High-frequency noise suppression method and device based on frequency wavenumber

Abstract

The invention relates to the technical field of exploration and development, and discloses a high-frequency noise suppression method and device based on frequency wavenumber, and the method comprises the steps: obtaining the seismic data of a target region, and completing the recognition of the high-frequency noise of the target region in a mode of building a standard frequency spectrum of the target region; and by determining the wavenumber range of the effective signal in the frequency-wavenumber domain, suppressing the high-frequency noise to obtain a suppressed frequency spectrum, thereby obtaining the seismic data after high-frequency noise suppression. In the process, whether the seismic data contains high-frequency noise or not is identified in a mode of establishing a standard frequency spectrum, and the interval range of the effective signal in a high frequency band is delineated by determining the wave number range of the effective signal in a frequency-wave number domain, so that data outside the interval range is suppressed, and the seismic data are suppressed. Therefore, high-frequency effective signals are not suppressed in the high-frequency noise suppression process, the risk of effective signal damage is reduced, and fidelity denoising processing is realized.

Description

Technical Field

[0001] The present invention relates to the field of exploration and development technology, and in particular to a method and device for suppressing high-frequency noise based on frequency wave number. Background Art

[0002] High-frequency noise on seismic data generally mainly includes high-frequency environmental noise and high-frequency burst noise; high-frequency environmental noise has a wide frequency band and its energy is relatively concentrated in the higher frequency band, but its total energy is higher than that of the effective seismic wave; high-frequency burst noise has a relatively narrow frequency band, relatively strong energy, and is relatively concentrated in the high-frequency part. It has obvious time continuity in seismic records and is randomly distributed in space and time. High-frequency noise generally comes from the vicinity of the detector. As time increases, the main frequency moves toward the low-frequency direction. Its generation source and propagation distance are different from those of the effective wave, and its energy and main frequency do not decrease with the increase of recording time. High-frequency noise generally exists in a local range, which is manifested in the time direction on a single channel and in the space direction on multiple channels. Its main frequency range and energy attenuation characteristics are different from those of the effective wave. This difference makes the high-frequency signal-to-noise ratio on seismic records appear to be higher in shallow layers than in deep layers. Therefore, the methods for suppressing high-frequency noise are basically studied in different domains such as the time domain and the frequency domain, and are identified or distinguished from a statistical perspective.

[0003] In related technologies, in order to suppress high-frequency noise, it is usually done from the perspective of time-frequency domain analysis. By analyzing the differences in spatial distribution characteristics, frequency distribution characteristics, and energy distribution characteristics between seismic waves and high-frequency noise on seismic records, statistical analysis methods are used to obtain the normal amplitude spectrum of seismic records, and then the abnormal amplitude spectrum containing high-frequency noise is identified based on this. The abnormal amplitude spectrum is then suppressed to complete the suppression of high-frequency noise. In this process, when the amplitude difference between the effective signal and the noise at the high-frequency amplitude end is small, that is, when the amplitude of the local high-frequency effective signal is strong, the high-frequency noise cannot be accurately identified, so that the effective signal at the high-frequency end is easily damaged when suppressing the noise, such as Figure 1 As shown, after high-frequency noise suppression is performed in the related art, the high-frequency noise is significantly removed, but there is an obvious high-frequency effective signal in the noise. Summary of the invention

[0004] In view of this, the present invention provides a method and device for suppressing high-frequency noise based on frequency wave number, so as to solve the technical problem that effective signals are easily damaged in the process of suppressing high-frequency noise.

[0005] In a first aspect, the present invention provides a method for suppressing high-frequency noise 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; when the seismic data contains high-frequency noise, determining the wavenumber range of an effective signal in the frequency-wavenumber domain; based on the wavenumber range, suppressing the high-frequency noise to obtain a suppressed spectrum; and determining the seismic data after the high-frequency noise suppression is completed based on the suppressed spectrum.

[0006] In combination with the first aspect, in a possible implementation of the first aspect, a standard spectrum of the target area is established based on the seismic data, including: determining the seismic data spectrum in the time-space domain based on the seismic data; screening the seismic data based on the seismic data spectrum to determine standard data; and establishing a standard spectrum of the target area based on the standard data.

[0007] In combination with the first aspect, in a possible implementation of the first aspect, a standard spectrum of the target area is established based on standard data, including: determining, through the standard data, the time window range, the number of seismic channels, the number of sampling points of each target area seismic data within the time window range, and the corresponding spectrum within the time window range corresponding to the standard data; based on the time window range, the number of seismic channels, the number of sampling points and the spectrum, the standard spectrum of the target area is established by calculating the sub-wave amplitudes of different frequencies.

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

[0009]

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

[0011] In combination with the first aspect, in a possible implementation of the first aspect, high-frequency noise is identified on seismic data based on a standard spectrum, including: determining a main frequency parameter of the seismic data based on the seismic data; when, in an interval where the frequency of the seismic data is greater than the main frequency parameter, the amplitude of the seismic data spectrum is greater than the amplitude of the standard spectrum at the corresponding frequency, the seismic data is considered to contain high-frequency noise.

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

[0013] In combination with the first aspect, in a possible implementation manner of the first aspect, the suppressed spectrum is expressed by the following formula:

[0014]

[0015] Among them, F′ t (ω) represents the suppressed spectrum at time t, F t (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 smoothing step length of suppressed noise, and n represents the number of sampling points within the smoothing step length of suppressed noise.

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

[0017] In a second aspect, the present invention provides a high-frequency noise suppression device based on frequency wavenumber, the device comprising: a data acquisition module for acquiring seismic data of a target area; a standard spectrum establishment module for establishing a standard spectrum of a target area based on the seismic data; an identification module for identifying high-frequency noise in seismic data based on the standard spectrum; a range determination module for determining the wavenumber range of an effective signal in a 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] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the high-frequency noise suppression method based on frequency wave number of the above-mentioned first aspect or any corresponding embodiment thereof by executing the computer instructions.

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

[0020] The present invention provides a method and device for suppressing high-frequency noise based on frequency wavenumber, which completes the identification of high-frequency noise in the target area by acquiring seismic data of the target area and establishing a standard spectrum of the target area, and suppresses the high-frequency noise by determining the wavenumber range of the effective signal in the frequency-wavenumber domain to obtain a suppressed spectrum, thereby obtaining seismic data after the high-frequency noise is suppressed. In this process, by establishing a standard spectrum, it is identified whether the seismic data contains high-frequency noise, and by determining the wavenumber range of the effective signal in the frequency-wavenumber domain, the interval range of the effective signal in the high frequency band is circled, thereby suppressing the data outside the interval range, so that the high-frequency effective signal is not suppressed during the high-frequency noise suppression process, reducing the risk of effective signal damage, thereby achieving fidelity denoising processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

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

[0023] Figure 2 It is a flow chart of a high-frequency noise suppression method based on frequency wave number provided according to an embodiment of the present invention;

[0024] Figure 3 is a spectrum schematic diagram of a high-frequency noise suppression method based on frequency wave number provided according to an embodiment of the present invention;

[0025] Figure 4 is a schematic diagram of a spectrum in the frequency-wavenumber domain of a high-frequency noise suppression method based on frequency wavenumber provided in 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 wave number provided according to an embodiment of the present invention;

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

[0028] Figure 7 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

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

[0031] In order to ensure that the high-frequency effective signal is not damaged during the noise suppression process, the embodiment of the present invention provides a high-frequency noise suppression method based on frequency wave number, such as Figure 2 As shown, the following steps are included:

[0032] S101. Acquire seismic data of a target area.

[0033] Specifically, the seismic data of the target area refers to seismic data including seismic trace numbers, time window range, and sampling point data of each seismic trace number within the time window range.

[0034] S102: Establish a standard frequency spectrum of the target area based on the seismic data.

[0035] Specifically, establishing a standard spectrum for a target area based on seismic data means introducing the seismic data into the time-space domain, determining the seismic data spectrum of the seismic data in the time-space domain, and thereby establishing a standard spectrum for the target area by screening standard data in the seismic data spectrum.

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

[0037] Specifically, high-frequency noise identification of seismic data based on the standard spectrum refers to taking the standard spectrum as a spectrum that does not contain high-frequency noise, thereby identifying whether the seismic data contains high-frequency noise by comparing the amplitude of the standard spectrum with the seismic data spectrum in the high-frequency range.

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

[0039] Specifically, when the 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 thereby utilizing the characteristics of the effective signal to determine the wavenumber range of the effective signal in the frequency-wavenumber domain.

[0040] S105. Suppress high-frequency noise based on the wave number range to obtain a suppressed spectrum.

[0041] Specifically, based on the wavenumber range, high-frequency noise is suppressed to obtain a suppressed spectrum, which means that data outside the wavenumber range is suppressed based on a certain wavenumber range by existing software to obtain a suppressed spectrum, and data within the wavenumber range is not suppressed. Among them, the existing software includes such as GeoEast software or other software, and the present invention does not make specific limitations on this, as long as the noise of the data can be suppressed based on a certain wavenumber range. After the high-frequency noise is suppressed by the high-frequency noise suppression method based on frequency wavenumber provided by the present invention, Figure 5 As shown, it can be seen that the method provided by the present invention has a better effect on suppressing high-frequency noise, and at the same time, the noise does not contain effective signals, thereby achieving true fidelity denoising processing.

[0042] S106. Determine the seismic data after high-frequency noise suppression based on the suppressed spectrum.

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

[0044] The embodiment of the present invention provides a method for suppressing high-frequency noise based on frequency wavenumber. The method obtains seismic data of the target area and establishes a standard spectrum of the target area to complete the identification of high-frequency noise in the target area, and suppresses the high-frequency noise by determining the wavenumber range of the effective signal in the frequency-wavenumber domain to obtain a suppressed spectrum, thereby obtaining seismic data after the high-frequency noise is suppressed. In this process, by establishing a standard spectrum, it is identified whether the seismic data contains high-frequency noise, and by determining the wavenumber range of the effective signal in the frequency-wavenumber domain, the interval range of the effective signal in the high frequency band is circled, thereby suppressing the data outside the interval range, so that the high-frequency effective signal is not suppressed during the high-frequency noise suppression process, reducing the risk of effective signal damage, thereby achieving fidelity denoising processing.

[0045] In order to reduce the influence of high-frequency noise on the process of establishing a standard spectrum, in an optional implementation, a standard spectrum of a target area is established based on seismic data, including:

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

[0047] Specifically, based on seismic data, in the time-space domain, determining the seismic data spectrum means introducing the seismic data into the time window and space window, and determining the seismic data spectrum in the time-space domain, which is expressed as Figure 3 The spectrum of the high-frequency noise data is shown in FIG. 1 , where the horizontal axis is frequency and the vertical axis is amplitude.

[0048] Based on the seismic data spectrum, the seismic data is screened to determine the standard data.

[0049] Specifically, based on the seismic data spectrum, seismic data is screened, and determining standard data means selecting data that does not contain obvious high-frequency noise as standard data. Figure 3 As shown, it can be seen that the amplitude of the spectrum containing high-frequency noise data is significantly higher than that of the spectrum not containing high-frequency noise in the interval greater than the main frequency, among which the performance is obvious in the interval from the main frequency to 100Hz. Therefore, the data corresponding to the spectrum with such characteristics is data containing obvious high-frequency noise, and data that does not contain sub-class features should be selected as standard data.

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

[0051] In an optional implementation, a standard spectrum of the target area is established based on the standard data, including:

[0052] The time window range, the number of seismic channels, the number of sampling points of each target area seismic data within the time window range and the corresponding frequency spectrum within the time window range are determined through the standard data.

[0053] Specifically, the annotated data is part of the seismic data. When the seismic data contains the number of seismic channels, the time window range, and the sampling points of each seismic channel within the time window range, the time window range, the number of seismic channels, and the number of sampling points of each target area seismic data within the time window range corresponding to the standard data can be directly determined.

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

[0055] Based on the time window range, number of seismic channels, number of sampling points and spectrum, the standard spectrum of the target area is established by calculating the wavelet amplitudes of different frequencies.

[0056] Specifically, the standard spectrum is expressed as Figure 3As shown in the standard spectrum, the standard spectrum is determined by multiple sub-waves, and the amplitude of each sub-wave is determined by importing the time window range, the number of seismic channels, the number of sampling points and the spectrum to form the standard spectrum of the target area.

[0057] In an optional 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 channels involved in the calculation, m represents the number of sampling points of each target area seismic data within the time window range, t1 represents the starting time of the time window range, t2 represents the ending time of the time window range, and A t (ω) represents the frequency spectrum at time t within the time window, and ω represents the frequency at time t on the seismic trace.

[0060] By implementing this embodiment, by introducing seismic data into the time-space domain, the seismic data is screened through the performance characteristics of the spectrum of data containing high-frequency noise in the time-space domain, and standard data, that is, seismic data that does not contain high-frequency noise, is determined. Through the standard data, a standard spectrum of the target area is established, so that more accurate screening can accurately reflect the data that does not contain high-frequency noise in the seismic data of the target area, reduce the impact of high-frequency noise on the standard spectrum establishment process, and provide a data basis for subsequent high-frequency noise identification in the target area, as well as reduce the risk of effective signal damage, to achieve fidelity denoising processing.

[0061] In order to accurately identify high-frequency noise, in an optional implementation, high-frequency noise is identified on seismic data based on a standard spectrum, including:

[0062] Based on the seismic data, the main frequency parameters of the seismic data are determined.

[0063] Specifically, based on the seismic data, determining the main frequency parameter of the seismic data means that the frequency corresponding to the highest point of the spectrum amplitude of the seismic data is the main frequency parameter of the seismic data.

[0064] When 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 main frequency parameter, the seismic data is considered to contain high-frequency noise.

[0065] Specifically, since the present invention provides suppression for high-frequency noise, the identification of high-frequency noise needs to be judged in an interval where the frequency of the seismic data is greater than the main frequency parameter.

[0066] Specifically, since the standard data is selected on the basis of not containing high-frequency noise, the amplitude of the standard spectrum in the corresponding interval is the amplitude of the spectrum that does not contain high-frequency noise. Therefore, when 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 main 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 when it is higher than the main frequency with the amplitude of the standard spectrum in the corresponding interval, the high-frequency noise in the target area can be identified, which reduces the risk of effective signal damage in the future and provides a data basis for achieving fidelity denoising processing.

[0068] In order to avoid the effective signal from being damaged during the noise suppression process, in an optional implementation, when the seismic data contains high-frequency noise, determining the wavenumber range of the effective signal in the frequency-wavenumber domain includes:

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

[0070] Specifically, calculating the frequency-wavenumber spectrum of seismic data containing high-frequency noise in the frequency-wavenumber domain refers to introducing the 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 component. Figure 4 , which exemplarily shows the FK spectrum of seismic data containing high-frequency noise in the frequency-wavenumber domain, wherein the abscissa is the wave number and the ordinate is the frequency.

[0071] Based on the characteristics of the effective signal, a frequency protection range and a wave number protection range of the effective signal in the frequency-wave number spectrum are determined, and the frequency protection range and the wave number protection range are used as the wave number range of the effective signal.

[0072] Specifically, the characteristic of the effective signal means that in the FK spectrum, the effective signal is regularly distributed around the 0 wave number, showing as a strong energy cluster.

[0073] Specifically, based on the characteristics of the effective signal, determining the frequency protection range and wave number protection range of the effective signal in the frequency-wave number spectrum refers to determining the effective range of the frequency and the effective range of the wave number of the effective signal in the frequency-wave number domain, wherein the frequency lower boundary value of the effective signal in the frequency-wave number domain is the main frequency parameter of the seismic data, denoted as ω0, because the data introduced into the FK domain is seismic data containing high-frequency noise, and the seismic data containing high-frequency noise are all data greater than the main frequency. Therefore, the frequency lower boundary value of the effective signal in the frequency-wave number domain is the main frequency parameter of the seismic data, denoted as ω0, and the frequency upper boundary value of the effective signal in the frequency-wave number domain is the highest frequency parameter of the energy group in the ordinate direction, that is, the highest frequency parameter of the effective signal that needs to be protected, denoted as ω1, the maximum wave number of the effective signal is denoted as k0, and the wave number of the data before the high-frequency noise is suppressed 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 an optional implementation, 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, including: determining the boundary value of the energy group in the frequency-wavenumber spectrum.

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

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

[0078] In an optional implementation, the suppressed spectrum is expressed by formula (2):

[0079]

[0080] Among them, F′ t (ω) represents the suppressed spectrum at time t, F t(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 smoothing step length of suppressed noise, and n represents the number of sampling points within the smoothing step length of suppressed noise.

[0081] Specifically, the specific number of noise suppression smoothing steps can be set according to actual working conditions. Usually, the number of seismic channels involved in smoothing is selected, so as to improve 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, thereby giving the effective signal performance characteristics in the frequency-wavenumber domain and determining the protection range of the effective signal, thereby avoiding damage to the effective signal during the noise suppression process, that is, the high-frequency effective signal is not suppressed during the high-frequency noise suppression process, reducing the risk of effective signal damage, thereby achieving fidelity denoising processing.

[0083] In this embodiment, a high-frequency noise suppression device based on frequency wave number is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware is also possible and conceived.

[0084] This embodiment provides a high-frequency noise suppression device based on frequency wave number, such as Figure 6 As shown, including:

[0085] The data acquisition module 201 is used to acquire seismic data of the target area. The specific process can be found in the description of step S101 in the above embodiment, which will not be repeated here.

[0086] The standard spectrum establishment module 202 is used to establish a standard spectrum of the target area based on the seismic data. The specific process can be found in the description of step S102 in the above embodiment, which will not be repeated here.

[0087] The identification module 203 is used to identify high-frequency noise of seismic data based on the standard spectrum. The specific process can be found in the description of step S103 in the above embodiment, which will not be repeated here.

[0088] The range determination module 204 is used to determine the wave number range of the effective signal in the frequency-wave number domain when the seismic data contains high frequency noise. The specific process can be found in the description of step S104 in the above embodiment, which will not be repeated here.

[0089] The high-frequency noise suppression module 205 is used to suppress the high-frequency noise based on the wave number range to obtain a suppressed spectrum. The specific process can be found in the description of step S105 in the above embodiment, 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 suppressed spectrum. The specific process can be found in the description of step S106 in the above embodiment, which will not be repeated here.

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

[0092] The embodiment of the present invention also provides a computer device having the above Figure 6 The high frequency noise suppression device based on the frequency wave number is shown. Figure 7 , Figure 7 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 7 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0093] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0094] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0095] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

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

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

Claims

1. A high-frequency noise suppression method based on frequency wave number, characterized in that: The method comprises: Acquire seismic data of the target area; Based on the seismic data, establishing a standard frequency spectrum of the target area; Based on the standard frequency spectrum, high-frequency noise identification is performed on the seismic data; When the seismic data contains high-frequency noise, determining the wavenumber range of the effective signal in the frequency-wavenumber domain; Based on the wave number range, high frequency noise is suppressed to obtain a suppressed spectrum; Based on the suppressed spectrum, seismic data after high-frequency noise suppression is determined.

2. The method according to claim 1, characterized in that The step of establishing a standard frequency spectrum of the target area based on the seismic data comprises: Based on the seismic data, determining a seismic data spectrum in a time-space domain; Based on the seismic data spectrum, the seismic data is screened to determine standard data; Based on the standard data, a standard spectrum of the target area is established.

3. The method according to claim 2, characterized in that The step of establishing a standard spectrum of the target area based on the standard data includes: Determine the time window range, the number of seismic channels, the number of sampling points of each target area seismic data within the time window range and the frequency spectrum within the corresponding time window range corresponding to the standard data through the standard data; Based on the time window range, the number of seismic channels, the number of sampling points and the frequency spectrum, a standard frequency spectrum of the target area is established by calculating the wavelet amplitudes of different frequencies.

4. The method according to claim 2, characterized in that: The process of establishing the standard spectrum is expressed by the following formula: Where F(ω) represents the standard spectrum, N represents the number of seismic channels involved in the calculation, m represents the number of sampling points of each target area seismic data within the time window range, t1 represents the starting time of the time window range, t2 represents the ending time of the time window range, and A t (ω) represents the frequency spectrum at time t within the time window, and ω represents the frequency at time t on the seismic trace.

5. The method according to claim 2, characterized in that: The step of identifying high-frequency noise on the seismic data based on the standard spectrum includes: Based on the seismic data, determining a main frequency parameter of the seismic data; When the amplitude of the spectrum of the seismic data 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 main frequency parameter, the seismic data is considered to contain high-frequency noise.

6. The method according to claim 1, characterized in that When the seismic data contains high-frequency noise, determining the wavenumber range of the effective signal in the frequency-wavenumber domain comprises: Calculating a frequency-wavenumber spectrum of the seismic data containing high-frequency noise in a frequency-wavenumber domain; Based on the characteristics of the effective signal, a frequency protection range and a wave number protection range of the effective signal in the frequency-wave number spectrum are determined, and the frequency protection range and the wave number protection range are used as the wave number range of the effective signal.

7. The method according to claim 1, characterized in that The suppressed spectrum is expressed by the following formula: Among them, F′ t (ω) represents the suppressed spectrum at time t, F t (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 smoothing step length of suppressed noise, and n represents the number of sampling points within the smoothing step length of suppressed noise.

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

9. A high-frequency noise suppression device based on frequency wave number, characterized in that: The device comprises: A data acquisition module, used to acquire seismic data of a target area; A standard spectrum establishment module, used for establishing a standard spectrum of the target area based on the seismic data; An identification module, used for identifying high-frequency noise of the seismic data based on the standard spectrum; A range determination module, for determining a wavenumber range of a valid signal in a frequency-wavenumber domain when the seismic data contains high-frequency noise; A high-frequency noise suppression module, used to suppress high-frequency noise based on the wave number range to obtain a suppressed spectrum; The data determination module is used to determine the seismic data after high-frequency noise suppression based on the suppressed spectrum.

10. A computer device, characterized in that: include: 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 high-frequency noise suppression based on frequency wave number as described in any one of claims 1 to 7 by executing the computer instructions.

Images