阅读说明：本技术 深度域成像模拟方法及系统 (Depth domain imaging simulation method and system ) 是由 张建磊 慕文韬 王成祥 岳玉波 钱忠平 张超阳 于 2020-05-29 设计创作，主要内容包括：本发明提供一种深度域成像模拟方法及系统。该深度域成像模拟方法包括：将初始密度模型划分为窗口,在各个窗口中设置密度扰动点；根据密度扰动点影响下的初始密度模型确定扰动点密度模型；根据扰动点密度模型和初始密度模型得到点散射波场数据；对点散射波场数据进行偏移处理,得到点扩散函数；根据点扩散函数和反射率模型得到深度域模拟成像。本发明可以得到与实际偏移成像匹配且稳定连续的模拟成像。(The invention provides a depth domain imaging simulation method and system. The depth domain imaging simulation method comprises the following steps: dividing the initial density model into windows, and setting density disturbance points in each window; determining a density model of the disturbance point according to the initial density model under the influence of the density disturbance point; obtaining point scattering wave field data according to the disturbance point density model and the initial density model; carrying out migration processing on the point scattering wave field data to obtain a point diffusion function; and obtaining depth domain simulation imaging according to the point spread function and the reflectivity model. The invention can obtain stable and continuous analog imaging matched with actual offset imaging.)

1. A depth-domain imaging simulation method, comprising:

dividing the initial density model into windows, and setting density disturbance points in each window;

determining a density model of the disturbance point according to the initial density model under the influence of the density disturbance point;

obtaining point scattering wave field data according to the disturbance point density model and the initial density model;

carrying out migration processing on the point scattering wave field data to obtain a point spread function;

and obtaining depth domain simulation imaging according to the point spread function and the reflectivity model.

2. The depth-domain imaging simulation method of claim 1, wherein deriving point-scattered wavefield data from the perturbation point density model and the initial density model comprises:

obtaining first seismic data according to a preset velocity model and the disturbance point density model, and obtaining second seismic data according to the velocity model and the initial density model;

and obtaining point scattering wave field data according to the first seismic data and the second seismic data.

3. The depth-domain imaging simulation method of claim 1, wherein obtaining the depth-domain simulated imaging from the point spread function and the reflectivity model comprises:

carrying out spatial interpolation on the point spread function to obtain a point spread function subjected to spatial interpolation;

and performing spatial convolution according to the point spread function subjected to spatial interpolation and the reflectivity model to obtain depth domain simulation imaging.

4. The depth-domain imaging simulation method of claim 2, wherein obtaining the first seismic data according to the preset velocity model and the disturbance point density model comprises:

obtaining first single scattering wave field data according to the speed model and the disturbance point density model;

and obtaining first seismic data according to the first single scattering wave field data.

5. The depth domain imaging simulation method of claim 2, wherein obtaining second seismic data from the velocity model and the initial density model comprises:

obtaining second single scattering wave field data according to the speed model and the initial density model;

and obtaining second seismic data according to the second single scattering wave field data.

6. A depth domain imaging simulation system, comprising:

the density disturbance point setting unit is used for dividing the initial density model into windows and setting density disturbance points in each window;

the disturbance point density model unit is used for determining a disturbance point density model according to the initial density model under the influence of the density disturbance points;

the point scattering wave field data unit is used for obtaining point scattering wave field data according to the disturbance point density model and the initial density model;

the migration unit is used for carrying out migration processing on the point scattering wave field data to obtain a point spread function;

and the depth domain simulation imaging unit is used for obtaining depth domain simulation imaging according to the point spread function and the reflectivity model.

7. The depth-domain imaging simulation system of claim 6, wherein the point-scatter wave field data unit is specifically configured to:

obtaining first seismic data according to a preset velocity model and the disturbance point density model, and obtaining second seismic data according to the velocity model and the initial density model;

and obtaining point scattering wave field data according to the first seismic data and the second seismic data.

8. The depth-domain imaging simulation system of claim 6, wherein the depth-domain simulation imaging unit is specifically configured to:

carrying out spatial interpolation on the point spread function to obtain a point spread function subjected to spatial interpolation;

and performing spatial convolution according to the point spread function subjected to spatial interpolation and the reflectivity model to obtain depth domain simulation imaging.

9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the depth domain imaging simulation method of any of claims 1 to 5 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the depth domain imaging simulation method of any one of claims 1 to 5.

Technical Field

The invention relates to the technical field of seismic data imaging, in particular to a depth domain imaging simulation method and system.

Background

The traditional method for simulating migration imaging in seismic inversion is to perform one-dimensional convolution in a time domain, and the method is based on the approximation of horizontal stratigraphic assumption and time migration data and does not consider the influence of a 3D complex medium on seismic wave propagation. In a complex medium, due to the influence of an offset algorithm, a geological model and irregular acquisition, the whole waveform propagation process is not perfectly reversible, so that the method is difficult to obtain a satisfactory inversion result. As oil and gas exploration extends into deep complex geological structures, conventional seismic migration inversion methods face a number of challenges, such as amplitude preservation imaging, salt dome bottom imaging, and the like. New methods are continuously developed for these problems, such as least squares migration and full waveform inversion.

The current least squares inversion is mainly performed in the data domain, and the iterative process is as follows: and shifting the observation data to obtain reflectivity imaging, performing reverse shifting on the reflectivity imaging to obtain simulation data, subtracting the observation data from the simulation data, and shifting the residual error to update the reflectivity model, thereby forming an iteration. Typically, about 15 iterations are required to obtain an acceptable solution. This can result in expensive production because each iteration requires two offsets (offset and anti-offset). Instead of solving directly in the data domain with least squares iterations, many authors have attempted to find a standard filter/weighting function that processes offset imaging to compensate for the effects of irregular illumination and acquisition, such as: 1. the least square reverse time migration of an image domain is originated from a deconvolution operator of a Hubby telescope at the earliest time, the deconvolution operator can be introduced into the post-stack migration, and inversion is carried out by approaching a Hessian operator in geophysical exploration to improve the spatial resolution and reduce artifacts; 2. approximating diagonal elements of the Hessian matrix to compute illumination compensation, the method estimating illumination from a ratio of an initial reference model to offset synthetic data; 3. the inverse Hessian function can be approximated with a set of non-stationary filters by matching the offset imaging and the anti-offset imaging of the real data; 4. and constructing an approximate acoustic linear inversion system through filtering and scale deviation output. Although these methods reduce computational cost, there is still a problem of instability in the case of insufficient lighting, and it is difficult to design a suitable regularization scheme.

Disclosure of Invention

The present invention provides a method and a system for simulating a degree domain imaging, so as to obtain a stable and continuous simulated imaging matched with an actual offset imaging.

In order to achieve the above object, an embodiment of the present invention provides a depth domain imaging simulation method, including:

dividing the initial density model into windows, and setting density disturbance points in each window;

determining a density model of the disturbance point according to the initial density model under the influence of the density disturbance point;

obtaining point scattering wave field data according to the disturbance point density model and the initial density model;

carrying out migration processing on the point scattering wave field data to obtain a point diffusion function;

and obtaining depth domain simulation imaging according to the point spread function and the reflectivity model.

The embodiment of the present invention further provides a depth domain imaging simulation system, including:

the density disturbance point setting unit is used for dividing the initial density model into windows and setting density disturbance points in each window;

the disturbance point density model unit is used for determining a disturbance point density model according to the initial density model under the influence of the density disturbance points;

the point scattering wave field data unit is used for obtaining point scattering wave field data according to the disturbance point density model and the initial density model;

the migration unit is used for performing migration processing on the point scattering wave field data to obtain a point diffusion function;

and the depth domain simulation imaging unit is used for obtaining depth domain simulation imaging according to the point spread function and the reflectivity model.

The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of the depth domain imaging simulation method are implemented.

Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the depth domain imaging simulation method.

According to the depth domain imaging simulation method and system provided by the embodiment of the invention, density disturbance points are arranged in each window of the initial density model, then the disturbance point density model is determined according to the initial density model under the influence of the density disturbance points, then the point spread function is determined according to the disturbance point density model and the initial density model, and the depth domain simulated imaging is obtained according to the point spread function and the reflectivity model, so that the stable and continuous simulated imaging matched with the actual offset imaging can be obtained.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.

FIG. 1 is a flow chart of a depth domain imaging simulation method in an embodiment of the invention;

FIG. 2 is a schematic diagram of a velocity model in an embodiment of the invention;

FIG. 3 is a schematic diagram of a disturbance point density model and a partial enlargement thereof according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a single shot of first seismic data in an embodiment of the invention;

FIG. 5 is a schematic diagram of a single shot of second seismic data in an embodiment of the invention;

FIG. 6 is a schematic diagram of a single shot of point-scattered wavefield data in an embodiment of the invention;

FIG. 7 is a diagram of a point spread function in an embodiment of the invention;

FIG. 8 is a schematic diagram of actual offset imaging;

FIG. 9 is a schematic illustration of depth domain simulation imaging in an embodiment of the invention;

FIG. 10 is a block diagram of a depth domain imaging simulation system in an embodiment of the invention;

fig. 11 is a block diagram of a computer device in the embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.

In view of the unstable problem of the prior art, the embodiment of the invention provides a depth domain imaging simulation method to obtain stable and continuous simulation imaging matched with actual offset imaging. The present invention will be described in detail below with reference to the accompanying drawings.

Fig. 1 is a flow chart of a depth domain imaging simulation method in an embodiment of the invention. As shown in fig. 1, the depth domain imaging simulation method includes:

s101: and dividing the initial density model into windows, and setting density disturbance points in each window.