CN114325818A - Deconvolution method and apparatus - Google Patents
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Abstract
The invention provides a deconvolution method and a device, wherein the method comprises the following steps: collecting sand dune seismic data of a target area; defining an observation system for the sand dune seismic data; performing autocorrelation on the sand dune seismic data based on a seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero-crossing time of each seismic record; obtaining the length of a prediction operator according to the characteristic parameters of the seismic record autocorrelation function; determining a deconvolution prediction step length according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record; and performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length. The invention can suppress the interference of sand dune singing and vibration and has good effect.
Description
Technical Field
The invention relates to the technical field of seismic data processing, in particular to a deconvolution method and a deconvolution device.
Background
With the continuous deepening of seismic exploration, seismic data of high signal-to-noise ratio exploration areas are less and less, exploration areas of complex surface underground structures such as mountain zones, gobi and sand dunes are more and more emphasized, the seismic signal-to-noise ratio of the areas is generally very low, particularly in sand dunes and mountain areas, terrain changes violently, geological outcrops are more, and changes of low-speed-reduction zones are larger. The static correction problem is serious due to the complex geological conditions, and in addition, the phenomenon of ringing is serious in a sand dune area, the signal-to-noise ratio of data is greatly reduced due to the existence of ringing, and effective signals are covered by the ringing.
For the acoustic interference problem, it is originally common to marine seismic data. Aiming at the interference of marine ringing, the prior art provides a deconvolution method, and most of ringing can be eliminated while each main reflected wave waveform is compressed, so as to achieve the effect of suppressing noise; researchers believe that sand dune ringing is an interlayer multiple wave generated by multiple reflection of seismic waves in a sand layer, and as shown in fig. 1, the sand dune ringing generation mechanism is a schematic diagram, so that a Radon transformation method is proposed to eliminate sand dune ringing interference based on Omega software.
The periphery of the Liaohe belongs to a middle-age basin, the geological age is old, the near sources and multiple sources are deposited, the depressed area is small, volcanic rock is extremely developed, the fracture is complex, the structure is broken, and a unique seismic geological condition is formed; the earthquake data collected in the geological environment has serious earthquake shock interference, the earthquake shock generated in the area has the characteristics of low frequency, large energy and obvious periodicity, and the figure 2 is the frequency characteristic of the earthquake shock at the periphery of the Liaohe river. When the sand dune acoustic shock of the area is researched, the periodic variation characteristic of the sand dune acoustic shock is found to be related to the ground surface elevation of the area, namely the elevation of a shot point and a wave detection point, the sand dune acoustic shock period is long in the area with high ground surface elevation, a series of phenomena in the time direction are shown on an earthquake section, and the sand dune acoustic shock period is short when the ground surface elevation is low. Therefore, other methods are needed to suppress the sand hill blast disturbance for this area.
Disclosure of Invention
The embodiment of the invention provides a deconvolution method for suppressing sand dune ringing interference, which has a good effect and comprises the following steps:
collecting sand dune seismic data of a target area;
defining an observation system for the sand dune seismic data;
performing autocorrelation on the sand dune seismic data based on a seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero-crossing time of each seismic record;
obtaining the length of a prediction operator according to the characteristic parameters of the seismic record autocorrelation function;
determining a deconvolution prediction step length according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record;
and performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length.
The embodiment of the invention provides a deconvolution device which is used for suppressing the noise of a sand dune due to a ringing shock and has good effect, and the device comprises:
the data acquisition module is used for acquiring sand dune seismic data of a target area;
the writing module is used for carrying out observation system definition on the sand dune seismic data;
the autocorrelation module is used for performing autocorrelation on the sand dune seismic data based on the seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero-crossing time of each seismic record;
the prediction operator length obtaining module is used for obtaining the length of the prediction operator according to the characteristic parameters of the seismic record autocorrelation function;
the deconvolution prediction step length obtaining module is used for determining a deconvolution prediction step length according to sand dune seismic data defined by the observation system and the first zero-crossing time of each seismic record;
and the deconvolution processing module is used for performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the deconvolution method when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program for executing the deconvolution method.
In the embodiment of the invention, sand dune seismic data of a target area are collected; defining an observation system for the sand dune seismic data; performing autocorrelation on the sand dune seismic data based on a seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero-crossing time of each seismic record; obtaining the length of a prediction operator according to the characteristic parameters of the seismic record autocorrelation function; determining a deconvolution prediction step length according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record; and performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length. In the process, according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record, the deconvolution prediction step length is determined, namely, the deconvolution prediction step length of each channel is changed and is more in line with the actual situation, so that the effect of suppressing sand dune ringing interference after deconvolution processing is better.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a schematic diagram of a mechanism of generation of a sand dune earthquake;
FIG. 2 is the frequency characteristics of the sand dune ringing around the Liaohe river;
FIG. 3 is a flow chart of a deconvolution method in an embodiment of the present invention;
FIG. 4 is a detailed flow chart of a deconvolution method in an embodiment of the present invention;
FIG. 5 is a seismic record in an observation system prior to application of the method of the present invention in an embodiment of the present invention;
FIG. 6 is a seismic record in an observation system after application of the method of the present invention in an embodiment of the present invention;
FIG. 7 is a cross-sectional view of a stack of prior embodiments of the present invention before application of the method of the present invention;
FIG. 8 is an overlaid cross-sectional view after application of the method of the present invention in an embodiment of the present invention;
FIG. 9 is a graph showing frequency comparison before and after applying the method of the present invention in the example of the present invention;
FIG. 10 is a schematic view of a deconvolution device in an embodiment of the present invention;
FIG. 11 is a diagram of a computer device in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are used in an open-ended fashion, i.e., to mean including, but not limited to. Reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in the embodiments is for illustrative purposes to illustrate the implementation of the present application, and the sequence of steps is not limited and can be adjusted as needed.
FIG. 3 is a flow chart of a deconvolution method in an embodiment of the present invention, as shown in FIG. 3, the method comprising:
303, performing autocorrelation on the sand dune seismic data based on a seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero crossing time of each seismic record;
305, determining a deconvolution prediction step length according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record;
and step 306, performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length.
In the embodiment of the invention, the deconvolution prediction step length is determined according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record, namely, the deconvolution prediction step length of each channel is changed and is more suitable for the actual situation, so that the effect of suppressing sand dune ringing interference after deconvolution processing is better.
In step 301, the seismic data of the sand dune in the target area, which are mainly the original seismic data such as the waveform of the seismic waves propagated in the underground, the geodetic coordinates and the relative relationship between the seismic source and the receiving point, are acquired.
In step 302, an observation system definition is performed on the sand dune seismic data, and in an embodiment, before the observation system definition is performed on the sand dune seismic data, the method further includes:
when the sand dune seismic data do not meet the format requirement of the observation system, converting the sand dune seismic data into the sand dune seismic data meeting the format requirement of the observation system;
performing observation system definition on the sand dune seismic data, wherein the observation system definition comprises the following steps:
and defining the observation system for the sand dune seismic data meeting the format requirement of the observation system.
Therefore, correct writing of the sand dune seismic data can be ensured, and the writing success rate is improved. The process of writing sand dune seismic data into an observation system is also referred to as observation system definition, and in one embodiment, the observation system definition of the sand dune seismic data includes:
and writing the elevations of the receiving point and the shot point in the sand dune seismic data which meet the format requirement of the observation system and the static correction values of the receiving point and the shot point into the track head of the observation system.
After the track head of the observation system is accurately written, the method can be directly applied subsequently.
In step 303, performing autocorrelation on the sand dune seismic data based on the seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, and in order to improve the accuracy of autocorrelation, in an embodiment, before performing autocorrelation on the sand dune seismic data based on the seismic record autocorrelation function, the method further includes:
performing static correction processing and denoising processing on the sand dune seismic data to obtain processed sand dune seismic data;
autocorrelation of the sand dune seismic data based on a seismic record autocorrelation function, comprising:
and carrying out autocorrelation on the processed sand dune seismic data based on the seismic record autocorrelation function.
In the above embodiment, besides the static correction processing and the denoising processing, there may be other processing methods, which are all intended to improve the accuracy of autocorrelation, where the autocorrelation function is:
wherein x isijThe seismic record of the jth receiving point of the ith shot point is also called as the ith seismic record;
tau is the time interval and is also a characteristic parameter of the autocorrelation function of the seismic records.
From the autocorrelation function, the first zero-crossing time t of the ith seismic record can be extracted0。
According to the characteristic parameters of the autocorrelation function, multiples of the autocorrelation function can be obtained, a second wave peak value in the autocorrelation function graph is related to the periodic vibration of the signal, and the corresponding second zero crossing time can be used as the length of a predictor.
In particular, the method for determining the deconvolution prediction step size includes two methods.
In one embodiment, determining a deconvolution prediction step size based on the observation system defined sand dune seismic data and the first zero-crossing time of each seismic record comprises:
determining a deconvolution prediction step length according to static correction values of a receiving point and a shot point in an observation system and the first zero-crossing time of each seismic record;
and/or determining a deconvolution predicted step length according to the elevations of a receiving point and a shot point in the observation system and the first zero-crossing time of each seismic record.
In the above embodiment, the following formula is used to determine the deconvolution prediction step length according to the statics correction values of the receiving point and the shot point in the observation system and the first zero-crossing time of each seismic record:
wherein liPredicting a step size for deconvolution of the ith seismic record;
j is 1,2, …, m is the CDP number in the observation system;
n represents the number of tracks in a CDP;
Determining a deconvolution predicted step length according to the elevations of a receiving point and a shot point in an observation system and the first zero-crossing time of each seismic record by adopting the following formula:
wherein,
and (4) the elevations of the receiving point and the shot point of the ith seismic record are shown, and n is the number of the receiving points.
In step 306, based on the predictor length and the deconvolution predictor step size, deconvolution processing is performed as follows:
performing convolution on the length of the prediction operator and sand dune seismic data to obtain a prediction trace;
performing amplitude matching on the prediction trace and the sand dune seismic data based on the deconvolution prediction step length to obtain a prediction trace after amplitude adjustment;
and subtracting the prediction channel after amplitude adjustment from the sand dune seismic data to finish deconvolution processing, thereby achieving the purpose of suppressing the acoustic interference.
Based on the above embodiments, the present invention provides the following embodiments to describe the detailed flow of the deconvolution method, and fig. 4 is a detailed flow chart of the deconvolution method in the embodiments of the present invention, which includes:
and step 410, subtracting the prediction trace after amplitude adjustment from the sand dune seismic data to complete deconvolution processing, thereby achieving the purpose of suppressing the acoustic interference.
Of course, it is understood that other variations of the above detailed flow can be made, and all such variations are intended to fall within the scope of the present invention.
An embodiment is given below to illustrate a specific application of the deconvolution method proposed in the embodiment of the present invention.
Taking a depressed area in the east of Liaohe as an example, fig. 5 is a seismic record in an observation system before the method of the invention is applied in the embodiment of the invention, and fig. 6 is a seismic record in an observation system after the method of the invention is applied in the embodiment of the invention, it can be seen that the sand dune ringing interference on the seismic record before the method of the invention is applied is relatively serious, and after the method of the invention is applied, the sand dune ringing interference is well suppressed, and effective reflection is gradually highlighted. Fig. 7 is a cross-sectional view of the stack before the method of the present invention is applied in the embodiment of the present invention, and fig. 8 is a cross-sectional view of the stack after the method of the present invention is applied in the embodiment of the present invention, it can be seen that noise is very serious in fig. 7, reflection information is covered, interference is well eliminated in fig. 8, reflection information is gradually highlighted, and the signal-to-noise ratio of seismic data is improved after the method of the present invention is applied. Fig. 9 is a frequency comparison graph before and after applying the method of the present invention in the embodiment of the present invention, in which the low frequency part before suppressing the ringing (i.e., before deconvolution processing) has large energy and the effective information is submerged, and the frequency band of the spectrogram after eliminating the ringing (i.e., after deconvolution processing) is widened, which also shows that the noise interference is suppressed well and the data resolution is high after applying the method of the present invention.
In summary, in the method provided by the embodiment of the present invention, sand dune seismic data of a target area are collected; defining an observation system for the sand dune seismic data; performing autocorrelation on the sand dune seismic data based on a seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero-crossing time of each seismic record; obtaining the length of a prediction operator according to the characteristic parameters of the seismic record autocorrelation function; determining a deconvolution prediction step length according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record; and performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length. In the process, according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record, the deconvolution prediction step length is determined, namely, the deconvolution prediction step length of each channel is changed and is more in line with the actual situation, so that the effect of suppressing sand dune ringing interference after deconvolution processing is better.
The embodiment of the present invention further provides a deconvolution device, which has a similar principle to the deconvolution method and is not described herein again.
FIG. 10 is a schematic view of a deconvolution device in an embodiment of the present invention, the device comprising:
the data acquisition module 1001 is used for acquiring sand dune seismic data of a target area;
a writing module 1002, configured to perform observation system definition on the sand dune seismic data;
the autocorrelation module 1003 is configured to perform autocorrelation on the sand dune seismic data based on a seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, where the characteristic parameters include a first zero-crossing time of each seismic record;
a predictor length obtaining module 1004, configured to obtain a predictor length according to a characteristic parameter of the seismic record autocorrelation function;
a deconvolution prediction step length obtaining module 1005, configured to determine a deconvolution prediction step length according to sand dune seismic data defined by the observation system and a first zero-crossing time of each seismic record;
and a deconvolution processing module 1006, configured to perform deconvolution processing based on the predictor length and the deconvolution predictor step size.
In an embodiment, the apparatus further includes a format conversion module 1007 configured to: when the sand dune seismic data do not meet the format requirement of the observation system, converting the sand dune seismic data into the sand dune seismic data meeting the format requirement of the observation system;
the write module 1002 is specifically configured to: and defining the observation system for the sand dune seismic data meeting the format requirement of the observation system.
In an embodiment, the write module 1002 is specifically configured to:
and writing the elevations of the receiving point and the shot point in the sand dune seismic data which meet the format requirement of the observation system and the static correction values of the receiving point and the shot point into the track head of the observation system.
In an embodiment, the deconvolution prediction step size obtaining module 1005 is specifically configured to:
determining a deconvolution prediction step length according to static correction values of a receiving point and a shot point in an observation system and the first zero-crossing time of each seismic record;
and/or determining a deconvolution predicted step length according to the elevations of a receiving point and a shot point in the observation system and the first zero-crossing time of each seismic record.
In an embodiment, the apparatus further comprises a data processing module 1008 for:
performing static correction processing and denoising processing on the sand dune seismic data to obtain processed sand dune seismic data;
the autocorrelation module 1003 is specifically configured to: and carrying out autocorrelation on the processed sand dune seismic data based on the seismic record autocorrelation function.
In summary, in the apparatus provided in the embodiment of the present invention, sand dune seismic data of a target area is collected; defining an observation system for the sand dune seismic data; performing autocorrelation on the sand dune seismic data based on a seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero-crossing time of each seismic record; obtaining the length of a prediction operator according to the characteristic parameters of the seismic record autocorrelation function; determining a deconvolution prediction step length according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record; and performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length. In the process, according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record, the deconvolution prediction step length is determined, namely, the deconvolution prediction step length of each channel is changed and is more in line with the actual situation, so that the effect of suppressing sand dune ringing interference after deconvolution processing is better.
An embodiment of the present application further provides a computer device, and fig. 11 is a schematic diagram of a computer device in an embodiment of the present invention, where the computer device is capable of implementing all steps in the deconvolution method in the foregoing embodiment, and the computer device specifically includes the following contents:
a processor (processor)1101, a memory (memory)1102, a communication Interface (Communications Interface)1103, and a communication bus 1104;
the processor 1101, the memory 1102 and the communication interface 1103 complete mutual communication through the communication bus 1104; the communication interface 1103 is configured to implement information transmission between related devices, such as a server-side device, a detection device, and a client-side device;
the processor 1101 is used to call the computer program in the memory 1102, and the processor executes the computer program to realize all the steps of the deconvolution method in the above-mentioned embodiments.
Embodiments of the present application also provide a computer-readable storage medium, which can implement all the steps in the deconvolution method in the above embodiments, and the computer-readable storage medium stores thereon a computer program, which when executed by a processor implements all the steps of the deconvolution method in the above embodiments.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, 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, 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.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, 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 apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (12)
1. A method of deconvolution, comprising:
collecting sand dune seismic data of a target area;
defining an observation system for the sand dune seismic data;
performing autocorrelation on the sand dune seismic data based on a seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero-crossing time of each seismic record;
obtaining the length of a prediction operator according to the characteristic parameters of the seismic record autocorrelation function;
determining a deconvolution prediction step length according to sand dune seismic data defined by an observation system and the first zero-crossing time of each seismic record;
and performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length.
2. The deconvolution method of claim 1, further comprising, prior to the observation system definition of the sand dune seismic data:
when the sand dune seismic data do not meet the format requirement of the observation system, converting the sand dune seismic data into the sand dune seismic data meeting the format requirement of the observation system;
performing observation system definition on the sand dune seismic data, wherein the observation system definition comprises the following steps:
and defining the observation system for the sand dune seismic data meeting the format requirement of the observation system.
3. The deconvolution method of claim 2 wherein the performing an observation system definition on the sand dune seismic data comprises:
and writing the elevations of the receiving point and the shot point in the sand dune seismic data which meet the format requirement of the observation system and the static correction values of the receiving point and the shot point into the track head of the observation system.
4. The deconvolution method of claim 3 wherein determining a deconvolution prediction step size based on the observation system defined sand dune seismic data and the first zero-crossing time of each seismic record comprises:
determining a deconvolution prediction step length according to static correction values of a receiving point and a shot point in an observation system and the first zero-crossing time of each seismic record;
and/or determining a deconvolution predicted step length according to the elevations of a receiving point and a shot point in the observation system and the first zero-crossing time of each seismic record.
5. The deconvolution method of claim 1, further comprising, prior to auto-correlating the sand dune seismic data based on a seismic record auto-correlation function:
performing static correction processing and denoising processing on the sand dune seismic data to obtain processed sand dune seismic data;
autocorrelation of the sand dune seismic data based on a seismic record autocorrelation function, comprising:
and carrying out autocorrelation on the processed sand dune seismic data based on the seismic record autocorrelation function.
6. A deconvolution device, comprising:
the data acquisition module is used for acquiring sand dune seismic data of a target area;
the writing module is used for carrying out observation system definition on the sand dune seismic data;
the autocorrelation module is used for performing autocorrelation on the sand dune seismic data based on the seismic record autocorrelation function to obtain characteristic parameters of the seismic record autocorrelation function, wherein the characteristic parameters comprise the first zero-crossing time of each seismic record;
the prediction operator length obtaining module is used for obtaining the length of the prediction operator according to the characteristic parameters of the seismic record autocorrelation function;
the deconvolution prediction step length obtaining module is used for determining a deconvolution prediction step length according to sand dune seismic data defined by the observation system and the first zero-crossing time of each seismic record;
and the deconvolution processing module is used for performing deconvolution processing based on the length of the predictor and the deconvolution prediction step length.
7. The deconvolution device of claim 6, further comprising a format conversion module to: when the sand dune seismic data do not meet the format requirement of the observation system, converting the sand dune seismic data into the sand dune seismic data meeting the format requirement of the observation system;
the write module is specifically configured to: and defining the observation system for the sand dune seismic data meeting the format requirement of the observation system.
8. The deconvolution device of claim 7, wherein the write module is specifically configured to:
and writing the elevations of the receiving point and the shot point in the sand dune seismic data which meet the format requirement of the observation system and the static correction values of the receiving point and the shot point into the track head of the observation system.
9. The deconvolution device of claim 8, wherein the deconvolution prediction step-size obtaining module is specifically configured to:
determining a deconvolution prediction step length according to static correction values of a receiving point and a shot point in an observation system and the first zero-crossing time of each seismic record;
and/or determining a deconvolution predicted step length according to the elevations of a receiving point and a shot point in the observation system and the first zero-crossing time of each seismic record.
10. The deconvolution device of claim 6, further comprising a data processing module to:
performing static correction processing and denoising processing on the sand dune seismic data to obtain processed sand dune seismic data;
the autocorrelation module is specifically configured to: and carrying out autocorrelation on the processed sand dune seismic data based on the seismic record autocorrelation function.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 5 when executing the computer program.
12. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 5.
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