Offset noise suppression method and device, electronic equipment and storage medium
By using orthogonal polynomial decomposition and weighted summation, the reflected wave and migration noise are decomposed into sub-profiles of different orders, which solves the problem of migration noise affecting imaging accuracy and achieves reflected wave imaging with a higher signal-to-noise ratio.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA PETROLEUM & CHEMICAL CORP
- Filing Date
- 2024-11-12
- Publication Date
- 2026-05-12
AI Technical Summary
During seismic wave imaging, strong migration noise energy affects the imaging accuracy of reflected waves, which in turn affects the interpretation of horizons and the identification of breakpoints.
An orthogonal polynomial decomposition method is used to decompose the reflected wave migration profile containing migration noise into sub-profiles of different orders. By utilizing the energy consistency of the phase axis of the reflected wave and the energy variation characteristics of the migration noise, the migration noise is suppressed by weighted summation, thereby improving the signal-to-noise ratio.
It effectively suppresses offset noise, improves the accuracy of reflected wave imaging, and enhances the interpretation of torsional layers and the identification of breakpoints.
Smart Images
Figure CN122017999A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of seismic data processing technology, specifically to a method, apparatus, electronic device, and storage medium for suppressing migration noise. Background Technology
[0002] When the velocity of the subsurface medium varies complexly and the tectonic changes are drastic, especially at the pinch-out points of steep strata, the characteristics of reflected waves become exceptionally complex. Furthermore, a large amount of diffraction occurs during the propagation of seismic waves. Existing seismic data processing techniques typically process reflected signals, and a large number of diffracted wave signals play the role of "noise" during the processing. Especially during imaging, because diffracted waves do not meet the kinematic characteristics of reflected waves, the energy of diffracted waves cannot be properly repositioned in reflection-based imaging processing, and will appear as noise on the imaging profile. This phenomenon manifests as migration noise at stratigraphic pinch-out points and fault discontinuities on the imaging profile. When this migration noise energy is strong, it will affect the imaging accuracy of reflected waves, and thus affect the interpretation of stratigraphic horizons and the identification of discontinuities.
[0003] It should be noted that the information disclosed in the background section of this application is intended only to enhance the understanding of the general background of this application, and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention
[0004] In view of this, this application provides a method, apparatus, electronic device and storage medium for mitigation noise suppression, in order to solve the problem that when the mitigation noise energy is strong, it will affect the imaging accuracy of the reflected wave, and thus affect the layer interpretation and breakpoint identification.
[0005] In a first aspect, embodiments of this application provide a method for suppressing offset noise based on orthogonal polynomial decomposition, including:
[0006] Orthogonal polynomial decomposition is performed on the offset profile containing offset noise to obtain multiple sub-profiles of different orders.
[0007] Determine the weighting coefficients for each of the sub-sections of multiple different orders;
[0008] All the sub-profiles are weighted and summed according to the weighting coefficient of each sub-profile to obtain the offset profile after suppressing the offset noise.
[0009] In one possible implementation, the orthogonal polynomial decomposition of the offset profile containing offset noise to obtain multiple sub-profiles of different orders includes:
[0010] On an offset profile containing offset noise, a time window range in which offset noise exists is determined, the time window range including a time range and a spatial range;
[0011] Within the time window, the offset profile is decomposed into orthogonal polynomials to obtain multiple sub-profiles of different orders.
[0012] In one possible implementation, determining the weighting coefficients for each of the multiple sub-profiles of different orders includes:
[0013] The weighting coefficients for each of the sub-sections of different orders are determined based on the energy levels of the in-phase axes of the reflected waves and the offset noise on the sub-sections of different orders.
[0014] In one possible implementation, the weighting coefficients of the higher-order sub-profiles are smaller than the weighting coefficients of the lower-order sub-profiles.
[0015] Secondly, embodiments of this application provide a displacement noise suppression device based on orthogonal polynomial decomposition, comprising:
[0016] The decomposition module is used to perform orthogonal polynomial decomposition on the offset profile containing offset noise to obtain multiple sub-profiles of different orders.
[0017] A weighting coefficient determination module is used to determine the weighting coefficients of each of the sub-sections of multiple different orders;
[0018] The weighting module is used to weight and sum all the sub-sections according to the weighting coefficient of each sub-section to obtain the offset profile after suppressing the offset noise.
[0019] In one possible implementation, the decomposition module is specifically used for:
[0020] On an offset profile containing offset noise, a time window range in which offset noise exists is determined, the time window range including a time range and a spatial range;
[0021] Within the time window, the offset profile is decomposed into orthogonal polynomials to obtain multiple sub-profiles of different orders.
[0022] In one possible implementation, the weighting coefficient determination module is specifically used for:
[0023] The weighting coefficients for each of the sub-sections of different orders are determined based on the energy levels of the in-phase axes of the reflected waves and the offset noise on the sub-sections of different orders.
[0024] In one possible implementation, the weighting coefficients of the higher-order sub-profiles are smaller than the weighting coefficients of the lower-order sub-profiles.
[0025] Thirdly, embodiments of this application provide an electronic device, including:
[0026] processor;
[0027] Memory;
[0028] And a computer program, wherein the computer program is stored in the memory, and when the computer program is executed by the processor, implements the method described in any one of the first aspects.
[0029] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method described in any one of the first aspects.
[0030] Fifthly, embodiments of this application provide a computer program product, the computer program product including a computer program, which, when executed by a processor, implements the method described in any one of the first aspects.
[0031] In this embodiment, the orthogonal polynomial decomposition method is used to decompose the reflected wave migration profile containing migration noise into sub-profiles of different orders. Typically, the phase axis of the reflected wave has good energy consistency in the spatial direction, while the migration noise exhibits relatively rapid energy changes. This results in the energy of the phase axis of the reflected wave being decomposed into lower-order sub-profiles during the orthogonal polynomial decomposition process, while the migration noise is decomposed into higher-order sub-profiles. By assigning a smaller weighting coefficient to the higher-order profiles, the migration noise can be effectively suppressed during weighted summation, resulting in a reflected wave migration profile with a higher signal-to-noise ratio. Attached Figure Description
[0032] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments 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.
[0033] Figure 1 A flowchart illustrating an offset noise suppression method based on orthogonal polynomial decomposition provided in this application embodiment;
[0034] Figure 2A A reflected wave offset profile containing offset noise is provided in an embodiment of this application;
[0035] Figure 2B This application provides a reflected wave offset profile after suppressing offset noise, as an embodiment of the present application.
[0036] Figure 3A Another reflected wave offset profile containing offset noise is provided in the embodiments of this application;
[0037] Figure 3B This is another reflected wave offset profile after suppressing offset noise, provided in an embodiment of this application.
[0038] Figure 4 This application also provides a structural block diagram of an offset noise suppression device based on orthogonal polynomial decomposition;
[0039] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0040] To better understand the technical solution of this application, the embodiments of this application will be described in detail below with reference to the accompanying drawings.
[0041] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.
[0042] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.
[0043] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.
[0044] This application provides a method for suppressing offset noise based on orthogonal polynomial decomposition. By performing orthogonal polynomial decomposition on the offset profile, the effective reflected signal and offset noise are decomposed into sub-profiles of different orders. Typically, the effective reflected in-phase axis is located in a lower-order sub-profile, while the offset noise is located in a higher-order sub-profile. Then, by using a weighted summation method, the offset noise is suppressed on the offset profile. The specific implementation method is described in detail below.
[0045] See Figure 1 This is a flowchart illustrating an offset noise suppression method based on orthogonal polynomial decomposition provided in an embodiment of this application. Figure 1 As shown, it mainly includes the following steps.
[0046] Step S101: Perform orthogonal polynomial decomposition on the offset profile containing offset noise to obtain multiple sub-profiles of different orders.
[0047] Specifically, the time window range where the offset noise exists is determined on the offset profile containing offset noise. The time window range includes both time and spatial ranges. Within the time window range, the offset profile is decomposed into orthogonal polynomials to obtain multiple sub-profiles of different orders.
[0048] For example, Figure 2A A reflected wave offset profile containing offset noise is provided in an embodiment of this application; Figure 3A Another reflected wave offset profile containing offset noise is provided for embodiments of this application. Figure 2A and Figure 3A In the image, the blue box represents the time window range, and the arrow within the blue box indicates offset noise. Figure 2A and Figure 3A The data within the blue box is subjected to orthogonal polynomial decomposition to obtain multiple sub-profiles of different orders.
[0049] Step S102: Determine the weighting coefficients for each sub-section among multiple sub-sections of different orders.
[0050] Specifically, the weighting coefficients for each sub-profile of different orders are determined based on the energy levels of the in-phase axes of the reflected waves and the migration noise on multiple sub-profiles of different orders. Typically, the energy of the reflected axes is concentrated in lower-order sub-profiles, while the migration noise is concentrated in higher-order sub-profiles. This allows for assigning higher weighting coefficients to lower-order sub-profiles and lower weighting coefficients to higher-order sub-profiles, thereby suppressing migration noise. In other words, the weighting coefficients for higher-order sub-profiles are smaller than those for lower-order sub-profiles.
[0051] Step S103: Weight all sub-sections according to the weighting coefficient of each sub-section to obtain the offset profile after suppressing the offset noise.
[0052] For example, the method provided in the embodiments of this application is used to... Figure 2A The reflected wave migration profile containing migration noise shown is obtained after migration noise suppression, as shown in the figure. Figure 2B As shown. Comparison Figure 2A and Figure 2BAs can be seen from the data within the blue box, after processing the reflected wave offset profile using the method provided in this application embodiment, the offset noise is effectively suppressed.
[0053] For example, the method provided in the embodiments of this application is used to... Figure 3A The reflected wave migration profile containing migration noise shown is obtained after migration noise suppression, as shown in the figure. Figure 3B As shown. Comparison Figure 3A and Figure 3B As can be seen from the data within the blue box, after processing the reflected wave offset profile using the method provided in this application embodiment, the offset noise is effectively suppressed.
[0054] In this embodiment, the orthogonal polynomial decomposition method is used to decompose the reflected wave migration profile containing migration noise into sub-profiles of different orders. Typically, the phase axis of the reflected wave has good energy consistency in the spatial direction, while the migration noise exhibits relatively rapid energy changes. This results in the energy of the phase axis of the reflected wave being decomposed into lower-order sub-profiles during the orthogonal polynomial decomposition process, while the migration noise is decomposed into higher-order sub-profiles. By assigning a smaller weighting coefficient to the higher-order profiles, the migration noise can be effectively suppressed during weighted summation, resulting in a reflected wave migration profile with a higher signal-to-noise ratio.
[0055] Corresponding to the above embodiments, this application also provides an offset noise suppression device based on orthogonal polynomial decomposition.
[0056] See Figure 4 This application also provides a structural block diagram of an offset noise suppression device based on orthogonal polynomial decomposition. For example... Figure 4 As shown, it mainly includes the following modules.
[0057] The decomposition module 401 is used to perform orthogonal polynomial decomposition on the offset profile containing offset noise to obtain multiple sub-profiles of different orders.
[0058] Specifically, the time window range where the offset noise exists is determined on the offset profile containing offset noise. The time window range includes both time and spatial ranges. Within the time window range, the offset profile is decomposed into orthogonal polynomials to obtain multiple sub-profiles of different orders.
[0059] The weighting coefficient determination module 402 is used to determine the weighting coefficient of each sub-section in multiple sub-sections of different orders.
[0060] Specifically, the weighting coefficients for each sub-profile of different orders are determined based on the energy levels of the in-phase axes of the reflected waves and the migration noise on multiple sub-profiles of different orders. Typically, the energy of the reflected axes is concentrated in lower-order sub-profiles, while the migration noise is concentrated in higher-order sub-profiles. This allows for assigning higher weighting coefficients to lower-order sub-profiles and lower weighting coefficients to higher-order sub-profiles, thereby suppressing migration noise. In other words, the weighting coefficients for higher-order sub-profiles are smaller than those for lower-order sub-profiles.
[0061] The weighting module 403 is used to weight and sum all sub-sections according to the weighting coefficient of each sub-section to obtain the offset profile after suppressing the offset noise.
[0062] In this embodiment, the orthogonal polynomial decomposition method is used to decompose the reflected wave migration profile containing migration noise into sub-profiles of different orders. Typically, the phase axis of the reflected wave has good energy consistency in the spatial direction, while the migration noise exhibits relatively rapid energy changes. This results in the energy of the phase axis of the reflected wave being decomposed into lower-order sub-profiles during the orthogonal polynomial decomposition process, while the migration noise is decomposed into higher-order sub-profiles. By assigning a smaller weighting coefficient to the higher-order profiles, the migration noise can be effectively suppressed during weighted summation, resulting in a reflected wave migration profile with a higher signal-to-noise ratio.
[0063] It should be noted that the specific content involved in the embodiments of this application can be found in the description of the above method embodiments, and will not be repeated here for the sake of brevity.
[0064] Corresponding to the above embodiments, this application also provides an electronic device.
[0065] See Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 5 As shown, the electronic device 500 may include a processor 501, a memory 502, and a communication unit 503. These components communicate via one or more buses. Those skilled in the art will understand that the electronic device structure shown in the figure does not constitute a limitation on the embodiments of this application. It may be a bus topology or a star topology, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.
[0066] The communication unit 503 is used to establish a communication channel, thereby enabling the electronic device to communicate with other devices.
[0067] Processor 501 serves as the control center of the electronic device, connecting various parts of the device via various interfaces and lines. It executes software programs and / or modules stored in memory 502, and calls data stored in memory to perform various functions and / or process data. The processor may be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs with the same or different functions connected together. For example, processor 501 may consist only of a central processing unit (CPU). In this embodiment, the CPU may have a single processing core or include multiple processing cores.
[0068] Memory 502 is used to store the execution instructions of processor 501. Memory 502 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.
[0069] When the execution instructions in memory 502 are executed by processor 501, the electronic device 500 is able to perform some or all of the steps in the above method embodiments.
[0070] Corresponding to the above embodiments, this application also provides a computer-readable storage medium, wherein the computer-readable storage medium may store a computer program, and when the computer program is executed by a processor, it may implement some or all of the steps in the above method embodiments.
[0071] In specific implementations, the computer-readable storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.
[0072] Corresponding to the above embodiments, this application also provides a computer program product, which includes a computer program that, when executed by a processor, can implement some or all of the steps in the above method embodiments.
[0073] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.
[0074] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. 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.
[0075] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0076] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0077] The above description is merely a specific embodiment of this application. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. The protection scope of this application should be determined by the protection scope of the claims.
Claims
1. A method for suppressing offset noise based on orthogonal polynomial decomposition, characterized in that, include: Orthogonal polynomial decomposition is performed on the offset profile containing offset noise to obtain multiple sub-profiles of different orders. Determine the weighting coefficients for each of the sub-sections of multiple different orders; All the sub-profiles are weighted and summed according to the weighting coefficient of each sub-profile to obtain the offset profile after suppressing the offset noise.
2. The method according to claim 1, characterized in that, The orthogonal polynomial decomposition of the offset profile containing offset noise yields multiple sub-profiles of different orders, including: On an offset profile containing offset noise, a time window range in which offset noise exists is determined, the time window range including a time range and a spatial range; Within the time window, the offset profile is decomposed into orthogonal polynomials to obtain multiple sub-profiles of different orders.
3. The method according to claim 1, characterized in that, The determination of the weighting coefficients for each of the multiple sub-profiles of different orders includes: The weighting coefficients for each of the sub-sections of different orders are determined based on the energy levels of the in-phase axes of the reflected waves and the offset noise on the sub-sections of different orders.
4. The method according to claim 3, characterized in that, The weighting coefficients of higher-order sub-profiles are smaller than those of lower-order sub-profiles.
5. A displacement noise suppression device based on orthogonal polynomial decomposition, characterized in that, include: The decomposition module is used to perform orthogonal polynomial decomposition on the offset profile containing offset noise to obtain multiple sub-profiles of different orders. A weighting coefficient determination module is used to determine the weighting coefficients of each of the sub-sections of multiple different orders; The weighting module is used to weight and sum all the sub-sections according to the weighting coefficient of each sub-section to obtain the offset profile after suppressing the offset noise.
6. The apparatus according to claim 1, characterized in that, The decomposition module is specifically used for: On an offset profile containing offset noise, a time window range in which offset noise exists is determined, the time window range including a time range and a spatial range; Within the time window, the offset profile is decomposed into orthogonal polynomials to obtain multiple sub-profiles of different orders.
7. The apparatus according to claim 1, characterized in that, The weighting coefficient determination module is specifically used for: The weighting coefficients for each of the sub-sections of different orders are determined based on the energy levels of the in-phase axes of the reflected waves and the offset noise on the sub-sections of different orders.
8. The apparatus according to claim 3, characterized in that, The weighting coefficients of higher-order sub-profiles are smaller than those of lower-order sub-profiles.
9. An electronic device, characterized in that, include: processor; Memory; And a computer program, wherein the computer program is stored in the memory, and when executed by the processor, the computer program implements the method of any one of claims 1-4.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-4.
11. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-4.