CN113341456A

CN113341456A - Offset imaging method and device and electronic equipment

Info

Publication number: CN113341456A
Application number: CN202110774494.9A
Authority: CN
Inventors: 仇楚钧; 杨顶辉
Original assignee: Tsinghua University
Current assignee: Tsinghua University
Priority date: 2021-07-08
Filing date: 2021-07-08
Publication date: 2021-09-03
Anticipated expiration: 2041-07-08
Also published as: CN113341456B

Abstract

The embodiment of the invention discloses an offset imaging method, an offset imaging device and electronic equipment, wherein the method comprises the following steps: determining a target background speed parameter of each irregular grid in a target imaging area based on an interpolation method and the background speed parameter of the target imaging area; determining an adjoint wave field of the target imaging region based on the target background velocity parameter, the first slowness disturbance, the medium density, the background wave field and the observation wave field data of the irregular grid by an interrupted finite element method; determining a first gradient for updating the first slowness perturbation based on the adjoint wavefield and the background wavefield; updating the first slowness disturbance based on a preset gradient descent method and the first gradient to obtain a target slowness disturbance; and performing offset imaging on the target imaging area based on the target slowness disturbance. By the method, the imaging accuracy of the target imaging area can be improved.

Description

Offset imaging method and device and electronic equipment

Technical Field

The present invention relates to the field of computer technologies, and in particular, to an offset imaging method and apparatus, and an electronic device.

Background

Seismic exploration methods are important means for humans to acquire information in the subsurface space, where seismic migration imaging is a key step in seismic data processing. The deviation can enable the reflected wave to be accurately reset, has the characteristics of high imaging precision and wide adaptability, and can visually display the real form of the underground structure.

At present, a least square reverse time migration method based on an inversion idea can be used for performing migration imaging on an imaging area with a complex terrain structure and large surface relief through regular grid subdivision.

However, when offset imaging is performed on an imaging region where the processing surface relief is large, the trapezoidal approximation causes generation of a scattered wave, and the scattered wave affects imaging, which results in poor imaging accuracy on the imaging region.

Disclosure of Invention

The embodiment of the invention aims to provide an offset imaging method, an offset imaging device and electronic equipment, so as to solve the problem of poor imaging accuracy when offset imaging is carried out on an imaging region with a complex structure in the prior art.

To solve the above technical problem, the embodiment of the present invention is implemented as follows:

in a first aspect, an embodiment of the present invention provides an offset imaging method, where the method includes:

determining a target background speed parameter of each irregular grid in a target imaging area based on an interpolation method and the background speed parameter of the target imaging area;

determining an adjoint wave field of the target imaging region based on the target background velocity parameter, the first slowness disturbance, the medium density, the background wave field and the observation wave field data of the irregular grid by an interrupted finite element method;

determining a first gradient for updating the first slowness perturbation based on the adjoint wavefield and the background wavefield;

updating the first slowness disturbance based on a preset gradient descent method and the first gradient to obtain a target slowness disturbance;

and performing offset imaging on the target imaging area based on the target slowness disturbance.

Optionally, the determining a target background velocity parameter of each irregular grid in the target imaging region based on the interpolation method and the background velocity parameter of the target imaging region includes:

selecting four relevant points corresponding to the center points of the irregular grid based on a preset relevant point selection rule;

acquiring position coordinates and background speed parameters of each relevant point in the depth and horizontal directions;

substituting the position coordinates of each of the four relevant points in the depth and horizontal directions and the background speed parameter into a formula

Obtaining a background velocity parameter of a center point of the irregular grid, wherein,

a background velocity parameter being a center point of the irregular grid, c_i,j、c_i+1,j、c_i,j+1And c_i+1,j+1Background velocity parameters (x) for the four correlation points, respectively_i，z_j)、(x_i+1，z_j)、(x_i，z_j+1) And (x)_i+1，z_j+1) The position coordinates of the four related points are respectively;

and determining the background speed parameter of the central point of the irregular grid as a target background speed parameter of the irregular grid.

Optionally, the determining, by a discontinuous finite element method, an adjoint wavefield of the target imaging region based on the target background velocity parameter, the first slowness disturbance, the medium density, the background wavefield, and the observed wavefield data of the irregular grid comprises:

determining a background slowness of the irregular grid based on a target background velocity parameter of the irregular grid;

acquiring position coordinates of the central point of each irregular grid in the depth and horizontal directions;

determining a disturbance wave field of the target imaging region based on the background slowness of the irregular grid, the position coordinates of the center point of the irregular grid, the first slowness disturbance, the medium density and the background wave field by the discontinuous finite element method;

determining an adjoint wavefield of the target imaging region based on the location coordinates of the irregular grid center point, the perturbation wavefield, the medium density, and the observation wavefield data.

Optionally, determining a concomitant wavefield of the target imaging region based on the perturbation wavefield and the observation wavefield data, further comprises:

acquiring first observation wave field data acquired by a receiver after each seismic source in a plurality of seismic sources emits a cannon;

acquiring Gaussian distribution random numbers corresponding to the seismic sources;

substituting the Gaussian distribution random number corresponding to each seismic source and the first observation wave field data into a formula

Obtaining the observed wavefield data, wherein d_superFor said observed wave field data, ω_iFor the Gaussian-distributed random number corresponding to the ith seismic source, d_iAnd N is the number of the seismic sources.

Optionally, the determining, by the discontinuous finite element method, a disturbance wave field of the target imaging region based on the background slowness of the irregular grid, the position coordinates of the center point of the irregular grid, the first slowness disturbance, the medium density, and the background wave field includes:

substituting the background slowness of the irregular grid, the position coordinates of the center point of the irregular grid, the first slowness disturbance, the medium density and the background wave field into a formula

Obtaining a perturbed wavefield of the target imaging region, wherein (p)_s，u_s，w_s) For the disturbance wavefield, ρ is the medium density, Δ s²For the first slowness disturbance, p₀For the background wave field, s₀Is the background slowness of the irregular grid,

the target background speed parameter of the irregular grid is obtained, t is time, and (x, z) are position coordinates of the central point of the irregular grid;

the determining an adjoint wavefield of the target imaging region based on the location coordinates of the irregular grid center point, the perturbation wavefield, the medium density, and the observation wavefield data comprises:

substituting the position coordinates of the central point of the irregular grid, the disturbance wave field, the medium density and the observation wave field data into a formula

Obtaining said adjoint wavefield, wherein (p)^*，u^*，w^*) For said adjoint wavefield, (p)_obs，u_obs，w_obs) Is the observed wavefield data.

Optionally, the determining a first gradient for updating the first slowness perturbation based on the adjoint wavefield and the background wavefield comprises:

substituting the adjoint wave field and the background wave field into a formula

And obtaining the first gradient, wherein g is the first gradient, and T is the maximum recording time length.

Optionally, the offset imaging the target imaging region based on the target slowness disturbance includes:

determining, by the discontinuous finite element method, a first adjoint wavefield based on a target background velocity parameter of the irregular grid, the target slowness perturbation, the medium density, the background wavefield, and the observed wavefield data;

determining a second gradient for updating the target slowness perturbation based on the first adjoint wavefield and the background wavefield;

correcting the second gradient based on the second gradient, the first gradient and a preset attenuation coefficient;

updating the target slowness disturbance based on the preset gradient descent method and the corrected second gradient to obtain a second slowness disturbance;

and performing offset imaging on the target imaging area based on the second slowness disturbance.

In a second aspect, an embodiment of the present invention provides an offset imaging apparatus, including:

the parameter determination module is used for determining a target background speed parameter of each irregular grid in the target imaging area based on an interpolation method and the background speed parameter of the target imaging area;

a wave field determination module for determining an adjoint wave field of the target imaging region based on the target background velocity parameter, the first slowness disturbance, the medium density, the background wave field, and the observation wave field data of the irregular grid by a discontinuous finite element method;

a gradient determination module to determine a first gradient for updating the first slowness perturbation based on the adjoint wavefield and the background wavefield;

the updating module is used for updating the first slowness disturbance based on a preset gradient descent method and the first gradient to obtain a target slowness disturbance;

and the imaging module is used for carrying out offset imaging on the target imaging area based on the target slowness disturbance.

Optionally, the parameter determining module is configured to:

Optionally, the wavefield determination module is to:

Optionally, the apparatus further comprises:

the data acquisition module is used for acquiring first observation wave field data acquired by a receiver after each seismic source in the plurality of seismic sources emits a cannon seismic wave;

the data acquisition module is used for acquiring Gaussian distribution random numbers corresponding to the seismic sources;

a determining module for substituting the Gaussian distribution random number corresponding to each seismic source and the first observation wave field data into a formula

Optionally, the wavefield determination module is to:

Obtaining a perturbed wavefield of the target imaging region, wherein (p)_s，u_s，w_s) For the disturbance wavefield, ρ is the medium density, Δ s²For the first slowness disturbance, p₀For the background wave field, s₀Is that it isThe background slowness of the irregular grid is,

Optionally, the gradient location module is configured to:

Optionally, the imaging module is configured to:

In a third aspect, an embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a computer program stored on the memory and executable on the processor, where the computer program, when executed by the processor, implements the steps of the offset imaging method provided in the first aspect.

In a fourth aspect, an embodiment of the present invention provides 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 offset imaging method provided in the first aspect.

According to the technical scheme provided by the embodiment of the invention, the embodiment of the invention determines the target background speed parameter of each irregular grid in the target imaging area based on the interpolation method and the background speed parameter of the target imaging area, determines the adjoint wave field of the target imaging area based on the target background speed parameter, the first slowness disturbance, the medium density, the background wave field and the observation wave field data of the irregular grids by the discontinuous finite element method, determines the first gradient for updating the first slowness disturbance based on the adjoint wave field and the background wave field, updates the first slowness disturbance based on the preset gradient descent method and the first gradient to obtain the target slowness disturbance, and performs migration imaging on the target imaging area based on the target slowness disturbance. Therefore, by carrying out irregular grid subdivision on the target imaging area, the undulating structure of the earth surface can be better approximated, and the target program area is subjected to offset imaging in the target slowness disturbance obtained by the discontinuous finite element method, so that the influence of scattered waves caused by trapezoidal approximation can be reduced, and the imaging accuracy of the target imaging area with a complex structure is improved.

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 or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a schematic flow chart of an offset imaging method according to the present invention;

FIG. 2 is a schematic illustration of initial velocity data for a target imaging region;

FIG. 3 is a schematic representation of the results of an irregular triangulation of a target imaging region according to the present invention;

FIG. 4 is a schematic flow chart of another offset imaging method of the present invention;

FIG. 5 is a schematic illustration of the imaging results of a target imaging region of the present invention;

FIG. 6 is a schematic diagram of an error curve comparison according to the present invention;

FIG. 7 is a schematic diagram of an offset imaging apparatus according to the present invention;

fig. 8 is a schematic structural diagram of an electronic device according to the present invention.

Detailed Description

The embodiment of the invention provides an offset imaging method and device and electronic equipment.

In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all 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.

Example one

As shown in fig. 1, an embodiment of the present specification provides an offset imaging method, where an execution subject of the method may be a server, and the server may be an independent server or a server cluster composed of multiple servers. The method may specifically comprise the steps of:

in S102, a target background velocity parameter for each irregular grid in the target imaging region is determined based on the interpolation method and the background velocity parameter of the target imaging region.

The target imaging area may be a field-acquired area, the background speed parameter may be determined based on initial speed data of the target imaging area, for example, the initial speed data of the target imaging area may be obtained, the initial speed data is filtered through a preset filtering algorithm (e.g., a gaussian smooth filtering algorithm) to obtain a background speed parameter of the target imaging area, the determination method of the background speed parameter may be various and may be different according to different actual application scenarios (e.g., different surface geometric configurations of the target imaging area), this is not specifically limited in this specification, the irregular mesh may be obtained by mesh-dividing the target imaging area based on a preset irregular mesh-dividing algorithm, for example, a processing mechanism of a Delaunay triangulation algorithm may be preset in the server, and the target imaging area may be subjected to irregular triangulation by the Delaunay triangulation algorithm, in addition, the method for performing irregular meshing on the target imaging area may be various, and different irregular meshing algorithms may be selected according to different terrain structures of the target imaging area, which is not specifically limited in the embodiment of the present invention.

In practice, seismic exploration methods are an important means for humans to acquire information about the subsurface space, where seismic migration imaging is a key step in seismic data processing. The deviation can enable the reflected wave to be accurately reset, has the characteristics of high imaging precision and wide adaptability, and can visually display the real form of the underground structure.

At present, a least square reverse time migration method based on an inversion idea can be used for performing migration imaging on an imaging area with a complex terrain structure and large surface relief through regular grid subdivision. However, when offset imaging is performed on an imaging region where the processing topography is large, the trapezoidal approximation causes generation of a scattered wave, which deteriorates accuracy of imaging on the imaging region. Therefore, the embodiment of the present invention provides a technical solution capable of solving the above problems, which can be specifically referred to as the following:

a plurality of different sources and receivers may be positioned at different locations within the target imaging area, and the sources may be activated to emit seismic waves and the receivers may acquire corresponding waveform record data to obtain corresponding waveform record data for each source.

Initial speed data of the target imaging area (as shown in fig. 2) can be acquired according to actual exploration data of the target imaging area, and the initial speed data of the target imaging area is input into the server, and the server can process the initial speed data based on a preset filtering algorithm to obtain a background speed parameter of the target imaging area.

The server may determine the target background velocity parameter for each irregular mesh based on the irregular mesh partitioning result as shown in fig. 3 and the background velocity parameter of the target imaging area. As can be seen from fig. 3, the subdivided irregular grid can better approximate the undulating structure of the ground surface.

The target background velocity parameter of each irregular mesh may be determined based on an interpolation method and the background velocity parameter of the target program region corresponding to each irregular mesh, for example, taking the irregular mesh as the irregular triangular mesh shown in fig. 3 as an example, the target background velocity parameter of the irregular triangular mesh may be determined based on the background velocity parameters of three vertices of the irregular triangular mesh and the interpolation method.

The method for determining the target background velocity parameter of the irregular grid may be various, and may be different according to different actual application scenarios, and this is not specifically limited in the embodiments of the present specification.

In S104, determining an adjoint wave field of the target imaging region by a discontinuous finite element method based on the target background velocity parameter, the first slowness disturbance, the medium density, the background wave field and the observation wave field data of the irregular grid.

In implementation, the server may forward simulate the target background velocity parameter, the first slowness perturbation, the medium density, the background wavefield, and the observed wavefield data of the irregular grid by a discontinuous finite element method to determine an adjoint wavefield of the target imaging region.

In S106, a first gradient for updating the first slowness perturbation is determined based on the adjoint wavefield and the background wavefield.

In an implementation, the server may determine a first gradient for updating the first slowness perturbation by an adjoint wavefield corresponding to each time in the maximum recording duration and a background wavefield.

In S108, the first slowness disturbance is updated based on the preset gradient descent method and the first gradient, so as to obtain a target slowness disturbance.

In an implementation, for example, the server may update the first slowness disturbance based on a preset search step and the first gradient to obtain a target slowness disturbance.

In S110, a target imaging region is offset imaged based on the target slowness perturbation.

In implementation, the server can perform offset imaging on the target imaging area based on the obtained target slowness disturbance, so that the imaging accuracy of the target imaging area with complex structure (especially severe surface relief) can be improved, and the imaging definition of the near-surface structure and the middle-deep structure can be improved.

The embodiment of the invention provides a migration imaging method, which is characterized by determining a target background speed parameter of each irregular grid in a target imaging area based on an interpolation method and a background speed parameter of the target imaging area, determining an accompanying wave field of the target imaging area based on the target background speed parameter, first slowness disturbance, medium density, a background wave field and observation wave field data of the irregular grids by using a discontinuous finite element method, determining a first gradient for updating the first slowness disturbance based on the accompanying wave field and the background wave field, updating the first slowness disturbance based on a preset gradient descent method and the first gradient to obtain target slowness disturbance, and performing migration imaging on the target imaging area based on the target slowness disturbance. Therefore, by carrying out irregular grid subdivision on the target imaging area, the undulating structure of the earth surface can be better approximated, and the target program area is subjected to offset imaging in the target slowness disturbance obtained by the discontinuous finite element method, so that the influence of scattered waves caused by trapezoidal approximation can be reduced, and the imaging accuracy of the target imaging area with a complex structure is improved.

Example two

As shown in fig. 4, an execution subject of the offset imaging method may be a server, and the server may be an independent server or a server cluster composed of a plurality of servers. The method may specifically comprise the steps of:

in S402, based on a preset relevant point selection rule, four relevant points corresponding to the center points of the irregular grid are selected.

In an implementation, a user may obtain position information of a plurality of sources and receivers for a target imaging area, and the user may input the position information of the plurality of sources and receivers into a server, that is, the server may obtain position information of a plurality of sources and receivers for the target imaging area, for example, according to actual exploration materials, position information (e.g., position coordinates) of N sources and M receivers for the target imaging area, and the user may input the position information of the N sources and the M receivers into the server.

After obtaining the result of the irregular grid division of the target imaging area, the server may match the position information of each seismic source in the N seismic sources input by the user with the result of the irregular grid division of the target imaging area to determine the corresponding position of the position information of each seismic source in the irregular grid of the target imaging area (i.e., determine the corresponding position of the seismic source in the irregular grid), and similarly, the server may also match the position information of each receiver in the M receivers with the result of the irregular grid division of the target imaging area to determine the corresponding position of each receiver in the irregular grid of the target imaging area. Wherein, the corresponding position of the source (or receiver) in the irregular grid may include a grid number in the irregular grid corresponding to the position information of the source (or receiver) and corresponding grid coordinates, etc.

After matching, four relevant points corresponding to the center point of each irregular grid in the position information of the source or receiver can be obtained.

In S404, the position coordinates of each relevant point in the depth and horizontal directions and the background velocity parameter are acquired.

In an implementation, the irregular grid may be matched with the location information of the seismic source to obtain the location coordinates of the center point and four relevant points of the irregular grid in the depth and horizontal directions and the background velocity parameter. The acquired position coordinates may be actual exploration position information of the seismic source and the receiver when seismic waves are acquired in the target imaging area, and the position information may be known data acquired through exploration data.

In S406, the position coordinates of each of the four correlation points in the depth and horizontal directions and the background velocity parameter are substituted into the formula

And obtaining the background speed parameter of the central point of the irregular grid.

Wherein the content of the first and second substances,

background velocity parameter, c, being the center point of an irregular grid_i,j、c_i+1,j、c_i,j+1And c_i+1,j+1Background velocity parameters for four relevant points, respectively, (x)_i，z_j)、(x_i+1，z_j)、(x_i，z_j+1) And (x)_i+1，z_j+1) Respectively, the position coordinates of the four relevant points.

In S408, the background velocity parameter of the center point of the irregular grid is determined as the target background velocity parameter of the irregular grid.

In S410, first observed wavefield data acquired by a receiver after each of a plurality of seismic sources emits a shot seismic wave is acquired.

In S412, gaussian-distributed random numbers corresponding to each seismic source are acquired.

In S414, the Gaussian distribution random number corresponding to each seismic source and the first observation wave field data are substituted into the formula

And obtaining observation wave field data.

Wherein d is_superFor observing wave field data, ω_iFor the Gaussian-distributed random number corresponding to the ith seismic source, d_iAnd N is the number of the seismic sources.

In S416, a background slowness of the irregular grid is determined based on the target background velocity parameter of the irregular grid.

In an implementation, the background slowness of the irregular grid may be the inverse of the target background velocity parameter.

In S418, the position coordinates of the center point of each irregular mesh in the depth and horizontal directions are acquired.

In S420, a disturbance wave field of the target imaging area is determined through a discontinuous finite element method based on the background slowness of the irregular grid, the position coordinates of the central point of the irregular grid, the first slowness disturbance, the medium density and the background wave field.

In implementation, the background slowness of the irregular grid, the position coordinates of the center point of the irregular grid, the first slowness disturbance, the medium density and the background wave field can be substituted into the formula

And obtaining a disturbance wave field of the target imaging area. Wherein (p)_s，u_s，w_s) For perturbing the wavefield, ρ is the density of the medium, Δ s²For first slowness disturbance, p₀For the background wave field, s₀Is the background slowness of the irregular grid,

the target background velocity parameter of the irregular grid, t is time, and (x, z) is the position coordinate of the central point of the irregular grid.

In S422, an adjoint wavefield of the target imaging region is determined based on the position coordinates of the center point of the irregular grid, the disturbance wavefield, the medium density, and the observed wavefield data.

In implementation, the residual error between the observed wave field data and the disturbance wave field can be used as a seismic source item to perform reverse time propagation to obtain an accompanying wave field, for example, the position coordinates of the central point of the irregular grid, the disturbance wave field, the medium density and the observed wave field data can be substituted into a formula

Obtaining a adjoint wave field, wherein (p)^*，u^*，w^*) For the adjoint wavefield, (p)_obs，u_obs，w_obs) For observing wave field data d_superThree physical quantities are involved.

In S424, a first gradient for updating the first slowness perturbation is determined based on the adjoint wavefield and the background wavefield.

In implementation, the adjoint wavefield and the background wavefield may be substituted into a formula

A first gradient is obtained, where g is the first gradient and T is the maximum recording duration.

In S426, the first slowness disturbance is updated based on the preset gradient descent method and the first gradient, so as to obtain a target slowness disturbance.

In S428, a first adjoint wavefield is determined by a discontinuous finite element method based on the target background velocity parameter, the target slowness perturbations, the medium density, the background wavefield, and the observed wavefield data for the irregular grid.

In S430, a second gradient for updating the target slowness perturbation is determined based on the first adjoint wavefield and the background wavefield.

In S432, the second gradient is corrected based on the second gradient, the first gradient, and a preset attenuation coefficient.

In operation, since the first observed wavefield data of each seismic source is aliased based on the gaussian distributed random number to obtain the observed wavefield data in S414, in order to reduce the influence of randomness caused by the gaussian distributed random number, the second gradient may be modified to improve the imaging accuracy.

The second gradient, the first gradient and the preset attenuation coefficient can be substituted into the formula

A modified second gradient is obtained, wherein,

for the second gradient after correction, g_kIn order to be the second gradient, the gradient is,

for the first gradient, λ is a preset attenuation coefficient (which may be a constant less than 1, such as 0.7, etc.).

In S434, the target slowness disturbance is updated based on the preset gradient descent method and the corrected second gradient, so as to obtain a second slowness disturbance.

In S436, the target imaging region is shift imaged based on the second slowness disturbance.

In implementation, before performing offset imaging on the target imaging area based on the second slowness disturbance, whether the second slowness disturbance meets a preset updating requirement or not may be determined, for example, whether a variation amplitude of the second slowness disturbance (i.e., a difference between the second slowness disturbance and the target slowness disturbance and a ratio between the second slowness disturbance) is smaller than a preset threshold or not may be determined, and if the variation amplitude of the second slowness disturbance is smaller than the preset threshold, offset imaging may be performed on the target imaging area based on the second slowness disturbance.

If the second slowness does not meet the preset updating requirement (if the variation amplitude of the second slowness disturbance is not smaller than the preset threshold), the second slowness disturbance can be determined as the target slowness disturbance, and S428-S436 is executed again to obtain the second slowness disturbance again, and whether the variation amplitude of the second slowness disturbance meets the preset updating requirement or not is judged.

Further, before performing S428 to S436, S414 may be performed again to determine observed wavefield data based on the regenerated gaussian-distributed random numbers, and then S428 to S436 may be performed.

In addition, in S426, the first slowness perturbation may be updated based on a preset search step, where the preset search step may be determined based on the perturbation wave field and the observation wave field data in S420, for example, the perturbation wave field may be calculated based on different search steps, and a search step corresponding to the perturbation wave field with the smallest difference between the perturbation wave field and the observation wave field data is determined as the preset search step.

After the target imaging area shown in fig. 2 is imaged based on the above steps, the imaging result shown in fig. 5 can be obtained, and it can be seen from the imaging result shown in fig. 5 that each reflection interface can be clearly imaged, the speed discontinuity near the earth surface is relatively accurate, the continuity is better, the image resolution is higher, and the imaging amplitude is more balanced.

In addition, fig. 6 is a comparison graph of a least square inverse time shift error decreasing curve (i.e., curve 2) obtained by imaging based on the corrected second gradient and a least square inverse time shift error decreasing curve (i.e., curve 1) obtained by imaging based on the original gradient (i.e., the preset gradient), and it can be seen that the error of imaging based on the corrected second gradient decreases more rapidly.

In summary, in the embodiments of the present disclosure, by performing the least-squares reverse-time migration on the complex structure region through the irregular mesh subdivision and the discontinuous finite element method, the imaging accuracy for the region with the complex structure (especially, the region with severe surface relief) may be improved, and the imaging definition of the near-surface structure and the mid-deep structure may be improved. Meanwhile, the first observation data of the seismic source is subjected to aliasing through the Gaussian distribution random number, and the current second gradient is corrected by using the first gradient calculated before, so that the calculation efficiency can be improved.

EXAMPLE III

Based on the same idea, the offset imaging method provided in the embodiments of the present specification further provides an offset imaging apparatus, as shown in fig. 7.

The offset imaging apparatus includes: parameter determination module 701, wavefield determination module 702, gradient determination module 703, update module 704, and imaging module 705, wherein:

a parameter determining module 701, configured to determine a target background speed parameter of each irregular grid in a target imaging region based on an interpolation method and a background speed parameter of the target imaging region;

a wave field determination module 702 configured to determine an adjoint wave field of the target imaging region by a discontinuous finite element method based on the target background velocity parameter, the first slowness disturbance, the medium density, the background wave field, and the observed wave field data of the irregular grid;

a gradient determination module 703 for determining a first gradient for updating the first slowness perturbation based on the adjoint wavefield and the background wavefield;

an updating module 704, configured to update the first slowness disturbance based on a preset gradient descent method and the first gradient, to obtain a target slowness disturbance;

an imaging module 705 configured to perform offset imaging on the target imaging region based on the target slowness disturbance.

In this embodiment of the present invention, the parameter determining module 701 is configured to:

In an embodiment of the present invention, the wave field determining module 702 is configured to:

In the embodiment of the present invention, the apparatus further includes:

In this embodiment of the present invention, the gradient determining module 703 is configured to:

In this embodiment of the present invention, the imaging module 705 is configured to:

Example four

Figure 8 is a schematic diagram of a hardware configuration of an electronic device implementing various embodiments of the invention,

the electronic device 800 includes, but is not limited to: a radio frequency unit 801, a network module 802, an audio output unit 803, an input unit 804, a sensor 805, a display unit 806, a user input unit 807, an interface unit 808, a memory 809, a processor 810, and a power supply 811. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 8 does not constitute a limitation of the electronic device, and that the electronic device may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted terminal, a wearable device, a pedometer, and the like.

The processor 810 is configured to determine a target background velocity parameter of each irregular grid in the target imaging area based on an interpolation method and a background velocity parameter of the target imaging area;

the processor 810 is further configured to determine an adjoint wavefield of the target imaging region based on the target background velocity parameter, the first slowness perturbation, the medium density, the background wavefield, and the observed wavefield data of the irregular grid by a discontinuous finite element method;

the processor 810 is further configured to determine a first gradient for updating the first slowness perturbation based on the adjoint wavefield and the background wavefield;

the processor 810 is further configured to update the first slowness disturbance based on a preset gradient descent method and the first gradient to obtain a target slowness disturbance;

the processor 810 is further configured to perform offset imaging on the target imaging region based on the target slowness disturbance.

In addition, the processor 810 is further configured to select, based on a preset relevant point selection rule, four relevant points corresponding to the center point of the irregular grid;

in addition, the processor 810 is further configured to obtain position coordinates of each of the relevant points in the depth and horizontal directions and a background speed parameter;

the processor 810 is further configured to substitute the position coordinates of each of the four correlated points in the depth and horizontal directions and the background velocity parameter into a formula

in addition, the processor 810 is further configured to determine a background velocity parameter of a center point of the irregular grid as a target background velocity parameter of the irregular grid.

In addition, the processor 810 is further configured to determine a background slowness of the irregular grid based on a target background velocity parameter of the irregular grid;

in addition, the processor 810 is further configured to obtain position coordinates of a center point of each irregular grid in the depth and horizontal directions;

the processor 810 is further configured to determine, by the discontinuous finite element method, a disturbance wavefield of the target imaging region based on a background slowness of the irregular grid, the location coordinates of the center point of the irregular grid, the first slowness disturbance, the medium density, and the background wavefield;

in addition, the processor 810 is further configured to determine an adjoint wavefield of the target imaging region based on the location coordinates of the irregular grid center point, the perturbation wavefield, the medium density, and the observation wavefield data.

In addition, the processor 810 is further configured to obtain first observed wavefield data collected by a receiver after each of the plurality of seismic sources emits a shot;

in addition, the processor 810 is further configured to obtain a gaussian-distributed random number corresponding to each of the seismic sources;

the processor 810 is further configured to substitute the gaussian-distributed random number corresponding to each seismic source and the first observed wavefield data into a formula

In addition, the processor 810 is further configured to substitute the background slowness of the irregular grid, the position coordinates of the center point of the irregular grid, the first slowness disturbance, the medium density, and the background wavefield into a formula

in addition, the processor 810 is further configured to substitute the position coordinates of the center point of the irregular grid, the disturbance wavefield, the medium density, and the observation wavefield data into a formula

The processor 810 is further configured to substitute the adjoint wavefield and the background wavefield into a formula

Additionally, the processor 810 is further configured to determine, by the discontinuous finite element method, a first adjoint wavefield based on the target background velocity parameter, the target slowness perturbation, the medium density, the background wavefield, and the observed wavefield data for the irregular grid;

further, the processor 810 is further configured to determine a second gradient for updating the target slowness perturbation based on the first adjoint wavefield and the background wavefield;

in addition, the processor 810 is further configured to modify the second gradient based on the second gradient, the first gradient and a preset attenuation coefficient;

in addition, the processor 810 is further configured to update the target slowness disturbance based on the preset gradient descent method and the corrected second gradient, so as to obtain a second slowness disturbance;

in addition, the processor 810 is further configured to perform offset imaging on the target imaging region based on the second slowness disturbance.

The embodiment of the invention provides electronic equipment, the target background speed parameter of each irregular grid in a target imaging area is determined based on an interpolation method and the background speed parameter of the target imaging area, an accompanying wave field of the target imaging area is determined based on the target background speed parameter, first slowness disturbance, medium density, a background wave field and observation wave field data of the irregular grids through a discontinuous finite element method, a first gradient used for updating the first slowness disturbance is determined based on the accompanying wave field and the background wave field, the first slowness disturbance is updated based on a preset gradient descent method and the first gradient to obtain the target slowness disturbance, and offset imaging is performed on the target imaging area based on the target slowness disturbance. Therefore, by carrying out irregular grid subdivision on the target imaging area, the undulating structure of the earth surface can be better approximated, and the target program area is subjected to offset imaging in the target slowness disturbance obtained by the discontinuous finite element method, so that the influence of scattered waves caused by trapezoidal approximation can be reduced, and the imaging accuracy of the target imaging area with a complex structure is improved.

It should be understood that, in the embodiment of the present invention, the radio frequency unit 801 may be used for receiving and sending signals during a message sending and receiving process or a call process, and specifically, receives downlink data from a base station and then processes the received downlink data to the processor 810; in addition, the uplink data is transmitted to the base station. In general, radio frequency unit 801 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. Further, the radio frequency unit 801 can also communicate with a network and other devices through a wireless communication system.

The electronic device provides wireless broadband internet access to the user via the network module 802, such as to assist the user in sending and receiving e-mails, browsing web pages, and accessing streaming media.

The audio output unit 803 may convert audio data received by the radio frequency unit 801 or the network module 802 or stored in the memory 809 into an audio signal and output as sound. Also, the audio output unit 803 may also provide audio output related to a specific function performed by the electronic apparatus 800 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 803 includes a speaker, a buzzer, a receiver, and the like.

The input unit 804 is used for receiving an audio or video signal. The input Unit 804 may include a Graphics Processing Unit (GPU) 8041 and a microphone 8042, and the Graphics processor 8041 processes image data of a still picture or video obtained by an image capturing device (such as a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 806. The image frames processed by the graphics processor 8041 may be stored in the memory 809 (or other storage medium) or transmitted via the radio frequency unit 801 or the network module 802. The microphone 8042 can receive sound, and can process such sound into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 801 in case of a phone call mode.

The electronic device 800 also includes at least one sensor 805, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 8061 according to the brightness of ambient light and a proximity sensor that can turn off the display panel 8061 and/or the backlight when the electronic device 800 is moved to the ear. As one type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of an electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 805 may also include fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which are not described in detail herein.

The display unit 806 is used to display information input by the user or information provided to the user. The Display unit 806 may include a Display panel 8061, and the Display panel 8061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.

The user input unit 807 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic apparatus. Specifically, the user input unit 807 includes a touch panel 8071 and other input devices 8072. The touch panel 8071, also referred to as a touch screen, may collect touch operations by a user on or near the touch panel 8071 (e.g., operations by a user on or near the touch panel 8071 using a finger, a stylus, or any other suitable object or accessory). The touch panel 8071 may include two portions of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 810, receives a command from the processor 810, and executes the command. In addition, the touch panel 8071 can be implemented by various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 8071, the user input unit 807 can include other input devices 8072. In particular, other input devices 8072 may include, but are not limited to, a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail herein.

Further, the touch panel 8071 can be overlaid on the display panel 8061, and when the touch panel 8071 detects a touch operation on or near the touch panel 8071, the touch operation is transmitted to the processor 810 to determine the type of the touch event, and then the processor 810 provides a corresponding visual output on the display panel 8061 according to the type of the touch event. Although in fig. 8, the touch panel 8071 and the display panel 8061 are two independent components to implement the input and output functions of the electronic device, in some embodiments, the touch panel 8071 and the display panel 8061 may be integrated to implement the input and output functions of the electronic device, and the implementation is not limited herein.

The interface unit 808 is an interface for connecting an external device to the electronic apparatus 800. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 808 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the electronic device 800 or may be used to transmit data between the electronic device 800 and external devices.

The memory 809 may be used to store software programs as well as various data. The memory 809 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 409 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The processor 810 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 809 and calling data stored in the memory 809, thereby monitoring the whole electronic device. Processor 810 may include one or more processing units; preferably, the processor 810 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 810.

The electronic device 800 may also include a power supply 811 (e.g., a battery) for powering the various components, and preferably, the power supply 811 may be logically coupled to the processor 810 via a power management system to manage charging, discharging, and power consumption management functions via the power management system.

Preferably, an embodiment of the present invention further provides an electronic device, which includes a processor 810, a memory 809, and a computer program stored in the memory 809 and capable of running on the processor 810, where the computer program is executed by the processor 810 to implement each process of the above offset imaging method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not described here again.

EXAMPLE five

An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned offset imaging method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.

The embodiment of the invention provides a computer-readable storage medium, which is used for determining a target background speed parameter of each irregular grid in a target imaging area based on an interpolation method and a background speed parameter of the target imaging area, determining an accompanying wave field of the target imaging area based on the target background speed parameter, first slowness disturbance, medium density, a background wave field and observation wave field data of the irregular grids by using a discontinuous finite element method, determining a first gradient for updating the first slowness disturbance based on the accompanying wave field and the background wave field, updating the first slowness disturbance based on a preset gradient descent method and the first gradient to obtain a target slowness disturbance, and performing offset imaging on the target imaging area based on the target slowness disturbance. Therefore, by carrying out irregular grid subdivision on the target imaging area, the undulating structure of the earth surface can be better approximated, and the target program area is subjected to offset imaging in the target slowness disturbance obtained by the discontinuous finite element method, so that the influence of scattered waves caused by trapezoidal approximation can be reduced, and the imaging accuracy of the target imaging area with a complex structure is improved.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

Claims

1. An offset imaging method, comprising:

2. The method of claim 1, wherein determining the target background velocity parameter for each irregular grid in the target imaging region based on interpolation and the background velocity parameter for the target imaging region comprises:

a background velocity parameter being a center point of the irregular grid, c_i，j、c_i+1，j、c_i，j+1And c_i+1，j+1Background velocity parameters (x) for the four correlation points, respectively_i，z_j)、(x_i+1，z_j)、(x_i，z_j+1) And (x)_i+1，z_j+1) The position coordinates of the four related points are respectively;

3. The method of claim 2, wherein determining the adjoint wavefield of the target imaging region based on the target background velocity parameter, the first slowness perturbation, the medium density, the background wavefield, and the observed wavefield data for the irregular grid by a discontinuous finite element method comprises:

4. The method of claim 3, further comprising, prior to the determining a adjoint wavefield of the target imaging region based on the perturbation wavefield and the observation wavefield data:

5. The method of claim 4, wherein determining, by the discontinuous finite element method, a perturbation wavefield of the target imaging region based on a background slowness of the irregular grid, a location coordinate of a center point of the irregular grid, the first slowness perturbation, the medium density, and the background wavefield comprises:

6. The method of claim 5, wherein determining a first gradient for updating the first slowness perturbation based on the adjoint wavefield and the background wavefield comprises:

7. The method of claim 6, wherein the offset imaging the target imaging region based on the target slowness perturbation comprises:

8. An offset imaging apparatus, comprising:

9. An electronic device, comprising a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the offset imaging method as claimed in any one of claims 1 to 7.

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 offset imaging method as set forth in any one of claims 1 to 7.