Surface wave data processing method and device, equipment and medium

Abstract

The invention relates to a surface wave data processing method, device, equipment and medium, and the method comprises the steps: converting original seismic data in a target work area into a plurality of primary functions; correcting a pre-generated spatial model according to the plurality of primary functions, the spatial model being generated by the plurality of primary functions; and processing the surface wave data in the original seismic data according to the corrected space model and the frequency dispersion curve of the surface wave data in the original seismic data so as to separate and obtain an effective reflection signal of the original seismic data. According to the invention, effective separation of effective reflection signals in original seismic data can be realized under complex working conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas geophysical exploration, and in particular to a surface wave data processing method, device, equipment and medium. Background Art

[0002] It is understandable that surface waves are widely present in seismic data collected in the field and are an important factor restricting the quality of seismic data. Surface waves are a very common noise that is characterized by low frequency, low speed, strong energy, and has dispersion and multi-mode properties. In order to make effective signals such as reflected waves and refracted waves more prominent, it is necessary to effectively suppress and eliminate surface wave noise.

[0003] The strength of surface wave energy is related to the exciting lithology, exciting depth and surface seismic geological conditions. Especially when the amplitude of effective reflection signals in deep and ultra-deep layers is relatively weak, the high amplitude and strong dispersion of surface waves have a strong masking effect on effective signals.

[0004] At present, with the complexity of field exploration terrain and the increase in the burial depth of underground target layers, the difficulty in distinguishing surface waves from effective reflection signals has become increasingly prominent. There is an urgent need for a technology that can effectively separate effective reflection signals from original seismic data under complex working conditions. Summary of the invention

[0005] The present invention provides a method, device, equipment and medium for processing surface wave data, so as to solve the problem that surface wave and effective reflection signal are difficult to distinguish.

[0006] To achieve the above object, in a first aspect, the present invention provides a method for processing surface roll data, comprising:

[0007] Converting the original seismic data in the target work area into multiple basis functions;

[0008] modifying a pre-generated spatial model according to the plurality of basis functions, wherein the spatial model is generated by the plurality of basis functions;

[0009] Acquiring surface wave data from the original seismic data;

[0010] The surface wave data in the original seismic data are processed according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data to separate and obtain effective reflection signals of the original seismic data.

[0011] Preferably, the converting of the original seismic data in the target work area into a plurality of basis functions comprises:

[0012] Converting the raw seismic data into a discrete time series;

[0013] In the potential energy-wave function domain of the original seismic data, the discrete time series is decomposed channel by channel to generate multiple basis functions, and the multiple basis functions include one or more of polynomial basis functions, Fourier basis functions, wavelet basis functions, Gaussian basis functions, B-spline basis functions, Laguerre basis functions, Chebyshev basis functions and orthogonal basis functions.

[0014] Preferably, before the pre-generated spatial model is modified according to the multiple basis functions, and after the original seismic data in the target work area is converted into the multiple basis functions, the method further includes:

[0015] Generate a loss function according to the multiple basis functions and the discrete time series; wherein the loss function is used to characterize the error between the multiple basis functions and the discrete time series;

[0016] The loss function is defined as:

[0017]

[0018] in δ is a tuning parameter, y i is the basis function, is the discrete time series;

[0019] The step of modifying the pre-generated spatial model according to the plurality of basis functions comprises:

[0020] Correcting a pre-generated spatial model based on errors between the plurality of basis functions and the original seismic data;

[0021] The processing of the surface wave data according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data to separate and obtain the effective reflection signal of the original seismic data includes:

[0022] Solving the loss function according to the modified spatial model to determine the amplitude, phase and travel time of the spatial model;

[0023] performing bilateral filtering on the amplitude, the phase and the travel time respectively;

[0024] The surface roll data in the original seismic data is processed according to the dispersion curve of the surface roll data in the original seismic data and the result of the bilateral filtering to separate and obtain the effective reflection signal of the original seismic data.

[0025] Preferably, the step of acquiring the surface wave data in the original seismic data comprises:

[0026] Slicing the original seismic data to obtain fundamental surface wave data;

[0027] Determining the effective frequency band range of the fundamental surface roll data;

[0028] Reconstructing the wavelength of the frequency-domain surface roll data corresponding to the fundamental-order surface roll data within the effective frequency band to obtain an amplitude field and a phase spectrum of the frequency-domain surface roll data;

[0029] The surface wave data of the original seismic data are determined according to the amplitude field and the phase spectrum.

[0030] Preferably, the pre-generated spatial model is corrected according to the errors between the multiple basis functions and the original seismic data, comprising:

[0031] Determine respective coefficients of the plurality of basis functions in the spatial model according to the spatial model and errors between the plurality of basis functions and the original seismic data;

[0032] The spatial model is modified according to the respective coefficients.

[0033] To achieve the above object, in a second aspect, the present invention relates to a surface wave data processing device, comprising:

[0034] The original seismic data conversion module is used to convert the original seismic data in the target work area into multiple basis functions;

[0035] A space model correction module is used to correct the pre-generated space model according to the multiple basis functions.

[0036] wherein the spatial model is generated by the plurality of basis functions;

[0037] A surface wave data acquisition module, used for acquiring surface wave data in the original seismic data;

[0038] The surface wave data processing module is used to process the surface wave data in the original seismic data according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data, so as to separate and obtain the effective reflection signal of the original seismic data.

[0039] Preferably, the original seismic data conversion module is specifically used for:

[0040] Converting the raw seismic data into a discrete time series;

[0041] In the potential energy-wave function domain of the original seismic data, the discrete time series is decomposed channel by channel to generate multiple basis functions, and the multiple basis functions include one or more of polynomial basis functions, Fourier basis functions, wavelet basis functions, Gaussian basis functions, B-spline basis functions, Laguerre basis functions, Chebyshev basis functions and orthogonal basis functions.

[0042] Preferably, it also includes: a loss function generating unit, used to: generate a loss function according to the multiple basis functions and the discrete time series; wherein the loss function is used to characterize the error between the multiple basis functions and the discrete time series; the loss function is defined as:

[0043]

[0044] in δ is a tuning parameter, y i is the basis function, is the discrete time series;

[0045] The module for acquiring surface wave data is specifically used to: correct the pre-generated spatial model according to the errors between the multiple basis functions and the original seismic data;

[0046] The surface roll data processing module is specifically used to: solve the loss function according to the modified spatial model to determine the amplitude, phase and travel time of the spatial model;

[0047] performing bilateral filtering on the amplitude, the phase and the travel time respectively;

[0048] The surface roll data in the original seismic data is processed according to the dispersion curve of the surface roll data in the original seismic data and the result of the bilateral filtering to separate and obtain the effective reflection signal of the original seismic data.

[0049] To achieve the above-mentioned purpose, in a third aspect, the present invention also relates to 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 a method for processing surface wave data as described in any one of claims 1 to 5.

[0050] To achieve the above-mentioned purpose, in a fourth aspect, the present invention also relates to a computer-readable storage medium, in which instructions are stored, and when the instructions are executed, the above-mentioned method for processing surface roll data is executed.

[0051] The present invention relates to a method, device, equipment and medium for processing surface wave data, which have the following beneficial effects compared with the prior art:

[0052] The present invention can effectively separate effective reflection signals such as reflection waves and refracted waves in original seismic data under complex working conditions. First, the original seismic data in the target work area is converted into multiple basis functions; each basis function has a different frequency width and phase distribution. Then, the pre-generated spatial model is corrected according to the multiple basis functions, wherein the spatial model is generated by multiple basis functions; it can be understood that the spatial model is constructed using several signal segments of a discrete time series, which overcomes the problem of introducing noise in the prior art.

[0053] The surface wave data are processed according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data. It can be understood that the surface wave components are completely restricted to a certain basis function through the above steps, and finally the amplitude, travel time and phase are respectively suppressed. The surface wave in the discrete time series after reconstruction is completely suppressed in terms of amplitude, travel time and phase, thereby effectively separating effective signals such as reflected waves and refracted waves. The method of the present invention performs surface wave suppression of the original seismic data by dividing the basis functions, ensuring that the surface waves are effectively suppressed and the effective signals are well protected. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 The method flow of a surface wave data processing method in the first embodiment of the present invention is as follows Figure 1 ;

[0055] Figure 2 The method flow of a surface wave data processing method in the first embodiment of the present invention is as follows Figure 2 ;

[0056] Figure 3 The method flow of a surface wave data processing method in the first embodiment of the present invention is as follows Figure 3 ;

[0057] Figure 4 The method flow of a surface wave data processing method in the first embodiment of the present invention is as follows Figure 4 ;

[0058] Figure 5 The method flow of a surface wave data processing method in the first embodiment of the present invention is as follows Figure 5 ;

[0059] Figure 6 The method flow of a surface wave data processing method in the first embodiment of the present invention is as follows Figure 6 ;

[0060] Figure 7 The structure of a surface wave data processing device in the second embodiment of the present invention is shown in FIG. Figure 1 ;

[0061] Figure 8The structure of a surface wave data processing device in the second embodiment of the present invention is shown in FIG. Figure 2 . DETAILED DESCRIPTION

[0062] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0063] Embodiment 1

[0064] A method for processing surface wave data, see Figure 1-6 , Figure 1 A schematic flow chart of a surface roll data processing method provided in an embodiment of the present disclosure includes the following steps: S10 to S40.

[0065] S10: Convert the original seismic data in the target work area into multiple basis functions.

[0066] S20: Modifying a pre-generated spatial model according to a plurality of basis functions, wherein the spatial model is generated by a plurality of basis functions.

[0067] S30: Acquire surface wave data from the original seismic data.

[0068] S40: Processing the surface wave data in the original seismic data according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data to separate and obtain effective reflection signals of the original seismic data.

[0069] First, the original seismic data in the target work area are converted into multiple basis functions; then, a pre-generated spatial model is corrected according to the multiple basis functions, wherein the spatial model is generated by the multiple basis functions; finally, the surface wave data is processed according to the corrected spatial model and the dispersion curve of the surface wave data in the original seismic data.

[0070] In summary, the method provided in the embodiment of the present disclosure performs surface roll suppression on the original seismic data by using basis functions, thereby ensuring that the surface roll is effectively suppressed and that the effective signal is well protected.

[0071] Preferably, the basis function includes one or more of a polynomial basis function, a Fourier basis function, a wavelet basis function, a Gaussian basis function, a B-spline basis function, a Laguerre basis function, a Chebyshev basis function and an orthogonal basis function.

[0072] It can be understood that step S20 is an iterative process, that is, iteratively generating basis functions, generating a spatial initial model, and updating the spatial initial model until the error meets the preset requirements. Figure 2As shown, preferably after S10 and before S20, it also includes: S50: generating a loss function according to multiple basis functions and discrete time series; wherein the loss function is used to characterize the error between the multiple basis functions and the discrete time series. Preferably, the loss function is defined as:

[0073]

[0074] in δ is a tuning parameter. This loss function combines the advantages of the minimum square error and the minimum absolute deviation, using square terms for small errors and absolute value terms for large errors. This can reduce the sensitivity to the original seismic data while maintaining sensitivity to small errors.

[0075] For the dispersion curve of the surface wave data in step S40, the present application has the following definition: When a surface wave propagates in an inhomogeneous or layered medium, waves of different frequencies may propagate at different speeds, a phenomenon known as dispersion. The dispersion curve reflects the relationship between the wave velocity (or phase velocity, group velocity) and the frequency.

[0076] For extracting the dispersion curve of surface wave data, the present application provides the following steps: Select a time window containing surface waves, and use the time difference between the arrival time of the direct wave and the arrival time of the surface wave. Obtain the dispersion curve by calculating the group velocity of different frequency components. For multiple station records, the group velocity between stations can be calculated by the cross-correlation function. The frequency-time diagram or cross-correlation function obtained by the above steps can be further used to extract the dispersion curve. Then, use curve fitting or inversion technology to extract the phase velocity and group velocity at different frequencies from the frequency-time diagram.

[0077] Based on the above embodiments, Figure 3 As shown, for step S10, the original seismic data is represented by a set of relatively simple basis functions, specifically including: S11-S12.

[0078] S11: Convert the raw seismic data into discrete time series.

[0079] Specifically, determine the sampling frequency (in Hz) and the time window length (the sampling frequency determines the time resolution of the time series, and the time window length determines the length of the sequence.) According to the sampling frequency and the time window length, calculate the number of sampling points of the discrete time series. For example, if the sampling frequency is 100Hz and the time window length is 10 seconds, the number of sampling points is 1000. Sample the continuous time original seismic data at equal intervals to obtain a discrete time series. The original data can be converted into discrete data points using interpolation methods. Finally, the discrete data points obtained by sampling are saved as a one-dimensional array or vector as a discrete time series. This completes the conversion of seismic trace data to discrete time series.

[0080] S12: In the potential energy-wave function domain of the original seismic data, the discrete time series is decomposed trace by trace to generate multiple basis functions.

[0081] In this embodiment, first, Fourier transform is performed on the discrete time series to obtain frequency domain representation (so that the time domain series can be converted to the frequency domain). Then, potential energy-wave function decomposition is performed on the frequency domain signal. Some commonly used basis functions can be used here, such as Morlet wavelet, Gabor wavelet, etc. By performing potential energy-wave function transformation on the frequency domain signal, a time-frequency domain representation can be obtained. Each time-frequency unit corresponds to a basis function coefficient. By traversing all time-frequency units, a set of basis functions and their corresponding coefficients can be obtained. In this way, the original discrete time series can be decomposed into a linear combination of multiple basis functions. Each basis function represents a different time-frequency characteristic.

[0082] The beneficial effects of step S11 are: the time-frequency characteristics of non-stationary signals can be better characterized, a small number of basis functions can be used to reconstruct and compress signals, and feature extraction can be used to provide an important basis for subsequent signal analysis and processing.

[0083] In addition, the potential energy-wave function domain in step S12 involves the concept of quantum mechanics. In quantum mechanics, the wave function describes the quantum state of a particle, while the potential energy describes the potential field in the environment in which the particle is located. The wave function domain can be understood as the definition domain of the wave function, that is, the range of possible positions or states of the particle.

[0084] In quantum mechanics, the wave function is a complex function whose squared absolute value gives the probability density of a particle at a location and time. Potential energy is a real function that describes the potential field felt by a particle at that location. The Schrödinger equation is one of the equations that describes the evolution of the wave function over time and has the following form:

[0085]

[0086] Where i is the imaginary unit, h is the reduced Planck constant, m is the mass of the particle, is the second-order spatial derivative (the one-dimensional form of the Laplace operator), is a wave function that varies with position x and time t.

[0087] In the steady-state case, the time-independent Schrödinger equation can be written as:

[0088]

[0089] Here E is the energy of the particle.

[0090] Based on the above embodiments, see Figure 3, a method for processing surface wave data, between S10 and S20 also includes: S50: generating a loss function according to multiple basis functions and discrete time series; wherein the loss function is used to characterize the error between the multiple basis functions and the discrete time series.

[0091] In addition, the loss function in S50 is also used to characterize the errors between the multiple basis functions and the original seismic trace data.

[0092] Based on the above embodiments, see Figure 4 , S40 also includes: S41-S43.

[0093] S41: solving the loss function according to the modified spatial model to determine the amplitude, phase and travel time of the spatial model;

[0094] S42: performing bilateral filtering on the amplitude, phase and travel time respectively;

[0095] S43: Processing the surface wave data in the original seismic data according to the dispersion curve of the surface wave data in the original seismic data and the result of bilateral filtering to separate and obtain effective reflection signals of the original seismic data.

[0096] In steps S41-S43, when the value of the loss function is less than the target value, the solution calculation is completed, and the amplitude, travel time and phase are used to suppress the surface roll components respectively. In the reconstructed time series, the surface roll is completely suppressed in terms of amplitude, travel time and phase.

[0097] Based on the above embodiments, see Figure 5 , S30 of a surface wave data processing method also includes: S31-S34.

[0098] S31: segmenting the original seismic data to obtain fundamental surface wave data;

[0099] S32: Determine the effective frequency band range of the fundamental surface wave data;

[0100] First, perform Fourier transform on the fundamental surface roll data to obtain a spectrum. This is to clarify the frequency components contained in the data. Next, calculate the signal-to-noise ratio of the fundamental surface roll data to determine the frequency band range of the effective signal. Generally speaking, the frequency range with a higher signal-to-noise ratio is the effective frequency band of the data. Preferably, the correlation of the fundamental surface roll data in different frequency bands is calculated to further determine the effective frequency band. The frequency range with a higher correlation is the effective frequency band of the data. Based on the theoretical dispersion relationship of the fundamental surface roll and combined with the geological conditions of the study area, the theoretical frequency band of the fundamental surface roll is predicted, and compared and corrected with the above analysis results.

[0101] S33: reconstructing the wavelength of the frequency domain surface roll data corresponding to the fundamental surface roll data within the effective frequency band to obtain the amplitude field and phase spectrum of the frequency domain surface roll data;

[0102] The fundamental surface roll data in the time domain is converted to the frequency domain to obtain the surface roll data in the frequency domain. Within the effective frequency band determined above, the wavelength of the surface roll data in the frequency domain is reconstructed (by restoring the wavelengths of different frequency components, the corresponding frequency domain amplitude field and phase spectrum can be obtained). From the result of the wavelength reconstruction, the amplitude field information of the surface roll data in the frequency domain is extracted (the amplitude field reflects the energy distribution characteristics of different frequency components), and similarly, the phase spectrum information of the surface roll data in the frequency domain is extracted from the result of the wavelength reconstruction (the phase spectrum reflects the phase changes of different frequency components).

[0103] S34: Determine surface wave data of the original seismic data according to the amplitude field and the phase spectrum.

[0104] First, the amplitude field and phase spectrum information of the frequency domain surface wave data are used to reconstruct it back to the time domain through the inverse Fourier transform method to obtain the time domain surface wave data. The surface wave data reconstructed in the time domain are separated from the original seismic data. This can be done by using methods such as filtering and frequency domain separation to extract the surface wave part from the original data. According to the amplitude field information of the frequency domain surface wave data, the amplitude of the time domain surface wave data is corrected to make it more consistent with the amplitude characteristics of the original seismic data. Similarly, according to the phase spectrum information of the frequency domain surface wave data, the phase characteristics of the time domain surface wave data are corrected to reflect the phase characteristics of the surface wave in the original seismic data.

[0105] Based on the above embodiments, see Figure 6 , step S50 comprises:

[0106] S51: determining respective coefficients of a plurality of basis functions in the spatial model according to the spatial model and errors between the plurality of basis functions and the original seismic trace data;

[0107] S52: Modify the spatial model according to the respective coefficients.

[0108] A method for processing surface wave data provided by an embodiment of the present disclosure comprises: first, converting original seismic data in a target work area into a plurality of basis functions; then, correcting a pre-generated spatial model according to the plurality of basis functions, wherein the spatial model is generated by the plurality of basis functions; and finally, processing the surface wave data according to the corrected spatial model and a dispersion curve of the surface wave data in the original seismic data.

[0109] Embodiment 2

[0110] A surface wave data processing device, such as Figure 7As shown, it includes: an original seismic data conversion module 61, a space model correction module 62, a surface wave data acquisition module 63 and a surface wave data processing module 64.

[0111] The original seismic data conversion module 61 is used to convert the original seismic data in the target work area into a plurality of basis functions;

[0112] A space model correction module 62, used to correct a pre-generated space model according to a plurality of basis functions, wherein the space model is generated by the plurality of basis functions;

[0113] A surface wave data acquisition module 63 is used to acquire surface wave data from the original seismic data;

[0114] The surface wave data processing module 64 is used to process the surface wave data in the original seismic data according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data, so as to separate and obtain the effective reflection signal of the original seismic data.

[0115] In some embodiments, the raw seismic data conversion module 61 is specifically used to:

[0116] Convert raw seismic data into discrete time series;

[0117] In the potential energy-wave function domain of the original seismic data, the discrete time series is decomposed trace by trace to generate multiple basis functions.

[0118] In some embodiments, Figure 8 As shown, it also includes: a loss function generating unit 65, which is used to: generate a loss function according to multiple basis functions and discrete time series; wherein the loss function is used to characterize the error between the multiple basis functions and the discrete time series;

[0119] The surface wave data acquisition module 63 is specifically used to: correct the pre-generated spatial model according to the errors between the multiple basis functions and the original seismic data;

[0120] The surface wave data processing module 64 is specifically used for:

[0121] Solving the loss function according to the modified spatial model to determine the amplitude, phase and travel time of the spatial model;

[0122] Perform bilateral filtering on amplitude, phase and travel time respectively;

[0123] The surface wave data in the original seismic data are processed according to the dispersion curve of the surface wave data in the original seismic data and the result of bilateral filtering to separate and obtain the effective reflection signal of the original seismic data.

[0124] The implementation process, method and effect of the surface roll data processing device of this embodiment are the same as those of the surface roll data processing method described in the first embodiment, and will not be described in detail here.

[0125] Embodiment 3

[0126] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the steps of the method described in the above embodiment.

[0127] Embodiment 4

[0128] The present invention relates to a computer-readable storage medium, in which instructions are stored. When the instructions are executed, a method for processing surface roll data of embodiment 1 is executed. The process method and effect of the execution of the method are the same as those of the method for processing surface roll data described in embodiment 1, and will not be repeated here.

[0129] The processor may include, but is not limited to, one or more processors or microprocessors, etc. Each processor may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components to execute the methods in the above embodiments.

[0130] The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, and the computer-readable storage medium may include but is not limited to, for example, 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.).

[0131] The computer-readable storage medium may also store at least one computer executable program / instruction, which may be, for example, a computer-readable instruction. The computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The computer-readable storage medium may include, for example, a read-only memory (ROM), a hard disk, a 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 runs the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0132] In addition, the computer device may also include (but not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (eg, keyboard, mouse, speaker, etc.), etc.

[0133] The processor may communicate with external devices via an I / O bus via a wired or wireless network.

[0134] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0135] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0136] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0137] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for processing surface roll data, characterized in that: include: Converting the original seismic data in the target work area into multiple basis functions; modifying a pre-generated spatial model according to the plurality of basis functions, wherein the spatial model is generated by the plurality of basis functions; Acquiring surface wave data from the original seismic data; The surface wave data in the original seismic data are processed according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data to separate and obtain effective reflection signals of the original seismic data.

2. A surface wave data processing method according to claim 1, characterized in that: The converting of the original seismic data in the target work area into a plurality of basis functions comprises: Converting the raw seismic data into a discrete time series; In the potential energy-wave function domain of the original seismic data, the discrete time series is decomposed channel by channel to generate multiple basis functions, and the multiple basis functions include one or more of polynomial basis functions, Fourier basis functions, wavelet basis functions, Gaussian basis functions, B-spline basis functions, Laguerre basis functions, Chebyshev basis functions and orthogonal basis functions.

3. The method for processing surface wave data according to claim 2, characterized in that: Before the pre-generated spatial model is modified according to the multiple basis functions, and after the original seismic data in the target work area is converted into the multiple basis functions, the method further includes: Generate a loss function according to the multiple basis functions and the discrete time series; wherein the loss function is used to characterize the error between the multiple basis functions and the discrete time series; The loss function is defined as: in δ is a tuning parameter, y i is the basis function, is the discrete time series; The step of modifying the pre-generated spatial model according to the plurality of basis functions comprises: Correcting a pre-generated spatial model based on errors between the plurality of basis functions and the original seismic data; The processing of the surface wave data according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data to separate and obtain the effective reflection signal of the original seismic data includes: Solving the loss function according to the modified spatial model to determine the amplitude, phase and travel time of the spatial model; performing bilateral filtering on the amplitude, the phase and the travel time respectively; The surface roll data in the original seismic data is processed according to the dispersion curve of the surface roll data in the original seismic data and the result of the bilateral filtering to separate and obtain the effective reflection signal of the original seismic data.

4. A method for processing surface wave data according to any one of claims 1 to 3, characterized in that: The step of obtaining surface wave data from the original seismic data comprises: Slicing the original seismic data to obtain fundamental surface wave data; Determining the effective frequency band range of the fundamental surface roll data; Reconstructing the wavelength of the frequency-domain surface roll data corresponding to the fundamental-order surface roll data within the effective frequency band to obtain an amplitude field and a phase spectrum of the frequency-domain surface roll data; The surface wave data of the original seismic data are determined according to the amplitude field and the phase spectrum.

5. The method for processing surface wave data according to claim 2, characterized in that: The method of correcting the pre-generated spatial model according to the errors between the plurality of basis functions and the original seismic data comprises: Determine respective coefficients of the plurality of basis functions in the spatial model according to the spatial model and errors between the plurality of basis functions and the original seismic data; The spatial model is modified according to the respective coefficients.

6. A surface wave data processing device, characterized in that: include: The original seismic data conversion module is used to convert the original seismic data in the target work area into multiple basis functions; A space model correction module is used to correct the pre-generated space model according to the multiple basis functions. wherein the spatial model is generated by the plurality of basis functions; A surface wave data acquisition module, used for acquiring surface wave data in the original seismic data; The surface wave data processing module is used to process the surface wave data in the original seismic data according to the modified spatial model and the dispersion curve of the surface wave data in the original seismic data, so as to separate and obtain the effective reflection signal of the original seismic data.

7. A surface wave data processing device according to claim 6, characterized in that: The original seismic data conversion module is specifically used for: Converting the raw seismic data into a discrete time series; In the potential energy-wave function domain of the original seismic data, the discrete time series is decomposed channel by channel to generate multiple basis functions, and the multiple basis functions include one or more of polynomial basis functions, Fourier basis functions, wavelet basis functions, Gaussian basis functions, B-spline basis functions, Laguerre basis functions, Chebyshev basis functions and orthogonal basis functions.

8. The surface wave data processing device according to claim 6, characterized in that: Also includes: A loss function generating unit is used to generate a loss function according to the multiple basis functions and the discrete time series; wherein the loss function is used to characterize the error between the multiple basis functions and the discrete time series; the loss function is defined as: in δ is a tuning parameter, y i is the basis function, is the discrete time series; The module for acquiring surface wave data is specifically used to: correct the pre-generated spatial model according to the errors between the multiple basis functions and the original seismic data; The surface roll data processing module is specifically used to: solve the loss function according to the modified spatial model to determine the amplitude, phase and travel time of the spatial model; performing bilateral filtering on the amplitude, the phase and the travel time respectively; The surface roll data in the original seismic data is processed according to the dispersion curve of the surface roll data in the original seismic data and the result of the bilateral filtering to separate and obtain the effective reflection signal of the original seismic data.

9. 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 method for processing surface wave data as described in any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that: The storage medium stores instructions, and when the instructions are executed, a method for processing surface wave data according to any one of claims 1 to 5 is executed.

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