A frequency-wave number based high frequency noise suppression method and device

Abstract

The application relates to the technical field of exploration and development, and discloses a high-frequency noise suppression method and device based on frequency-wavenumber, which comprises the following steps: obtaining seismic data of a target area to establish a standard frequency spectrum of the target area, identifying high-frequency noise of the target area, determining a wavenumber range of effective signals in a frequency-wavenumber domain, suppressing the high-frequency noise, obtaining a suppressed frequency spectrum, and obtaining seismic data after high-frequency noise suppression. In this process, whether the seismic data contains high-frequency noise is identified by establishing a standard frequency spectrum, the wavenumber range of effective signals in the frequency-wavenumber domain is determined, the interval range of the effective signals in the high-frequency band is circled, data outside the interval range is suppressed, the high-frequency effective signals are not suppressed in the high-frequency noise suppression process, the risk of effective signal damage is reduced, and the fidelity denoising processing is realized.

Description

Technical Field

[0001] This invention relates to the field of exploration and development technology, and specifically to a method and apparatus for suppressing high-frequency noise based on frequency wavenumber. Background Technology

[0002] High-frequency noise in seismic data generally includes high-frequency ambient noise and high-frequency burst noise. High-frequency ambient noise has a wider frequency band and its energy is relatively concentrated in the higher frequency range, but its total energy is higher than that of the effective seismic wave. High-frequency burst noise has a relatively narrower frequency band, relatively stronger energy, and is relatively concentrated in the high-frequency part, showing obvious temporal continuity in seismic records and exhibiting random distribution both spatially and temporally. High-frequency noise generally originates near the detector, and its dominant frequency shifts to lower frequencies as time increases. Its source and propagation distance differ from the effective wave, and its energy and dominant frequency do not decrease with increasing recording time. High-frequency noise generally exists in a localized area, manifesting temporally in single-channel recordings and spatially in multi-channel recordings. Its dominant frequency range and energy attenuation characteristics differ from those of the effective wave, resulting in a higher high-frequency signal-to-noise ratio (SNR) in shallower seismic records compared to deeper layers. Therefore, methods for suppressing high-frequency noise are primarily studied in different domains, such as the time and frequency domains, to identify or differentiate it from a statistical perspective.

[0003] In related technologies, to suppress high-frequency noise, a time-frequency domain analysis approach is typically used. This involves analyzing the differences in spatial, frequency, and energy distribution characteristics between seismic waves and high-frequency noise in seismic records. Statistical analysis methods are then used to obtain the normal amplitude spectrum of the seismic record. Based on this, anomalous amplitude spectra containing high-frequency noise are identified, and these anomalous amplitude spectra are then suppressed, thus completing the suppression of high-frequency noise. However, in this process, when the amplitude difference between the effective signal and noise at the high-frequency amplitude end is small—that is, when the local effective high-frequency signal amplitude is strong—it is difficult to accurately identify high-frequency noise. Consequently, suppressing noise can easily damage the effective signal at the high-frequency end. Figure 1 As shown, after high-frequency noise suppression in related technologies, the high-frequency noise is significantly removed, but there are still obvious high-frequency effective signals in the noise. Summary of the Invention

[0004] In view of this, the present invention provides a method and apparatus for suppressing high-frequency noise based on frequency wavenumber, in order to solve the technical problem that effective signals are easily damaged during the suppression of high-frequency noise.

[0005] In a first aspect, the present invention provides a high-frequency noise suppression method based on frequency-wavenumber, the method comprising: acquiring seismic data of a target area; establishing a standard spectrum of the target area based on the seismic data; identifying high-frequency noise in the seismic data based on the standard spectrum; determining the wavenumber range of the effective signal in the frequency-wavenumber domain when the seismic data contains high-frequency noise; suppressing the high-frequency noise based on the wavenumber range to obtain a suppressed spectrum; and determining the seismic data after high-frequency noise suppression based on the suppressed spectrum.

[0006] In conjunction with the first aspect, one possible implementation of the first aspect involves establishing a standard spectrum for the target area based on seismic data, including: determining the seismic data spectrum in the time-space domain based on the seismic data; filtering the seismic data based on the seismic data spectrum to determine standard data; and establishing a standard spectrum for the target area based on the standard data.

[0007] In conjunction with the first aspect, in one possible implementation of the first aspect, a standard spectrum of the target area is established based on standard data, including: determining the time window range, number of seismic traces, number of sampling points for each seismic data of the target area within the time window range, and the corresponding spectrum within the time window range through the standard data; and establishing the standard spectrum of the target area by calculating the wavelet amplitude of different frequencies based on the time window range, number of seismic traces, number of sampling points, and spectrum.

[0008] In conjunction with the first aspect, in one possible implementation of the first aspect, the process of establishing the standard spectrum is represented by the following formula:

[0009]

[0010] Where F(ω) represents the standard spectrum, N represents the number of seismic traces involved in the calculation, m represents the number of sampling points for each target area seismic data within the time window, t1 represents the start time of the time window, t2 represents the end time of the time window, and A t (ω) represents the spectrum of time t within the time window, and ω represents the frequency of time t on the seismic trace.

[0011] In conjunction with the first aspect, in one possible implementation of the first aspect, high-frequency noise identification of seismic data is performed based on a standard spectrum, including: determining the dominant frequency parameter of the seismic data based on the seismic data; and considering the seismic data to contain high-frequency noise when the amplitude of the seismic data spectrum is greater than the amplitude of the standard spectrum at the corresponding frequency in an interval where the frequency of the seismic data is greater than the dominant frequency parameter.

[0012] In conjunction with the first aspect, in one possible implementation of the first aspect, when the seismic data contains high-frequency noise, determining the wavenumber range of the effective signal in the frequency-wavenumber domain includes: calculating the frequency-wavenumber spectrum of the seismic data containing high-frequency noise in the frequency-wavenumber domain; determining the frequency protection range and wavenumber protection range of the effective signal in the frequency-wavenumber spectrum based on the characteristics of the effective signal, and using the frequency protection range and wavenumber protection range as the wavenumber range of the effective signal.

[0013] In conjunction with the first aspect, in one possible implementation of the first aspect, the suppressed spectrum is represented by the following formula:

[0014]

[0015] Among them, F′ t (ω) represents the suppression spectrum at time t, F t F(ω) represents the spectrum before high-frequency noise suppression at time t, F(ω) represents the standard spectrum, ω represents the frequency at time t on the seismic trace, s represents the noise suppression smoothing step size, and n represents the number of sampling points within the noise suppression smoothing step size.

[0016] In conjunction with the first aspect, in one possible implementation of the first aspect, high-frequency noise is suppressed based on the wavenumber range to obtain a suppressed spectrum, including: suppressing data outside the wavenumber range to obtain a suppressed spectrum.

[0017] Secondly, the present invention provides a high-frequency noise suppression device based on frequency-wavenumber. The device includes: a data acquisition module for acquiring seismic data of a target area; a standard spectrum establishment module for establishing a standard spectrum of the target area based on the seismic data; an identification module for identifying high-frequency noise in the seismic data based on the standard spectrum; a range determination module for determining the wavenumber range of the effective signal in the frequency-wavenumber domain when the seismic data contains high-frequency noise; a high-frequency noise suppression module for suppressing high-frequency noise based on the wavenumber range to obtain a suppressed spectrum; and a data determination module for determining the seismic data after high-frequency noise suppression based on the suppressed spectrum.

[0018] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the frequency wavenumber-based high-frequency noise suppression method of the first aspect or any corresponding embodiment described above.

[0019] The technical solution of this invention has the following advantages:

[0020] This invention provides a high-frequency noise suppression method and apparatus based on frequency-wavenumber. By acquiring seismic data of a target area and establishing a standard spectrum for that area, high-frequency noise is identified. Then, by determining the wavenumber range of the effective signal in the frequency-wavenumber domain, the high-frequency noise is suppressed to obtain a suppressed spectrum, thus yielding seismic data with suppressed high-frequency noise. In this process, establishing a standard spectrum identifies whether the seismic data contains high-frequency noise. Determining the wavenumber range of the effective signal in the frequency-wavenumber domain delineates the high-frequency range of the effective signal, thereby suppressing data outside this range. This ensures that the effective high-frequency signal is not suppressed during the high-frequency noise suppression process, reducing the risk of damage to the effective signal and achieving fidelity-preserving noise reduction. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 It is based on the high-frequency noise suppression effect diagram in related technologies;

[0023] Figure 2 This is a flowchart illustrating a high-frequency noise suppression method based on frequency wavenumber provided by an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the spectrum of a high-frequency noise suppression method based on frequency wavenumber provided in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the frequency-wavenumber domain of a high-frequency noise suppression method based on frequency-wavenumber provided by an embodiment of the present invention.

[0026] Figure 5 A high-frequency noise suppression effect diagram of a high-frequency noise suppression method based on frequency wavenumber provided by an embodiment of the present invention;

[0027] Figure 6 This is a structural block diagram of a high-frequency noise suppression device based on frequency wavenumber according to an embodiment of the present invention;

[0028] Figure 7 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 embodiments of the present invention, not all embodiments. 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.

[0030] According to an embodiment of the present invention, a method for suppressing high-frequency noise based on frequency wavenumber is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] To ensure that the effective high-frequency signal is not damaged during noise suppression, embodiments of the present invention provide a high-frequency noise suppression method based on frequency wavenumber, such as... Figure 2 As shown, it includes the following steps:

[0032] S101. Obtain seismic data for the target area.

[0033] Specifically, the seismic data for the target area refers to seismic data that includes the number of seismic traces, the time window range, and the data collected by each seismic trace within the time window range.

[0034] S102. Based on seismic data, establish a standard spectrum for the target area.

[0035] Specifically, establishing a standard spectrum for a target area based on seismic data refers to introducing seismic data into the time-space domain, determining the seismic data spectrum in the time-space domain, and then establishing a standard spectrum for the target area by filtering standard data from the seismic data spectrum.

[0036] S103. Based on the standard spectrum, high-frequency noise is identified in seismic data.

[0037] Specifically, high-frequency noise identification of seismic data based on the standard spectrum refers to using the standard spectrum as a spectrum that does not contain high-frequency noise, and then comparing the amplitude of the standard spectrum and the seismic data spectrum in the high-frequency range to identify whether the seismic data contains high-frequency noise.

[0038] S104. When seismic data contains high-frequency noise, determine the wavenumber range of the effective signal in the frequency-wavenumber domain.

[0039] Specifically, when seismic data contains high-frequency noise, determining the wavenumber range of the effective signal in the frequency-wavenumber domain means introducing the seismic data containing high-frequency noise into the frequency-wavenumber domain, determining the frequency-wavenumber spectrum of the seismic data in the frequency-wavenumber domain, and thus utilizing the characteristics of the effective signal to determine the wavenumber range of the effective signal in the frequency-wavenumber domain.

[0040] S105. Based on the wavenumber range, high-frequency noise is suppressed to obtain the suppressed spectrum.

[0041] Specifically, suppressing high-frequency noise based on a wavenumber range to obtain a suppressed spectrum refers to using existing software to suppress data outside a defined wavenumber range, while leaving data within the wavenumber range unsuppressed. This existing software includes software such as GeoEast or others; this invention does not specifically limit its use, as long as it can suppress noise based on a defined wavenumber range. After suppressing high-frequency noise using the wavenumber-based high-frequency noise suppression method provided by this invention, as shown... Figure 5 As shown, the method provided by this invention has a good effect on suppressing high-frequency noise, and at the same time, the noise does not contain effective signals, thus achieving true fidelity noise reduction processing.

[0042] S106. Based on the suppressed spectrum, determine the seismic data after high-frequency noise suppression.

[0043] Specifically, determining the seismic data after high-frequency noise suppression based on the suppressed spectrum means reconstructing the suppressed spectral data into suppressed seismic data through inverse Fourier transform after determining the suppressed spectrum.

[0044] This invention provides a high-frequency noise suppression method based on frequency-wavenumber. This method acquires seismic data of a target area, establishes a standard spectrum for the target area to identify high-frequency noise, and suppresses the high-frequency noise by determining the wavenumber range of the effective signal in the frequency-wavenumber domain, obtaining a suppressed spectrum, thus yielding seismic data with suppressed high-frequency noise. In this process, establishing a standard spectrum identifies whether the seismic data contains high-frequency noise, and determining the wavenumber range of the effective signal in the frequency-wavenumber domain delineates the high-frequency range of the effective signal. Data outside this range is then suppressed, ensuring that the effective high-frequency signal is not suppressed during the high-frequency noise suppression process, reducing the risk of damage to the effective signal, and thus achieving fidelity-preserving noise reduction.

[0045] To reduce the impact of high-frequency noise on the standard spectrum establishment process, in one optional implementation, a standard spectrum for the target area is established based on seismic data, including:

[0046] Based on seismic data, the seismic data spectrum is determined in the time-space domain.

[0047] Specifically, determining the seismic data spectrum in the time-space domain, based on seismic data, refers to introducing seismic data into time and space windows to determine the seismic data spectrum in the time-space domain. The format is as follows: Figure 3 The spectrum of the data containing high-frequency noise is shown, where the horizontal axis represents frequency and the vertical axis represents amplitude.

[0048] Based on the seismic data spectrum, seismic data are filtered to determine standard data.

[0049] Specifically, based on the seismic data spectrum, the seismic data is screened to determine standard data, which refers to selecting data that does not contain significant high-frequency noise as standard data. For example... Figure 3 As shown, the amplitude of the spectrum containing high-frequency noise is significantly higher than that of the spectrum without high-frequency noise in the range above the dominant frequency. This is particularly evident in the range from the dominant frequency to 100Hz. Therefore, the data corresponding to the spectrum with this characteristic contains significant high-frequency noise, and the data without subclass characteristics should be selected as the standard data.

[0050] Based on standard data, a standard spectrum for the target region is established.

[0051] In one alternative implementation, a standard spectrum of the target region is established based on standard data, including:

[0052] Using standard data, determine the time window range, number of seismic traces, number of sampling points for each target area seismic data within the time window range, and the corresponding spectrum within the time window range.

[0053] Specifically, as part of the seismic data, the labeled data can be directly determined when the seismic data includes the number of seismic traces, the time window range, and the number of sampling points for each seismic trace within the time window range.

[0054] Specifically, the spectrum within the corresponding time window is determined by Fourier transform.

[0055] Based on the time window range, number of seismic traces, number of sampling points, and spectrum, a standard spectrum for the target area is established by calculating the amplitude of wavelet waves at different frequencies.

[0056] Specifically, the standard spectrum is represented as follows: Figure 3The standard spectrum is shown in the figure. The standard spectrum is determined by multiple wavelets. The amplitude of each wavelet is determined by importing the time window range, the number of seismic traces, the number of sampling points, and the spectrum, thus forming the standard spectrum of the target area.

[0057] In one alternative implementation, the process of establishing the standard spectrum is represented by formula (1):

[0058]

[0059] Where F(ω) represents the standard spectrum, N represents the number of seismic traces involved in the calculation, m represents the number of sampling points for each target area seismic data within the time window, t1 represents the start time of the time window, t2 represents the end time of the time window, and A t (ω) represents the spectrum of time t within the time window, and ω represents the frequency of time t on the seismic trace.

[0060] By implementing this embodiment, seismic data is introduced into the time-space domain. The seismic data is then filtered based on the spectral characteristics of data containing high-frequency noise in the time-space domain to determine standard data, i.e., seismic data that does not contain high-frequency noise. Standard spectra for the target area are then established using the standard data. This allows for more accurate filtering of seismic data that accurately reflects the target area and does not contain high-frequency noise, reducing the impact of high-frequency noise on the standard spectrum establishment process. This provides a data foundation for subsequent high-frequency noise identification in the target area and reduces the risk of damage to effective signals, thus achieving fidelity-preserving denoising processing.

[0061] To accurately identify high-frequency noise, in one optional implementation, high-frequency noise identification of seismic data is performed based on a standard spectrum, including:

[0062] Based on seismic data, determine the dominant frequency parameters of the seismic data.

[0063] Specifically, based on seismic data, the dominant frequency parameter of seismic data refers to the frequency corresponding to the highest point of the seismic data spectrum amplitude.

[0064] If the amplitude of the seismic data spectrum is greater than the amplitude of the standard spectrum at the corresponding frequency in the interval where the frequency of the seismic data is greater than the dominant frequency parameter, the seismic data is considered to contain high-frequency noise.

[0065] Specifically, since the present invention provides suppression of high-frequency noise, the identification of high-frequency noise needs to be performed in the range where the frequency of the seismic data is greater than the dominant frequency parameter.

[0066] Specifically, since the standard data is selected based on the absence of high-frequency noise, the amplitude of the standard spectrum in the corresponding interval is the amplitude of the spectrum without high-frequency noise. Therefore, if the amplitude of the seismic data spectrum is higher than the amplitude of the standard spectrum at the same frequency in the interval where the frequency of the seismic data is greater than the dominant frequency parameter, the seismic data is considered to contain high-frequency noise.

[0067] By implementing this embodiment, by comparing the amplitude of the seismic data spectrum at frequencies higher than the dominant frequency with the amplitude of the standard spectrum in the corresponding interval, high-frequency noise in the target area can be identified, providing a data foundation for reducing the risk of damage to the effective signal and achieving fidelity denoising processing.

[0068] To avoid damage to the effective signal during noise suppression, in one optional implementation, when the seismic data contains high-frequency noise, the wavenumber range of the effective signal in the frequency-wavenumber domain is determined, including:

[0069] Calculate the frequency-wavenumber spectrum of seismic data containing high-frequency noise in the frequency-wavenumber domain.

[0070] Specifically, calculating the frequency-wavenumber spectrum of seismic data containing high-frequency noise in the frequency-wavenumber domain refers to introducing seismic data identified as containing high-frequency noise into the frequency-wavenumber (FK) domain and calculating the FK (frequency-wavenumber) spectrum of the high-frequency components. For example... Figure 4 As shown, an exemplary FK spectrum of seismic data containing high-frequency noise is presented in the frequency-wavenumber domain, where the horizontal axis represents the wave number and the vertical axis represents the frequency.

[0071] Based on the characteristics of the effective signal, the frequency protection range and wavenumber protection range of the effective signal in the frequency-wavenumber spectrum are determined, and the frequency protection range and wavenumber protection range are taken as the wavenumber range of the effective signal.

[0072] Specifically, the characteristics of an effective signal refer to the fact that in the FK spectrum, the effective signal is regularly distributed near the 0 wavenumber, exhibiting as a strong energy cluster.

[0073] Specifically, based on the characteristics of the effective signal, determining the frequency protection range and wavenumber protection range of the effective signal in the frequency-wavenumber spectrum refers to determining the effective range of frequency and the effective range of wavenumber in the frequency-wavenumber domain. The lower frequency boundary value of the effective signal in the frequency-wavenumber domain is denoted as ω0, because the data introduced into the FK domain is seismic data containing high-frequency noise, and all seismic data containing high-frequency noise is data with frequencies greater than the dominant frequency. The upper frequency boundary value of the effective signal in the frequency-wavenumber domain is the highest frequency parameter of the energy cluster in the vertical direction, i.e., the highest frequency parameter of the effective signal that needs protection, denoted as ω1. The maximum wavenumber of the effective signal is denoted as k0, and the wavenumber of the data before high-frequency noise suppression is denoted as k. Specifically, the adjustment for suppressing high-frequency noise can be expressed by formula (3):

[0074] (ω>ω1)V[(ω0<ω<ω1)∧(|k|>|k0|)], and F t (ω)>F(ω) (3)

[0075] In one alternative implementation, determining the frequency protection range and wavenumber protection range of the effective signal in the frequency-wavenumber spectrum based on the characteristics of the effective signal includes: determining the boundary values ​​of the energy cluster in the frequency-wavenumber spectrum.

[0076] Specifically, the effective signal protection range can be slightly larger than the energy cluster boundary range. For example, it can be read by the scale adjacent to each boundary value in the frequency-wavenumber spectrum or by the closest value. For example, if the upper boundary of the energy cluster frequency is between 50 and 60, 60 or 57 can be taken as the corresponding value of the upper boundary of the energy cluster frequency. If the right boundary of the energy cluster wavenumber is between 0.004 and 0.008, 0.008 or 0.007 can be taken as the corresponding value of the right boundary of the energy cluster frequency-wavenumber. This embodiment does not make specific limitations on this, and the effective signal protection range can be slightly larger than the energy cluster boundary range.

[0077] Specifically, the frequency range for high-frequency noise suppression is expressed as: ω0<ω<Niquist frequency, where Niquist frequency represents the frequency threshold related to the sampling frequency, such as 250 samples in 2 milliseconds.

[0078] In one alternative implementation, the suppression spectrum is represented by formula (2):

[0079]

[0080] Among them, F′ t (ω) represents the suppression spectrum at time t, F tF(ω) represents the spectrum before high-frequency noise suppression at time t, F(ω) represents the standard spectrum, ω represents the frequency at time t on the seismic trace, s represents the noise suppression smoothing step size, and n represents the number of sampling points within the noise suppression smoothing step size.

[0081] Specifically, the number of noise suppression smoothing steps can be set according to the actual working conditions. Usually, the number of seismic traces involved in smoothing is selected, thereby improving data stability by introducing noise suppression smoothing steps.

[0082] By implementing this embodiment, seismic data containing high-frequency noise is introduced into the frequency-wavenumber domain, and the frequency-wavenumber spectrum of the corresponding data is determined. This gives the effective signal its performance characteristics in the frequency-wavenumber domain, determines the protection range of the effective signal, and thus avoids damage to the effective signal during noise suppression. That is, the high-frequency effective signal is not suppressed during high-frequency noise suppression, reducing the risk of damage to the effective signal, thereby achieving fidelity-preserving noise reduction processing.

[0083] This embodiment also provides a high-frequency noise suppression device based on frequency wavenumber, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0084] This embodiment provides a high-frequency noise suppression device based on frequency wavenumber, such as... Figure 6 As shown, it includes:

[0085] The data acquisition module 201 is used to acquire seismic data of the target area. For details, please refer to the description of step S101 in the above embodiments, which will not be repeated here.

[0086] The standard spectrum establishment module 202 is used to establish a standard spectrum for the target area based on seismic data. For details, please refer to the description of step S102 in the above embodiments, which will not be repeated here.

[0087] The identification module 203 is used to identify high-frequency noise in seismic data based on a standard spectrum. For details, please refer to the description of step S103 in the above embodiments, which will not be repeated here.

[0088] The range determination module 204 is used to determine the wavenumber range of the effective signal in the frequency-wavenumber domain when the seismic data contains high-frequency noise. For details, please refer to the description of step S104 in the above embodiments, which will not be repeated here.

[0089] The high-frequency noise suppression module 205 is used to suppress high-frequency noise based on a wavenumber range to obtain a suppressed spectrum. For details, please refer to the description of step S105 in the above embodiments, which will not be repeated here.

[0090] The data determination module 206 is used to determine the seismic data after high-frequency noise suppression based on the suppression spectrum. For details, please refer to the description of step S106 in the above embodiments, which will not be repeated here.

[0091] In this embodiment, the high-frequency noise suppression device based on frequency wavenumber is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0092] This invention also provides a computer device having the above-described features. Figure 6 The diagram shows a high-frequency noise suppression device based on frequency wavenumber. Please refer to [link / reference]. Figure 7 , Figure 7 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 7 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 7 Take a processor 10 as an example.

[0093] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0094] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0095] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0096] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include combinations of the above types of memory. The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0097] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A high-frequency noise suppression method based on frequency wavenumber, characterized in that, The method includes: Acquire seismic data for the target area; Based on the earthquake data, a standard spectrum for the target area is established; Based on the standard spectrum, high-frequency noise is identified in the seismic data; When the seismic data contains high-frequency noise, determine the wavenumber range of the effective signal in the frequency-wavenumber domain; Based on the wavenumber range, high-frequency noise is suppressed to obtain the suppressed spectrum; Based on the suppressed spectrum, the seismic data after high-frequency noise suppression is determined; When the seismic data contains high-frequency noise, determining the wavenumber range of the effective signal in the frequency-wavenumber domain includes: Calculate the frequency-wavenumber spectrum of the seismic data, including high-frequency noise, in the frequency-wavenumber domain; Based on the characteristics of the effective signal, the frequency protection range and the wavenumber protection range of the effective signal in the frequency-wavenumber spectrum are determined, and the frequency protection range and the wavenumber protection range are taken as the wavenumber range of the effective signal. The process of establishing a standard spectrum for the target area based on the seismic data includes: Based on the earthquake data, the earthquake data spectrum is determined in the time-space domain; Based on the seismic data spectrum, the seismic data is filtered to determine standard data; Based on the aforementioned standard data, a standard spectrum for the target region is established; The step of establishing a standard spectrum for the target region based on the standard data includes: Using the standard data, determine the time window range, number of seismic traces, number of sampling points for each target area seismic data within the time window range, and the corresponding spectrum within the time window range; Based on the time window range, the number of seismic traces, the number of sampling points, and the spectrum, a standard spectrum for the target area is established by calculating the amplitude of wavelets at different frequencies.

2. The method according to claim 1, characterized in that, The process of establishing a standard spectrum can be represented by the following formula: in, Represents the standard spectrum. N This indicates the number of seismic traces involved in the calculation. m This indicates the number of sampling points for each target area seismic data point within the time window. t 1 indicates the start time of the time window range. t 2 indicates the end time of the time window range. Indicates time within the time window range t The spectrum, The frequency of time t in the seismic trace.

3. The method according to claim 1, characterized in that, The process of identifying high-frequency noise in the seismic data based on the standard spectrum includes: Based on the earthquake data, determine the dominant frequency parameters of the earthquake data; If the amplitude of the seismic data spectrum is greater than the amplitude of the standard spectrum at the corresponding frequency in the range where the frequency of the seismic data is greater than the dominant frequency parameter, the seismic data is considered to contain high-frequency noise.

4. The method according to claim 1, characterized in that, The suppression spectrum is expressed by the following formula: in, This represents the suppression spectrum at time t. This represents the spectrum before high-frequency noise suppression at time t. Represents the standard spectrum. represents the frequency of time t on the seismic trace, s represents the noise suppression smoothing step size, and n represents the number of sampling points within the noise suppression smoothing step size.

5. The method according to claim 1, characterized in that, The step of suppressing high-frequency noise based on the wavenumber range to obtain a suppressed spectrum includes: suppressing data outside the wavenumber range to obtain a suppressed spectrum.

6. A high-frequency noise suppression device based on frequency wavenumber, characterized in that, The device includes: The data acquisition module is used to acquire seismic data for the target area; A standard spectrum establishment module is used to establish a standard spectrum of the target area based on the seismic data. Establishing the standard spectrum of the target area based on the seismic data includes: determining the seismic data spectrum in the time-space domain based on the seismic data; filtering the seismic data based on the seismic data spectrum to determine standard data; and establishing the standard spectrum of the target area based on the standard data. Establishing the standard spectrum of the target area based on the standard data also includes: determining the time window range, number of seismic traces, number of sampling points for each seismic data trace in the target area within the time window range, and the corresponding spectrum within the time window range using the standard data; and establishing the standard spectrum of the target area by calculating the wavelet amplitudes of different frequencies based on the time window range, the number of seismic traces, the number of sampling points, and the spectrum. The identification module is used to identify high-frequency noise in the seismic data based on the standard spectrum. A range determination module is used to determine the wavenumber range of the effective signal in the frequency-wavenumber domain when the seismic data contains high-frequency noise. The determination of the wavenumber range of the effective signal in the frequency-wavenumber domain when the seismic data contains high-frequency noise includes: calculating the frequency-wavenumber spectrum of the seismic data containing high-frequency noise in the frequency-wavenumber domain; determining the frequency protection range and the wavenumber protection range of the effective signal in the frequency-wavenumber spectrum based on the characteristics of the effective signal, and using the frequency protection range and the wavenumber protection range as the wavenumber range of the effective signal. A high-frequency noise suppression module is used to suppress high-frequency noise based on the wavenumber range to obtain a suppressed spectrum; The data determination module is used to determine the seismic data after high-frequency noise suppression is completed based on the suppression spectrum.

7. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform high-frequency noise suppression based on frequency wavenumber as described in any one of claims 1 to 5.

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