Interpolation method and device based on rapid data windowing, medium and equipment

Abstract

The invention provides an interpolation method and device based on rapid data windowing, a medium and equipment, and belongs to the technical field of geophysical exploration. The method comprises the steps that time window division is carried out according to input seismic data, all data are scanned to find the positions, corresponding to all seismic channels, of each window, the result of each window is calculated through five-dimensional regularization, and finally the regularization result is divided by a corresponding weight coefficient to obtain a final result. According to the method, data are scanned, which window each data belongs to is judged, the position of each data is stored, the positions of all seismic channels corresponding to the windows are found during subsequent calculation, the data are directly extracted, a large number of repeated data IO operations are avoided, and the stability and practicability of the seismic data denoising and interpolation effect are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of geophysical exploration, can be applied to seismic data noise suppression and data interpolation in geophysical exploration, and specifically relates to an interpolation method, device, medium and equipment based on fast data windowing. Background Art

[0002] With the in-depth development of oil and gas exploration, exploration and development has gradually turned to complex oil and gas reservoirs, and exploration technologies such as high-resolution seismic exploration and time-lapse seismic exploration have gradually increased the requirements for the quality of seismic data. Due to the influence of factors such as surface terrain conditions, seismic data acquisition is often irregular, which seriously affects the quality of seismic data migration imaging. With the development of seismic data interpolation technology, this problem has gradually been solved by five-dimensional regularization technology, but due to the large amount of pre-stack seismic data, generally 5Tb and above, conventional methods are difficult to effectively process large-scale data, and it is necessary to process seismic data in a multi-node parallel manner, which is of great significance for the application of regularization technology in actual data.

[0003] Since seismic data is too large to be read into memory, it must be processed in windows. However, in the process of windowing data, how to filter out the data of the corresponding window from the overall data and quickly read the data in the subsequent processing is the difficulty of this technology. Summary of the invention

[0004] The purpose of the present invention is to solve the problems existing in the above-mentioned prior art and to provide an interpolation method, device, medium and equipment based on fast data windowing. By calculating the positional relationship between the window and the corresponding captured data, the efficiency of the algorithm in capturing seismic data in each window is improved during the calculation process. On the one hand, the data does not need to be stored in the memory, and on the other hand, repeated redundant data IO operations are avoided.

[0005] The present invention is achieved through the following technical solutions:

[0006] The first aspect of the present invention provides an interpolation method based on fast data windowing, which divides the time window according to the input seismic data, scans all the data to find the position of each window corresponding to all seismic traces, uses five-dimensional regularization to calculate the result of each window, and finally divides the regularization result and the corresponding weight coefficient to obtain the final result.

[0007] A further improvement of the present invention is:

[0008] The method comprises the following steps:

[0009] Step 1: Input earthquake data;

[0010] Step 2: Divide the time window according to the range of earthquake data;

[0011] Step 3: Scan all data and find the position of each window corresponding to all seismic traces;

[0012] Step 4: Calculate the results of each window using five-dimensional regularization;

[0013] Step 5: Output the results.

[0014] A further improvement of the present invention is:

[0015] In step 1, earthquake data is input, and the specific operations include:

[0016] Input the seismic data X(t,x) to be denoised or interpolated, with the lengths of the two dimensions being T and X respectively.

[0017] A further improvement of the present invention is:

[0018] In step 2, time windows are divided according to the range of seismic data, and the specific operations include:

[0019] The seismic data X(t,x) is processed by windowing, and the number of all windows is total_win. The size of each window is not necessarily the same. The range of the i_win (0≤i_win<total_win) window is 0≤x<X_i_win, 0≤t<T_i_win, where 0≤X_i_win<X, 0≤T_i_win<T;

[0020] Set the maximum number of traces max_traces corresponding to a single window. Each window stores the two-dimensional array pos_win[total_win][max_traces] of the data position. total_win and max_traces correspond to the number of rows and columns of the two-dimensional array.

[0021] A further improvement of the present invention is:

[0022] In step 3, all data are scanned to find the position of all seismic traces corresponding to each window. The specific operations include:

[0023] (1) Set the initial values ​​x1 = 0, t1 = 0, store the calculation result Y(t, x) and the corresponding weight coefficient W(t, x), where the matrix sizes of Y(t, x) and W(t, x) are the same, and initialize Y(t, x) and the corresponding weight coefficient W(t, x) to 0;

[0024] (2) According to the current coordinates (t1, x1), find the window i_win containing the coordinates (t1, x1) and store the coordinates in pos_win[i_win]. 1 ,x 1 )=W(t1 ,x 1 )+1;

[0025] (3) t1 = t1 + 1, determine whether t1 is less than T, if so, jump to step (2), otherwise, jump to step (4);

[0026] (4) x1 = x1 + 1, determine whether x1 is less than X. If so, jump to step (2); otherwise, jump to step (5);

[0027] (5)End.

[0028] A further improvement of the present invention is:

[0029] In step 4, the result of calculating each window by five-dimensional regularization is calculated, and the specific operations include:

[0030] Extract all data in the i_win window according to pos_win[i_win], process all data extracted from the i_win window using regularization technology, and store the processing results in the corresponding position in Y(t,x).

[0031] A further improvement of the present invention is:

[0032] The step 5 outputs the result, and the specific operations include:

[0033] Divide the five-dimensional regularization calculation result by the corresponding weight coefficient Y(t,x). / W(t,x), where . / represents the division of corresponding elements, to obtain the final result and output it.

[0034] A second aspect of the present invention provides an interpolation device based on fast data windowing, comprising:

[0035] A data input unit, used for inputting seismic data;

[0036] A time window division unit, used for dividing the time window according to the range of seismic data;

[0037] A data scanning unit is used to scan all data and find the position of each window corresponding to all seismic traces;

[0038] A calculation unit, used for calculating the result of each window using five-dimensional regularization;

[0039] Output unit, used to output results.

[0040] According to a third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps in the interpolation method based on fast data windowing as described above.

[0041] A fourth aspect of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps in the interpolation method based on fast data windowing as described above.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention solves the problem that conventional algorithms are difficult to quickly and effectively extract data from irregular windows. By scanning the data, it is determined which window each data belongs to and its position is stored. In subsequent calculations, the position of all seismic traces corresponding to the window is found, and the data is directly extracted, avoiding a large number of repeated data IO operations, and improving the stability and practicality of the effects of seismic data denoising and interpolation. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The present invention provides a flowchart of an interpolation method based on fast data windowing. DETAILED DESCRIPTION

[0045] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0046] Aiming at the problem of slow data capture in different windows during the regularization of seismic data, the present invention proposes an interpolation method based on fast data windowing, which applies window data segmentation to existing seismic data interpolation and denoising algorithms to achieve fast data extraction according to windows.

[0047] The present invention provides an interpolation method based on fast data windowing, which divides the time window according to the input seismic data, scans all the data to find the position of all seismic traces corresponding to each window, calculates the result of each window using five-dimensional regularization, and finally divides the regularization result and the corresponding weight coefficient to obtain the final result.

[0048] [Example 1]

[0049] The embodiment of the present invention provides an interpolation method based on fast data windowing, such as Figure 1 As shown, the method specifically comprises the following steps:

[0050] Step 1: Input earthquake data;

[0051] Specific operations include:

[0052] Input the seismic data X(t,x) to be denoised or interpolated, with the lengths of the two dimensions being T and X respectively.

[0053] Step 2: Divide the time window according to the range of earthquake data;

[0054] Specific operations include:

[0055] The seismic data X(t,x) is processed by windowing, and the number of all windows is total_win. The size of each window is not necessarily the same. The range of the i_win (0≤i_win<total_win) window is 0≤x<X_i_win, 0≤t<T_i_win, where 0≤X_i_win<X, 0≤T_i_win<T;

[0056] Set the maximum number of traces max_traces corresponding to a single window. Each window stores the two-dimensional array pos_win[total_win][max_traces] of the data position. total_win and max_traces correspond to the number of rows and columns of the two-dimensional array.

[0057] Step 3: Scan all data and find the position of each window corresponding to all seismic traces;

[0058] Specific operations include:

[0059] (1) Set the initial values ​​x1 = 0, t1 = 0, store the calculation result Y(t, x) and the corresponding weight coefficient W(t, x), where the matrix sizes of Y(t, x) and W(t, x) are the same, and initialize Y(t, x) and the corresponding weight coefficient W(t, x) to 0;

[0060] (2) According to the current coordinates (t1, x1), find the window i_win containing the coordinates (t1, x1) and store the coordinates in pos_win[i_win]. 1 ,x 1 )=W(t 1 ,x 1 )+1;

[0061] (3) t1 = t1 + 1, determine whether t1 is less than T, if so, jump to step (2), otherwise, jump to step (4);

[0062] (4) x1 = x1 + 1, determine whether x1 is less than X. If so, jump to step (2); otherwise, jump to step (5);

[0063] (5)End.

[0064] Step 4: Calculate the results of each window using five-dimensional regularization;

[0065] Specific operations include:

[0066] Extract all data in the i_win window according to pos_win[i_win], process all data extracted from the i_win window using regularization technology, and store the processing results in the corresponding position in Y(t,x).

[0067] Step 5: Output the results

[0068] Specific operations include:

[0069] Divide the five-dimensional regularization calculation result by the corresponding weight coefficient Y(t,x). / W(t,x), where . / represents the division of corresponding elements, to obtain the final result and output it.

[0070] When the existing method is used for interpolation calculation, the time required is about 26 hours. When the interpolation calculation method based on fast data windowing is used for interpolation calculation, data is extracted for each window, which can improve the calculation efficiency and shorten the time to 21 hours.

[0071] [Example 2]

[0072] The embodiment of the present invention provides an interpolation device based on fast data windowing, comprising:

[0073] The data input unit is used to input earthquake data, and specifically performs the following operations:

[0074] Input the seismic data X(t,x) to be denoised or interpolated, with the lengths of the two dimensions being T and X respectively.

[0075] The time window division unit is used to divide the time window according to the range of earthquake data, and specifically performs the following operations:

[0076] The seismic data X(t,x) is processed by windowing, and the number of all windows is total_win. The size of each window is not necessarily the same. The range of the i_win (0≤i_win<total_win) window is 0≤x<X_i_win, 0≤t<T_i_win, where 0≤X_i_win<X, 0≤T_i_win<T;

[0077] Set the maximum number of traces max_traces corresponding to a single window. Each window stores the two-dimensional array pos_win[total_win][max_traces] of the data position. total_win and max_traces correspond to the number of rows and columns of the two-dimensional array.

[0078] The data scanning unit is used to scan all data and find the position of each window corresponding to all seismic traces. Specifically, the following operations are performed:

[0079] (1) Set the initial values ​​x1 = 0, t1 = 0, store the calculation result Y(t, x) and the corresponding weight coefficient W(t, x), where the matrix sizes of Y(t, x) and W(t, x) are the same, and initialize Y(t, x) and the corresponding weight coefficient W(t, x) to 0;

[0080] (2) According to the current coordinates (t1, x1), find the window i_win containing the coordinates (t1, x1) and store the coordinates in pos_win[i_win]. 1 ,x 1 )=W(t 1 ,x 1 )+1;

[0081] (3) t1 = t1 + 1, determine whether t1 is less than T, if so, jump to step (2), otherwise, jump to step (4);

[0082] (4) x1 = x1 + 1, determine whether x1 is less than X. If so, jump to step (2); otherwise, jump to step (5);

[0083] (5)End.

[0084] The calculation unit is used to calculate the result of each window using five-dimensional regularization, and specifically performs the following operations:

[0085] Extract all data in the i_win window according to pos_win[i_win], process all data extracted from the i_win window using regularization technology, and store the processing results in the corresponding position in Y(t,x).

[0086] The output unit is used to output the results. Specifically, it performs the following operations:

[0087] Divide the five-dimensional regularization calculation result by the corresponding weight coefficient Y(t,x). / W(t,x), where . / represents the division of corresponding elements, to obtain the final result and output it.

[0088] [Example 3]

[0089] An embodiment of the present invention provides a computer-readable storage medium, which stores at least one computer-executable program. When the at least one program is executed by the computer, the computer executes the steps in the interpolation method based on fast data windowing.

[0090] The steps in the interpolation method based on fast data windowing are specifically as follows:

[0091] Step 1: Input earthquake data;

[0092] Specific operations include:

[0093] Input the seismic data X(t,x) to be denoised or interpolated, with the lengths of the two dimensions being T and X respectively.

[0094] Step 2: Divide the time window according to the range of earthquake data;

[0095] Specific operations include:

[0096] The seismic data X(t,x) is processed by windowing, and the number of all windows is total_win. The size of each window is not necessarily the same. The range of the i_win (0≤i_win<total_win) window is 0≤x<X_i_win, 0≤t<T_i_win, where 0≤X_i_win<X, 0≤T_i_win<T;

[0097] Set the maximum number of traces max_traces corresponding to a single window. Each window stores the two-dimensional array pos_win[total_win][max_traces] of the data position. total_win and max_traces correspond to the number of rows and columns of the two-dimensional array.

[0098] Step 3: Scan all data and find the position of each window corresponding to all seismic traces;

[0099] Specific operations include:

[0100] (1) Set the initial values ​​x1 = 0, t1 = 0, store the calculation result Y(t, x) and the corresponding weight coefficient W(t, x), where the matrix sizes of Y(t, x) and W(t, x) are the same, and initialize Y(t, x) and the corresponding weight coefficient W(t, x) to 0;

[0101] (2) According to the current coordinates (t1, x1), find the window i_win containing the coordinates (t1, x1) and store the coordinates in pos_win[i_win]. 1 ,x 1 )=W(t 1 ,x 1 )+1;

[0102] (3) t1 = t1 + 1, determine whether t1 is less than T, if so, jump to step (2), otherwise, jump to step (4);

[0103] (4) x1 = x1 + 1, determine whether x1 is less than X. If so, jump to step (2); otherwise, jump to step (5);

[0104] (5)End.

[0105] Step 4: Calculate the results of each window using five-dimensional regularization;

[0106] Specific operations include:

[0107] Extract all data in the i_win window according to pos_win[i_win], process all data extracted from the i_win window using regularization technology, and store the processing results in the corresponding position in Y(t,x).

[0108] Step 5: Output the results

[0109] Specific operations include:

[0110] Divide the five-dimensional regularization calculation result by the corresponding weight coefficient Y(t,x). / W(t,x), where . / represents the division of corresponding elements, to obtain the final result and output it.

[0111] [Example 4]

[0112] An embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps in the interpolation method based on fast data windowing.

[0113] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0114] The above technical solution is only one implementation mode of the present invention. For those skilled in the art, it is easy to make various types of improvements or modifications based on the principles disclosed in the present invention, and it is not limited to the technical solution described in the above specific embodiments of the present invention. Therefore, the above description is only preferred and does not have a restrictive meaning.

Claims

1. An interpolation method based on fast data windowing, It is characterized in that The input seismic data is divided into time windows, all data are scanned to find the position of all seismic traces corresponding to each window, the result of each window is calculated using five-dimensional regularization, and finally the regularization result is divided by the corresponding weight coefficient to obtain the final result.

2. The interpolation method based on fast data windowing according to claim 1, It is characterized in that The method comprises the following steps: Step 1: Input earthquake data; Step 2: Divide the time window according to the range of earthquake data; Step 3: Scan all data and find the position of each window corresponding to all seismic traces; Step 4: Calculate the results of each window using five-dimensional regularization; Step 5: Output the results.

3. The interpolation method based on fast data windowing according to claim 2, It is characterized in that In step 1, earthquake data is input, and the specific operations include: Input the seismic data X(t,x) to be denoised or interpolated, with the lengths of the two dimensions being T and X respectively.

4. The interpolation method based on fast data windowing according to claim 3, It is characterized in that In step 2, time windows are divided according to the range of seismic data, and the specific operations include: The seismic data X(t,x) is processed by windowing, and the number of all windows is total_win. The size of each window is not necessarily the same. The range of the i_win (0≤i_win<total_win) window is 0≤x<X_i_win, 0≤t<T_i_win, where 0≤X_i_win<X, 0≤T_i_win<T; Set the maximum number of traces max_traces corresponding to a single window. Each window stores the two-dimensional array pos_win[total_win][max_traces] of the data position. total_win and max_traces correspond to the number of rows and columns of the two-dimensional array.

5. The interpolation method based on fast data windowing according to claim 4, It is characterized in that In step 3, all data are scanned to find the position of all seismic traces corresponding to each window. The specific operations include: (1) Set the initial values ​​x1 = 0, t1 = 0, store the calculation result Y(t, x) and the corresponding weight coefficient W(t, x), where the matrix sizes of Y(t, x) and W(t, x) are the same, and initialize Y(t, x) and the corresponding weight coefficient W(t, x) to 0; (2) According to the current coordinates (t1, x1), find the window i_win containing the coordinates (t1, x1) and store the coordinates in pos_win[i_win]. 1 ,x 1 )=W(t 1 ,x 1 )+1; (3) t1 = t1 + 1, determine whether t1 is less than T, if so, jump to step (2), otherwise, jump to step (4); (4) x1 = x1 + 1, determine whether x1 is less than X. If so, jump to step (2); otherwise, jump to step (5); (5)End.

6. The interpolation method based on fast data windowing according to claim 5, It is characterized in that In step 4, the result of calculating each window by five-dimensional regularization is calculated, and the specific operations include: Extract all data in the i_win window according to pos_win[i_win], process all data extracted from the i_win window using regularization technology, and store the processing results in the corresponding position in Y(t,x).

7. The interpolation method based on fast data windowing according to claim 6, It is characterized in that The step 5 outputs the result, and the specific operations include: Divide the five-dimensional regularization calculation result by the corresponding weight coefficient Y(t,x). / W(t,x), where . / represents the division of corresponding elements, to obtain the final result and output it.

8. An interpolation device based on fast data windowing, It is characterized in that include: A data input unit, used for inputting seismic data; A time window division unit, used for dividing the time window according to the range of seismic data; A data scanning unit is used to scan all data and find the position of each window corresponding to all seismic traces; A calculation unit, used for calculating the result of each window using five-dimensional regularization; Output unit, used to output results.

9. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps in the interpolation method based on fast data windowing as described in any one of claims 1 to 7.

10. A computer device, It is characterized in that It comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps in the interpolation method based on fast data windowing as described in any one of claims 1 to 7.

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