Method for quickly regularizing mass seismic data

Abstract

The invention provides a method for quickly regularizing mass seismic data, which comprises the following steps of: pre-processing initial seismic data and then performing shot combination and superposition, namely designing a reasonable output surface element for a shot point, performing combination and superposition on single shot data falling in the same surface element and merging into one shot, and placing the coordinate of the combined shot in the center of the surface element. According to the method, the original data volume is greatly reduced, the data processing efficiency is improved, the method is suitable for seismic data processing based on structural trap exploration, and regularization of high-density mass seismic data can be quickly realized on the premise that the signal-to-noise ratio of the data is not reduced, so that the processing efficiency is improved, and the processing period is shortened.

Description

Technical Field

[0001] The present invention relates to oil and gas exploration and development technologies, and particularly to a method for rapidly regularizing a large amount of seismic data. Background Art

[0002] In the existing domestic seismic processing technologies, the data volume can be compressed through gather combination stacking, but it performs adjacent stacking according to the input trace or gather order and cannot achieve reasonable data regularization.

[0003] Foreign processing software can achieve five-dimensional interpolation in five dimensions including the time direction, X-direction shot domain, X-direction geophone domain, Y-direction shot domain, and Y-direction geophone domain, so that the method can achieve data regularization. This method is based on the matching pursuit Fourier interpolation algorithm, uses the non-aliasing characteristics of the low-frequency end of the data to derive prior information, stretches the spectrum of the low-frequency band along the wavenumber direction and applies it to the high-frequency band as the weighting coefficient of the high-frequency band. A larger weighting coefficient is applied to the real signal, and a smaller weighting coefficient is applied to the aliased signal, so as to realize an anti-aliasing matching pursuit Fourier interpolation technology for aliasing protection. At the same time, in order to suppress spectral leakage, the frequency component with the largest energy is found in the frequency domain, and then subtracted in the time-space domain to obtain the updated data. The updated data is used to find the next frequency component with the largest energy, and all frequency components are obtained through continuous iterative processing, so as to achieve the purpose of suppressing spectral leakage, complete data interpolation and reconstruction, and thus improve the signal-to-noise ratio of seismic data. This method can also compress the data volume, but it is extremely time-consuming and resource-consuming, and it is difficult for the existing equipment resources and processing cycles to bear. Therefore, it has become an urgent problem to effectively and reasonably regularize a large amount of seismic data under limited resources and cycles. Summary of the Invention

[0004] In order to solve the problems of unreasonable regularization results of conventional technologies for a large amount of seismic data and time-consuming and resource-consuming data processing, the present invention proposes a method for rapidly regularizing a large amount of seismic data. Through the preprocessing of a large amount of seismic data, the shot combination bin is reasonably divided, and the time-varying diversity weighting technology is used to process the signal amplitude of the stacked traces, so as to compress the data of the large amount of seismic data and improve the overall processing efficiency of the data without reducing the signal-to-noise ratio of the data.

[0005] The present invention provides the following specific solutions:

[0006] A method for rapidly regularizing a large amount of seismic data includes the following steps:

[0007] S1. Data preparation: Preprocess the initial seismic data to obtain the first seismic data, and the preprocessing steps are successively: decompilation preprocessing, static correction processing, and pre-stack denoising processing; perform dynamic correction processing on the first seismic data and sort the shot point domain;

[0008] S2. Divide the shot combination bins: Group and divide the selected shot point area in S1 to obtain bins, such that the sum of variances of the distances from the central point coordinates of the bins to the coordinates of each shot point within the bin range is minimized, and the distance from the central point coordinates of the bin to the shot line is the shortest, where the shot line is a line formed by multiple shot points;

[0009] S3. Stack the seismic traces of the shot points of the same geophone within the same bin: Use time-varying weighted technology to equalize the signal amplitude, so that each stacked seismic trace has the same signal-to-noise ratio and the same amplitude level. After stacking the seismic trace data with the same signal-to-noise ratio and amplitude level, generate the stacked seismic trace data;

[0010] S4. Reset the shot point coordinates: Combine all the shot point coordinates within the bin into a single shot point coordinate, and set the single shot point coordinate at the central point coordinates of the bin; Set the central point coordinates within a bin as the single shot point coordinate to replace all the shot point coordinates within the bin;

[0011] S5. Evaluate whether the distance between the combined single shot point and the geophone in S4 exceeds 1 / 2 of the bin. If it exceeds, repeat S1 - S4; until the distance between the single shot point and the geophone does not exceed 1 / 2 of the bin, the stacked seismic trace data is used as the regularized second seismic data, and then the second seismic data is subjected to reverse movement correction processing to obtain the final common midpoint gather, and then perform fast migration imaging.

[0012] Preferably, the method for processing data in S1 is as follows:

[0013] S11. Decode and preprocess the initial seismic data: Convert the initial seismic data from the time sequence arrangement form to the trace sequence arrangement, so that the same seismic trace data under different time sequences are arranged together to obtain the decoded data;

[0014] S12. Static correction of the decoded data: Use the static correction amount to compensate for the deviation caused by the changes in the surface elevation, shot hole depth, thickness and velocity of the weathered layer for the decoded data in S11. The static correction amount is the time amount that the propagation time of the reflected wave needs to be corrected;

[0015] S13. Prestack denoising processing: Perform surface wave suppression, linear noise suppression, and abnormal amplitude suppression on the seismic data processed in S12 to obtain the first seismic data.

[0016] Preferably, the method for obtaining the static correction amount in S12 is as follows: First, correct the shot point and the receiving point to the CMP (common midpoint) reference plane, where the CMP reference plane is a reference plane that is equal to the average of the datum correction amounts of all traces in the CMP gather in terms of time; then, correct from the CMP reference plane to the floating datum plane of the CMP gather, where the floating datum plane is a reference plane determined according to the principle of minimizing the static correction error during the processing, and is usually horizontal.

[0017] Preferably, the method for performing dynamic correction and sorting the shot point domain on the first seismic data in S1 is as follows:

[0018] S14. Perform dynamic correction on the first seismic data: Sort the first seismic data into the common midpoint domain, and use the stacking velocity to eliminate the dynamic correction amount for all seismic traces in the common midpoint domain to complete the dynamic correction process. The dynamic correction amount is the dynamic time difference between the two-way travel time of the reflected wave at a non-zero shot-receiver offset and the two-way travel time of the reflected wave at a zero shot-receiver offset. The shot-receiver offset is the distance between the shot point and the geophone, and the zero shot-receiver offset means that the shot point and the geophone are at the same position;

[0019] S15. Sort the shot point domain: Sort the common midpoint gather after dynamic correction in S14 into the shot domain. The common midpoint gather is a set of all seismic record traces with the same reflection point.

[0020] Preferably, the specific implementation method of the time-varying diversity weighting technique in S3 is: Y tj represents the amplitude of the j-th trace at time t, then the amplitude value of the stacked trace X at time t is given by the following formula:

[0021]

[0022] In the formula, N represents the total number of stacked traces, j represents the current stacked trace number, X tj represents the amplitude of the j-th trace at time t, and W tj represents the weighting coefficient;

[0023] The weighting coefficient W tj The solution equation is:

[0024]

[0025] In the formula, L is the window length, s is the moment L / 2 before time t, and Y sj is the amplitude of the j-th trace at time s; Substitute equation (2) into equation (1), and the amplitude of the stacked trace X at time t can be solved.

[0026] The present invention provides a method for rapid regularization of massive seismic data. S1: Perform decompilation processing, static correction processing, pre-stack denoising processing, and dynamic correction processing on the initial seismic data, and sort it into the shot point domain; S2: Divide the sorted shot point domain into groups to form bins; S3: Stack the seismic traces of the shot points at the same geophone within the same bin; S4: Set the combined shot point coordinates within the bin at the center point coordinates of the bin to complete the data regularization. The method successfully realizes data compression and efficiency improvement without reducing the signal-to-noise ratio of the data. Seismic data of a certain mountain area in the west is selected for testing. The original data of the selected data is 87T, and the data volume becomes 23T after rapid regularization, greatly compressing the data while ensuring that the impact on the final imaging is not obvious. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a flowchart of a method for rapid regularization of massive seismic data provided by the present invention.

[0028] Figure 2 is a schematic diagram of shot combination bins in an embodiment of the present invention.

[0029] Figure 3 is a schematic diagram of stacking seismic traces of shot points within a bin in an embodiment of the present invention.

[0030] Figure 4 is a comparison diagram of the single-shot morphology before and after shot combination in an embodiment of the present invention.

[0031] Figure 5 is a comparison diagram of the shot point positions before and after shot combination in an embodiment of the present invention.

[0032] Figure 6 is a comparison diagram of the pre-stack depth migration profiles before and after shot combination in an embodiment of the present invention.

[0033] In the figure: 1. Shot point; 2. Shot line; 3. Shot point distance; 4. Shot line distance; 5. Bin; 101, 102, 103: Single-shot point seismic traces. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] The present invention will be further described below with reference to the drawings and embodiments.

[0035] As Figure 1 shown, a method for rapid regularization of massive seismic data includes the following steps:

[0036] S1. Data preparation: Perform preprocessing on the initial seismic data to obtain the first seismic data. The preprocessing steps are successively: decompilation preprocessing, static correction processing, and pre-stack denoising processing; perform dynamic correction processing on the first seismic data and sort it into the shot point domain;

[0037] S2. Divide the shot - combined bin: Group and divide the selected shot - point area in S1 to obtain bins, such that the sum of variances of the distances from the central - point coordinates of the bin to the coordinates of each shot - point within the bin range is minimized, and the distance from the central - point coordinates of the bin to the shot - line is the shortest, where the shot - line is a line formed by multiple shot - points;

[0038] S3. Stack the seismic traces of the shot - points of the same geophone within the same bin: Use time - variant weighted technology to equalize the signal amplitude, so that each stacked seismic trace of each shot has the same signal - to - noise ratio and the same amplitude level. After stacking the seismic - trace data with the same signal - to - noise ratio and amplitude level, generate the stacked seismic - trace data;

[0039] S4. Reset the shot - point coordinates: Combine all the shot - point coordinates within the bin into a single - shot - point coordinate, and set the single - shot - point coordinate at the central - point coordinates of the bin; Set the central - point coordinates within a bin as the single - shot - point coordinate to replace all the shot - point coordinates within the bin;

[0040] S5. Evaluate whether the distance between the combined single - shot - point and the geophone in S4 exceeds 1 / 2 of the bin. If it exceeds, repeat S1 - S4; until the distance between the single - shot - point and the geophone does not exceed 1 / 2 of the bin, the stacked seismic - trace data is used as the regularized second seismic data, then perform NMO correction processing on the second seismic data to obtain the final common - mid - point gather, and then perform fast migration imaging.

[0041] Preferably, the steps to pre - process the initial seismic data in S1 are as follows:

[0042] S11. Decode and pre - process the initial seismic data: Convert the initial seismic data from the time - series arrangement form to the trace - order arrangement, so that the seismic - trace data of the same trace under different time - series are arranged together to obtain the decoded data;

[0043] S12. Static correction of the decoded data: Use the static - correction amount to compensate for the deviation caused by the changes in the surface elevation, shot - hole depth, thickness and velocity of the weathered layer in the decoded data in S11. The static - correction amount is the time amount that the propagation time of the reflected wave needs to be corrected;

[0044] S13. Pre - stack noise reduction processing: Perform surface - wave suppression, linear - noise suppression, and abnormal - amplitude suppression on the seismic data processed in S12 to obtain the first seismic data.

[0045] Preferably, the method for obtaining the static correction amount in S12 is as follows: First, correct the shot point and the receiving point to the CMP (common midpoint) reference plane, where the CMP reference plane is a time reference plane that is equal to the average of the datum corrections of all traces in the CMP gather in terms of time; then, correct from the CMP reference plane to the floating datum plane of the CMP gather, where the floating datum plane is a reference plane determined according to the principle of minimizing the static correction error during the processing and is usually horizontal.

[0046] Preferably, the method for performing NMO correction and sorting the shot domain for the first seismic data in S1 is as follows:

[0047] S14. Perform NMO correction on the first seismic data: Sort the first seismic data into the common midpoint domain, and use the stacking velocity to eliminate the NMO correction amount for all seismic traces in the common midpoint domain to complete the NMO correction process. The NMO correction amount is the dynamic time difference between the two-way travel time of the reflected wave at a non-zero offset and the two-way travel time of the reflected wave at a zero offset. The offset is the distance between the shot point and the geophone, and the zero offset means that the shot point and the geophone are at the same position;

[0048] S15. Sort the shot domain: Sort the common midpoint gathers after NMO correction in S14 into the shot domain. The common midpoint gather is a set of all seismic recording traces with the same reflection point.

[0049] Preferably, the specific implementation method of the time-varying diversity weighting technique in S3 is as follows: Y tj represents the amplitude of the j-th trace at time t. Then, the amplitude value of the stacked trace X at time t after combination is given by the following formula:

[0050]

[0051] In the formula, N represents the total number of stacked traces, j represents the current stacked trace number, X tj represents the amplitude of the j-th trace at time t, and W tj represents the weighting coefficient;

[0052] The weighting coefficient W tj The solution equation is:

[0053]

[0054] In the formula, L is the window length, s is the moment L / 2 before time t, and Y sj is the amplitude of the j-th trace at time s; Substitute equation (2) into equation (1), and the amplitude of the stacked trace X at time t can be solved.

[0055] Example 1:

[0056] The project is about the seismic data acquisition parameters in a certain area. The acquisition annual span is from 2000 to 2018, with a span of 18 years, and the total data volume reaches 87T. The specific parameters are as follows in the table:

[0057]

[0058]

[0059] Specifically, as Figure 2 shown, in the above embodiment, taking Area 1 as an example, a suitable shot combination bin is divided. Taking the division of one bin 5 with 3 shot points 1 as an example, the center point of bin 5 is made to be as close as possible to all the shot points 1 within bin 5, and the distance from the center point coordinate of bin 5 to the shot line 2 where the shot points 1 in the bin are located is the shortest.

[0060] Then, the seismic traces with the same geophone point and shot points within the same bin are stacked. During the stacking process, the "time-varying diversity weighting" technology is used to balance the signal amplitudes of each stacked trace, that is, different weights are applied to the amplitudes of each stacked trace at different time points, so as to make the signals of each shot stack have the same signal-to-noise ratio and the same amplitude level as much as possible, and avoid reducing the signal quality after stacking. Exemplarily, as Figure 2 、 Figure 3 shown, the original shot interval 3 is 60 meters, the shot line interval 4 is 240 meters, and the seismic traces of the 3 shot points within bin 5 are respectively Figure 3 the seismic trace 101, seismic trace 102, and seismic trace 103 in Figure 4 . The seismic trace data of the 3 shot points are stacked through the time-varying diversity weighting technology. As

[0061] shown, the upper part is the single-shot morphology graph before combination, and the lower part is the single-shot morphology graph after stacking combination. If the difference between the two is not significant, it is normal. Figure 5 shown, the left side is the position graph of the shot points before combination, and the right side is the position graph of the shot points after combination; stacking in the shot point direction and keeping the shot line direction unchanged, after stacking, the shot interval 3 becomes 180 meters, while the shot line interval 4 remains 240 meters.

[0062] Using the method disclosed in the present invention, the data of Areas 1, 6, and 10 in Embodiment 1 are regularized. The data volume changes from 87T to 23T. It takes 38 hours to collectively deviate the traces before combination to the target line, and it takes 11 hours to collectively deviate the traces after combination to the target line, greatly improving the modeling cycle.

[0063] As Figure 6 shown, from the pre-stack depth migration effect, it can be seen that the shot combination has little impact on the pre-stack depth migration structure imaging, and while improving the processing efficiency, the data quality is not reduced.

[0064] It should be noted that the specific embodiments described above can enable those skilled in the art to understand the present invention more comprehensively, but do not limit the present invention in any way. Therefore, although this specification has described the present invention in detail with reference to the accompanying drawings and embodiments, those skilled in the art should understand that the present invention can still be modified or equivalently replaced. In short, all technical solutions and their improvements that do not depart from the spirit and scope of the present invention should be covered by the protection scope of the patent of the present invention.

Claims

1. A method for rapid regularization of massive seismic data, characterized in that, it includes the following steps: S1. Data preparation: Preprocess the initial seismic data to obtain the first seismic data. The preprocessing steps are, in sequence: decompilation preprocessing, static correction processing, and pre-stack denoising processing; Perform dynamic correction processing on the first seismic data and sort the shotpoint domain; S2. Divide the shot combination bins: Group and divide the sorted shotpoint domain in S1 to obtain bins, so that the sum of variances of the distances from the central point coordinates of the bins to the coordinates of each shotpoint within the bin range is minimized, and the distance from the central point coordinates of the bin to the shot line is the shortest. The shot line is a line formed by multiple shotpoints; S3. Stack the seismic traces of the shotpoints of the same geophone within the same bin: Use time-varying weighted technology to equalize the signal amplitude, so that each seismic trace stacked for each shot has the same signal-to-noise ratio and the same amplitude level. Stack the seismic trace data with the same signal-to-noise ratio and amplitude level to generate the stacked seismic trace data; S4. Reset the shotpoint coordinates: Combine all the shotpoint coordinates within the bin into a single shotpoint coordinate, and set the single shotpoint coordinate at the central point coordinates of the bin; Set the central point coordinates within a bin as the single shotpoint coordinate to replace all the shotpoint coordinates within the bin; S5. Evaluate whether the distance between the combined single shotpoint and the geophone in S4 exceeds 1 / 2 of the bin. If it exceeds, repeat S1 - S4; until the distance between the single shotpoint and the geophone does not exceed 1 / 2 of the bin, the stacked seismic trace data is used as the second seismic data after regularization. Then perform reverse dynamic correction processing on the second seismic data to obtain the final common midpoint gather, and then perform fast migration imaging.

2. A method for rapid regularization of massive seismic data according to claim 1, characterized in that, the method for processing data in S1 is as follows: S11. Decompile and preprocess the initial seismic data: Convert the initial seismic data from the time-series arrangement form to the trace-order arrangement, so that the seismic trace data of the same trace under different time series are arranged together to obtain the decompiled data; S12. Static correct the decompiled data: Use the static correction amount to compensate for the deviation caused by the changes in the surface elevation, shot hole depth, thickness and velocity of the weathered layer for the decompiled data in S11. The static correction amount is the time amount that the propagation time of the reflected wave needs to be corrected; S13. Perform pre-stack denoising processing on the seismic data: Perform surface wave suppression, linear noise suppression, and abnormal amplitude suppression on the seismic data processed in S12 to obtain the first seismic data.

3. A method for rapid regularization of massive seismic data according to claim 2, characterized in that, the method for obtaining the static correction amount in S12 is as follows: First, correct the shotpoint and the receiving point to the common midpoint CMP reference surface. The CMP reference surface is a time reference surface that is equal to the average value of the datum correction amounts of all traces in the CMP gather in terms of time. Then, correct from the CMP reference surface to the floating datum surface of the CMP gather. The floating datum surface is a reference surface determined according to the principle of minimum static correction error during the processing, usually horizontal.

4. A method for rapid regularization of a large amount of seismic data according to claim 1, characterized in that, the method for dynamic correction and sorting of shotpoint domain for the first seismic data in S1 is as follows: S14. Perform dynamic correction on the first seismic data: Sort the first seismic data into the common midpoint domain, and use the stacking velocity to eliminate the dynamic correction amount for all seismic traces in the common midpoint domain to complete the dynamic correction process. The dynamic correction amount is the dynamic time difference between the two-way travel time of the reflected wave at a non-zero offset and the two-way travel time of the reflected wave at a zero offset. The offset is the distance between the shotpoint and the geophone, and the zero offset means that the shotpoint and the geophone are at the same position; S15. Sort the shotpoint domain: Sort the common midpoint trace gather after dynamic correction in S14 into the shot domain. The common midpoint trace gather is a set of all seismic recording traces with the same reflection point.

5. A method for rapid regularization of a large amount of seismic data according to claim 1, characterized in that, The specific implementation method of the time-varying diversity weighting technique described in S3 is as follows: Y tj Let \(Y_{j}(t)\) represent the amplitude of the \(j\)-th trace at time \(t\). Then the amplitude value of the stacked trace \(X\) after combination at time \(t\) is given by the following formula: Wherein, N represents the total number of stacked channels, j represents the current stacking channel number, X tj represents the amplitude of the j-th channel at time t, and W tj represents the weighting coefficient; Weight coefficient W tj The solution equation is: where L is the window length, s is the time moment L / 2 before time t, and Y sj is the amplitude of the j-th trace at time s; substituting equation (2) into equation (1), the amplitude of the stacked trace X at time t can be solved and obtained.

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