Seismic data processing method, device, computer equipment and storage medium

Abstract

The present application provides a seismic data processing method, device, computer equipment and storage medium, which belongs to the field of geophysical exploration technology. The method includes: obtaining seismic data and reference seismic data of a target plot, wherein the seismic data includes seismic data of multiple seismic channels, and the reference seismic data is seismic data obtained by equally weighted addition of the seismic data of the multiple seismic channels; for any seismic channel, performing local correlation processing on the seismic data of the seismic channel and the reference seismic data to obtain the stacking weight of the seismic channel; based on the stacking weights of the multiple seismic channels, performing weighted summation on the seismic data of the multiple seismic channels to obtain the post-stack seismic data of the target plot. The above technical solution can reduce the influence of noise on the seismic data addition process, improve the signal-to-noise ratio of the post-stack seismic data, and thus improve the imaging quality of the post-stack seismic data.

Description

Technical Field

[0001] The present application relates to the field of geophysical exploration technology, and in particular to a seismic data processing method, device, computer equipment and storage medium. Background Art

[0002] Seismic exploration involves artificially stimulating seismic waves, recording the seismic data as they propagate through strata, and processing this data to investigate the properties of subsurface rocks and geological structures. During seismic exploration, receivers often receive interference noise from both the earthquake source and external sources. While various noise suppression methods can attenuate this interference noise, the residual noise after suppression can sometimes severely impact the imaging quality of the seismic data received at the receivers. Therefore, improving the imaging quality of seismic data remains a pressing technical challenge.

[0003] In related technologies, stacking imaging is often used to suppress interfering noise in seismic data. Currently, the most common stacking imaging method is the linear common center point stacking method. This method first selects seismic traces with a common center point from the seismic data acquired at different shot points and different receiver points during seismic exploration. The seismic data corresponding to these traces are then equally weighted and added together. Finally, imaging is performed based on the added seismic data to produce a seismic stack profile. The center point is the midpoint between the shot point and the receiver point.

[0004] However, in the addition process of the above method, some non-stationary noise and coherent noise in the seismic data will inevitably remain on the seismic stacking section, resulting in a decrease in the imaging quality of the added seismic data. Summary of the Invention

[0005] The present invention provides a method, apparatus, computer device, and storage medium for processing seismic data, which can reduce the impact of noise on the seismic data addition process, improve the signal-to-noise ratio of post-stack seismic data, and thus improve the imaging quality of post-stack seismic data. The technical solution is as follows:

[0006] In one aspect, a method for processing seismic data is provided, the method comprising:

[0007] Acquire seismic data and reference seismic data of a target plot, wherein the seismic data includes seismic data of a plurality of seismic channels, and the reference seismic data is seismic data obtained by equally weighted addition of the seismic data of the plurality of seismic channels;

[0008] For any seismic trace, performing local correlation processing on the seismic data of the seismic trace and the reference seismic data to obtain a stacking weight of the seismic trace, wherein the local correlation processing is used to determine a degree of similarity between the seismic data of the seismic trace and the reference seismic data, and the stacking weight is positively correlated with the degree of similarity;

[0009] Based on the stacking weights of the multiple seismic traces, weighted summation is performed on the seismic data of the multiple seismic traces to obtain post-stack seismic data of the target block.

[0010] In another aspect, a seismic data processing device is provided, comprising:

[0011] an acquisition module, configured to acquire seismic data of a target land parcel and reference seismic data, wherein the seismic data includes seismic data of a plurality of seismic channels, and the reference seismic data is seismic data obtained by performing equal-weighted addition of the seismic data of the plurality of seismic channels;

[0012] a data processing module configured to perform, for any seismic trace, local correlation processing on the seismic data of the seismic trace and the reference seismic data to obtain a stacking weight of the seismic trace, wherein the local correlation processing is used to determine a degree of similarity between the seismic data of the seismic trace and the reference seismic data, and the stacking weight is positively correlated with the degree of similarity;

[0013] A calculation module is used to perform weighted summation on the seismic data of the multiple seismic traces based on the stacking weights of the multiple seismic traces to obtain post-stack seismic data of the target block.

[0014] In some embodiments, the processing module includes:

[0015] a data processing unit configured to perform local correlation processing on the seismic data of any seismic trace and the reference seismic data to obtain a correlation coefficient of the seismic trace, wherein the correlation coefficient indicates a degree of similarity between the seismic data of the seismic trace and the reference seismic data;

[0016] A determining unit is configured to determine the superposition weight based on the correlation coefficient, where the superposition weight is positively correlated with the correlation coefficient.

[0017] In some embodiments, the seismic trace includes a plurality of sampling points;

[0018] The data processing unit includes:

[0019] a sampling subunit, configured to sample the seismic data of the seismic trace and the reference seismic data at any sampling point in the seismic trace based on the sampling time of the sampling point and the length of a time window, respectively, to obtain the seismic data and the reference seismic data within the time window, wherein the center point of the time window is the sampling time of the sampling point;

[0020] a data processing subunit, configured to perform local correlation processing on the seismic data within the time window and the reference seismic data within the time window to obtain correlation coefficients of the sampling points;

[0021] The operator unit is configured to average the correlation coefficients of the plurality of sampling points to obtain the correlation coefficient of the seismic trace.

[0022] In some embodiments, the data processing subunit is further used to perform time smoothing on the correlation coefficients of the multiple sampling points in any seismic trace according to the time sequence of the multiple sampling points in the seismic trace to obtain the intermediate correlation coefficients of the multiple sampling points, and the time smoothing is used to smooth the correlation coefficients of adjacent sampling points in the multiple sampling points; and to perform spatial smoothing on the intermediate correlation coefficients of the multiple sampling points in the multiple seismic traces according to the arrangement order of the multiple seismic traces, and the spatial smoothing is used to smooth the intermediate correlation coefficients of the multiple sampling points with the same sampling time in the multiple seismic traces.

[0023] In some embodiments, the determining unit includes:

[0024] a first determining subunit, configured to determine the stacking weight based on the correlation coefficient, the reference correlation coefficient, and a control parameter when the correlation coefficient is less than a reference correlation coefficient, wherein the reference correlation coefficient is used to indicate a reference similarity between the seismic data of the seismic trace and the reference seismic data, and the control parameter is used to indicate an influence of the correlation coefficient on the stacking weight, wherein the stacking weight is positively correlated with the correlation coefficient and the control parameter, and negatively correlated with the reference correlation coefficient;

[0025] The second determining subunit is configured to determine the superposition weight based on the correlation coefficient and the control parameter when the correlation coefficient is not less than the reference correlation coefficient, wherein the superposition weight is positively correlated with the correlation coefficient and the control parameter.

[0026] In some embodiments, the apparatus further comprises:

[0027] The computing module is further configured to perform equal-weighted addition on the seismic data of the plurality of seismic channels to obtain reference stacked seismic data of the target land parcel;

[0028] an evaluation module, configured to perform a quality evaluation on the reference stacked seismic data to obtain a quality evaluation result of the reference stacked seismic data, wherein the quality evaluation result is used to indicate a signal-to-noise ratio of the reference stacked seismic data;

[0029] A noise reduction module is used to reduce noise on the reference stacked seismic data based on the quality assessment result to obtain the reference seismic data.

[0030] On the other hand, a computer device is provided, which includes a processor and a memory, wherein the memory is used to store at least one computer program, and the at least one computer program is loaded and executed by the processor to implement the seismic data processing method in the embodiment of the present application.

[0031] On the other hand, a computer-readable storage medium is provided, in which at least one computer program is stored. The at least one computer program is loaded and executed by a processor to implement the seismic data processing method as in the embodiment of the present application.

[0032] On the other hand, a computer program product is provided, comprising a computer program, wherein the computer program is executed by a processor to implement the seismic data processing method provided in the embodiments of the present application.

[0033] The present invention provides a seismic data processing method that determines the stacking weights for adding the seismic data of the multiple seismic traces by analyzing the similarity between the seismic data of multiple seismic traces in the seismic data of a target plot and the reference seismic data of the target plot. By reducing the stacking weights of the seismic data of seismic traces with low similarity to the reference seismic data and increasing the stacking weights of the seismic data with high similarity, the influence of noise on the seismic data addition process can be reduced, the signal-to-noise ratio of the post-stack seismic data can be improved, and thus the imaging quality of the post-stack seismic data can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0035] Figure 1 Schematic diagram of an implementation environment of a seismic data processing method provided according to an embodiment of the present application;

[0036] Figure 2 is a flow chart of a seismic data processing method provided according to an embodiment of the present application;

[0037] Figure 3 is a flowchart of another seismic data processing method provided according to an embodiment of the present application;

[0038] Figure 4 is a schematic diagram of reference stacked seismic data provided according to an embodiment of the present application;

[0039] Figure 5 is a schematic diagram of reference seismic data provided according to an embodiment of the present application;

[0040] Figure 6 is a schematic diagram of post-stack seismic data provided according to an embodiment of the present application;

[0041] Figure 7 is a block diagram of a seismic data processing device provided according to an embodiment of the present application;

[0042] Figure 8 is a block diagram of another seismic data processing device provided according to an embodiment of the present application;

[0043] Figure 9 This is a structural block diagram of a terminal provided according to an embodiment of the present application;

[0044] Figure 10 It is a structural diagram of a server provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0046] In this application, the terms "first", "second", etc. are used to distinguish identical or similar items with substantially the same effects and functions. It should be understood that there is no logical or temporal dependency between "first", "second", and "nth", nor is there any limitation on the quantity and execution order.

[0047] In the present application, the term "at least one" means one or more, and the term "plurality" means two or more.

[0048] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the earthquake data and reference earthquake data involved in this application were obtained with full authorization.

[0049] The seismic data processing method provided in the embodiment of the present application can be applied to a computer device. In some embodiments, the computer device is a terminal or a server. The following first takes the computer device as an example to introduce the implementation environment of the seismic data processing method provided in the embodiment of the present application. Figure 1 Schematic diagram of an implementation environment of a seismic data processing method provided in accordance with an embodiment of the present application. Figure 1 , the implementation environment includes a source 101, a detector 102 and a terminal 103.

[0050] The seismic source 101 is used to excite seismic waves in any direction below the ground from the shot point. The geophone 102 is used to collect seismic data of the seismic waves propagating in the stratum at the geophone point.

[0051] Seismic source 101 may generally refer to one of a plurality of seismic sources. This embodiment uses seismic source 101 as an example. Those skilled in the art will appreciate that the number of seismic sources may be greater or lesser. For example, there may be a few seismic sources, or dozens, hundreds, or even more. This embodiment of the application does not limit the number of seismic sources or the type of device.

[0052] The detector 102 may generally refer to one of multiple detectors. This embodiment uses the detector 102 as an example. Those skilled in the art will appreciate that the number of detectors may be greater or lesser. For example, there may be a few detectors, or dozens, hundreds, or even more. This embodiment does not limit the number or type of detectors.

[0053] In some embodiments, terminal 103 is at least one of a smartphone, a desktop computer, a handheld computer, and a portable computer. An application may be installed and run on terminal 103, and the application is used to process seismic data of a target parcel to obtain post-stack seismic data of the target parcel. A user may log in to the application through terminal 103 to obtain post-stack seismic data of the target parcel. The application is associated with geophone 102, and geophone 102 provides seismic data of the target parcel to terminal 103. Terminal 103 may be connected to geophone 102 via a wireless network or a wired network.

[0054] Terminal 103 may generally refer to one of multiple terminals. This embodiment uses terminal 103 as an example. Those skilled in the art will appreciate that the number of terminals may be greater or lesser. For example, there may be a few terminals, or dozens, hundreds, or even more. This embodiment of the application does not limit the number or device type of terminals.

[0055] Figure 2 is a flow chart of a seismic data processing method provided according to an embodiment of the present application, such as Figure 2 As shown, in the embodiment of the present application, the method for processing seismic data is described by taking the execution by a terminal as an example. The method comprises the following steps:

[0056] 201. The terminal obtains seismic data and reference seismic data of a target plot, where the seismic data includes seismic data of multiple seismic channels, and the reference seismic data is seismic data obtained by performing equal-weighted addition on the seismic data of the multiple seismic channels.

[0057] In an embodiment of the present application, the target plot is an underground rock formation having a certain geological structure. Seismic data for the target plot is used to indicate the geological structure of the target plot, and the seismic data includes seismic data from multiple seismic channels. A terminal can obtain the seismic data for the target plot from seismic data collected by a geophone at a detection point, or from a server. After obtaining the seismic data for the target plot, the terminal can perform equal-weighted addition of the seismic data from multiple seismic channels in the seismic data to obtain reference seismic data for the target plot.

[0058] 202. For any seismic channel, the terminal performs local correlation processing on the seismic data of the seismic channel and the reference seismic data to obtain the superposition weight of the seismic channel. The local correlation processing is used to determine the similarity between the seismic data of the seismic channel and the reference seismic data. The superposition weight is positively correlated with the similarity.

[0059] In the embodiment of the present application, since the reference seismic data is obtained by equally weighted addition of seismic data from multiple seismic channels, the seismic data from each seismic channel has a certain degree of similarity with the reference seismic data. For any seismic channel, the terminal performs local correlation processing on the seismic data from that channel and the reference seismic data to determine the degree of similarity between the seismic data from that channel and the reference seismic data. Since the degree of similarity is positively correlated with the stacking weight of the seismic channel, the terminal can determine the weight of the seismic data from that channel when adding data, i.e., the stacking weight of the seismic channel, based on the degree of similarity between the seismic data from that channel and the reference seismic data.

[0060] 203. The terminal performs weighted summation on the seismic data of the multiple seismic channels based on the stacking weights of the multiple seismic channels to obtain post-stack seismic data of the target block.

[0061] In an embodiment of the present application, the seismic data of the target plot includes seismic data of multiple seismic channels, and the seismic data of different seismic channels are different. Generally speaking, the noise content in the seismic data with a high degree of similarity to the reference seismic data is low, and the quality of the seismic data is better. Conversely, the noise content in the seismic data with a low degree of similarity to the reference seismic data is high, and the quality of the seismic data is poor. Therefore, the terminal can better suppress the noise in the seismic data with a low degree of similarity by increasing the stacking weight of the seismic channels with a high degree of similarity and reducing the stacking weight of the seismic channels with a low degree of similarity, thereby reducing the impact of noise on the seismic data addition process. The terminal also has a higher signal-to-noise ratio and better imaging quality by performing weighted summation on the seismic data of multiple seismic channels based on the stacking weights of the multiple seismic channels.

[0062] In an embodiment of the present application, by analyzing the similarity between the seismic data of multiple seismic channels before stacking and the reference seismic data after stacking, the terminal can identify the seismic data of the seismic channels that have a greater impact on the reference seismic data from the seismic data of the multiple seismic channels. Then, based on the stacking weights of the multiple seismic channels determined by the similarity, the seismic data of the multiple seismic channels are added together, which can improve the signal-to-noise ratio and resolution of the post-stack seismic data to a certain extent, and improve the imaging quality. Seismic images with high imaging quality not only lay a good foundation for better interpretation of seismic data in the later stage, but also provide favorable conditions for later seismic wave imaging, attribute extraction, and reservoir development.

[0063] For example, in the field of oil and gas exploration and development, the seismic data processing method provided in the embodiments of this application can be used to process seismic data observed in the field, thereby generating higher-quality seismic images based on the processed post-stack seismic data. By interpreting these high-quality seismic images, the occurrence and structural relationships of underground rock formations can be better restored. During oil and gas exploration, the location of underground reservoirs can be more accurately determined, allowing the identification of favorable oil and gas-bearing areas.

[0064] The present invention provides a seismic data processing method that determines the stacking weights for adding the seismic data of the multiple seismic traces by analyzing the similarity between the seismic data of multiple seismic traces in the seismic data of a target plot and the reference seismic data of the target plot. By reducing the stacking weights of the seismic data of seismic traces with low similarity to the reference seismic data and increasing the stacking weights of the seismic data with high similarity, the influence of noise on the seismic data addition process can be reduced, the signal-to-noise ratio of the post-stack seismic data can be improved, and thus the imaging quality of the post-stack seismic data can be improved.

[0065] Figure 3 is a flow chart of another seismic data processing method provided in an embodiment of the present application. Figure 3As shown, in the embodiment of the present application, the method for processing seismic data is described by taking the execution by a terminal as an example. The method comprises the following steps:

[0066] 301. The terminal obtains seismic data and reference seismic data of a target plot, where the seismic data includes seismic data of multiple seismic channels, and the reference seismic data is seismic data obtained by performing equal-weighted addition on the seismic data of the multiple seismic channels.

[0067] In an embodiment of the present application, the target plot is an underground rock formation with a certain geological structure. The seismic data of the target plot is used to indicate the geological structure of the target plot, and the seismic data includes seismic data of multiple seismic channels. The terminal can obtain the seismic data of the target plot from the seismic data collected by the detector at the detection point, and can also obtain the seismic data of the target plot from the server. After obtaining the seismic data of the target plot, the terminal can perform equal-weighted addition of the seismic data of multiple seismic channels in the seismic data to obtain reference seismic data of the target plot. Optionally, the seismic data of the target plot is seismic data obtained after conventional processing, wherein conventional processing operations refer to a series of necessary seismic data processing such as decompression, static correction, noise suppression, energy compensation, velocity analysis, and deconvolution of the seismic data.

[0068] In some embodiments, the terminal performs a quality assessment on the reference stacked seismic data obtained after equal-weighted addition, and can improve the imaging quality of the reference stacked seismic data based on the assessment results. Accordingly, the terminal performs equal-weighted addition on the seismic data of multiple seismic traces to obtain reference stacked seismic data for the target plot; performs a quality assessment on the reference stacked seismic data to obtain a quality assessment result for the reference stacked seismic data, the quality assessment result being used to indicate the signal-to-noise ratio of the reference stacked seismic data; and based on the quality assessment result, performs noise reduction on the reference stacked seismic data to obtain the reference seismic data. The terminal employs the conventional linear common center point stacking method to perform equal-weighted addition on the seismic data of multiple seismic traces to obtain the reference stacked seismic data. Because the quality assessment result is used to indicate the signal-to-noise ratio of the reference stacked seismic data, the terminal can, based on the quality assessment result, request a quality improvement to improve the signal-to-noise ratio of the stacked seismic data. Based on this quality improvement request, the terminal can select the most appropriate processing method to reduce the noise of the reference stacked seismic data to improve the signal-to-noise ratio of the reference stacked seismic data, thereby obtaining reference seismic data with a higher signal-to-noise ratio and better imaging quality.

[0069] For example, Figure 4 According to a schematic diagram of a reference stacked seismic data provided in an embodiment of the present application, Figure 5 is a schematic diagram of reference seismic data provided according to an embodiment of the present application. Figure 4 and Figure 5 , terminal pair Figure 4The quality assessment of the reference stacked seismic data shown in the figure was carried out. The assessment found that the signal-to-noise ratio of the reference stacked seismic data was low, the random signal noise was serious, and some phase axes were unclear. Therefore, based on the quality assessment result, the terminal can reduce the noise of the reference stacked seismic data and obtain Figure 5 Considering that the noise in the reference stacked seismic data is mainly random interference noise, the terminal can use a random noise attenuation method on the reference stacked seismic data to improve the signal-to-noise ratio of the reference stacked seismic data.

[0070] In some embodiments, the terminal can filter the seismic data of the target plot to improve the signal-to-noise ratio of the seismic data. Alternatively, the terminal can perform energy equalization on the seismic data of the target plot to improve the fidelity of the seismic data. The filtered or energy-equalized seismic data from multiple seismic traces are then equally weighted added to obtain reference stacked seismic data.

[0071] In some embodiments, the terminal can request targeted quality improvements for the reference stacked seismic data based on the exploration objective. For example, when the exploration objective is high-resolution exploration, the terminal may request improved resolution for the reference stacked seismic data; when the exploration objective is high signal-to-noise ratio exploration, the terminal may request improved signal-to-noise ratio for the reference stacked seismic data; and when the exploration objective is small structures, faults, and fractures, the terminal may request improved fidelity for the reference stacked seismic data.

[0072] 302. For any seismic channel, the terminal performs local correlation processing on the seismic data of the seismic channel and the reference seismic data to obtain a correlation coefficient of the seismic channel. The correlation coefficient is used to indicate the degree of similarity between the seismic data of the seismic channel and the reference seismic data.

[0073] In the embodiment of the present application, since the reference seismic data is obtained by equally weighted addition of seismic data from multiple seismic channels, there is a certain degree of similarity between the seismic data of each seismic channel and the reference seismic data. For any seismic channel, the terminal performs local correlation processing on the seismic data of the seismic channel and the reference seismic data to obtain a correlation coefficient for the seismic channel. The correlation coefficient is used to indicate the degree of similarity between the seismic data of the seismic channel and the reference seismic data. The correlation coefficient is positively correlated with the degree of similarity. The larger the correlation coefficient, the higher the degree of similarity between the seismic data of the seismic channel and the reference seismic data, indicating that the seismic data of the seismic channel has a greater degree of influence on the reference seismic data.

[0074] In some embodiments, the terminal can divide multiple seismic channels to obtain multiple CMP (Common Middle Point) channel sets. Each CMP channel set includes multiple seismic channels with a common center point. Then, the terminal divides the seismic data of the multiple seismic channels according to the multiple CMP channel sets to obtain multiple data units. Multiple CMP channel sets correspond one to one to multiple data units. The data unit refers to the minimum processing unit when the terminal processes seismic data. Each data unit includes seismic data of multiple seismic channels with a common center point. The center point is the midpoint between the shot point and the detection point. Accordingly, for any data unit, the terminal can perform local correlation processing on the seismic data of the multiple seismic channels in the data unit with the reference seismic data in turn to obtain correlation coefficients of the multiple seismic channels.

[0075] In some embodiments, a seismic trace includes multiple sampling points, and the terminal can average the correlation coefficients of the multiple sampling points to obtain the correlation coefficient of the seismic trace. Accordingly, for any sampling point in the seismic trace, the terminal samples the seismic data and reference seismic data of the seismic trace based on the sampling time of the sampling point and the length of a time window, obtaining the seismic data and reference seismic data within the time window, with the sampling time of the sampling point being the center point of the time window. The terminal performs local correlation processing on the seismic data and reference seismic data within the time window to obtain the correlation coefficient of the sampling point. The terminal averages the correlation coefficients of the multiple sampling points to obtain the correlation coefficient of the seismic trace. Each seismic trace includes multiple sampling points, each with a different sampling time. For any sampling point, the terminal can use the sampling time of the sampling point as the center point of the time window and sample the seismic data and reference seismic data of the seismic trace to obtain the seismic data and reference seismic data of the seismic trace within the time window. Optionally, the length of the time window is 200 milliseconds, as 200 milliseconds spans one wave group in the temporal direction of the seismic data. A wave group is a combination of reflected waves generated by several closely spaced reflection interfaces. Because the thickness between these interfaces is generally stable or gradually varying, the corresponding reflected waves have stable waveforms, with a certain time interval between each reflection wave. The terminal performs local correlation processing on seismic data with a time window length equal to the window length and reference seismic data to obtain the correlation coefficient for that sampling point. The correlation coefficient for a sampling point indicates the degree of similarity between the seismic data of the seismic trace at that sampling point and the reference seismic data at that sampling point. The terminal averages the correlation coefficients of multiple sampling points to obtain the correlation coefficient for the seismic trace.

[0076] In some embodiments, the server performs local correlation processing on the seismic data within the time window and the reference seismic data within the time window using the following formula 1 to obtain the correlation coefficient of the sampling points.

[0077] Formula 1:

[0078]

[0079] Among them, γ z (t) is the correlation coefficient of the sampling point corresponding to the sampling time t, z is the window length of the time window, x i is the seismic data of the seismic trace sampled at sampling time i, y i is the reference seismic data sampled at sampling time i.

[0080] In some embodiments, the terminal performs smoothing on the correlation coefficients of multiple sampling points to avoid sudden changes in the correlation coefficients of the sampling points. Accordingly, for any seismic trace, the terminal performs temporal smoothing on the correlation coefficients of the multiple sampling points according to the temporal order of the multiple sampling points in the seismic trace to obtain intermediate correlation coefficients of the multiple sampling points. Temporal smoothing is used to smooth the correlation coefficients of adjacent sampling points among the multiple sampling points. The terminal also performs spatial smoothing on the intermediate correlation coefficients of the multiple sampling points in the multiple seismic traces according to the arrangement order of the multiple seismic traces. Spatial smoothing is used to smooth the intermediate correlation coefficients of multiple sampling points with the same sampling time in the multiple seismic traces. Each seismic trace includes multiple sampling points, each with a different sampling time. For any seismic trace, the terminal can perform temporal smoothing on the correlation coefficients of the multiple sampling points according to the temporal order of the multiple sampling points in the seismic trace. That is, the correlation coefficients of the multiple sampling points in each earthquake are smoothed in the temporal direction to avoid sudden changes in the correlation coefficients of adjacent sampling points in the seismic trace. The terminal then spatially smooths the correlation coefficients of sampling points with the same sampling time across multiple seismic traces. This means it smooths the intermediate correlation coefficients of the sampling points obtained after temporal smoothing. Finally, the terminal averages the correlation coefficients of the multiple sampling points obtained after spatial smoothing to obtain the correlation coefficients of the seismic traces.

[0081] 303. The terminal determines a superposition weight based on the correlation coefficient, and the superposition weight is positively correlated with the correlation coefficient.

[0082] In the embodiment of the present application, the correlation coefficient is positively correlated with the stacking weight of the seismic trace. The larger the correlation coefficient of the seismic trace, the greater the stacking weight of the seismic trace, and the greater the similarity between the seismic data of the seismic trace and the reference seismic data. The terminal can determine the weight of the seismic data of the seismic trace when adding data, i.e., the stacking weight of the seismic trace, based on the similarity between the seismic data of the seismic trace indicated by the correlation coefficient and the reference seismic data.

[0083] In some embodiments, the terminal can determine the stacking weight of a seismic trace in different situations by comparing the correlation coefficient of the seismic trace with a reference correlation coefficient. Accordingly, when the correlation coefficient is less than the reference correlation coefficient, the terminal determines the stacking weight based on the correlation coefficient, the reference correlation coefficient, and a control parameter. The reference correlation coefficient indicates the reference similarity between the seismic data of the seismic trace and the reference seismic data, and the control parameter indicates the influence of the correlation coefficient on the stacking weight. The stacking weight is positively correlated with the correlation coefficient and the control parameter, and negatively correlated with the reference correlation coefficient. When the correlation coefficient is not less than the reference correlation coefficient, the terminal determines the stacking weight based on the correlation coefficient and the control parameter. The stacking weight is positively correlated with the correlation coefficient and the control parameter. The reference correlation coefficient indicates the reference similarity between the seismic data of the seismic trace and the reference seismic data. When the correlation coefficient is less than the reference correlation coefficient, the similarity between the seismic data of the seismic trace and the reference seismic data is less than the reference similarity, indicating that the similarity between the seismic data of the seismic trace and the reference seismic data is low. The terminal needs to set the stacking weight of the seismic trace to a smaller value. In this case, the terminal can determine the stacking weight based on the correlation coefficient, the reference correlation coefficient, and the control parameter indicating the influence of the correlation coefficient on the reference weight. The stacking weight is positively correlated with the correlation coefficient and the control parameters, and negatively correlated with the reference correlation coefficient. Similarly, when the correlation coefficient is not less than the reference correlation coefficient, the degree of similarity between the seismic data of the seismic trace and the reference seismic data is high. The terminal needs to set the stacking weight of the seismic trace to a larger value. At this time, the terminal can determine the stacking weight based on the correlation coefficient and the control parameters. The stacking weight is positively correlated with the correlation coefficient and the control parameters. When the degree of similarity is low, the terminal introduces a reference correlation coefficient that is negatively correlated with the stacking weight, which can effectively reduce the stacking weight of the seismic trace, thereby suppressing the noise in the seismic data of the seismic trace and improving the signal-to-noise ratio and imaging quality of the post-stack seismic data.

[0084] In some embodiments, the server determines the stacking weight of the seismic traces based on the correlation coefficient of the seismic traces using the following formula 2.

[0085] Formula 2:

[0086]

[0087] Where w is the stacking weight of the seismic trace, a is the reference correlation coefficient, b is the control parameter, and c is the correlation coefficient of the seismic trace. Optionally, b is 0.5 and a is 0.3.

[0088] 304. The terminal performs weighted summation on the seismic data of the multiple seismic traces based on the stacking weights of the multiple seismic traces to obtain post-stack seismic data of the target block.

[0089] In an embodiment of the present application, the seismic data of the target plot includes seismic data of multiple seismic channels, and the seismic data of different seismic channels are different. Generally speaking, the noise content in the seismic data with a high degree of similarity to the reference seismic data is low, and the quality of the seismic data is better. Conversely, the noise content in the seismic data with a low degree of similarity to the reference seismic data is high, and the quality of the seismic data is poor. Therefore, the terminal can better suppress the noise in the seismic data with a low degree of similarity by increasing the stacking weight of the seismic channels with a high degree of similarity and reducing the stacking weight of the seismic channels with a low degree of similarity, thereby reducing the impact of noise on the seismic data addition process. The terminal also has a higher signal-to-noise ratio and better imaging quality by performing weighted summation on the seismic data of multiple seismic channels based on the stacking weights of the multiple seismic channels.

[0090] For example, Figure 6 is a schematic diagram of post-stack seismic data provided according to an embodiment of the present application. Figure 4 The reference stacked seismic data shown and Figure 6 It can be seen from the post-stack seismic data shown that, compared with the reference stacked seismic data obtained after equal-weighted addition, the seismic data processing method provided in the embodiment of the present application can greatly improve the signal-to-noise ratio and resolution of the post-stack seismic data, thereby improving the imaging quality of the post-stack seismic data.

[0091] In an embodiment of the present application, by analyzing the similarity between the seismic data of multiple seismic channels before stacking and the reference seismic data after stacking, the terminal can identify the seismic data of the seismic channels that have a greater impact on the reference seismic data from the seismic data of the multiple seismic channels. Then, based on the stacking weights of the multiple seismic channels determined by the similarity, the seismic data of the multiple seismic channels are added together, which can improve the signal-to-noise ratio and resolution of the post-stack seismic data to a certain extent, and improve the imaging quality. Seismic images with high imaging quality not only lay a good foundation for better interpretation of seismic data in the later stage, but also provide favorable conditions for later seismic wave imaging, attribute extraction, and reservoir development.

[0092] For example, in the field of oil and gas exploration and development, the seismic data processing method provided in the embodiments of this application can be used to process seismic data observed in the field, thereby generating higher-quality seismic images based on the processed post-stack seismic data. By interpreting these high-quality seismic images, the occurrence and structural relationships of underground rock formations can be better restored. During oil and gas exploration, the location of underground reservoirs can be more accurately determined, allowing the identification of favorable oil and gas-bearing areas.

[0093] The present invention provides a seismic data processing method that determines the stacking weights for adding the seismic data of the multiple seismic traces by analyzing the similarity between the seismic data of multiple seismic traces in the seismic data of a target plot and the reference seismic data of the target plot. By reducing the stacking weights of the seismic data of seismic traces with low similarity to the reference seismic data and increasing the stacking weights of the seismic data with high similarity, the influence of noise on the seismic data addition process can be reduced, the signal-to-noise ratio of the post-stack seismic data can be improved, and thus the imaging quality of the post-stack seismic data can be improved.

[0094] Figure 7 This is a block diagram of a seismic data processing device provided according to an embodiment of the present application. The device is used to perform the above-mentioned seismic data processing method, see Figure 7 The device includes: an acquisition module 701, a data processing module 702 and a calculation module 703.

[0095] An acquisition module 701 is configured to acquire seismic data of a target land parcel and reference seismic data, wherein the seismic data includes seismic data of multiple seismic channels, and the reference seismic data is seismic data obtained by performing equal-weighted addition of the seismic data of multiple seismic channels;

[0096] A data processing module 702 is configured to perform local correlation processing on the seismic data of any seismic trace and the reference seismic data to obtain a stacking weight of the seismic trace. The local correlation processing is used to determine the degree of similarity between the seismic data of the seismic trace and the reference seismic data. The stacking weight is positively correlated with the degree of similarity.

[0097] The calculation module 703 is used to perform weighted summation on the seismic data of the multiple seismic traces based on the stacking weights of the multiple seismic traces to obtain the post-stack seismic data of the target block.

[0098] In some embodiments, Figure 8 is a block diagram of another seismic data processing device provided according to an embodiment of the present application. Figure 8 , the processing module 702 includes:

[0099] The data processing unit 801 is configured to perform local correlation processing on the seismic data of any seismic trace and the reference seismic data to obtain a correlation coefficient of the seismic trace, where the correlation coefficient indicates the degree of similarity between the seismic data of the seismic trace and the reference seismic data.

[0100] The determining unit 802 is configured to determine a superposition weight based on the correlation coefficient, where the superposition weight is positively correlated with the correlation coefficient.

[0101] In some embodiments, the seismic trace includes a plurality of sampling points;

[0102] Continue to see Figure 8, the data processing unit 801 includes:

[0103] The sampling subunit 8011 is configured to sample the seismic data and reference seismic data of any sampling point in the seismic trace based on the sampling time of the sampling point and the length of the time window, respectively, to obtain the seismic data and reference seismic data within the time window, where the center point of the time window is the sampling time of the sampling point.

[0104] The data processing subunit 8012 is used to perform local correlation processing on the seismic data within the time window and the reference seismic data within the time window to obtain the correlation coefficient of the sampling points;

[0105] The operator unit 8013 is used to average the correlation coefficients of multiple sampling points to obtain the correlation coefficient of the seismic trace.

[0106] In some embodiments, the data processing subunit 8012 is also used to perform time smoothing on the correlation coefficients of multiple sampling points in any seismic trace according to the time sequence of the multiple sampling points in the seismic trace to obtain the intermediate correlation coefficients of the multiple sampling points. The time smoothing is used to smooth the correlation coefficients of adjacent sampling points among the multiple sampling points; and to perform spatial smoothing on the intermediate correlation coefficients of multiple sampling points in the multiple seismic traces according to the arrangement order of the multiple seismic traces. The spatial smoothing is used to smooth the intermediate correlation coefficients of multiple sampling points with the same sampling time in the multiple seismic traces.

[0107] In some embodiments, see Figure 8 , the determining unit 802 includes:

[0108] A first determining subunit 8021 is configured to determine a stacking weight based on the correlation coefficient, the reference correlation coefficient, and a control parameter when the correlation coefficient is less than a reference correlation coefficient. The reference correlation coefficient is used to indicate a reference similarity between the seismic data of the seismic trace and the reference seismic data. The control parameter is used to indicate an influence of the correlation coefficient on the stacking weight. The stacking weight is positively correlated with the correlation coefficient and the control parameter, and negatively correlated with the reference correlation coefficient.

[0109] The second determining subunit 8022 is configured to determine a superposition weight based on the correlation coefficient and the control parameter when the correlation coefficient is not less than the reference correlation coefficient, where the superposition weight is positively correlated with the correlation coefficient and the control parameter.

[0110] In some embodiments, see Figure 8 , the device further comprises:

[0111] The operation module 703 is further configured to perform equal-weighted addition of seismic data of multiple seismic channels to obtain reference stacked seismic data of the target land block;

[0112] An evaluation module 704 is configured to perform a quality evaluation on the reference stacked seismic data to obtain a quality evaluation result of the reference stacked seismic data, wherein the quality evaluation result is used to indicate a signal-to-noise ratio of the reference stacked seismic data;

[0113] The noise reduction module 705 is used to reduce noise on the reference stacked seismic data based on the quality assessment result to obtain reference seismic data.

[0114] An embodiment of the present application provides a seismic data processing device that can determine the stacking weights for adding the seismic data of the multiple seismic traces in the seismic data of a target plot by analyzing the similarity between the seismic data of the multiple seismic traces and the reference seismic data of the target plot. By reducing the stacking weights of the seismic data of the seismic traces with a lower degree of similarity to the reference seismic data and increasing the stacking weights of the seismic data with a higher degree of similarity, the influence of noise on the seismic data addition process can be reduced, the signal-to-noise ratio of the post-stack seismic data can be improved, and thus the imaging quality of the post-stack seismic data can be improved.

[0115] It should be noted that the seismic data processing device provided in the above embodiment is merely exemplified by the division of the above-mentioned functional modules. In actual applications, the above-mentioned functions can be distributed among different functional modules as needed, that is, the internal structure of the terminal can be divided into different functional modules to complete all or part of the functions described above. In addition, the seismic data processing device provided in the above embodiment and the seismic data processing method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0116] In the embodiments of the present application, the computer device can be configured as a terminal or a server. When the computer device is configured as a terminal, the terminal can be used as the execution subject to implement the technical solution provided in the embodiments of the present application. When the computer device is configured as a server, the server can be used as the execution subject to implement the technical solution provided in the embodiments of the present application. The technical solution provided in the present application can also be implemented through interaction between the terminal and the server. The embodiments of the present application do not limit this.

[0117] Figure 9 It is a structural block diagram of a terminal 900 provided according to an embodiment of the present application.

[0118] Typically, the terminal 900 includes a processor 901 and a memory 902 .

[0119] The processor 901 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 901 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 901 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 901 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 901 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0120] The memory 902 may include one or more computer-readable storage media, which may be non-transitory. The memory 902 may also include high-speed random access memory and non-volatile memory, such as one or more magnetic disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 902 is used to store at least one computer program, which is executed by the processor 901 to implement the seismic data processing method provided in the method embodiment of the present application.

[0121] In some embodiments, terminal 900 may also optionally include a peripheral device interface 903 and at least one peripheral device. The processor 901, memory 902, and peripheral device interface 903 may be connected via a bus or signal lines. Each peripheral device may be connected to peripheral device interface 903 via a bus, signal lines, or circuit boards. Specifically, the peripheral device may include at least one of a radio frequency circuit 904, a display screen 905, a camera assembly 906, an audio circuit 907, and a power supply 908.

[0122] The peripheral device interface 903 can be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 901 and the memory 902. In some embodiments, the processor 901, the memory 902, and the peripheral device interface 903 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 901, the memory 902, and the peripheral device interface 903 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0123] The radio frequency circuit 904 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 904 communicates with communication networks and other communication devices through electromagnetic signals. The radio frequency circuit 904 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. In some embodiments, the radio frequency circuit 904 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The radio frequency circuit 904 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or WiFi ( Wireless Fidelity In some embodiments, the radio frequency circuit 904 may further include a circuit related to NFC (Near Field Communication), which is not limited in this application.

[0124] The display screen 905 is used to display a user interface (UI). This UI may include graphics, text, icons, videos, or any combination thereof. When the display screen 905 is a touch screen, it is also capable of collecting touch signals on or above the surface of the display screen 905. These touch signals can be input as control signals to the processor 901 for processing. In this case, the display screen 905 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 can be a single display screen 905, located on the front panel of the terminal 900. In other embodiments, there can be at least two display screens 905, located on different surfaces of the terminal 900 or in a foldable design. In other embodiments, the display screen 905 can be a flexible display screen, located on a curved or foldable surface of the terminal 900. Furthermore, the display screen 905 can be configured as a non-rectangular irregular shape, i.e., a special-shaped screen. The display screen 905 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0125] The camera assembly 906 is used to capture images or videos. In some embodiments, the camera assembly 906 includes a front camera and a rear camera. Typically, the front camera is arranged on the front panel of the terminal, and the rear camera is arranged on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 906 may also include a flash. The flash can be a monochrome temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0126] The audio circuit 907 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals to be input into the processor 901 for processing, or input into the radio frequency circuit 904 to achieve voice communication. For the purpose of stereo sound collection or noise reduction, there may be multiple microphones, each located in different parts of the terminal 900. The microphone may also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert electrical signals from the processor 901 or the radio frequency circuit 904 into sound waves. The speaker may be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert electrical signals into sound waves audible to humans, but also convert electrical signals into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 907 may also include a headphone jack.

[0127] Power supply 908 is used to power various components in terminal 900. Power supply 908 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 908 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is charged via a wired line, while a wireless rechargeable battery is charged via a wireless coil. The rechargeable battery can also support fast charging technology.

[0128] In some embodiments, the terminal 900 further includes one or more sensors 909 , including but not limited to: an acceleration sensor 910 , a gyroscope sensor 911 , a pressure sensor 912 , an optical sensor 913 , and a proximity sensor 914 .

[0129] The accelerometer 910 can detect the magnitude of acceleration along the three coordinate axes of the coordinate system established by the terminal 900. For example, the accelerometer 910 can be used to detect the components of gravity acceleration along the three coordinate axes. The processor 901 can control the display screen 905 to display the user interface in a landscape or portrait view based on the gravity acceleration signal collected by the accelerometer 910. The accelerometer 910 can also be used to collect game or user motion data.

[0130] The gyroscope sensor 911 can detect the orientation and rotation angle of the terminal 900. It can also work with the accelerometer 910 to collect the user's 3D movements of the terminal 900. Based on the data collected by the gyroscope sensor 911, the processor 911 can implement the following functions: motion sensing (for example, changing the UI based on the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

[0131] The pressure sensor 912 can be provided on the side frame of the terminal 900 and / or below the display screen 905. When the pressure sensor 912 is provided on the side frame of the terminal 900, it can detect the user's gripping signal of the terminal 900, and the processor 901 can perform left-hand or right-hand recognition or shortcut operations based on the gripping signal collected by the pressure sensor 912. When the pressure sensor 912 is provided below the display screen 905, the processor 901 controls the operable controls on the UI interface based on the user's pressure operation on the display screen 905. Operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0132] Optical sensor 913 is used to detect ambient light intensity. In one embodiment, processor 901 can control the display brightness of display screen 905 based on the ambient light intensity detected by optical sensor 913. Specifically, when the ambient light intensity is high, the display brightness of display screen 905 is increased; when the ambient light intensity is low, the display brightness of display screen 905 is decreased. In another embodiment, processor 901 can also dynamically adjust the shooting parameters of camera assembly 906 based on the ambient light intensity detected by optical sensor 913.

[0133] The proximity sensor 914, also known as a distance sensor, is typically located on the front panel of the terminal 900. The proximity sensor 914 is used to detect the distance between the user and the front of the terminal 900. In one embodiment, when the proximity sensor 914 detects that the distance between the user and the front of the terminal 900 is gradually decreasing, the processor 901 controls the display screen 905 to switch from the screen-on state to the screen-off state. When the proximity sensor 904 detects that the distance between the user and the front of the terminal 900 is gradually increasing, the processor 901 controls the display screen 905 to switch from the screen-off state to the screen-on state.

[0134] Those skilled in the art will understand that Figure 9 The structure shown in the figure does not constitute a limitation on the terminal 900, and the terminal 900 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0135] Figure 101 is a schematic diagram of the structure of a server provided in accordance with an embodiment of the present application. The server 1000 may vary significantly due to different configurations or performances, and may include one or more processors (Central Processing Units, CPUs) 1001 and one or more memories 1002, wherein the memories 1002 store at least one computer program, which is loaded and executed by the processor 1001 to implement the seismic data processing methods provided in the above-mentioned various method embodiments. Of course, the server may also have components such as a wired or wireless network interface, a keyboard, and an input / output interface for input and output. The server may also include other components for implementing device functions, which will not be described in detail here.

[0136] The present application also provides a computer-readable storage medium storing at least one computer program, which is loaded and executed by a processor to implement the seismic data processing method of the above embodiment. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, or an optical data storage device.

[0137] An embodiment of the present application further provides a computer program product, including a computer program product, which is executed by a processor to implement the seismic data processing method in the above embodiment.

[0138] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0139] The above description is merely an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A seismic data processing method, characterized in that: The method comprises: Acquire seismic data and reference seismic data of a target plot, wherein the seismic data includes seismic data of a plurality of seismic channels, and the reference seismic data is seismic data obtained by equally weighted addition of the seismic data of the plurality of seismic channels; For any seismic trace, performing local correlation processing on the seismic data of the seismic trace and the reference seismic data to obtain a correlation coefficient of the seismic trace, where the correlation coefficient is used to indicate a degree of similarity between the seismic data of the seismic trace and the reference seismic data; When the correlation coefficient is less than a reference correlation coefficient, determining a stacking weight of the seismic trace based on the correlation coefficient, the reference correlation coefficient, and a control parameter, wherein the reference correlation coefficient is used to indicate a reference similarity between the seismic data of the seismic trace and the reference seismic data, and the control parameter is used to indicate an influence of the correlation coefficient on the stacking weight, and the stacking weight is positively correlated with the correlation coefficient and the control parameter, and negatively correlated with the reference correlation coefficient; When the correlation coefficient is not less than the reference correlation coefficient, determining the superposition weight based on the correlation coefficient and the control parameter, wherein the superposition weight is positively correlated with the correlation coefficient and the control parameter; Based on the stacking weights of the multiple seismic traces, weighted summation is performed on the seismic data of the multiple seismic traces to obtain post-stack seismic data of the target block.

2. The method according to claim 1, characterized in that The seismic trace includes a plurality of sampling points; For any seismic trace, performing local correlation processing on the seismic data of the seismic trace and the reference seismic data to obtain a correlation coefficient of the seismic trace includes: For any sampling point in the seismic trace, based on the sampling time of the sampling point and the length of the time window, the seismic data of the seismic trace and the reference seismic data are sampled respectively to obtain the seismic data located within the time window and the reference seismic data located within the time window, wherein the center point of the time window is the sampling time of the sampling point; Performing local correlation processing on the seismic data within the time window and the reference seismic data within the time window to obtain correlation coefficients of the sampling points; The correlation coefficients of the multiple sampling points are averaged to obtain the correlation coefficient of the seismic trace.

3. The method according to claim 2, characterized in that The method further comprises: For any seismic trace, performing time smoothing on the correlation coefficients of the multiple sampling points according to the time sequence of the multiple sampling points in the seismic trace to obtain intermediate correlation coefficients of the multiple sampling points, wherein the time smoothing is used to smooth the correlation coefficients of adjacent sampling points among the multiple sampling points; According to the arrangement order of the multiple seismic traces, spatial smoothing processing is performed on the intermediate correlation coefficients of multiple sampling points in the multiple seismic traces, and the spatial smoothing processing is used to smooth the intermediate correlation coefficients of multiple sampling points with the same sampling time in the multiple seismic traces.

4. The method according to claim 1, wherein The method further comprises: performing equal-weighted addition on the seismic data of the plurality of seismic channels to obtain reference stacked seismic data of the target land block; Performing a quality assessment on the reference stacked seismic data to obtain a quality assessment result of the reference stacked seismic data, wherein the quality assessment result is used to indicate a signal-to-noise ratio of the reference stacked seismic data; Based on the quality assessment result, the reference stacked seismic data is subjected to noise reduction to obtain the reference seismic data.

5. A seismic data processing device, characterized in that: The device comprises: an acquisition module, configured to acquire seismic data of a target land parcel and reference seismic data, wherein the seismic data includes seismic data of a plurality of seismic channels, and the reference seismic data is seismic data obtained by performing equal-weighted addition of the seismic data of the plurality of seismic channels; a data processing module configured to perform local correlation processing on the seismic data of any seismic trace and the reference seismic data to obtain a correlation coefficient of the seismic trace, wherein the correlation coefficient is used to indicate a degree of similarity between the seismic data of the seismic trace and the reference seismic data; determine a stacking weight of the seismic trace based on the correlation coefficient, the reference correlation coefficient, and a control parameter when the correlation coefficient is less than a reference correlation coefficient, wherein the reference correlation coefficient is used to indicate a reference degree of similarity between the seismic data of the seismic trace and the reference seismic data, and the control parameter is used to indicate an influence of the correlation coefficient on the stacking weight, wherein the stacking weight is positively correlated with the correlation coefficient and the control parameter and negatively correlated with the reference correlation coefficient; and determine the stacking weight based on the correlation coefficient and the control parameter when the correlation coefficient is not less than the reference correlation coefficient, wherein the stacking weight is positively correlated with the correlation coefficient and the control parameter; A calculation module is used to perform weighted summation on the seismic data of the multiple seismic traces based on the stacking weights of the multiple seismic traces to obtain post-stack seismic data of the target block.

6. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory is used to store at least one computer program, and the at least one computer program is loaded by the processor and executes the seismic data processing method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium is used to store at least one computer program, and the at least one computer program is used to execute the seismic data processing method according to any one of claims 1 to 4.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the seismic data processing method according to any one of claims 1 to 4 is implemented.

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