High-dimensional pre-stack seismic data filtering method and device
阅读说明：本技术 一种高维叠前地震数据滤波方法及装置 (High-dimensional pre-stack seismic data filtering method and device ) 是由 曹中林 李亚林 李乐 熊定钰 王光银 张华� 于 2021-03-08 设计创作，主要内容包括：本发明提供了一种高维叠前地震数据滤波方法及装置,包括：根据获取的地震数据构建叠前三维共中点道集数据；获取叠前三维共中点道集数据中的最大主测线号、最小主测线号、最大交叉测线号、最小交叉测线号和最大道数；根据最大主测线号、最小主测线号、最大交叉测线号和最小交叉测线号填补叠前三维共中点道集数据中的交叉测线道集,生成叠前三维数据体；通过预设的窗口将叠前三维数据体分割成若干个窗口数据；对窗口数据进行小波变换获得滤波后的叠前三维数据体。本申请可以较好地对随机噪声进行衰减并能够很好地保持叠前道集中的剩余静校正量,与剩余静校正处理技术相结合,有助于提高剩余静校正量估算的精度,保护信号的高频成分。(The invention provides a high-dimensional pre-stack seismic data filtering method and device, which comprises the following steps: constructing prestack three-dimensional common midpoint channel set data according to the acquired seismic data; acquiring a maximum main survey line number, a minimum main survey line number, a maximum cross survey line number, a minimum cross survey line number and a maximum track number in pre-stack three-dimensional common midpoint track set data; filling a cross survey line gather in the pre-stack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number and the minimum cross survey line number to generate a pre-stack three-dimensional data body; dividing the prestack three-dimensional data volume into a plurality of window data through a preset window; and performing wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume. The method and the device can better attenuate random noise and well keep the residual static correction value concentrated in the pre-stack channel, and are combined with the residual static correction processing technology, so that the method and the device are favorable for improving the estimation precision of the residual static correction value and protecting the high-frequency component of the signal.)
1. A method for filtering high-dimensional pre-stack seismic data, comprising:
constructing prestack three-dimensional common midpoint channel set data according to the acquired seismic data;
acquiring a maximum main survey line number, a minimum main survey line number, a maximum cross survey line number, a minimum cross survey line number and a maximum track number in the pre-stack three-dimensional common midpoint track set data;
filling a cross survey line gather in the pre-stack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number and the minimum cross survey line number to generate a pre-stack three-dimensional data body;
dividing the prestack three-dimensional data volume into a plurality of window data through a preset window;
and performing wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume.
2. The method of high-dimensional pre-stack seismic data filtering according to claim 1, wherein said filling cross-line gathers in pre-stack three-dimensional common midpoint gather data according to the maximum master line number, the minimum master line number, the maximum cross-line number, and the minimum cross-line number, generating a pre-stack three-dimensional data volume, comprises:
filling empty channels for the crossed measuring line numbers missing from each main measuring line according to the maximum crossed measuring line number and the minimum crossed measuring line number;
and counting the total track number of each cross survey line gather, and if the total track number is less than the maximum track number, completing the total track number to ensure that the total track number is equal to the maximum track number.
3. The method for filtering high-dimensional pre-stack seismic data according to claim 1, wherein constructing pre-stack three-dimensional common midpoint gather data from the acquired seismic data comprises:
screening an X axis of the pre-stack three-dimensional common midpoint gather data of the seismic channel structure along the same main survey line direction from the obtained seismic data;
screening seismic channels along the same cross survey line direction from the acquired seismic data to form a Y axis of pre-stack three-dimensional common midpoint channel set data;
and taking the time direction of the seismic data as the Z axis of the prestack three-dimensional common midpoint gather data.
4. The method of filtering high dimensional pre-stack seismic data according to claim 1, wherein said segmenting the pre-stack three dimensional data volume into a number of window data by a preset window comprises:
and traversing the pre-stack three-dimensional data volume by using a preset window in a rolling manner, wherein the traversed pre-stack three-dimensional data volume is divided into a plurality of window data.
5. The method of filtering high dimensional pre-stack seismic data according to claim 4, wherein said wavelet transforming said windowed data to obtain a filtered pre-stack three dimensional data volume comprises:
performing wavelet transformation on each channel of data in the window data along the Z-axis direction to obtain a wavelet coefficient;
performing wavelet transformation on the window data according to the wavelet coefficient to obtain a data volume;
taking a corresponding relative data volume from the data volume according to a set scale;
generating a high-dimensional matrix according to the relative data volume;
performing singular value decomposition on the high-dimensional matrix to obtain a new data volume;
and deleting all seismic channels with the new data body channel head flags of 0 to obtain the filtered prestack three-dimensional data body.
6. A high dimensional pre-stack seismic data filtering apparatus, comprising:
the system comprises a trace set data construction unit, a pre-stack three-dimensional common midpoint trace set data acquisition unit and a pre-stack three-dimensional common midpoint trace set data acquisition unit, wherein the trace set data acquisition unit is used for acquiring seismic data;
the acquisition unit is used for acquiring the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number, the minimum cross survey line number and the maximum track number in the pre-stack three-dimensional common midpoint track set data;
the pre-stack three-dimensional data body generating unit is used for filling up cross survey line gathers in the pre-stack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number and the minimum cross survey line number to generate a pre-stack three-dimensional data body;
the window segmentation unit is used for segmenting the prestack three-dimensional data volume into a plurality of window data through a preset window;
and the wavelet transformation unit is used for performing wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume.
7. The high dimensional pre-stack seismic data filtering apparatus of claim 6, wherein the acquisition unit comprises:
the first empty channel filling module is used for filling empty channels for the cross measuring line numbers missing from each main measuring line according to the maximum cross measuring line number and the minimum cross measuring line number;
and the second empty channel filling module is used for counting the total channel number of each cross survey line channel set, and filling the total channel number to enable the total channel number to be equal to the maximum channel number if the total channel number is less than the maximum channel number.
8. The high-dimensional pre-stack seismic data filtering apparatus of claim 6, wherein the gather data construction unit comprises:
the X-axis construction module is used for screening the X-axis of the pre-stack three-dimensional common midpoint gather data of the seismic channel structure along the same main survey line direction from the acquired seismic data;
the Y-axis construction module is used for screening seismic channels along the same cross survey line direction from the acquired seismic data to form a Y axis of pre-stack three-dimensional common midpoint channel set data;
and the Z-axis construction module is used for taking the time direction of the seismic data as the Z axis of the prestack three-dimensional common midpoint gather data.
9. The high-dimensional pre-stack seismic data filtering apparatus according to claim 6, wherein the window splitting unit includes:
and the dividing module is used for traversing the pre-stack three-dimensional data volume by utilizing a preset window in a rolling manner, and dividing the traversed pre-stack three-dimensional data volume into a plurality of window data.
10. The high-dimensional pre-stack seismic data filtering apparatus according to claim 9, wherein the wavelet transform unit includes:
the wavelet coefficient acquisition module is used for performing wavelet transformation on each channel of data in the window data along the Z-axis direction to obtain a wavelet coefficient;
the data volume acquisition module is used for performing wavelet transformation on the window data according to the wavelet coefficients to obtain a data volume;
the relative data volume acquisition module is used for acquiring a corresponding relative data volume from the data volume according to a set scale;
the high-dimensional matrix generating module is used for generating a high-dimensional matrix according to the relative data volume;
the singular value decomposition module is used for carrying out singular value decomposition on the high-dimensional matrix to obtain a new data volume;
and the eliminating module is used for deleting all seismic channels with the new data body channel head flag number of 0 to obtain the filtered prestack three-dimensional data body.
11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the high-dimensional pre-stack seismic data filtering method according to any of claims 1 to 5 are implemented by the processor when executing the program.
12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the high dimensional pre-stack seismic data filtering method according to any one of claims 1 to 5.
Technical Field
The application belongs to the technical field of seismic exploration, and particularly relates to a high-dimensional pre-stack seismic data filtering method and device.
Background
Random noise is inevitable noise in seismic exploration, which not only reduces the signal-to-noise ratio of seismic data, but also directly affects the accuracy of dynamic and static correction. The problem of pre-stack random noise suppression is a difficult problem in seismic signal processing: on one hand, with the deep exploration, the quality of deep seismic data is required to be higher, and the problem of low signal-to-noise ratio of the deep seismic data is the result of the combined action of random noise and effective signal energy attenuation; on the other hand, the current oil and gas exploration target has been changed into 'two width and one height', and a more severe processing efficiency problem is provided for a random noise suppression method by a larger-scale data volume; in addition, the artificial seismic data are time-space-variant in nature, and the characteristics such as energy, trajectory, time frequency spectrum and the like of the seismic event change along with different time and space positions, so that the traditional random noise processing method is difficult to adapt to the time-varying characteristics of the actual effective signals. Therefore, developing a fast and effective random noise attenuation processing method is still one of the core problems that need to be solved urgently in the current artificial seismic exploration data processing.
Disclosure of Invention
The application provides a high-dimensional pre-stack seismic data filtering method and device, which are used for at least solving the problem that a random noise processing method during current seismic data acquisition is difficult to adapt to time-varying characteristics of actual effective signals.
According to one aspect of the application, there is provided a method of filtering high-dimensional pre-stack seismic data, comprising:
constructing prestack three-dimensional common midpoint channel set data according to the acquired seismic data;
acquiring a maximum main survey line number, a minimum main survey line number, a maximum cross survey line number, a minimum cross survey line number and a maximum track number in pre-stack three-dimensional common midpoint track set data;
filling a cross survey line gather in the pre-stack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number and the minimum cross survey line number to generate a pre-stack three-dimensional data body;
dividing the prestack three-dimensional data volume into a plurality of window data through a preset window;
and performing wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume.
In one embodiment, filling a cross-line survey gather in the prestack three-dimensional common midpoint gather data according to the maximum master line number, the minimum master line number, the maximum cross-line survey number, and the minimum cross-line survey number to generate a prestack three-dimensional data volume, including:
filling empty channels for the crossed measuring line numbers missing from each main measuring line according to the maximum crossed measuring line number and the minimum crossed measuring line number;
and counting the total track number of each cross survey line gather, and if the total track number is less than the maximum track number, filling the total track number to ensure that the total track number is equal to the maximum track number.
In one embodiment, constructing prestack three-dimensional common midpoint gather data from acquired seismic data comprises:
screening an X axis of the pre-stack three-dimensional common midpoint gather data of the seismic channel structure along the same main survey line direction from the obtained seismic data;
screening seismic channels along the same cross survey line direction from the acquired seismic data to form a Y axis of pre-stack three-dimensional common midpoint channel set data;
and taking the time direction of the seismic data as the Z axis of the prestack three-dimensional common midpoint gather data.
In one embodiment, the segmenting the prestack three-dimensional data volume into a plurality of window data through a preset window includes:
and traversing the pre-stack three-dimensional data volume by using a preset window in a rolling manner, wherein the traversed pre-stack three-dimensional data volume is divided into a plurality of window data.
In one embodiment, wavelet transforming the window data to obtain a filtered prestack three-dimensional data volume includes:
performing wavelet transformation on each channel of data in the window data along the Z-axis direction to obtain wavelet coefficients;
performing wavelet transformation on the window data according to the wavelet coefficients to obtain a data volume;
taking a corresponding relative data volume from the data volume according to a set scale;
generating a high-dimensional matrix according to the relative data volume;
performing singular value decomposition on the high-dimensional matrix to obtain a new data volume;
and deleting all seismic channels with the new data body channel head flags of 0 to obtain the filtered prestack three-dimensional data body.
According to another aspect of the present application, there is also provided a high-dimensional pre-stack seismic data filtering apparatus, comprising:
the system comprises a trace set data construction unit, a pre-stack three-dimensional common midpoint trace set data acquisition unit and a pre-stack three-dimensional common midpoint trace set data acquisition unit, wherein the trace set data acquisition unit is used for acquiring seismic data;
the acquisition unit is used for acquiring the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number, the minimum cross survey line number and the maximum track number in the pre-stack three-dimensional common midpoint track set data;
the pre-stack three-dimensional data body generating unit is used for filling a cross survey line gather in the pre-stack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number and the minimum cross survey line number to generate a pre-stack three-dimensional data body;
the window segmentation unit is used for segmenting the prestack three-dimensional data volume into a plurality of window data through a preset window;
and the wavelet transformation unit is used for performing wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume.
In one embodiment, the acquisition unit includes:
the first empty channel filling module is used for filling empty channels for the crossed measuring line numbers missing from each main measuring line according to the maximum crossed measuring line number and the minimum crossed measuring line number;
and the second empty channel filling module is used for counting the total channel number of each cross survey line channel set, and filling the total channel number to ensure that the total channel number is equal to the maximum channel number if the total channel number is less than the maximum channel number.
In one embodiment, the gather data construction unit includes:
the X-axis construction module is used for screening the X-axis of the pre-stack three-dimensional common midpoint gather data of the seismic channel structure along the same main survey line direction from the acquired seismic data;
the Y-axis construction module is used for screening seismic channels along the same cross survey line direction from the acquired seismic data to form a Y axis of pre-stack three-dimensional common midpoint channel set data;
and the Z-axis construction module is used for taking the time direction of the seismic data as the Z axis of the prestack three-dimensional common midpoint gather data.
In one embodiment, the window splitting unit includes:
and the dividing module is used for traversing the pre-stack three-dimensional data volume by utilizing a preset window in a rolling manner, and dividing the traversed pre-stack three-dimensional data volume into a plurality of window data.
In one embodiment, a wavelet transform unit includes:
the wavelet coefficient acquisition module is used for performing wavelet transformation on each channel of data in the window data along the Z-axis direction to obtain a wavelet coefficient;
the data volume acquisition module is used for performing wavelet transformation on the window data according to the wavelet coefficients to obtain a data volume;
the relative data volume acquisition module is used for acquiring a corresponding relative data volume from the data volume according to a set scale;
the high-dimensional matrix generation module is used for generating a high-dimensional matrix according to the relative data volume;
the singular value decomposition module is used for carrying out singular value decomposition on the high-dimensional matrix to obtain a new data body;
and the eliminating module is used for deleting all seismic channels with the new data body channel head flag number of 0 to obtain the filtered prestack three-dimensional data body.
The method is operated on a prestack three-dimensional common midpoint gather, firstly, aiming at an irregular prestack three-dimensional common midpoint gather, a regular prestack three-dimensional data body is formed by adopting a method of filling empty channels according to the minimum and maximum CMP numbers in an observation system and the maximum number of CMP gathers, on the basis, the prestack three-dimensional data body is divided into a plurality of window data according to a certain method, wavelet transformation is carried out on each window data in sequence, each slice data is taken to construct a high-dimensional matrix, singular value decomposition is operated, the matrix is reconstructed, wavelet inverse transformation is carried out after all slice data are processed, thereby finally realizing the suppression of random noise in the prestack three-dimensional gather, the method can better attenuate the random noise and well keep the residual static correction value in the prestack gather, and is combined with the residual static correction processing technology to help to improve the estimation precision of the residual static correction value, the high frequency components of the signal are protected.
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.
Fig. 1 is a flow chart of a high-dimensional pre-stack seismic data filtering method provided by the present application.
Fig. 2 is a flowchart of a method for generating a prestack three-dimensional data volume in an embodiment of the present application.
FIG. 3 is a flowchart of a method for constructing prestack three-dimensional common midpoint gather data from acquired seismic data according to an embodiment of the present application.
Fig. 4 is a flowchart of a method for performing wavelet transform on window data to obtain a filtered prestack three-dimensional data volume in an embodiment of the present application.
Fig. 5 is a block diagram of a high-dimensional pre-stack seismic data filtering apparatus according to the present application.
Fig. 6 is a block diagram of a structure of an acquisition unit in the embodiment of the present application.
FIG. 7 is a block diagram illustrating a structure of a gather data construction unit according to an embodiment of the present invention.
Fig. 8 is a block diagram of a wavelet transform unit in the embodiment of the present application.
FIG. 9A is an original view of a prestack three-dimensional gather in an embodiment of the present application.
FIG. 9B is a schematic diagram of a prestack three-dimensional gather after random noise suppression in an embodiment of the present application.
FIG. 9C is a schematic diagram of another pre-stack three-dimensional gather after random noise suppression according to an embodiment of the present application.
Fig. 10 is a specific implementation of an electronic device in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Many correlation techniques such as median filtering, polynomial fitting, frequency space prediction filtering and the like are proposed at present for the attenuation of random noise, but most of the methods are developed based on a post-stack data model, so that a satisfactory result can be obtained in post-stack application. Although some methods can be popularized and applied before stacking, the application effect is greatly restricted due to the limitation of theoretical basis or mathematical assumed conditions. Such as frequency prediction, median filtering and the like are effective in suppressing random noise, but because they are all based on a multi-channel mathematical model, certain requirements are imposed on the linearity, coherence and the like of signals between channels, and there are certain problems when they are directly used for prestack processing, especially when the signal-to-noise ratio of a gather is very low and obvious static correction value exists, the result is often bad.
Based on the above problem, the present application provides a high-dimensional pre-stack seismic data filtering method, as shown in fig. 1, including:
s101: and constructing prestack three-dimensional common midpoint channel set data according to the acquired seismic data.
S102: and acquiring the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number, the minimum cross survey line number and the maximum track number in the pre-stack three-dimensional common midpoint track set data.
S103: and filling a cross survey line gather in the pre-stack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number and the minimum cross survey line number to generate a pre-stack three-dimensional data body.
S104: and dividing the prestack three-dimensional data volume into a plurality of window data through a preset window.
S105: and performing wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume.
In an embodiment, padding a cross-line gather in the pre-stack three-dimensional common midpoint gather data according to the maximum main line number, the minimum main line number, the maximum cross-line number, and the minimum cross-line number to generate a pre-stack three-dimensional data volume, as shown in fig. 2, includes:
s201: and filling empty channels for the crossed measuring line numbers missing from each main measuring line according to the maximum crossed measuring line number and the minimum crossed measuring line number.
S202: and counting the total track number of each cross survey line gather, and if the total track number is less than the maximum track number, filling the total track number to ensure that the total track number is equal to the maximum track number.
In one embodiment, constructing prestack three-dimensional common midpoint gather data from acquired seismic data, as shown in FIG. 3, comprises:
s301: and screening the X axis of the pre-stack three-dimensional common midpoint gather data of the seismic channel structure along the same main survey line direction from the obtained seismic data.
S302: and screening seismic channels along the same cross survey line direction from the acquired seismic data to form a Y axis of pre-stack three-dimensional common midpoint gather data.
S303: and taking the time direction of the seismic data as the Z axis of the prestack three-dimensional common midpoint gather data.
In one embodiment, the segmenting the prestack three-dimensional data volume into a plurality of window data through a preset window includes:
and traversing the pre-stack three-dimensional data volume by using a preset window in a rolling manner, wherein the traversed pre-stack three-dimensional data volume is divided into a plurality of window data.
In an embodiment, performing wavelet transform on the window data to obtain a filtered prestack three-dimensional data volume, as shown in fig. 4, includes:
s401: and performing wavelet transformation on each channel of data in the window data along the Z-axis direction to obtain wavelet coefficients.
S402: and performing wavelet transformation on the window data according to the wavelet coefficient to obtain a data volume.
S403: and taking a corresponding relative data volume from the data volume according to a set scale.
S404: a high-dimensional matrix is generated from the relative data volumes.
S405: and carrying out singular value decomposition on the high-dimensional matrix to obtain a new data volume.
S406: and deleting all seismic channels with the new data body channel head flags of 0 to obtain the filtered prestack three-dimensional data body.
In one embodiment, the application achieves random noise suppression in pre-stack seismic data by:
firstly, acquiring seismic data and constructing prestack three-dimensional common midpoint channel set data, wherein the method specifically comprises the following steps: the seismic traces along the same Inline (Inline) direction constitute the X-axis, the seismic traces along the same cross-Inline (CMP) direction constitute the Y-axis, the seismic data time direction constitutes the Z-axis, and the origin of coordinates of the three-dimensional data volume is (1,1, 1).
According to an observation system of seismic data, the maximum Inline number, the minimum Inline number, the maximum CMP number, the minimum CMP number and the maximum CMP number of all survey lines in the prestack three-dimensional common-center gather data can be obtained and recorded as Max _ Inline, Min _ Inline, Max _ Cmp and Min _ Cmp, and the maximum track number of each CMP gather in the seismic data is recorded as Max _ Num _ CMP.
In the field acquisition process of seismic data, the situations of shot missing and channel missing can occur, so that the prestack three-dimensional concentric gather data is an irregular three-dimensional data body, namely: the total number of tracks of each main line (Inline) is different, the CMP number range of each main line (Inline) is different, and the number of tracks in each CMP track set is different.
According to the pre-stack three-dimensional common-center gather data, filling empty channels (amplitude values of all sampling points in the seismic channels are 0) for the CMP numbers missing from each main survey line Inline according to the maximum CMP number and the minimum CMP number; on the basis, the total track number of each CMP track set is counted and recorded as Num _ CMP, if Num _ CMP < Max _ Num _ CMP, then (Max _ Num _ CMP-Num _ CMP +1) empty tracks are complemented, so that the total track number of each CMP track set is Max _ Num _ CMP, and in addition, a Flag number Flag of the track head of the data of the empty tracks is set to be 0.
Giving a window size N to the regular prestack three-dimensional data volume formed as described aboveX,NY,NZI.e. taking N in the X-axis directionXTaking N in the Y-axis directionYTaking N in Z-axis directionZAnd (4) rolling the window to slide forwards, and overlapping the window by half in the moving process until the whole pre-stack three-dimensional data volume is traversed. For example: the starting point of the first window is (1,1,1) and the end point is (N)X,NY,NZ) The starting point of the second window is (N)X/2+1,NY/2+1,NZ2+1), the end point of the second window being (3N)X/2,3NY/2,3NZAnd/2), and so on, the prestack three-dimensional data volume can be divided into a plurality of window data. The data in this window is denoted as S (N)X,NY,NZ)。
Taking a certain window data S (N)X,NY,NZ) Each data of S (t), t 1,2, L, NzPerforming wavelet transformation on each channel of data along the Z-axis direction to obtain wavelet coefficients M (tau, a), wherein a is the scale of the wavelet transformation, and a is 1,2, L and M1τ is translation amount of wavelet transform, τ is 1,2, L, M2. To data S (N) in sequenceX,NY,NZ) The data volume obtained by wavelet transform of each channel is marked as M (N)X,NY,τ,a)；
One rule for each givenDegree a ═ i, from data volume M (N)X,NYτ, a) the data volume corresponding to the scale a ═ i is denoted as D (N)X,NY,τ)；
For the data volume D (N)X,NYτ) of the slice data D (N) corresponding to each τX,NY) A high-dimensional matrix is formed as follows:
wherein:
performing singular value decomposition on the following A of the high-dimensional Hankel matrix, sequentially arranging singular values obtained after decomposition from large to small, reserving the previous K singular values (K is given by a user), and reconstructing a new data body D '(N') by a singular value decomposition methodX,NY)；
Repeating the above steps for each tau in turn to obtain a new data volume D' (N)X,NY,τ)；
Repeating the above steps for each scale to obtain a data volume M' (N)X,NYτ, a), performing wavelet inverse transformation on the data volume, repeating the steps, and finishing data processing in all windows to obtain data after random noise suppression;
and finally, removing the seismic channels with the channel head Flag number being equal to 0, thereby obtaining the irregular prestack three-dimensional data volume after random noise suppression, and simultaneously keeping the data size of the irregular prestack three-dimensional data volume consistent with that of the prestack three-dimensional data volume before denoising. The pre-stack random noise suppression pre-and post-stack effect is shown in fig. 9A-9C.
Based on the same inventive concept, the embodiment of the present application further provides a high-dimensional pre-stack seismic data filtering apparatus, which can be used to implement the method described in the above embodiments, as described in the following embodiments. The problem solving principle of the high-dimensional pre-stack seismic data filtering device is similar to that of the high-dimensional pre-stack seismic data filtering method, so the implementation of the high-dimensional pre-stack seismic data filtering device can refer to the implementation of the high-dimensional pre-stack seismic data filtering method, and repeated parts are not described again. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. While the system described in the embodiments below is preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.
There is also provided according to another aspect of the present application, a high-dimensional pre-stack seismic data filtering apparatus, as shown in fig. 5, comprising:
the gather data construction unit 501 is configured to construct prestack three-dimensional common midpoint gather data according to the acquired seismic data;
an obtaining unit 502, configured to obtain a maximum main survey line number, a minimum main survey line number, a maximum cross survey line number, a minimum cross survey line number, and a maximum track number in the prestack three-dimensional common midpoint track set data;
a prestack three-dimensional data volume generating unit 503, configured to fill up a cross survey line gather in the prestack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number, and the minimum cross survey line number, and generate a prestack three-dimensional data volume;
a window dividing unit 504, configured to divide the prestack three-dimensional data volume into a plurality of window data through a preset window;
and a wavelet transformation unit 505, configured to perform wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume.
In one embodiment, as shown in fig. 6, the obtaining unit 502 includes:
a first empty track filling module 601, configured to fill empty tracks for the cross survey line number missing from each main survey line according to the maximum cross survey line number and the minimum cross survey line number;
and a second empty track filling module 602, configured to count a total track number of each cross-line survey gather, and if the total track number is smaller than the maximum track number, fill the total track number to make the total track number equal to the maximum track number.
In one embodiment, as shown in FIG. 7, the gather data construction unit 501 comprises:
the X-axis construction module 701 is used for screening the X-axis of the pre-stack three-dimensional common midpoint gather data of the seismic channel structure along the same main survey line direction from the acquired seismic data;
a Y-axis construction module 702, configured to screen seismic traces along the same cross line direction from the acquired seismic data to form a Y-axis of pre-stack three-dimensional common midpoint gather data;
and the Z-axis structure modeling block 703 is used for taking the time direction of the seismic data as the Z axis of the prestack three-dimensional common midpoint gather data.
In one embodiment, the window splitting unit 504 includes:
and the dividing module is used for traversing the pre-stack three-dimensional data volume by utilizing a preset window in a rolling manner, and dividing the traversed pre-stack three-dimensional data volume into a plurality of window data.
In one embodiment, as shown in fig. 8, the wavelet transform unit 505 includes:
a wavelet coefficient obtaining module 801, configured to perform wavelet transform on each channel of data in the window data along the Z-axis direction to obtain a wavelet coefficient;
a data volume obtaining module 802, configured to perform wavelet transformation on the window data according to the wavelet coefficients to obtain a data volume;
a relative data volume obtaining module 803, configured to obtain a corresponding relative data volume from the data volume according to a set scale;
a high-dimensional matrix generating module 804, configured to generate a high-dimensional matrix according to the relative data volume;
a singular value decomposition module 805, configured to perform singular value decomposition on the high-dimensional matrix to obtain a new data volume;
and a removing module 806, configured to delete all seismic traces with new data body heading flags of 0 to obtain a filtered prestack three-dimensional data body.
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 principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand 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.
An embodiment of the present application further provides a specific implementation manner of an electronic device capable of implementing all steps in the method in the foregoing embodiment, and referring to fig. 10, the electronic device specifically includes the following contents:
an embodiment of the present application further provides a specific implementation manner of an electronic device capable of implementing all steps in the method in the foregoing embodiment, and referring to fig. 10, the electronic device specifically includes the following contents:
a processor (processor)1101, a memory 1102, a Communications Interface 1103, a bus 1104, and a non-volatile memory 1105;
the processor 1101, the memory 1102 and the communication interface 1103 complete mutual communication through the bus 1104;
the processor 1101 is configured to call the computer programs in the memory 1102 and the nonvolatile memory 1105, and when the processor executes the computer programs, the processor implements all the steps in the method in the foregoing embodiments, for example, when the processor executes the computer programs, the processor implements the following steps:
s101: and constructing prestack three-dimensional common midpoint channel set data according to the acquired seismic data.
S102: and acquiring the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number, the minimum cross survey line number and the maximum track number in the pre-stack three-dimensional common midpoint track set data.
S103: and filling a cross survey line gather in the pre-stack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number and the minimum cross survey line number to generate a pre-stack three-dimensional data body.
S104: and dividing the prestack three-dimensional data volume into a plurality of window data through a preset window.
S105: and performing wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume.
Embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps of the method in the above embodiments, where the computer-readable storage medium stores thereon a computer program, and the computer program when executed by a processor implements all the steps of the method in the above embodiments, for example, the processor implements the following steps when executing the computer program:
s101: and constructing prestack three-dimensional common midpoint channel set data according to the acquired seismic data.
S102: and acquiring the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number, the minimum cross survey line number and the maximum track number in the pre-stack three-dimensional common midpoint track set data.
S103: and filling a cross survey line gather in the pre-stack three-dimensional common midpoint gather data according to the maximum main survey line number, the minimum main survey line number, the maximum cross survey line number and the minimum cross survey line number to generate a pre-stack three-dimensional data body.
S104: and dividing the prestack three-dimensional data volume into a plurality of window data through a preset window.
S105: and performing wavelet transformation on the window data to obtain a filtered prestack three-dimensional data volume.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to the partial description of the method embodiment. Although embodiments of the present description provide method steps as described in embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or end product executes, it may execute sequentially or in parallel (e.g., parallel processors or multi-threaded environments, or even distributed data processing environments) according to the method shown in the embodiment or the figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the embodiments of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, and the like. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. 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.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description 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 description 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 so forth) having computer-usable program code embodied therein. The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification.
In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction. The above description is only an example of the embodiments of the present disclosure, and is not intended to limit the embodiments of the present disclosure. Various modifications and variations to the embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification should be included in the scope of the claims of the embodiments of the present specification.