Frequency-space domain alternating iterative seismic random noise suppression method and system

Abstract

The application discloses a frequency-space domain alternating iteration seismic random noise suppression method and system, transforms a seismic signal from a time-space domain to a frequency-space domain, and obtains a frequency slice by taking data of a fixed frequency domain index; arranges the frequency slice into a Hankel matrix and performs singular value decomposition, selects singular values and corresponding singular vectors to perform rank reduction reconstruction on the Hankel matrix; obtains the reconstructed frequency slice, and takes the next frequency slice to complete spatial direction denoising; takes single seismic trace data of a fixed space domain index in the frequency-space domain data, arranges the single seismic trace data into a Hankel matrix and performs singular value decomposition, selects singular values and corresponding singular vectors to perform rank reduction reconstruction on the Hankel matrix; then, the reconstructed single seismic trace data is obtained through anti-diagonal average, the next seismic trace data is taken, the obtained frequency-space domain data after denoising is transformed back to the time-space domain, and a signal after noise suppression is obtained.

Description

Technical Field

[0001] This invention belongs to the field of exploration geophysics technology, specifically relating to a method and system for suppressing seismic random noise through alternating frequency-spatial domain iteration. Background Technology

[0002] Seismic exploration is a primary method for finding underground resources such as oil and natural gas. However, due to various interferences from the natural environment and human factors, seismic data acquired in the field often contains a large amount of random noise, severely masking the effective signals reflected by the subsurface medium and rendering them unobservable. Suppressing seismic random noise is extremely important for subsequent data stacking, migration, and interpretation. Currently available methods for suppressing seismic random noise mainly include:

[0003] Existing technology 1: Transform-based noise suppression method

[0004] Transformers such as Short-Time Fourier Transform and Wavelet Transform transform seismic data from the time-space domain to their respective transform domains. Then, values ​​belonging to random noise regions are filtered out, and finally, the data is transformed back to the time-space domain to obtain the noise-suppressed seismic data.

[0005] Disadvantages of prior art 1:

[0006] In actual seismic data, effective signals and random noise are usually mixed together in the transform domain, making it impossible to completely suppress random noise and easily damaging the effective signal.

[0007] Prior art 2: f-x Noise suppression methods for the domain

[0008] like f-x Domain prediction filtering, Cadzow filtering, and other methods utilize the continuity of the effective signal in the spatial direction and the discontinuity of random noise in the spatial direction to predict the effective signal and suppress random noise at the same time.

[0009] Disadvantages of prior art 2:

[0010] When the random noise in the seismic data is strong f-x Noise suppression methods in the domain can result in a large amount of residual random noise. Summary of the Invention

[0011] The technical problem to be solved by the present application is to provide a frequency-space domain alternating iteration seismic random noise suppression method and system to solve the technical problem of incomplete suppression of random noise by the prior art noise suppression method.

[0012] The present application adopts the following technical solutions:

[0013] The frequency-space domain alternating iteration seismic random noise suppression method comprises the following steps:

[0014] The seismic signal is transformed from the time-space domain to the frequency-space domain by Fourier transform, and data with a fixed frequency domain index is taken from the frequency-space domain data to obtain a frequency slice.

[0015] The frequency slice is arranged into a Hankel matrix, and singular value decomposition is performed on the Hankel matrix, and the first r largest singular values and corresponding singular vectors are selected to perform rank reduction reconstruction on the Hankel matrix.

[0016] The rank reduction reconstructed Hankel matrix is subjected to anti-diagonal line averaging to obtain the reconstructed frequency slice, and the next frequency slice is taken until all frequency slices are processed, and the spatial direction denoising is completed.

[0017] Single seismic trace data with a fixed spatial domain index is taken from the frequency-space domain data, and the single seismic trace data is arranged into a Hankel matrix and subjected to singular value decomposition, and the first r largest singular values and corresponding singular vectors are selected to perform rank reduction reconstruction on the Hankel matrix.

[0018] The rank reduction reconstructed Hankel matrix is subjected to anti-diagonal line averaging to obtain the reconstructed single seismic trace data, and the next seismic trace data is taken until all seismic traces are processed, and the frequency direction denoising is completed to obtain the denoised frequency-space domain data The processed frequency-space domain data is transformed back to the time-space domain by Fourier inverse transform to obtain the noise suppressed signal .

[0019] Preferably, the seismic signal is transformed from the time-space domain to the frequency-space domain by Fourier transform, and the expression of the first trace signal in the frequency-space domain is:

[0020] ​

[0021] wherein, is the number of time domain sampling points of the signal, is the time domain index, is the frequency domain index, is the unit of imaginary part in complex number operation.

[0022] Preferably, the first r largest singular values and corresponding singular vectors are selected to reduce the rank of the Hankel matrix as follows:

[0023]

[0024] wherein, is the i largest singular value, is its corresponding left singular vector, is its corresponding right singular vector, is the reduced rank Hankel matrix.

[0025] Preferably, the singular value decomposition of the Hankel matrix is as follows:

[0026]

[0027] wherein, is the rank of the matrix, usually the smaller of the number of rows and columns of the matrix.

[0028] Preferably, the single seismic trace data is arranged into a Hankel matrix and the singular value decomposition of the Hankel matrix is as follows:

[0029]

[0030] wherein, is the i largest singular value, is its corresponding left singular vector, is its corresponding right singular vector.

[0031] Preferably, the single seismic trace data is arranged into a Hankel matrix as follows:

[0032]

[0033] wherein, N is the number of points of Fourier transform, is the fixed spatial domain index, is the number of columns of the matrix selected artificially.

[0034] Preferably, the fixed spatial domain index , to obtain the data of single seismic trace signal in frequency domain:

[0035]

[0036] Preferably, the frequency-space domain data after noise suppression is obtained Specifically:

[0037] The reconstructed matrix According to the inverse process of arranging Hankel matrix, the anti-diagonal line average is performed, that is, the elements on each anti-diagonal line of the matrix are averaged to restore one-dimensional single seismic trace data; the spatial domain index is changed , the next data is taken out, and the repetition is performed until all seismic traces are processed; the steps S1-S4 are repeatedly executed, the rank reduction noise suppression in frequency and spatial directions is alternately performed, and the iteration number reaches the preset iteration number, to obtain the frequency-space domain data after noise suppression .

[0038] Preferably, the signal after noise suppression is:

[0039]

[0040] , wherein, is the number of time domain sampling points of the signal, is the time domain index, is the frequency domain index, is the unit of the imaginary part in complex operation.

[0041] In the second aspect, the embodiment of the present application provides a frequency-space domain alternating iteration seismic random noise suppression system, which comprises:

[0042] A transformation module is configured to transform the seismic signal from time-space domain to frequency-space domain by Fourier transform, take the data with fixed frequency domain index in the frequency-space domain data, to obtain a frequency slice;

[0043] A first reconstruction module is configured to arrange the frequency slice into a Hankel matrix, perform singular value decomposition on the Hankel matrix, select the first r largest singular values and corresponding singular vectors to perform rank reduction reconstruction on the Hankel matrix;

[0044] A denoising module is configured to perform anti-diagonal line average on the rank reduction reconstructed Hankel matrix to obtain the reconstructed frequency slice, take the next frequency slice, and perform the spatial direction noise suppression until all frequency slices are processed.

[0045] A second reconstruction module is configured to take the data with fixed spatial domain index The single seismic trace data is arranged into a Hankel matrix and singular value decomposition is performed on the Hankel matrix, the first r largest singular values and corresponding singular vectors are selected to perform rank reduction reconstruction on the Hankel matrix;

[0046] The output module performs anti-diagonal average on the rank reduction reconstructed Hankel matrix to obtain reconstructed single seismic trace data, takes the next seismic trace data, and processes all seismic traces until the frequency direction denoising is completed to obtain denoised frequency-space domain data The Fourier transform is performed on the processed frequency-space domain data to transform back to the time-space domain to obtain the noise suppressed signal .

[0047] In a third aspect, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the frequency-space domain alternating iterative seismic random noise suppression method when executing the computer program.

[0048] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium including a computer program, and the computer program implements the steps of the frequency-space domain alternating iterative seismic random noise suppression method when executed by a processor.

[0049] In a fifth aspect, a chip includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the frequency-space domain alternating iterative seismic random noise suppression method when executing the computer program.

[0050] In a sixth aspect, an embodiment of the present application provides an electronic device including a computer program, and the computer program implements the steps of the frequency-space domain alternating iterative seismic random noise suppression method when executed by the electronic device.

[0051] Compared with the prior art, the present application has at least the following beneficial effects:

[0052] The application discloses a frequency-space domain alternating iteration seismic random noise suppression method, which comprises the following steps: firstly, changing a seismic signal from a time-space domain to a frequency-space domain; then, constructing a Hankel matrix in a frequency direction and performing rank reduction reconstruction on the Hankel matrix to complete frequency direction denoising; then, constructing a Hankel matrix in a space direction again and performing rank reduction reconstruction on the Hankel matrix to complete space direction denoising; then, performing rank reduction denoising from the frequency and space directions again; and finally, alternating iteration is performed to complete the suppression of the seismic random noise.

[0053] Further, the seismic signal is subjected to Fourier transform, and the seismic signal is changed from the time-space domain to the frequency-space domain, so that the effective signal presents linear phase characteristics in the frequency-space domain, and the random noise does not have linear phase characteristics in the frequency-space domain, thereby facilitating subsequent removal of the random noise.

[0054] Further, the first r largest singular values and the corresponding singular vectors are selected to perform rank reduction reconstruction on the Hankel matrix, so that the main singular components corresponding to the main singular values of the effective signal are reserved, and the secondary singular components mainly including the random noise are removed.

[0055] Further, the single seismic trace data is arranged into the Hankel matrix, and the Hankel matrix is subjected to singular value decomposition, so that the effective signal characteristics in the single trace data can be fully extracted, the effective signal components are concentrated in the components corresponding to the larger singular values, and subsequent suppression of the random noise is facilitated.

[0056] Further, the reconstructed matrix is subjected to anti-diagonal line averaging according to the inverse process of arranging the Hankel matrix, that is, the elements on each anti-diagonal line of the matrix are averaged to restore one-dimensional single seismic trace data, so that the dimensionality of the dimensionality-raised single seismic trace data is restored, and the random noise suppression effect is achieved by averaging the elements.

[0057] It can be understood that the beneficial effects of the second aspect to the sixth aspect can be referred to the related description in the first aspect, and will not be repeated here.

[0058] In conclusion, the application adopts the space-frequency direction alternating iteration denoising method, which is superior to the traditional method of denoising in the space direction only, improves the correlation of the effective signal in the frequency direction, and enables the denoising process to be repeatedly performed in the space and frequency directions, so that the random noise suppression is more thorough, and the fidelity of the effective signal is higher.

[0059] The technical scheme of the application will be further described in detail through the drawings and the embodiments. Attached Figure Description

[0060] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application 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.

[0061] Figure 1 This is a flowchart of the present invention;

[0062] Figure 2 This is a two-dimensional seismic signal map containing random noise;

[0063] Figure 3 shows the results of the Cadzow filtering method, where (a) is the noise suppression result and (b) is the difference profile.

[0064] Figure 4 is a schematic diagram of the results of the method of the present invention, wherein (a) is the noise suppression result and (b) is the difference profile;

[0065] Figure 5 A schematic diagram of a computer device provided in an embodiment of the present invention;

[0066] Figure 6 This is a block diagram of an electronic device according to an embodiment of the present invention.

[0067] Among them, 60. Computer equipment; 61. Processor; 62. Memory; 63. Computer program; 600. Electronic device; 610. Processing unit; 620. Storage unit; 6201. Random access memory unit; 6202. Cache memory unit; 6203. Read-only memory unit; 6204. Program / utility; 6205. Program module; 630. Bus; 640. Display unit; 650. Input / output interface; 660. Network adapter; 700. External device. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments 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 are within the scope of protection of the present invention.

[0069] In the description of the present application, it should be understood that the terms "include" and "comprise" indicate the presence of the described features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0070] It should also be understood that the terms used in the present application specification are only for the purpose of describing particular embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0071] It should be further understood that the term "and / or" used in the present application specification is intended to mean one or more of the associated listed items, as well as all possible combinations of the items, and includes these combinations, for example, A and / or B can mean A alone, A and B together, or B alone. In addition, the character " / " in the present application generally represents an "or" relationship between the objects before and after it.

[0072] It should be understood that although the terms first, second, third, etc. can be used in the embodiments of the present application to describe a certain range, etc., these ranges should not be limited by these terms. These terms are only used to distinguish the ranges from each other. For example, the first range can also be referred to as the second range, and similarly, the second range can also be referred to as the first range, without departing from the scope of the embodiments of the present application.

[0073] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to determining" or "in response to detecting." Similarly, the phrase "if determined" or "if detecting (a stated condition or event)" can be interpreted to mean "when determined" or "in response to determining" or "when detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)," depending on the context.

[0074] Various structural diagrams according to the disclosed embodiments of the present application are shown in the accompanying drawings. These drawings are not drawn to scale, in which certain details are exaggerated for the purpose of clarity and some details can be omitted. The shapes of various regions, layers, and their relative sizes and positional relationships shown in the drawings are only exemplary, and in actuality, they can deviate due to manufacturing tolerances or technical limitations, and a person skilled in the art can additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0075] The application provides a frequency-space domain alternating iterative seismic random noise suppression method, which uses two-dimensional seismic data, transforms the data to a frequency-space domain, and alternately constructs a Hankel matrix and reconstructs the rank of the data from a spatial direction and a frequency direction in an iterative manner to achieve the purpose of suppressing random noise.

[0076] Embodiment 1

[0077] Please refer to Figure 1 The application provides a frequency-space domain alternating iterative seismic random noise suppression method, which comprises the following steps:

[0078] S1, Fourier transform is used to transform a seismic signal from a time-space domain to a frequency-space domain, and data of a certain fixed frequency point in the frequency-space domain data is taken to obtain a frequency slice;

[0079] The discrete Fourier transform is performed on each channel signal in the two-dimensional seismic data, and the Fourier transform of the first channel signal is taken as an example.

[0080]

[0081] Among them, is the time domain sampling point number of the signal, is a time domain index, is a frequency domain index, is the unit of the imaginary part in complex number operation, is the expression of the signal in the frequency-space domain.

[0082] The frequency domain index is fixed, and the frequency domain index corresponding to the frequency slice is obtained.

[0083]

[0084] Among them, is the number of channels of the two-dimensional seismic data.

[0085] S2, the frequency slice is arranged into a Hankel matrix, and singular value decomposition is performed on the Hankel matrix, and the front several larger singular values and corresponding singular vectors are selected to reconstruct the rank of the Hankel matrix;

[0086] The frequency slice is arranged into a Hankel matrix :

[0087]

[0088] The singular value decomposition is performed on the matrix :

[0089] ​​

[0090] in, For the first i Large singular values, Let it be its corresponding left singular vector. It is its corresponding right singular vector.

[0091] Select the first r largest singular values ​​and their corresponding singular vectors to form a matrix. The rank reduction reconstruction is performed as follows:

[0092]

[0093] S3. Average the reconstructed Hankel matrix along the anti-diagonal to obtain the reconstructed frequency slices. Take the next frequency slice and repeat until all frequency slices have been processed to complete spatial directional denoising.

[0094] For the reconstructed matrix Following the inverse process of arranging the Hankel matrix, anti-diagonal averaging is performed, that is, averaging the elements along each anti-diagonal line of the matrix to reconstruct a one-dimensional frequency slice; the frequency domain index is then changed. Remove the next frequency slice and repeat until all frequency slices have been processed.

[0095] S4. Take data from a single seismic trace in the frequency-spatial domain data, arrange the single seismic trace data into a Hankel matrix, and perform singular value decomposition on the Hankel matrix. Select the first few larger singular values ​​and their corresponding singular vectors to reconstruct the Hankel matrix by reducing its rank.

[0096] Fixed spatial domain index The frequency domain data of the single seismic trace signal were obtained:

[0097]

[0098] in, N is the number of points in the Fourier transform.

[0099] Arrange single seismic trace data into a Hankel matrix. :

[0100]

[0101] For matrix Perform singular value decomposition:

[0102]

[0103] in, For the first i Large singular values, Let it be its corresponding left singular vector. It is its corresponding right singular vector.

[0104] Select the first r largest singular values ​​and their corresponding singular vectors to form a matrix. Perform rank reduction reconstruction:

[0105]

[0106] S5. Average the reconstructed Hankel matrix using its anti-diagonal method to obtain the reconstructed single-trace data. Then, take the next trace data and repeat this process until all traces have been processed, completing frequency denoising to obtain the denoised frequency-spatial domain data. The frequency-space domain data obtained by the inverse Fourier transform is then processed. Transform back into the time-space domain to obtain the noise-suppressed signal. .

[0107] For the reconstructed matrix By performing anti-diagonal averaging—that is, averaging the elements along each anti-diagonal line of the matrix—one-dimensional single-trace data can be reconstructed. This involves changing the spatial domain indices. Take the next data trace and repeat until all seismic traces have been processed; repeat steps S1-S4, alternating between frequency and spatial direction rank reduction and denoising, until the preset number of iterations is reached, to obtain the denoised frequency-spatial domain data. .

[0108] Signal after noise suppression for:

[0109]

[0110] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "platform."

[0111] Example 2

[0112] This invention provides a frequency-spatial domain alternating iterative seismic noise suppression system. This system can be used to implement the above-mentioned frequency-spatial domain alternating iterative seismic noise suppression method. Specifically, the frequency-spatial domain alternating iterative seismic noise suppression system includes a transformation module, a first reconstruction module, a denoising module, a second reconstruction module, and an output module.

[0113] The transform module transforms the seismic signal from a time-space domain to a frequency-space domain by Fourier transform, and obtains a frequency slice by taking a fixed frequency domain index in the frequency-space domain data

[0114] The first reconstruction module arranges the frequency slice into a Hankel matrix, and performs singular value decomposition on the Hankel matrix, selects the first r largest singular values and corresponding singular vectors to perform rank reduction reconstruction on the Hankel matrix.

[0115] The denoising module performs anti-diagonal average on the rank reduction reconstructed Hankel matrix to obtain the reconstructed frequency slice, takes the next frequency slice, and processes all the frequency slices until the spatial direction denoising is completed.

[0116] The second reconstruction module takes single seismic trace data with a fixed spatial domain index The first reconstruction module arranges the frequency slice into a Hankel matrix, and performs singular value decomposition on the Hankel matrix, selects the first r largest singular values and corresponding singular vectors to perform rank reduction reconstruction on the Hankel matrix.

[0117] The output module performs anti-diagonal average on the rank reduction reconstructed Hankel matrix to obtain the reconstructed single seismic trace data, takes the next seismic trace data, and processes all the seismic traces until the frequency direction denoising is completed, to obtain the denoised frequency-space domain data The transform module transforms the seismic signal from a time-space domain to a frequency-space domain by Fourier transform, and obtains a frequency slice by taking a fixed frequency domain index in the frequency-space domain data The transform module transforms the seismic signal from a time-space domain to a frequency-space domain by Fourier transform, and obtains a frequency slice by taking a fixed frequency domain index in the frequency-space domain data .

[0118] Example 3

[0119] ​The application provides a terminal device, which comprises a processor and a memory for storing a computer program, wherein the computer program comprises program instructions, and the processor is used for executing the program instructions stored in the computer storage medium. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components and the like, which are the computing core and control core of the terminal, and are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions to implement a corresponding method flow or a corresponding function. The processor in the embodiment of the application can be used for the operation of the frequency-space domain alternating iteration seismic random noise suppression method, comprising:

[0120] The seismic signal is transformed from the time-space domain to the frequency-space domain by using Fourier transform, and the data of a fixed frequency domain index in the frequency-space domain data is taken to obtain a frequency slice; the frequency slice is arranged into a Hankel matrix, and singular value decomposition is performed on the Hankel matrix, the first r largest singular values and corresponding singular vectors are selected, and the Hankel matrix is reconstructed in a reduced rank; the Hankel matrix after the reduced rank reconstruction is subjected to anti-diagonal line averaging to obtain the reconstructed frequency slice, the next frequency slice is taken, and the processing of all the frequency slices is completed until the spatial direction denoising is completed; single seismic trace data of a fixed spatial domain index in the frequency-space domain data is taken, the single seismic trace data is arranged into a Hankel matrix, and singular value decomposition is performed on the Hankel matrix, the first r largest singular values and corresponding singular vectors are selected, and the Hankel matrix is reconstructed in a reduced rank; the Hankel matrix after the reduced rank reconstruction is subjected to anti-diagonal line averaging to obtain the reconstructed single seismic trace data, the next seismic trace data is taken, and the processing of all the seismic traces is completed until the frequency direction denoising is completed, and the frequency-space domain data after denoising is obtained The frequency-space domain data obtained by processing is transformed back to the time-space domain by using Fourier inverse transform to obtain a signal after noise suppression .

[0121] Please refer to Figure 5 The terminal device is a computer device. The computer device 60 in this embodiment includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. The computer program 63, when executed by the processor 61, implements the frequency-space domain alternating iterative seismic random noise suppression method in the embodiment. To avoid repetition, details are not described here. Alternatively, the computer program 63, when executed by the processor 61, implements the functions of each model / unit in the frequency-space domain alternating iterative seismic random noise suppression system in the embodiment. To avoid repetition, details are not described here.

[0122] The computer device 60 can be a desktop computer, a notebook computer, a palm computer, a cloud server, or the like. The computer device 60 can include, but is not limited to, the processor 61 and the memory 62. Those skilled in the art can understand that Figure 5 The computer device 60 is only an example and does not constitute a limitation on the computer device 60. The computer device 60 can include more or fewer components than shown, or combine certain components, or include different components, for example, the computer device can also include an input / output device, a network access device, a bus, and the like.

[0123] The processor 61 can be a central processing unit (CPU), and can also be other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, or the like. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0124] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or a memory of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like.

[0125] Further, the memory 62 can include both the internal storage unit of the computer device 60 and the external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0126] Referring to Figure 6 , the terminal device is an electronic device 600, which is in the form of a general computing device. The components of the electronic device can include, but are not limited to, at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, and the like.

[0127] Among them, the storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 executes the steps according to various exemplary embodiments of the present application described in the method part of the present specification. For example, the processing unit 610 can execute the steps as shown in Figure 1 .

[0128] The storage unit 620 can include a readable medium in the form of a volatile storage unit, such as a random access memory (RAM) 6201 and / or a cache memory unit 6202, and can further include a read-only memory (ROM) 6203.

[0129] The storage unit 620 can further include a program / utility 6204 having a set of (at least one) program modules 6205, including but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or a combination of which can include the implementation of a network environment.

[0130] The bus 630 can be one or more of several types of bus structures, including a storage unit bus or storage unit controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of a variety of bus structures.

[0131] The electronic device 600 can also communicate with one or more external devices 700 such as a keyboard or pointing device, a Bluetooth device, or a database, and / or one or more devices that enable a user to interact with the electronic device 600 and / or one or more devices (e.g., routers, modems) that enable the electronic device 600 to communicate with one or more other computing devices. The communication can be via the input / output interface(s) 650. Still yet, the electronic device 600 can communicate with one or more networks, such as one or more local area networks, wide area networks, and / or public networks, such as the Internet, via the network adapter 660. The network adapter 660 can communicate with the other components of the electronic device 600 via the bus 630. It should be appreciated that although the network adapter 660 is shown as a single component, the network adapter 660 can comprise two or more components that work together to allow the electronic device 600 to communicate with one or more networks. It should be appreciated that although not shown, other hardware and / or software components that are commonly used in computing devices, such as a disk controller, a graphics processor, a high- speed controller, and the like, can also be included in the electronic device 600.

[0132] Embodiment 4

[0133] The present application also provides a storage medium, specifically a computer readable storage medium, which is a memory device in the terminal device, and is used to store programs and data. It should be understood that the computer readable storage medium herein can include the built-in storage medium in the terminal device, and of course can also include the expansion storage medium supported by the terminal device, and can be any tangible medium containing or storing programs, which can be used by or in combination with an instruction execution system, device or apparatus. The computer readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and the instructions can be one or more computer programs (including program codes). It should be noted that more specific examples of the computer readable storage medium include an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0134] Computer readable storage media further includes data signals transported through a carrier wave and a propagation medium comprising or storing the program code. These data signals can be taken to further include any information delivery or transport media. Computer readable storage media can be any available media that can be accessed by a general purpose or special purpose computing device. By way of example, and not limitation, such computer readable storage media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other storage medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a general-purpose or special-purpose computing device, also referred to as computer readable media. Combinations of the above should also be included within the scope of computer readable media.

[0135] instructions in any combination of one or more programming languages including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages such as "C" or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network ("LAN") or a wide area network ("WAN"), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider ("ISP").

[0136] The one or more instructions stored in the computer readable storage medium can be executed by a processor to implement the corresponding steps of the frequency-space domain alternating iterative seismic random noise suppression method described in the above embodiments; the one or more instructions stored in the computer readable storage medium are loaded and executed by the processor to implement the following steps:

[0137] The seismic signal is transformed from the time-space domain to the frequency-space domain by using Fourier transform, and data with a fixed frequency domain index in the frequency-space domain data is taken to obtain a frequency slice; the frequency slice is arranged into a Hankel matrix, and singular value decomposition is performed on the Hankel matrix, and the Hankel matrix is reconstructed in a reduced rank by selecting the first r largest singular values and corresponding singular vectors; the Hankel matrix reconstructed in the reduced rank is subjected to anti-diagonal average to obtain a reconstructed frequency slice, and the next frequency slice is taken until all the frequency slices are processed, and spatial direction denoising is completed; data with a fixed spatial domain index The single seismic trace data is arranged into a Hankel matrix and singular value decomposition is performed on the Hankel matrix, the first r largest singular values and corresponding singular vectors are selected to perform rank reduction reconstruction on the Hankel matrix; the rank reduction reconstructed Hankel matrix is subjected to anti-diagonal average to obtain reconstructed single seismic trace data, the next seismic trace data is taken, and the processing is completed on all seismic traces, the frequency direction denoising is completed, and the denoised frequency-space domain data is obtained The frequency-space domain data obtained by processing is transformed back to the time-space domain by Fourier inverse transform to obtain the noise suppressed signal .

[0138] The database involved in each embodiment provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, and the like, without being limited thereto. The processor involved in each embodiment provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, and the like, without being limited thereto.

[0139] In order to make the objects, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present application belong to the scope of protection of the present application.

[0140] Please refer to Figure 2 , the horizontal coordinate is the number of seismic traces, the vertical coordinate is time, the sampling interval is 2 ms, and there are 500 sampling points, which is the noisy data used for noise suppression.

[0141] Please refer to FIG. 3, wherein FIG. 3(a) is the noise suppression result of the Cadzow filtering method, and FIG. 3(b) is the difference profile of FIG. 3(a) and FIG. 1(a). Figure 2 The noise suppression result can basically filter out most of the random noise in the noisy data, but still contains a large amount of random noise residues.

[0142] Please refer to FIG. 4, wherein FIG. 4(a) is the noise suppression result of the method of the present application, and FIG. 4(b) is the difference profile of FIG. 4(a) and FIG. 1(a).​Figure 2 The random noise residual in the noise suppression result of the method is less than that in the difference profile of Figure 3, which shows that the effect of suppressing random noise by the method is more thorough, and the difference profile does not contain effective signal components, and the signal-to-noise ratio of the noise suppression result is higher.

[0143] In summary, the frequency-space domain alternating iterative seismic random noise suppression method and system constructs a Hankel matrix for seismic data in the spatial and frequency directions respectively, and performs rank reduction reconstruction denoising, and alternately iterates in the spatial and frequency directions for denoising, which can more thoroughly suppress random noise in seismic data and make the fidelity of effective signals higher.

[0144] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is exemplified, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of each functional unit and module are only for easy distinction, and do not limit the protection scope of the application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0145] In the above embodiments, the description of each embodiment has its own emphasis, and the parts not described or recorded in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0146] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0147] In the embodiments of the present application, it should be understood that the disclosed apparatus / terminal and method can be implemented in other manners. For example, the embodiments of the apparatus / terminal described above are merely schematic, and the division of the modules or units is merely logical function division, and there can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between the units can be indirect couplings or communication connections through some interfaces, devices or units, and can be electrical, mechanical or in other forms.

[0148] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0149] In addition, each functional unit in the various embodiments of the present application can be integrated into a processing unit, or each unit can be a physically independent unit, or two or more units can be integrated into a unit. The integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0150] The integrated module / unit, if implemented in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the above-mentioned embodiment methods can be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the processor executes the computer program, the steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable file or some intermediate form. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the computer readable medium can include or exclude contents according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0151] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 means for functionally implementing the steps in one or more flow or blocks

[0152] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 means for functionally implementing the steps in one or more flow or blocks

[0153] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 means for functionally implementing the steps in one or more flow or blocks

[0154] The above merely provides the technical idea of the present application, and cannot be used to limit the protection scope of the present application. Any modification made according to the technical idea of the present application, on the basis of the technical solutions, falls within the protection scope of the claims of the present application.

Claims

1. A frequency-space domain alternating iterative seismic random noise suppression method, characterized in that, The method comprises the following steps: The seismic signal is transformed from time-space domain to frequency-space domain by Fourier transform, and the data with fixed frequency domain index is obtained from the frequency-space domain data to obtain a frequency slice. The frequency slices are arranged into a Hankel matrix, and singular value decomposition is performed on the Hankel matrix, the first r largest singular values and corresponding singular vectors are selected, and the Hankel matrix is reconstructed in a reduced rank; The reduced rank reconstructed Hankel matrix is subjected to anti-diagonal line averaging to obtain reconstructed frequency slices, the next frequency slice is taken, and the processing of all frequency slices is completed until spatial direction denoising is completed; Taking fixed spatial domain index in frequency-space domain data Single seismic trace data is arranged into a Hankel matrix and singular value decomposition is performed on the Hankel matrix, the first r largest singular values and corresponding singular vectors are selected, and the Hankel matrix is reconstructed in a reduced rank manner. The Hankel matrix of the reduced rank reconstruction is inversely diagonally averaged to obtain the reconstructed single seismic trace data, the next seismic trace data is taken, and the processing is completed for all seismic traces to complete frequency direction denoising to obtain denoised frequency-space domain data The frequency-space domain data obtained by processing is transformed back to the time-space domain by Fourier inverse transform to obtain the noise-suppressed signal .​ 2. The frequency-space domain alternating iterative seismic random noise suppression method of claim 1, wherein, The seismic signal is transformed from time-space domain to frequency-space domain by Fourier transform, and the expression of the seismic signal in frequency-space domain is: The seismic signal The expression of the seismic signal in frequency-space domain is: ​ wherein, is the number of time-domain sampling points of a signal, is a time-domain index, is a frequency-domain index, is the unit of the imaginary part in complex number operation.

3. The frequency-space domain alternating iterative seismic random noise suppression method of claim 1, wherein, The first r largest singular values and corresponding singular vectors are selected to reconstruct the Hankel matrix in a reduced rank as follows: wherein, is the i largest singular value, is its corresponding left singular vector, is its corresponding right singular vector, is the Hankel matrix obtained after the rank reduction reconstruction.

4. The frequency-space domain alternating iterative seismic random noise suppression method of claim 3, wherein, The singular value decomposition of the Hankel matrix is as follows: wherein is the rank of the matrix.

5. The frequency-space domain alternating iterative seismic random noise suppression method of claim 1, wherein, The single seismic trace data is arranged into a Hankel matrix, and singular value decomposition is performed on the Hankel matrix as follows: wherein is the i largest singular value, is its corresponding left singular vector, is its corresponding right singular vector.

6. The frequency-space domain alternating iterative seismic random noise suppression method of claim 5, wherein, Single seismic trace data is arranged into a Hankel matrix As follows: wherein N is the number of points of the Fourier transform, is the fixed spatial domain index, is the number of columns of the artificially selected matrix.

7. The frequency-space domain alternating iterative seismic random noise suppression method of claim 5, wherein, Fixed spatial domain index Obtaining data in the frequency domain of a single seismic trace signal: 。 8. The frequency-space domain alternating iterative seismic random noise suppression method of claim 1, wherein, obtaining de-noised frequency-space domain data Specifically: reconstructed matrix The inverse process of arranging Hankel matrix is performed, i.e. the elements on each anti-diagonal line of the matrix are averaged to restore one-dimensional single seismic trace data; the spatial domain index is changed, the next trace data is taken out, and the process is repeated until all seismic traces are processed. The steps S1-S4 are repeatedly performed, and the frequency and spatial direction are alternately reduced in rank for denoising until a preset iteration number is reached, to obtain frequency-spatial domain data after denoising .

9. The frequency-space domain alternating iterative seismic random noise suppression method of claim 1, wherein, Noise suppressed signal Is: wherein, is the number of time domain sampling points of the signal, is the time domain index, is the frequency domain index, is the unit of imaginary part in complex operation.

10. A frequency-space domain alternating iterative seismic random noise suppression system, characterized in that, The method comprises the following steps: The transformation module uses Fourier transform to transform the seismic signal from the time-space domain to the frequency-space domain, and extracts fixed frequency domain indices from the frequency-space domain data. From the data, frequency slices are obtained; The first reconstruction module arranges the frequency slices into a Hankel matrix, performs singular value decomposition on the Hankel matrix, selects the first r largest singular values and corresponding singular vectors, and reconstructs the Hankel matrix in a reduced rank; The denoising module subjects the reduced rank reconstructed Hankel matrix to anti-diagonal line averaging to obtain reconstructed frequency slices, takes the next frequency slice, and processes all frequency slices until spatial direction denoising is completed; a second reconstruction module, taking a fixed spatial domain index in the frequency-space domain data singular value decomposition is performed on the Hankel matrix, and the first r largest singular values and corresponding singular vectors are selected to perform rank reduction reconstruction on the Hankel matrix; The output module averages the reduced rank reconstruction Hankel matrix by anti-diagonal lines to obtain reconstructed single seismic trace data, takes the next seismic trace data, and processes all seismic traces until the frequency direction denoising is completed to obtain denoised frequency-space domain data The Fourier inverse transform is used to transform the processed frequency-space domain data back to the time-space domain to obtain the noise-suppressed signal .

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