Dominant orientation constrained seismic imaging method based on extended bins

Abstract

A method for constraining seismic imaging based on dominant azimuth based on extended facets includes the following steps: 1. Input of shot records of a single offset surface; 2. Extended facets screen dominant azimuth channels corresponding to central facets; 3. Extended facets screen minimum distance channels corresponding to central facets; 4. According to the envelope energy of dominant azimuth channels and minimum distance channels, the weighting coefficient of the scaled seismic channels is weighted to weight the two seismic channels; 5. Weight the dominant azimuth channels and minimum distance channels facet by facet; 6. Regularization of single offset surface data by anti-leakage Fourier transform; 7. Repeating the first step to the sixth step for the shot records of each offset surface to complete the processing of the shot records of all offset surfaces; 8. Output of all offset surface shot records after regularization; 9. Velocity modeling of target geological bodies; 10. Offset imaging. The present invention realizes the utilization of dominant azimuth information in the process of seismic imaging, and improves the imaging quality of complex geological bodies sensitive to azimuth.

Description

Technical Field

[0001] The invention belongs to the field of oil and gas field exploration, and in particular relates to a dominant orientation constrained seismic imaging method based on extended facets. Background Art

[0002] As geological exploration targets become more and more complex, the requirements for seismic exploration accuracy are also constantly increasing. In addition to conventional seismic information such as amplitude, frequency, phase, and travel time, azimuth information has also received more and more attention.

[0003] In different orientations, the imaging of some complex geological bodies is quite different. For example, the dominant imaging orientation of faults is perpendicular to their strike direction, and the cross-sectional wave can be better imaged in this orientation; while the dominant imaging orientation of gas clouds is in the direction of their short axis, and the imaging quality of the gas cloud influence area is better in this orientation. Therefore, in the process of seismic imaging, effectively mining and utilizing the information of the dominant orientation is of great significance to improving the imaging quality of complex geological bodies.

[0004] At present, in the seismic data processing process, the main aspects related to orientation are: data regularization, velocity modeling and migration imaging. Among them, data regularization is the basis for subsequent velocity modeling and migration imaging. Good data regularization is crucial for effectively mining the information of the dominant orientation. However, most conventional data regularization methods use inverse distance weighted technology, ignoring the azimuth information of seismic traces; while the five-dimensional interpolation data regularization method performs indifferent interpolation processing on seismic traces in five dimensions: vertical, horizontal, time, offset, and azimuth. However, it does not take into account the differences in geological body imaging under different orientations and effectively mines the information of seismic traces in the dominant orientation. In other words, the seismic imaging method based on the existing data regularization technology ignores the azimuth information of seismic traces or does not consider the dominant orientation information enough, and often loses some of the information of seismic traces in the dominant orientation; in this way, it is only suitable for imaging of geological bodies that are insensitive to orientation, but not for imaging of complex geological bodies that are sensitive to orientation. Therefore, developing a seismic imaging method based on new data regularization technology so that the advantageous orientation information can be effectively mined and contribute a relatively greater role in geological body imaging is the key to improving the imaging quality of complex geological bodies that are sensitive to orientation. Summary of the invention

[0005] The purpose of the present invention is to provide a dominant azimuth constraint seismic imaging method based on extended facets to solve the technical problem that the existing seismic imaging method based on data regularization technology often loses part of the dominant azimuth seismic trace information due to ignoring the azimuth information of the seismic trace or insufficient consideration of the dominant azimuth information.

[0006] To achieve the above object, the specific technical solution of the dominant orientation constrained seismic imaging method based on extended bins of the present invention is as follows:

[0007] A dominant azimuth constrained seismic imaging method based on extended bins comprises the following steps:

[0008] Step 1: Input of shot records for a single offset surface;

[0009] Step 2: Expand the facets to select the dominant direction path corresponding to the central facet;

[0010] The expansion of the facets to select the dominant orientation corresponding to the central facet is carried out in the following steps:

[0011] ① Expand from a single center bin to several bins around it, and calculate: the average weighted seismic trace of all seismic traces within the range of several bins including the center bin as the model trace;

[0012] ② Calculate the cross-correlation between each seismic trace and the model trace, and select the seismic trace with the largest correlation coefficient as the dominant azimuth trace corresponding to the central bin;

[0013] Step 3: Expand the facets to select the minimum distance path corresponding to the central facet;

[0014] Step 4: According to the envelope energy of the dominant azimuth trace and the minimum distance trace, calibrate the seismic trace weighting coefficient and weight the two seismic traces;

[0015] Step 5: Weight the dominant azimuth path and the minimum distance path for each facet;

[0016] Step 6: Regularize the single offset range surface data by anti-leakage Fourier transform;

[0017] Step 7: Repeat the operations of Step 1 to Step 6 for each shot record of the offset distance surface to complete the processing of the shot records of all offset distance surfaces;

[0018] Step 8: Output all offset shot records after regularization;

[0019] Step 9: Velocity modeling of target geological body;

[0020] Carry out velocity modeling on the target geological body to obtain a velocity model with higher accuracy;

[0021] Step 10: Offset imaging;

[0022] Based on the velocity model established in the ninth step, the shot records regularized in the eighth step are subjected to migration imaging, and finally the migration imaging results of the geological body are obtained;

[0023] After the tenth step, the seismic imaging effect is demonstrated in the area affected by the complex geological body and compared with the seismic imaging method based on the existing data regularization technology.

[0024] Furthermore, in the first step, the shot record input of a single offset plane refers to the shot record of a single offset range after the input is grouped according to the offset, and after the previous work area surface element grid definition and trace merging processing, the entire work area is divided into a uniform surface element grid, and the seismic traces are irregularly distributed in each surface element.

[0025] Furthermore, in the third step, the minimum distance track corresponding to the expanded facet element screening center facet element is calculated based on the shot point coordinates and detection point coordinates of the seismic track, and the distance from each seismic track to the facet element center within the range of several facet elements including the center facet element in the second step is calculated, and the seismic track with the shortest distance is selected as the minimum distance track corresponding to the center facet element.

[0026] Furthermore, in the fourth step, the weight coefficients corresponding to the dominant azimuth trace and the minimum distance trace are calculated, and the value of the weight coefficient is proportional to the envelope energy; then, the dominant azimuth trace and the minimum distance trace are weighted according to the weight coefficient to obtain the dominant azimuth weighted seismic trace corresponding to the central face element.

[0027] Furthermore, in the fifth step, the operations of the second step to the fourth step are repeated for each face element to complete the processing of all face elements in the single offset plane.

[0028] Furthermore, in the sixth step, the anti-leakage Fourier transform is applied to regularize the data of the single offset plane, and according to the interpolation principle, the seismic trace weighted by the dominant azimuth corresponding to each surface element in the fifth step is moved to the center of the surface element;

[0029] The anti-leakage Fourier transform formula is: Among them, k is: frequency domain component, x l is: spatial non-uniform sampling point position, f(x l ) is: x l The signal value at is the spectrum corresponding to the signal, N is the number of non-uniform sample points, ΔX is the maximum space, Δx l is: spatial sampling interval, f k (x l ) is: time domain seismic data, f u (x l ) is: seismic data after iterative subtraction in time domain.

[0030] The dominant azimuth constraint seismic imaging method based on extended bins of the present invention has the following advantages:

[0031] 1. The present invention can effectively mine and utilize the advantageous azimuth information while fully considering the imaging differences of geological bodies in different azimuths, thus solving the problem that the existing seismic imaging method based on data regularization technology often loses part of the advantageous azimuth seismic trace information due to ignoring the azimuth information of the seismic trace or insufficient consideration of the advantageous azimuth information;

[0032] 2. When screening seismic traces, the present invention expands the single surface element to several surrounding surfaces through the expanded surface element processing, so as to find the dominant azimuth trace in a relatively larger spatial range, and can effectively mine the local optimal dominant azimuth information;

[0033] 3. The present invention is particularly suitable for imaging complex geological bodies such as faults and gas clouds that are sensitive to orientation. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of the process of the present invention;

[0035] Figure 2-1 A schematic diagram of an application process (a) of an embodiment of the present invention;

[0036] Figure 2-2 A schematic diagram of an application process (b) of an embodiment of the present invention;

[0037] Figure 2-3 A schematic diagram of an application process (c) of an embodiment of the present invention;

[0038] Figure 2-4 A schematic diagram of the application process (d) of one embodiment of the present invention;

[0039] Figure 2-5 A schematic diagram of an application process (e) of an embodiment of the present invention;

[0040] Figure 2-6 A schematic diagram of an application process (f) of an embodiment of the present invention;

[0041] Figure 3 : This is a RMS amplitude attribute diagram of the gas cloud plane of a complex geological body in an embodiment of the present invention (the shaded area at the arrow indicates the distribution range of the gas cloud plane);

[0042] Figure 4-1 Schematic diagram of the imaging section (a) of the gas cloud influence zone of a complex geological body after the application of the present invention;

[0043] Figure 4-2 Schematic diagram of the imaging section of the gas cloud influence zone of a complex geological body after the application of the seismic imaging method based on the existing data regularization technology (b). DETAILED DESCRIPTION

[0044] In order to better understand the purpose, structure and function of the present invention, a dominant orientation constrained seismic imaging method based on extended bins of the present invention is further described in detail below with reference to the accompanying drawings.

[0045] like Figure 1-Figure 4-2 As shown, the present invention is specifically carried out according to the following steps:

[0046] Step 1: Input of shot records for a single offset surface;

[0047] Before the input data is regularized, the shot records of a single offset surface are divided into uniform surface grids after the previous work area surface grid definition and trace merging process. Taking nine adjacent surface elements as an example (i.e., three rows and three columns, arranged as: 1, 2, 3, 4, 5, 6, 7, 8, 9), the seismic traces are irregularly distributed in each surface element, such as Figure 2-1 (a), and the waveforms of each seismic trace are obviously different, such as Figure 2-4 (d) as shown.

[0048] Step 2: Expand the facets to select the dominant direction path corresponding to the central facet;

[0049] 1. Yes Figure 2-2 (b) is expanded from the central bin 5 to several surrounding bins. In this embodiment, eight surrounding bins, namely, 1, 2, 3, 4, 6, 7, 8, and 9, are used to calculate the average weighted seismic trace of all seismic traces in the nine bins including the central bin 5 as the model trace. Figure 2-5 (e) is shown in the model track;

[0050] 2. Calculate the cross-correlation between each seismic trace and the model trace in the nine bins, and select the seismic trace with the largest correlation coefficient as the dominant azimuth trace corresponding to the center bin No. 5, that is, the seismic trace in bin No. 1. Its azimuth and waveform are as follows: Figure 2-2 (b) and 2-5(e).

[0051] Step 3: Expand the facets to select the minimum distance path corresponding to the central facet;

[0052] According to the shot point coordinates and receiver point coordinates of the seismic trace, the distance between each seismic trace in the nine bins in the second step and the bin center is calculated, and the seismic trace with the smallest distance is selected as the minimum distance trace corresponding to the center bin No. 5, that is, the seismic trace in bin No. 6. Its azimuth and waveform are as follows: Figure 2-2 (b) and 2-5(e).

[0053] Step 4: According to the envelope energy of the dominant azimuth trace and the minimum distance trace, calibrate the seismic trace weighting coefficient and weight the two seismic traces;

[0054] like Figure 2-6 As shown in (f), the envelope energy of the dominant azimuth trace and the minimum distance trace obtained in the second and third steps within the given time window is calculated, and the energy values ​​are 2110 and 690 respectively. The weight coefficients corresponding to the dominant azimuth trace and the minimum distance trace are calculated, which are 0.75 and 0.25 respectively; this is based on the principle that the value of the weight coefficient is proportional to the size of the envelope energy. Then, the dominant azimuth trace and the minimum distance trace are weighted according to the weight coefficient to obtain the dominant azimuth weighted seismic trace corresponding to the center plane element No. 5.

[0055] Step 5: Weight the dominant azimuth path and the minimum distance path for each facet;

[0056] Repeat the second to fourth steps for each face element to complete the processing of all face elements in a single offset plane;

[0057] Step 6: Regularize the single offset range surface data by anti-leakage Fourier transform;

[0058] The anti-leakage Fourier transform is applied to regularize the data of a single offset surface, and according to the interpolation principle, the weighted seismic trace corresponding to each surface element in the fifth step is moved to the center of the surface element, such as Figure 2-3 (c) As shown in the center bin No. 5, the seismic trace after data regularization is located at the bin center.

[0059] The above anti-leakage Fourier transform formula is:

[0060] Among them, k is: frequency domain component, x l is: spatial non-uniform sampling point position, f(x l ) is: x l The signal value at is the spectrum corresponding to the signal, N is the number of non-uniform sample points, ΔX is the maximum space, Δx l is: spatial sampling interval, f k (x l ) is: time domain seismic data, f u (x l ) is: seismic data after iterative subtraction in time domain.

[0061] Step 7: Repeat the operations of Step 1 to Step 6 for each shot record of the offset distance surface to complete the processing of the shot records of all offset distance surfaces;

[0062] Step 8: Output all offset shot records after regularization;

[0063] After data regularization, the shot records of all offset distance surfaces are output as input data for subsequent migration imaging.

[0064] Step 9: Velocity modeling of target geological body;

[0065] Carry out velocity modeling on the target geological body to obtain a velocity model with higher accuracy; Step 10:

[0066] Migration imaging;

[0067] Based on the velocity model established in the ninth step, the shot records regularized in the eighth step are subjected to migration imaging, and finally the migration imaging results of the geological body are obtained.

[0068] like Figure 3-Figure 4-2 As shown, the application effect of the present invention in seismic imaging of areas affected by complex geological bodies is demonstrated. Figure 3 This is the plane root mean square amplitude attribute diagram of the gas cloud in a complex geological body. From the figure, we can see that the gas cloud develops in a strip-like shape, resulting in a significant impact on its imaging quality at different orientations.

[0069] Figure 4-1 Schematic diagram of the imaging section (a) of the gas cloud influence zone of a complex geological body after the application of the present invention, Figure 4-2 This is a schematic diagram of the imaging profile (b) of the gas cloud influence zone of a complex geological body after the application of the seismic imaging method based on the existing data regularization technology. By comparison, it can be seen that the imaging quality of the gas cloud and other complex geological body influence zones after the application of the present invention is better, the seismic wave group characteristics are clearer, the seismic phase axis is more continuous, and the signal-to-noise ratio is also higher.

[0070] The above-mentioned technologies not described are prior art and will not be described in detail.

[0071] It is to be understood that the present invention is described by some embodiments, and it is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the scope of protection of the present invention.

Claims

1. A dominant azimuth constrained seismic imaging method based on extended bins, characterized in that: The steps include: Step 1: Input of shot records for a single offset surface; Step 2: Expand the facets to select the dominant direction path corresponding to the central facet; The expansion of the facets to select the dominant orientation corresponding to the central facet is carried out in the following steps: ① Expand from a single center bin to several bins around it, and calculate: the average weighted seismic trace of all seismic traces within the range of several bins including the center bin as the model trace; ② Calculate the cross-correlation between each seismic trace and the model trace, and select the seismic trace with the largest correlation coefficient as the dominant azimuth trace corresponding to the central bin; Step 3: Expand the facets to select the minimum distance path corresponding to the central facet; Step 4: According to the envelope energy of the dominant azimuth trace and the minimum distance trace, calibrate the seismic trace weighting coefficient and weight the two seismic traces; Step 5: Weight the dominant azimuth path and the minimum distance path for each facet; Step 6: Regularize the single offset range surface data by anti-leakage Fourier transform; Step 7: Repeat the operations of Step 1 to Step 6 for each shot record of the offset distance surface to complete the processing of the shot records of all offset distance surfaces; Step 8: Output all offset shot records after regularization; Step 9: Velocity modeling of target geological body; Carry out velocity modeling on the target geological body to obtain a velocity model with higher accuracy; Step 10: Offset imaging; Based on the velocity model established in the ninth step, the shot records regularized in the eighth step are subjected to migration imaging, and finally the migration imaging results of the geological body are obtained; After the tenth step, the seismic imaging effect is demonstrated in the area affected by the complex geological body and compared with the seismic imaging method based on the existing data regularization technology.

2. The method for dominant orientation constrained seismic imaging based on extended bins according to claim 1, characterized in that: In the first step, the shot record input of a single offset plane refers to the shot records of a single offset range after the input is grouped according to the offset, and after the previous work area surface element grid definition and trace merging processing, the entire work area is divided into a uniform surface element grid, and the seismic traces are irregularly distributed in each surface element.

3. The method for dominant orientation constrained seismic imaging based on extended bins according to claim 1, characterized in that: In the third step, the minimum distance track corresponding to the expanded facet element screening center facet element is calculated based on the shot point coordinates and detection point coordinates of the seismic track, and the distance from each seismic track to the facet element center within the range of several facet elements including the center facet element in the second step is calculated, and the seismic track with the smallest distance is selected as the minimum distance track corresponding to the center facet element.

4. The method for dominant orientation constrained seismic imaging based on extended bins according to claim 1, characterized in that: In the fourth step, the weight coefficients corresponding to the dominant azimuth trace and the minimum distance trace are calculated, and the value of the weight coefficient is proportional to the envelope energy; then, the dominant azimuth trace and the minimum distance trace are weighted according to the weight coefficient to obtain the dominant azimuth weighted seismic trace corresponding to the central plane element.

5. The method for dominant orientation constrained seismic imaging based on extended bins according to claim 1, characterized in that: In the fifth step, the operations of the second step to the fourth step are repeated for each face element to complete the processing of all face elements in the single offset plane.

6. The method for dominant orientation constrained seismic imaging based on extended bins according to claim 1, characterized in that: In the sixth step, the anti-leakage Fourier transform is applied to regularize the data of the single offset plane, and the weighted seismic traces corresponding to each surface element in the fifth step after the dominant azimuth weighting are moved to the surface element center according to the interpolation principle; The anti-leakage Fourier transform formula is: f u (x l )=f(x l )-f k (x l ), where k is: frequency domain component, x l is: spatial non-uniform sampling point position, f(x l ) is: x l The signal value at is the spectrum corresponding to the signal, N is the number of non-uniform sample points, ΔX is the maximum space, Δx l is: spatial sampling interval, f k (x l ) is: time domain seismic data, f u (x l ) is: seismic data after iterative subtraction in time domain.

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