’s energy spectrum, E j (X S ) is the jth initially located noise source S j (X S ) spectrum, and S i (X S ) and S j (X S ) is the first channel data S M (X S ) in which there are two noise sources, is the cross-correlation operator, and Vαl is the correlation between the two noise sources. When the conditions of equations 8 and 10 are met, when the cross-correlation calculation result of the ith noise source and the jth noise source is greater than Vαl, it proves that the ith noise source and the jth noise source are homologous noises.

[0130] On the basis of the above implementation method, by judging the homologous noise of adjacent noise sources according to the correlation, and relocating and merging multiple noise sources belonging to the homologous noise, the number of located noise sources is reduced, the workload of eliminating noise sources in seismic exploration is reduced, and the work efficiency of seismic exploration is improved.

[0131] Based on the above implementation, Figure 7 As shown, in the noise source location method provided by the present application, after step 104, the following steps are further included:

[0132] Step 105, comparing the correlation between the noise source corresponding to the original earthquake record and the preset template noise source;

[0133] Step 106: classify the noise sources corresponding to the original earthquake records according to the correlation comparison results.

[0134] Specifically, after completing the positioning, the noise source corresponding to the original earthquake record can also be classified according to the preset template noise source, for example, into current interference, urban factory and mine interference, automobile vibration type mechanical interference and single-channel random interference. For example, the noise source located in this application can be cross-correlated, and when the correlation coefficient is greater than the preset value, it is determined that the noise source located in this application and the template noise source are the same type of noise source, as shown in Formula 12:

[0135]

[0136] Where Vαl Tem is the noise source S located in this application i (X S ) and template noise source S m (X S ), when the correlation coefficient is greater than a preset value, it is determined that the noise source located in the present application and the template noise source are the same noise source, thereby classifying all noise sources.

[0137] It should be emphasized that Vαl in Eq. Tem This is different from Vαl in Formula 10 in the above embodiment. Tem It is used to analyze the type of noise source, so as to realize the classification of the type of noise source after positioning, while Vαl is mainly used to merge the noise sources after the initial positioning to obtain new noise sources.

[0138] On the basis of the above implementation mode, by comparing the correlation between the noise source and the preset template noise source, the noise sources in the seismic exploration raw data are classified according to the comparison results. The classified noise sources are convenient for users to judge whether they need to be excluded according to actual conditions, thereby reducing the workload of seismic exploration and improving the work efficiency of seismic exploration.

[0139] Based on the above implementation, Figure 8 As shown, the present application provides a specific noise source positioning process diagram in combination with a noise source positioning system that applies the noise source positioning method provided by the present application:

[0140] Obtain original seismic data such as single shot records and background noise records during the seismic data acquisition process, enter these original seismic data into the system for data format conversion and load into the observation system, for example, decode the original seismic data to obtain a data set, load the observation coordinates according to the data set, and construct a coordinate system through the known source coordinates and observation point coordinates.

[0141] Then, the energy spectrum is scanned according to the data set obtained after the decoding to obtain the first energy spectrum data set and the first channel data set. Then, it is judged that when the channel energy spectrum ratio of the first energy spectrum data and the first channel data of one band is greater than the threshold, the first energy spectrum data and the first channel data of this band are removed, and the second-level energy scan is performed according to the remaining data of the first energy spectrum data set and the first channel data set. When the channel energy spectrum ratio of the second energy spectrum data and the second channel data after the second-level energy scan is greater than the threshold, the second energy spectrum data and the second channel data are extracted, and the energy scan is repeated until the channel energy spectrum ratio of all the remaining data in the first energy spectrum data set and the first channel data set is less than or equal to the preset threshold. According to these removed energy spectrum data and channel data, multiple noise sources in the original seismic data are initially located. According to the preset correlation judgment, these noise sources are accurately judged whether they are of the same source, and multiple noise sources that are essentially of the same source are relocated and output for display. In addition, after the positioning is completed, these noise sources can also be classified, so that users can quickly exclude them according to the classification results, thereby improving the work efficiency of seismic exploration.

[0142] The second embodiment of the present application also provides a noise source positioning device, such as Fig. 9 As shown, including:

[0143] The seismic wave data acquisition module 201 is used to decode the original seismic exploration records to obtain seismic wave data;

[0144] A coordinate loading module 202 is used to perform coordinate loading on the observation point and the seismic source according to the seismic wave data to obtain a coordinate loading result;

[0145] A noise source acquisition module 203, used to acquire noise source data according to the seismic wave data;

[0146] The first positioning module 204 is used to locate the noise source on the coordinate loading result according to the noise source data.

[0147] Based on the above implementation, Fig.10 As shown, the noise source acquisition module 203 includes:

[0148] A first energy spectrum acquisition unit 231 is used to perform energy scanning according to the seismic wave data to acquire first energy spectrum data;

[0149] The first channel gather acquisition unit 232 is used to perform noise source channel gather on the first energy spectrum data to extract first channel gather data.

[0150] Based on the above implementation, Fig.11 As shown, the noise source acquisition module 203 also includes:

[0151] The threshold screening module 233 is used to screen the first energy spectrum data according to a preset threshold to obtain screened first energy spectrum data whose energy spectrum is higher than the threshold.

[0152] Based on the above implementation, Fig.12 As shown, the noise source acquisition module 203 also includes:

[0153] The threshold setting module 234 is used to determine the threshold according to the signal-to-noise ratio of the seismic data and the quality of the environmental data.

[0154] Based on the above implementation, Fig.13 As shown, the noise source locating device also includes:

[0155] A removal module 235 is used to remove the seismic wave data related to the filtered first energy spectrum data from the seismic wave data to obtain the removed seismic wave data;

[0156] A second energy spectrum acquisition module 236 is used to perform energy scanning on the eliminated seismic wave data to acquire second energy spectrum data;

[0157] A second gather acquisition module 237, used for performing noise source gather on the second energy spectrum data to extract second gather data;

[0158] A gather data set merging module 238, configured to merge the first gather data and the second gather data to obtain a noise source gather data set;

[0159] An energy spectrum data set merging module 239, configured to merge the first energy spectrum data and the second energy spectrum data to obtain a noise source energy spectrum data set;

[0160] The second positioning module 240 is used to locate the noise source based on the coordinate loading result according to the noise source energy spectrum data set and the noise source gather data set.

[0161] Based on the above implementation, Fig.14 As shown, the noise sources corresponding to the original earthquake record provided in the present application include a first noise source and a second noise source, and the first positioning module 204 includes:

[0162] An initial positioning unit 241, configured to perform an initial positioning of the first noise source according to the first energy spectrum data and the first gather data;

[0163] A surrounding sound source positioning unit 242, configured to position the second noise source around the first noise source according to the energy spectrum spatial distribution of the first energy spectrum data;

[0164] A correlation determination unit 243, configured to determine whether the second noise source and the first noise source are of the same source according to a preset correlation determination criterion;

[0165] The re-positioning unit 244 is used to position the first noise source and the second noise source according to the result of the correlation judgment.

[0166] Based on the above implementation, Fig.15 As shown, the noise source locating device also includes:

[0167] The template judgment module 205 is used to compare the correlation between the noise source corresponding to the original earthquake record and the preset template noise source;

[0168] Classification module 206, for classifying the noise sources corresponding to the original earthquake records according to the correlation comparison results

[0169] A third embodiment of the present application relates to a mobile terminal, such as Fig.16 As shown, including:

[0170] at least one processor 161; and,

[0171] A memory 162 is communicatively connected to the at least one processor 161; wherein,

[0172] The memory 162 stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor 161 so that the at least one processor 161 can implement the sample data collection method described in the first embodiment of the present application.

[0173] Among them, the memory and the processor are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and memories together. The bus can also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor is transmitted on a wireless medium via an antenna, and further, the antenna also receives data and transmits the data to the processor.

[0174] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory can be used to store data used by the processor when performing operations.

[0175] The fourth embodiment of the present application relates to a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the sample data collection method described in the first embodiment of the present application.

[0176] That is, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0177] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the application disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0178] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A noise source location method, characterized in that: include: Decode and process the original records of seismic exploration to obtain seismic wave data; Performing coordinate loading on the observation point and the seismic source according to the seismic wave data to obtain a coordinate loading result; Acquiring noise source data according to the seismic wave data; The noise source is located on the coordinate loading result according to the noise source data.

2. The method according to claim 1, characterized in that The noise source data includes first energy spectrum data and first track gather data, and obtaining the noise source data according to the seismic wave data includes: Performing energy scanning according to the seismic wave data to acquire first energy spectrum data; Perform noise source gather on the first energy spectrum data to extract first gather data.

3. The method according to claim 2, characterized in that After performing energy scanning according to the seismic wave data to obtain the first energy spectrum data, and before performing noise source gather extraction on the first energy spectrum data to obtain the first gather data, the method further includes: The first energy spectrum data is screened according to a preset threshold to obtain screened first energy spectrum data whose energy spectrum is higher than the threshold.

4. The method according to claim 3, characterized in that Before the first energy spectrum data is screened according to a preset threshold to obtain first energy spectrum data with an energy spectrum higher than the threshold, the method further includes: The threshold is determined based on the signal-to-noise ratio of the seismic data and the quality of the environmental data.

5. The method according to claim 2, characterized in that: After performing noise source gather extraction on the first energy spectrum data to obtain first gather data, the method further includes: Eliminate the seismic wave data related to the filtered first energy spectrum data from the seismic wave data to obtain the eliminated seismic wave data; Performing energy scanning on the eliminated seismic wave data to obtain second energy spectrum data; Performing noise source gather on the second energy spectrum data to extract second gather data; Combining the first track gather data and the second track gather data to obtain a noise source track gather data set; Combining the first energy spectrum data and the second energy spectrum data to obtain a noise source energy spectrum data set; The noise source is located based on the coordinate loading result according to the noise source energy spectrum data set and the noise source gather data set.

6. The method according to claim 2, characterized in that The noise source corresponding to the original earthquake record includes a first noise source and a second noise source, and locating the noise source corresponding to the original earthquake record according to the noise source data includes: Preliminarily locating the first noise source according to the first energy spectrum data and the first gather data; Positioning the second noise source around the first noise source according to the energy spectrum spatial distribution of the first energy spectrum data; Determine whether the second noise source and the first noise source are of the same source according to a preset correlation judgment criterion; The first noise source and the second noise source are located according to the result of the correlation determination.

7. The method according to claim 1, characterized in that After locating the noise source on the coordinate loading result according to the noise source data, the method further includes: Comparing the noise source with a preset template noise source for correlation; The noise sources are classified according to the correlation comparison result.

8. A noise source locating device, characterized in that: include: A seismic wave data acquisition module is used to decode and process the original seismic exploration records to obtain seismic wave data; A coordinate loading module, used to perform coordinate loading on the observation point and the seismic source according to the seismic wave data to obtain a coordinate loading result; A noise source acquisition module, used for acquiring noise source data according to the seismic wave data; The first positioning module is used to locate the noise source on the coordinate loading result according to the noise source data.

9. An electronic device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can implement the noise source localization method described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the noise source localization method described in any one of claims 1 to 7 is implemented.

Images