A geothermal rock mass elastic wave reverse time migration method based on adaptive variable mesh

Abstract

The embodiment of the specification discloses a geothermal rock mass elastic wave reverse time migration method based on adaptive variable grid. By inputting the migration velocity model and seismic record of the geothermal rock mass, and setting the imaging parameters, the seismic wave is generated according to the migration velocity model, the seismic record and the imaging parameters; the migration velocity model is adaptively processed by variable grid, the mapping relationship between the coordinate systems is determined, and the wave equation under the variable grid is determined based on the mapping relationship; according to the wave equation, the reverse time continuation of the wave field of the receiver point wave field is carried out in the variable grid along the time reverse propagation direction, and the reverse continuation wave field is generated; the cross-correlation imaging condition is used for the forward continuation wave field and the reverse continuation wave field, the reverse time migration profile under the variable grid is generated, and the imaging result under the variable grid is obtained by stacking; the imaging result is reversely processed by the variable grid according to the mapping relationship, and the reverse time migration imaging result in the conventional coordinate system is obtained; thereby the memory occupation is reduced, and the calculation is fast.

Description

Technical Field

[0001] This specification relates to the field of geothermal resource exploration technology, and in particular to a method for reverse time migration of elastic waves in geothermal rock masses based on adaptive variable grids. Background Technology

[0002] Reverse time migration (RTM) imaging is a crucial step in seismic data processing within the field of seismic exploration and development. The accuracy and efficiency of RTM imaging directly impact the effectiveness and cost of seismic data processing. Furthermore, with the continuous development of seismic exploration in my country, the amount of data acquired through seismic data acquisition is constantly increasing. Therefore, how to significantly improve computational efficiency while ensuring imaging accuracy is a significant challenge facing my country's exploration and development sector.

[0003] Therefore, a reverse time migration imaging method is needed that can improve computational efficiency while ensuring imaging accuracy. Summary of the Invention

[0004] This specification provides an embodiment of an elastic wave reverse-time migration method for geothermal rock masses based on adaptive variable grids, in order to solve the following technical problem: the need for a reverse-time migration imaging method that can improve computational efficiency while ensuring imaging accuracy.

[0005] To solve the above-mentioned technical problems, one or more embodiments of this specification are implemented as follows:

[0006] In a first aspect, embodiments of this specification provide a method for reverse-time migration of elastic waves in geothermal rock masses based on adaptive variable grids, comprising: inputting a migration velocity model of the geothermal rock mass and seismic records, simultaneously setting imaging parameters, and generating seismic waves based on the migration velocity model, seismic records, and imaging parameters. The imaging parameters include: the number of horizontal grid points (nx), the number of vertical grid points (nz), the size of the absorbing boundary (d), the horizontal grid spacing (dx), the vertical grid spacing (dz), the number of time slices (nt), the time sampling rate (dt), and the wavelet dominant frequency (f). m Initial firing position (S) x S z Given the shot spacing ds and the total number of shots ns, an adaptive variable mesh processing is applied to the offset velocity model to determine the mapping relationship between coordinate systems. Based on this mapping relationship, the wave equation under the variable mesh is determined.

[0007]

[0008] Where, ν x ν represents the transverse velocity of the total wave field. xp ν represents the transverse velocity of the longitudinal wave. xs Indicates the transverse velocity of a transverse wave; ν z ν represents the vertical velocity of the total wave field. zpν represents the vertical velocity of the longitudinal wave. zs This represents the vertical velocity of the transverse wave; v p V represents the longitudinal wave velocity. s τ represents the transverse wave velocity, ρ represents the density of the medium; xx τ represents the transverse normal stress acting on the medium. zz This indicates that the medium is subjected to longitudinal normal stress, τ xz This indicates that the medium is subjected to shear stress; This represents the mapping relationship between the adaptive variable mesh coordinate system and the conventional mesh coordinate system;

[0009] According to the wavefield equation, the seismic wavefield is extended along the forward propagation direction of the time axis in the variable grid, and the wavefield value at each moment is stored to generate a forward extended wavefield. According to the wavefield equation, the receiver wavefield is reverse-time extended along the backward propagation direction of time in the variable grid to generate a reverse extended wavefield. The forward and reverse extended wavefields are cross-correlation imaging conditions to generate a reverse-time migration profile under the variable grid, and the profiles are superimposed to obtain the imaging result under the variable grid. According to the mapping relationship, the imaging result is reverse-time processed using the variable grid to obtain the reverse-time migration imaging result in the conventional coordinate system.

[0010] The above-described technical solutions employed in one or more embodiments of this specification can achieve the following beneficial effects: By inputting the migration velocity model and seismic records of the geothermal rock mass, and simultaneously setting imaging parameters, seismic waves are generated based on the migration velocity model, seismic records, and imaging parameters; adaptive variable mesh processing is applied to the migration velocity model to determine the mapping relationship between coordinate systems, and the wave equation under the variable mesh is determined based on the mapping relationship; according to the wave field equation, the receiver wavefield is reverse-time extrapolated along the time-backward propagation direction in the variable mesh to generate a reverse extrapolated wavefield; cross-correlation imaging conditions are applied to the forward extrapolated wavefield and the reverse extrapolated wavefield to generate a reverse-time migration profile under the variable mesh, and the images are superimposed to obtain the imaging results under the variable mesh; the imaging results are reverse-time processed using the variable mesh according to the mapping relationship to obtain the reverse-time migration imaging results in the conventional coordinate system; thereby significantly reducing the computational load and computer memory usage, and achieving fast computation speed. This provides a high-efficiency, high-precision imaging guarantee for seismic data processing in geothermal rock mass areas, improving the quality and reliability of subsequent interpretation and drilling work. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart illustrating an embodiment of the present specification;

[0013] Figure 2 This diagram illustrates the adaptive variable grid resampling method provided in the embodiments of this specification.

[0014] Figure 3 This is a diagram of the initial model longitudinal wave velocity field provided in the embodiments of this specification;

[0015] Figure 4 This is a diagram of the initial model shear wave velocity field provided in the embodiments of this specification;

[0016] Figure 5 This is a diagram showing the initial model medium density distribution provided in the embodiments of this specification;

[0017] Figure 6 The horizontal P-wave single-shot seismic record provided in the embodiments of this specification;

[0018] Figure 7 The horizontal S-wave single-shot seismic record diagram provided in the embodiments of this specification;

[0019] Figure 8 This is a vertical P-wave single-shot seismic record provided in the embodiments of this specification;

[0020] Figure 9 Vertical S-wave single-shot seismic record diagram provided in the embodiments of this specification;

[0021] Figure 10 This is a diagram showing the horizontal PP component imaging results provided in the embodiments of this specification;

[0022] Figure 11 This is a diagram showing the horizontal PS component imaging results provided in the embodiments of this specification;

[0023] Figure 12 This is a diagram showing the vertical PP component imaging results provided in the embodiments of this specification;

[0024] Figure 13 This is a diagram showing the vertical PS component imaging results provided in the embodiments of this specification;

[0025] Figure 14 A comparison of the time consumption for reverse time migration imaging of elastic waves using a conventional grid and an adaptive variable grid. Detailed Implementation

[0026] This specification provides an embodiment of a method for reverse time migration of elastic waves in geothermal rock masses based on adaptive variable grids.

[0027] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0028] like Figure 1 As shown, Figure 1 This is a flowchart illustrating a method for reverse-time migration of elastic waves in geothermal rock masses based on an adaptive variable grid, as provided in the embodiments of this specification.

[0029] Figure 1 The process may include the following steps:

[0030] S1: Input the migration velocity model of the geothermal rock mass and the seismic record, and set the imaging parameters. Generate seismic waves based on the migration velocity model, seismic record and imaging parameters.

[0031] The pre-set imaging parameters include: number of horizontal grid points nx, number of vertical grid points nz, size of the absorption boundary d, horizontal grid spacing dx, vertical grid spacing dz, number of time slices nt, time sampling rate dt, and wavelet dominant frequency f. m Initial firing position (S) x S z (e.g., gun spacing ds, total number of guns ns).

[0032] S2, Adaptive variable mesh processing is performed on the offset velocity model to determine the mapping relationship between coordinate systems, and the wave equation under the variable mesh is determined based on the mapping relationship.

[0033] Adaptive variable meshing can resample only in the vertical direction while keeping the number of grid points in the horizontal direction unchanged. Therefore, a mapping relationship can be established from the initial model to the resampled model.

[0034]

[0035] Where, x vg ,z vg The independent variable of the variable grid coordinate system. It is the mapping from the initial model to the resampled model, obtained based on the coordinate transformation relationship.

[0036] The adaptive variable mesh processing of the velocity model includes:

[0037] Adaptive variable mesh processing is performed in the following manner. Where xvg ,z vg is the independent variable of the variable grid coordinate system.

[0038] Keeping the horizontal grid spacing constant, calculate the new, depth-varying vertical grid spacing using the following formula:

[0039]

[0040] The initial velocity field is adaptively resampled based on the new, depth-varying longitudinal grid spacing to obtain the resampled offset velocity field v. pnew ;

[0041] The mapping relationship between the Cartesian coordinate system and the variable mesh coordinate system is obtained by using the adaptive variable mesh principle, and the input parameters are transformed into the variable mesh coordinate system and the wave equation is corrected.

[0042] Using the mapping relationship between the initial offset velocity field and the new velocity field after adaptive variable mesh resampling, the new first-order velocity-stress elastic wave equation after adaptive variable mesh resampling is derived:

[0043] ν x =ν xp +ν xs

[0044] ν z =ν zp +ν zs

[0045]

[0046]

[0047]

[0048]

[0049]

[0050]

[0051]

[0052] Based on the relationship between the Lamé coefficient and velocity and density, the first-order velocity-stress decoupled elastic wave equation can be expressed as:

[0053]

[0054] Where, ν x ν represents the transverse velocity of the total wave field. xp ν represents the transverse velocity of the longitudinal wave.xs Indicates the transverse velocity of a transverse wave; ν z ν represents the vertical velocity of the total wave field. zp ν represents the vertical velocity of the longitudinal wave. zs This represents the vertical velocity of the transverse wave; v p V represents the longitudinal wave velocity. s τ represents the transverse wave velocity, ρ represents the density of the medium; xx τ represents the transverse normal stress acting on the medium. zz This indicates that the medium is subjected to longitudinal normal stress, τ xz This indicates that the medium is subjected to shear stress; This represents the mapping relationship between the adaptive variable mesh coordinate system and the regular mesh coordinate system.

[0055] S3. According to the wave field equation, the seismic wave field is extended in the direction of positive propagation along the time axis in the variable grid, and the wave field value at each moment is stored to generate a positively extended wave field.

[0056] S4. According to the wave field equation, the wave field at the receiver point is subjected to reverse time extension along the reverse propagation direction in the variable grid to generate a reverse extended wave field.

[0057] S5. Apply cross-correlation imaging conditions to the forward and reverse extended wavefields to generate a reverse time-shifted profile under a variable grid, and then superimpose them to obtain the imaging result under the variable grid.

[0058] Specifically, cross-correlation imaging can be performed using the following methods: Among them, R im (x,z) represents the imaging result under variable grid conditions, F(x,z,t) represents the forward continuation wavefield, B(x,z,t) represents the reverse continuation wavefield, and t max This represents the maximum time in the reverse extension.

[0059] Furthermore, after stacking the reverse-time offset profiles of each shot point to generate a stacked profile, the stacked profile can be filtered to obtain the filtered imaging result.

[0060] S6. Based on the mapping relationship, the imaging result is processed in reverse using variable mesh to obtain the reverse time-shifted imaging result in the conventional coordinate system.

[0061] By inputting a migration velocity model of the geothermal rock mass and seismic records, and simultaneously setting imaging parameters, seismic waves are generated based on the migration velocity model, seismic records, and imaging parameters. Adaptive variable mesh processing is applied to the migration velocity model to determine the mapping relationship between coordinate systems, and the wave equation under the variable mesh is determined based on this mapping relationship. According to the wave field equation, the receiver wavefield is reverse-time extrapolated along the backward propagation direction in the variable mesh to generate a reverse extrapolated wavefield. Cross-correlation imaging conditions are applied to the forward and reverse extrapolated wavefields to generate a reverse-time migration profile under the variable mesh, and these are superimposed to obtain the imaging result under the variable mesh. The imaging result is then reverse-time migration imaging in a conventional coordinate system by applying variable mesh processing in reverse according to the mapping relationship. This significantly reduces computational load and computer memory usage, while increasing computational speed. It provides high-efficiency and high-precision imaging support for seismic data processing in geothermal rock mass areas, improving the quality and reliability of subsequent interpretation and drilling operations.

[0062] The following description illustrates the actual effects of the embodiments in the model.

[0063] The technical methods contained in this invention were applied to imaging of geothermal rock masses, achieving good results. The imaging parameters were set as follows: the model had a grid of 801×401 points, with an initial horizontal and vertical grid spacing of 10 meters; a 20Hz dominant frequency Ricker wavelet was selected as the seismic source; a total of 21 shots were fired, with a shot interval of 40 meters; the number of sampling points within the shortest wavelength was set to 10 to ensure sampling accuracy. Next, the new depth-varying vertical grid spacing was calculated, and based on the new depth-varying vertical grid spacing, the initial model (e.g., ...) was modified. Figure 3 , Figure 4 and Figure 5 As shown) Adaptive variable mesh resampling is performed (sampling principle is as follows) Figure 2 (as shown), and the wave equation is modified.

[0064] After adaptive variable mesh resampling, the velocity field maintains 801 grid points horizontally, while the number of grid points vertically decreases from 401 to 319, a reduction of 20.45%. This percentage reduction in grid points demonstrates that the invention can reduce the dimensionality of the processed velocity field, thereby reducing computational memory usage. Furthermore, the percentage reduction in memory usage is the same as the percentage reduction in grid points, both being 20.45%.

[0065] This invention employs a modified first-order velocity-stress wave equation for forward and reverse wave field continuation (as shown in the seismic record of shot 11). Figure 6 , Figure 7 , Figure 8 and Figure 9 (As shown) and cross-correlation imaging is performed. The imaging results of each shot are superimposed and the final reverse time migration imaging result is obtained through the mapping relationship between coordinates (as shown). Figure 10 , Figure 11 , Figure 12 and Figure 13 (As shown).

[0066] To illustrate the advantages of the technical solution of this invention, the adaptive variable grid elastic wave imaging method of this invention and the conventional grid elastic wave imaging method were used to conduct imaging studies on geothermal rock masses, with the finite difference space order being eighth. Figures 10-13 The final imaging result obtained using this invention shows the imaging results of the PP and PS components in the horizontal and vertical directions, respectively.

[0067] Compared to conventional grid-based finite difference elastic wave reverse time migration imaging methods, the adaptive variable grid elastic wave reverse time migration method of this invention can obtain imaging results with the same accuracy, but the memory usage of the scheme in the calculation process of this invention is only 20.45% of that of the former.

[0068] Figure 14 This chart compares the time consumption of elastic wave reverse-time migration imaging of geothermal rock masses using conventional and adaptive variable meshes. Finite-difference elastic wave reverse-time migration imaging using a conventional mesh takes 2623.69 s, while the proposed method based on adaptive variable meshes takes only 1886.76 s, a reduction of 28.09%, approximately one-third, compared to the conventional method. The results demonstrate that the imaging method of this invention significantly improves computational efficiency, reduces computation time, and thus saves computational costs.

[0069] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for reverse-time migration of elastic waves in geothermal rock masses based on adaptive variable grids, comprising: Input the migration velocity model of the geothermal rock mass and the seismic record, and simultaneously set the imaging parameters. Generate a seismic wave based on the migration velocity model, seismic record, and imaging parameters. The imaging parameters include: number of horizontal grid points nx, number of vertical grid points nz, absorbing boundary size d, horizontal grid spacing dx, vertical grid spacing dz, number of time slices nt, time sampling rate dt, and wavelet dominant frequency f. m Initial firing position (S) x S z ), gun spacing ds, total number of guns ns; Adaptive variable mesh processing is applied to the offset velocity model to determine the mapping relationship between coordinate systems, and the wave equation under the variable mesh is determined based on the mapping relationship: Where, ν x ν represents the transverse velocity of the total wave field. xp ν represents the transverse velocity of the longitudinal wave. xs Indicates the transverse velocity of a transverse wave; ν z ν represents the vertical velocity of the total wave field. zp ν represents the vertical velocity of the longitudinal wave. zs This represents the vertical velocity of the transverse wave; v p V represents the longitudinal wave velocity. s τ represents the transverse wave velocity, ρ represents the density of the medium; xx τ represents the transverse normal stress acting on the medium. zz This indicates that the medium is subjected to longitudinal normal stress, τ xz This indicates that the medium is subjected to shear stress; This represents the mapping relationship between the adaptive variable mesh coordinate system and the conventional mesh coordinate system. The fitting function for the vertical grid spacing of the selected adaptive variable mesh; According to the wave equation, the seismic wave field is extended in the direction of positive propagation along the time axis in the variable grid, and the wave field value at each moment is stored to generate a positively extended wave field. According to the wave equation, the wave field at the detector point is reverse-time extended along the backward propagation direction in the variable grid to generate a reverse extended wave field. Cross-correlation imaging conditions are applied to the forward and reverse extended wavefields to generate a time-shifted profile under a variable grid, and the profiles are superimposed to obtain the imaging results under the variable grid. Based on the mapping relationship, the imaging results are reverse-processed using variable mesh to obtain the reverse time-shifted imaging results in the conventional coordinate system.

2. The method as described in claim 1, wherein, Adaptive variable mesh processing is applied to the velocity model, including: Adaptive variable mesh processing is performed in the following manner. Where x vg Let z be the independent variable in the horizontal direction of the variable grid coordinate system. vg The vertical direction is the independent variable of the variable grid coordinate system.

3. The method as described in claim 2, wherein, Adaptive variable mesh processing is applied to the velocity model, including: Keeping the horizontal grid spacing constant, calculate the new, depth-varying vertical grid spacing using the following formula. Where f represents the dominant frequency of the Ricker wavelet, n is the number of grid points per seismic wavelength, and adaptive resampling of the initial velocity field yields the resampled migration velocity field v. pmin (z) represents the minimum velocity value of the velocity field at each depth along the vertical direction.

4. The method of claim 1, wherein, Using cross-correlation imaging conditions on the forward and reverse extended wavefields, a reverse-time migration profile under a variable grid is generated, including: Cross-correlation imaging was performed using the following method: Among them, R im (x,z) represents the imaging result under variable grid conditions, F(x,z,t) represents the forward continuation wavefield, B(x,z,t) represents the reverse continuation wavefield, and t max This represents the maximum time in the reverse extension.

5. The method of claim 1, wherein, The imaging results obtained by superimposing the images under the variable grid include: superimposing the reverse time offset profiles of each shot point to generate a superimposed profile; and filtering the superimposed profile to obtain the filtered imaging results.

Images