Batch dynamic fitting modification method and system for spherical nodes of three-dimensional geological bodies

Abstract

The present invention discloses a method and system for batch dynamic fitting and modification of spherical nodes of a three-dimensional geological body, which determines all the grid points to be fitted within the range to be modified of the three-dimensional geological body, and obtains a point set A( xc , yc , zc );The point set A( xc , yc , zc ) is converted into spherical coordinates( r , θ , φ );Kriging spherical interpolation is performed on the spherical coordinates to obtain a spherical coordinate fitting result;The spherical coordinate fitting result is converted into three-dimensional rectangular coordinates to obtain updated grid point coordinates, and the geological grid body is reconstructed. The present invention can perform batch smooth fitting and modification on grid points in various directions in the geological grid body within a certain range, so as to obtain an adjusted geological grid body.

Description

Technical Field

[0001] The present invention relates to dynamic fitting technology, in particular to a method and system for batch dynamic fitting modification of spherical nodes of a three-dimensional geological body. Background Art

[0002] In the process of establishing a three-dimensional geological model, a geological body cannot be expressed by ordinary entities or elements. The common practice is to use a grid envelope to express the geological body. A geological grid body can reflect the upper and lower boundaries of strata at one or more exploration points at the same time. When the exploration data changes and needs to be adjusted, during the modification process of the grid envelope, the grid nodes can only be modified one by one or in batches at the same height, and cannot meet the requirement of batch spherical fitting and smoothing modification within a certain range. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and system for batch dynamic fitting modification of spherical nodes of a three-dimensional geological body, which can perform batch smoothing fitting modification on grid points in each direction in a geological grid body within a certain range, aiming at the deficiencies of the prior art.

[0004] To solve the above technical problem, the technical solution adopted by the present invention is: A method for batch dynamic fitting modification of spherical nodes of a three-dimensional geological body, comprising the following steps:

[0005] Determine all grid points to be fitted within the radius R of the three-dimensional geological body to obtain a point set A( xc , yc , zc );

[0006] Convert the point set A( xc , yc , zc ) into spherical coordinates( r , θ , φ );

[0007] Perform Kriging spherical interpolation on the spherical coordinates to obtain a spherical coordinate fitting result;

[0008] Convert the spherical coordinate fitting result into three-dimensional rectangular coordinates to obtain updated grid point coordinates and reconstruct the geological grid body.

[0009] The present invention determines the grid points to be fitted, converts them into spherical coordinates, performs fitting using Kriging interpolation, and then converts the result back into three-dimensional rectangular coordinates to reconstruct the geological grid body. Kriging interpolation comprehensively considers spatial correlation to achieve batch smoothing fitting, ensuring the uniformity and continuity of grid points in all directions in three-dimensional space. The present invention can efficiently and flexibly modify the geological grid body in the target area, retain local features and overall structure, and complete batch optimization and reconstruction.

[0010] Before converting the point set A( xc , yc , zc ) into spherical coordinates( r , θ , φ ), it also includes:

[0011] Preprocess A( xc , yc , zc ) to obtain B( x ′, y ′, z ′);

[0012] Among them, ; α , β are the distance coefficient and the height coefficient respectively. ([[]] xc , yc , zc ) is the coordinate of the point to be modified, ([[]] xe , ye ) is the plane coordinate of the edge point, and Δ z is the elevation difference.

[0013] In the preprocessing process of the present invention, by introducing the distance coefficient α and the height coefficient β , the point to be modified ( xc , yc , zc ) is moved closer to the plane coordinate of the edge point ( xe , ye ), and the height is adjusted according to the elevation difference Δ z to generate an optimized point set B ( x ′, y ′, z ′). This process makes the point set closer to the boundary and shape of the actual geological body, improves the accuracy and stability of the spherical coordinate conversion, and reduces the errors in the edge area and the area with large elevation difference changes. At the same time, the preprocessing avoids the problem of unstable fitting caused by uneven distribution or local outliers in the original point set, and enhances the robustness of subsequent Kriging interpolation and coordinate conversion. By flexibly adjusting α and β , the preprocessing can adapt to the morphological characteristics of different geological bodies, providing a reliable basis for batch smooth fitting and geological grid body reconstruction.

[0014] The calculation formula for the spherical coordinates( r , θ , φ ) is: . ​​; λ i is the i-th observation point Z i is the weight coefficient of L is the maximum order β lm is the regression coefficient l is the spherical correlation length parameter is the spherical harmonic function

[0015] , where n is the number of Gaussian kernels

[0016] As an inventive concept, the present invention also provides a batch dynamic fitting and modification system for spherical nodes of a three-dimensional geological body, including a memory, a processor, and a computer program stored on the memory; the processor executes the computer program to implement the steps of the above method

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: After using the batch dynamic fitting and modification method for nodes of a three-dimensional geological body in the present invention on the original geological grid body, the grid points in each direction in the geological grid body can be batch-smoothly fitted and modified within a certain range, so as to obtain an adjusted geological grid body BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is the perspective view before fitting and modification of an embodiment of the present invention

[0019] Figure 2 is the perspective view after fitting and modification of an embodiment of the present invention DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention

[0021] Embodiment 1

[0022] This embodiment provides a batch dynamic fitting and modification method for spherical nodes of a three-dimensional geological body, including the following implementation process

[0023] The first step: Obtain the data point set A

[0024] According to the preset center point and influence radius R, determine all the grid points to be fitted within the radius R as the point set A of the modification area( xc ,yc , zc ).

[0025] Step 2: Preprocess A( xc , yc , zc ) to obtain B( x ′, y ′, z ′)

[0026] 1. Input distance coefficient α and height coefficient β ;

[0027] 2. Calculate the position of the point( x ′, y ′) and height z ′:

[0028] ;

[0029] where ([[]] xc xc , yc , zc ) are the coordinates of the point to be modified, and ([[]] xe xe , ye , ze ) are the coordinates of the edge point.

[0030] Step 3: Convert the three-dimensional coordinates of B( x ′, y ′, z ′) to spherical coordinates:

[0031] For each point B ( x ′, y ′, z ′), convert it to spherical coordinates ( r , θ , φ ):

[0032] ;

[0033] In this embodiment, the azimuth angle φ is calculated using atan2( y ′, x ′) to avoid quadrant errors.

[0034] Step 4: Kriging spherical interpolation for spherical coordinates( θ , φ , r )

[0035] 1. Definition of spherical distance: The distance between two points ( θ i , φi ) and ( θ j , φ j ) spherical distance d ij Using the central angle formula:

[0036] ;

[0037] ;

[0038] 2. Gaussian model

[0039] Parameters: nugget value c0, sill value c, range a, d ij representing the spherical distance between two points in space

[0040] ;

[0041] 3. Spherical harmonic regression model

[0042] Using spherical harmonic functions as the regression basis functions to capture the spherical periodic characteristics:

[0043] ;

[0044] where L is the maximum order, is the regression coefficient;

[0045] 4. Solving the Kriging equations

[0046] ;

[0047] Solving the equations to obtain the weights λ i and the Lagrange multipliers μ ;

[0048] 5. Calculation of predicted values and variances

[0049] From we get the following equation

[0050] ;

[0051] The variance is as follows: ;

[0052] Weight constraint: satisfying the unbiased condition .

[0053] In the embodiments of the present invention, the variance is used to test the deviation between the fitted value and the original value.

[0054] Step Five: Inverse coordinate transformation

[0055] The spherical fitting result is converted back to three-dimensional rectangular coordinates:

[0056] ;

[0057] According to the updated grid point coordinates and topological relationships, reconstruct the geological grid body.

[0058] As can be seen from the above table, in this embodiment, through the constraints of the Gaussian function and the spherical harmonic regression model function, the fitted data is smoother, can effectively correct the local fluctuations of the original data, and at the same time maintain the overall spatial trend. The fitted coordinates and elevation values are smoother and conform to the basic assumptions of geostatistics.

[0059] Embodiment 2

[0060] Embodiment 2 of the present invention provides a terminal device corresponding to the above Embodiment 1. The terminal device can be a processing device for a client, such as a mobile phone, a notebook computer, a tablet computer, a desktop computer, etc., to execute the method of the above embodiment.

[0061] The terminal device of this embodiment includes a memory, a processor, and a computer program stored on the memory; the processor executes the computer program on the memory to implement the steps of the method of the above Embodiment 1.

[0062] In some implementations, the memory can be a high-speed random access memory (RAM: Random Access Memory), and may also include a non-volatile memory, such as at least one disk memory.

[0063] In other implementations, the processor can be a general-purpose processor of various types such as a central processing unit (CPU), a digital signal processor (DSP), etc., which is not limited here.

[0064] Embodiment 3

[0065] Embodiment 3 of the present invention provides a computer-readable storage medium corresponding to the above Embodiment 1, on which a computer program / instructions are stored. When the computer program / instructions are executed by a processor, the steps of the method of the above Embodiment 1 are implemented.

[0066] A computer-readable storage medium can be a tangible device that holds and stores instructions used by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination of the above.

[0067] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages. For example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript, etc.

[0068] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, so that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable devices provide steps for realizing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0070] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be construed as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0071] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. A method for batch dynamic fitting and modification of spherical nodes of three-dimensional geological bodies, characterized in that Including the following steps: Determine all the grid points to be fitted within the range of the 3D geological body to be modified, and obtain the point set A( xc , yc , zc ); ([ xc xc , yc , zc ) is the coordinate of the point to be modified; The point set A( xc , yc , zc ) is converted to spherical coordinates ( r , θ , φ ); Perform Kriging spherical interpolation on the said spherical coordinates to obtain the spherical coordinate fitting result; Convert the said spherical coordinate fitting result into three-dimensional Cartesian coordinates to obtain the updated grid point coordinates and reconstruct the geological grid body; The expression of the spherical coordinate fitting result is as follows: ; are the polar angle and azimuth angle of the prediction point, are the polar angle and azimuth angle of the known point i, r i is the radial distance from the known point i to the center of the sphere, is an arbitrary position on the sphere to the radial distance from the center of the sphere, λ i is the i-th observation point Z i 's weight coefficient, L is the maximum order, β lm are the regression coefficients, l is the spherical correlation length parameter, is the spherical harmonic function, and n is the number of Gaussian kernels.

2. The batch dynamic fitting modification method of the three-dimensional geological body spherical node according to claim 1 is characterized in that: Before converting the point set A( xc , yc , zc ) to spherical coordinates( r , θ , φ ), it also includes: Preprocess A( xc , yc , zc ) to obtain the preprocessed result B( x ′, y ′, z ′); Among them, ; α and β are the distance coefficient and the height coefficient respectively, and ([[]] xe , ye , ze ) are the coordinates of the control points.​ 3. The batch dynamic fitting and modification method for spherical nodes of three-dimensional geological bodies according to claim 2, wherein Spherical coordinates ( r , θ , φ ) is calculated as: .

4. The batch dynamic fitting and modification method for spherical nodes of three-dimensional geological bodies according to claim 1, wherein 。 5. The batch dynamic fitting and modification method for spherical nodes of three-dimensional geological bodies according to claim 1, characterized in that Weight coefficient λ i The calculation formula is as follows: ； Among them, μ is the Lagrange multiplier, , c0 is the nugget effect, c is the sill, and a is the range, d ij represents the spherical distance between two points in space.

6. The batch dynamic fitting and modification method for spherical nodes of three-dimensional geological bodies according to claim 1, wherein Spherical fitting results The expression converted to three-dimensional rectangular coordinates is: ； Among them, i.e., , is a three-dimensional rectangular coordinate.

7. A batch dynamic fitting and modification system for spherical nodes of three-dimensional geological bodies, comprising a memory, a processor, and a computer program stored on the memory; characterized in that, The said processor executes the said computer program to implement the steps of the method according to any one of claims 1 to 6.

Images