A method for velocity modeling of surface layer azimuthal anisotropic medium

Abstract

The application discloses a method for modeling surface layer azimuth anisotropy medium velocity, which comprises the following steps: CMP gather signal-to-noise ratio improvement processing, TTI full-azimuth common reflection angle gather target line grid point migration, identification and determination of orthorhombic layer bottom boundary, establishment of orthorhombic medium parameter model and the like. The application considers the influence of azimuth anisotropy in surface layer velocity modeling, and has higher precision in surface layer velocity modeling. The application is suitable for media with azimuth anisotropy phenomenon in the surface layer, and the method can improve the precision of the surface layer velocity model, is favorable for further iteration of the depth migration velocity model, and improves the imaging effect of the medium and deep layers.

Description

Technical Field

[0001] This invention belongs to the field of petroleum exploration technology and relates to the problem of surface orientation anisotropy in anisotropic pre-stack depth migration modeling. Specifically, it is a method for velocity modeling of surface orientation anisotropic media. Background Technology

[0002] As seismic exploration and development deepen, the requirements for imaging accuracy are becoming increasingly stringent. Seismic migration imaging methods have evolved from the isotropic medium assumption to the anisotropic medium assumption. Tilted transverse isotropic (TTI) pre-stack depth migration typically yields flatter common-point gathers, improving image focusing and significantly reducing well-seismic errors. However, in thin-layered media, the presence of significant cracks caused by tectonic stress or stress inhomogeneity can lead to directional changes in seismic wave propagation velocity, or azimuth anisotropy. In such cases, TTI migration cannot address the azimuth-varying residual depth differences appearing in different azimuths within the imaging gathers. This type of medium typically requires description using orthorhombic crystal systems.

[0003] Current research in several regions of western China has revealed severe azimuthal anisotropy in the surface layer. This anisotropy manifests as that of HTI media, but the intensity of anisotropy (the velocity ratio between the two directions) far exceeds the range of typical HTI media. In these regions, surface velocity models derived from first arrivals in different azimuthals vary significantly, hindering surface modeling in pre-stack depth migration.

[0004] The micro-logging-constrained omnidirectional first-arrival tomography surface inversion method can initially solve the problem of inconsistent first-arrival inversion results in different directions. However, the inverted surface velocity can only represent the near-vertical propagation velocity of seismic waves in the surface layer, and the difference in the propagation velocity of seismic waves in different azimuths has not yet been resolved. Especially when there is a very thick azimuthally anisotropic medium in the surface layer, the calculation of seismic wave travel time has a large error, which seriously affects the quality of migration imaging. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention aims to provide a velocity modeling method for surface-oriented anisotropic media, thereby eliminating the influence of surface-oriented anisotropy, improving surface processing accuracy, and enhancing mid-to-deep imaging performance.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for modeling velocities in a surface anisotropic medium, comprising the following steps performed sequentially:

[0008] S1. Offset pre-gathering to improve signal-to-noise ratio processing;

[0009] S2. Collect the layer velocities along the symmetry axis and the Thomson anisotropic parameters δ, ε, dip angle, and azimuth angle field obtained from TTI anisotropic modeling;

[0010] S3. Perform TTI all-round common reflection angle gather target line migration on the pre-migration gather with improved signal-to-noise ratio, layer velocity, δ, ε, dip angle and azimuth angle fields along the symmetry axis;

[0011] S4. Analyze the azimuth anisotropy on the TTI all-round common reflection angle gather after offset, determine the bottom boundary depth of the surface orthorhombic crystal system layer, and pick the layer at that depth on the depth domain post-stack data volume.

[0012] S5. Pick up the azimuth remaining depth difference along the layer on the TTI all-round common reflection angle gather after offset, and obtain the anisotropic parameters of the orthogonal crystal system layer by calculation;

[0013] S6. Use the anisotropy parameters of the obtained orthorhombic crystal system layers to perform orthorhombic crystal system shift.

[0014] As a limitation, in step S1, the signal-to-noise ratio after the signal-to-noise ratio enhancement process is greater than or equal to 1.

[0015] As another limitation, in step S3, the target line is the location of spatially discrete grid points, and the interval between grid points is less than or equal to 400 meters.

[0016] As a third limitation, step S5 includes the following steps performed sequentially:

[0017] S51. Pick up the remaining delayed RMOs of the layer along the bottom boundary of the surface orthorhombic layer on the offset TTI all-around common reflection angle gather;

[0018] S52. Calculate the residual NMO velocity ratio α in the fast direction using RMOs. fast The ratio of the remaining NMO velocity in the slow direction to α slow The azimuth angle φ corresponding to the slow direction slow ;

[0019] S53. Ratio of the remaining NMO velocity in the fast direction to α fast The ratio of the remaining NMO velocity in the slow direction to α slow Converting to orthorhombic layered fast-direction NMO velocity VNMO fast Slow-direction NMO velocity VNMO slow ;

[0020] S54. According to VNMO fast VNMO slowThe anisotropy parameters δ1 in the fast direction and δ2 in the slow direction are obtained.

[0021] S55. Obtain δ3 based on δ1 and δ2;

[0022] The δ3 = sqrt(δ1xδ2) or 0;

[0023] S56. Based on δ1 and δ2, obtain the horizontal anisotropy parameter ε1 in the fast direction and the horizontal anisotropy parameter ε2 in the slow direction.

[0024] As a fourth limitation, in step S6, the anisotropy parameter includes φ. slow , δ1, δ2, δ3, ε1 and ε2.

[0025] By adopting the above-described technical solution, the beneficial effects achieved by this invention compared to the prior art are as follows:

[0026] ① The velocity modeling method for surface anisotropic media provided by this invention uses orthogonal crystal system modeling to model the surface, which can thoroughly solve the anisotropy problem of the surface medium, eliminate the influence of the orientation anisotropy of the surface medium, and improve the imaging quality of the surface and middle-deep layers.

[0027] ② The surface orientation anisotropic medium velocity modeling method provided by this invention forms a complete technical process and provides a specific technical solution for pre-stack depth migration anisotropic velocity modeling in similar regions.

[0028] This invention is applicable to velocity modeling of media with azimuth anisotropy on the surface. Attached Figure Description

[0029] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0030] Figure 1 It is an orthorhombic crystal system medium model;

[0031] Figure 2 This is the omnidirectional common reflection angle gather for the test area in this embodiment of the invention;

[0032] Figure 3 This invention presents an example of anisotropy phenomenon and analysis of the omnidirectional common reflection angle gather.

[0033] Figure 4 This is the bottom boundary of the surface orthorhombic crystal system medium model picked up in the embodiments of the present invention;

[0034] Figure 5 is a comparison diagram of the gathers before and after orthogonal crystal system shift in an embodiment of the present invention. Figure 5a For orthorhombic crystal system shift pre-gathering, Figure 5bFor orthorhombic crystal system shifted gathers;

[0035] Figure 6 is a comparison of the offset cross-sections before and after the orthogonal crystal system offset in an embodiment of the present invention. Figure 6a This is a cross-sectional view before orthorhombic crystal system shift. Figure 6b This is a cross-sectional view after the orthorhombic crystal system has been shifted. Detailed Implementation

[0036] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and understanding only and are not intended to limit the present invention.

[0037] An embodiment of a velocity modeling method for surface-oriented anisotropic media

[0038] This embodiment describes a velocity modeling method for surface azimuth anisotropic media conducted in a test area on the southern margin of the Junggar Basin. The orthorhombic crystal system medium model is as follows: Figure 1 As shown;

[0039] Where Vpo is the vertical velocity of the P-wave; ε2 is the VTI parameter ε on the symmetry plane [x1,x3]; δ2 is the VTI parameter δ on the symmetry plane [x1,x3]; ε1 is the VTI parameter ε on the symmetry plane [x2,x3]; δ1 is the VTI parameter δ on the symmetry plane [x2,x3]; and δ3 is the VTI parameter δ on the symmetry plane [x1,x2].

[0040] In this embodiment, the omnidirectional common reflection angle collection of the test area is as follows: Figure 2 As shown, the anisotropy phenomenon and analysis of the omnidirectional common reflection angle gather are as follows: Figure 3 As shown;

[0041] Depend on Figure 2 It can be seen that there is obvious azimuth anisotropy in the shallow layer of the all-around common reflection angle gather in this test area; from Figure 3 It can be seen that the surface velocity in the east-west direction (azimuth angles of 90 degrees and 270 degrees) of the test area is slower than that in the north-south direction (azimuth angles of 180 degrees and 360 degrees).

[0042] This embodiment includes the following steps performed sequentially:

[0043] S1. Improve CMP gather signal-to-noise ratio processing

[0044] The signal-to-noise ratio (SNR) of the pre-offset CMP gathers, which has an SNR of 0.5-1, is improved to 2-4.

[0045] S2. Collect the depth domain layer velocity along the symmetry axis obtained from TTI anisotropic modeling, as well as the Thomson anisotropic parameters δ, ε, dip angle, and azimuth angle fields, such as... Figure 3As shown, the layer velocity along the axis of symmetry is 3200 m / s, δ is 0.02, ε is 0.03, the dip angle is 5 degrees, and the azimuth field is 35 degrees.

[0046] S3. The target line of the CMP gather with improved signal-to-noise ratio, velocity, δ, ε, tilt angle and azimuth angle field along the axis of symmetry is offset by TTI all-round common reflection angle gather, where the density of the target line is 200m x 200m;

[0047] S4. Azimuth anisotropy on the TTI omnidirectional common reflection angle gather after reference offset, picking the bottom boundary of the orthorhombic crystal layer on the depth-domain post-stack data volume, such as Figure 4 As shown;

[0048] S51. Pick the residual moveouts (RMOs) of the layer along the defined orthogonal crystal system surface bottom boundary on the TTI all-round common reflection angle gather after offset, and obtain the RMO range of -35 m to 35 m;

[0049] S52. Calculate the residual NMO velocity ratio α in the fast direction using RMOs. fast The residual NMO velocity ratio in the slow direction is 0.06. slow The azimuth angle φ corresponding to the slow direction is 0.025. slow It is 90 degrees;

[0050] S53. Ratio of the remaining NMO velocity in the fast direction to α fast The ratio of the remaining NMO velocity in the slow direction to α slow Converting to orthorhombic layered fast-direction NMO velocity VNMO fast The speed is 3400 m / s, and the slow-direction NMO velocity is VNMO. slow It is 3280 m / s;

[0051] S54. According to VNMO fast VNMO slow The anisotropy parameter δ1 in the fast direction is 0.064, and the anisotropy parameter δ2 in the slow direction is 0.023.

[0052] S55. Based on δ1 and δ2, the horizontal anisotropy parameter ε1 in the fast direction is 0.164 and the horizontal anisotropy parameter ε2 in the slow direction is 0.123. Based on experience, δ3 is taken as 0.

[0053] S6. Orthogonal crystal system shift was performed using the obtained orthogonal crystal system parameters, and the results are shown in Figures 5 and 6.

[0054] Figure 5 shows a comparison of the gathers before and after the orthorhombic shift, and Figure 6 shows a cross-sectional comparison before and after the orthorhombic shift.

[0055] As shown in Figures 5 and 6, the collection and profile quality of the shallow and overlying strata were greatly improved by eliminating the influence of surface azimuth anisotropy.

Claims

1. A method of velocity modeling for surface layer azimuthal anisotropy media, characterized in that, The method comprises the following steps in sequence: S1. SNR improvement processing of pre-migration gathers; S2. collecting the layer velocity in the direction of the symmetry axis and the Thomson anisotropy parameters δ, ε, dip angle and azimuth angle field obtained by TTI anisotropy modeling; S3. performing TTI full-azimuth common reflection angle target line migration on the pre-migration gathers after SNR improvement processing, the layer velocity in the direction of the symmetry axis, δ, ε, dip angle and azimuth angle field; S4. analyzing the azimuthal anisotropy phenomenon on the migrated TTI full-azimuth common reflection angle gathers, determining the bottom boundary depth of the surface orthorhombic layer, and picking up the depth horizon on the depth domain stacked data volume; S5. picking up the azimuthal residual depth difference along the layer on the migrated TTI full-azimuth common reflection angle gathers, and obtaining the anisotropy parameters of the orthorhombic layer by calculation; S6. performing orthorhombic migration by using the obtained anisotropy parameters of the orthorhombic layer.

2. The method of claim 1, wherein: In step S1, the SNR after SNR improvement processing is greater than or equal to 1.

3. The method of claim 1, wherein: In step S3, the target line is a spatially discrete grid point position, and the interval of the grid points is less than or equal to 400 meters.

4. The method of claim 1, wherein: The step S5 comprises the following steps in sequence: S51. picking up the residual delay RMOs of the layer along the bottom boundary of the surface orthorhombic layer on the migrated TTI full-azimuth common reflection angle gathers; S52. Calculate the fast direction residual NMO velocity ratio a with RMOs fast , the slow direction residual NMO velocity ratio a slow , and the azimuth angle φ slow corresponding to the slow direction S53. Convert the fast direction residual NMO velocity ratio a fast to the slow direction residual NMO velocity ratio a slow to the fast direction NMO velocity VNMO fast of the orthorhombic layer slow ; S54. According to VNMO fast , VNMO slow obtain the anisotropy parameter δ1 of the fast direction, the anisotropy parameter δ2 of the slow direction; S55. obtaining δ3 according to δ1 and δ2; The δ3=sqrt(δ1xδ2) or 0; S56. obtaining the horizontal anisotropy parameter ε1 of the fast direction and the horizontal anisotropy parameter ε2 of the slow direction according to δ1 and δ2.

5. The method of claim 1-4, wherein: The anisotropy parameters in the step S6 include φ slow , δ1, δ2, δ3, ε1, and ε2.

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