CN107561588A - Seismic data noise suppression method and device - Google Patents
Seismic data noise suppression method and device Download PDFInfo
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Abstract
The embodiment of the application discloses a method and a device for suppressing seismic data noise. The method comprises the steps that frequency-space domain seismic data are obtained by carrying out Fourier transform processing on the time-space domain seismic data, wherein the frequency-space domain seismic data comprise a plurality of single-frequency seismic data which are arranged according to frequency; the method comprises the following steps: acquiring a constraint factor corresponding to current single-frequency seismic data, wherein the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and the frequency of the target single-frequency seismic data is less than that of the current single-frequency seismic data; carrying out noise suppression on the current single-frequency seismic data by using the constraint factor to obtain the current single-frequency seismic data after noise suppression; and determining the time-space domain seismic data after the noise suppression based on the single-frequency seismic data after the noise suppression. Random noise data in the seismic data can be effectively suppressed.
Description
Technical Field
The application relates to the field of geophysical exploration, in particular to a method and a device for suppressing seismic data noise.
Background
Noise can be generally classified as regular noise and irregular noise by the nature of the noise that appears on a seismic section. The regular noise mainly refers to noise with a certain main frequency and a certain apparent speed, such as surface wave, alternating current interference, sound wave, shallow refraction and the like. Irregular noise, i.e., random noise, refers primarily to waves without fixed frequency and fixed propagation direction, forming a cluttered background in the seismic data. Random noise appears as a very wide frequency on seismic records without a certain velocity, and thus it is difficult to suppress the random noise from differences between the random noise and the effective wave in the spectrum or in the propagation direction. Due to the complexity of the surface conditions, seismic data often contain random noise, such as microseisms, background interference, etc. These noises are widely distributed and severely affect the signal-to-noise ratio of the seismic data.
In the field of seismic exploration, research on a random noise suppression method of seismic data has been receiving wide attention of related researchers. The method for suppressing random noise generally adopted at present is mainly a polynomial fitting suppression method, and the method is mainly characterized in that on the premise that the seismic signals keep certain continuity in space and the phase and amplitude of the seismic signals are uniform in space, the specified polynomial is adopted to fit the seismic signals so as to enhance the continuity of the signals and improve the signal-to-noise ratio, and therefore the purpose of noise suppression is achieved. However, in an actual seismic exploration process, the seismic signals may not meet the precondition, and if the random noise suppression is still performed by using the method in the prior art, the effect of suppressing the random noise data in the seismic data may be poor.
With the development of the technology, an exploration target gradually shifts to a deep part and a region with a complex earth surface, and the processing requirement of seismic data is higher and higher, so how to effectively suppress noise and improve the signal-to-noise ratio of seismic data is a problem which needs to be solved urgently in the field of seismic exploration.
Disclosure of Invention
The embodiment of the application aims to provide a seismic data noise suppression method and a device, so as to effectively suppress random noise data in seismic data.
In order to solve the above technical problem, an embodiment of the present application provides a method and a device for suppressing seismic data noise, which are implemented as follows:
a seismic data noise suppression method is provided with frequency-space domain seismic data obtained by Fourier transform processing based on time-space domain seismic data, wherein the frequency-space domain seismic data comprise a plurality of single-frequency seismic data arranged according to frequency; the method comprises the following steps:
acquiring a constraint factor corresponding to current single-frequency seismic data, wherein the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and the frequency of the target single-frequency seismic data is less than that of the current single-frequency seismic data;
carrying out noise suppression on the current single-frequency seismic data by using the constraint factor to obtain current single-frequency seismic data after noise suppression;
and determining the time-space domain seismic data after the noise suppression based on the single-frequency seismic data after the noise suppression.
In a preferred scheme, when the target single-frequency seismic data is the single-frequency seismic data with the minimum frequency in the plurality of single-frequency seismic data, the target single-frequency seismic data is used as the noise-suppressed target single-frequency seismic data, and the constraint factor corresponding to the current single-frequency seismic data is determined according to the noise-suppressed target single-frequency seismic data.
In a preferred embodiment, the obtaining of the constraint factor corresponding to the current single-frequency seismic data includes:
determining the noise suppressed target single-frequency seismic data corresponding to the target single-frequency seismic data;
filtering the noise-suppressed target single-frequency seismic data to obtain filtered target single-frequency seismic data;
determining filtered target single-frequency seismic data of a frequency-wave number domain corresponding to the filtered target single-frequency seismic data;
and determining the constraint factor according to the filtered target single-frequency seismic data of the frequency-wave number domain.
In a preferred embodiment, the filtering processing of the noise-suppressed target single-frequency seismic data includes:
performing median filtering processing on the noise-suppressed target single-frequency seismic data to obtain median-filtered target single-frequency seismic data;
and carrying out mean value filtering processing on the target single-frequency seismic data after the median value filtering processing.
In a preferred embodiment, the constraint factor is determined by the following formula:
wherein W represents the constraint factor,representing the target single-frequency seismic data after the mean value filtration of the frequency-wave number domain, H representing a conjugate transpose operation symbol,is shown inIs a matrix of diagonal elements.
In an embodiment, the performing noise suppression on the current single-frequency seismic data by using the constraint factor to obtain noise-suppressed current single-frequency seismic data includes:
establishing an objective function associated with the current single-frequency seismic data according to the constraint factor;
and determining the current single-frequency seismic data after noise suppression based on the objective function.
In a preferred scheme, the objective function associated with the current single-frequency seismic data is established by adopting the following formula:
Q(m)＝||d-Gm||2+λwmHW-2m
wherein Q (m) represents the objective function, d represents the current single-frequency seismic data, m represents the current single-frequency seismic data of the frequency-wavenumber domain after initial noise suppression corresponding to the current single-frequency seismic data, H represents a conjugate transpose operation symbol, W represents the constraint factor, and λwRepresenting a weight factor which is a non-negative real number, G representing an unequally spaced inverse Fourier transform matrix, the ith in GxAnd row and columnikThe matrix elements of the columns areWherein D represents the dimension of the spatial coordinates, kη(ikη) wavenumber coordinate, k, representing the eta dimensionη(ikη)＝ikη，xη(ix) representing the space coordinate of the eta dimension before noise suppression, ikηRepresenting a multi-dimensional wavenumber coordinate index, Nkηrepresenting the space coordinates of the eta dimension after initial noise suppression, where l represents the unit of imaginary number, and l2＝-1。
In a preferred embodiment, the determining the noise-suppressed current single-frequency seismic data based on the objective function includes:
determining current single-frequency seismic data of a frequency-wavenumber domain after target noise suppression corresponding to the current single-frequency seismic data so as to enable the value of the target function to be minimum;
and transforming the current single-frequency seismic data of the frequency-wavenumber domain after the target noise suppression into a frequency-space domain to obtain the current single-frequency seismic data after the noise suppression.
In a preferred embodiment, the determining the noise suppressed time-space domain seismic data according to the noise suppressed single-frequency seismic data includes:
determining the frequency-space domain seismic data after noise suppression corresponding to the frequency-space domain seismic data according to the single-frequency seismic data after noise suppression;
and performing inverse Fourier transform processing on the frequency-space domain seismic data after the noise suppression to obtain the time-space domain seismic data after the noise suppression.
A seismic data noise suppression device provides frequency-space domain seismic data obtained by Fourier transform processing based on time-space domain seismic data, wherein the frequency-space domain seismic data comprise a plurality of single-frequency seismic data arranged according to frequency; the device comprises: the device comprises a constraint factor determining module, a single-frequency noise suppression module and a noise suppression seismic data determining module; wherein,
the constraint factor determination module is configured to obtain a constraint factor corresponding to current single-frequency seismic data, where the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, where the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and a frequency of the target single-frequency seismic data is less than a frequency of the current single-frequency seismic data;
the single-frequency noise suppression module is used for performing noise suppression on the current single-frequency seismic data by using the constraint factor to obtain the current single-frequency seismic data after noise suppression;
and the noise suppression seismic data determination module is used for determining the time-space domain seismic data after noise suppression based on the single-frequency seismic data after noise suppression.
The embodiment of the application provides a seismic data noise suppression method and a device, which can obtain a constraint factor corresponding to current single-frequency seismic data, wherein the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and the frequency of the target single-frequency seismic data is less than that of the current single-frequency seismic data; performing noise suppression on the current single-frequency seismic data by using the constraint factor to obtain noise-suppressed current single-frequency seismic data; the post-noise-suppression time-space domain seismic data may be determined based on the post-noise-suppression single frequency seismic data. Therefore, noise suppression is performed on the global seismic data based on Fourier inversion, and the stability and the noise suppression effect of noise suppression can be improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.
FIG. 1 is a flow chart of an embodiment of a seismic data noise suppression method of the present application;
FIG. 2 is a schematic cross-sectional view of seismic data prior to noise suppression in an embodiment of the present application;
FIG. 3 is a schematic cross-sectional view of seismic data after noise suppression using a prior art method in an embodiment of the present application;
FIG. 4 is a schematic cross-sectional view of seismic data after noise suppression using the method of the present application in an embodiment of the present application;
fig. 5 is a block diagram of the components of an embodiment of the seismic data noise suppression apparatus of the present application.
Detailed Description
The embodiment of the application provides a method and a device for suppressing seismic data noise.
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiment of the application provides a seismic data noise suppression method. The seismic data noise suppression method is provided with frequency-space domain seismic data obtained by performing Fourier transform processing on time-space domain seismic data, wherein the frequency-space domain seismic data comprise a plurality of single-frequency seismic data arranged according to frequency.
In this embodiment, the time-space domain seismic data may be acquired by means of seismic exploration. Wherein the time-space domain seismic data may include a plurality of sample points. For example, the time-space domain seismic data may be characterized using a function d (t, x). Where t denotes a time coordinate, x denotes a space coordinate, and x ═ x (i) denotes a space coordinatex)＝[x0(ix),x1(ix),...,xD-1(ix)]Where D represents the dimension of the spatial coordinate, ixIndex representing spatial coordinates, ix＝0,1,...,Nx-1，NxRepresenting the number of spatial coordinates in the time-space domain seismic data.
In this embodiment, fourier transform processing may be performed on the time-space domain seismic data to obtain the frequency-space domain seismic data. Wherein the frequency-space domain seismic data may include a plurality of single frequency seismic data. For example, the frequency-space domain seismic data may be characterized using a function d (f, x). Where f denotes the time coordinate, x denotes the space coordinate,wherein l represents an imaginary unit, and l2Is-1. As such, the frequency-space domain seismic data may be comprised of a plurality of single frequency seismic data.
FIG. 1 is a flow chart of an embodiment of a seismic data noise suppression method of the present application. As shown in fig. 1, the seismic data noise suppression method includes the following steps.
Step S101: obtaining a constraint factor corresponding to current single-frequency seismic data, wherein the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and the frequency of the target single-frequency seismic data is less than that of the current single-frequency seismic data.
In this embodiment, when the target single-frequency seismic data is the single-frequency seismic data with the minimum frequency in the single-frequency seismic data, the target single-frequency seismic data may be used as the noise-suppressed target single-frequency seismic data, and the constraint factor corresponding to the current single-frequency seismic data may be determined according to the noise-suppressed target single-frequency seismic data.
In this embodiment, obtaining the constraint factor corresponding to the current single-frequency seismic data may specifically include determining the noise-suppressed target single-frequency seismic data corresponding to the target single-frequency seismic data. And filtering the noise suppressed target single-frequency seismic data to obtain filtered target single-frequency seismic data. Filtered target single frequency seismic data in a frequency-wavenumber domain corresponding to the filtered target single frequency seismic data may be determined. The constraint factor may be determined from the filtered target single frequency seismic data in the frequency-wavenumber domain.
In this embodiment, the filtering processing may be specifically performed on the noise-suppressed target single-frequency seismic data, and specifically, the filtering processing may be performed on the noise-suppressed target single-frequency seismic data to obtain median-filtered target single-frequency seismic data. Wherein, in any spatial dimension of the single-frequency seismic data, the window length of the median filtering process may be 5 sampling points. The median filtering process may be performed on the target single-frequency seismic data after the median filtering process, so that the filtered target single-frequency seismic data may be obtained. Wherein, in any spatial dimension of the single-frequency seismic data, the window length of the mean filtering process may be 9 sampling points.
In this embodiment, the transform matrix F may be used to determine the frequency-wavenumber corresponding to the filtered target single-frequency seismic dataFiltered target single frequency seismic data of the domain. Wherein the transformation matrix F is a two-dimensional matrix, and the ith matrix of the transformation matrix FyRow and ithkThe matrix elements of the columns areD represents the dimension of the spatial coordinates, kη(ikη) wavenumber coordinate, k, representing the eta dimensionη(ikη)＝ikη，yη(iyη) spatial coordinates, y, representing the eta dimensionη(iyη)＝iyη，ikηRepresenting a multi-dimensional wavenumber coordinate index, iyηIndex representing a multidimensional space coordinate, l represents an imaginary unit, and l2＝-1；ikIs both the column index of the transformation matrix F and the multi-dimensional wave number coordinate index ikηVectorized index of ikAnd ikηThe relationship between them can be determined by the following formula:
iyboth the row index of the transformation matrix F and the index i of the multidimensional space coordinateyηVectorized index of iyAnd iyηThe relationship between them can be determined by the following formula:
where D represents the dimension of the spatial coordinate.
In this embodiment, the constraint factor may be determined using the following equation:
wherein W represents the constraintThe factor(s) is (are),representing the target single-frequency seismic data after the mean value filtration of the frequency-wave number domain, H representing a conjugate transpose operation symbol,is shown inIs a matrix of diagonal elements.
Step S102: and carrying out noise suppression on the current single-frequency seismic data by using the constraint factor to obtain the noise-suppressed current single-frequency seismic data.
In this embodiment, the noise suppression of the current single-frequency seismic data by using the constraint factor may obtain the noise-suppressed current single-frequency seismic data, and specifically, the method may include establishing an objective function associated with the single-frequency seismic data according to the constraint factor. Based on the objective function, the noise suppressed current single frequency seismic data may be determined.
In this embodiment, the objective function associated with the current single-frequency seismic data may be established using the following formula:
Q(m)＝||d-Gm||2+λwmHW0 -2m
wherein Q (m) represents the objective function, d represents the current single-frequency seismic data, m represents the current single-frequency seismic data of the frequency-wavenumber domain after initial noise suppression corresponding to the current single-frequency seismic data, H represents a conjugate transpose operation symbol, W represents a conjugate transpose operation symbol, and0represents said first constraint factor, λwRepresenting a weight factor which is a non-negative real number, G representing an unequally spaced inverse Fourier transform matrix, the ith in GxRow and ithkThe matrix elements of the columns areWherein D represents the dimension of the spatial coordinates, kη(ikη) wavenumber coordinate, k, representing the eta dimensionη(ikη)＝ikη，xη(ix) representing the space coordinate of the eta dimension before noise suppression, ikηRepresenting a multi-dimensional wavenumber coordinate index, Nkηrepresenting the space coordinates of the eta dimension after initial noise suppression, l representing the unit of imaginary number, and l2＝-1；ikIs not only the column index of the matrix G, but also the multi-dimensional wave number coordinate index ikηVectorized index of ikAnd ikηThe relationship between them can be determined by the following formula:
ixis not only the row index of the matrix G, but also the space coordinate x of the eta dimension before noise suppressionη(ix) Is used to determine the index of (1).
In this embodiment, determining the noise-suppressed current single-frequency seismic data based on the objective function may specifically include determining current single-frequency seismic data in a target noise-suppressed frequency-wavenumber domain corresponding to the current single-frequency seismic data, so as to minimize a value of the objective function. The current single-frequency seismic data in the frequency-wavenumber domain after the target noise suppression can be transformed into a frequency-space domain, and the current single-frequency seismic data after the noise suppression can be obtained.
Step S103: and determining the time-space domain seismic data after the noise suppression according to the single-frequency seismic data after the noise suppression.
In this embodiment, determining the post-noise suppression time-space domain seismic data according to the post-noise suppression single-frequency seismic data includes: and determining the frequency-space domain seismic data after noise suppression corresponding to the frequency-space domain seismic data according to the single-frequency seismic data after noise suppression. Inverse fourier transform processing may be performed on the noise-suppressed frequency-space domain seismic data to obtain the noise-suppressed time-space domain seismic data.
For example, FIG. 2 is a schematic cross-sectional view of seismic data prior to noise suppression in an embodiment of the present application. FIG. 3 is a cross-sectional schematic of seismic data after noise suppression using a prior art method in an embodiment of the present application. FIG. 4 is a cross-sectional schematic of seismic data after noise suppression using the method of the present application in an embodiment of the present application. The abscissa and ordinate in fig. 2 to 4 represent the line position and the sampling time, respectively, and the gray scale values in fig. 2 to 4 represent the amplitude. As shown in fig. 2 to 4, it can be seen that, compared with the prior art, the seismic data after noise suppression by the method of the present application has better lateral continuity and higher longitudinal resolution, so that the method of the present application can effectively suppress random noise data in the seismic data.
According to the embodiment of the seismic data noise suppression method, a constraint factor corresponding to current single-frequency seismic data can be obtained, wherein the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and the frequency of the target single-frequency seismic data is less than that of the current single-frequency seismic data; performing noise suppression on the current single-frequency seismic data by using the constraint factor to obtain noise-suppressed current single-frequency seismic data; the post-noise-suppression time-space domain seismic data may be determined based on the post-noise-suppression single frequency seismic data. Therefore, noise suppression is performed on the global seismic data based on Fourier inversion, and the stability and the noise suppression effect of noise suppression can be improved.
Fig. 5 is a block diagram of the components of an embodiment of the seismic data noise suppression apparatus of the present application. The seismic data noise suppression device provides frequency-space domain seismic data obtained by performing Fourier transform processing on time-space domain seismic data, wherein the frequency-space domain seismic data comprise a plurality of single-frequency seismic data arranged according to frequency. As shown in fig. 5, the seismic data noise suppression apparatus may include: a constraint factor determination module 100, a single frequency noise suppression module 200 and a noise suppression seismic data determination module 300.
The constraint factor determining module 100 may be configured to obtain a constraint factor corresponding to current single-frequency seismic data, where the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, where the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and a frequency of the target single-frequency seismic data is less than a frequency of the current single-frequency seismic data.
The single-frequency noise suppression module 200 may be configured to perform noise suppression on the current single-frequency seismic data by using the constraint factor, so as to obtain noise-suppressed current single-frequency seismic data.
The noise-suppressed seismic data determination module 300 may be configured to determine noise-suppressed time-space domain seismic data based on the noise-suppressed single-frequency seismic data.
The embodiment of the seismic data noise suppression device corresponds to the embodiment of the seismic data noise suppression method, the technical scheme of the embodiment of the seismic data noise suppression method can be realized, and the technical effect of the embodiment of the method can be obtained.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as ABEL (Advanced Boolean Expression Language), AHDL (alternate Hardware Description Language), traffic, CUPL (core universal Programming Language), HDCal, jhddl (Java Hardware Description Language), Lava, Lola, HDL, PALASM, rhyd (Hardware Description Language), and vhjhddl (Hardware Description Language), which is currently used in most popular version-version Language (Hardware Description Language). It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The apparatuses and modules illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the various modules may be implemented in the same one or more software and/or hardware implementations as the present application.
From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus necessary general hardware platform. With this understanding in mind, the present solution, or portions thereof that contribute to the prior art, may be embodied in the form of a software product, which in a typical configuration includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The computer software product may include instructions for causing a computing device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in the various embodiments or portions of embodiments of the present application. The computer software product may be stored in a memory, which may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium. Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include transitory computer readable media (transient media), such as modulated data signals and carrier waves.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
While the present application has been described with examples, those of ordinary skill in the art will appreciate that there are numerous variations and permutations of the present application without departing from the spirit of the application, and it is intended that the appended claims encompass such variations and permutations without departing from the spirit of the application.
Claims (10)
1. A seismic data noise suppression method is characterized in that frequency-space domain seismic data obtained by Fourier transform processing based on time-space domain seismic data are provided, and the frequency-space domain seismic data comprise a plurality of single-frequency seismic data arranged according to frequency; the method comprises the following steps:
acquiring a constraint factor corresponding to current single-frequency seismic data, wherein the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and the frequency of the target single-frequency seismic data is less than that of the current single-frequency seismic data;
carrying out noise suppression on the current single-frequency seismic data by using the constraint factor to obtain current single-frequency seismic data after noise suppression;
and determining the time-space domain seismic data after the noise suppression based on the single-frequency seismic data after the noise suppression.
2. The method according to claim 1, wherein when the target single-frequency seismic data is the single-frequency seismic data with the minimum frequency in the single-frequency seismic data, the target single-frequency seismic data is used as the noise-suppressed target single-frequency seismic data, and the constraint factor corresponding to the current single-frequency seismic data is determined according to the noise-suppressed target single-frequency seismic data.
3. The method according to claim 1, wherein the obtaining of the constraint factor corresponding to the current single-frequency seismic data comprises:
determining the noise suppressed target single-frequency seismic data corresponding to the target single-frequency seismic data;
filtering the noise-suppressed target single-frequency seismic data to obtain filtered target single-frequency seismic data;
determining filtered target single-frequency seismic data of a frequency-wave number domain corresponding to the filtered target single-frequency seismic data;
and determining the constraint factor according to the filtered target single-frequency seismic data of the frequency-wave number domain.
4. The method of claim 3, wherein the filtering the noise-suppressed target single-frequency seismic data comprises:
performing median filtering processing on the noise-suppressed target single-frequency seismic data to obtain median-filtered target single-frequency seismic data;
and carrying out mean value filtering processing on the target single-frequency seismic data after the median value filtering processing.
5. A method as claimed in claim 3 wherein said constraint factor is determined using the following equation:
<mrow> <msup> <mi>W</mi> <mrow> <mo>-</mo> <mn>2</mn> </mrow> </msup> <mo>=</mo> <mi>d</mi> <mi>i</mi> <mi>a</mi> <mi>g</mi> <msup> <mrow> <mo>(</mo> <msup> <msub> <mover> <mi>m</mi> <mo>~</mo> </mover> <mn>0</mn> </msub> <mi>H</mi> </msup> <msub> <mover> <mi>m</mi> <mo>~</mo> </mover> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow>
wherein W represents the constraint factor,representing the target single-frequency seismic data after the mean value filtration of the frequency-wave number domain, H representing a conjugate transpose operation symbol,is shown inIs a matrix of diagonal elements.
6. The method of claim 1, wherein the noise suppressing the current single-frequency seismic data by using the constraint factor to obtain noise-suppressed current single-frequency seismic data comprises:
establishing an objective function associated with the current single-frequency seismic data according to the constraint factor;
and determining the current single-frequency seismic data after noise suppression based on the objective function.
7. The seismic data noise suppression method of claim 6, wherein the objective function associated with the current single frequency seismic data is established using the following formula:
Q(m)＝||d-Gm||2+λwmHW-2m
wherein Q (m) represents the objective function, d represents the current single-frequency seismic data, m represents the current single-frequency seismic data of the frequency-wavenumber domain after initial noise suppression corresponding to the current single-frequency seismic data, H represents a conjugate transpose operation symbol, W represents the constraint factor, and λwRepresenting a weight factor which is a non-negative real number, G representing an unequally spaced inverse Fourier transform matrix, the ith in GxRow and ithkThe matrix elements of the columns areWherein D represents the dimension of the spatial coordinates, kη(ikη) wavenumber coordinate, k, representing the eta dimensionη(ikη)＝ikη，xη(ix) representing the space coordinate of the eta dimension before noise suppression, ikηRepresenting a multi-dimensional wavenumber coordinate index, Nkηrepresenting the space coordinates of the eta dimension after initial noise suppression, where l represents the unit of imaginary number, and l2＝-1。
8. The method of claim 7, wherein determining the noise-suppressed current single-frequency seismic data based on the objective function comprises:
determining current single-frequency seismic data of a frequency-wavenumber domain after target noise suppression corresponding to the current single-frequency seismic data so as to enable the value of the target function to be minimum;
and transforming the current single-frequency seismic data of the frequency-wavenumber domain after the target noise suppression into a frequency-space domain to obtain the current single-frequency seismic data after the noise suppression.
9. The method of claim 1, wherein determining the noise suppressed time-space domain seismic data from the noise suppressed single frequency seismic data comprises:
determining the frequency-space domain seismic data after noise suppression corresponding to the frequency-space domain seismic data according to the single-frequency seismic data after noise suppression;
and performing inverse Fourier transform processing on the frequency-space domain seismic data after the noise suppression to obtain the time-space domain seismic data after the noise suppression.
10. The device for suppressing the noise of the seismic data is characterized by providing frequency-space domain seismic data obtained by carrying out Fourier transform processing on the time-space domain seismic data, wherein the frequency-space domain seismic data comprise a plurality of single-frequency seismic data which are arranged according to the frequency; the device comprises: the device comprises a constraint factor determining module, a single-frequency noise suppression module and a noise suppression seismic data determining module; wherein,
the constraint factor determination module is configured to obtain a constraint factor corresponding to current single-frequency seismic data, where the constraint factor is obtained by performing noise suppression on target single-frequency seismic data, where the target single-frequency seismic data is adjacent to the current single-frequency seismic data, and a frequency of the target single-frequency seismic data is less than a frequency of the current single-frequency seismic data;
the single-frequency noise suppression module is used for performing noise suppression on the current single-frequency seismic data by using the constraint factor to obtain the current single-frequency seismic data after noise suppression;
and the noise suppression seismic data determination module is used for determining the time-space domain seismic data after noise suppression based on the single-frequency seismic data after noise suppression.
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