Seismic data processing method, device, equipment and storage medium

Abstract

The application discloses a seismic data processing method, device and equipment and a storage medium, and belongs to the technical field of seismic exploration. The method transforms first seismic data from a time-space domain to a Radon domain through first relationship data, then updates the seismic data corresponding to each zero-offset travel time under each slowness based on first weights to obtain fifth seismic data, and transforms the fifth seismic data from the Radon domain to the time-space domain through second relationship data. In the case that the energy loss of the first seismic data after the forward and reverse transformation of the Radon model meets a preset condition, the seismic data corresponding to the multiple waves is determined, and the seismic data corresponding to the multiple waves is finally removed from the first seismic data. The method reduces the energy loss of the seismic data after the forward and reverse transformation of the Radon model by continuously updating the seismic data corresponding to each zero-offset travel time under each slowness, thereby improving the resolution of the Radon model to the multiple waves and effectively removing the multiple waves.

Description

Technical Field

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

[0002] Multiple waves are widely present in seismic data. In general seismic exploration, multiple waves are interference waves that can mask valid signals. Therefore, removing multiple waves is an important step in seismic data processing.

[0003] Currently, multiple removal is primarily achieved by applying a Radon transform to seismic data using the Radon model. Therefore, the key to this approach lies in improving the Radon model's resolution for both multiples and primaries. Related technologies primarily use the least squares inversion method to obtain the Radon model, but this method often produces a low-resolution Radon model, making it ineffective in removing multiples. Summary of the Invention

[0004] The present invention provides a method, apparatus, device, and storage medium for processing seismic data, which can effectively remove multiple waves. The technical solution is as follows:

[0005] In one aspect, a method for processing seismic data is provided, the method comprising:

[0006] Acquiring first seismic data of a target work area, where the first seismic data is seismic data in a time-space domain;

[0007] Based on the first relationship data, the first seismic data is transformed from the spatiotemporal domain to the Ladon domain to obtain second seismic data; wherein the first seismic data includes third seismic data corresponding to different seismic travel times at multiple offsets, and the second seismic data includes fourth seismic data corresponding to different zero-offset travel times at multiple slownesses, and the first relationship data is used to represent the relationship between the seismic travel time and offset in the spatiotemporal domain and the zero-offset travel time and slowness in the Ladon domain;

[0008] For each zero-offset travel time at each slowness, determining a first weight corresponding to the zero-offset travel time at the slowness;

[0009] updating, based on the first weight, fourth seismic data corresponding to the zero-offset travel time at the slowness to obtain fifth seismic data;

[0010] Based on the second relational data, the fifth seismic data is transformed from the Radon domain to the spatiotemporal domain to obtain sixth seismic data; wherein the transformation process represented by the second relational data and the transformation process represented by the first relational data are conjugate processes to each other;

[0011] Determine loss seismic data based on the first seismic data and the sixth seismic data; wherein the loss seismic data is used to represent energy loss of the first seismic data after Radon forward and inverse transformation;

[0012] Repeating the step of determining the first weight, and determining seventh seismic data corresponding to the multiple wave based on the updated seismic data corresponding to the zero-offset travel time at the slowness when the lost seismic data meets a preset condition, wherein the seventh seismic data is seismic data in the spatiotemporal domain;

[0013] The seventh seismic data is removed from the first seismic data.

[0014] In another aspect, a seismic data processing device is provided, comprising:

[0015] An acquisition module, configured to acquire first seismic data of a target work area, wherein the first seismic data is seismic data in a time-space domain;

[0016] a first transformation module for transforming the first seismic data from the spatiotemporal domain to the Ladon domain based on first relationship data to obtain second seismic data; wherein the first seismic data includes third seismic data corresponding to different seismic travel times at multiple offsets, the second seismic data includes fourth seismic data corresponding to different zero-offset travel times at multiple slownesses, and the first relationship data is used to represent the relationship between the seismic travel time and offset in the spatiotemporal domain and the zero-offset travel time and slowness in the Ladon domain;

[0017] a first determining module, configured to determine, for each zero-offset travel time at each slowness, a first weight corresponding to the zero-offset travel time at the slowness;

[0018] An updating module, configured to update, based on the first weight, fourth seismic data corresponding to the zero-offset travel time at the slowness to obtain fifth seismic data;

[0019] a second transformation module, configured to transform the fifth seismic data from the Radon domain to the spatiotemporal domain based on the second relational data to obtain sixth seismic data; wherein the transformation process represented by the second relational data and the transformation process represented by the first relational data are conjugate processes to each other;

[0020] A second determining module is configured to determine lost seismic data based on the first seismic data and the sixth seismic data; wherein the lost seismic data is used to represent energy loss of the first seismic data after undergoing Radon forward and inverse transformation;

[0021] a third determining module, configured to repeatedly perform the step of determining the first weight, and determine seventh seismic data corresponding to the multiple wave based on the updated seismic data corresponding to the zero-offset travel time at the slowness when the lost seismic data meets a preset condition, wherein the seventh seismic data is seismic data in the spatiotemporal domain;

[0022] A removal module is used to remove the seventh seismic data from the first seismic data.

[0023] In one possible implementation, the first determination module is used to determine the total energy corresponding to the slowness based on the fourth seismic data corresponding to each zero-offset travel time under the slowness; based on the total energy corresponding to the slowness and the second relationship data, transform the fourth seismic data corresponding to the zero-offset travel time under the slowness from the Ladon domain to the time-space domain to obtain eighth seismic data; based on the eighth seismic data and the first seismic data, determine the second weight corresponding to the zero-offset travel time under the slowness; based on the fourth seismic data corresponding to the zero-offset travel time under the slowness and multiple fourth seismic data corresponding to the slowness, determine the third weight corresponding to the zero-offset travel time under the slowness; determine the product of the second weight and the third weight to obtain the first weight.

[0024] In another possible implementation, the eighth seismic data includes first seismic sub-data corresponding to a plurality of points, and the first seismic data includes second seismic sub-data corresponding to the plurality of points;

[0025] The first determination module is used to determine the product of the first seismic sub-data and the second seismic sub-data corresponding to each point to obtain a first product value; determine the sum of the first product values ​​corresponding to the multiple points to obtain a first sum value; determine the square of the first seismic sub-data corresponding to each point to obtain a second product value; determine the sum of the second product values ​​corresponding to the multiple points to obtain a second sum value; determine the ratio of the first sum value to the second sum value to obtain the second weight.

[0026] In another possible implementation, the fourth seismic data includes amplitude;

[0027] The first determination module is configured to determine a maximum amplitude from multiple amplitudes corresponding to the slowness; determine a ratio of the amplitude corresponding to the zero-offset travel time at the slowness to the maximum amplitude to obtain a first ratio; determine an absolute value of the first ratio to obtain a second ratio; and determine an e-th power of the second ratio to obtain the third weight, wherein e is a sparsity coefficient greater than 0.

[0028] In another possible implementation, the first determination module is used to determine the number of sampling points of the seismic trace; substitute the number of sampling points of the seismic trace and the fourth seismic data corresponding to each zero-offset travel time under the slowness into the third relationship data to obtain the total energy corresponding to the slowness; wherein the third relationship data is used to represent the relationship between the total energy corresponding to each slowness and the fourth seismic data corresponding to each zero-offset travel time under each slowness.

[0029] In another possible implementation, the update module is used to determine the product of the fourth seismic data corresponding to the zero offset travel time under the slowness and the first weight to obtain ninth seismic data; and determine the sum of the fourth seismic data and the ninth seismic data to obtain the fifth seismic data.

[0030] In another possible implementation, the third determination module is used to determine the tenth seismic data of the target work area based on the updated seismic data corresponding to the zero offset travel time under the slowness, and the tenth seismic data is the seismic data of the Ladong domain; based on the tenth seismic data, predict the eleventh seismic data corresponding to the multiple waves; based on the second relationship data, transform the eleventh seismic data from the Ladong domain to the time-space domain to obtain the seventh seismic data.

[0031] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one program code, and the at least one program code is loaded and executed by the processor to implement any of the above-mentioned seismic data processing methods.

[0032] On the other hand, a computer-readable storage medium is provided, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to implement any of the above-mentioned seismic data processing methods.

[0033] On the other hand, a computer program product is provided, wherein at least one program code is stored in the computer program product, and the at least one program code is loaded and executed by a processor to implement any of the above-mentioned seismic data processing methods.

[0034] An embodiment of the present application provides a method for processing seismic data, which transforms first seismic data from a time-space domain to a Radon domain through first relational data, and then updates the seismic data corresponding to each zero-offset travel time at each slowness based on a first weight to obtain fifth seismic data, and transforms the fifth seismic data from the Radon domain to the time-space domain through second relational data. When the energy loss of the first seismic data after Radon positive and negative transformations meets a preset condition, the seismic data corresponding to the multiple waves are determined, and finally the seismic data corresponding to the multiple waves are removed from the first seismic data. This method reduces the energy loss of seismic data after Radon positive and negative transformations by continuously updating the seismic data corresponding to each zero-offset travel time at each slowness, thereby improving the resolution of the Radon model for multiple waves and effectively removing multiple waves.

[0035] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a schematic diagram of an implementation environment of a seismic data processing method provided in an embodiment of the present application;

[0037] Figure 2 is a flow chart of a seismic data processing method provided in an embodiment of the present application;

[0038] Figure 3 a is a schematic diagram of first seismic data provided in an embodiment of the present application;

[0039] Figure 3 b is a schematic diagram of a tenth earthquake data provided in an embodiment of the present application;

[0040] Figure 3 c is a schematic diagram of seismic data after multiple wave suppression provided by an embodiment of the present application;

[0041] Figure 4 This is a schematic diagram of seismic data corresponding to a common center point gather provided in an embodiment of the present application;

[0042] Figure 5 The method provided by this application is used to Figure 4 Schematic diagram of seismic data obtained after multiple wave suppression of the seismic data shown;

[0043] Figure 6 It is through the method in the related art Figure 4 Schematic diagram of seismic data obtained after multiple wave suppression of the seismic data shown;

[0044] Figure 7 1 is a schematic diagram of a common-offset section corresponding to a multiple wave suppression before multiple wave suppression provided by an embodiment of the present application;

[0045] Figure 8 The method provided by this application is used to Figure 7 Schematic diagram of the common offset section obtained after multiple wave suppression of the seismic data shown;

[0046] Figure 9 This is a structural diagram of a seismic data processing device provided in an embodiment of the present application;

[0047] Figure 10 This is a structural block diagram of a terminal provided in an embodiment of the present application;

[0048] Figure 11 This is a structural block diagram of a server provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to make the technical solutions and advantages of the present application clearer, the implementation methods of the present application are described in further detail below.

[0050] The terms "first," "second," "third," and "fourth," etc. in the specification and claims of this application and the accompanying drawings are used to distinguish different objects, not to describe a specific order. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0051] 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, storage, display, 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 seismic data and relationship data involved in this application were obtained with full authorization.

[0052] Figure 1 This is a schematic diagram of an implementation environment of a seismic data processing method provided in an embodiment of the present application, see Figure 1 The implementation environment includes: an electronic device, which can be provided as a terminal 101 or provided as a terminal 101 and a server 102. If the electronic device is provided as a terminal 101 and a server 102, the terminal 101 and the server 102 can be connected via a wireless or wired network. In the embodiments of the present application, the electronic device is not specifically limited.

[0053] If the electronic device is provided as the terminal 101 , the terminal 101 processes the seismic data to remove multiple waves.

[0054] If the electronic device is provided as a terminal 101 and a server 102 , the terminal 101 sends the seismic data to the server 102 , and the server 102 processes the seismic data to remove multiple waves, and then returns the seismic data after removing multiple waves to the terminal 101 .

[0055] The terminal 101 is at least one of a mobile phone, a tablet computer, a PC (Personal Computer), an intelligent voice interaction device, and an in-vehicle terminal. The server 102 can be at least one of a single server, a server cluster consisting of multiple servers, a cloud server, a cloud computing platform, and a virtualization center.

[0056] Figure 2 This is a flow chart of a seismic data processing method provided by an embodiment of the present application, which is executed by an electronic device. Figure 2 , the method comprising:

[0057] Step 201: The electronic device acquires first seismic data of the target work area.

[0058] The target work area is the area where the reservoir to be predicted is located.

[0059] The electronic device may obtain the first seismic data by obtaining raw seismic data input by a user or from another electronic device, performing dynamic correction on the raw seismic data, and obtaining the first seismic data. The first seismic data is seismic data in the spatiotemporal domain, and the raw seismic data is data collected by exciting seismic waves in a target work area.

[0060] Step 202: The electronic device transforms the first seismic data from the time-space domain to the Ladon domain based on the first relationship data to obtain second seismic data.

[0061] The first seismic data includes third seismic data corresponding to different seismic travel times at multiple offset distances, the second seismic data includes fourth seismic data corresponding to different zero-offset travel times at multiple slownesses, and the first relationship data is used to represent the relationship between the seismic travel time and offset distance in the time-space domain and the zero-offset travel time and slowness in the Ladong domain.

[0062] In the embodiment of the present application, after the original seismic data is corrected by dynamic correction, the seismic travel time can be approximated by the parabolic equation: t = τ + ph 2 ; where t is the earthquake travel time, h is the offset, τ is the zero-offset travel time, and p is the slowness.

[0063] The principle of the Radon transform is to transform the first seismic data from the time-space domain to the Radon domain, and to perform a summation operation along the earthquake travel time to obtain the second seismic data in the Radon domain. In the embodiment of the present application, the first relational data can be expressed by the following formula (1):

[0064] m(τ, p) = ∑ h d(h, t=τ+ph 2 );

[0065] Wherein, d represents the first seismic data, and m(τ, p) represents the fourth seismic data corresponding to the point (τ, p), that is, the amplitude corresponding to the point (τ, p).

[0066] The electronic device substitutes the first seismic data into the first relational data, and converts the first seismic data from the time-space domain to the Ladon domain through the first relational data to obtain the second seismic data.

[0067] Step 203: For each zero-offset travel time at each slowness, the electronic device determines a first weight corresponding to the zero-offset travel time at the slowness.

[0068] This step can be achieved by following the steps (1) to (5), including:

[0069] (1) The electronic device determines the total energy corresponding to the slowness based on the fourth seismic data corresponding to each zero-offset travel time under the slowness.

[0070] The electronic device determines the number of sampling points in the seismic trace, substitutes the number of sampling points in the seismic trace and the fourth seismic data corresponding to each zero-offset travel time at the slowness into the third relationship data, and obtains the total energy corresponding to the slowness. The third relationship data is used to represent the relationship between the total energy corresponding to each slowness and the fourth seismic data corresponding to each zero-offset travel time at each slowness.

[0071] In the embodiment of the present application, the third relationship data can be expressed by the following formula (2):

[0072]

[0073] Where S(p) represents the total energy corresponding to the slowness p, and n represents the number of sampling points of the seismic trace.

[0074] The electronic device substitutes the number of sampling points of the seismic trace and the fourth seismic data corresponding to each zero-offset travel time under the slowness into the third relationship data to obtain the total energy corresponding to the slowness.

[0075] The electronic device sorts the total energies corresponding to the plurality of slownesses in descending order of energy, and sequentially performs steps (2) to (5) on the sorted plurality of slownesses in descending order of energy.

[0076] (2) The electronic device transforms the fourth seismic data corresponding to the zero offset travel time under the slowness from the Ladon domain to the time-space domain based on the total energy corresponding to the slowness and the second relationship data to obtain the eighth seismic data.

[0077] The transformation process represented by the second relational data is a conjugate process to the transformation process represented by the first relational data. In the embodiment of the present application, the second relational data can be represented by the following formula (3):

[0078] d pred (t, h) = ∑ p m(p,τ=t-ph 2 );

[0079] Among them, d pred (t, h) represents the seismic data in the time and space domain. In this step, d pred (t, h) represents the eighth earthquake data.

[0080] The electronic device substitutes the fourth seismic data corresponding to the zero offset travel time under the slowness into the second relational data, and transforms the fourth seismic data from the Radon domain to the time-space domain through the second relational data, that is, the Radon inverse transform, to obtain the eighth seismic data.

[0081] (3) The electronic device determines a second weight corresponding to the zero-offset travel time at the slowness based on the eighth seismic data and the first seismic data.

[0082] The eighth seismic data includes first seismic sub-data corresponding to a plurality of points, and the first seismic data includes second seismic sub-data corresponding to a plurality of points.

[0083] The eighth seismic data corresponds to a space-time domain curve, which can be fitted by k discrete points. By performing line integration along the space-time domain curve, the point in the Ladon domain, namely (τ, p), can be obtained.

[0084] Based on this, the process of the electronic device determining the second weight can be: the electronic device determines the product of the first seismic sub-data and the second seismic sub-data corresponding to each point to obtain a first product value; determines the sum of the first product values ​​corresponding to multiple points to obtain a first sum value; determines the square of the first seismic sub-data corresponding to each point to obtain a second product value; determines the sum of the second product values ​​corresponding to multiple points to obtain a second sum value; determines the ratio of the first sum value to the second sum value to obtain a second weight.

[0085] The above process can be expressed by the following formula (4):

[0086]

[0087] Among them, ω1(τ, p) indicates that the point (τ, p) corresponds to the second weight, which is used to fit the first seismic data. represents the first earthquake sub-data corresponding to the i-th point, d i Represents the second earthquake sub-data corresponding to the i-th point.

[0088] (4) The electronic device determines a third weight corresponding to the zero-offset travel time at the slowness based on the fourth seismic data corresponding to the zero-offset travel time at the slowness and multiple fourth seismic data corresponding to the slowness.

[0089] If the fourth seismic data is amplitude, this step is: the electronic device determines a third weight corresponding to the zero-offset travel time under the slowness based on the amplitude corresponding to the zero-offset travel time under the slowness and multiple amplitudes corresponding to the slowness.

[0090] Correspondingly, the process of the electronic device determining the third weight can be: the electronic device determines the maximum amplitude from multiple amplitudes corresponding to the slowness; determines the ratio of the amplitude corresponding to the zero offset travel time under the slowness to the maximum amplitude to obtain a first ratio; determines the absolute value of the first ratio to obtain a second ratio; determines the e-th power of the second ratio to obtain the third weight; wherein e is a sparse coefficient greater than 0.

[0091] The above process can be expressed by the following formula (5):

[0092]

[0093] Among them, ω2(τ, p) represents the third weight, which is used to highlight strong earthquake events, that is, larger amplitudes, m max Represents the maximum amplitude, e represents the sparse coefficient, the larger the coefficient is, the sparser the final model is.

[0094] (5) The electronic device determines the product of the second weight and the third weight to obtain the first weight.

[0095] If the first weight is expressed as ω(τ, p), then ω(τ, p) = ω1(τ, p) × ω2(τ, p).

[0096] It should be noted that the transformation process represented by the second relational data is a conjugate process to the transformation process represented by the first relational data, but it is not a direct inverse process. In other words, the seismic data calculated using the first relational data cannot be substituted into the second relational data to obtain the original input data. To obtain a model that can accurately predict seismic data, it is necessary to rely on the inversion method. Specifically, it is required to obtain a model that can minimize the following objective function, which can be expressed by the following formula (6):

[0097] J(m)=||d-Lm|| 2;

[0098] Among them, L is a positive operator.

[0099] Assuming that the Radon model m of the seismic data d is expressed as m′ after the second weight ω1 is optimized, then m′=m×ω1, and substituting it into formula (6), the following formula (7) can be obtained:

[0100]

[0101] Where R is the normalization function, and λ is the normalization weight coefficient. Common normalization functions include the quadratic modulus, the linear modulus, and the Cauchy modulus. When the quadratic modulus is used, the Radon model has low resolution. However, when the linear modulus or the Cauchy modulus is used, the Radon model exhibits sparse characteristics and has higher resolution.

[0102] In formula (7), d represents the first earthquake data, Lm is equivalent to formula (3), which means that the earthquake data is calculated by the Radon model. Let d pred =Lm, and substituting it into formula (7), we get the following formula (8):

[0103]

[0104] By taking the derivative of both sides of formula (8) with respect to ω1 and setting the derivative to 0, we can obtain the following formula (9):

[0105] 0 = -2 × d × d pred +2d pred 2 ×ω1;

[0106] From formula (9), we can get:

[0107] In order to highlight strong earthquake events, ω1 can be multiplied by make Thus we get ω=ω1×ω2.

[0108] Step 204: The electronic device updates the fourth seismic data corresponding to the zero-offset travel time at the slowness based on the first weight to obtain fifth seismic data.

[0109] The electronic device determines the product of the fourth seismic data corresponding to the zero offset travel time under the slowness and the first weight to obtain ninth seismic data; determines the sum of the fourth seismic data and the ninth seismic data to obtain fifth seismic data.

[0110] This process can be expressed by the following formula (10):

[0111] m(τ,p)′=m(τ,p)+m(τ,p)×w(τ,p);

[0112] Here, m(τ, p)′ represents the fifth earthquake data.

[0113] Step 205: The electronic device transforms the fifth seismic data from the Ladon domain to the spatiotemporal domain based on the second relationship data to obtain sixth seismic data.

[0114] According to step (2) in step 203, the second relational data can be expressed as:

[0115] d pred (t, h) = ∑ p m(p,τ=t-ph 2 );

[0116] The electronic device substitutes the fifth seismic data into the second relational data and transforms the fifth seismic data from the Ladon domain to the spatiotemporal domain using the second relational data to obtain sixth seismic data. The sixth seismic data is seismic data corresponding to the seismic travel time and offset in the spatiotemporal domain corresponding to the zero-offset travel time at the slowness.

[0117] Step 206: The electronic device determines loss seismic data based on the first seismic data and the sixth seismic data.

[0118] The loss seismic data is used to represent the energy loss of the first seismic data after the Radon forward and inverse transformation.

[0119] The electronic device determines the twelfth seismic data for the target area based on the sixth seismic data corresponding to different earthquake travel times at multiple offsets. The electronic device also determines the difference between the first seismic data and the twelfth seismic data to obtain the lost seismic data. This process can be expressed by the following formula (11):

[0120] d resi =dd pred ;

[0121] Among them, d resi represents the loss earthquake data, d pred Represents the seismic data in the time and space domain. In this step, d pred Indicates the twelfth earthquake data.

[0122] Step 207: The electronic device repeatedly performs the step of determining the first weight, and determines seventh seismic data corresponding to the multiple wave based on the updated seismic data corresponding to the zero offset travel time at the slowness when the lost seismic data meets the preset conditions.

[0123] The electronic device determines whether the lost seismic data meets a preset condition. If so, the electronic device directly executes the step of determining the seventh seismic data corresponding to the multiple wave based on the updated seismic data corresponding to the zero-offset travel time at the slowness. If the electronic device does not meet the preset condition, steps 203 to 206 are repeated until the lost seismic data meets the preset condition.

[0124] For example, after the electronic device repeats steps 203 to 206 four or five times, it determines that the lost earthquake data meets a preset condition. The preset condition can be set and modified as needed, for example, the preset condition is that the lost earthquake data is less than a preset threshold.

[0125] If the lost seismic data meets a preset condition, the electronic device determines seventh seismic data corresponding to the multiple wave based on the updated seismic data corresponding to the zero-offset travel time at the slowness. The process may include: the electronic device determines tenth seismic data for the target work area based on the updated seismic data corresponding to the zero-offset travel time at the slowness; predicts eleventh seismic data corresponding to the multiple wave based on the tenth seismic data; and transforms the eleventh seismic data from the Ladong domain to the spatiotemporal domain based on the second relationship data to obtain the seventh seismic data. The tenth seismic data is seismic data in the Ladong domain.

[0126] In this implementation, when the electronic device determines that the lost seismic data meets the preset conditions, the updated seismic data in step 204 is fused with the updated seismic data corresponding to different zero offset travel times at each slowness to obtain the tenth seismic data.

[0127] Based on the tenth seismic data, the electronic device may determine seismic data with non-convergence of energy and an amplitude less than a threshold, and determine the seismic data as the eleventh seismic data corresponding to the multiple wave. The electronic device may display the tenth seismic data corresponding to the target work area, i.e., the amplitude of the entire work area, and determine the eleventh seismic data from the non-convergence of energy and the smaller amplitude.

[0128] The electronic device substitutes the eleventh earthquake data into the second relational data, and transforms the eleventh earthquake data from the Ladon domain to the spatiotemporal domain through the second relational data to obtain the seventh earthquake data.

[0129] Step 208: The electronic device removes the seventh seismic data from the first seismic data.

[0130] The electronic device determines the difference between the first seismic data and the seventh seismic data to obtain seismic data after multiple wave suppression. The electronic device can characterize the reservoir based on the seismic data after multiple wave suppression to perform reservoir prediction.

[0131] This application applies a greedy algorithm to the Radon transform. By calculating the Radon model corresponding to the spatiotemporal seismic data, sorting the seismic data by amplitude, performing forward and inverse Radon transforms, calculating and updating weights, optimizing the Radon model, and predicting multiples in the Radon domain, the multiples in the spatiotemporal domain are then calculated, resulting in seismic data after multiple suppression. This method does not require time-sharing windowing, is free of boundary effects, and exhibits rapid convergence, good stability, and high computational accuracy.

[0132] See also Figure 3 , Figure 3 a is a schematic diagram of the first seismic data, Figure 3 b is the final Ladon model of the target area, which is also the schematic diagram of the tenth earthquake data. Figure 3 c is a schematic diagram of seismic data after multiple wave suppression. Figure 3 From b, we can see that the Radon model obtained in this application has a good convergence degree and can clearly distinguish the effective waves and multiple waves. Figure 3 c It can be seen that the present application can effectively suppress multiple waves whose velocities are not much different from those of the effective wave.

[0133] See also Figures 4 to 6 , Figure 4 This is a schematic diagram of the seismic data corresponding to the actual common center point gather. Figure 5 The method provided by this application is Figure 4 Schematic diagram of seismic data obtained after multiple wave suppression of seismic data shown. Figure 6 It is through the method in the related art Figure 4 Schematic diagram of seismic data obtained after multiple wave suppression of seismic data shown in FIG. Figure 5 and Figure 6 It can be seen that the method provided by the present application can suppress multiple waves better, and the local details are better than the suppression results of related technologies.

[0134] See also Figures 7 and 8 , Figure 7 is the common offset profile corresponding to the multiple wave suppression, Figure 8 The method provided by this application is Figure 7 Schematic diagram of the common offset section obtained after multiple wave suppression of the seismic data shown in FIG. Figure 7 and Figure 8 It can be seen that the multiple wave events are significantly suppressed.

[0135] An embodiment of the present application provides a method for processing seismic data, which transforms first seismic data from a time-space domain to a Radon domain through first relational data, and then updates the seismic data corresponding to each zero-offset travel time at each slowness based on a first weight to obtain fifth seismic data, and transforms the fifth seismic data from the Radon domain to the time-space domain through second relational data. When the energy loss of the first seismic data after Radon positive and negative transformations meets a preset condition, the seismic data corresponding to the multiple waves are determined, and finally the seismic data corresponding to the multiple waves are removed from the first seismic data. This method reduces the energy loss of seismic data after Radon positive and negative transformations by continuously updating the seismic data corresponding to each zero-offset travel time at each slowness, thereby improving the resolution of the Radon model for multiple waves and effectively removing multiple waves.

[0136] Figure 9 This is a structural diagram of a seismic data processing device provided in an embodiment of the present application, see Figure 9 , the device comprises:

[0137] An acquisition module 901 is configured to acquire first seismic data of a target work area, where the first seismic data is seismic data in a time-space domain;

[0138] A first transformation module 902 is configured to transform the first seismic data from the spatiotemporal domain to the Ladon domain based on the first relationship data to obtain second seismic data; wherein the first seismic data includes third seismic data corresponding to different seismic travel times at multiple offsets, and the second seismic data includes fourth seismic data corresponding to different zero-offset travel times at multiple slownesses, and the first relationship data is configured to represent a relationship between the seismic travel time and offset in the spatiotemporal domain and the zero-offset travel time and slowness in the Ladon domain;

[0139] A first determining module 903 is configured to determine, for each zero-offset travel time at each slowness, a first weight corresponding to the zero-offset travel time at the slowness;

[0140] An updating module 904 is configured to update the fourth seismic data corresponding to the zero-offset travel time under the slowness based on the first weight to obtain fifth seismic data;

[0141] A second transformation module 905 is configured to transform the fifth seismic data from the Ladon domain to the spatiotemporal domain based on the second relational data to obtain sixth seismic data; wherein the transformation process represented by the second relational data is a conjugate process to the transformation process represented by the first relational data;

[0142] A second determining module 906 is configured to determine lost seismic data based on the first seismic data and the sixth seismic data, wherein the lost seismic data is used to represent energy loss after the first seismic data undergoes Radon forward and inverse transformation;

[0143] A third determination module 907 is configured to repeatedly execute the step of determining the first weight, and determine seventh seismic data corresponding to the multiple wave based on the updated seismic data corresponding to the zero-offset travel time under slowness when the lost seismic data meets a preset condition, where the seventh seismic data is seismic data in the spatiotemporal domain;

[0144] The removal module 908 is configured to remove the seventh seismic data from the first seismic data.

[0145] In one possible implementation, the first determination module 903 is used to determine the total energy corresponding to the slowness based on the fourth seismic data corresponding to each zero-offset travel time under the slowness; based on the total energy corresponding to the slowness and the second relationship data, the fourth seismic data corresponding to the zero-offset travel time under the slowness is transformed from the Ladong domain to the time-space domain to obtain the eighth seismic data; based on the eighth seismic data and the first seismic data, the second weight corresponding to the zero-offset travel time under the slowness is determined; based on the fourth seismic data corresponding to the zero-offset travel time under the slowness and multiple fourth seismic data corresponding to the slowness, the third weight corresponding to the zero-offset travel time under the slowness is determined; and the product of the second weight and the third weight is determined to obtain the first weight.

[0146] In another possible implementation, the eighth seismic data includes first seismic sub-data corresponding to a plurality of points, and the first seismic data includes second seismic sub-data corresponding to a plurality of points;

[0147] The first determination module 903 is used to determine the product of the first seismic sub-data and the second seismic sub-data corresponding to each point to obtain a first product value; determine the sum of the first product values ​​corresponding to multiple points to obtain a first sum value; determine the square of the first seismic sub-data corresponding to each point to obtain a second product value; determine the sum of the second product values ​​corresponding to multiple points to obtain a second sum value; determine the ratio of the first sum value to the second sum value to obtain a second weight.

[0148] In another possible implementation, the fourth seismic data includes amplitude;

[0149] The first determination module 903 is configured to determine a maximum amplitude from multiple amplitudes corresponding to the slowness; determine a ratio of the amplitude corresponding to the zero-offset travel time under the slowness to the maximum amplitude to obtain a first ratio; determine an absolute value of the first ratio to obtain a second ratio; and determine the e-th power of the second ratio to obtain a third weight, wherein e is a sparsity coefficient greater than 0.

[0150] In another possible implementation, the first determination module 903 is used to determine the number of sampling points of the seismic trace; substitute the number of sampling points of the seismic trace and the fourth seismic data corresponding to each zero offset travel time under the slowness into the third relationship data to obtain the total energy corresponding to the slowness; wherein the third relationship data is used to represent the relationship between the total energy corresponding to each slowness and the fourth seismic data corresponding to each zero offset travel time under each slowness.

[0151] In another possible implementation, the update module 904 is used to determine the product of the fourth seismic data corresponding to the zero offset travel time under slowness and the first weight to obtain the ninth seismic data; determine the sum of the fourth seismic data and the ninth seismic data to obtain the fifth seismic data.

[0152] In another possible implementation, the third determination module 907 is used to determine the tenth seismic data of the target work area based on the updated seismic data corresponding to the zero offset travel time under slowness, where the tenth seismic data is the seismic data in the Ladong domain; based on the tenth seismic data, predict the eleventh seismic data corresponding to the multiple waves; based on the second relationship data, transform the eleventh seismic data from the Ladong domain to the time-space domain to obtain the seventh seismic data.

[0153] An embodiment of the present application provides a seismic data processing device that transforms first seismic data from a spatiotemporal domain to a Radon domain using first relational data, and then updates the seismic data corresponding to each zero-offset travel time at each slowness based on a first weight to obtain fifth seismic data, and transforms the fifth seismic data from the Radon domain to the spatiotemporal domain using second relational data. When the energy loss of the first seismic data after Radon positive and negative transformations satisfies a preset condition, the seismic data corresponding to the multiple waves is determined, and finally the seismic data corresponding to the multiple waves is removed from the first seismic data. The device reduces the energy loss of the seismic data after Radon positive and negative transformations by continuously updating the seismic data corresponding to each zero-offset travel time at each slowness, thereby improving the resolution of the Radon model for multiple waves and effectively removing multiple waves.

[0154] refer to Figure 10 , Figure 10The following is a block diagram of a terminal 1000 according to an exemplary embodiment of the present application. Terminal 1000 may be a portable mobile terminal, such as a smartphone, tablet computer, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, or desktop computer. Terminal 1000 may also be referred to as user equipment, portable terminal, laptop terminal, desktop terminal, or other similar names.

[0155] Typically, the terminal 1000 includes a processor 1001 and a memory 1002 .

[0156] The processor 1001 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1001 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 1001 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 1001 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 1001 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0157] The memory 1002 may include one or more computer-readable storage media, which may be non-transitory. The memory 1002 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 1002 is used to store at least one program code, which is used to be executed by the processor 1001 to implement the operations performed by the terminal in the seismic data processing method provided in the method embodiment of the present application.

[0158] In some embodiments, terminal 1000 may optionally include a peripheral device interface 1003 and at least one peripheral device. Processor 1001, memory 1002, and peripheral device interface 1003 may be connected via a bus or signal lines. Each peripheral device may be connected to peripheral device interface 1003 via a bus, signal lines, or circuit boards. Specifically, the peripheral device may include at least one of a radio frequency circuit 1004, a display screen 1005, a camera assembly 1006, an audio circuit 1007, and a power supply 1008.

[0159] The peripheral device interface 1003 can be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 1001 and the memory 1002. In some embodiments, the processor 1001, the memory 1002, and the peripheral device interface 1003 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1001, the memory 1002, and the peripheral device interface 1003 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0160] The RF circuit 1004 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 1004 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 1004 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the RF circuit 1004 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, and the like. The RF circuit 1004 can communicate with other terminals via at least one wireless communication protocol. Such wireless communication protocols include, but are not limited to, the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 1004 may also include circuitry related to Near Field Communication (NFC), which is not limited in this application.

[0161] The display screen 1005 is used to display a UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 1005 is a touch screen display, the display screen 1005 also has the ability to collect touch signals on the surface or above the surface of the display screen 1005. The touch signal can be input as a control signal to the processor 1001 for processing. At this time, the display screen 1005 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, there can be one display screen 1005, which is set on the front panel of the terminal 1000; in other embodiments, there can be at least two display screens 1005, which are respectively set on different surfaces of the terminal 1000 or in a folding design; in other embodiments, the display screen 1005 can be a flexible display screen, which is set on the curved surface or folding surface of the terminal 1000. Even more, the display screen 1005 can be set to a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 1005 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0162] The camera assembly 1006 is used to capture images or videos. Optionally, the camera assembly 1006 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 1006 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.

[0163] The audio circuit 1007 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 that are input into the processor 1001 for processing, or input into the RF circuit 1004 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 1000. The microphone may also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert electrical signals from the processor 1001 or the RF circuit 1004 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 1007 may also include a headphone jack.

[0164] Power supply 1008 is used to power various components in terminal 1000. Power supply 1008 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 1008 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.

[0165] In some embodiments, the terminal 1000 further includes one or more sensors 1009 . The one or more sensors 1009 include, but are not limited to, an acceleration sensor 1010 , a gyroscope sensor 1011 , a pressure sensor 1012 , an optical sensor 1013 , and a proximity sensor 1014 .

[0166] The accelerometer 1010 can detect the magnitude of acceleration along the three coordinate axes of the coordinate system established by the terminal 1000. For example, the accelerometer 1010 can be used to detect the components of gravity acceleration along the three coordinate axes. The processor 1001 can control the display screen 1005 to display the user interface in a landscape or portrait view based on the gravity acceleration signal collected by the accelerometer 1010. The accelerometer 1010 can also be used to collect game or user motion data.

[0167] The gyroscope sensor 1011 can detect the body orientation and rotation angle of the terminal 1000. The gyroscope sensor 1011 can cooperate with the acceleration sensor 1010 to collect the user's 3D movements on the terminal 1000. Based on the data collected by the gyroscope sensor 1011, the processor 1001 can implement the following functions: motion sensing (such as changing the UI based on the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

[0168] The pressure sensor 1012 can be set on the side frame of the terminal 1000 and / or the lower layer of the display screen 1005. When the pressure sensor 1012 is set on the side frame of the terminal 1000, it can detect the user's grip signal of the terminal 1000, and the processor 1001 performs left and right hand recognition or shortcut operations based on the grip signal collected by the pressure sensor 1012. When the pressure sensor 1012 is set on the lower layer of the display screen 1005, the processor 1001 controls the operable controls on the UI interface based on the user's pressure operation on the display screen 1005. Operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0169] Optical sensor 1013 is used to detect ambient light intensity. In one embodiment, processor 1001 can control the display brightness of display screen 1005 based on the ambient light intensity detected by optical sensor 1013. Specifically, when the ambient light intensity is high, the display brightness of display screen 1005 is increased; when the ambient light intensity is low, the display brightness of display screen 1005 is decreased. In another embodiment, processor 1001 can also dynamically adjust the shooting parameters of camera assembly 1006 based on the ambient light intensity detected by optical sensor 1013.

[0170] Proximity sensor 1014, also known as a distance sensor, is typically located on the front panel of terminal 1000. Proximity sensor 1014 is used to detect the distance between the user and the front of terminal 1000. In one embodiment, when proximity sensor 1014 detects that the distance between the user and the front of terminal 1000 is gradually decreasing, processor 1001 controls display screen 1005 to switch from the screen-on state to the screen-off state. When proximity sensor 1014 detects that the distance between the user and the front of terminal 1000 is gradually increasing, processor 1001 controls display screen 1005 to switch from the screen-off state to the screen-on state.

[0171] Those skilled in the art will understand that Figure 10 The structure shown in the figure does not constitute a limitation on the terminal 1000, and the terminal 1000 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0172] The server structure diagram can be found in Figure 11The server 1100 may vary significantly depending on its configuration or performance, and may include a processor (central processing unit, CPU) 1101 and a memory 1102. The memory 1102 stores at least one program code, which is loaded and executed by the processor 1101 to implement the operations performed by the server in the above-mentioned seismic data processing method. Of course, the server 1100 may also have components such as a wired or wireless network interface, a keyboard, and input / output interfaces for input and output. The server 1100 may also include other components for implementing device functions, which will not be detailed here.

[0173] In an exemplary embodiment, a computer-readable storage medium is further provided. The computer-readable medium stores at least one program code. The at least one program code is loaded and executed by a processor to implement the seismic data processing method in the above embodiment.

[0174] In an exemplary embodiment, a computer program product is further provided. The computer program product stores at least one program code, and the at least one program code is loaded and executed by a processor to implement the seismic data processing method in the above embodiment.

[0175] 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 may be accomplished by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0176] The above description is only for the purpose of facilitating those skilled in the art to understand the technical solution of this application and is not intended to limit this application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included in the scope of protection of this application.

Claims

1. A seismic data processing method, characterized in that: The method comprises: Acquiring first seismic data of a target work area, where the first seismic data is seismic data in a time-space domain; Based on the first relationship data, the first seismic data is transformed from the spatiotemporal domain to the Ladon domain to obtain second seismic data; wherein the first seismic data includes third seismic data corresponding to different seismic travel times at multiple offsets, and the second seismic data includes fourth seismic data corresponding to different zero-offset travel times at multiple slownesses, and the first relationship data is used to represent the relationship between the seismic travel time and offset in the spatiotemporal domain and the zero-offset travel time and slowness in the Ladon domain; For each zero-offset travel time at each slowness, determining a first weight corresponding to the zero-offset travel time at the slowness; updating, based on the first weight, fourth seismic data corresponding to the zero-offset travel time at the slowness to obtain fifth seismic data; Based on the second relational data, the fifth seismic data is transformed from the Radon domain to the spatiotemporal domain to obtain sixth seismic data; wherein the transformation process represented by the second relational data and the transformation process represented by the first relational data are conjugate processes to each other; Determine loss seismic data based on the first seismic data and the sixth seismic data; wherein the loss seismic data is used to represent energy loss of the first seismic data after Radon forward and inverse transformation; Repeating the step of determining the first weight, and determining seventh seismic data corresponding to the multiple wave based on the updated seismic data corresponding to the zero-offset travel time at the slowness when the lost seismic data meets a preset condition, wherein the seventh seismic data is seismic data in the spatiotemporal domain; The seventh seismic data is removed from the first seismic data.

2. The method according to claim 1, characterized in that Determining a first weight corresponding to the zero-offset traveltime at the slowness includes: determining a total energy corresponding to the slowness based on fourth seismic data corresponding to each zero-offset travel time at the slowness; Based on the total energy corresponding to the slowness and the second relationship data, transforming the fourth seismic data corresponding to the zero-offset travel time at the slowness from the Ladon domain to the spatiotemporal domain to obtain eighth seismic data; determining a second weight corresponding to the zero-offset travel time at the slowness based on the eighth seismic data and the first seismic data; determining a third weight corresponding to the zero-offset travel time at the slowness based on fourth seismic data corresponding to the zero-offset travel time at the slowness and a plurality of fourth seismic data corresponding to the slowness; A product of the second weight and the third weight is determined to obtain the first weight.

3. The method according to claim 2, characterized in that The eighth seismic data includes first seismic sub-data corresponding to a plurality of points, and the first seismic data includes second seismic sub-data corresponding to the plurality of points; The determining, based on the eighth seismic data and the first seismic data, a second weight corresponding to the zero-offset travel time at the slowness includes: Determine the product of the first seismic sub-data and the second seismic sub-data corresponding to each point to obtain a first product value; Determine a sum of the first product values ​​corresponding to the plurality of points to obtain a first sum value; Determine the square of the first seismic sub-data corresponding to each point to obtain a second product value; Determine a sum of the second product values ​​corresponding to the plurality of points to obtain a second sum value; A ratio of the first sum value to the second sum value is determined to obtain the second weight.

4. The method according to claim 2, characterized in that The fourth seismic data includes amplitude; The determining, based on the fourth seismic data corresponding to the zero-offset travel time at the slowness and a plurality of fourth seismic data corresponding to the slowness, a third weight corresponding to the zero-offset travel time at the slowness includes: determining a maximum amplitude from a plurality of amplitudes corresponding to the slowness; determining a ratio of an amplitude corresponding to the zero-offset traveltime at the slowness to the maximum amplitude to obtain a first ratio; determining an absolute value of the first ratio to obtain a second ratio; Determine the e-th power of the second ratio to obtain the third weight; wherein e is a sparse coefficient greater than 0.

5. The method according to claim 2, characterized in that Determining the total energy corresponding to the slowness based on fourth seismic data corresponding to each zero-offset travel time under the slowness includes: Determine the number of sampling points of the seismic trace; The number of sampling points of the seismic trace and the fourth seismic data corresponding to each zero-offset travel time under the slowness are substituted into the third relationship data to obtain the total energy corresponding to the slowness; wherein the third relationship data is used to represent the relationship between the total energy corresponding to each slowness and the fourth seismic data corresponding to each zero-offset travel time under each slowness.

6. The method according to claim 1, characterized in that The updating, based on the first weight, of the fourth seismic data corresponding to the zero-offset travel time at the slowness to obtain the fifth seismic data includes: determining a product of fourth seismic data corresponding to the zero-offset travel time at the slowness and the first weight to obtain ninth seismic data; The sum of the fourth seismic data and the ninth seismic data is determined to obtain the fifth seismic data.

7. The method according to claim 1, characterized in that Determining seventh seismic data corresponding to multiple waves based on the updated seismic data corresponding to the zero-offset travel time at the slowness includes: Determining tenth seismic data of the target work area based on updated seismic data corresponding to the zero-offset travel time at the slowness, wherein the tenth seismic data is seismic data of the Ladong domain; Based on the tenth seismic data, predicting an eleventh seismic data corresponding to the multiple wave; Based on the second relationship data, the eleventh seismic data is transformed from the Ladon domain to the spatiotemporal domain to obtain the seventh seismic data.

8. A seismic data processing device, characterized in that: The device comprises: An acquisition module, configured to acquire first seismic data of a target work area, wherein the first seismic data is seismic data in a time-space domain; a first transformation module for transforming the first seismic data from the spatiotemporal domain to the Ladon domain based on first relationship data to obtain second seismic data; wherein the first seismic data includes third seismic data corresponding to different seismic travel times at multiple offsets, the second seismic data includes fourth seismic data corresponding to different zero-offset travel times at multiple slownesses, and the first relationship data is used to represent the relationship between the seismic travel time and offset in the spatiotemporal domain and the zero-offset travel time and slowness in the Ladon domain; a first determining module, configured to determine, for each zero-offset travel time at each slowness, a first weight corresponding to the zero-offset travel time at the slowness; An updating module, configured to update, based on the first weight, fourth seismic data corresponding to the zero-offset travel time at the slowness to obtain fifth seismic data; a second transformation module, configured to transform the fifth seismic data from the Radon domain to the spatiotemporal domain based on the second relational data to obtain sixth seismic data; wherein the transformation process represented by the second relational data and the transformation process represented by the first relational data are conjugate processes to each other; A second determining module is configured to determine lost seismic data based on the first seismic data and the sixth seismic data; wherein the lost seismic data is used to represent energy loss of the first seismic data after undergoing Radon forward and inverse transformation; a third determining module, configured to repeatedly perform the step of determining the first weight, and determine seventh seismic data corresponding to the multiple wave based on the updated seismic data corresponding to the zero-offset travel time at the slowness when the lost seismic data meets a preset condition, wherein the seventh seismic data is seismic data in the spatiotemporal domain; A removal module is used to remove the seventh seismic data from the first seismic data.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one program code, and the at least one program code is loaded and executed by the processor to implement the seismic data processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores at least one program code, and the at least one program code is loaded and executed by a processor to implement the seismic data processing method according to any one of claims 1 to 7.

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