Seismic data processing method, device, equipment and medium

Abstract

The application provides a seismic data processing method, device, equipment and medium, and belongs to the field of oil exploration. The method comprises the following steps: determining a plurality of nearest receiver arrays corresponding to a plurality of shot points respectively from seismic data of a target region based on the distance between the shot points and the receiver arrays; for each shot point in the plurality of shot points, determining the number of strong energy channels corresponding to the shot point based on the seismic data collected by the nearest receiver array corresponding to the shot point; re-adjusting the partition of different surfaces in the target region based on the number of strong energy channels corresponding to each shot point in each sub-region to obtain a plurality of adjusted sub-regions; and performing differential denoising on the seismic data of the target region based on the plurality of adjusted sub-regions to obtain denoised seismic data. The scheme can more accurately perform partitioning and improve the denoising effect of seismic data.

Description

Technical Field

[0001] This application relates to the field of petroleum exploration, and in particular to a method, apparatus, equipment and medium for processing seismic data. Background Technology

[0002] In recent years, with the continuous improvement of oil and gas exploration technology, high-efficiency lithological exploration of medium and deep formations has received increasing attention. The identification and prediction of lithological exploration targets place extremely high demands on the fidelity of seismic data. However, during the entire propagation process of seismic waves from the excitation point to the receiver point, the main energy of the source is concentrated near the near offset of the shot point, causing the effective signals from deep formations to be completely submerged in strong energy noise from shallow formations during imaging. Therefore, denoising of seismic data is crucial. Since oil and gas exploration areas are typically large and contain various types of surfaces, seismic data denoising usually involves differentiated denoising based on surface zoning in electronic maps to improve data fidelity. However, in practical applications, it has been found that the zoning of different surfaces in electronic maps is inaccurate, resulting in poor denoising effects on seismic data. Summary of the Invention

[0003] This application provides a method, apparatus, device, and medium for processing seismic data, which can more accurately partition the data and improve the denoising effect of seismic data. The technical solution is as follows:

[0004] On the one hand, a method for processing seismic data is provided, the method comprising:

[0005] Based on the distance between the shot points and receiver arrangements, the nearest receiver arrangements corresponding to multiple shot points are determined from the seismic data of the target area. The nearest receiver arrangement corresponding to any shot point is the receiver arrangement that is closest to the shot point among the multiple receiver arrangements corresponding to the shot point. The target area includes multiple sub-areas with different surface types, and multiple shot points are distributed in each sub-area.

[0006] For each of the plurality of shot points, based on the seismic data acquired from the nearest geophone array corresponding to the shot point, the number of high-energy channels corresponding to the shot point is determined. The number of high-energy channels is the number of seismic channels with energy intensity greater than an intensity threshold. One seismic channel corresponds to one geophone in the geophone array and the shot point corresponding to the geophone array.

[0007] Based on the number of high-energy channels corresponding to each shot point in each sub-region, the partitions of different surfaces in the target region are readjusted to obtain multiple adjusted sub-regions, so that the difference in the number of high-energy channels corresponding to different shot points in the adjusted sub-regions does not exceed the high-energy channel threshold.

[0008] Based on the multiple adjusted sub-regions, the seismic data of the target region is differentially denoised to obtain denoised seismic data.

[0009] In one possible implementation, the partitioning of different surfaces in the target area is readjusted based on the number of high-energy channels corresponding to each shot point in each sub-region, resulting in multiple adjusted sub-regions, including:

[0010] For any sub-region, the number of high-energy channels corresponding to the reference shot point in the sub-region is determined as the reference channel number;

[0011] Based on the number of high-energy channels and the reference channel number corresponding to each shot point in each sub-region, shot points whose difference between the number of high-energy channels and the reference channel number does not exceed the threshold of the number of high-energy channels are determined.

[0012] Based on the reference firing point and the determined firing point, an adjusted sub-region is determined, wherein the adjusted sub-region includes the reference firing point and the determined firing point.

[0013] In one possible implementation, the method further includes any of the following:

[0014] The shot point located at the center of the sub-region is designated as the reference shot point;

[0015] The shot point closest to the center in the sub-region is determined as the reference shot point;

[0016] The target area is displayed as a gun point distribution interface, which includes multiple gun points distributed in the target area; in response to the selection operation of any gun point in the gun point distribution interface, the gun point is determined as a reference gun point in the sub-area where the gun point is located.

[0017] In one possible implementation, determining the number of high-energy channels corresponding to each of the plurality of shot points, based on seismic data acquired from the nearest receiver array corresponding to that shot point, includes:

[0018] For each of the plurality of shot points, the seismic data acquired by the nearest geophone array corresponding to the shot point are subjected to autocorrelation processing to obtain the amplitude of the plurality of seismic traces formed by the shot point and the nearest geophone array.

[0019] Based on the amplitude of the multiple seismic traces, the number of high-energy traces corresponding to the shot point is determined.

[0020] In one possible implementation, the method further includes:

[0021] For each of the plurality of shot points, multiple seismic data segments of equal time intervals are selected from the seismic data acquired from the nearest receivers corresponding to the shot point in chronological order; based on each seismic data segment, the number of high-energy channels corresponding to the shot point in the multiple time periods is determined; based on the variation rules of the number of high-energy channels of the shot point in different time periods, the surface type corresponding to the shot point is determined, and the surface type corresponding to the shot point is used to indicate the surface type at the location of the shot point;

[0022] For any adjusted sub-region, the surface type of the adjusted sub-region is determined based on the surface type corresponding to the shot point in the adjusted sub-region.

[0023] The step involves differentially denoising the seismic data of the target region based on the multiple adjusted sub-regions to obtain denoised seismic data, including:

[0024] Based on the multiple adjusted sub-regions and the surface types of the multiple adjusted sub-regions, differential denoising is performed on the seismic data of the target region to obtain the denoised seismic data.

[0025] In one possible implementation, determining the surface type corresponding to the shot point based on the variation rules of the high-energy channel number of the shot point over different time periods includes:

[0026] The ratio of the number of high-energy channels corresponding to the gun point in the first time period to the number of high-energy channels corresponding to the gun point in the second time period is obtained to obtain the first ratio.

[0027] The ratio of the number of strong energy channels corresponding to the gun point in the second time period to the number of strong energy channels corresponding to the gun point in the third time period is obtained to obtain the second ratio. The first time period, the second time period, and the third time period are arranged in chronological order from front to back.

[0028] The difference between the first ratio and the second ratio is determined as the first relationship coefficient, which is used to represent the strength of the relationship between the high-energy channel number and the noise.

[0029] Based on the first relation coefficient and the correspondence between the relation coefficient and the surface type, the surface type corresponding to the first relation coefficient is determined as the surface type corresponding to the shot point.

[0030] On the other hand, a seismic data processing apparatus is provided, the apparatus comprising:

[0031] The first determining module is used to determine the nearest geophone arrangement corresponding to multiple shot points from the seismic data of the target area based on the distance between the arrangement of shot points and geophone points. The nearest geophone arrangement corresponding to any shot point is the arrangement of geophone points that is closest to the shot point among the multiple geophone arrangements corresponding to the shot point. The target area includes multiple sub-regions with different surface types, and multiple shot points are distributed in each sub-region.

[0032] The second determining module is used to determine the number of high-energy channels corresponding to each of the plurality of shot points based on the seismic data acquired by the nearest geophone arrangement corresponding to the shot point. The number of high-energy channels is the number of seismic channels with energy intensity greater than an intensity threshold. One seismic channel corresponds to one geophone in the nearest geophone arrangement and the shot point corresponding to the nearest geophone arrangement.

[0033] The adjustment module is used to readjust the partitions of different surfaces in the target area based on the number of high-energy channels corresponding to each shot point in each sub-region, so as to obtain multiple adjusted sub-regions, and the difference in the number of high-energy channels corresponding to different shot points in the adjusted sub-regions does not exceed the high-energy channel threshold.

[0034] The denoising module is used to perform differential denoising on the seismic data of the target area based on the multiple adjusted sub-regions, so as to obtain denoised seismic data.

[0035] In one possible implementation, the adjustment module is configured to, for any sub-region, determine the high-energy channel number corresponding to a reference shot point in the sub-region as a reference channel number; based on the high-energy channel number corresponding to each shot point in each sub-region and the reference channel number, determine shot points whose difference between the high-energy channel number and the reference channel number does not exceed the high-energy channel number threshold; and based on the reference shot point and the determined shot points, determine an adjusted sub-region, wherein the adjusted sub-region includes the reference shot point and the determined shot points.

[0036] In one possible implementation, the device further includes a third determining module, the third determining module being configured to point to any one of the following:

[0037] The shot point located at the center of the sub-region is designated as the reference shot point;

[0038] The shot point closest to the center in the sub-region is determined as the reference shot point;

[0039] The target area is displayed as a gun point distribution interface, which includes multiple gun points distributed in the target area; in response to the selection operation of any gun point in the gun point distribution interface, the gun point is determined as a reference gun point in the sub-area where the gun point is located.

[0040] In one possible implementation, the second determining module is configured to perform autocorrelation processing on the seismic data acquired from the nearest geophone array corresponding to each of the plurality of shot points to obtain the amplitude of the plurality of seismic traces formed by the shot point and the nearest geophone array; and determine the number of high-energy traces corresponding to the shot point based on the amplitude of the plurality of seismic traces.

[0041] In one possible implementation, the device further includes:

[0042] The fourth determining module is used to, for each of the plurality of shot points, select multiple seismic data segments of equal time intervals from the seismic data acquired from the nearest receivers corresponding to the shot point in chronological order; determine the number of high-energy channels corresponding to the shot point in the multiple time periods based on each seismic data segment; and determine the surface type corresponding to the shot point based on the variation rules of the number of high-energy channels of the shot point in different time periods, wherein the surface type corresponding to the shot point is used to indicate the surface type at the location of the shot point.

[0043] The fifth determining module is used to determine the surface type of any adjusted sub-region based on the surface type corresponding to the shot point in the adjusted sub-region.

[0044] The denoising module is used to perform differential denoising on the seismic data of the target area based on the plurality of adjusted sub-regions and the surface types of the plurality of adjusted sub-regions, to obtain the denoised seismic data.

[0045] In one possible implementation, the fourth determining module is used to obtain a first ratio by comparing the number of high-energy channels corresponding to the shot point in a first time period with the number of high-energy channels corresponding to the shot point in a second time period; to obtain a second ratio by comparing the number of high-energy channels corresponding to the shot point in the second time period with the number of high-energy channels corresponding to the shot point in a third time period, wherein the first time period, the second time period, and the third time period are arranged in chronological order; the difference between the first ratio and the second ratio is determined as a first relationship coefficient, wherein the relationship coefficient is used to represent the strength of the relationship between the number of high-energy channels and noise; and based on the first relationship coefficient and the correspondence between the relationship coefficient and the surface type, the surface type corresponding to the first relationship coefficient is determined as the surface type corresponding to the shot point.

[0046] On the other hand, a computer device is provided, the computer device including a processor and a memory, the memory storing at least one piece of program code, the at least one piece of program code being loaded and executed by the processor to implement the seismic data processing method as described in any of the above implementations.

[0047] On the other hand, a computer-readable storage medium is provided, wherein at least one piece of program code is stored in the computer-readable storage medium, the at least one piece of program code being loaded and executed by a processor to implement the seismic data processing method as described in any of the above implementations.

[0048] On the other hand, a computer program product is provided, the computer program product including at least one piece of program code, the at least one piece of program code being loaded and executed by a processor to implement the seismic data processing method as described in any of the above implementations.

[0049] The beneficial effects of the technical solutions provided in this application include at least the following:

[0050] This application provides a method for processing seismic data. Considering that seismic waves lose energy differently when propagating on different types of surfaces, the target area is divided into zones based on the number of strong energy traces at different locations in the target area. This zoning is consistent with the energy loss of seismic waves when propagating on different types of surfaces. Therefore, this zoning is more accurate, and thus it can more accurately perform differentiated denoising on the seismic data, improving the denoising effect of the seismic data. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0052] Figure 1 This is a flowchart of a seismic data processing method provided in an embodiment of this application;

[0053] Figure 2 This is a flowchart of a seismic data processing method provided in an embodiment of this application;

[0054] Figure 3 This is a comparison image of denoised seismic data provided in an embodiment of this application;

[0055] Figure 4 This is a schematic diagram of the structure of a seismic data processing device provided in an embodiment of this application;

[0056] Figure 5 This is a schematic diagram of the structure of a seismic data processing device provided in an embodiment of this application;

[0057] Figure 6 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application;

[0058] Figure 7 This is a schematic diagram of the structure of a server provided in an embodiment of this application. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0060] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0061] The seismic data processing method provided in this application is executed by a computer device. In some embodiments, the computer device may be a terminal, such as a mobile phone, tablet computer, laptop computer, desktop computer, or any other type of terminal; this application does not limit the type of terminal. In other embodiments, the computer device may be a server, such as a single server, a server cluster consisting of several servers, or a cloud computing service center. Of course, the server may also include other functional servers to provide more comprehensive and diversified services. In other embodiments, the computer device includes both a terminal and a server. It should be noted that this application is merely an illustrative description of the execution subject of the seismic data processing method and does not limit the execution subject. It should also be noted that the seismic data processing method provided in this application can be executed by a terminal and a server in cooperation, and the specific steps performed by the terminal and server are not limited.

[0062] Figure 1 This is a flowchart illustrating a seismic data processing method provided in an embodiment of this application. This embodiment uses a computer device as an example for illustrative purposes. See also... Figure 1 The method includes:

[0063] 101. The computer equipment determines the nearest geophone arrangement corresponding to multiple shot points from the seismic data of the target area based on the distance between the shot point and the geophone arrangement. The nearest geophone arrangement corresponding to any shot point is the geophone arrangement that is closest to the shot point among the multiple geophone arrangements corresponding to the shot point. The target area includes multiple sub-regions with different surface types, and multiple shot points are distributed in each sub-region.

[0064] In oil and gas exploration, multiple shot points and multiple geophones can be arranged in the work area. Each geophone arrangement includes multiple geophones located in the same row. After a seismic wave is generated by any shot point, the seismic wave is received based on the arrangement of multiple geophones. In this embodiment, when determining the nearest geophone arrangement corresponding to multiple shot points from the seismic data of the target area, the multiple shot points can be all shot points in the target area or only some shot points; this embodiment does not limit this. Since this embodiment aims to divide the target area into zones, it is only necessary to ensure that the multiple shot points are distributed in multiple different locations within the target area, and that each sub-region of the target area has multiple shot points.

[0065] It should be noted that the multiple sub-regions with different surface types in step 101 above can be determined based on an electronic map or by dividing the target area into equal parts. Since the target area contains different types of surface, the surface types of the multiple sub-regions are not completely the same after dividing the target area into multiple sub-regions.

[0066] The land surface type can be Gobi, small desert, large desert, grassland, etc., but this application does not limit the land surface type.

[0067] 102. For each of multiple shot points, the computer equipment determines the number of high-energy channels corresponding to that shot point based on the seismic data acquired from the nearest receiver array. The number of high-energy channels is the number of seismic channels with energy intensity greater than the intensity threshold. One seismic channel corresponds to one receiver array and the shot point corresponding to the receiver array.

[0068] A seismic trace corresponds to a receiver point in a receiver point array and a shot point in the receiver point array. This means that a receiver point and a shot point together form a seismic trace, and the seismic data of the seismic trace is the data excited from the shot point and received at the receiver point.

[0069] The intensity threshold can be any value, and this application embodiment does not limit the intensity threshold. Optionally, the intensity threshold is a preset value; alternatively, the intensity threshold is an empirical value. Since the number of high-energy traces is the number of seismic traces with energy intensity greater than the intensity threshold, the number of high-energy traces can also be regarded as the number of high-energy traces corresponding to the shot point.

[0070] 103. The computer equipment readjusts the partitions of different surfaces in the target area based on the number of high-energy channels corresponding to each shot point in each sub-region, resulting in multiple adjusted sub-regions, so that the difference in the number of high-energy channels corresponding to different shot points in the adjusted sub-regions does not exceed the high-energy channel threshold.

[0071] Since different types of land surfaces have different effects on seismic waves, the number of strong energy channels at shot points located on different types of land surfaces will also be different. Therefore, in this embodiment, the zoning of different land surfaces in the target area is readjusted based on the number of strong energy channels corresponding to each shot point in each sub-region, so that the number of strong energy channels corresponding to different shot points in each sub-region is similar. In this way, the noise impact at the location of the shot point in each sub-region is also similar, ensuring the consistency of land surface type at multiple locations in the sub-region.

[0072] 104. The computer equipment performs differential denoising on the seismic data of the target area based on multiple adjusted sub-regions to obtain denoised seismic data.

[0073] Because different types of land surfaces have varying effects on seismic wave propagation, differentiated denoising is necessary for seismic data from different sub-regions to obtain accurate data. This differentiated denoising can take the following forms: using different denoising methods for sub-regions with different land surface types; or using different noise suppression parameters for sub-regions with different land surface types. Of course, other types of differentiated denoising are also possible, and this application does not limit the specific methods used in its embodiments.

[0074] After the computer equipment performs differential denoising on the seismic data of the target area, it can also perform superposition processing, deconvolution processing, interpretation processing, etc. on the denoised seismic data. The application of the denoised seismic data is not limited in the embodiments of this application.

[0075] The seismic data processing method provided in this application takes into account the different energy losses of seismic waves propagating on different types of surfaces. Therefore, the target area is divided into zones according to the number of strong energy traces of shot points at different locations in the target area. This zoning is consistent with the energy loss of seismic waves propagating on different types of surfaces. Therefore, this zoning is more accurate, and thus it can more accurately perform differential denoising on seismic data, thereby improving the denoising effect of seismic data.

[0076] In one possible implementation, based on the number of high-energy channels corresponding to each shot point in each sub-region, the different surface partitions in the target region are readjusted to obtain multiple adjusted sub-regions, including:

[0077] For any sub-region, the high-energy channel number corresponding to the reference shot point in the sub-region is determined as the reference channel number;

[0078] Based on the high-energy channel number and reference channel number corresponding to each shot point in each sub-region, shot points whose difference between the high-energy channel number and the reference channel number does not exceed the high-energy channel number threshold are determined.

[0079] Based on the reference shot point and the determined shot point, an adjusted sub-region is determined, which includes the reference shot point and the determined shot point.

[0080] In one possible implementation, the method also includes any of the following:

[0081] The firing point located at the center of the sub-region is designated as the reference firing point;

[0082] The firing point closest to the center in the sub-region is designated as the reference firing point;

[0083] The target area's shot point distribution interface is displayed, which includes multiple shot points distributed throughout the target area. In response to the selection of any shot point in the shot point distribution interface, the shot point is designated as the reference shot point for the sub-area where the shot point is located.

[0084] In one possible implementation, for each of multiple shot points, the number of high-energy traces corresponding to the shot point is determined based on the seismic data acquired from the nearest receiver array corresponding to the shot point, including:

[0085] For each of the multiple shot points, the seismic data acquired by the nearest geophones corresponding to the shot point are subjected to autocorrelation processing to obtain the amplitude of multiple seismic traces formed by the shot point and the nearest geophones.

[0086] Based on the amplitude of multiple seismic traces, the number of high-energy traces corresponding to the shot point is determined.

[0087] In one possible implementation, the method also includes:

[0088] For each of the multiple shot points, multiple seismic data segments with equal time intervals are selected from the seismic data acquired from the nearest receivers corresponding to the shot point in chronological order. Based on each seismic data segment, the number of high-energy traces corresponding to the shot point in the multiple time periods is determined. Based on the variation rules of the number of high-energy traces of the shot point in different time periods, the surface type corresponding to the shot point is determined. The surface type corresponding to the shot point is used to indicate the surface type at the location of the shot point.

[0089] For any adjusted sub-region, the surface type of the adjusted sub-region is determined based on the surface type corresponding to the shot points in the adjusted sub-region.

[0090] Based on multiple adjusted sub-regions, differential denoising is performed on the seismic data of the target region to obtain denoised seismic data, including:

[0091] Based on multiple adjusted sub-regions and the surface types of multiple adjusted sub-regions, differential denoising is performed on the seismic data of the target region to obtain denoised seismic data.

[0092] In one possible implementation, the surface type corresponding to the shot point is determined based on the variation rules of the high-energy trace number of the shot point over different time periods, including:

[0093] The first ratio is obtained by comparing the number of strong energy channels corresponding to the first firing point in the first time period with the number of strong energy channels corresponding to the second firing point in the second time period.

[0094] The ratio of the number of strong energy channels corresponding to the gun point in the second time period to the number of strong energy channels corresponding to the gun point in the third time period is obtained to obtain the second ratio. The first time period, the second time period, and the third time period are arranged in chronological order.

[0095] The difference between the first ratio and the second ratio is determined as the first relationship coefficient. The relationship coefficient is used to represent the strength of the relationship between the high-energy channel number and the noise.

[0096] Based on the first relation coefficient and the correspondence between the relation coefficient and the surface type, the surface type corresponding to the first relation coefficient is determined as the surface type corresponding to the shot point.

[0097] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0098] Figure 2 This is a flowchart illustrating a seismic data processing method provided in an embodiment of this application. This embodiment uses a computer device as an example for illustrative purposes. See also... Figure 2 The method includes:

[0099] 201. The computer equipment determines the nearest geophone arrangement corresponding to multiple shot points from the seismic data of the target area based on the distance between the shot point and the geophone arrangement. The nearest geophone arrangement corresponding to any shot point is the geophone arrangement that is closest to the shot point among the multiple geophone arrangements corresponding to that shot point. The target area includes multiple sub-regions with different surface types, and multiple shot points are distributed in each sub-region.

[0100] In some embodiments, the computer device determines the nearest geophone arrangements corresponding to multiple shot points from seismic data of a target area based on the distance between shot point and geophone arrangement. This includes: for any shot point in the target area, obtaining the distance between the shot point and each geophone arrangement of that shot point, and determining the geophone arrangement corresponding to the minimum distance as the nearest geophone arrangement for that shot point. The distance between the shot point and the geophone arrangement can be the perpendicular distance between the shot point and the geophone arrangement.

[0101] Step 201 is the same as step 101 above, and will not be described in detail here.

[0102] 202. For each of the multiple shot points, the computer equipment selects multiple seismic data segments of equal time intervals from the seismic data acquired from the nearest receivers corresponding to the shot point in chronological order; based on each seismic data segment, it determines the number of strong energy channels corresponding to the shot point in the multiple time periods.

[0103] The duration of a seismic data segment can be any duration, such as 200 milliseconds, 300 milliseconds, etc., and this embodiment does not limit this. The time interval between multiple seismic data segments can be any time interval, such as 1000 milliseconds, and this embodiment does not limit the time interval.

[0104] For example, for any shot point, the computer device selects the seismic data segments from the 1500-1700 ms, the 2500-2700 ms, and the 3500-3700 ms from the seismic data acquired from the nearest receiver array corresponding to that shot point.

[0105] In this embodiment, the number of high-energy channels refers to the number of high-energy seismic channels. Since the energy intensity is determined by the amplitude, it is possible to determine whether a seismic channel is a high-energy seismic channel based on its amplitude.

[0106] In some embodiments, the computer device determines the number of high-energy channels corresponding to a shot point in multiple time periods based on each seismic data segment, including: for each seismic data segment, obtaining the amplitude of multiple seismic channels formed by the arrangement of the shot point and the nearest receiver point based on the seismic data segment, and determining the number of high-energy channels corresponding to the shot point based on the amplitude of the multiple seismic channels. For example, when the amplitude of a seismic channel is greater than a first amplitude threshold, the seismic channel is determined to be a high-energy seismic channel, and the number of high-energy channels is the number of seismic channels with amplitudes greater than the first amplitude threshold. The first amplitude threshold can be any value, and this application embodiment does not limit the first amplitude threshold. Optionally, the first amplitude threshold is a preset value; alternatively, the first amplitude threshold is an empirical value.

[0107] Assuming the seismic data segment is recorded as x, the subcorrelation function of this seismic data segment x can be expressed as:

[0108] r xx (τ)=E[x n x n+τ ];

[0109] Where, r xx (τ) represents the sub-correlation of a seismic data segment, E is the energy function, and x n Let x represent the seismic data at time n in the seismic data segment. n+τ This represents the earthquake data at time n+τ in the earthquake data segment.

[0110] Although the autocorrelation function r xx The waveform of (τ) appears to have no direct relationship with the waveform of the seismic data segment x, but the autocorrelation function r xx The autocorrelation function (τ) is related to the frequency and amplitude contained in the seismic data segment. Therefore, the characteristics of the autocorrelation function reflect the energy and frequency characteristics of the seismic data segment to a certain extent. According to the theory of stationary random signal analysis, the autocorrelation function is completely determined by its spectrum, which in turn is determined by the amplitude spectrum of the seismic data segment. In other words, the energy spectrum of the seismic data segment is the spectrum of the autocorrelation function. Therefore, computer equipment can obtain the amplitude of each seismic trace through autocorrelation processing. In some embodiments, the computer equipment determines the number of strong energy traces corresponding to the shot point in multiple time periods based on each seismic data segment, including: for each seismic data segment, performing autocorrelation processing on the seismic data segment to obtain the amplitudes of multiple seismic traces formed by the shot point and the nearest receiver, and determining the number of strong energy traces corresponding to the shot point based on the amplitudes of the multiple seismic traces.

[0111] Optionally, the computer device determines the number of high-energy traces corresponding to the shot point based on the amplitudes of multiple seismic traces, including: the computer device normalizes the amplitudes of the multiple seismic traces to obtain reference amplitudes corresponding to the multiple seismic traces; if the reference amplitude of a seismic trace is greater than a second amplitude threshold, then the seismic trace is determined to be a high-energy seismic trace; if the reference amplitude of a seismic trace is not greater than the second amplitude threshold, then the seismic trace is determined to be a non-high-energy seismic trace; the number of high-energy seismic traces is counted to obtain the number of high-energy traces.

[0112] The second amplitude threshold can be any value between 0 and 1, such as 0.5. This application embodiment does not limit the second amplitude threshold.

[0113] 203. The computer equipment determines the surface type corresponding to the shot point based on the variation rules of the high energy channel number of the shot point in different time periods. The surface type corresponding to the shot point is used to indicate the surface type of the location of the shot point.

[0114] In this embodiment, if the high-energy trace number at any shot point varies significantly over different time periods, the relationship between the high-energy trace number and noise is strong; conversely, if the high-energy trace number at any shot point varies only slightly over different time periods, the relationship between the high-energy trace number and noise is weak. Since noise is strongly correlated with land surface type, the land surface type can be determined based on the strength of the relationship between the high-energy trace number and noise.

[0115] In some embodiments, the variation rule of the high-energy channel number in different time periods is exemplified by the variation rule of the high-energy channel number in the first time period, the second time period, and the third time period. The computer device determines the surface type corresponding to the shot point based on the variation rule of the high-energy channel number in different time periods, including: obtaining the ratio of the high-energy channel number corresponding to the shot point in the first time period to the high-energy channel number corresponding to the shot point in the second time period, obtaining a first ratio; obtaining the ratio of the high-energy channel number corresponding to the shot point in the second time period to the high-energy channel number corresponding to the shot point in the third time period, obtaining a second ratio, wherein the first time period, the second time period, and the third time period are arranged in chronological order; determining the difference between the first ratio and the second ratio as a first relationship coefficient, the relationship coefficient being used to represent the strength of the relationship between the high-energy channel number and the noise; and determining the surface type corresponding to the first relationship coefficient as the surface type corresponding to the shot point based on the first relationship coefficient and the correspondence between the relationship coefficient and the surface type.

[0116] The first, second, and third time periods are arranged in chronological order. When collecting seismic data, the receivers first collect seismic wave signals reflected from shallow layers and then from deep layers. Therefore, the number of strong energy channels corresponding to the shot points in the first, second, and third time periods reflects the change in the number of strong energy channels from shallow to deep strata, and thus reflects the stratum type, that is, the surface type.

[0117] In the correspondence between the relationship coefficients and the land surface types, one land surface type can correspond to one or more relationship coefficients, or it can correspond to a range of relationship coefficients. This application does not limit the correspondence.

[0118] 204. The computer equipment determines the number of high-energy channels corresponding to each shot point. The number of high-energy channels corresponding to each shot point is the sum of the number of high-energy channels corresponding to each shot point in different time periods.

[0119] Steps 202 to 203 above involved dividing the seismic data into multiple data segments to determine the pattern of high-energy trace count changes over time and further identify the surface type, thus determining the high-energy trace count corresponding to each segment. Steps 204 to 205, however, are for dividing the target area into different surface zones. Therefore, it is unnecessary to divide the seismic data into multiple segments; the high-energy trace count for each shot point can be directly determined. This high-energy trace count is the sum of the high-energy trace counts for each shot point at different time periods.

[0120] In step 204 above, when determining the number of strong energy traces corresponding to each shot point, the number of strong energy traces corresponding to the shot point in multiple time periods determined in step 202 above can be added together, or the seismic data of the shot point can be directly processed as shown in step 202 for the seismic data fragment to obtain the number of strong energy traces corresponding to the shot point. This application embodiment does not limit this.

[0121] 205. The computer equipment readjusts the partitioning of different surfaces in the target area for each shot point in each sub-region, so that the difference in the number of high energy channels corresponding to different shot points in the adjusted sub-regions does not exceed the high energy channel threshold.

[0122] In some embodiments, shot points specifically located in a certain surface type can be identified first. The high-energy channel number corresponding to this shot point is used as a reference value, and the locations of other shot points with high-energy channel numbers similar to the reference value are all classified into that surface type. The computer device, based on the high-energy channel numbers corresponding to each shot point in each sub-region, readjusts the partitioning of different surfaces in the target area to obtain multiple adjusted sub-regions, including: for any sub-region, determining the high-energy channel number corresponding to a reference shot point in the sub-region as a reference channel number; based on the high-energy channel numbers and reference channel numbers corresponding to each shot point in each sub-region, identifying shot points whose difference between the high-energy channel number and the reference channel number does not exceed a high-energy channel number threshold; and based on the reference shot points and the identified shot points, determining the adjusted sub-regions, where the adjusted sub-regions include the reference shot points and the identified shot points.

[0123] Optionally, the method for determining the reference firing point includes any of the following: determining the firing point located at the center of the sub-region as the reference firing point; determining the firing point closest to the center of the sub-region as the reference firing point; displaying the firing point distribution interface of the target area, the firing point distribution interface including multiple firing points distributed in the target area; in response to the selection operation of any firing point in the firing point distribution interface, determining the firing point as the reference firing point of the sub-region where the firing point is located.

[0124] 206. For any adjusted sub-region, the computer equipment determines the surface type of the adjusted sub-region based on the surface type corresponding to the shot points in the adjusted sub-region; based on multiple adjusted sub-regions and the surface types of multiple adjusted sub-regions, the seismic data of the target region is differentially denoised to obtain denoised seismic data.

[0125] The computer equipment determines the surface type of the adjusted sub-region based on the surface type corresponding to the shot points in the adjusted sub-region, that is, it uses the surface type corresponding to the shot points in the adjusted sub-region as the surface type of the adjusted sub-region.

[0126] In some embodiments, sub-regions with different surface types require processing with different noise suppression parameters. The computer device performs differential denoising on the seismic data of the target area based on multiple adjusted sub-regions and their surface types, obtaining denoised seismic data. This includes: the computer device determining the corresponding noise suppression parameter based on the correspondence between surface type and noise suppression parameter and the surface type of the adjusted sub-region, and then using this noise suppression parameter to denoise the adjusted sub-region.

[0127] The seismic data processing method provided in this application takes into account the different energy losses of seismic waves propagating on different types of surfaces. Therefore, the target area is divided into zones according to the number of strong energy traces of shot points at different locations in the target area. This zoning is consistent with the energy loss of seismic waves propagating on different types of surfaces. Therefore, this zoning is more accurate, and thus it can more accurately perform differential denoising on seismic data, thereby improving the denoising effect of seismic data.

[0128] Some exploration work is primarily conducted on desert and Gobi surfaces. Deserts are mainly composed of aeolian dunes with complex surface structures, significant lateral variations, and well-developed high-energy noise, which greatly impacts the signal-to-noise ratio of seismic data. The surface structure makes fine noise zoning difficult, significantly affecting noise suppression and deconvolution processing. The zoning method provided in this application's embodiments effectively distinguishes the noise development range and suppresses noise in seismic data (such as…). Figure 3 As shown in the figure, the left side is the seismic data before denoising, and the right side is the seismic data after denoising. This improves the quality of the denoised seismic data and lays the foundation for subsequent processing.

[0129] Figure 4 This is a schematic diagram of the structure of a seismic data processing device provided in an embodiment of this application, as shown below. Figure 4 As shown, the device includes:

[0130] The first determining module 401 is used to determine the nearest geophone arrangement corresponding to multiple shot points from the seismic data of the target area based on the distance between the arrangement of shot points and geophone points. The nearest geophone arrangement corresponding to any shot point is the arrangement of geophone points that is closest to the shot point among the multiple geophone arrangements corresponding to the shot point. The target area includes multiple sub-areas with different surface types, and multiple shot points are distributed in each sub-area.

[0131] The second determining module 402 is used to determine the number of high-energy channels corresponding to each of the multiple shot points based on the seismic data acquired from the nearest receiver array corresponding to the shot point. The number of high-energy channels is the number of seismic channels with energy intensity greater than the intensity threshold. One seismic channel corresponds to one receiver array and the shot point corresponding to the receiver array.

[0132] The adjustment module 403 is used to readjust the partitions of different surfaces in the target area based on the number of high energy channels corresponding to each shot point in each sub-region, so as to obtain multiple adjusted sub-regions, so that the difference in the number of high energy channels corresponding to different shot points in the adjusted sub-regions does not exceed the high energy channel threshold.

[0133] The denoising module 404 is used to perform differential denoising on the seismic data of the target area based on multiple adjusted sub-regions to obtain denoised seismic data.

[0134] In one possible implementation, the adjustment module 403 is used to, for any sub-region, determine the high-energy channel number corresponding to the reference shot point in the sub-region as the reference channel number; based on the high-energy channel number and the reference channel number corresponding to each shot point in each sub-region, determine the shot points whose difference between the high-energy channel number and the reference channel number does not exceed the high-energy channel number threshold; and based on the reference shot point and the determined shot points, determine the adjusted sub-region, the adjusted sub-region including the reference shot point and the determined shot points.

[0135] like Figure 5 As shown, in one possible implementation, the device further includes a third determining module 405, which is configured to point to any of the following:

[0136] The firing point located at the center of the sub-region is designated as the reference firing point;

[0137] The firing point closest to the center in the sub-region is designated as the reference firing point;

[0138] The target area's shot point distribution interface is displayed, which includes multiple shot points distributed throughout the target area. In response to the selection of any shot point in the shot point distribution interface, the shot point is designated as the reference shot point for the sub-area where the shot point is located.

[0139] In one possible implementation, the second determining module 402 is used to perform autocorrelation processing on the seismic data acquired by the nearest geophone array corresponding to each of the multiple shot points to obtain the amplitude of multiple seismic traces formed by the shot point and the nearest geophone array; and to determine the number of high-energy traces corresponding to the shot point based on the amplitude of the multiple seismic traces.

[0140] In one possible implementation, the device further includes:

[0141] The fourth determining module 406 is used to select multiple seismic data segments of equal time intervals from the seismic data acquired from the nearest receivers corresponding to each of the multiple shot points in chronological order; based on each seismic data segment, determine the number of high energy channels corresponding to the shot point in the multiple time periods; and based on the variation rules of the number of high energy channels of the shot point in different time periods, determine the surface type corresponding to the shot point, and the surface type corresponding to the shot point is used to indicate the surface type at the location of the shot point.

[0142] The fifth determining module 407 is used to determine the surface type of any adjusted sub-region based on the surface type corresponding to the shot point in the adjusted sub-region.

[0143] The denoising module 404 is used to perform differential denoising on the seismic data of the target area based on multiple adjusted sub-regions and the surface types of multiple adjusted sub-regions, so as to obtain denoised seismic data.

[0144] In one possible implementation, the fourth determining module 406 is used to obtain the ratio of the number of strong energy channels corresponding to the shot point in the first time period to the number of strong energy channels corresponding to the shot point in the second time period, to obtain a first ratio; obtain the ratio of the number of strong energy channels corresponding to the shot point in the second time period to the number of strong energy channels corresponding to the shot point in the third time period, to obtain a second ratio, wherein the first time period, the second time period, and the third time period are arranged in chronological order; the difference between the first ratio and the second ratio is determined as a first relation coefficient, which is used to represent the strength of the relationship between the number of strong energy channels and the noise; based on the first relation coefficient and the correspondence between the relation coefficient and the surface type, the surface type corresponding to the first relation coefficient is determined as the surface type corresponding to the shot point.

[0145] It should be noted that the earthquake data processing apparatus provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer equipment can be divided into different functional modules to complete all or part of the functions described above. In addition, the earthquake data processing apparatus and the earthquake data processing method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0146] Optionally, the computer device is provided as a terminal. Figure 6 This is a structural block diagram of a terminal 600 provided in an embodiment of this application. The terminal 600 includes a processor 601 and a memory 602.

[0147] Processor 601 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 601 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 601 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 601 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 601 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0148] The memory 602 may include one or more computer-readable storage media, which may be non-transitory. The memory 602 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 602 are used to store at least one program code, which is executed by the processor 601 to implement the seismic data processing method provided in the method embodiments of this application.

[0149] In some embodiments, the terminal 600 may also optionally include a peripheral device interface 603 and at least one peripheral device. The processor 601, memory 602, and peripheral device interface 603 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 603 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of the following: a radio frequency circuit 604, a display screen 605, a camera 606, an audio circuit 607, a positioning component 608, and a power supply 609.

[0150] Peripheral interface 603 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 601 and memory 602. In some embodiments, processor 601, memory 602 and peripheral interface 603 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 601, memory 602 and peripheral interface 603 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0151] Display screen 605 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 605 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 601 for processing. In this case, display screen 605 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 605, which serves as the front panel of terminal 600; in other embodiments, there may be at least two display screens, respectively disposed on different surfaces of terminal 600 or in a folded design; in still other embodiments, display screen 605 may be a flexible display screen, disposed on a curved or folded surface of terminal 600. Furthermore, display screen 605 may be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. Display screen 605 may be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0152] Power supply 609 is used to supply power to the various components in terminal 600. Power supply 609 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 609 includes a rechargeable battery, the rechargeable battery can support wired or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0153] Those skilled in the art will understand that Figure 6 The structure shown does not constitute a limitation on terminal 600, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0154] Figure 7This is a schematic diagram of a server structure provided in an embodiment of this application. The server 700 can vary significantly due to different configurations or performance. It may include one or more Central Processing Units (CPUs) 701 and one or more memories 702. The memory 702 stores at least one line of program code, which is loaded and executed by the processor 701 to implement the methods provided in the various method embodiments described above. Of course, the server may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The server may also include other components for implementing device functions, which will not be elaborated upon here.

[0155] The server 700 is used to execute the steps performed by the server in the above method embodiments.

[0156] This application also provides a computer-readable storage medium storing at least one piece of program code, which is loaded and executed by a processor to implement the seismic data processing method as described in any of the above implementations.

[0157] This application also provides a computer program product, which includes at least one piece of program code that is loaded and executed by a processor to implement the seismic data processing method as described in any of the above implementations.

[0158] In some embodiments, the computer program involved in the present application embodiments may be deployed and executed on a computer device, or executed on multiple computer devices located in one location, or executed on multiple computer devices distributed in multiple locations and interconnected through a communication network. Multiple computer devices distributed in multiple locations and interconnected through a communication network may constitute a blockchain system.

[0159] The above are merely optional embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for processing seismic data, characterized in that, The method includes: Based on the distance between the shot points and receiver arrangements, the nearest receiver arrangements corresponding to multiple shot points are determined from the seismic data of the target area. The nearest receiver arrangement corresponding to any shot point is the receiver arrangement that is closest to the shot point among the multiple receiver arrangements corresponding to the shot point. The target area includes multiple sub-areas with different surface types, and multiple shot points are distributed in each sub-area. For each of the plurality of shot points, based on the seismic data acquired from the nearest geophone array corresponding to the shot point, the number of high-energy channels corresponding to the shot point is determined. The number of high-energy channels is the number of seismic channels with energy intensity greater than an intensity threshold. One seismic channel corresponds to one geophone in the geophone array and the shot point corresponding to the geophone array. For any sub-region, the number of high-energy channels corresponding to the reference shot point in the sub-region is determined as the reference channel number; Based on the number of high-energy channels corresponding to each shot point in each sub-region and the reference channel number, shot points whose difference between the number of high-energy channels and the reference channel number does not exceed the high-energy channel number threshold are determined. Based on the reference firing point and the determined firing point, an adjusted sub-region is determined, wherein the adjusted sub-region includes the reference firing point and the determined firing point. Based on multiple adjusted sub-regions, the seismic data of the target region is differentially denoised to obtain denoised seismic data.

2. The method according to claim 1, characterized in that, The method further includes any one of the following: The shot point located at the center of the sub-region is determined as the reference shot point; The shot point closest to the center in the sub-region is determined as the reference shot point; The target area is displayed as a gun point distribution interface, which includes multiple gun points distributed in the target area; in response to the selection operation of any gun point in the gun point distribution interface, the gun point is determined as a reference gun point in the sub-area where the gun point is located.

3. The method according to claim 1, characterized in that, For each of the plurality of shot points, the number of high-energy traces corresponding to the shot point is determined based on the seismic data acquired from the nearest receiver array corresponding to the shot point, including: For each of the plurality of shot points, the seismic data acquired by the nearest geophone array corresponding to the shot point are subjected to autocorrelation processing to obtain the amplitude of the plurality of seismic traces formed by the shot point and the nearest geophone array. Based on the amplitude of the multiple seismic traces, the number of high-energy traces corresponding to the shot point is determined.

4. The method according to claim 1, characterized in that, The method further includes: For each of the plurality of shot points, multiple seismic data segments of equal time intervals are selected from the seismic data acquired from the nearest receivers corresponding to the shot point in chronological order; based on each seismic data segment, the number of high-energy channels corresponding to the shot point in the multiple time periods is determined; based on the variation rules of the number of high-energy channels of the shot point in different time periods, the surface type corresponding to the shot point is determined, and the surface type corresponding to the shot point is used to indicate the surface type at the location of the shot point; For any adjusted sub-region, the surface type of the adjusted sub-region is determined based on the surface type corresponding to the shot point in the adjusted sub-region. The process involves differentially denoising the seismic data of the target region based on multiple adjusted sub-regions to obtain denoised seismic data, including: Based on the multiple adjusted sub-regions and the surface types of the multiple adjusted sub-regions, differential denoising is performed on the seismic data of the target region to obtain the denoised seismic data.

5. The method according to claim 4, characterized in that, The method of determining the surface type corresponding to the shot point based on the variation rules of the high-energy channel number of the shot point in different time periods includes: The ratio of the number of high-energy channels corresponding to the gun point in the first time period to the number of high-energy channels corresponding to the gun point in the second time period is obtained to obtain the first ratio. The ratio of the number of strong energy channels corresponding to the gun point in the second time period to the number of strong energy channels corresponding to the gun point in the third time period is obtained to obtain the second ratio. The first time period, the second time period, and the third time period are arranged in chronological order from front to back. The difference between the first ratio and the second ratio is determined as the first relationship coefficient, which is used to represent the strength of the relationship between the high energy channel number and the noise. Based on the first relation coefficient and the correspondence between the relation coefficient and the surface type, the surface type corresponding to the first relation coefficient is determined as the surface type corresponding to the shot point.

6. A seismic data processing device, characterized in that, The device includes: The first determining module is used to determine the nearest geophone arrangement corresponding to multiple shot points from the seismic data of the target area based on the distance between the arrangement of shot points and geophone points. The nearest geophone arrangement corresponding to any shot point is the arrangement of geophone points that is closest to the shot point among the multiple geophone arrangements corresponding to the shot point. The target area includes multiple sub-regions with different surface types, and multiple shot points are distributed in each sub-region. The second determining module is used to determine the number of high-energy channels corresponding to each of the plurality of shot points based on the seismic data acquired by the nearest geophone arrangement corresponding to the shot point. The number of high-energy channels is the number of seismic channels with energy intensity greater than an intensity threshold. One seismic channel corresponds to one geophone in the geophone arrangement and the shot point corresponding to the geophone arrangement. An adjustment module is configured to, for any sub-region, determine the high-energy channel number corresponding to a reference shot point in the sub-region as a reference channel number; based on the high-energy channel number corresponding to each shot point in each sub-region and the reference channel number, determine shot points whose difference between the high-energy channel number and the reference channel number does not exceed a high-energy channel number threshold; and based on the reference shot points and the determined shot points, determine an adjusted sub-region, wherein the adjusted sub-region includes the reference shot point and the determined shot points. The denoising module is used to perform differential denoising on the seismic data of the target area based on multiple adjusted sub-regions to obtain denoised seismic data.

7. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one piece of program code, which is loaded and executed by the processor to implement the seismic data processing method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to implement the seismic data processing method as described in any one of claims 1 to 5.

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