CN116482753B - Diffracted wave extraction method, device, electronic equipment and medium - Google Patents
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- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
Abstract
The invention provides a diffraction wave extraction method, a device, electronic equipment and a medium, which relate to the technical field of seismic exploration and comprise the following steps: acquiring original seismic data; performing initial wave field separation on the original seismic data to obtain initial diffracted wave data and initial reflected wave data; and optimizing the initial diffracted wave data and the initial reflected wave data based on a least square space optimization algorithm to obtain the separated diffracted wave data and reflected wave data. The invention is beneficial to the high-fidelity extraction of the diffraction wave signals.
Description
Technical Field
The present invention relates to the field of seismic exploration, and in particular, to a method and apparatus for extracting diffracted waves, an electronic device, and a medium.
Background
Underground discontinuous geologic bodies, such as holes, faults, cracks and the like, often have a close relationship with mineral resource distribution, and can accurately position the non-uniform discontinuous geologic bodies, so that the exploration success rate can be effectively improved, the cost is reduced, possible geological disasters are avoided, and risks are avoided. The diffraction wave is the earthquake response of the small-scale geologic body, contains the structural information of the small-scale geologic body, can be used for accurately positioning the non-uniform discontinuous geologic body, and provides stronger illumination of the underground space. However, compared with the reflected wave, the diffracted wave decays faster in the propagation process, the energy is weaker, and the diffracted wave is easily covered by the reflected wave with strong energy. Therefore, it is necessary to separate the diffracted wave from the reflected wave to enhance the diffraction response, thereby performing high-precision imaging of the diffracted wave and accurately positioning the small-scale geologic body.
At present, the traditional diffraction wave extraction method based on the singular spectrum analysis method needs to preset the rank threshold values of the reflected wave and the diffracted wave, but for complex actual data, the rank threshold values of the reflected wave and the diffracted wave are difficult to preset, so that the applicability of the method is limited, and the separated reflected wave data have leaked diffracted wave signals, so that the high-fidelity extraction of the diffracted wave signals is not facilitated.
Disclosure of Invention
Accordingly, the present invention is directed to a method, apparatus, electronic device and medium for extracting diffracted wave, which are beneficial to high-fidelity extraction of diffracted wave signals.
In order to achieve the above object, the technical scheme adopted by the embodiment of the invention is as follows:
in a first aspect, an embodiment of the present invention provides a diffracted wave extraction method, including: acquiring original seismic data; performing initial wave field separation on the original seismic data to obtain initial diffracted wave data and initial reflected wave data; and optimizing the initial diffracted wave data and the initial reflected wave data based on a least square space optimization algorithm to obtain the separated diffracted wave data and reflected wave data.
In one embodiment, optimizing the initial diffracted wave data and the initial reflected wave data based on a least squares space optimization algorithm to obtain separated diffracted wave data and reflected wave data includes: constructing a least square space optimization function based on the initial diffracted wave data and the initial reflected wave data, and determining a diffracted wave signal extraction factor based on the least square space optimization function; extracting leaked diffracted wave data from the initial reflected wave data based on the diffracted wave signal extraction factor; and calculating the separated diffracted wave data and reflected wave data based on the leaked diffracted wave data, the initial diffracted wave data and the initial reflected wave data.
In one embodiment, constructing a least squares space optimization function based on the initial diffracted wave data and the initial reflected wave data, and determining a diffracted wave signal extraction factor based on the least squares space optimization function, comprises: the least squares space optimization function is constructed according to the following formula:
wherein, wrepresents the diffraction wave signal extraction factor, d d Representing initial diffracted wave data, d r Representing the data of the initial reflected wave,Rrepresenting a regularized smoothing operator;
and determining the optimal solution of the least square space optimization function as a diffracted wave signal extraction factor.
In one embodiment, extracting leaked diffracted wave data from the initial reflected wave data based on the diffracted wave signal extraction factor includes: extracting leaked diffracted wave data from the initial reflected wave data according to the following formula:
wherein d d1 Diffracted wave data representing the leak.
In one embodiment, the separated diffracted wave data and reflected wave data are calculated based on the leaked diffracted wave data, the initial diffracted wave data, and the initial reflected wave data, comprising: superposing the initial diffracted wave data and the leaked diffracted wave data to obtain separated diffracted wave data; and subtracting the initial reflected wave data from the leaked diffracted wave data to obtain separated reflected wave data.
In one embodiment, after optimizing the initial diffracted wave data and the initial reflected wave data based on the least squares space optimization algorithm to obtain the separated diffracted wave data and reflected wave data, the method further includes: and calculating the area similarity coefficient of the separated diffraction wave data and reflection wave data, and evaluating the quality of wave field separation based on the area similarity coefficient.
In one embodiment, calculating the region similarity coefficients of the separated diffracted wave data and reflected wave data includes: region similarity coefficients calculated according to the following formula:
in a second aspect, an embodiment of the present invention provides a diffracted wave extraction apparatus, including: the data acquisition module is used for acquiring original seismic data; the field wave separation module is used for carrying out initial wave field separation on the original seismic data to obtain initial diffracted wave data and initial reflected wave data; and the optimizing module is used for optimizing the initial diffracted wave data and the initial reflected wave data based on a least square space optimizing algorithm to obtain the separated diffracted wave data and reflected wave data.
In a third aspect, an embodiment of the present invention provides an electronic device comprising a processor and a memory storing computer executable instructions executable by the processor to perform the steps of the method of any one of the first aspects described above.
In a fourth aspect, embodiments of the present invention provide a computer readable storage medium having a computer program stored thereon, which when executed by a processor performs the steps of the method of any of the first aspects provided above.
The embodiment of the invention has the following beneficial effects:
the diffracted wave extraction method, the diffracted wave extraction device, the electronic equipment and the medium provided by the embodiment of the invention are characterized in that firstly, original seismic data are obtained; then, carrying out initial wave field separation on the original seismic data to obtain initial diffraction wave data and initial reflection wave data; and finally, optimizing the initial diffracted wave data and the initial reflected wave data based on a least square space optimization algorithm to obtain the separated diffracted wave data and reflected wave data. According to the method, the leaked diffraction wave data in the reflectance data can be recovered to the greatest extent through the least square space optimization algorithm, so that the defects of the existing extraction method are overcome, high-fidelity extraction of diffraction wave signals is facilitated, the accuracy of the wave-surrounding signals is improved, and the accuracy of identifying and positioning abnormal structures in a coal field can be improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for extracting diffracted waves according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for high fidelity diffraction wave extraction according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a diffracted wave extraction device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, the traditional diffraction wave extraction method based on the singular spectrum analysis method needs to preset the rank threshold values of the reflected wave and the diffracted wave, but for complex actual data, the rank threshold values of the reflected wave and the diffracted wave are difficult to preset, so that the applicability of the method is limited, a leaked diffracted wave signal exists in separated reflected wave data, the high-fidelity extraction of the diffracted wave signal is not facilitated, and the recognition and the positioning errors of abnormal structures in a coal field are caused.
Based on the above, the diffracted wave extraction method, the device, the electronic equipment and the medium provided by the embodiment of the invention are beneficial to high-fidelity extraction of the diffracted wave signals and improve the accuracy of the wave-surrounding signals.
For the sake of understanding the present embodiment, a method for extracting diffracted waves disclosed in the present embodiment will be described in detail, and the method may be executed by an electronic device, such as a smart phone, a computer, a tablet computer, and the like. Referring to the flowchart of a diffracted wave extraction method shown in fig. 1, it is shown that the method mainly includes the following steps S101 to S103:
step S101: raw seismic data is acquired.
In one embodiment, post-stack raw seismic data or co-migration domain raw seismic data for the region to be processed may be acquired.
Step S102: and carrying out initial wave field separation on the original seismic data to obtain initial diffracted wave data and initial reflected wave data.
In one embodiment, the original seismic data is subjected to an initial wavefield separation by a conventional singular spectrum analysis method to obtain initial diffracted wave data and initial reflected wave data. Specifically, the initial diffraction wave data and the initial reflection wave data obtained by the singular spectrum analysis method can be expressed as:
wherein d d Representing initial diffracted wave data, d r Representing the initial reflected wave data, d representing the original seismic data, and H representing the singular spectrum analysis operator.
Step S103: and optimizing the initial diffracted wave data and the initial reflected wave data based on a least square space optimization algorithm to obtain the separated diffracted wave data and reflected wave data.
In one embodiment, after obtaining the initial diffracted wave data and the initial reflected wave data, a least squares space optimization function related to the diffracted wave signal extraction factor can be constructed according to the initial diffracted wave data and the initial reflected wave data, and an optimal solution of the least squares space optimization function is solved as the diffracted wave signal extraction factor; and then optimizing the initial diffracted wave data and the initial reflected wave data according to the diffracted wave signal extraction factors, and recovering the leaked diffracted wave signals to obtain finally separated diffracted wave data and reflected wave data.
The diffracted wave extraction method provided by the embodiment of the invention can recover the leaked diffracted wave data in the reflectance data to the greatest extent, thereby overcoming the defects of the existing extraction method, being beneficial to high-fidelity extraction of the diffracted wave signals, improving the accuracy of the wave-surrounding signals and further improving the accuracy of identifying and positioning abnormal structures in coal fields.
In one embodiment, for the step S103, that is, when the initial diffracted wave data and the initial reflected wave data are optimized based on the least squares space optimization algorithm, the separated diffracted wave data and reflected wave data may be used in the following manners, which include but are not limited to:
first, a least squares space optimization function is constructed based on initial diffracted wave data and initial reflected wave data, and a diffracted wave signal extraction factor is determined based on the least squares space optimization function.
In practice, the spatial relationship between reflected and diffracted wave data can be used to construct a least squares spatial optimization function according to the following formula:
wherein, wrepresents the diffraction wave signal extraction factor, d d Representing initial diffracted wave data, d r Representing the data of the initial reflected wave,Rthe regularized smoothing operator is represented to ensure the smoothness and continuity of the solution, and a triangular smoothing operator may be used in this embodiment.
Further, the least square space optimization function is solved, and an optimal solution of the least square space optimization function is determined as a diffracted wave signal extraction factor. Specifically, the optimal solution of the least squares space optimization function is:
wherein, represents a scale parameter related to convergence speed, +.>The triangular smoothing operator is represented as such,Irepresenting the identity matrix.
Then, leaked diffracted wave data is extracted from the initial reflected wave data based on the diffracted wave signal extraction factor.
In practice, the leaked diffracted wave data may be extracted from the initial reflected wave data according to the following formula:
wherein the method comprises the steps of，d d1 Diffracted wave data representing the leak.
Finally, the separated diffracted wave data and reflected wave data are calculated based on the leaked diffracted wave data, the initial diffracted wave data and the initial reflected wave data.
In the specific implementation, the initial diffracted wave data and the leaked diffracted wave data can be overlapped to obtain separated diffracted wave data; and subtracting the initial reflected wave data from the leaked diffracted wave data to obtain separated reflected wave data.
Specifically, the obtained leaked diffraction wave data and the initial diffraction wave data are superimposed, and the initial reflection wave data and the obtained leaked diffraction wave data are subtracted to obtain superimposed diffraction wave data (i.e., separated diffraction wave data) and subtracted reflection wave data (i.e., separated reflection wave data), that is:
wherein d dd Representing superimposed diffraction wave data, d rr Representing the subtracted reflected wave data.
In one embodiment, the purpose of high fidelity separation of diffracted waves is to determine the quality of the field wave separation (i.e., the extraction of diffracted waves) and to determine whether or not the purpose of high fidelity separation of diffracted waves is achieved. In the embodiment of the invention, after the initial diffracted wave data and the initial reflected wave data are optimized based on the least square space optimization algorithm to obtain the separated diffracted wave data and reflected wave data, the method further comprises the following steps: and calculating the area similarity coefficient of the separated diffraction wave data and reflection wave data, and evaluating the quality of wave field separation based on the area similarity coefficient.
In practice, the region similarity coefficient may be calculated according to the following formula:
specifically, the area similarity coefficient is calculated from the separated diffraction wave data and reflection wave datapAnd (5) completing a high-fidelity extraction process of the non-uniform geologic body diffraction waves. Wherein, p 1 、p 2 is the optimal solution of the least square problem. According to the embodiment of the invention, the quality of wave field separation can be evaluated according to the region similarity coefficient, and the smaller the region similarity coefficient is, the higher the quality of the wave field separation is, so that the purpose of high-fidelity separation of diffracted waves is achieved.
In order to facilitate understanding, the embodiment of the present invention further provides a method for extracting diffraction waves with high fidelity, as shown in fig. 2, which mainly includes the following steps S201 to S206:
step S201: and acquiring post-stack or co-offset distance domain seismic data of the region to be processed.
Step S202: and carrying out initialized wave field separation on the seismic data by using a traditional singular spectrum analysis method to obtain initial diffracted wave data and initial reflected wave data.
Step S203: and constructing a least square space optimization function, and calculating a diffraction wave signal extraction factor in the initial reflected wave data.
Step S204: a leaked diffraction wave signal is extracted from the initial reflection wave data using the diffraction wave signal extraction factor.
Step S205: and superposing the extracted leaked diffraction wave signal and the initial diffraction wave data, and subtracting the initial reflection wave data from the extracted leaked diffraction wave signal to obtain superposed diffraction wave data and subtracted reflection wave data.
Step S206: and calculating the area similarity coefficient of the superimposed diffraction wave data and the subtracted reflection wave data to finish the high-fidelity extraction process of the non-uniform geologic body diffraction wave.
According to the method for extracting the diffraction wave of the inhomogeneous geologic body with high fidelity, provided by the embodiment of the invention, the seismic data is subjected to initialization wave field separation based on the traditional singular spectrum analysis method, and the diffraction wave signal extraction factor is constructed by utilizing the local orthogonalization relation between the diffraction wave data and the reflected wave data before and after separation, so that the diffraction wave field signal with high fidelity is obtained. According to the method, the local orthogonalization relation between the diffracted wave data and the reflected wave data is considered, the optimal extraction factor of the leaked diffracted wave can be obtained through the least square optimization framework, the leaked diffracted wave signal is recovered to the greatest extent, the optimal separation of the reflected wave and the diffracted wave is completed, the problem that the diffracted wave and the reflected wave are difficult to separate due to wave field coupling in the traditional method is solved, the purpose of high-fidelity extraction of the diffracted wave of the underground inhomogeneous geologic body is achieved, and the guarantee is provided for identifying and positioning abnormal structures of coal fields.
For the above-mentioned diffracted wave extraction method, the embodiment of the present invention further provides a diffracted wave extraction device, referring to a schematic structural diagram of the diffracted wave extraction device shown in fig. 3, which illustrates that the device mainly includes the following parts:
the data acquisition module 301 is configured to acquire original seismic data.
The wave-field separation module 302 is configured to perform initial wave-field separation on the original seismic data to obtain initial diffracted wave data and initial reflected wave data.
And an optimizing module 303, configured to optimize the initial diffracted wave data and the initial reflected wave data based on a least square space optimization algorithm, so as to obtain the separated diffracted wave data and reflected wave data.
The diffracted wave extraction device provided by the embodiment of the invention can recover the leaked diffracted wave data in the reflectance data to the greatest extent, thereby overcoming the defects of the existing extraction method, being beneficial to high-fidelity extraction of the diffracted wave signals, improving the accuracy of the wave-surrounding signals and further improving the accuracy of identifying and positioning abnormal structures in coal fields.
In one embodiment, the optimizing module 303 is further configured to: constructing a least square space optimization function based on the initial diffracted wave data and the initial reflected wave data, and determining a diffracted wave signal extraction factor based on the least square space optimization function; extracting leaked diffracted wave data from the initial reflected wave data based on the diffracted wave signal extraction factor; and calculating the separated diffracted wave data and reflected wave data based on the leaked diffracted wave data, the initial diffracted wave data and the initial reflected wave data.
In one embodiment, the optimizing module 303 is further configured to: the least squares space optimization function is constructed according to the following formula:
wherein, wrepresents the diffraction wave signal extraction factor, d d Representing initial diffracted wave data, d r Representing the data of the initial reflected wave,Rrepresenting a regularized smoothing operator;
and determining the optimal solution of the least square space optimization function as a diffracted wave signal extraction factor.
In one embodiment, the optimizing module 303 is further configured to: extracting leaked diffracted wave data from the initial reflected wave data according to the following formula:
wherein d d1 Diffracted wave data representing the leak.
In one embodiment, the optimizing module 303 is further configured to: superposing the initial diffracted wave data and the leaked diffracted wave data to obtain separated diffracted wave data; and subtracting the initial reflected wave data from the leaked diffracted wave data to obtain separated reflected wave data.
In one embodiment, the apparatus further includes an evaluation module configured to: and calculating the area similarity coefficient of the separated diffraction wave data and reflection wave data, and evaluating the quality of wave field separation based on the area similarity coefficient.
In one embodiment, the above-mentioned evaluation module is further configured to: region similarity coefficients calculated according to the following formula:
the device provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the foregoing method embodiment, and for the sake of brevity, reference may be made to the corresponding content in the foregoing method embodiment where the device embodiment is not mentioned.
The embodiment of the invention also provides electronic equipment, which comprises a processor and a storage device; the storage means has stored thereon a computer program which, when run by a processor, performs the method according to any of the above embodiments.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 100 includes: a processor 40, a memory 41, a bus 42 and a communication interface 43, the processor 40, the communication interface 43 and the memory 41 being connected by the bus 42; the processor 40 is arranged to execute executable modules, such as computer programs, stored in the memory 41.
The memory 41 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and the at least one other network element is achieved via at least one communication interface 43 (which may be wired or wireless), which may use the internet, a wide area network, a local network, a metropolitan area network, etc.
Bus 42 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 4, but not only one bus or type of bus.
The memory 41 is configured to store a program, and the processor 40 executes the program after receiving an execution instruction, and the method executed by the apparatus for flow defining disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 40 or implemented by the processor 40.
The processor 40 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in processor 40. The processor 40 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 41 and the processor 40 reads the information in the memory 41 and in combination with its hardware performs the steps of the method described above.
The computer program product of the readable storage medium provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where the program code includes instructions for executing the method described in the foregoing method embodiment, and the specific implementation may refer to the foregoing method embodiment and will not be described herein.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A diffracted wave extraction method, comprising:
acquiring original seismic data;
performing initial wave field separation on the original seismic data to obtain initial diffracted wave data and initial reflected wave data; the method comprises the steps of initializing wave field separation for original seismic data by adopting a singular spectrum analysis method;
optimizing the initial diffracted wave data and the initial reflected wave data based on a least square space optimization algorithm to obtain separated diffracted wave data and reflected wave data;
optimizing the initial diffracted wave data and the initial reflected wave data based on a least squares space optimization algorithm to obtain separated diffracted wave data and reflected wave data, including: constructing a least squares space optimization function based on the initial diffracted wave data and the initial reflected wave data, and determining a diffracted wave signal extraction factor based on the least squares space optimization function; extracting leaked diffracted wave data from the initial reflected wave data based on the diffracted wave signal extraction factor; calculating to obtain separated diffracted wave data and reflected wave data based on the leaked diffracted wave data, the initial diffracted wave data and the initial reflected wave data;
constructing a least squares space optimization function based on the initial diffracted wave data and the initial reflected wave data, and determining a diffracted wave signal extraction factor based on the least squares space optimization function, comprising:
the least squares space optimization function is constructed according to the following formula:
wherein, wrepresents the diffraction wave signal extraction factor, d d Representing initial diffracted wave data, d r Representing the data of the initial reflected wave,Rrepresenting a regularized smoothing operator;
determining an optimal solution of the least square space optimization function as a diffracted wave signal extraction factor; wherein the optimal solution of the least squares space optimization function is:
wherein, represents a scale parameter related to convergence speed, +.>The triangular smoothing operator is represented as such,Irepresenting the identity matrix of the cell,diag() The function is used to construct a diagonal matrix and returns diagonal elements on the matrix.
2. The method of claim 1, wherein extracting leaked diffracted wave data from the initial reflected wave data based on the diffracted wave signal extraction factor comprises:
extracting leaked diffracted wave data from the initial reflected wave data according to the following formula:
wherein d d1 Diffracted wave data representing the leak.
3. The method of claim 1, wherein computing separated diffracted wave data and reflected wave data based on the leaked diffracted wave data, the initial diffracted wave data, and the initial reflected wave data comprises:
superposing the initial diffracted wave data and the leaked diffracted wave data to obtain separated diffracted wave data;
and subtracting the initial reflected wave data from the leaked diffracted wave data to obtain separated reflected wave data.
4. The method of claim 1, wherein after optimizing the initial diffracted wave data and the initial reflected wave data based on a least squares space optimization algorithm to obtain separated diffracted wave data and reflected wave data, the method further comprises:
and calculating the area similarity coefficient of the separated diffraction wave data and reflection wave data, and evaluating the quality of wave field separation based on the area similarity coefficient.
5. The method of claim 4, wherein calculating the area similarity coefficients of the separated diffracted wave data and reflected wave data comprises:
region similarity coefficients calculated according to the following formula:
wherein, p 1 、p 2 is the optimal solution of the least square problem.
6. A diffracted wave extraction apparatus, comprising:
the data acquisition module is used for acquiring original seismic data;
the field wave separation module is used for carrying out initial wave field separation on the original seismic data to obtain initial diffracted wave data and initial reflected wave data; the method comprises the steps of initializing wave field separation for original seismic data by adopting a singular spectrum analysis method;
the optimizing module is used for optimizing the initial diffracted wave data and the initial reflected wave data based on a least square space optimizing algorithm to obtain separated diffracted wave data and reflected wave data;
the optimization module is also used for: constructing a least squares space optimization function based on the initial diffracted wave data and the initial reflected wave data, and determining a diffracted wave signal extraction factor based on the least squares space optimization function; extracting leaked diffracted wave data from the initial reflected wave data based on the diffracted wave signal extraction factor; calculating to obtain separated diffracted wave data and reflected wave data based on the leaked diffracted wave data, the initial diffracted wave data and the initial reflected wave data;
the optimization module is also used for: constructing a least squares space optimization function based on the initial diffracted wave data and the initial reflected wave data, and determining a diffracted wave signal extraction factor based on the least squares space optimization function, comprising:
the least squares space optimization function is constructed according to the following formula:
wherein, wrepresents the diffraction wave signal extraction factor, d d Representing initial diffracted wave data, d r Representing the data of the initial reflected wave,Rrepresenting a regularized smoothing operator;
determining an optimal solution of the least square space optimization function as a diffracted wave signal extraction factor; wherein the optimal solution of the least squares space optimization function is:
wherein, represents a scale parameter related to convergence speed, +.>The triangular smoothing operator is represented as such,Irepresenting the identity matrix of the cell,diag() The function is used to construct a diagonal matrix and returns diagonal elements on the matrix.
7. An electronic device comprising a processor and a memory, the memory storing computer executable instructions executable by the processor, the processor executing the computer executable instructions to implement the steps of the method of any one of claims 1 to 5.
8. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor performs the steps of the method of any of the preceding claims 1 to 5.
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| CN113917535A (en) * | 2020-07-09 | 2022-01-11 | 中国石油化工股份有限公司 | Method for suppressing multiple interference, storage medium and computer device |
| CN113945987A (en) * | 2021-10-15 | 2022-01-18 | 中国矿业大学(北京) | Method and device for detecting disease geologic body and electronic equipment |
| CN113945967A (en) * | 2021-10-14 | 2022-01-18 | 中国矿业大学(北京) | Diffraction wave separation method and device |
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| CN113917535A (en) * | 2020-07-09 | 2022-01-11 | 中国石油化工股份有限公司 | Method for suppressing multiple interference, storage medium and computer device |
| CN113640872A (en) * | 2021-08-12 | 2021-11-12 | 中国矿业大学(北京) | Diffracted wave separation method and device and electronic equipment |
| CN113945967A (en) * | 2021-10-14 | 2022-01-18 | 中国矿业大学(北京) | Diffraction wave separation method and device |
| CN113945987A (en) * | 2021-10-15 | 2022-01-18 | 中国矿业大学(北京) | Method and device for detecting disease geologic body and electronic equipment |
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