An adaptive variable-grid forward modeling method for middle-deep dry hot rock mass

Abstract

The embodiment of the specification discloses a self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass. p , a transverse wave velocity V s and a medium density p model, pre-setting forward modeling parameters; performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, and determining a wave equation under variable grid based on the mapping relationship; performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, obtaining the underground medium longitudinal wave velocity, transverse wave velocity and density after variable grid, determining a wave equation under variable grid based on the mapping relationship, and generating final regular grid horizontal direction longitudinal wave field, horizontal direction transverse wave field, vertical direction longitudinal wave field and vertical direction transverse wave field information by using the mapping relationship reversely according to the wave field information in each direction at a specific moment after the variable grid, so that the memory occupation is small and the calculation speed is faster.

Description

TECHNICAL FIELD

[0001] The present specification relates to the technical field of geothermal resource exploration, and particularly relates to a self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass. BACKGROUND

[0002] In the conventional grid forward modeling method, the horizontal and vertical grid spacings are set to specific values. If the grid spacing is too large, numerical dispersion is prone to occur in the low-velocity area, and the wave field simulation accuracy is reduced. If the grid spacing is too small, the high-velocity area is prone to oversampling, resulting in waste of computing resources and high computing cost. In addition, the conventional variable grid forward modeling method usually uses fine grids in the target area and uses coarse grids in other areas. When the simulation parameters are not reasonably selected, strong false reflections are generated in the transition area between the coarse and fine grids, thereby reducing the accuracy of the simulated wave field.

[0003] Therefore, there is a need for a self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass with faster calculation speed. SUMMARY

[0004] The self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass provided by the embodiments of the present specification solves the technical problem of needing a self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass with faster calculation speed.

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

[0006] In a first aspect, the embodiments of the present specification provide a self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass, comprising:

[0007] inputting an initial underground medium longitudinal wave velocity V p , a transverse wave velocity V s and a medium density p model, pre-setting forward modeling parameters, the parameters including: a horizontal grid point number nx, a vertical grid point number nz, an absorbing boundary size d, a horizontal grid spacing dx, a vertical grid spacing dz, a time slice number nt, a time sampling rate dt, a wavelet main frequency f m , an initial shot point position (S x , S z ), a shot spacing ds, and a total shot number ns;

[0008] performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, and determining a wave equation under variable grid based on the mapping relationship:

[0009]

[0010] wherein, v x represents the horizontal velocity of the total wave field, and vxp denotes the transverse velocity of the P-wave, v xs denotes the transverse velocity of the S-wave, v z denotes the longitudinal velocity of the total wave field, v zp denotes the longitudinal velocity of the P-wave, v zs denotes the longitudinal velocity of the S-wave, v p denotes the P-wave velocity, v s denotes the S-wave velocity, p denotes the medium density; t xx denotes the transverse normal stress suffered by the medium, t zz denotes the longitudinal normal stress and t xz denotes the shear stress suffered by the medium; is the mapping relationship between the adaptive variable grid coordinate system and the regular grid coordinate system, is a fitting function of the vertical grid spacing of the selected adaptive variable grid;

[0011] According to the P-wave velocity, S-wave velocity and density of the underground medium after the variable grid, forward modeling is performed using the dynamic equation to obtain the wave field information in each direction at a specific time after the variable grid, and the mapping relationship is used reversely to generate the final regular grid horizontal direction P-wave wave field, horizontal direction S-wave wave field, vertical direction P-wave wave field and vertical direction S-wave wave field information.

[0012] The above at least one technical solution adopted by one or more embodiments of the present specification can achieve the following beneficial effects: by inputting an initial underground medium P-wave velocity V p , S-wave velocity V s and medium density p model, setting the forward modeling parameters in advance; performing adaptive variable grid processing on the velocity model, determining the mapping relationship between the coordinate systems, and determining the wave equation under the variable grid based on the mapping relationship; performing adaptive variable grid processing on the velocity model, determining the mapping relationship between the coordinate systems, obtaining the P-wave velocity, S-wave velocity and density of the underground medium after the variable grid, determining the wave equation under the variable grid based on the mapping relationship; and using the mapping relationship reversely to generate the final regular grid horizontal direction P-wave wave field, horizontal direction S-wave wave field, vertical direction P-wave wave field and vertical direction S-wave wave field information according to the wave field information in each direction at a specific time after the variable grid. Thus, it is realized that no transition area needs to be set between different size grids, the difference format is changed, or interpolation processing is performed, which can effectively avoid the false reflection problem, and the calculation amount and computer memory occupation amount are greatly reduced, and the calculation speed is fast. The present specification provides efficient imaging guarantee for seismic data processing in the middle-deep dry hot rock body region. BRIEF DESCRIPTION OF DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present specification or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0014] Figure 1 The flowchart provided by the embodiments of the present specification;

[0015] Figure 2 The adaptive variable mesh resampling method provided by the embodiments of the present specification;

[0016] Figure 3 The initial model P-wave velocity field provided by the embodiments of the present specification;

[0017] Figure 4 The initial model S-wave velocity field provided by the embodiments of the present specification;

[0018] Figure 5 The initial model medium density distribution provided by the embodiments of the present specification;

[0019] Figure 6 The P-wave velocity field after adaptive variable mesh resampling provided by the embodiments of the present specification;

[0020] Figure 7 The S-wave velocity field after adaptive variable mesh resampling provided by the embodiments of the present specification;

[0021] Figure 8 The medium density distribution after adaptive variable mesh resampling provided by the embodiments of the present specification;

[0022] Figure 9 The horizontal direction P-wave wave field information obtained by the present application provided by the embodiments of the present specification;

[0023] Figure 10 The horizontal direction S-wave wave field information obtained by the present application provided by the embodiments of the present specification;

[0024] Figure 11 The vertical direction P-wave wave field information obtained by the present application provided by the embodiments of the present specification;

[0025] Figure 12 The vertical direction S-wave wave field information obtained by the present application provided by the embodiments of the present specification;

[0026] Figure 13A comparison chart of time consumption of the conventional grid and the adaptive variable grid elastic wave forward modeling provided by the embodiments of the present specification. DETAILED DESCRIPTION

[0027] The embodiments of the present specification provide a method for adaptive variable grid forward modeling of a middle-deep dry hot rock mass.

[0028] In order to enable persons skilled in the art to better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments of the present specification, all other embodiments obtained by persons skilled in the art without creative labor should fall within the scope of protection of the present application.

[0029] As shown in Figure 1 , Figure 1 The embodiments of the present specification provide a flowchart of a method for adaptive variable grid forward modeling of a middle-deep dry hot rock mass.

[0030] Figure 1 The flow in the method can include the following steps:

[0031] S1, input initial underground medium P-wave velocity V p , S-wave velocity V s and medium density p model, and pre-set forward modeling parameters.

[0032] The parameters include: horizontal grid point number nx, vertical grid point number nz, absorption boundary size d, horizontal grid spacing dx, vertical grid spacing dz, time slice number nt, time sampling rate dt, wavelet main frequency f m , initial shot point position (S x , S z ), shot interval ds, total shot number ns, etc.

[0033] S2, performing adaptive variable grid processing on the velocity model, determining the mapping relationship between the coordinate systems, obtaining the P-wave velocity, S-wave velocity and density of the underground medium after variable grid, and determining the wave equation under variable grid based on the mapping relationship.

[0034] The adaptive variable grid method only performs variable grid resampling in the vertical direction, and the horizontal grid point number remains unchanged, so that the mapping relationship from the initial model to the resampled model can be established:

[0035]

[0036] Wherein, x vg , z vg are independent variables of the variable grid coordinate system. is the mapping from the initial model to the resampled model, according to the coordinate transformation relationship, we get

[0037] The general form of the first-order velocity-stress wave equation in the Cartesian coordinate system is:

[0038] ν x =ν xp +ν xs

[0039] ν z =ν zp +ν zs

[0040]

[0041]

[0042]

[0043]

[0044]

[0045]

[0046]

[0047] By using the adaptive variable mesh principle, it can be modified into the form in the variable mesh coordinate system:

[0048]

[0049] wherein, ν x represents the transverse velocity of the total wave field, ν xp represents the transverse velocity of the longitudinal wave, ν xs represents the transverse velocity of the transverse wave, ν z represents the longitudinal velocity of the total wave field, ν zp represents the longitudinal velocity of the longitudinal wave, ν zs represents the longitudinal velocity of the transverse wave, v p represents the longitudinal wave velocity, v s represents the transverse wave velocity, and ρ represents the medium density size; τ xx represents the transverse normal stress of the medium, τ zz represents the longitudinal normal stress of the medium, and τ xz represents the shear stress of the medium. is the mapping relationship between the adaptive variable mesh coordinate system and the conventional mesh coordinate system, is the fitting function of the selected vertical grid spacing of the adaptive variable mesh.

[0050] Further, when the above speed model is processed by adaptive variable grid principle, the lateral grid interval is kept unchanged, and the new longitudinal grid interval varying with depth is calculated by the following formula:

[0051]

[0052] The initial speed field is adaptively resampled according to the new longitudinal grid interval varying with depth, to obtain a resampled migration speed field, including the variable grid underground medium P-wave speed, S-wave speed and density.

[0053] S3, according to the variable grid underground medium P-wave speed, S-wave speed and density, the dynamic equation is used for forward modeling to obtain the wave field information in each direction at a specific time after the grid is changed.

[0054] According to the above variable grid P-wave and S-wave speed model, the first-order speed-stress wave equation in the variable grid coordinate system is derived and discretized by finite difference. The first-order speed-stress decoupling elastic wave equation is run for forward modeling to obtain the wave field information in each direction at a specific time after the grid is changed, including horizontal direction P-wave field, horizontal direction S-wave field, vertical direction P-wave field and vertical direction S-wave field.

[0055] S4, according to the wave field information in each direction at a specific time after the grid is changed, the mapping relationship is reversely used to generate the final regular grid horizontal direction P-wave field, horizontal direction S-wave field, vertical direction P-wave field and vertical direction S-wave field information.

[0056] By inputting the initial underground medium P-wave speed V p , S-wave speed V s and medium density p model, the forward modeling parameters are pre-set; the speed model is adaptively processed by variable grid to determine the mapping relationship between coordinate systems, and the wave equation under variable grid is determined based on the mapping relationship; the speed model is adaptively processed by variable grid to determine the mapping relationship between coordinate systems, and the variable grid underground medium P-wave speed, S-wave speed and density are obtained, and the wave equation under variable grid is determined based on the mapping relationship; according to the wave field information in each direction at a specific time after the grid is changed, the mapping relationship is reversely used to generate the final regular grid horizontal direction P-wave field, horizontal direction S-wave field, vertical direction P-wave field and vertical direction S-wave field information. Thus, without setting transition area, changing difference format or performing interpolation processing, the false reflection problem can be effectively avoided, the calculation amount and computer memory occupation amount can be greatly reduced, and the calculation speed is fast. The high-efficiency imaging guarantee is provided for seismic data processing of middle-deep dry hot rock body region.

[0057] The following gives a description of the actual effect of the embodiment in the model.

[0058] The technical method contained in the present application is applied to the forward modeling of the middle-deep dry hot rock model, and good results are obtained. Figure 3 , Figure 4 and Figure 5 The initial horizontal and vertical grid spacings are both 10 meters; a 20Hz main frequency Rayleigh wave is selected as the source; a single shot is placed at the center of the upper boundary (401, 0); the number of sampling points within the shortest wavelength is set to 10 to ensure sampling accuracy. Then, the new depth-varying vertical grid spacing is calculated, and the initial model is adaptively resampled according to the new depth-varying vertical grid spacing (the sampling principle is shown in Figure 2 ). Figure 6 , Figure 7 and Figure 8 .

[0059] After adaptive variable grid resampling, the horizontal grid points of the velocity field remain unchanged, and the vertical grid points are reduced from 401 to 319, a reduction of 20.45%. The percentage reduction in grid points indicates that the present application can reduce the dimension of the processed velocity field, thereby reducing the calculation memory, and the percentage reduction in memory is the same as the percentage reduction in grid points, both being 20.45%.

[0060] Forward modeling requires solving the first-order velocity-stress wave equation, and the present application uses finite difference spatial eight-order accuracy to solve the first-order velocity-stress wave equation.

[0061] To illustrate the advantages of the technical scheme of the present application, the adaptive variable grid elastic wave forward modeling method of the present application and the conventional grid elastic wave forward modeling method are used for middle-deep dry hot rock numerical simulation, both with an order of eight. Figure 9 , Figure 10 , Figure 11 and Figure 12 are the final simulation results of the adaptive variable grid elastic wave forward modeling method for middle-deep dry hot rock bodies of the present application, from which the wave field information of P and S waves in the horizontal and vertical directions can be seen.

[0062] Compared with the conventional grid finite difference elastic wave forward method, the adaptive variable grid elastic wave forward modeling method of the present application can obtain the same accuracy of wave field information results, but the memory occupation during the calculation process of the present application scheme is only 20.45% of the former.

[0063] Figure 13The figure is a comparison chart of time consumption of conventional grid and adaptive variable grid elastic wave forward simulation, the finite difference elastic wave forward simulation method of the conventional grid consumes 513.66s, and the adaptive variable grid elastic wave forward simulation method of the present application for the middle-deep dry hot rock consumes only 384.76s, which is 25.09% of the former. It can be seen from the result that the forward simulation method of the present application can greatly improve the calculation efficiency, reduce the calculation time consumption, and save the calculation cost.

[0064] Correspondingly, the present application also provides a multi-thread parallel computer device, which comprises a processor, a memory, a display card and the like, and a computer C language program which can be successfully run on the processor, wherein the processor implements the method of the adaptive variable grid elastic wave forward simulation method for the middle-deep dry hot rock when executing the program.

[0065] Each embodiment in the specification is described in a progressive manner, and the same and similar parts between each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments. Especially, the device, equipment and non-volatile computer storage medium embodiments are basically similar to the method embodiments, so the description is relatively simple, and the related parts can be referred to the part of the method embodiment.

[0066] The above describes the specific embodiments of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be executed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0067] The above only describes one or more embodiments of the specification and does not limit the specification. One or more embodiments of the specification can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement and the like within the spirit and principle of one or more embodiments of the specification shall be included in the scope of claims of the specification.

Claims

1. An adaptive variable grid forward modeling method for a middle-deep dry hot rock mass, comprising: Input initial subsurface medium P-wave velocity V p , S-wave velocity V s and medium density p model, preset forward simulation parameters, which include: horizontal grid point number nx, vertical grid point number nz, absorbing boundary size d, horizontal grid interval dx, vertical grid interval dz, time slice number nt, time sampling rate dt, wavelet main frequency f m , initial shot point position (S x , S z ), shot interval ds, total shot number ns; performing adaptive variable grid processing on a velocity model, determining a mapping relationship between coordinate systems, obtaining underground medium P-wave velocity, S-wave velocity and density after variable grid processing, and determining a wave equation under variable grid processing based on the mapping relationship: wherein, v x represents the transverse velocity of the total wave field, v xp represents the transverse velocity of the longitudinal wave, v xs represents the transverse velocity of the transverse wave, v z represents the longitudinal velocity of the total wave field, v zp represents the longitudinal velocity of the longitudinal wave, v zs represents the longitudinal velocity of the transverse wave, v p represents the longitudinal wave velocity, v s represents the transverse wave velocity, and p represents the medium density; τ xx represents the transverse normal stress received by the medium, τ zz represents the longitudinal normal stress received by the medium, and τ xz represents the shear stress received by the medium; is the mapping relationship between the adaptive variable mesh coordinate system and the conventional mesh coordinate system, is a fitting function of the vertical mesh interval of the selected adaptive variable mesh. performing forward modeling using the wave equation according to the underground medium P-wave velocity, S-wave velocity and density after variable grid processing to obtain wave field information in each direction at a specific time after variable grid processing; generating final regular grid horizontal direction P-wave wave field, horizontal direction S-wave wave field, vertical direction P-wave wave field and vertical direction S-wave wave field information using the mapping relationship in reverse according to the wave field information in each direction at the specific time after variable grid processing.

2. The method of claim 1, wherein, performing adaptive variable grid processing on the velocity model, comprising: Adaptive mesh refinement is performed in the following manner, where x vg is the horizontal direction independent variable of the adaptive mesh refinement coordinate system, and z vg is the vertical direction independent variable of the adaptive mesh refinement coordinate system.

3. The method of claim 2, wherein, performing adaptive variable grid processing on the velocity model, comprising: The new depth-varying vertical grid spacing is calculated using the following equation, keeping the lateral grid spacing constant where f represents the dominant frequency of the Ricker wavelet, n is the number of grid points per seismic wavelength, and the initial velocity field is adaptively resampled to obtain the resampled migration velocity field v pmin (z) represents the minimum velocity value of the depth velocity field in the vertical direction.

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