Method and device for multiple wave suppression of multi-component converted wave data of seabed node

Abstract

This application provides a method and apparatus for suppressing multiples in multi-component converted wave data from seabed nodes, belonging to the field of seabed seismic data acquisition and processing technology. The method includes: performing migration imaging on downlink multiple data of converted wave data to obtain seabed information; constructing a Green's function for effective seabed reflection based on the seabed information; suppressing water layer multiples in actual seismic data based on the Green's function; and suppressing free surface multiples in the actual seismic data after water layer multiple suppression based on the effective waves obtained from the back migration, thereby obtaining the target seismic data. This application's solution can improve the suppression effect of multiples.

Description

Technical Field

[0001] This application relates to the field of submarine seismic data acquisition and processing technology, specifically to a method and apparatus for suppressing multiples of multi-component converted wave data from submarine nodes. Background Technology

[0002] Currently, the non-coplanarity of shot and receiver points, the large number of data components, and the complexity of waveform recording in OBN (Ocean Bottom Node) data lead to certain limitations in conventional towed cable seismic multiple wave suppression methods.

[0003] In existing technologies, surface-correlated multiple suppression is the most commonly used multiple suppression method for towed seismic data. This method is entirely data-driven, using the data itself to predict the multiple model, and then using matched filtering technology to subtract the multiples from the original seismic data, thereby achieving the purpose of multiple suppression.

[0004] However, conventional surface-correlated wave suppression methods are ineffective at suppressing wave multiples. Furthermore, existing methods also perform poorly in suppressing wave multiples in shallow water data. Therefore, improving wave multiple suppression remains an unresolved issue. Summary of the Invention

[0005] The purpose of this application is to provide a method and apparatus for suppressing multiples in multi-component converted wave data of seabed nodes, which can solve the problem of poor suppression effect of multiples in the prior art.

[0006] In a first aspect, embodiments of this application provide a method for suppressing multiple wave data of multi-component converted wave data at seabed nodes, the method comprising:

[0007] Migration imaging was performed on downlink multiple wave data of converted wave data to obtain seabed information;

[0008] Based on seabed information, a Green's function for effective seabed reflection is constructed, and water layer multiples in actual seismic data are suppressed based on the Green's function.

[0009] Based on the effective waves obtained from the inverse migration, the free surface multiples in the actual seismic data after water layer multiple suppression are suppressed to obtain the target seismic data.

[0010] In one possible implementation of the first aspect, before performing migration imaging on the downlink multiple data of the converted wave data, the method further includes: performing wave merging based on the P-component and Z-component at the source end to generate downlink multiple data.

[0011] In one possible implementation of the first aspect, downlink multiple wave data of converted wave data are used for migration imaging to acquire seabed information, including:

[0012] Based on downlink multiple wave data, a model of the shot point location and the mirror image location of the receiver point is constructed, and a mirror image velocity model is also constructed. Based on the location model and the mirror image velocity model, and according to the shot point end travel time and receiver end travel time of the downlink wave, Koschkhov pre-stack depth migration is performed to obtain the seabed model.

[0013] The seabed model is processed by a reference surface to obtain a seabed model with a reference surface; seabed information is obtained based on the seabed model with a reference surface.

[0014] In one possible implementation of the first aspect, the method further includes, prior to performing the Koschhof pre-stack depth migration, calculating the shot-end travel time and the receiver-end travel time.

[0015] In one possible implementation of the first aspect, after constructing a Green's function for effective seabed reflection based on seabed information, the method further includes: recovering and reconstructing the effective reflection based on the Green's function.

[0016] In one possible implementation of the first aspect, suppression of water layer multiples in actual seismic data based on the Green's function includes:

[0017] The Green's function is convolved with the original multi-component seismic gather data to obtain the water layer multiples prediction model; the multiples of the source end P component predicted based on the water layer multiples prediction model are adaptively removed from the actual seismic data.

[0018] In one possible implementation of the first aspect, based on the effective waves obtained from the inverse migration, the free surface multiples in the actual seismic data after water layer multiple suppression are suppressed, including:

[0019] The effective waves are obtained by back-migrating the actual seismic data after water layer multiple suppression; the effective waves of the P-wave P component and the effective waves of the converted wave R component of the original multi-component seismic gather data are convolved to obtain the free surface multiple prediction model; the free surface multiples predicted based on the free surface multiple prediction model are adaptively removed from the actual seismic data after water layer multiple suppression.

[0020] In one possible implementation of the first aspect, the method further includes: performing quality control based on gather data, overlay data, and autocorrelation of overlay profiles.

[0021] Secondly, embodiments of this application provide a device for suppressing multiple wave data of a seabed node multi-component converted wave, the device comprising:

[0022] The acquisition unit is used to perform offset imaging on the downlink multiple wave data of the converted wave data to acquire seabed information;

[0023] The first suppression unit is used to construct the Green's function for effective seabed reflection based on seabed information, and to suppress water layer multiples in actual seismic data based on the Green's function.

[0024] The second suppression unit is used to suppress the free surface multiples in the actual seismic data after water layer multiple suppression, based on the effective waves obtained by inverse migration, to obtain the target seismic data.

[0025] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for suppressing multiple waves of multi-component converted wave data at seabed nodes as described in any of the first aspects above.

[0026] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for suppressing multiple wave data of multi-component converted wave data at a seabed node as described in any of the first aspects above.

[0027] Fifthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to execute the seabed node multi-component converted wave data multiple wave suppression method described in any of the first aspects above.

[0028] This application first obtains seabed information by performing migration imaging on downlink multiple data, then constructs a Green's function for effective seabed reflection, and suppresses water layer multiples in actual seismic data based on the Green's function. Finally, it suppresses free surface multiples in actual seismic data after water layer multiple suppression based on the effective waves obtained by inverse migration, thus obtaining seismic data with suppressed multiples.

[0029] This application proposes a solution that improves the suppression of multiple waves in shallow water data by constructing a Green's function for effective reflection. By using effective waves to suppress multiple waves on free surfaces, the suppression effect of multiple waves on free surfaces can be improved, and the solution is highly user-friendly and practical.

[0030] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the steps of the method for suppressing multiple wave data of seabed nodes provided in the embodiments of this application;

[0033] Figure 2 This is a schematic diagram of the multiple wave model of the OBN multi-component converted wave seismic data provided in this application.

[0034] Figure 3 This is a schematic diagram of the shot point location and receiver point mirror image location model provided in this application.

[0035] Figure 4 This is a schematic diagram of the mirror velocity model provided in this application.

[0036] Figure 5 This is a schematic diagram of the seabed model provided in this application.

[0037] Figure 6 This is a schematic diagram of the original shallow water wavefront multi-component seismic gather data provided in this application.

[0038] Figure 7 This is a schematic diagram of the water layer multiple wave prediction model provided in this application;

[0039] Figure 8 This is a schematic diagram of the gather data after multiple wave suppression of the water layer provided in this application.

[0040] Figure 9 This is a schematic diagram showing the difference in gather data before and after water layer multiple wave suppression provided in this application.

[0041] Figure 10 This is a schematic diagram of the superimposed wavefront profile of shallow water depletion provided in this application.

[0042] Figure 11 This is a schematic diagram of the superimposed cross-section after the removal of multiple waves in shallow water provided in this application.

[0043] Figure 12 This is a schematic diagram of the difference between the superimposed profiles before and after shallow water demultiplexing provided in this application.

[0044] Figure 13 This is a schematic diagram of the autocorrelation of multiple wavefront superposition profiles in shallow water provided in this application.

[0045] Figure 14 This is a schematic diagram of the autocorrelation of the superimposed profile after shallow water multiple wave removal provided in this application.

[0046] Figure 15 This is a schematic diagram of the spectral analysis of the shallow and deep layers of the superimposed profile before and after the shallow water multiple wave removal provided in this application.

[0047] Figure 16 This is a schematic diagram of the free surface-correlated multiple wave suppression front gather data provided in this application.

[0048] Figure 17 This is a schematic diagram of the free surface multiple wave prediction model provided in this application.

[0049] Figure 18 This is a schematic diagram of the gather data after free surface-correlated multiple wave suppression provided in this application.

[0050] Figure 19 This is a schematic diagram of the difference in gather data before and after free surface correlated multiple wave suppression provided in this application.

[0051] Figure 20 This is a schematic diagram of the superimposed cross-section before the suppression of free surface correlated multiple waves provided in the embodiments of this application;

[0052] Figure 21 This is a schematic diagram of the superimposed cross-section after suppression of correlated multiple waves on a free surface provided in an embodiment of this application;

[0053] Figure 22 This is a schematic diagram of the superimposed profile difference before and after free surface correlated multiple wave suppression provided in the embodiments of this application;

[0054] Figure 23 This is a schematic diagram of autocorrelation of the superimposed profile before suppression of free surface correlated multiple waves provided in the embodiments of this application;

[0055] Figure 24 This is a schematic diagram of the autocorrelation of the superimposed profile after suppression of free surface correlated multiple waves provided in the embodiments of this application;

[0056] Figure 25 This is a schematic diagram of the spectral analysis of the superimposed profiles before and after the suppression of free surface correlated multiple waves provided in this application.

[0057] Figure 26 This is a schematic diagram of the overall structure of the multi-component converted wave data multiple suppression device for seabed nodes provided in this application embodiment;

[0058] Figure 27 This is a schematic diagram of the specific structure of the multi-component converted wave data multiple suppression device for seabed nodes provided in the embodiments of this application;

[0059] Figure 28 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0060] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0061] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or photovoltaic modules, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, photovoltaic modules and / or combinations thereof.

[0062] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0063] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0064] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [the described condition or event] is detected," or "in response to detection of [the described condition or event]."

[0065] Furthermore, in the description of this application, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0066] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in some other embodiments," "in other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0067] Currently, the non-coplanarity of shot-receiver points, the large number of data components, and the complexity of waveform recording in OBN data lead to certain limitations in conventional towed cable seismic multiple wave suppression methods.

[0068] In existing technologies, surface-correlated multiple suppression is the most commonly used multiple suppression method for towed seismic data. This method is entirely data-driven, using the data itself to predict the multiple model, and then using matched filtering techniques to subtract the multiples from the original seismic data, thereby achieving the purpose of multiple suppression. The premise of this method is that the shot point and the receiver point (sensor point) are on the same horizontal plane and have effective primary reflection information with a small offset.

[0069] In actual OBN data, the surface-correlated multiple suppression method will face many problems: (1) OBN is a special observation system with the source on the sea surface and the receiver on the seabed. The two are not coplanar, which does not conform to the principle of surface-correlated multiple suppression; (2) The receivers of OBN seismic data acquisition are sparsely distributed, which makes it difficult to meet the requirements of surface-correlated multiple suppression for predicting multiples.

[0070] (3) In shallow water environments, the incident angle of seismic waves quickly reaches the critical angle, and when the seismic waves propagate to the seabed, they will generate refracted waves, which will result in a lack of effective primary reflection information; (4) Marine seismic data usually lacks near-offset data. In this case, conventional surface-correlated multiple suppression methods can no longer achieve good suppression effects.

[0071] Furthermore, for multi-component OBN data, the suppression of multiples of converted waves differs from that of P-waves. OBN converted wave seismic data is significantly affected by the seafloor and free surface boundaries, resulting from water reverberation and elastic mode conversion on the seafloor.

[0072] Most of the seabed is covered by consolidated soft sediments with high Poisson's ratios and increasing P-wave velocities with depth. Simultaneously, due to consolidation, the porosity of these sediments decreases rapidly with depth, while their density increases.

[0073] The average reflection and transmission coefficients of longitudinal and transverse waves at the precritical angle were calculated using the linearized Zoeppritz equation. The analysis results show that the conversion coefficient of the converted wave is very small, indicating that the conversion at the bottom of the water is weak.

[0074] Since shear waves cannot propagate in water, and interlayer multiples of converted waves are negligible in most cases, the multiples in converted wave data are mainly generated by the mixing and reverberation of P-waves at the source. These multiples generally satisfy specific mathematical relationships, and the first-order multiples include water-related and long-period P-wave multiples.

[0075] The presence of multiples at the source end in converted wave data has a significant impact on converted wave data processing. Since the velocity of shear waves is much lower than that of p-waves, it is difficult to remove converted wave multiples using velocity-based methods (such as the Radon transform method).

[0076] Although some studies and methods have proposed removing multiples from OBN PS (P for P-wave, S for S-wave, PS for converted P-wave) data associated with the free surface, processing shallow water data remains challenging, and the suppression effect on multiples in shallow water data is poor. Therefore, how to improve the suppression effect of multiples remains an unsolved problem.

[0077] To address the aforementioned deficiencies, this application provides a method for suppressing multiples in multi-component converted wave data from seafloor nodes. First, seafloor information is obtained by migrating and imaging the downlink multiples data. Then, a Green's function for effective seafloor reflection is constructed. Based on the Green's function, water layer multiples in the actual seismic data are suppressed. Finally, based on the effective waves obtained from the inverse migration, free surface multiples in the actual seismic data after water layer multiple suppression are suppressed, resulting in seismic data with suppressed multiples.

[0078] This application's solution improves the suppression effect of multiple waves in shallow water data by constructing a Green's function for effective reflection. It utilizes effective waves (effective primary reflection information with small offset) to suppress multiple waves on free surfaces, thereby enhancing the suppression effect of multiple waves on free surfaces. It is highly user-friendly and practical.

[0079] The specific process implemented in this application is described below through specific embodiments.

[0080] Please see Figure 1 , Figure 1This is a schematic diagram illustrating the steps of the multi-component converted wave data multiple suppression method for seabed nodes provided in this application embodiment. For example... Figure 1 As shown, the method may include the following steps:

[0081] S101 performs migration imaging on the downlink multiple wave data of the converted wave data to obtain seabed information.

[0082] In some embodiments, downlink multiple migration imaging can acquire precise seabed structures and obtain seabed features. Although downlink wave data consists of multiples, they differ from the significant waves only in travel time. Mirror migration of downlink waves can improve the imaging accuracy of shallow seawater while obtaining a wider illumination range.

[0083] In one embodiment, the seabed structure is first obtained using the downwave mirror offset method, and the seabed reflectivity is acquired to construct a multiple wave model. Then, the multiple waves are suppressed. Figure 2 This is a schematic diagram of the multiple wave model of the OBN multi-component converted wave seismic data provided in this application, as shown below. Figure 2 As shown, Source is the shot point that receives seismic waves, Receiver is the receiving point that receives reflected seismic waves, Free surface is the free surface, and Sea floor is the seabed. Figure 2 As shown in Figure (a), the converted wave is PS, as... Figure 2 As shown in Figures (b) and (c), the converted wave is PPPS.

[0084] According to one embodiment of this application, before performing migration imaging on the downlink multiple data of the converted wave data, the method may further include the following steps: performing wave merging based on the P component and Z component at the source end to generate downlink multiple data.

[0085] In this dataset, the source end is the shot point, the P component is the pressure component of the P-wave from the original multi-component seismic gather data, and the Z component is the vertical component. The P and Z components are two components acquired by OBN, both collecting P-wave data. The difference lies in that the P component is located in the seawater and receives the pressure information of the P-wave, while the Z component is located in the seafloor strata and receives the velocity or acceleration information of the seafloor strata.

[0086] According to one embodiment of this application, performing migration imaging on downlink multiple wave data of converted wave data to obtain seabed information may include the following steps:

[0087] Based on downlink multiple wave data, image models of the shot point location and receiver location are constructed, along with an image velocity model. Based on these models, and according to the shot-end travel time and receiver-end travel time of the downlink waves, Koschkhov pre-stack depth migration is performed to obtain a seabed model. The seabed model is then processed using a reference plane to obtain a reference-plane-processed seabed model. Seabed information is then obtained based on this reference-plane-processed seabed model.

[0088] In some embodiments, datum plane correction of the seabed model can eliminate errors caused by the elevation difference between the shot point and the receiver point. Figure 3 This is a schematic diagram of the shot point location and receiver point mirror image location model provided in this application, showing the torsional information of multiple wave migration imaging. The upper red line represents the receiver point location, and the lower yellow line represents the shot point location.

[0089] It should be noted that, Figure 3 The image showing the shot point and receiver mirror positions is used to modify the positions of the shot point and receiver to obtain a better seabed model. In seismic data acquired by OBN, direct waves can be used to correct the positions of the shot point and receiver.

[0090] In some embodiments, Figure 4 This is a schematic diagram of the mirror velocity model provided in this application. The biggest difference from the conventional effective signal offset is that the depth has shifted downward by 200m, and the velocity of the seawater above 200m is filled. Figure 5 This is a schematic diagram of the seabed model provided in this application, showing the accurate seabed model obtained by downlink multiple migration.

[0091] According to one embodiment of this application, before performing Koschhof pre-stack depth migration, the method may further include the following steps: calculating the shot point end travel time and the receiver point end travel time.

[0092] S102, construct the Green's function for effective seabed reflection based on seabed information, and suppress water layer multiples in actual seismic data based on the Green's function.

[0093] In one embodiment, Figure 6 This is a schematic diagram of the original shallow water wavefront multi-component seismic gather data provided in this application.

[0094] According to one embodiment of this application, after constructing the Green's function for effective seabed reflection based on seabed information, the method may further include the following steps: recovering and reconstructing the effective reflection based on the Green's function. Here, the Green's function represents the propagation path of the effective seabed reflection.

[0095] In existing technologies, the OBN shot point and receiver point are not on the same horizontal plane. This embodiment can make the shot point and receiver point lie on the same horizontal plane by restoring and reconstructing effective reflections.

[0096] According to one embodiment of this application, suppressing water layer multiples in actual seismic data based on the Green's function may include the following steps:

[0097] The Green's function is convolved with the original multi-component seismic gather data to obtain the water layer multiple prediction model. Multiples of the P-component at the source end predicted based on the water layer multiple prediction model are adaptively removed from the actual seismic data.

[0098] In one embodiment, a water layer multiples prediction model can be used to predict the multiples of the P component at the source end, and the multiples of the P component can be adaptively subtracted from the actual seismic data to suppress the water layer multiples.

[0099] In some embodiments, Figure 7 This is a schematic diagram of the water layer multiple wave prediction model provided in this application. Figure 8 This is a schematic diagram of the gather data after multiple wave suppression of the water layer provided in this application. Figure 9 This is a schematic diagram showing the difference in gather data before and after multiple wave suppression of the water layer provided in this application.

[0100] In some embodiments, Figure 10 This is a schematic diagram of the superimposed wavefront profile of shallow water provided in this application. Figure 10 This allows us to obtain superimposed data of multiple wavefronts in shallow water. Figure 11 This is a schematic diagram of the superimposed cross-section after shallow water wave removal provided in this application. Figure 11 The superimposed data after multiple waves in shallow water can be obtained. Figure 12 This is a schematic diagram illustrating the difference between the superimposed profiles before and after shallow water demultiplexing provided in this application. Figure 12 The difference between the superimposed data before and after the shallow water outburst can be obtained.

[0101] In some embodiments, Figure 13 This is a schematic diagram of the autocorrelation of multiple wavefront stacking profiles in shallow water provided in this application, with a time window of 500–2500 ms. Figure 14 This is a schematic diagram of the autocorrelation of shallow water multiple wave removal and superimposed profiles provided in this application, with a time window of 500–2500 ms. From Figure 13 and Figure 14 It can be seen that the autocorrelation of the superimposed profile weakens before and after shallow water multiple wave suppression.

[0102] In one embodiment, Figure 15This is a schematic diagram of the spectral analysis of the shallow and deep layers in the superimposed profile before and after multiple wavelet removal in shallow water, provided in this application. (See attached diagram.) Figure 15 As shown, the gray line represents the spectrum before shallow water demultiplexing, and the blue line represents the spectrum after shallow water demultiplexing. Both the shallow and deep windows display one spectrum before and one spectrum after shallow water demultiplexing.

[0103] from Figure 15 As can be seen, before multiple wave removal, the seismic data spectrum fluctuated (due to multiple wave interference), but after multiple wave removal, the seismic data spectrum became smooth. Therefore, this method has a good multiple wave removal effect.

[0104] It should be noted that since the constructed Green's function only represents the propagation path of the effective reflection from the seabed, the prediction obtained after convolution with the original data is only the multiple waves related to the water layer. After the adaptive subtraction process, it can only attenuate the multiple waves related to the water layer, but cannot attenuate the multiple waves generated by the seabed strata.

[0105] Therefore, by suppressing free surface multiples based on effective waves, seismic data with most multiples attenuated is obtained. Free surface multiples are those generated by the seafloor strata.

[0106] S103, based on the effective waves obtained by inverse migration, suppresses the free surface multiples in the actual seismic data after water layer multiple suppression, to obtain the target seismic data.

[0107] According to one embodiment of this application, suppressing free surface multiples in actual seismic data after water layer multiple suppression, based on the effective waves obtained by back migration, may include the following steps:

[0108] Inverse migration was performed on the actual seismic data after water-layer multiple suppression to obtain the effective waves. The effective waves of the P-wave P-component and the effective waves of the converted wave R-component of the original multi-component seismic gather data were convolved to obtain the free-surface multiple prediction model. The free-surface multiples predicted based on the free-surface multiple prediction model were adaptively removed from the actual seismic data after water-layer multiple suppression.

[0109] In some embodiments, the R component is a radial component used to receive radial vibration information of seismic waves. Based on the free-surface multiple prediction model, free-surface multiples can be predicted. The free-surface multiples are adaptively subtracted from the actual seismic data after water layer multiple suppression, thereby suppressing the free-surface multiples.

[0110] In some embodiments, Figure 16 This is a schematic diagram of the free surface-correlated multiple wave suppression front gather data provided in this application. Figure 17This is a schematic diagram of the free surface multiple prediction model provided in this application. Because the water layer multiple suppression basically removes most of the multiples, there are relatively few residual multiples here.

[0111] In some embodiments, Figure 18 This is a schematic diagram of the gather data after free surface correlation multiple wave suppression provided in this application. Figure 19 This is a schematic diagram of the difference in gather data before and after free surface correlated multiple wave suppression provided in this application. Figure 19 Basic and Figure 17 Consistent.

[0112] According to one embodiment of this application, the method may further include the following steps: performing quality control based on gather data, overlay data, and autocorrelation of overlay profiles.

[0113] In some embodiments, by observation Figures 16-19 Changes before and after can be quality controlled based on either shot gather data or line gather data. Shot gather data and line gather data are the same type of data but reside in different domains. Shot gather data is multi-component shot gather seismic data, a dataset formed by arranging data emitted from the shot point to all receiver points. Line gather data is multi-component line gather seismic data, a dataset formed by arranging data received by all receiver points from the shot point.

[0114] In other embodiments, Figure 20 This is a schematic diagram of the superimposed cross-section before the suppression of correlated multiple waves on a free surface, provided in an embodiment of this application. Figure 21 This is a schematic diagram of the superimposed cross-section after suppression of correlated multiple waves on a free surface, provided in an embodiment of this application. Figure 22 This is a schematic diagram of the superimposed profile difference before and after free surface correlated multiple wave suppression provided in an embodiment of this application. By observation... Figures 20-22 The changes before and after can be used for quality control based on the superimposed data.

[0115] In other embodiments, Figure 23 This is a schematic diagram of autocorrelation of the superimposed profile before suppression of free surface correlated multiple waves, provided in an embodiment of this application, with a time window of 2300–3500 ms. Figure 24 This is a schematic diagram of the autocorrelation of a superimposed profile after suppression of free surface correlated multiple waves, provided in an embodiment of this application, with a time window of 2300–3500 ms. Through observation… Figure 13 and Figure 14 Changes before and after, or Figure 23 and Figure 24 The changes before and after were analyzed by autocorrelation, and quality control was carried out based on the autocorrelation of the superimposed profile.

[0116] In one embodiment, Figure 25This is a schematic diagram of the spectral analysis of the superimposed profiles before and after the suppression of correlated multiple waves on a free surface provided in this application. For example... Figure 25 As shown, the gray line represents the spectrum before surface-dependent multiple attenuation, and the blue line represents the spectrum after surface-dependent multiple attenuation. The shallow and deep windows each display one spectrum before and one spectrum after surface-dependent multiple attenuation.

[0117] from Figure 25 As can be seen, before multiple wave removal, the seismic data spectrum fluctuated (due to multiple wave interference), while after multiple wave removal, the seismic data spectrum became slightly smoother. Therefore, this method achieves good multiple wave removal performance.

[0118] It should be noted that, Figure 15 and Figure 25 Spectrum analysis is also a quality control method.

[0119] This application provides a method for suppressing multiples in multi-component converted wave data of seabed nodes. First, seabed information is obtained by migrating and imaging the downlink multiple data. Then, a Green's function for effective seabed reflection is constructed. Based on the Green's function, water layer multiples in the actual seismic data are suppressed. Finally, based on the effective waves obtained by inverse migration, free surface multiples in the actual seismic data after water layer multiple suppression are suppressed, resulting in seismic data with suppressed multiples.

[0120] This application's solution, by constructing a Green's function for effective reflection, can improve the suppression effect of multiple waves in shallow water data. By utilizing effective waves (effective primary reflection information with small offsets) to suppress multiple waves on free surfaces, it can enhance the suppression effect of multiple waves on free surfaces. It can fully utilize the multi-component data information of OBN data, achieving excellent application results in the output data. It effectively suppresses multiple wave noise, broadens the effective frequency band range of the data to a certain extent, enriches the information of different frequency bands on the profile, improves the resolution, and has strong usability and practicality.

[0121] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0122] Corresponding to the method in the above embodiments, Figure 26 This is a schematic diagram of the overall structure of the multi-component converted wave data multiple suppression device for seabed nodes provided in this application embodiment. For ease of explanation, only the parts relevant to this application embodiment are shown.

[0123] See Figure 26 The device includes:

[0124] Acquisition unit 261 is used to perform offset imaging on downlink multiple wave data of converted wave data to acquire seabed information;

[0125] The first suppression unit 262 is used to construct the Green function of effective seabed reflection based on seabed information, and to suppress water layer multiples in actual seismic data based on the Green function.

[0126] The second suppression unit 263 is used to suppress the free surface multiples in the actual seismic data after water layer multiple suppression based on the effective waves obtained by reverse migration, so as to obtain the target seismic data.

[0127] Please see Figure 27 , Figure 27 This is a schematic diagram of the specific structure of the multi-component converted wave data multiple suppression device for seabed nodes provided in this application embodiment. For example... Figure 27 As shown, the device also includes a merging unit 264. The merging unit 264 is used to merge waves based on the P-components and Z-components at the source end to generate downlink multiple wave data.

[0128] Please continue reading Figure 27 According to one embodiment of this application, the acquisition unit 261 includes: a modeling module 2612, an offset module 2614, and a reference surface processing module 2616.

[0129] Modeling module 2612 is used to construct image models of the shot point location and receiver location based on downlink multiple wave data, and to construct an image velocity model. Migration module 2614 is used to perform Koschkhov pre-stack depth migration based on the location model and image velocity model, and according to the shot point end travel time and receiver end travel time of the downlink wave, to obtain the seabed model.

[0130] The datum surface processing module 2616 is used to perform datum surface processing on the seabed model to obtain the datum surface-processed seabed model, and to obtain seabed information based on the datum surface-processed seabed model.

[0131] Please continue reading Figure 27 According to one embodiment of this application, the offset module 2614 is also used to calculate the shot point end travel time and the receiver point end travel time.

[0132] Please continue reading Figure 27 According to one embodiment of this application, the first suppression unit 262 is also used to recover and reconstruct effective reflections based on the Green's function.

[0133] Please continue reading Figure 27 According to one embodiment of this application, the first suppression unit 262 includes: a first multiple wave generation module 2622 and a first adaptive subtraction module 2624.

[0134] The first multiple generation module 2622 is used to convolve the Green's function with the original multi-component seismic gather data to obtain the water layer multiple prediction model. The first adaptive subtraction module 2624 is used to adaptively remove the multiples of the source end P component predicted based on the water layer multiple prediction model from the actual seismic data.

[0135] Please continue reading Figure 27 According to one embodiment of this application, the second suppression unit 263 includes: an anti-offset module 2632, a second multiple wave generation module 2634, and a second adaptive subtraction module 2636.

[0136] The reverse migration module 2632 is used to reverse migrate the actual seismic data after water layer multiple suppression to obtain the effective waves. The second multiple generation module 2634 is used to convolve the effective waves of the P-wave P-component and the effective waves of the converted wave R-component of the original multi-component seismic gather data to obtain the free surface multiple prediction model.

[0137] The second adaptive subtraction module 2636 is used to adaptively remove the free surface multiples predicted based on the free surface multiples prediction model from the actual seismic data after water layer multiples suppression.

[0138] Please continue reading Figure 27 According to one embodiment of this application, the device further includes a quality control unit 265, which is used to perform quality control based on gather data, stacked data, and autocorrelation of stacked profiles. The quality control unit 265 is also used to perform spectrum analysis.

[0139] Please continue reading Figure 27 According to one embodiment of this application, the device further includes a superposition unit 266, which is used to superimpose data generated during the multiple wave suppression process.

[0140] It should be noted that the calculations and derivations not elaborated in detail in all the above embodiments can basically be performed using existing software. Even if no software is available, these calculations and derivations can be performed using existing methods. Furthermore, this method can be implemented as a module of a multi-component converted wave data multiple suppression device for seabed nodes, or its functionality can be added to an existing module of a multi-component converted wave data multiple suppression device for seabed nodes.

[0141] It should be further noted that noise attenuation processing, migration processing, and other methods are generally used in seismic data processing. The order of these methods with the specific steps in the embodiments of this application is not specifically limited in this application. Those skilled in the art can make flexible adjustments based on the existing technology.

[0142] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0143] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0144] Please see Figure 28 , Figure 28 This is a schematic diagram of the structure of the electronic device 28 provided in an embodiment of this application. Figure 28 As shown, the electronic device 28 of this embodiment includes: at least one processor 281 ( Figure 28 Only one is shown in the diagram), memory 283, and computer program 282 stored in memory 283 and executable on at least one processor 281, wherein processor 281 executes computer program 282 to implement the steps in the above method embodiments.

[0145] Electronic device 28 can be a desktop computer, laptop, PDA, or mobile phone, etc. This electronic device 28 may include, but is not limited to, a processor 281 and a memory 283. Those skilled in the art will understand that... Figure 28 This is merely an example of electronic device 28 and does not constitute a limitation on electronic device 28. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0146] The processor 281 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware photovoltaic modules, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0147] In some embodiments, memory 283 may be an internal storage unit of electronic device 28, such as a hard disk or memory of electronic device 28. In other embodiments, memory 283 may be an external storage device of electronic device 28, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on electronic device 28. Furthermore, memory 283 may include both internal and external storage units of electronic device 28. Memory 283 is used to store operating system, application programs, boot loader, data, and other programs, such as program code of computer programs. Memory 283 may also be used to temporarily store data that has been output or will be output.

[0148] If the integrated units described above are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, when implementing all or part of the processes in the methods of the above embodiments of this application, it can be accomplished by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps applied to the method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include at least: any entity or device capable of carrying computer program code to a computing device / electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, such as a USB flash drive, a portable hard drive, a magnetic disk, or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable storage media cannot be electrical carrier signals or telecommunication signals.

[0149] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the various method embodiments described above.

[0150] This application provides a computer program product that, when run on an electronic device, causes the electronic device to execute the steps described in the various method embodiments above.

[0151] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0152] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0153] In the embodiments provided in this application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. The device / electronic device embodiments described above are merely illustrative, and the division of modules or units described above is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple units or photovoltaic modules may be combined or integrated into another system, and some features may be ignored. Furthermore, the indirect coupling, direct coupling, or communication connection shown or discussed may be through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0154] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0155] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the above embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for suppressing multiple wave data from multi-component converted wave data at seabed nodes, characterized in that, The method includes: Migration imaging was performed on downlink multiple wave data of converted wave data to obtain seabed information; Based on the seabed information, a Green's function for effective seabed reflection is constructed, and water layer multiples in actual seismic data are suppressed based on the Green's function. Based on the effective waves obtained from the inverse migration, the free surface multiples in the actual seismic data after water layer multiple suppression are suppressed to obtain the target seismic data.

2. The method for suppressing multiple wave data of multi-component converted wave at seabed nodes according to claim 1, characterized in that, Before performing migration imaging on the downlink multiple wave data of the converted wave data, the method further includes: The downlink multiple wave data are generated by combining the P and Z components at the source end.

3. The method for suppressing multiple wave data of multi-component converted wave at seabed nodes according to claim 1, characterized in that, Migration imaging is performed on downlink multiple wave data from converted wave data to obtain seabed information, including: Based on the downlink multiple wave data, a model of the shot point location and the mirror image location of the receiver point is constructed, and a model of the mirror image velocity is also constructed. Based on the position model and the mirror velocity model, and according to the shot-end travel time and receiver-end travel time of the downlink wave, Koschkhov pre-stack depth migration is performed to obtain the seabed model. The seabed model is subjected to datum surface processing to obtain the seabed model after datum surface processing; The seabed information is obtained based on the seabed model processed from the reference surface.

4. The method for suppressing multiple waves of multi-component converted wave data at seabed nodes according to claim 3, characterized in that, Prior to performing the Koschhof pre-stack depth migration, the method further includes: Calculate the travel time at the shot point and the travel time at the receiver point.

5. The method for suppressing multiple wave data of multi-component converted wave at seabed nodes according to claim 1, characterized in that, After constructing the Green's function for effective seabed reflection based on the seabed information, the method further includes: Effective reflections are recovered and reconstructed based on the Green's function.

6. The method for suppressing multiple wave data of multi-component converted wave at seabed nodes according to claim 1, characterized in that, Suppressing water layer multiples in actual seismic data based on the Green's function includes: The Green's function is convolved with the original multi-component seismic gather data to obtain the water layer multiple wave prediction model. Multiples of the source P component predicted based on the water layer multiple prediction model are adaptively removed from the actual seismic data.

7. The method for suppressing multiple wave data of multi-component converted wave at seabed nodes according to claim 6, characterized in that, Based on the effective waves obtained from the inverse migration, the free surface multiples in the actual seismic data after water layer multiple suppression are suppressed, including: The effective wave is obtained by inverse migration of the actual seismic data after suppression by multiple waves from the water layer; The effective wave of the P-wave component of the original multi-component seismic gather data is convolved with the effective wave of the R-wave component of the converted wave to obtain a free surface multiple wave prediction model. The free surface multiples predicted based on the free surface multiples prediction model are adaptively removed from the actual seismic data after water layer multiples suppression.

8. The method for suppressing multiple wave data of multi-component converted wave data at seabed nodes according to any one of claims 1-7, characterized in that, The method further includes: Quality control is performed based on gather data, overlay data, and autocorrelation of overlay profiles.

9. A device for suppressing multiple wave data from a seabed node multi-component converted wave, characterized in that, The device includes: The acquisition unit is used to perform offset imaging on the downlink multiple wave data of the converted wave data to acquire seabed information; The first suppression unit is used to construct a Green's function for effective seabed reflection based on the seabed information, and to suppress water layer multiples in actual seismic data based on the Green's function. The second suppression unit is used to suppress the free surface multiples in the actual seismic data after water layer multiple suppression, based on the effective waves obtained by inverse migration, to obtain the target seismic data.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for suppressing multiple wave data of seabed node multi-component converted wave data as described in any one of claims 1-8.

11. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for suppressing multiple wave data of seabed node multi-component converted wave data as described in any one of claims 1-8.

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