CN115639593A - Irregular data reconstruction method and device, electronic equipment and storage medium - Google Patents
Irregular data reconstruction method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application relates to an irregular data reconstruction method, an irregular data reconstruction device, electronic equipment and a storage medium, and belongs to the technical field of geophysical exploration. The method comprises the following steps: by obtaining irregular data; carrying out pre-reconstruction processing on the irregular data to generate first data; preprocessing the first data to generate second data; acquiring a signal-to-noise ratio control factor of the second data; and reconstructing the second data through the signal-to-noise ratio control factor to generate third data. By selecting different reconstruction strategies according to different signal-to-noise ratio regions, irregular seismic data in the compressed sensing exploration technology are reconstructed, the signal-to-noise ratio and the accuracy of the reconstructed irregular acquisition data are improved, and the seismic imaging quality is improved.
Description
Technical Field
The invention relates to the technical field of geophysical exploration, in particular to an irregular data reconstruction method, an irregular data reconstruction device, electronic equipment and a storage medium.
Background
With the acceleration of social development, the oil and gas exploration target is increasingly complicated, and the requirement for seismic data refinement is continuously increased. The high-density seismic data acquisition can meet the sampling requirement of seismic signals, but the production cost is too high, the high-efficiency seismic data acquisition method based on the compressed sensing theory breaks through the limitation of the Nyquist sampling theorem, is an important method for realizing cost reduction and efficiency improvement of seismic acquisition, can promote the rapid development of a synchronous seismic source mixed acquisition technology, and simultaneously drives the development of corresponding data processing and imaging technologies. The compressed sensing technology mainly means that signals with sparse properties are assumed in actually measured data, then the sparse properties are marked by using proper basis functions, and the sparse features can be reflected by the basis functions. The key point of the compressed sensing seismic exploration technology is the reconstruction and recovery of irregular data, and the success or failure of the compressed sensing seismic exploration technology is directly determined by the quality of the reconstruction and recovery of the irregular data.
In the prior art, a commonly used reconstruction technology is a data reconstruction technology based on sparse domain constraint inversion, the technology is based on that data to be processed is sparse or compressible in a certain transformation domain, irregular data are recovered by an optimization method through constructing constraint terms, and the reconstruction precision is high.
However, the existing data reconstruction technology based on sparse domain constraint inversion cannot select different reconstruction strategies according to data with different signal-to-noise ratios.
Disclosure of Invention
In view of the above problems, embodiments of the present invention are proposed to provide an irregular data reconstruction method, apparatus, electronic device and storage medium that overcome or at least partially solve the above problems.
According to a first aspect of the present invention, there is provided an irregular data reconstruction method, comprising:
acquiring irregular data;
carrying out pre-reconstruction processing on the irregular data to generate first data;
preprocessing the first data to generate second data;
acquiring a signal-to-noise ratio control factor of the second data;
and reconstructing the second data through the signal-to-noise ratio control factor to generate third data.
Optionally, the acquiring irregular data includes:
data collected by compressive sensing exploration techniques.
Optionally, the first data comprises: first simulation data and first acquisition data.
Optionally, the preprocessing the first data and generating second data includes:
preprocessing the first data to generate second analog data and second acquisition data;
removing the second analog data to generate second data, wherein the second data is the second acquisition data;
optionally, the acquiring a signal-to-noise ratio control factor of the second data includes:
judging whether the second data meets a preset condition or not, wherein the preset condition comprises that: the method comprises the following steps of A, first preset conditions and second preset conditions, wherein the first preset conditions comprise the condition of meeting seismic migration imaging processing, and the second preset conditions comprise data quality requirements;
if the first preset condition is met, the signal-to-noise ratio control factor is 1;
if the first preset condition is not met, the signal-to-noise ratio control factor is 0;
if the second preset condition is met, acquiring the signal-to-noise ratio of the second data;
when the signal-to-noise ratio of the second data is greater than a preset threshold value, the signal-to-noise ratio control factor is 1;
and when the signal-to-noise ratio of the second data is smaller than a preset threshold value, the signal-to-noise ratio control factor is 0. Optionally, when the signal-to-noise ratio control factor is 1, the method includes: the signal-to-noise ratio of the second data is not changed.
Optionally, when the signal-to-noise ratio control factor is 0, the method includes: and improving the signal-to-noise ratio of the second data.
According to a second aspect of the present invention, there is provided an irregular data reconstruction apparatus, the apparatus comprising:
the first acquisition module is used for acquiring irregular data;
the first processing module is used for carrying out pre-reconstruction processing on the irregular data to generate first data;
the second processing module is used for preprocessing the first data to generate second data;
the second acquisition module is used for acquiring the signal-to-noise ratio control factor of the second data;
and the third processing module is used for reconstructing the second data through the signal-to-noise ratio control factor to generate third data.
According to a third aspect of the present invention, there is provided an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;
a memory for storing a computer program;
and a processor for executing the program stored in the memory.
According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon.
The embodiment of the invention provides a method, a device, electronic equipment and a storage medium for reconstructing irregular data, which are used for reconstructing the irregular data by acquiring the irregular data; carrying out pre-reconstruction processing on the irregular data to generate first data; preprocessing the first data to generate second data; acquiring a signal-to-noise ratio control factor of the second data; and reconstructing the second data through the signal-to-noise ratio control factor to generate third data. The problem of how to select different reconstruction strategies according to data with different signal-to-noise ratios is solved, the irregular seismic data in the compressed sensing exploration technology are reconstructed by increasing the signal-to-noise ratio control factors and selecting different reconstruction strategies according to different signal-to-noise ratio areas, the signal-to-noise ratio and the accuracy of the reconstructed irregular acquisition data are improved, and the seismic imaging quality is improved. The method optimizes the reconstruction process of the irregular seismic data, selects different reconstruction strategies according to different signal-to-noise ratio regions, and improves the signal-to-noise ratio and the fidelity of the data.
The above description is only an overview of the technical solutions of the present invention, and the present invention can be implemented in accordance with the content of the description so as to make the technical means of the present invention more clearly understood, and the above and other objects, features, and advantages of the present invention will be more clearly understood.
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 refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart of an irregular data reconstruction method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an irregular data reconstruction apparatus according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an electronic device provided by an embodiment of the invention;
FIG. 4 is a schematic diagram of a storage medium provided by an embodiment of the invention;
fig. 5 is a flowchart of another irregular data reconstruction method according to an 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 invention are shown in the drawings, it should be understood that the invention can 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.
The terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application may be practiced in sequences other than those illustrated or described herein, and that the terms "first," "second," and the like are generally used herein in a generic sense and do not limit the number of terms, e.g., the first term can be one or more than one. In addition, "and/or" in the specification and claims means at least one of connected objects, a character "/" generally means that a preceding and succeeding related objects are in an "or" relationship.
The method, the apparatus, the electronic device, and the storage medium for irregular data reconstruction provided by the embodiments of the present application are described in detail with reference to the accompanying drawings.
The first embodiment of the present invention relates to a method for irregular data reconstruction, a flowchart of which is shown in fig. 1, and the method comprises the following steps:
In the present embodiment, the irregular data specifically refers to irregular seismic data acquired by a compressive sensing survey technique in seismic exploration.
For seismic exploration in some complex regions, cliff, river, ravine, village, industrial area and the like are often encountered, so that detectors cannot be easily or even cannot be arranged, and thus certain difficulty or even no acquisition is brought to data acquisition, or in order to reduce cost, detectors need to be reduced in space, and therefore, the acquired irregular data needs to be processed in step 102.
And 102, carrying out pre-reconstruction processing on the irregular data to generate first data.
It should be noted that, in the present embodiment, the irregular data is subjected to pre-reconstruction, that is, pre-reconstruction in the present application is to complete missing data in the irregular seismic data acquired by the compressed sensing exploration technology due to various reasons by using a reconstruction technology in the prior art, and a result of the first data that is not required to be generated by pre-processing the original irregular data is very accurate, and the operation of this step is favorable for performing some pre-stack pre-processing before final reconstruction by using the reconstruction technology in the present application, such as denoising, static correction, amplitude compensation, and the like.
It should be noted that, in the pre-reconstruction process in the present application, a conventional interpolation technique may be selected, for example, a reconstruction technique of an inversion class may also be selected, and the present application is not limited in particular.
It should be noted that, in this embodiment, the first data is generated by performing pre-reconstruction processing on the acquired irregular seismic data in step 102, where the first data includes first simulation data and first acquired data, the first acquired data refers to seismic data actually acquired in a seismic exploration process, the first simulation data refers to when no more denser sampling points can be acquired due to geological factors or human factors in the seismic exploration process, a null 0 is artificially placed on the acquired actual data, a missing part of the irregular data (where the null 0 exists) is restored by using an existing reconstruction technique in step 102 to obtain complete first data (regular data), and then the first data is pre-processed, where the pre-processing includes, but is not limited to, techniques such as denoising, static correction, amplitude compensation, deconvolution, and the like, and this application is not limited in particular.
Further, as shown in fig. 5, the preprocessing the first data in step 103, and generating the second data includes:
It should be noted that the first data is preprocessed, and the first data includes the first simulation data and the first collected data, which have been already described in the above step 103, so that the preprocessed data generates the corresponding second simulation data and second collected data.
And 1032, removing the second simulation data to generate second data, wherein the second data is second acquired data.
It should be noted that, in the embodiment of the present application, the second data is second acquired data, and is second analog data generated by removing the first data and performing preprocessing, that is, a processing result of data that is not actually acquired.
And 104, acquiring a signal-to-noise ratio control factor of the second data.
Further, as shown in fig. 5, acquiring the signal-to-noise ratio control factor of the second data includes:
It should be noted that, for the signal-to-noise ratio control factor, the value is determined to be 0 or 1 according to whether the subsequent seismic migration imaging processing and the data quality requirement of the second party are met, and a corresponding value is obtained as long as any preset condition in the preset conditions is met.
1042, if the first preset condition is met, the signal-to-noise ratio control factor is 1; if the first preset condition is not met, the signal-to-noise ratio control factor is 0;
it should be noted that if the first preset condition is met, that is, the subsequent seismic migration imaging processing is met, at this time, the signal-to-noise ratio of the second data is higher, a strategy of retaining the original data is adopted, and the value of the signal-to-noise ratio control factor is 1; if the first preset condition is not met, namely the subsequent seismic migration imaging processing is not met, the signal-to-noise ratio of the second data is low, the signal-to-noise ratio of the second data needs to be improved, and the value of a signal-to-noise ratio control factor is 0.
It should be noted that, a relationship between the signal-to-noise ratio of the second data and a preset threshold is determined, where the preset threshold is defined according to a data quality requirement of the second party (party a), and different second parties (party a) may determine different thresholds in specific implementation, so the present application is not limited specifically.
And 105, reconstructing the second data through the signal-to-noise ratio control factor to generate third data.
It should be noted that, in a general case, the reconstruction problem of irregular data can be expressed as:
d obs = Md (equation 1)
Wherein d is obs Representing the collected irregular data, M representing an irregular sampling operator, and d representing the completely collected data.
Equation 1 can be solved by a least squares optimization method to obtain:
wherein R represents a regularization constraint term,
representL 2 And (5) molding.
Solving the general solution of equation 2 using a sparse domain iterative thresholding method is represented as:
d n+1 ＝ST λ S H {d n +d obs -Md n } (formula 3)
Wherein, d n Representing the result of the nth iteration, S represents sparse transformation, and can be selected from Fourier transformation, wavelet transformation, curvelet transformation, shearlet transformation and the like, and S represents H Representing the inverse transform corresponding thereto, S representing a threshold function, typically a hard threshold function or a soft threshold function; t is λ Representing a set constraint threshold, defined by the user.
However, the above reconstruction method cannot select different reconstruction strategies according to different snr regions, and thus the snr control factor α in step 104 is increased.
The above formula 3 is optimized by increasing the signal-to-noise ratio control factor α, and the improved reconstruction formula is shown in formula 4:
d n+1 ＝αd obs +(I-αM)ST λ S H {[I-(1-α)M]d n +(1-α)d obs } (formula 4)
In the above formula 4, α is the snr control factor, I represents the identity matrix, S is selected as the curvelet transform in the embodiment of the present application, and T is selected in the present application λ For the soft threshold function, λ is selected as the adaptive attenuation threshold, and λ k ＝τ k,max (1-a (N+1-k) ) Denotes a threshold selected in the kth iteration, k =1 k,max The largest sparse coefficient in the sparse domain is the kth iteration data.
Further, the signal-to-noise ratio control factor α in step 104 is determined, the second data is reconstructed by the optimized formula 4, and a final reconstruction result is output and used for subsequent seismic migration image processing, where the seismic migration image processing is not specifically limited in the present application.
In the method for reconstructing irregular data provided in this embodiment, the irregular data is obtained; carrying out pre-reconstruction processing on the irregular data to generate first data; preprocessing the first data to generate second data; acquiring a signal-to-noise ratio control factor of the second data; and reconstructing the second data through the signal-to-noise ratio control factor to generate third data. The problem of how to select different reconstruction strategies according to the data with different signal-to-noise ratios is solved, the reconstruction technology of the irregular seismic data is optimized by increasing the signal-to-noise ratio control factors, different reconstruction strategies are selected according to different signal-to-noise ratio areas, the irregular seismic data in the compressed sensing exploration technology is reconstructed, the signal-to-noise ratio and the accuracy of the reconstructed irregular acquisition data are improved, and the seismic imaging quality is improved. According to the method and the device, the irregular seismic data reconstruction process is optimized, different reconstruction strategies are selected according to different signal-to-noise ratio areas, the signal-to-noise ratio of the original data is improved while the missing data is reconstructed, the main structural form of the original data can be well recovered after reconstruction, the recovered signal and the original data have higher goodness of fit, the noise immunity is better, and the fidelity of the data is improved while the signal-to-noise ratio is improved.
A second embodiment of the present invention relates to an irregular data reconstruction apparatus 200, which may specifically include, as described with reference to fig. 2:
a first obtaining module 201, configured to obtain irregular data;
a first processing module 202, configured to perform pre-reconstruction processing on the irregular data to generate first data;
the second processing module 203 is configured to perform preprocessing on the first data to generate second data;
a second obtaining module 204, configured to obtain a signal-to-noise ratio control factor of the second data;
the third processing module 205 performs reconstruction processing on the second data through the snr control factor to generate third data.
For the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and reference may be made to the partial description of the method embodiment for relevant points.
Further, based on the same inventive concept, an electronic device 300 is further provided in the embodiment of the present application, as shown in fig. 3, and includes a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and capable of running on the processor 320, where the processor 320 executes the computer program 311 to implement the following steps:
acquiring irregular data;
carrying out pre-reconstruction processing on the irregular data to generate first data;
preprocessing the first data to generate second data;
acquiring a signal-to-noise ratio control factor of the second data;
and reconstructing the second data through the signal-to-noise ratio control factor to generate third data.
Based on the same inventive concept, in the specific embodiment of the present application, when the processor 320 executes the computer program 311, any embodiment of the method of the embodiment of the present invention may be implemented.
Since the electronic device described in the embodiment of the present application is a device used for implementing the method according to the embodiment of the present invention, a person skilled in the art can understand the specific structure and the deformation of the device based on the method described in the embodiment of the present invention, and thus the details are not described herein. All the devices adopted by the method of the embodiment of the invention belong to the protection scope of the invention.
Based on the same inventive concept, the specific embodiment of the present application further provides a storage medium corresponding to the method in the embodiment: the present embodiment provides a computer-readable storage medium 400, as shown in fig. 4, on which a computer program 411 is stored, the computer program 411 implementing the following steps when executed by a processor:
acquiring irregular data;
carrying out pre-reconstruction processing on the irregular data to generate first data;
preprocessing the first data to generate second data;
acquiring a signal-to-noise ratio control factor of the second data;
and reconstructing the second data through the signal-to-noise ratio control factor to generate third data.
In a specific implementation process, when being executed by a processor, the computer program 411 may implement any one of the methods of the specific embodiments of the present application.
The technical scheme provided in the specific embodiment of the application at least has the following technical effects or advantages:
in the irregular data reconstructing apparatus provided in this embodiment, the irregular data is obtained; carrying out pre-reconstruction processing on the irregular data to generate first data; preprocessing the first data to generate second data; acquiring a signal-to-noise ratio control factor of the second data; and reconstructing the second data through the signal-to-noise ratio control factor to generate third data. The problem of how to select different reconstruction strategies according to the data with different signal-to-noise ratios is solved, the reconstruction technology of the irregular seismic data is optimized by increasing the signal-to-noise ratio control factors, different reconstruction strategies are selected according to different signal-to-noise ratio areas, the irregular seismic data in the compressed sensing exploration technology is reconstructed, the signal-to-noise ratio and the accuracy of the reconstructed irregular acquisition data are improved, and the seismic imaging quality is improved. According to the method and the device, the irregular seismic data reconstruction process is optimized, different reconstruction strategies are selected according to different signal-to-noise ratio areas, the signal-to-noise ratio of the original data is improved while the missing data is reconstructed, the main structural form of the original data can be well recovered after reconstruction, the recovered signal and the original data have higher goodness of fit, the noise immunity is better, and the fidelity of the data is improved while the signal-to-noise ratio is improved.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
It will be appreciated by those skilled in the art that embodiments of the invention may be provided as methods, apparatus, storable medium and processors. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
In a typical configuration, the computer device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The memory 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 non-transitory computer readable media (fransitory media), such as modulated data signals and carrier waves.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "include", "including" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or terminal device including a series of elements includes not only those elements but also other elements not explicitly listed or inherent to such process, method, article, or terminal device. Without further limitation, an element defined by the phrases "comprising one of \ 8230; \8230;" does not exclude the presence of additional like elements in a process, method, article, or terminal device that comprises the element.
The irregular data reconstruction method, the irregular data reconstruction device, the electronic device and the storage medium provided by the invention are described in detail above, and a specific example is applied in the text to explain the principle and the implementation of the invention, and the description of the above embodiment is only used to help understanding the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A method for irregular data reconstruction, the method comprising:
acquiring irregular data;
carrying out pre-reconstruction processing on the irregular data to generate first data;
preprocessing the first data to generate second data;
acquiring a signal-to-noise ratio control factor of the second data;
and reconstructing the second data through the signal-to-noise ratio control factor to generate third data.
2. The method of claim 1, wherein the obtaining irregular data comprises:
seismic data acquired by compressive sensing exploration techniques.
3. The method of claim 1, wherein the first data comprises: first simulation data and first acquisition data.
4. The method of claim 1, wherein preprocessing the first data to generate second data comprises:
preprocessing the first data to generate second analog data and second acquisition data;
and removing the second analog data to generate second data, wherein the second data is the second acquisition data.
5. The method of claim 1, wherein obtaining the signal-to-noise ratio control factor of the second data comprises:
judging whether the second data meet preset conditions or not, wherein the preset conditions comprise: the method comprises the following steps of A, a first preset condition and a second preset condition, wherein the first preset condition comprises the condition of meeting seismic migration imaging processing, and the second preset condition comprises a data quality requirement;
if the first preset condition is met, the signal-to-noise ratio control factor is 1;
if the first preset condition is not met, the signal-to-noise ratio control factor is 0;
if the second preset condition is met, acquiring the signal-to-noise ratio of the second data;
when the signal-to-noise ratio of the second data is greater than a preset threshold value, the signal-to-noise ratio control factor is 1;
and when the signal-to-noise ratio of the second data is smaller than a preset threshold value, the signal-to-noise ratio control factor is 0.
6. The method of claim 5, wherein the SNR control factor is 1, comprising: the signal-to-noise ratio of the second data is not changed.
7. The method of claim 5, wherein the SNR control factor is 0, comprising: improving the signal-to-noise ratio of the second data.
8. An irregular data reconstruction apparatus, comprising:
the first acquisition module is used for acquiring irregular data;
the first processing module is used for carrying out pre-reconstruction processing on the irregular data to generate first data;
the second processing module is used for preprocessing the first data to generate second data;
the second acquisition module is used for acquiring the signal-to-noise ratio control factor of the second data;
and the third processing module is used for reconstructing the second data through the signal-to-noise ratio control factor to generate third data.
9. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method of any one of claims 1 to 7 when executing a program stored in the memory.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of digital conversion according to any one of claims 1 to 7.
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