CN117970480A - Water layer multiple prediction method, device, computing equipment and storage medium - Google Patents
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Abstract
The invention discloses a method, a device, computing equipment and a storage medium for predicting multiple waves of a water layer. The method comprises the following steps: collecting initial seismic shot gather data; converting the initial seismic shot gather data into frequency-wave number domain seismic shot gather data; wave field continuation processing is carried out on the frequency-wave number domain seismic shot set data to obtain water layer multiple wave prediction data of the frequency-wave number domain. By adopting the scheme, the prediction of the water layer multiple can be realized only by obtaining the seismic shot gather data, the prediction process is simple and feasible, and the prediction efficiency of the water layer multiple is high.
Description
Technical Field
The invention relates to the technical field of exploration, in particular to a water layer multiple prediction method, a device, computing equipment and a storage medium.
Background
The processing of the seismic data is an important link in oil and gas exploration, and the processing result of the seismic data can directly influence the oil and gas exploration result. The shallow water seismic data are generally interfered by multiple waves of the water layer due to the influence of the water layer in the shallow water sea area, so that the processing effect of the shallow water seismic data is affected.
The inventor finds that the following defects exist in the prior art in the implementation process: in the prior art, the mode of predicting the water layer multiple is complex, and the water layer multiple prediction efficiency is low.
Disclosure of Invention
The present invention has been made in view of the above problems, and provides a water layer multiple prediction method, apparatus, computing device, and storage medium that overcome or at least partially solve the above problems.
According to an aspect of the present invention, there is provided a water layer multiple prediction method including:
Collecting initial seismic shot gather data;
converting the initial seismic shot gather data into frequency-wave number domain seismic shot gather data;
And performing wave field prolongation processing on the frequency-wave number domain seismic shot set data to obtain water layer multiple prediction data of the frequency-wave number domain.
In an alternative embodiment, the converting the initial seismic gather data into frequency-wavenumber domain seismic gather data includes:
and performing Fourier transform on the initial seismic shot gather data twice to obtain the frequency-wave number domain seismic shot gather data.
In an alternative embodiment, the obtaining the frequency-wavenumber domain seismic shot gather data after performing the fourier transform on the initial seismic shot gather data twice includes:
performing time dimension Fourier transform on the initial seismic shot gather data to obtain frequency-space domain seismic shot gather data;
and carrying out space dimension Fourier transform on the frequency-space domain seismic shot gather data to obtain frequency-wave number domain seismic shot gather data.
In an alternative embodiment, the obtaining the water layer multiple prediction data of the frequency-wave number domain after the wave field continuation processing is performed on the frequency-wave number domain seismic shot gather data includes:
taking the frequency-wave number domain seismic shot gather data as an initial wave field;
and obtaining water layer multiple prediction data of the frequency-wave number domain according to the initial wave field, the seismic wave water layer propagation speed and the water layer depth.
In an alternative embodiment, the obtaining the water layer multiple prediction data of the frequency-wave number domain after the wave field continuation processing is performed on the frequency-wave number domain seismic shot gather data includes:
the water layer multiple prediction data of the frequency-wave number domain is obtained through the following formula:
Wherein M k (k, f) represents water layer multiple prediction data of the frequency-wave number domain; k (K, f) represents the frequency-wavenumber domain seismic shot gather data; v represents the propagation speed of the seismic wave water layer; ω=2pi f, f representing frequency; k represents wave number; z represents the depth of the aqueous layer.
In an alternative embodiment, the method further comprises: and carrying out wave number dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-wave number domain to obtain the water layer multiple prediction data of the frequency-space domain.
In an alternative embodiment, the method further comprises: and performing frequency dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-space domain to obtain the water layer multiple prediction data of the time-space domain.
According to a second aspect of the embodiment of the present invention, there is provided a water layer multiple prediction apparatus including:
the acquisition module is used for acquiring initial seismic shot gather data;
The conversion module is used for converting the initial seismic shot gather data into frequency-wave number domain seismic shot gather data;
And the extension module is used for carrying out wave field extension processing on the frequency-wave number domain seismic shot gather data to obtain water layer multiple wave prediction data of the frequency-wave number domain.
In an alternative embodiment, the conversion module is configured to: and performing Fourier transform on the initial seismic shot gather data twice to obtain the frequency-wave number domain seismic shot gather data.
In an alternative embodiment, the conversion module is configured to: performing time dimension Fourier transform on the initial seismic shot gather data to obtain frequency-space domain seismic shot gather data;
and carrying out space dimension Fourier transform on the frequency-space domain seismic shot gather data to obtain frequency-wave number domain seismic shot gather data.
In an alternative embodiment, the continuation module is configured to: taking the frequency-wave number domain seismic shot gather data as an initial wave field;
and obtaining water layer multiple prediction data of the frequency-wave number domain according to the initial wave field, the seismic wave water layer propagation speed and the water layer depth.
In an alternative embodiment, the continuation module is configured to: the water layer multiple prediction data of the frequency-wave number domain is obtained through the following formula:
Wherein M k (k, f) represents water layer multiple prediction data of the frequency-wave number domain; k (K, f) represents the frequency-wavenumber domain seismic shot gather data; v represents the propagation speed of the seismic wave water layer; ω=2pi f, f representing frequency; k represents wave number; z represents the depth of the aqueous layer.
In an alternative embodiment, the conversion module is configured to: and carrying out wave number dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-wave number domain to obtain the water layer multiple prediction data of the frequency-space domain.
In an alternative embodiment, the conversion module is configured to: and performing frequency dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-space domain to obtain the water layer multiple prediction data of the time-space domain.
According to a third aspect of embodiments of the present invention, there is provided a computing device comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the water layer multiple wave prediction method.
According to a fourth aspect of the embodiments of the present invention, there is provided a computer storage medium having at least one executable instruction stored therein, the executable instruction causing a processor to perform operations corresponding to the above-described water layer multiple prediction method.
In the water layer multiple prediction method, the device, the computing equipment and the storage medium disclosed by the invention, initial seismic shot set data are collected; converting the initial seismic shot gather data into frequency-wave number domain seismic shot gather data; wave field continuation processing is carried out on the frequency-wave number domain seismic shot set data to obtain water layer multiple wave prediction data of the frequency-wave number domain. By adopting the scheme, the prediction of the water layer multiple can be realized only by obtaining the seismic shot gather data, the prediction process is simple and feasible, and the prediction efficiency of the water layer multiple is high.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
Fig. 1 is a schematic flow chart of a water layer multiple prediction method according to a first embodiment of the present invention;
FIG. 2 shows a schematic wave propagation diagram provided by a first embodiment of the present invention;
Fig. 3 is a schematic flow chart of a water layer multiple prediction method according to a second embodiment of the present invention;
Fig. 4 shows a schematic diagram of multiple prediction effect based on forward model data according to a second embodiment of the present invention;
FIG. 5 shows a schematic diagram of a multiple prediction effect based on actual seismic shot gather data according to a second embodiment of the present invention;
fig. 6 shows a schematic structural diagram of a water layer multiple prediction apparatus according to a third embodiment of the present invention;
fig. 7 is a schematic structural diagram of a computing device according to a fifth embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Example 1
Fig. 1 shows a flow chart of a water layer multiple prediction method according to an embodiment of the invention. The method for predicting the multiple waves of the water layer can be executed through corresponding computing equipment, and the embodiment of the invention is not limited to the specific type of the computing equipment and the like.
Specifically, as shown in fig. 1, the method specifically includes the following steps:
step S110, collecting initial seismic shot gather data.
In the field of seismic exploration, shot points are typically used to excite seismic waves, and seismic wave data is acquired by corresponding detectors, which acquire seismic wave data that is initial seismic shot gather data. The initial seismic shot gather data is a two-dimensional sample data set, which may be represented as D (m, n), m corresponding to the shot gather data transverse sample direction, i.e., the spatial direction, and n corresponding to the shot gather data longitudinal sample direction, i.e., the temporal direction. The initial seismic shot gather data acquired in the step is time-space domain (TX domain) data, namely, the independent variable dimension of the initial seismic shot gather data is a time dimension and a space dimension.
Step S120, converting the initial seismic shot gather data into frequency-wave number domain seismic shot gather data.
Because the initial seismic shot gather data is time-space domain data, the initial seismic shot gather data can be converted into frequency-wave number domain (FK domain) seismic shot gather data through conversion processing, and the independent variable dimension of the frequency-wave number domain seismic shot gather data is a frequency dimension and a wave number dimension.
In an alternative embodiment, converting the initial seismic gather data into frequency-wavenumber domain seismic gather data includes: and performing Fourier transform on the initial seismic shot gather data twice to obtain frequency-wave number domain seismic shot gather data.
Specifically, the initial seismic shot set data comprises two dimensions, namely a transverse dimension (space dimension) and a longitudinal dimension (time dimension), in the specific transformation process, the initial seismic shot set data is subjected to time dimension Fourier transformation to obtain frequency-space domain seismic shot set data, and in the actual implementation process, the time dimension is usually arranged in the coordinate longitudinal direction, so that the transformation process can be expressed as that the initial seismic shot set data is subjected to the longitudinal dimension Fourier transformation to obtain the frequency-space domain seismic shot set data.
Further, the following formula 1 may be specifically adopted to perform time-dimension fourier transform on the initial seismic shot gather data to obtain frequency-space domain seismic shot gather data:
In the above formula 1, F (m, F) represents frequency-space domain seismic shot gather data; d (m, n) represents initial seismic shot gather data; m represents a space; n represents time; f represents frequency; n represents the number of frequency-dimensional samples.
After the frequency-space domain seismic shot gather data is obtained, the frequency-wave number domain seismic shot gather data is obtained after the frequency-space domain seismic shot gather data is subjected to space dimension Fourier transform. Because the spatial dimension is usually arranged in the transverse direction of coordinates in the actual implementation process, the conversion process can be expressed as that the frequency-wave number domain seismic shot set data is obtained after the transverse Fourier transform is performed on the frequency-spatial domain seismic shot set data.
Further, the following equation 2 may be specifically used to perform spatial dimension fourier transform:
In the above formula 2, K (K, f) represents frequency-wave number domain seismic shot gather data; f (m, F) represents frequency-space domain seismic shot gather data; k represents wave number; f represents frequency; m represents the number of wavenumber dimension samples, also the number of spatial dimension samples.
And step S130, performing wave field prolongation processing on the frequency-wave number domain seismic shot gather data to obtain water layer multiple prediction data of the frequency-wave number domain.
The embodiment of the invention specifically takes the frequency-wave number domain seismic shot set data as an initial wave field, and obtains the water layer multiple prediction data of the frequency-wave number domain according to the initial wave field, the water layer propagation speed of the seismic wave and the water layer depth through wave field extrapolation processing, wherein the water layer multiple prediction data of the frequency-wave number domain can reflect the water layer multiple wave fields under different depths.
In an alternative embodiment, a general frequency-wavenumber domain wavefield-extension equation is first obtained as shown in equation 3:
In equation 3 above, U (k, z, ω) represents the wavefield that the initial wavefield U (k, 0, ω) rebroadcasts to somewhere; v represents the wave propagation velocity; z represents depth. In connection with fig. 2, the initial wavefield U (k, 0, ω) reaches the sea floor at depth Z after reflection from the sea surface during propagation and is further reflected, where the wavefield is U (k, Z, ω).
In the above formula 3, ω is an angular frequency, ω=2pi f, and f is a frequency, then the formula 3 can be transformed into the following formula 4:
In the embodiment of the invention, the frequency-wave number domain seismic shot gather data is mapped into an initial wave field U (k x, 0, f) in a formula 4, and the water layer multiple prediction data at the water layer depth Z is mapped into U (k, Z, f) in the formula 4, so that the water layer multiple prediction data of the frequency-wave number domain is calculated according to the following formula 5:
In the above formula 5, M k (k, f) represents the water layer multiple prediction data of the frequency-wave number domain; k (K, f) represents frequency-wavenumber domain seismic shot gather data; v is the propagation speed of the seismic wave water layer; ω=2pi f, f being frequency; k is wave number; z is the depth of the aqueous layer.
Therefore, in the water layer multiple prediction method provided by the embodiment of the invention, the initial seismic shot set data is converted into the frequency-wave number domain seismic shot set data, and the water layer multiple prediction data of the frequency-wave number domain is obtained after wave field prolongation is carried out in the frequency-wave number domain, so that the water layer multiple prediction can be realized only by obtaining the seismic shot set data, the implementation process of the water layer multiple prediction scheme is simple and easy, and the prediction efficiency of the water layer multiple is improved.
Example two
Fig. 3 is a schematic flow chart of a water layer multiple prediction method according to a second embodiment of the present invention. The method for predicting the multiple waves of the water layer can be executed through corresponding computing equipment, and the embodiment of the invention is not limited to the specific type of the computing equipment and the like.
Specifically, as shown in fig. 3, the method specifically includes the following steps:
step S310, collecting initial seismic shot gather data.
Step S320, converting the initial seismic shot gather data into frequency-wave number domain seismic shot gather data.
And step S330, performing wave field prolongation processing on the frequency-wave number domain seismic shot gather data to obtain water layer multiple prediction data of the frequency-wave number domain.
The specific implementation process of step S310 to step S330 may refer to the description of the corresponding steps in the first embodiment, which is not described herein.
And step S340, performing wave number dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-wave number domain to obtain the water layer multiple prediction data of the frequency-space domain.
In the actual seismic data processing process, the imaging and processing are generally performed by using the seismic wave data in the time-space domain, so that after the water layer multiple prediction data in the frequency-wave number domain is obtained, the water layer multiple prediction data in the frequency-wave number domain is subjected to two times of inverse Fourier transformation, the water layer multiple prediction data in the frequency-wave number domain is converted into the water layer multiple prediction data in the time-space domain, and the processing such as imaging, pressing and the like is performed by using the water layer multiple prediction data in the time-space domain.
In a specific implementation process, wave number dimension inverse Fourier transform is performed on the water layer multiple prediction data of the frequency-wave number domain to obtain the water layer multiple prediction data of the frequency-space domain. Since the wave number dimension is generally set in the transverse direction of the coordinates, this step may also be expressed as performing transverse inverse fourier transform on the water layer multiple prediction data in the frequency-wave number domain to obtain the water layer multiple prediction data in the frequency-space domain.
In an alternative embodiment, the following equation 6 may be specifically used to perform wavenumber dimension inverse fourier transform on the water layer multiple prediction data in the frequency-wave number domain, so as to obtain the water layer multiple prediction data in the frequency-space domain:
In the above formula 6, M f (M, f) represents the water layer multiple prediction data of the frequency-space domain; m k (k, f) represents water layer multiple prediction data of the frequency-wave number domain; k represents wave number; f represents frequency; m represents the number of wavenumber dimension samples, also the number of spatial dimension samples.
And step S350, performing frequency dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-space domain to obtain the water layer multiple prediction data of the time-space domain.
After the water layer multiple prediction data in the frequency-space domain is obtained in step S340, the frequency dimension inverse fourier transform is further performed on the water layer multiple prediction data in the frequency-space domain, and the water layer multiple prediction data in the time-space domain is obtained after the transform. Since the frequency dimension is generally set in the vertical direction of the coordinates, this step may be expressed as performing vertical inverse fourier transform on the water layer multiple prediction data in the frequency-space domain to obtain the water layer multiple prediction data in the time-space domain.
In an alternative embodiment, the following equation 7 may be specifically used to perform frequency-dimensional inverse fourier transform on the water layer multiple prediction data in the frequency-space domain, so as to obtain the water layer multiple prediction data in the time-space domain:
In the above formula 7, M (M, n) represents water layer multiple prediction data of the time-space domain; m f (M, f) represents water layer multiple prediction data of the frequency-space domain; m represents a space; n represents time; f represents frequency; n represents the number of frequency-dimensional samples, also the number of time-dimensional samples.
The implementation of step S310-step S350 can obtain the water layer multiple prediction data of the time-space domain, which has higher accuracy. For example, fig. 4 shows a schematic view of multiple prediction effect based on forward model data, where P1 in fig. 4 is an image generated by using shot gather data of a forward model, and P2 is an image generated by using water layer multiple prediction data obtained by using a water layer multiple prediction method in an embodiment of the present invention based on shot gather data of a forward model, and comparing P1 and P2, it is known that P2 and P1 have a higher overlap ratio, so as to verify that the water layer multiple prediction method provided by the embodiment of the present invention has a higher prediction accuracy. Fig. 5 shows a schematic view of multiple prediction effect based on actual data, where P3 in fig. 5 is an image generated by actual shot gather data, and P2 is an image generated by water layer multiple prediction data obtained based on the actual shot gather data by using the water layer multiple prediction method in the embodiment of the present invention, and it is known from comparing P3 and P4 that P4 and P3 have a higher overlap ratio, so that it is verified that the water layer multiple prediction method provided by the embodiment of the present invention has a higher prediction precision.
Therefore, in the water layer multiple prediction method provided by the embodiment of the invention, the initial seismic shot set data is converted into the frequency-wave number domain seismic shot set data, the water layer multiple prediction data of the frequency-wave number domain is obtained after wave field continuation is carried out in the frequency-wave number domain, and the prediction efficiency of the water layer multiple is improved; after the water layer multiple prediction data of the frequency-wave number domain are obtained, the water layer multiple prediction data of the frequency-wave number domain are subjected to wave number dimension inverse Fourier transform to obtain the water layer multiple prediction data of the frequency-space domain, and the water layer multiple prediction data of the frequency-space domain are subjected to frequency dimension inverse Fourier transform to obtain the water layer multiple prediction data of the time-space domain, so that the processing such as suppression or imaging of the water layer multiple is conveniently carried out according to the water layer multiple prediction data of the time-space domain.
Example III
Fig. 6 shows a schematic structural diagram of a water layer multiple prediction apparatus according to a third embodiment of the present invention. As shown in fig. 6, the water layer multiple prediction apparatus includes: an acquisition module 610, a conversion module 620, and a continuation module 630.
The acquisition module 610 is used for acquiring initial seismic shot gather data;
A conversion module 620, configured to convert the initial seismic shot gather data into frequency-wavenumber domain seismic shot gather data;
and the continuation module 630 is configured to perform wave field continuation processing on the frequency-wave number domain seismic shot gather data to obtain water layer multiple prediction data of the frequency-wave number domain.
In an alternative embodiment, the conversion module 620 is configured to: and performing Fourier transform on the initial seismic shot gather data twice to obtain the frequency-wave number domain seismic shot gather data.
In an alternative embodiment, the conversion module 620 is configured to: performing time dimension Fourier transform on the initial seismic shot gather data to obtain frequency-space domain seismic shot gather data;
and carrying out space dimension Fourier transform on the frequency-space domain seismic shot gather data to obtain frequency-wave number domain seismic shot gather data.
In an alternative embodiment, continuation module 630 is configured to: taking the frequency-wave number domain seismic shot gather data as an initial wave field;
and obtaining water layer multiple prediction data of the frequency-wave number domain according to the initial wave field, the seismic wave water layer propagation speed and the water layer depth.
In an alternative embodiment, continuation module 630 is configured to: the water layer multiple prediction data of the frequency-wave number domain is obtained through the following formula:
Wherein M k (k, f) represents water layer multiple prediction data of the frequency-wave number domain; k (K, f) represents the frequency-wavenumber domain seismic shot gather data; v represents the propagation speed of the seismic wave water layer; ω=2pi f, f representing frequency; k represents wave number; z represents the depth of the aqueous layer.
In an alternative embodiment, the conversion module 620 is configured to: and carrying out wave number dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-wave number domain to obtain the water layer multiple prediction data of the frequency-space domain.
In an alternative embodiment, the conversion module 620 is configured to: and performing frequency dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-space domain to obtain the water layer multiple prediction data of the time-space domain.
Therefore, in the water layer multiple prediction device provided by the embodiment of the invention, the initial seismic shot set data is converted into the frequency-wave number domain seismic shot set data, and the water layer multiple prediction data of the frequency-wave number domain is obtained after wave field prolongation is carried out in the frequency-wave number domain, so that the water layer multiple prediction can be realized only by obtaining the seismic shot set data, the implementation process of the scheme is simple and feasible, and the prediction efficiency of the water layer multiple is improved.
Example IV
A fourth embodiment of the present invention provides a non-volatile computer storage medium, where at least one executable instruction is stored, where the computer executable instruction may perform the method for predicting multiple waves of a water layer in any of the above method embodiments.
Example five
Fig. 7 is a schematic structural diagram of a computing device according to a sixth embodiment of the present invention. The specific embodiments of the present invention are not limited to a particular implementation of a computing device.
As shown in fig. 7, the computing device may include: a processor 702, a communication interface (Communications Interface), a memory 706, and a communication bus 708.
Wherein: processor 702, communication interface 704, and memory 706 perform communication with each other via a communication bus 708. A communication interface 704 for communicating with network elements of other devices, such as clients or other servers. The processor 702 is configured to execute the program 710, and may specifically perform the relevant steps in the embodiment of the method for predicting multiple waves in a water layer.
In particular, program 710 may include program code including computer-operating instructions.
The processor 702 may be a Central Processing Unit (CPU) or an Application-specific integrated Circuit (ASIC) or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included by the computing device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
Memory 706 for storing programs 710. The memory 706 may comprise high-speed RAM memory or may further comprise non-volatile memory (non-volatile memory), such as at least one disk memory. The program 710 may be specifically configured to cause the processor 702 to perform the operations in the above-described aqueous layer multiple prediction method embodiment.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.
Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components according to embodiments of the present invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specifically stated.
Claims (10)
1. A method for predicting multiple waves in a water layer, comprising:
Collecting initial seismic shot gather data;
converting the initial seismic shot gather data into frequency-wave number domain seismic shot gather data;
And performing wave field prolongation processing on the frequency-wave number domain seismic shot set data to obtain water layer multiple prediction data of the frequency-wave number domain.
2. The method of claim 1, wherein said converting said initial seismic gather data into frequency-wavenumber domain seismic gather data comprises:
and performing Fourier transform on the initial seismic shot gather data twice to obtain the frequency-wave number domain seismic shot gather data.
3. The method of claim 2, wherein said obtaining said frequency-wavenumber domain seismic shot gather data after performing a two-time fourier transform on said initial seismic shot gather data comprises:
performing time dimension Fourier transform on the initial seismic shot gather data to obtain frequency-space domain seismic shot gather data;
and carrying out space dimension Fourier transform on the frequency-space domain seismic shot gather data to obtain frequency-wave number domain seismic shot gather data.
4. A method according to any one of claims 1-3, wherein obtaining water layer multiple prediction data of the frequency-wavenumber domain after performing wave field continuation processing on the frequency-wavenumber domain seismic shot gather data comprises:
taking the frequency-wave number domain seismic shot gather data as an initial wave field;
and obtaining water layer multiple prediction data of the frequency-wave number domain according to the initial wave field, the seismic wave water layer propagation speed and the water layer depth.
5. The method of claim 4, wherein obtaining water layer multiple prediction data of the frequency-wavenumber domain after performing wave field continuation processing on the frequency-wavenumber domain seismic shot gather data comprises:
the water layer multiple prediction data of the frequency-wave number domain is obtained through the following formula:
Wherein M k (k, f) represents water layer multiple prediction data of the frequency-wave number domain; k (K, f) represents the frequency-wavenumber domain seismic shot gather data; v represents the propagation speed of the seismic wave water layer; ω=2pi f, f representing frequency; k represents wave number; z represents the depth of the aqueous layer.
6. A method according to any one of claims 1-3, characterized in that the method further comprises:
And carrying out wave number dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-wave number domain to obtain the water layer multiple prediction data of the frequency-space domain.
7. The method of claim 6, wherein the method further comprises:
and performing frequency dimension inverse Fourier transform on the water layer multiple prediction data of the frequency-space domain to obtain the water layer multiple prediction data of the time-space domain.
8. A water layer multiple prediction apparatus, comprising:
the acquisition module is used for acquiring initial seismic shot gather data;
The conversion module is used for converting the initial seismic shot gather data into frequency-wave number domain seismic shot gather data;
And the extension module is used for carrying out wave field extension processing on the frequency-wave number domain seismic shot gather data to obtain water layer multiple wave prediction data of the frequency-wave number domain.
9. A computing device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
The memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the water layer multiple prediction method according to any one of claims 1-7.
10. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the water layer multiple prediction method of any one of claims 1-7.
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