Near-surface ground roll noise suppression method, device, equipment, medium and product

Abstract

The present application relates to the technical field of geophysical exploration, and particularly relates to a near-surface ground roll noise suppression method, device, equipment, medium and product, wherein the method comprises the following steps: performing sparse constraint on near-surface ground roll noise, combining a hyperbolic model operator and a ground roll model operator constructed in advance to construct a target function; performing sparse inversion on the target function to obtain a sparse term of the near-surface ground roll noise; and subtracting the near-surface ground roll noise from original seismic data based on the sparse term of the near-surface ground roll noise to suppress the near-surface ground roll noise, so that the suppression effect of the near-surface ground roll noise can be improved.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration technology, and in particular to a method, apparatus, equipment, medium, and product for suppressing near-surface rolling wave noise. Background Technology

[0002] In seismic exploration, due to the complexity of the near-surface medium, such as surface undulations, velocity variations, and anisotropy, interference waves with distinct propagation patterns are generated, known as coherent noise. Roll waves are a type of coherent noise that propagates along or near the Earth's surface. Their main component is Rayleigh surface waves, and therefore, they are characterized by low frequency, low velocity, and high amplitude in seismic records.

[0003] In seismic exploration, the presence of roll waves significantly obscures effective near-surface signals, especially weak reflection signals. The noise from near-surface roll waves complicates subsequent near-surface seismic data processing and significantly affects the imaging quality of the target reservoir.

[0004] There is a technical problem in this field that near-surface rolling wave noise is difficult to suppress. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, medium, and product for suppressing near-surface rolling wave noise, solving the technical problem of the difficulty in suppressing near-surface rolling wave noise.

[0006] In a first aspect, the present invention provides a method for suppressing near-surface rolling wave noise, the method comprising: applying sparse constraints to the near-surface rolling wave noise, constructing an objective function by combining a pre-constructed hyperbolic model operator and a pre-constructed rolling wave model operator; performing sparse inversion on the objective function to obtain sparse terms of the near-surface rolling wave noise; and subtracting the near-surface rolling wave noise from the original seismic data based on the sparse terms of the near-surface rolling wave noise to suppress the near-surface rolling wave noise.

[0007] In some embodiments, constructing a hyperbolic model operator includes: performing dynamic correction on the effective reflected wave signal in the original seismic data to construct a hyperbolic model operator.

[0008] In some embodiments, constructing a roll wave model operator includes: converting near-surface roll wave noise in the original seismic data to the frequency wavenumber domain, and constructing a roll wave model operator.

[0009] In some embodiments, the objective function includes the sum of the roll wave noise term and the original seismic data term.

[0010] In some embodiments, the roll wave noise term includes: the product of an inversion regularization operator and a sparse constraint on the roll wave noise.

[0011] In some embodiments, the raw seismic data item includes: the second norm of the difference between the raw seismic data and a pre-built hyperbolic model operator and a pre-built ground roll wave model operator.

[0012] Secondly, the present invention provides a near-surface rolling wave noise suppression device, the device comprising: a modeling module for applying sparse constraints to the near-surface rolling wave noise and constructing an objective function by combining a pre-constructed hyperbolic model operator and a pre-constructed rolling wave model operator; an inversion module for performing sparse inversion on the objective function to obtain sparse terms of the near-surface rolling wave noise; and a suppression module for subtracting the near-surface rolling wave noise from the original seismic data based on the sparse terms of the near-surface rolling wave noise, thereby suppressing the near-surface rolling wave noise.

[0013] Thirdly, the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any of the above-described near-surface rolling wave noise suppression methods.

[0014] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-described near-surface roll wave noise suppression methods.

[0015] Fifthly, the present invention provides a computer program product comprising a computer program that, when executed by a processor, implements the steps of any of the above-described near-surface roll wave noise suppression methods.

[0016] This invention provides a method, apparatus, device, medium, and product for suppressing near-surface rolling wave noise. The method includes: applying sparse constraints to the near-surface rolling wave noise; constructing an objective function by combining a pre-built hyperbolic model operator and a pre-built rolling wave model operator; performing sparse inversion on the objective function to obtain sparse terms of the near-surface rolling wave noise; and subtracting the near-surface rolling wave noise from the original seismic data based on the sparse terms of the near-surface rolling wave noise to suppress the near-surface rolling wave noise; thereby improving the suppression effect of near-surface rolling wave noise. Attached Figure Description

[0017] The invention will now be described in more detail with reference to embodiments and the accompanying drawings:

[0018] Figure 1 This is a schematic flowchart of a near-surface rolling wave noise suppression method provided in an embodiment of this application;

[0019] Figure 2 This is a schematic diagram of a near-surface rolling wave noise suppression device provided in an embodiment of this application;

[0020] Figure 3 This is a schematic diagram illustrating the principle of a near-surface rolling wave noise suppression method provided in an embodiment of this application;

[0021] Figure 4 This is a schematic diagram of a model data test result provided in an embodiment of this application;

[0022] Figure 5 This is a schematic diagram illustrating the result of converting model data to the frequency wavenumber domain according to an embodiment of this application;

[0023] Figure 6 This is a schematic diagram of actual seismic data test results provided in an embodiment of this application.

[0024] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention and to fully understand and implement the process of how the present invention uses technical means to solve technical problems and achieve corresponding technical effects, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. The embodiments of the present invention and the various features therein can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0028] In seismic exploration, the complexity of the near-surface medium, such as surface undulations, velocity variations, and anisotropy, generates interference waves with distinct propagation patterns, known as coherent noise. Roll waves are a type of coherent noise that propagates along or near the surface of the Earth. Their main component is Rayleigh surface waves, thus exhibiting low-frequency, low-velocity, and high-amplitude characteristics in seismic records. In seismic exploration, the presence of roll waves significantly masks effective near-surface signals, especially weak reflection signals. The presence of near-surface roll wave noise complicates subsequent near-surface seismic data processing and significantly affects the imaging quality of target reservoirs. There is a technical problem in this field regarding the difficulty in suppressing near-surface roll wave noise.

[0029] The technical solution of this application will be described below with reference to specific embodiments.

[0030] Example 1

[0031] Figure 1 This is a schematic flowchart of a near-surface rolling wave noise suppression method provided in an embodiment of this application, as shown below. Figure 1 As shown, in this embodiment, a method for suppressing near-surface rolling wave noise is provided. The method includes: applying sparse constraints to the near-surface rolling wave noise; constructing an objective function by combining a pre-built hyperbolic model operator and a pre-built rolling wave model operator; performing sparse inversion on the objective function to obtain sparse terms of the near-surface rolling wave noise; and subtracting the near-surface rolling wave noise from the original seismic data based on the sparse terms of the near-surface rolling wave noise to suppress the near-surface rolling wave noise.

[0032] The technical problem this embodiment aims to solve is how to suppress near-surface rolling wave noise. In seismic exploration, near-surface rolling wave noise is characterized by low frequency, low velocity, and strong amplitude, and it overlaps with the effective reflected signal. Conventional transform domain filtering methods are difficult to effectively constrain it, and suppressing noise can easily damage the effective signal, greatly affecting subsequent near-surface seismic data processing and the imaging quality of the target reservoir. Therefore, there is a technical problem in this field of effectively suppressing near-surface rolling wave noise.

[0033] In this embodiment, the technical solution first applies sparsity constraints to near-surface roll wave noise. These constraints, through set rules and conditions, allow the roll wave noise to be presented in a sparser form that is easier to analyze and manipulate during processing, thus enabling a more accurate understanding of its characteristics. Next, a target function is constructed by combining a pre-built hyperbolic model operator and a pre-built roll wave model operator. The hyperbolic model operator is constructed based on the dynamic correction velocity of the effective reflected wave signal in the original seismic data. It consists of a dynamic correction operator and a superposition operator, effectively describing the effective reflected wave signal. The roll wave model operator is constructed by converting the near-surface roll wave noise in the original seismic data to the frequency-wavenumber domain. It involves elements such as the frequency-wavenumber domain conversion coefficients and can be used to accurately characterize the roll wave noise in this domain. These two operators, along with the sparsity constraints, jointly construct the target function, thus incorporating the roll wave noise suppression problem into the target function, preparing for subsequent solutions. Then, a sparse inversion is performed on the target function to deduce the sparse term of the near-surface roll wave noise. Finally, based on the sparse terms of the obtained near-surface rolling wave noise, an adaptive subtraction method is used to subtract the near-surface rolling wave noise from the original seismic data, thereby suppressing the near-surface rolling wave noise.

[0034] The technical solution of this embodiment effectively solves the problem of suppressing near-surface roll wave noise. In practical applications, taking the model data described below as an example, it contains effective signals satisfying the hyperbolic assumption, roll wave noise, and random noise. Using the method of this embodiment, the hyperbolic model operator and the roll wave model operator are first accurately constructed, and then the objective function is reasonably constructed and sparse inversion is performed to obtain the sparse term. After finally subtracting the roll wave noise from the original seismic data, it can be clearly seen that the roll wave noise is significantly suppressed, and the effective signals that were originally masked by the roll wave noise are better presented. For example, when observing the performance of the data before and after processing in the frequency wavenumber domain, it can be intuitively seen that the frequency components of the roll wave are well suppressed. This greatly assists subsequent seismic data analysis and target reservoir imaging, improves the quality of seismic data and the accuracy of processing, and enables the entire seismic exploration work to proceed more smoothly. Moreover, in the actual controllable source data test in the work area, after the selected multi-shot actual seismic data were processed by this method, the strong amplitude ground roll wave noise was effectively suppressed, and the effective signal was also well recovered and reconstructed.

[0035] Example 2

[0036] Based on the above embodiments, a hyperbolic model operator is constructed, including: performing dynamic correction on the effective signal of reflected waves in the original seismic data, and constructing a hyperbolic model operator.

[0037] The technical problem to be solved in this embodiment is how to construct the hyperbolic model operator. In the process of near-surface rolling wave noise suppression, the accurate construction of the hyperbolic model operator plays a key role in distinguishing and processing the effective signal of reflected waves. However, traditional methods often lack a clear and effective construction method to dynamically correct the effective signal of reflected waves in the original seismic data and thus construct a suitable hyperbolic model operator. There is a technical problem in the field of constructing hyperbolic model operators.

[0038] In this embodiment, the core of constructing the hyperbolic model operator lies in dynamically correcting the effective reflected wave signal in the original seismic data. The dynamic correction process involves adjusting the effective reflected wave signal in time and space based on the propagation laws of seismic waves and the characteristics of the subsurface medium, making it better conform to the assumptions of the hyperbolic model. Specifically, this utilizes the dynamic correction velocity. Seismic wave propagation velocities vary in different subsurface medium environments, and the dynamic correction velocity accurately reflects the relevant characteristics of the area where the original seismic data is located. By applying the dynamic correction velocity to the effective reflected wave signal, combined with the dynamic correction operator and the superposition operator, the dynamic correction operator corrects the signal in dimensions such as time, while the superposition operator rationally superimposes and integrates the corrected signal. The two work synergistically to ultimately construct the hyperbolic model operator. This operator can accurately describe the existence form and characteristics of the effective reflected wave signal in the original seismic data, providing a solid foundation for subsequent operations such as constructing the objective function together with the roll wave model operator to suppress roll wave noise.

[0039] The technical solution of this embodiment utilizes dynamic correction speed for dynamic correction and combines it with relevant operators to construct a hyperbolic model operator. In model data processing, thanks to the accurately constructed hyperbolic model operator, the effective reflected wave signal can be clearly presented from the original data containing roll wave noise and random noise in a manner consistent with its own inherent laws. When constructing the objective function subsequently, the hyperbolic model operator can precisely define the effective signal portion, allowing the objective function to more reasonably integrate the relationship between the effective signal and roll wave noise. This enables more targeted calculation of the relevant situation of roll wave noise during operations such as sparse inversion. For example, when observing the comparison of model data before and after processing in the frequency-wavenumber domain, because the hyperbolic model operator accurately characterizes the effective signal, the recovery and presentation of the effective signal after suppressing roll wave noise is more accurate, avoiding signal distortion problems caused by inaccurate operators. The same applies to seismic data processing in actual work areas. Accurate hyperbolic model operators ensure the scientific nature of the entire roll wave noise suppression process, so that the effective signals in the final seismic data are well protected and the roll wave noise is effectively suppressed, which improves the quality of seismic data processing and the accuracy of subsequent geological analysis and judgment, and is of great significance for the smooth progress of seismic exploration work.

[0040] Example 3

[0041] Based on the above embodiments, a ground roll wave model operator is constructed, including: converting near-surface ground roll wave noise in the original seismic data to the frequency wavenumber domain, and constructing a ground roll wave model operator.

[0042] The technical problem to be solved in this embodiment is how to construct the aforementioned roll wave model operator. In near-surface roll wave noise suppression, constructing a suitable roll wave model operator is a crucial step in accurately grasping the characteristics of roll wave noise and achieving effective suppression. However, related technologies have shortcomings in converting near-surface roll wave noise in raw seismic data to the frequency-wavenumber domain and constructing accurate roll wave model operators. There is a technical problem in this field where the construction of roll wave model operators is not accurate and complete enough.

[0043] In this embodiment, the key to constructing the roll wave model operator lies in converting near-surface roll wave noise in the original seismic data to the frequency-wavenumber domain. This conversion is necessary because the frequency-wavenumber domain more clearly reveals the dispersion and other characteristics of roll wave noise, facilitating analysis and modeling. The conversion process involves frequency-wavenumber domain conversion coefficients, which are determined based on the physical characteristics of seismic wave propagation and related parameters such as frequency and wavenumber. These coefficients accurately convert the spatial representation of roll wave noise in the original time domain to the frequency-wavenumber domain, and then construct the roll wave model operator through certain mathematical representations and operations. This operator can accurately describe the key characteristics of roll wave noise, such as its sparse representation in the frequency-wavenumber domain, using relevant variables and coefficients. It then participates in the construction of the objective function along with the hyperbolic model operator, providing a strong basis for subsequent suppression of roll wave noise through sparse inversion and other methods. This ensures that the entire suppression process closely revolves around the characteristics of roll wave noise in the frequency-wavenumber domain.

[0044] The technical solution of this embodiment achieves good technical results by constructing a roll wave model operator by converting roll wave noise to the frequency-wavenumber domain. Taking model data testing as an example, after converting the roll wave noise in the original data containing roll wave noise, effective signal, and random noise to the frequency-wavenumber domain and constructing the model operator, the characteristics of roll wave noise in the frequency-wavenumber domain can be accurately captured based on this operator during subsequent operations such as constructing the objective function and performing sparse inversion, thus enabling more precise processing. When observing the comparison results before and after the model data is converted to the frequency-wavenumber domain, it can be clearly seen that after the suppression process based on this operator, the frequency components of the roll wave noise are well controlled. The originally messy and highly interfering roll wave noise becomes more regular and easier to distinguish from the effective signal. In actual seismic data applications in work areas, the constructed roll wave model operator can also effectively suppress roll wave noise, significantly reducing the noise of strong-amplitude roll waves. At the same time, the effective signal can be better recovered and presented in multiple dimensions such as frequency wavenumber domain and time domain, improving the fidelity of seismic data denoising and the reliability of subsequent analysis and processing, and providing a high-quality data foundation for accurate exploration of underground geological structures.

[0045] Example 4

[0046] Based on the above embodiments, the objective function includes: the sum of the roll wave noise term and the original seismic data term.

[0047] The technical problem to be solved in this embodiment is how to construct the objective function. In the near-surface roll wave noise suppression method based on frequency wavenumber domain sparse inversion, the objective function plays a key role in coordinating the relationship between the effective signal and the roll wave noise, and guiding subsequent solutions to achieve noise suppression. However, the relevant technologies lack a clear definition of what the objective function should specifically include and what its structure should be, resulting in a technical problem of unclear objective function structure in this field.

[0048] In this embodiment, the objective function comprises the sum of a roll wave noise term and a raw seismic data term. The roll wave noise term is a crucial part of the objective function, used to characterize and constrain the roll wave noise, and is closely related to a series of processing operations performed on the roll wave noise in the raw seismic data. The raw seismic data term is derived from the raw seismic data as a whole, through correlation operations with pre-built hyperbolic model operators and pre-built roll wave model operators. Specifically, it is the second norm of the difference between the raw seismic data and the results of these two operators. This setup allows the objective function to comprehensively consider the existence and interrelationship of the effective signal and roll wave noise in the raw seismic data from both global and local perspectives. By reasonably adding these two parts to form the objective function, in subsequent sparse inversion and other solution processes, the structure of the objective function can be used to accurately analyze and adjust the respective situations of the effective signal and roll wave noise, thereby achieving the goal of suppressing roll wave noise and protecting the effective signal.

[0049] The technical solution of this embodiment, by clearly defining the structure of the objective function, demonstrates outstanding performance in suppressing near-surface roll wave noise. In the model data verification stage, based on this clearly structured objective function, the effective signal portion represented by the hyperbolic model operator and the roll wave noise portion corresponding to the roll wave model operator can be accurately integrated during construction. This allows the objective function to systematically deduce key information such as the sparse term of the roll wave noise based on its structural characteristics during subsequent sparse inversion solutions. For example, when observing the comparison of model data before and after processing, due to the reasonable structure of the objective function, the process of suppressing roll wave noise is more targeted. The final result is that the roll wave noise is effectively suppressed, and the effective signal is well preserved. In different representations such as the frequency and wavenumber domains, the effective signal is not excessively damaged. The same applies to seismic data processing in actual work areas. The clear structure of the objective function ensures the orderliness of the entire suppression process, allowing the roll wave noise suppression operation to proceed according to the established logic. High-amplitude roll wave noise is significantly suppressed, and the effective signal is well recovered and reconstructed, greatly improving the quality of seismic data and providing reliable data support for subsequent geological analysis and other work.

[0050] Example 5

[0051] Based on the above embodiments, the ground roll wave noise term includes: the product of the inversion regularization operator and the sparse constraint on the ground roll wave noise.

[0052] The technical problem to be solved in this embodiment is how to construct the roll wave noise term of the objective function. When constructing an objective function for near-surface roll wave noise suppression, the accurate construction of the roll wave noise term is crucial for reasonably reflecting the characteristics of roll wave noise and achieving accurate suppression in subsequent solutions. However, current technology is not perfect in determining the specific composition and construction method of the roll wave noise term, and there is a technical problem in the field of accurately constructing the roll wave noise term in the objective function.

[0053] In this embodiment, the rolling wave noise term of the objective function comprises the product of an inversion regularization operator and a sparse constraint on the rolling wave noise. The inversion regularization operator plays a role in regulating and standardizing the entire rolling wave noise term. It can reasonably adjust the weight and representation of rolling wave noise in the objective function based on actual seismic data and suppression targets, avoiding over-suppression or under-suppression. The sparse constraint on the rolling wave noise, from the perspective of data characteristics, allows the rolling wave noise to be presented in a sparse form in the objective function that is easier to analyze and process. Specific constraints are set to accurately grasp its key characteristics. Multiplying these two terms to form the rolling wave noise term ensures that this part accurately reflects the essential characteristics of rolling wave noise in the objective function and participates in subsequent sparse inversion and other solution processes according to predetermined rules and constraints. It works synergistically with other parts of the objective function to guide the process towards suppressing rolling wave noise and protecting the effective signal.

[0054] The technical solution of this embodiment, by constructing the ground roll noise term in the objective function in this way, has achieved significant results in suppressing near-surface ground roll noise. In model data testing, because the ground roll noise term accurately includes the product of the inversion regularization operator and the sparse constraints, it can appropriately handle ground roll noise according to the actual situation when constructing the objective function and performing sparse inversion solutions. For example, when observing the comparison of model data before and after processing, the suppression effect of ground roll noise is obvious, and its key features such as frequency components are effectively controlled. This is due to the fact that the ground roll noise term reasonably reflects its characteristics in the objective function, enabling precise operation on ground roll noise during the solution process, and the effective signal is also well protected, without being mistakenly suppressed due to an unreasonable construction of the ground roll noise term. The same applies to the application of seismic data in actual work areas. The accurately constructed roll wave noise term ensures the scientific nature of the objective function, thereby enabling the entire roll wave noise suppression process to proceed smoothly. High-amplitude roll wave noise is well suppressed, and the effective signal can be clearly presented after processing. This improves the quality of seismic data and the accuracy of subsequent geological analysis and other work, providing strong data support for seismic exploration.

[0055] Example 6

[0056] Based on the above embodiments, the original seismic data item includes: the second norm of the difference between the original seismic data and the pre-built hyperbolic model operator and the pre-built ground roll wave model operator.

[0057] The technical problem to be solved in this embodiment is how to construct the original seismic data terms of the objective function. When constructing an objective function for near-surface roll wave noise suppression, the reasonable construction of the original seismic data terms has a key impact on understanding the overall seismic data situation and accurately correlating the relationship between the effective signal and the roll wave noise. However, the existing technology has shortcomings in determining the specific construction method of the original seismic data terms, and there is a technical problem in the art of accurately constructing the original seismic data terms in the objective function.

[0058] In this embodiment, the original seismic data term of the objective function includes the second norm of the difference between the original seismic data and the pre-constructed hyperbolic model operator and the pre-constructed roll wave model operator. This construction is because the original seismic data is fundamental data containing information on various aspects, including the effective signal, roll wave noise, and random noise. The hyperbolic model operator accurately describes the effective signal, and the roll wave model operator characterizes the roll wave noise. By taking the difference between the original seismic data and the results of these two operators, the portion already represented by these two operators is removed from the overall data. Taking the second norm allows for a quantitative assessment of the remaining portion, thus providing a holistic understanding of the information in the original seismic data besides the explicit effective signal and roll wave noise, and their relationship with the effective signal and roll wave noise. Adding this constructed original seismic data term to the objective function allows the objective function to more comprehensively cover all aspects of the seismic data. In subsequent sparse inversion and other solution processes, this construction method comprehensively considers all relevant factors, thereby better achieving the goal of suppressing roll wave noise and protecting the effective signal.

[0059] The technical solution of this embodiment, by constructing the original seismic data terms of the objective function in this way, has demonstrated good results in suppressing near-surface roll wave noise. During model data verification, because the original seismic data terms are constructed in the above manner, the objective function can fully consider various situations in the original seismic data when constructing the objective function and performing subsequent operations. For example, when observing the comparison of model data before and after processing, based on the original seismic data terms constructed in this way, the objective function can more comprehensively balance the relationship between the effective signal, roll wave noise, and other components in guiding sparse inversion and other solutions. This results in effective suppression of the roll wave noise, while the effective signal is well preserved, maintaining a good state in different representations such as the frequency and wavenumber domains. The same applies to the processing of seismic data in actual work areas. The rationally constructed original seismic data items ensure the scientific nature and comprehensiveness of the objective function, enabling the entire roll wave noise suppression process to be carried out in an orderly and accurate manner. High-amplitude roll wave noise is significantly suppressed, and the effective signal is well recovered and reconstructed, improving the quality of seismic data and providing a reliable data foundation for subsequent geological analysis and other work, thus powerfully promoting the smooth progress of seismic exploration work.

[0060] Example 7

[0061] Figure 2 This is a schematic diagram of a near-surface rolling wave noise suppression device provided in an embodiment of this application, as shown below. Figure 2 As shown, in this embodiment, a near-surface rolling wave noise suppression device is provided. The device includes: a modeling module for applying sparse constraints to the near-surface rolling wave noise and constructing an objective function by combining a pre-built hyperbolic model operator and a pre-built rolling wave model operator; an inversion module for performing sparse inversion on the objective function to obtain the sparse term of the near-surface rolling wave noise; and a suppression module for subtracting the near-surface rolling wave noise from the original seismic data based on the sparse term of the near-surface rolling wave noise to suppress the near-surface rolling wave noise.

[0062] The technical problem to be solved in this embodiment is how to suppress near-surface rolling wave noise. In seismic exploration, near-surface rolling wave noise is characterized by low frequency, low velocity, and strong amplitude, and it overlaps with the effective reflected signal. Conventional transform domain filtering devices are difficult to effectively constrain it, and suppressing noise can easily damage the effective signal, greatly affecting the subsequent processing of near-surface seismic data and the imaging quality of the target reservoir. There is a technical problem in this field that near-surface rolling wave noise is difficult to suppress effectively.

[0063] In this embodiment, the technical solution first applies sparsity constraints to near-surface roll wave noise. These constraints, through set rules and conditions, allow the roll wave noise to be presented in a sparser form that is easier to analyze and manipulate during processing, thus enabling a more accurate understanding of its characteristics. Next, a target function is constructed by combining a pre-built hyperbolic model operator and a pre-built roll wave model operator. The hyperbolic model operator is constructed based on the dynamic correction velocity of the effective reflected wave signal in the original seismic data. It consists of a dynamic correction operator and a superposition operator, effectively describing the effective reflected wave signal. The roll wave model operator is constructed by converting the near-surface roll wave noise in the original seismic data to the frequency-wavenumber domain. It involves elements such as the frequency-wavenumber domain conversion coefficients and can be used to accurately characterize the roll wave noise in this domain. These two operators, along with the sparsity constraints, jointly construct the target function, thus incorporating the roll wave noise suppression problem into the target function, preparing for subsequent solutions. Then, a sparse inversion is performed on the target function to deduce the sparse term of the near-surface roll wave noise. Finally, based on the sparse terms of the obtained near-surface rolling wave noise, an adaptive subtraction method is used to subtract the near-surface rolling wave noise from the original seismic data, thereby suppressing the near-surface rolling wave noise.

[0064] The technical solution of this embodiment effectively solves the problem of suppressing near-surface roll wave noise. In practical applications, taking the model data described below as an example, it contains effective signals satisfying the hyperbolic assumption, roll wave noise, and random noise. Using the device of this embodiment, the hyperbolic model operator and the roll wave model operator are first accurately constructed, and then the objective function is reasonably constructed and sparse inversion is performed to obtain the sparse term. After finally subtracting the roll wave noise from the original seismic data, it can be clearly seen that the roll wave noise is significantly suppressed, and the effective signals that were originally masked by the roll wave noise are better presented. For example, when observing the performance of the data before and after processing in the frequency wavenumber domain, it can be intuitively seen that the frequency components of the roll wave are well suppressed. This greatly assists subsequent seismic data analysis and target reservoir imaging, improves the quality of seismic data and the accuracy of processing, and enables the entire seismic exploration work to proceed more smoothly. Moreover, in the actual controllable source data test in the work area, after the selected multi-shot actual seismic data was processed by the device, the strong amplitude ground roll wave noise was effectively suppressed, and the effective signal was also well recovered and reconstructed.

[0065] Based on the above embodiments, a hyperbolic model operator is constructed, including: performing dynamic correction on the effective signal of reflected waves in the original seismic data, and constructing a hyperbolic model operator.

[0066] The technical problem to be solved in this embodiment is how to construct the hyperbolic model operator. In the process of near-surface rolling wave noise suppression, the accurate construction of the hyperbolic model operator plays a key role in distinguishing and processing the effective signal of reflected waves. However, traditional devices often lack a clear and effective construction method to dynamically correct the effective signal of reflected waves in the original seismic data and thus construct a suitable hyperbolic model operator. There is a technical problem in the field of difficulty in constructing hyperbolic model operators.

[0067] In this embodiment, the core of constructing the hyperbolic model operator lies in dynamically correcting the effective reflected wave signal in the original seismic data. The dynamic correction process involves adjusting the effective reflected wave signal in time and space based on the propagation laws of seismic waves and the characteristics of the subsurface medium, making it better conform to the assumptions of the hyperbolic model. Specifically, this utilizes the dynamic correction velocity. Seismic wave propagation velocities vary in different subsurface medium environments, and the dynamic correction velocity accurately reflects the relevant characteristics of the area where the original seismic data is located. By applying the dynamic correction velocity to the effective reflected wave signal, combined with the dynamic correction operator and the superposition operator, the dynamic correction operator corrects the signal in dimensions such as time, while the superposition operator rationally superimposes and integrates the corrected signal. The two work synergistically to ultimately construct the hyperbolic model operator. This operator can accurately describe the existence form and characteristics of the effective reflected wave signal in the original seismic data, providing a solid foundation for subsequent operations such as constructing the objective function together with the roll wave model operator to suppress roll wave noise.

[0068] The technical solution of this embodiment utilizes dynamic correction speed for dynamic correction and combines it with relevant operators to construct a hyperbolic model operator. In model data processing, thanks to the accurately constructed hyperbolic model operator, the effective reflected wave signal can be clearly presented from the original data containing roll wave noise and random noise in a manner consistent with its own inherent laws. When constructing the objective function subsequently, the hyperbolic model operator can precisely define the effective signal portion, allowing the objective function to more reasonably integrate the relationship between the effective signal and roll wave noise. This enables more targeted calculation of the relevant situation of roll wave noise during operations such as sparse inversion. For example, when observing the comparison of model data before and after processing in the frequency-wavenumber domain, because the hyperbolic model operator accurately characterizes the effective signal, the recovery and presentation of the effective signal after suppressing roll wave noise is more accurate, avoiding signal distortion problems caused by inaccurate operators. The same applies to seismic data processing in actual work areas. Accurate hyperbolic model operators ensure the scientific nature of the entire roll wave noise suppression process, so that the effective signals in the final seismic data are well protected and the roll wave noise is effectively suppressed, which improves the quality of seismic data processing and the accuracy of subsequent geological analysis and judgment, and is of great significance for the smooth progress of seismic exploration work.

[0069] Based on the above embodiments, a ground roll wave model operator is constructed, including: converting near-surface ground roll wave noise in the original seismic data to the frequency wavenumber domain, and constructing a ground roll wave model operator.

[0070] The technical problem to be solved in this embodiment is how to construct the aforementioned roll wave model operator. In near-surface roll wave noise suppression, constructing a suitable roll wave model operator is a crucial step in accurately grasping the characteristics of roll wave noise and achieving effective suppression. However, related technologies have shortcomings in converting near-surface roll wave noise in raw seismic data to the frequency-wavenumber domain and constructing accurate roll wave model operators. There is a technical problem in this field where the construction of roll wave model operators is not accurate and complete enough.

[0071] In this embodiment, the key to constructing the roll wave model operator lies in converting near-surface roll wave noise in the original seismic data to the frequency-wavenumber domain. This conversion is necessary because the frequency-wavenumber domain more clearly reveals the dispersion and other characteristics of roll wave noise, facilitating analysis and modeling. The conversion process involves frequency-wavenumber domain conversion coefficients, which are determined based on the physical characteristics of seismic wave propagation and related parameters such as frequency and wavenumber. These coefficients accurately convert the spatial representation of roll wave noise in the original time domain to the frequency-wavenumber domain, and then construct the roll wave model operator through certain mathematical representations and operations. This operator can accurately describe the key characteristics of roll wave noise, such as its sparse representation in the frequency-wavenumber domain, using relevant variables and coefficients. It then participates in the construction of the objective function along with the hyperbolic model operator, providing a strong basis for subsequent suppression of roll wave noise through sparse inversion and other methods. This ensures that the entire suppression process closely revolves around the characteristics of roll wave noise in the frequency-wavenumber domain.

[0072] The technical solution of this embodiment achieves good technical results by constructing a roll wave model operator by converting roll wave noise to the frequency-wavenumber domain. Taking model data testing as an example, after converting the roll wave noise in the original data containing roll wave noise, effective signal, and random noise to the frequency-wavenumber domain and constructing the model operator, the characteristics of roll wave noise in the frequency-wavenumber domain can be accurately captured based on this operator during subsequent operations such as constructing the objective function and performing sparse inversion, thus enabling more precise processing. When observing the comparison results before and after the model data is converted to the frequency-wavenumber domain, it can be clearly seen that after the suppression process based on this operator, the frequency components of the roll wave noise are well controlled. The originally messy and highly interfering roll wave noise becomes more regular and easier to distinguish from the effective signal. In actual seismic data applications in work areas, the constructed roll wave model operator can also effectively suppress roll wave noise, significantly reducing the noise of strong-amplitude roll waves. At the same time, the effective signal can be better recovered and presented in multiple dimensions such as frequency wavenumber domain and time domain, improving the fidelity of seismic data denoising and the reliability of subsequent analysis and processing, and providing a high-quality data foundation for accurate exploration of underground geological structures.

[0073] Based on the above embodiments, the objective function includes: the sum of the roll wave noise term and the original seismic data term.

[0074] The technical problem to be solved in this embodiment is how to construct the objective function. In a near-surface roll wave noise suppression device based on frequency wavenumber domain sparse inversion, the objective function plays a key role in coordinating the relationship between the effective signal and the roll wave noise, and guiding subsequent solutions to achieve noise suppression. However, the relevant technologies lack a clear definition of what the objective function should specifically include and what its structure should be, resulting in a technical problem of unclear objective function structure in this field.

[0075] In this embodiment, the objective function comprises the sum of a roll wave noise term and a raw seismic data term. The roll wave noise term is a crucial part of the objective function, used to characterize and constrain the roll wave noise, and is closely related to a series of processing operations performed on the roll wave noise in the raw seismic data. The raw seismic data term is derived from the raw seismic data as a whole, through correlation operations with pre-built hyperbolic model operators and pre-built roll wave model operators. Specifically, it is the second norm of the difference between the raw seismic data and the results of these two operators. This setup allows the objective function to comprehensively consider the existence and interrelationship of the effective signal and roll wave noise in the raw seismic data from both global and local perspectives. By reasonably adding these two parts to form the objective function, in subsequent sparse inversion and other solution processes, the structure of the objective function can be used to accurately analyze and adjust the respective situations of the effective signal and roll wave noise, thereby achieving the goal of suppressing roll wave noise and protecting the effective signal.

[0076] The technical solution of this embodiment, by clearly defining the structure of the objective function, demonstrates outstanding performance in suppressing near-surface roll wave noise. In the model data verification stage, based on this clearly structured objective function, the effective signal portion represented by the hyperbolic model operator and the roll wave noise portion corresponding to the roll wave model operator can be accurately integrated during construction. This allows the objective function to systematically deduce key information such as the sparse term of the roll wave noise based on its structural characteristics during subsequent sparse inversion solutions. For example, when observing the comparison of model data before and after processing, due to the reasonable structure of the objective function, the process of suppressing roll wave noise is more targeted. The final result is that the roll wave noise is effectively suppressed, and the effective signal is well preserved. In different representations such as the frequency and wavenumber domains, the effective signal is not excessively damaged. The same applies to seismic data processing in actual work areas. The clear structure of the objective function ensures the orderliness of the entire suppression process, allowing the roll wave noise suppression operation to proceed according to the established logic. High-amplitude roll wave noise is significantly suppressed, and the effective signal is well recovered and reconstructed, greatly improving the quality of seismic data and providing reliable data support for subsequent geological analysis and other work.

[0077] Based on the above embodiments, the ground roll wave noise term includes: the product of the inversion regularization operator and the sparse constraint on the ground roll wave noise.

[0078] The technical problem to be solved in this embodiment is how to construct the roll wave noise term of the objective function. When constructing an objective function for near-surface roll wave noise suppression, the accurate construction of the roll wave noise term is crucial for reasonably reflecting the characteristics of roll wave noise and achieving accurate suppression in subsequent solutions. However, current technology is not perfect in determining the specific composition and construction method of the roll wave noise term, and there is a technical problem in the field of accurately constructing the roll wave noise term in the objective function.

[0079] In this embodiment, the rolling wave noise term of the objective function comprises the product of an inversion regularization operator and a sparse constraint on the rolling wave noise. The inversion regularization operator plays a role in regulating and standardizing the entire rolling wave noise term. It can reasonably adjust the weight and representation of rolling wave noise in the objective function based on actual seismic data and suppression targets, avoiding over-suppression or under-suppression. The sparse constraint on the rolling wave noise, from the perspective of data characteristics, allows the rolling wave noise to be presented in a sparse form in the objective function that is easier to analyze and process. Specific constraints are set to accurately grasp its key characteristics. Multiplying these two terms to form the rolling wave noise term ensures that this part accurately reflects the essential characteristics of rolling wave noise in the objective function and participates in subsequent sparse inversion and other solution processes according to predetermined rules and constraints. It works synergistically with other parts of the objective function to guide the process towards suppressing rolling wave noise and protecting the effective signal.

[0080] The technical solution of this embodiment, by constructing the ground roll noise term in the objective function in this way, has achieved significant results in suppressing near-surface ground roll noise. In model data testing, because the ground roll noise term accurately includes the product of the inversion regularization operator and the sparse constraints, it can appropriately handle ground roll noise according to the actual situation when constructing the objective function and performing sparse inversion solutions. For example, when observing the comparison of model data before and after processing, the suppression effect of ground roll noise is obvious, and its key features such as frequency components are effectively controlled. This is due to the fact that the ground roll noise term reasonably reflects its characteristics in the objective function, enabling precise operation on ground roll noise during the solution process, and the effective signal is also well protected, without being mistakenly suppressed due to an unreasonable construction of the ground roll noise term. The same applies to the application of seismic data in actual work areas. The accurately constructed roll wave noise term ensures the scientific nature of the objective function, thereby enabling the entire roll wave noise suppression process to proceed smoothly. High-amplitude roll wave noise is well suppressed, and the effective signal can be clearly presented after processing. This improves the quality of seismic data and the accuracy of subsequent geological analysis and other work, providing strong data support for seismic exploration.

[0081] Based on the above embodiments, the original seismic data item includes: the second norm of the difference between the original seismic data and the pre-built hyperbolic model operator and the pre-built ground roll wave model operator.

[0082] The technical problem to be solved in this embodiment is how to construct the original seismic data terms of the objective function. When constructing an objective function for near-surface roll wave noise suppression, the reasonable construction of the original seismic data terms has a key impact on understanding the overall seismic data situation and accurately correlating the relationship between the effective signal and the roll wave noise. However, the existing technology has shortcomings in determining the specific construction method of the original seismic data terms, and there is a technical problem in the art of accurately constructing the original seismic data terms in the objective function.

[0083] In this embodiment, the original seismic data term of the objective function includes the second norm of the difference between the original seismic data and the pre-constructed hyperbolic model operator and the pre-constructed roll wave model operator. This construction is because the original seismic data is fundamental data containing information on various aspects, including the effective signal, roll wave noise, and random noise. The hyperbolic model operator accurately describes the effective signal, and the roll wave model operator characterizes the roll wave noise. By taking the difference between the original seismic data and the results of these two operators, the portion already represented by these two operators is removed from the overall data. Taking the second norm allows for a quantitative assessment of the remaining portion, thus providing a holistic understanding of the information in the original seismic data besides the explicit effective signal and roll wave noise, and their relationship with the effective signal and roll wave noise. Adding this constructed original seismic data term to the objective function allows the objective function to more comprehensively cover all aspects of the seismic data. In subsequent sparse inversion and other solution processes, this construction method comprehensively considers all relevant factors, thereby better achieving the goal of suppressing roll wave noise and protecting the effective signal.

[0084] The technical solution of this embodiment, by constructing the original seismic data terms of the objective function in this way, has demonstrated good results in suppressing near-surface roll wave noise. During model data verification, because the original seismic data terms are constructed in the above manner, the objective function can fully consider various situations in the original seismic data when constructing the objective function and performing subsequent operations. For example, when observing the comparison of model data before and after processing, based on the original seismic data terms constructed in this way, the objective function can more comprehensively balance the relationship between the effective signal, roll wave noise, and other components in guiding sparse inversion and other solutions. This results in effective suppression of the roll wave noise, while the effective signal is well preserved, maintaining a good state in different representations such as the frequency and wavenumber domains. The same applies to the processing of seismic data in actual work areas. The rationally constructed original seismic data items ensure the scientific nature and comprehensiveness of the objective function, enabling the entire roll wave noise suppression process to be carried out in an orderly and accurate manner. High-amplitude roll wave noise is significantly suppressed, and the effective signal is well recovered and reconstructed, improving the quality of seismic data and providing a reliable data foundation for subsequent geological analysis and other work, thus powerfully promoting the smooth progress of seismic exploration work.

[0085] Example 8

[0086] In the technical solution of this embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of any of the near-surface rolling wave noise suppression methods described in the above embodiments.

[0087] In the technical solution of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of any of the near-surface rolling wave noise suppression methods described in the above embodiments.

[0088] In the technical solution of this embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of any of the near-surface rolling wave noise suppression methods described in the above embodiments.

[0089] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for performing the methods in the above embodiments. The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, and may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (e.g., hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0090] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0091] In addition, the computer device may also include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., a keyboard, mouse, speakers, etc.). The processor can communicate with external devices via the I / O bus through a wired or wireless network. In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions, when executed by the processor, perform the steps of the various functions and / or methods in the embodiments described herein.

[0092] Example 9

[0093] Based on the above embodiments, this embodiment provides an application example.

[0094] This application example provides a method for suppressing near-surface rolling wave noise. This invention belongs to the field of geophysical exploration, and specifically relates to a method for suppressing near-surface rolling wave noise.

[0095] In seismic exploration, the complexity of the near-surface medium, such as surface undulations, velocity variations, and anisotropy, generates interference waves with distinct propagation patterns, known as coherent noise. Roll waves are a type of coherent noise that propagates along or near the surface of the Earth. Their main component is Rayleigh surface waves, thus exhibiting low-frequency, low-velocity, and high-amplitude characteristics in seismic records. In seismic exploration, the presence of roll waves significantly masks effective near-surface signals, especially weak reflection signals. The presence of near-surface roll wave noise complicates subsequent near-surface seismic data processing and significantly affects the imaging quality of target reservoirs. There is a technical problem in this field regarding the difficulty in suppressing near-surface roll wave noise.

[0096] Due to the overlap between near-surface roll wave noise and effective reflection signals, conventional transform domain filtering methods, such as FK filtering, Radon transform, and curvelet transform, cannot effectively constrain roll wave noise. Even after converting seismic data to the FK, Radon, or curvelet domains, roll wave noise and effective reflection signals cannot be completely separated, leading to damage to the effective signal during noise suppression and ultimately affecting the processing accuracy of seismic data. Furthermore, considering the dispersive characteristics of the roll wave component, direct modeling of roll waves is difficult. Therefore, finding a new modeling method that can accurately estimate roll waves while protecting the effective signal from damage when they overlap is urgently needed for current seismic data processing.

[0097] This invention addresses the challenge of traditional transform domain filtering methods in suppressing near-surface roll wave noise by providing a roll wave noise suppression method based on frequency-wavenumber domain sparse inversion. This method models and constructs objective functions for both the effective signal and roll wave noise in seismic data. Then, it solves these objective functions through sparse inversion, transforming the roll wave noise suppression problem into a least-squares problem of solving the objective function. The multi-dimensional inversion process replaces the traditional transform domain filtering process. This method constrains the inversion results by adding sparsity constraints and a linear search step size, and uses the output of each iteration as feedback for the next iteration, maximizing the preservation of the effective signal within the internal algorithm. Processing results from models and real data demonstrate that this method effectively suppresses roll wave noise in near-surface seismic data, and compared to traditional transform domain filtering methods, it maximizes the preservation of the effective signal.

[0098] A method for suppressing near-surface roll wave noise includes the following steps:

[0099] Step 1: Utilize dynamic correction velocity to analyze the effective reflected wave signal d in the original seismic data d. s Constructing the hyperbolic model operator L s ;

[0100] Step 2: Remove the near-surface roll wave noise d from the original seismic data d. g Transform to the frequency-wavenumber domain to construct the ground roll wave model operator L c ;

[0101] Step 3: Construct the objective function and evaluate the near-surface roll wave noise d. g Add sparse constraint Δx g Nearly surface rolling wave noise d g The suppression problem is transformed into a problem of solving the objective function;

[0102] Step 4: Solve for the objective function and predict the near-surface roll wave noise d using sparse inversion. g sparse terms x c ;

[0103] Step 5: The predicted near-surface roll wave noise d is then adjusted using adaptive subtraction. c Subtracting this from the original data achieves the purpose of suppressing near-surface rolling wave noise.

[0104] Furthermore, the original seismic data d in step one can be represented as the effective reflected wave signal d. s Near-surface roll wave noise d g and random noise d n That is:

[0105] d = d s +d g +d n (1)

[0106] Based on the hyperbolic motion correction assumption, the effective signal d of the reflected wave s This can be further represented as the hyperbolic model operator L s With reflectivity x s The product of, where the hyperbolic model operator L s Dynamic correction operator N T and superposition operator S T The composition can be specifically represented as:

[0107] d s =L s x s =N T S T xs (2)

[0108] In step two, the roll wave noise d contained in the original seismic data d can be removed. g Transform to the frequency-wavenumber domain to construct the ground roll wave model operator L g Specifically, it is expressed as:

[0109] d g =L g x g (3)

[0110] Among them, L g The frequency wavenumber domain operator for roll wave noise consists of frequency wavenumber domain conversion coefficients, x g This represents the sparse representation of ground roll noise in the frequency wavenumber domain.

[0111] In step three, ignoring the influence of random noise in the seismic data, the problem of suppressing roll wave noise is transformed into solving the objective function J by constructing an objective function in the frequency wavenumber domain. The specific form of the objective function J can be expressed as:

[0112] J=||dL s x s -L g x g || 2 +μ||x g ||1 (4)

[0113] Where μ is the inversion regularization operator, ||x g ||1 represents the ground rolling wave noise d g Apply sparsity constraints.

[0114] In step four, the objective function in equation (4) can be solved through iterative inversion, ultimately yielding the sparse representation x of the roll wave in the frequency-wavenumber domain. g This allows for the prediction of roll wave noise in seismic data. Finally, adaptive subtraction is used to subtract the predicted roll wave noise, thereby suppressing the near-surface roll wave noise.

[0115] Figure 3 This is a schematic diagram illustrating the principle of a near-surface rolling wave noise suppression method according to the present invention.

[0116] Figure 4 These are the test results for the model data. Figure 4 (a) is the input data. Figure 4 (b) shows the result after noise suppression. Figure 4 (c) shows the predicted roll wave noise data.

[0117] Figure 5It is the result of converting the model data to the frequency wavenumber domain. Figure 5 (a) Convert the input data to the frequency-wavenumber domain. Figure 5 (b) is the conversion to the frequency-wavenumber domain after the ground rolling wave is suppressed.

[0118] Figure 6 These are the results of actual earthquake data testing. Figure 6 (a) represents the actual seismic data before the suppression of the roll wave. Figure 6 (b) represents the actual seismic data after the ground roll wave suppression.

[0119] The following section verifies the near-surface roll wave noise suppression method involved in this invention using models and actual data. This method is purely data-driven and requires no prior information such as known subsurface medium structure and velocity models. Compared to traditional roll wave suppression methods based on transform domain filtering, this method can model the effective signal and roll wave noise separately in the frequency and wavenumber domains, and then obtain the suppressed seismic data through iterative inversion using a constructed objective function. Figure 3 This method can suppress ground rolling waves while protecting the effective signal to the greatest extent, thus improving the fidelity of seismic data denoising.

[0120] Model data such as Figure 4 As shown in (a), the model data includes an effective signal satisfying the hyperbolic assumption, roll wave noise, and random noise. Using the roll wave suppression method of this invention, the effective signal and roll wave in the input model data can be modeled separately in the frequency-wavenumber domain, and finally, after inversion, the roll wave-suppressed seismic data is obtained. Figure 4 b) and rolling wave noise ( Figure 4 c). The representations of the input data and the effective signal in the frequency-wavenumber domain are as follows: Figure 5 (a) and Figure 5 As shown in (b), the roll wave frequency component in the model data is significantly suppressed.

[0121] The method was further tested using actual controllable source data from a specific work area. Five actual seismic shots were selected as input data. Figure 5 (a) Using the method of the present invention to suppress roll wave noise, the resulting roll wave suppression effect is as follows: Figure 5 As shown in (b), the strong amplitude roll wave noise is significantly suppressed, and the effective signal is well recovered and reconstructed.

[0122] This invention addresses the challenge of traditional transform domain filtering methods in suppressing near-surface roll wave noise by providing a roll wave noise suppression method based on frequency-wavenumber domain sparse inversion. This method models and constructs objective functions for both the effective signal and roll wave noise in seismic data. Then, it solves these objective functions through sparse inversion, transforming the roll wave noise suppression problem into a least-squares problem of solving the objective function. The multi-dimensional inversion process replaces the traditional transform domain filtering process. This method constrains the inversion results by adding sparsity constraints and a linear search step size, and uses the output of each iteration as feedback for the next iteration, maximizing the preservation of the effective signal within the internal algorithm. Processing results from models and real data demonstrate that this method effectively suppresses roll wave noise in near-surface seismic data, and compared to traditional transform domain filtering methods, it maximizes the preservation of the effective signal.

[0123] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0124] It should be noted that, in this invention, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0125] While the embodiments disclosed in this invention are as described above, the above content is merely for the purpose of facilitating understanding of this invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope disclosed in this invention; however, the scope of patent protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for suppressing near-surface rolling wave noise, characterized in that, The method includes: Sparse constraints are applied to near-surface roll wave noise, and an objective function is constructed by combining a pre-built hyperbolic model operator and a pre-built roll wave model operator. The objective function is sparsely inverted to obtain the sparse term of near-surface roll wave noise; The near-surface rolling wave noise is subtracted from the original seismic data based on the sparse term of the near-surface rolling wave noise in order to suppress the near-surface rolling wave noise.

2. The near-surface roll wave noise suppression method according to claim 1, characterized in that, Constructing the hyperbolic model operator includes: Dynamic correction is performed on the effective signals of reflected waves in the original seismic data to construct a hyperbolic model operator.

3. The near-surface roll wave noise suppression method according to claim 1, characterized in that, Constructing the ground roll wave model operator includes: Near-surface roll wave noise in the original seismic data is converted to the frequency wavenumber domain to construct a roll wave model operator.

4. The near-surface roll wave noise suppression method according to claim 1, characterized in that, The objective function includes the sum of the roll wave noise term and the original seismic data term.

5. The near-surface roll wave noise suppression method according to claim 4, characterized in that, The ground roll noise term includes the product of the inversion regularization operator and the sparse constraint on the ground roll noise.

6. The near-surface roll wave noise suppression method according to claim 4, characterized in that, The original seismic data items include: The second norm of the difference between the raw seismic data and the pre-built hyperbolic model operator and the pre-built ground roll wave model operator.

7. A near-surface rolling wave noise suppression device, characterized in that, The device includes: The modeling module is used to apply sparse constraints to near-surface roll wave noise and to construct the objective function by combining pre-built hyperbolic model operators and pre-built roll wave model operators. The inversion module is used to perform sparse inversion on the objective function to obtain the sparse term of near-surface roll wave noise; The suppression module is used to subtract the near-surface rolling wave noise from the original seismic data based on the sparse term of the near-surface rolling wave noise, so as to suppress the near-surface rolling wave noise.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the near-surface rolling wave noise suppression method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the near-surface rolling wave noise suppression method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the near-surface rolling wave noise suppression method according to any one of claims 1 to 6.

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