Adaptive mesh-based implicit geological modeling method and electronic device

Abstract

Embodiments of the present disclosure disclose an implicit geological modeling method based on adaptive grid and an electronic device. A specific implementation of the method comprises: performing initial grid division on a calculation region according to geological modeling parameters and geological source data to obtain a first grid set; determining a grid to be refined in the first grid set according to a preset judgment rule; dividing the grid to be refined into a set of sub-elements according to a preset refinement rule to obtain a second grid set of the calculation region; storing grid data of the second grid set; performing difference on a second grid in the second grid set and determining a coefficient matrix A according to a difference coefficient; constructing a linear equation set Ax=b based on the Lagrange multiplier method, wherein the vector b is used to represent point constraints and directional constraints; solving the linear equation set to obtain a second grid value, and outputting a modeling result according to the second grid value. Thus, a new implicit geological modeling method based on adaptive grid is provided.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of computer, and particularly relates to an implicit geological modeling method based on adaptive grid and an electronic device. BACKGROUND

[0002] With the continuous progress of computer technology and the popularity of high-performance computing resources, computer-based geological modeling plays an increasingly important role in resource exploration, environmental protection, disaster prediction and other fields. Geological modeling is a process of describing, interpreting and predicting geological entities, and is an important part of geology, resource exploration and environmental science. The main task of geological modeling is to construct underground structure and attribute models according to geological data (such as drilling data, geophysical data, geological images, etc.) to help understand geological processes, guide resource exploration and management, and assess geological disaster risks.

[0003] Traditional geological modeling methods mainly include manual modeling and rule-based model fitting. These methods have problems such as slow computing speed, strong subjectivity, dependence on professional experience, etc. when dealing with large-scale geological data, and are difficult to meet the needs of modern geological engineering. SUMMARY

[0004] This part of the disclosure is provided to briefly introduce the concepts, which will be described in detail in the specific embodiments part. This part of the disclosure is not intended to identify key features or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0005] In a first aspect, the embodiments of the present disclosure provide an implicit geological modeling method based on adaptive grid, the method comprising: performing initial grid division on a calculation region according to geological modeling parameters and geological source data to obtain a first grid set; determining a grid to be refined in the first grid set according to a preset judgment rule; dividing the grid to be refined into a set of sub-elements according to a preset refinement rule to obtain a second grid set of the calculation region; storing grid data of the second grid set; performing difference on a second grid in the second grid set, and determining a coefficient matrix A according to a difference coefficient; constructing a linear equation set Ax=b based on the Lagrange multiplier method, wherein the vector b is used to represent point constraints and direction constraints; obtaining a second grid value by solving the linear equation set, and outputting a modeling result according to the second grid value.

[0006] Optionally, the determining the grid to be refined in the first grid set according to the preset judgment rule comprises: marking the grid according to a refinement level, wherein a grid where a control point or a fault point is located is marked as level 2, a grid directly adjacent to the grid where the control point or the fault point is located is marked as level 1, and the remaining grids are marked as level 0; and determining the grid marked as 2 or 1 as the grid to be refined.

[0007] Optionally, the second grid element set of the calculation region is obtained by splitting the grid to be refined into a sub-element set according to a preset refinement rule, including: taking a 3*3 grid region centered on the grid where the grid to be refined is located as a basic processing unit, and refining and encrypting the region grid where the grid to be refined is located; after completing a refinement process, checking the refinement level of the grid where the grid to be refined is located; if the refinement level of the grid where the grid to be refined is located is less than a specified refinement level, the recursive refinement is continued; if the refinement level of the grid to be refined is one less than the specified refinement level, the recursive process is stopped, and the grid currently marked as 2 is refined again, so that the grid to be refined reaches the specified refinement level, and the refinement levels of the adjacent grids around the grid to be refined and the grid to be refined differ by 1.

[0008] Optionally, the refining and encrypting of the region grid where the grid to be refined is located includes: adding four edge nodes and a center node in the grid in the region, and then combining the new nodes with the original grid nodes to form four refined grid elements.

[0009] Optionally, the grid data of the second grid set is stored, including: storing each level of grid separately according to different refinement levels; wherein each layer of grid in the first storage space is regarded as a uniform grid corresponding to the resolution of the refinement level; the second storage space stores the marks of the grid points of the single-layer grid, wherein the grid points actually existing in the second grid set store index values, and the grid points that do not exist are marked as -1.

[0010] Optionally, the difference of the second grid in the second grid set includes: determining whether to supplement the second grid; in response to determining to supplement the second grid, interpolating the missing grid point from the existing grid point to supplement the difference.

[0011] Optionally, the determination of whether to supplement the second grid includes: determining whether the grid points of the same level in the neighborhood of the point T to be differentiated are missing; if missing, determining to supplement the missing grid points.

[0012] Optionally, the interpolation of the missing grid point from the existing grid point in response to the determination to supplement the second grid includes: if the missing grid point is located on the grid line, supplementing the missing grid point according to the points at both ends of the grid line segment; if the missing grid point is located at the center of the grid, supplementing the missing grid point according to the points on the grid line of the grid where the grid center is located.

[0013] Optionally, the method further comprises: if the missing grid point is located at a center of the three-dimensional grid, based on the existing grid points on the grid line of the three-dimensional grid, the missing point on the grid line of the three-dimensional grid is supplemented to obtain a line point of the three-dimensional grid; and based on the line point of the three-dimensional grid, the missing point located at the center of the three-dimensional grid is supplemented.

[0014] In a second aspect, the embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device configured to store one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0015] The above and other features, advantages, and aspects of the embodiments of the present disclosure will become more apparent upon consideration of the following detailed description, taken in conjunction with the accompanying drawings. Throughout the drawings, like or similar reference numerals are used to refer to like or similar elements. It should be understood that the drawings are schematic and elements and features are not necessarily to scale.

[0016] Figure 1 is a flow chart of one embodiment of the adaptive grid based implicit geological modeling method according to the present disclosure;

[0017] Figure 2 is a flow chart of the adaptive grid refinement process;

[0018] Figure 3 is a flow chart of the recursive based adaptive refinement algorithm;

[0019] Figure 4 is a diagram of the adaptive grid data structure;

[0020] Figure 5 is a schematic diagram of the two-dimensional adaptive grid point supplementing difference method;

[0021] Figure 6 is a schematic diagram of the three-dimensional adaptive grid center point supplementing difference method;

[0022] Figure 7 is a schematic diagram of the basic structure of the electronic device provided by the embodiments of the present disclosure. DETAILED DESCRIPTION

[0023] Embodiments of the present disclosure will be described below in greater detail with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms and should not be construed as being limited to the embodiments set forth herein, but rather, these embodiments are provided so as to more completely and thoroughly understand the present disclosure. It is understood that the drawings and embodiments of the present disclosure are for exemplary purposes only and are not intended to limit the scope of protection of the present disclosure.

[0024] It should be understood that each of the steps recited in the method embodiments of the present disclosure can be performed in different orders and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0025] The term "comprising" and variations thereof as used herein are used inclusively, i.e., "comprising, but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Related definitions are given below in the description of the terms.

[0026] It should be noted that the terms "first", "second", and the like in the present disclosure are merely used to distinguish different devices, modules or units, and do not imply the order or interdependence of the functions performed by these devices, modules or units.

[0027] It should be noted that the terms "one", "multiple" in the present disclosure are illustrative and not restrictive, and those skilled in the art should understand that "one" or "multiple" should be understood as "one or more" unless otherwise explicitly indicated in the context.

[0028] The names of the messages or information exchanged between the devices in the embodiments of the present disclosure are merely used for illustrative purposes, and are not intended to limit the scope of the messages or information.

[0029] Implicit geological modeling is a data-driven geological modeling method that automatically infers subsurface structures and properties by utilizing spatial relationships and physical characteristics in geological data to generate a geological model. Compared with traditional methods, implicit geological modeling has the advantages of high automation, fast modeling speed, and suitability for complex geological environments. Implicit geological modeling is to transform the geological modeling problem into an optimization problem, which optimizes the model parameters to best fit the geological data by minimizing the residual error between the geological data and the model, thereby achieving geological modeling. However, the computational complexity of the implicit geological modeling method is high, especially when dealing with large-scale geological data, traditional methods often cannot meet the accuracy, real-time and efficiency requirements.

[0030] One or more embodiments of the present application provide an implicit geological modeling method based on adaptive grid to solve the problems of long calculation time, low model precision, difficulty in processing complex constraint structure region, and low modeling efficiency of existing implicit geological modeling methods.

[0031] One or more embodiments of the present application introduce an adaptive grid system to fully exert the multi-resolution advantage of the adaptive grid and significantly reduce the number of grid points and the size of the coefficient matrix.

[0032] One or more embodiments of the present application, in view of the significant characteristics of large scale and high complexity of implicit geological modeling data, dynamically adjust the modeling parameters and resolution according to the characteristics of the geological data and specific modeling requirements by means of multi-scale modeling based on adaptive grid, so as to effectively improve the overall precision and reliability of the model.

[0033] One or more embodiments of the present application introduce an adaptive grid system, refine the grid elements in the geological data, and keep the coarse grid unchanged in other regions, thereby avoiding a large amount of invalid calculation for non-critical regions of modeling, and greatly improving the precision and efficiency of the implicit geological modeling method.

[0034] In one or more embodiments of the present application, the refinement process of the adaptive grid method is a highly intelligent and dynamic adjustment process based on specific standards. Each grid element in the grid is regarded as a refinable element, and each element has its own refinement level, which represents the number of refinements of the current element in the adaptive grid refinement process. During initialization, the initial grid of the entire calculation region is divided. This grid is usually relatively coarse and covers the entire region to be solved. Each grid element has an initial refinement number. As the adaptive encryption proceeds, the refinement level of the element will increase when the element needs to be refined. Each refinement operation essentially divides the grid element into a smaller sub-element set according to the established rules. During refinement, the grid element first generates new grid nodes, and then connects the grid nodes to form new grid elements.

[0035] In one or more embodiments of the present application, an adaptive grid data structure is proposed. A layered data structure for the adaptive grid system is designed according to the characteristics of the adaptive grid with different refinement levels, which can effectively store grid information in different density regions and realize fast and efficient data access.

[0036] In one or more embodiments of the present application, an improved finite difference discretization method is proposed and applied to adaptive grids with uneven distribution of refinement levels.

[0037] Please refer to Figure 1 which shows a flow of one embodiment of the adaptive mesh based implicit geological modeling method according to the present disclosure. As shown in Figure 1 the adaptive mesh based implicit geological modeling method includes the following steps:

[0038] Step 101, performing initial mesh division on the calculation region according to the geological modeling parameters and the geological source data, to obtain a first mesh set.

[0039] Step 102, determining a to-be-refined mesh in the first mesh set according to a preset judgment rule.

[0040] Step 103, dividing the to-be-refined mesh into a sub-element set according to a preset refinement rule, to obtain a second mesh set of the calculation region.

[0041] Step 104, storing mesh data of the second mesh set.

[0042] Step 105, performing difference on a second mesh in the second mesh set, and determining a coefficient matrix A according to a difference coefficient.

[0043] Step 106, constructing a linear equation set Ax=b based on the Lagrange multiplier method.

[0044] In this embodiment, the vector b is used to represent point constraints and directional constraints.

[0045] Step 107, solving the linear equation set to obtain a second mesh value, and outputting a modeling result according to the second mesh value.

[0046] The geological modeling parameters or the geological source data can be set according to the specific scene of geological modeling, which is not limited herein.

[0047] The preset judgment rule is used to determine whether to refine the first mesh. For example, the mesh where the control point or the fault point is located is determined as the to-be-refined mesh; for example, the mesh adjacent to the mesh where the control point or the fault point is located is determined as the to-be-refined mesh.

[0048] The preset refinement rule is used to provide a specific way of refinement, and the specific refinement rule can be set according to the actual application.

[0049] In the finite difference method and the finite element method, the mesh is the basis for discretely solving the region.

[0050] The first mesh set can be a mesh set obtained by initially coarsely dividing the calculation region.

[0051] The second mesh set can be a mesh set obtained by refining the first mesh once or multiple times.

[0052] The stored grid data can be read and used in the differential process.

[0053] The linear equation set Ax=b can be constructed based on the Lagrange multiplier method.

[0054] The solving process of the second grid value is obtained by solving the linear equation set, and the mathematical algorithm for solving the linear equation set can be determined. According to the output of the modeling result based on the second grid value, it can be understood that the second grid value is to some extent the modeling result, and the second grid value can be read or presented according to the actual scene by the person skilled in the art, and output as the modeling result.

[0055] It should be noted that the implicit geological modeling method based on adaptive grid provided in the embodiment can more accurately capture the subtle changes of the geological properties around the control points by refining the grid, and ensure that the model is highly consistent with the actual geological conditions at this point, thereby laying a solid precision foundation for the entire model. In other areas except the control points, the setting of the coarse grid can not only avoid excessive investment of computing resources in these areas which have less impact on the overall model precision, prevent the problem of low efficiency caused by unnecessary high-precision calculation, but also significantly reduce the data storage and calculation time on the premise of ensuring the overall quality of the model. Therefore, the implicit geological modeling method can still maintain efficient and stable operation when facing large-scale complex geological scenes, and achieve an optimal balance between precision and efficiency.

[0056] By comparison, the traditional uniform grid uses a fixed grid spacing in the entire calculation area, which means that the same grid resolution is maintained regardless of whether the physical quantity changes in the region, whether it is in a flat area where the gradient of the solution is almost zero, or in a critical area where the physical phenomenon changes sharply and has a very high requirement for precision.

[0057] In some embodiments, the method further comprises: marking the grid according to the refinement level, wherein the grid where the control point or the fault point is located is marked as level 2, the grid directly adjacent to the grid where the control point or the fault point is located is marked as level 1, and the remaining grid is marked as level 0; and determining the grid marked as level 2 or level 1 as the grid to be refined.

[0058] In some embodiments, the grid to be refined is divided into a set of sub-elements according to a preset refinement rule to obtain a second grid element set of the calculation area, including: refining and encrypting the grid in the area where the grid to be refined is located, with a 3*3 grid area centered on the grid where the grid to be refined is located; after completing one refinement process, checking the refinement level of the grid where the grid to be refined is located; if the refinement level of the grid where the grid to be refined is located is less than the specified refinement level, continuing to recursively refine; if the refinement level of the grid to be refined is the specified refinement level minus 1, stopping the recursive process, and refining the grid currently marked as 2 again, so that the grid to be refined reaches the specified refinement level, and the refinement level of the adjacent grids around the grid to be refined differs from that of the grid to be refined by 1.

[0059] In some embodiments, refining and encrypting the grid in the area where the grid to be refined is located includes: adding four edge nodes and one center node to the grid in the area, and then combining the new nodes with the original grid nodes to form four refined grid elements.

[0060] As an example, Figure 2 As shown in the figure, four edge nodes and one center node are added to the mesh. These new nodes are then combined with the original mesh nodes to form four mesh elements of a higher refinement level, thus achieving mesh subdivision. Similarly, the refinement strategy for a 2D quadrilateral regular mesh can be extended to a 3D regular mesh, where the mesh elements are transformed from four-node regular quadrilaterals to eight-node regular hexahedrons.

[0061] In one or more embodiments of the present application, a method of fixing the level difference of the grid is proposed, and the level difference refers to the difference in the refinement level between adjacent grid elements, which reflects the unevenness of the mesh refinement in space. The level difference of the fixed grid can ensure the consistency of the discrete format. In numerical methods, the consistency of the discrete format (such as finite difference, finite element, etc.) is crucial to obtaining an accurate solution. In the adaptive grid method adopted in the present invention, the maximum level difference of adjacent grids is 1, which can maintain a consistent differential format and ensure the accuracy of the numerical solution of the grid system.

[0062] In one or more embodiments of the present application, a recursive adaptive refinement algorithm is proposed to maintain uniform level differences while efficiently achieving mesh refinement. The recursive adaptive refinement algorithm uses a 3x3 grid area centered on the grid where the control point or fault point is located as the basic processing unit, and recursively refines the grid according to a preset refinement level.

[0063] As an example, Figure 3 As shown, Figure 3 The (a)(b)(c)(d)(e) processes shown show the flow of the recursive-based adaptive refinement algorithm. Figure 3The dark dots in (a) represent control points or fault points. According to the adaptive refinement strategy, the grid where they are located should be refined and encrypted. The 3*3 area centered on the current grid where they are located is used as the basic processing unit of the recursive adaptive refinement algorithm.

[0064] like Figure 3 As shown in (b), the refinement algorithm marks the grids according to the refinement level, where the grid where the control point or fault point is located is marked as 2, the grid directly adjacent to the grid where the control point or fault point is located is marked as 1, and the remaining grids are marked as 0. For the grids marked as 2 or 1, the refinement algorithm refines the grid, and the results are shown in Figure 3 As shown in (c), the grid in the area where the control point or fault point is located is refined and encrypted, while other areas still maintain a coarse grid state.

[0065] Fault points or control points can be pre-specified or automatically identified.

[0066] After completing a refinement process, the refinement algorithm will check the refinement level of the grid where the control point or fault point is located. If it is less than the specified refinement level, it will continue to refine recursively. The process is as follows: Figure 3 (c) and Figure 3 As shown in (d), a new round of marking and refinement is performed, still using the 3*3 area centered on the grid where the control point or fault point is located after the last refinement as the processing unit.

[0067] like Figure 3 As shown in (e), when the refinement algorithm detects that the refinement level of the grid where the control point or fault point is located is the specified refinement level minus 1, the recursive process stops and the grid currently marked as 2 is refined again, so that the current grid reaches the specified refinement level, and the refinement level of the surrounding adjacent grids differs from it by 1, ensuring the consistency of the differential format.

[0068] In some embodiments, the grid data of the second grid set is stored, including: storing each level of grid separately according to different refinement levels; wherein, in each single-layer grid structure of the first storage space, each layer of grid is regarded as a uniform grid of the corresponding refinement level resolution; the second storage space stores the marks of the grid points of the single-layer grid, wherein the grid points that actually exist in the second grid set store index values, and the non-existent grid points are marked as -1.

[0069] Layered data structures for adaptive grids such as Figure 4As shown, the grid information of different density regions can be effectively stored, and fast and efficient data access can be achieved. The AdaptiveGridRefiner class is used as a container of the entire adaptive grid system, and the grid of each level is stored separately according to different subdivision levels (i.e., refinement levels). The SingleLevelGrid (which can be understood as a first storage space) stores a single-level grid as a uniform grid corresponding to the resolution of the subdivision level, and the GridPointFlag (which can be understood as a second storage space) stores the flag of the grid point of the single-level grid. In the adaptive grid, the grid points actually existing are stored with their index values, and the grid points not existing are marked as -1. The CellFlag (which can be understood as a second storage space) is used to store the grid flag shown in (b) of FIG. 10. Figure 3

[0070] In this data structure, the grid units are no longer stored in a tree structure, but are stored separately according to different subdivision levels of the adaptive grid, thereby avoiding the huge memory overhead caused by pointers and tree nodes when storing a tree structure. Meanwhile, the new data structure no longer actually constructs a grid, but uses a logical grid to replace it, and only stores the grid points in the grid. When the grid structure is needed, the grid is generated by finding the corresponding grid points. In the single-level grid structure, each level of the grid is stored as a uniform grid system corresponding to the resolution of the subdivision level. Although this approach generates additional memory overhead, it simplifies the storage of the entire grid, all grid points are stored in a sequential structure, and the time overhead of grid point searching is also very small, which is conducive to the subsequent development of finite difference discrete methods.

[0071] In some embodiments, the differentiating the second grid in the second set of grids includes determining whether to add a missing grid point to the second grid, and in response to determining to add the missing grid point to the second grid, interpolating the missing grid point from existing grid points.

[0072] In some embodiments, the determining whether to add the missing grid point to the second grid includes determining whether a grid point of the same level in a neighborhood of a point T to be differentiated is missing, and if the grid point is missing, determining to add the missing grid point.

[0073] In some embodiments, the interpolating the missing grid point from existing grid points in response to determining to add the missing grid point to the second grid includes, if the missing grid point is located on a grid line, adding the missing grid point according to the points at both ends of the grid line, and if the missing grid point is located at a grid center, adding the missing grid point according to the points on the grid line of the grid in which the grid center is located.

[0074] ​In some embodiments, the method further comprises: if the missing grid point is located at the center of the three-dimensional grid, based on the existing points on the grid line of the three-dimensional grid, complementing the missing point on the grid line of the three-dimensional grid to obtain the on-line point of the three-dimensional grid; and based on the on-line point of the three-dimensional grid, complementing the missing point located at the center of the three-dimensional grid.

[0075] As an example, as Figure 5 shown, Figure 5 (a) (b) and (c) of FIG. 1 illustrate three difference methods in a two-dimensional adaptive grid system. In the two-dimensional adaptive grid system, the difference scenarios can be complemented on the grid line or complemented at the grid center according to the neighborhood situation.

[0076] Figure 5 (a) of FIG. 1 illustrates an adaptive difference scenario without complementing points. At this time, point T is located at the center of the subdivision grid, and the same subdivision level grid exists around it, and there is no need to complement points for difference. Taking the difference in the x direction as an example, the difference formula is as shown in the following formula, which is consistent with the finite difference of the uniform grid.

[0077]

[0078] Figure 5 (b) of FIG. 1 illustrates a difference scenario of complementing points on the grid line. In order to perform finite difference on point T, it is observed that points A2 and B2 in the same subdivision level as points A1 and B1 in the neighborhood of point T are missing and need to be complemented. Points A2 and B2 are interpolated by known points T, A3 and B3, respectively, and the formula is as shown below:

[0079]

[0080] After complementing points A2 and B2, the related points involved in the difference in the neighborhood of T all exist, and according to the difference formula, we have:

[0081]

[0082] Figure 5 (c) of FIG. 1 illustrates another difference scenario of complementing points at the grid center. In order to perform finite difference on point T, the neighborhood of T is also checked, and it is found that point A2 in the same subdivision level as point A1 in the x direction is missing and needs to be interpolated. At this time, point A2 is located at the center of the grid, and is interpolated by its neighborhood points T, B1, B2 and B3, as shown in the following formula:

[0083]

[0084] But check point A2 neighborhood found that in addition to point T, points B1, B2, B3 are missing, at this time, B1, B2, B3 need to be supplemented and interpolated, the supplement method is just as Figure 5 (b) shown in the line on the supplement point scene, through the known points C1, C2, C3, C4, points B1, B2, B3 can be obtained:

[0085]

[0086]

[0087] The above formulas are substituted into the difference template, and the difference formula of point T in the x direction is obtained as follows:

[0088]

[0089] As an example, as shown in Figure 6 , it shows the regular hexahedron center supplement point method in three-dimensional adaptive grid. As shown in Figure 6 , in the process of differentiating point T, it is found that point A2 in the same subdivision level as point A1 is missing in the neighborhood, point A2 is located at the center of the regular hexahedron grid, so a new supplement point difference scene appears, that is, the regular hexahedron center supplement point, at this time, point A2 should be obtained by interpolating points T, B1, B2, B3, but B1, B2, B3 are also missing. Observation found that points B1, B2, B3 can be obtained by grid center supplement point from known points C1 to C8 and D1, D2. Based on the grid center supplement point method, point A2 can be obtained as follows:

[0090]

[0091] u _A2 After that, the point T can be differentiated in the manner of uniform grid finite difference. After supplementing the center of the hexahedron supplement point difference method, in the three-dimensional adaptive grid, the finite difference method of any difference scene can be realized according to the normal uniform grid difference, grid line on the supplement point difference, grid center supplement point difference, hexahedron center supplement point difference method combination.

[0092] In one or more embodiments of the application, after completing the difference of all grid points in the adaptive grid system, the difference coefficients are arranged into a coefficient matrix, combined with point constraints and direction constraints, and the linear equation Ax=b is formed by the Lagrange multiplier method. Subsequently, by solving the linear system, the values of all grid points in the adaptive grid system can be obtained.

[0093] Reference will now be made to Figure 7, which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present disclosure. The terminal device in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (such as in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 7 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0094] like Figure 7 As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage device 708 into a random access memory (RAM) 703. Various programs and data required for the operation of the electronic device 700 are also stored in the RAM 703. The processing device 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0095] Typically, the following devices may be connected to the I / O interface 705: an input device 706 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 707 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 708 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 709. The communication device 709 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 7 The electronic device is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0096] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 709, or installed from the storage device 708, or installed from the ROM 702. When the computer program is executed by the processing device 701, the above-mentioned functions defined in the method of the embodiment of the present disclosure are performed.

[0097] It should be noted that the computer-readable medium described above can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any suitable combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program used by or in connection with an instruction execution system, apparatus or device. In the present disclosure, the computer-readable signal medium can include a data signal propagated in baseband or propagated as a carrier wave in a propagated data signal, in which the computer-readable program code is contained. Such a propagated data signal can take many forms, including but not limited to, an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium that can send, propagate or transfer the program for use by or in connection with the instruction execution system, apparatus or device. The program code contained in the computer-readable medium can be transmitted by any suitable medium, including but not limited to, wire, cable, RF (radio frequency), etc., or any suitable combination of the above.

[0098] In some embodiments, the client, server, or both can communicate using any current known or future developed network protocol, such as HTTP (HyperText Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include local area networks ("LAN"), wide area networks ("WAN"), the Internet, and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any current known or future developed networks.

[0099] The computer-readable medium described above can be included in the electronic device described above; or can exist separately from the electronic device, and is not assembled into the electronic device.

[0100] The computer readable medium carries one or more programs when the one or more programs are executed by the electronic device, the electronic device is caused to: perform initial meshing on the calculation region according to the geological modeling parameters and the geological source data to obtain a first mesh set; determine a to-be-refined mesh in the first mesh set according to a preset judgment rule; split the to-be-refined mesh into a sub-element set according to a preset refinement rule to obtain a second mesh set of the calculation region; store mesh data of the second mesh set; perform difference on a second mesh in the second mesh set, and determine a coefficient matrix A according to a difference coefficient; construct a linear equation set Ax=b based on a Lagrange multiplier method, wherein the vector b is used to represent point constraints and direction constraints; solve the linear equation set to obtain a second mesh value, and output a modeling result according to the second mesh value.

[0101] Computer program code for carrying out operations of the present disclosure can be written in any of one or more programming languages, including object oriented programming languages such as Java, Smalltalk, C++, or conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0102] The flow diagrams and the block diagrams in the drawings are illustrations of architectures, functionalities, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of present disclosure. In this regard, each block in the flow diagrams and the block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may

[0103] The units involved in the embodiments described in this disclosure may be implemented in software or hardware, wherein the name of a unit does not necessarily limit the unit itself.

[0104] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0105] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0106] The above description is merely a preferred embodiment of the present disclosure and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also includes other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this disclosure.

[0107] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details have been included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0108] Although the subject matter has been described in language specific to structural features and / or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. An implicit geological modeling method based on adaptive grid, characterized in that: The method comprises: Performing initial grid division on the calculation area according to geological modeling parameters and geological source data to obtain a first grid set; Determining the grid to be refined in the first grid set according to a preset judgment rule; According to a preset refinement rule, the grid to be refined is divided into a set of sub-elements to obtain a second grid set of the calculation area; storing grid data of a second grid set; performing differentiation on a second grid in the second grid set, and determining a coefficient matrix A based on the differentiation coefficients; Based on the Lagrange multiplier method, a linear equation system Ax=b is constructed, where the vector b is used to represent the point constraint and direction constraint conditions; Solving the linear equations to obtain a second grid value, and outputting a modeling result according to the second grid value.

2. The method according to claim 1, characterized in that The step of determining the grids to be refined in the first grid set according to a preset judgment rule includes: The grids are marked according to the refinement level, where the grid where the control point or fault point is located is marked as level 2, the grids directly adjacent to the grid where the control point or fault point is located is marked as level 1, and the remaining grids are marked as level 0; The grid marked as 2 or 1 determines the grid to be refined.

3. The method according to claim 2, characterized in that The method of dividing the grid to be refined into a set of sub-elements according to a preset refinement rule to obtain a second set of grid elements in the calculation area includes: The 3*3 grid area centered on the grid to be refined is used as the basic processing unit, and the grid in the area where the grid to be refined is refined and encrypted; After completing a refinement process, check the refinement level of the grid where the grid to be refined is located; If the refinement level of the grid to be refined is less than the specified refinement level, recursive refinement continues; If the refinement level of the mesh to be refined is the specified refinement level minus 1, the recursive process stops and the mesh currently marked as 2 is refined again so that the mesh to be refined reaches the specified refinement level and the refinement level of the adjacent meshes around the mesh to be refined differs by 1 from that of the mesh to be refined.

4. The method according to claim 3, characterized in that The refining and encrypting of the grid in the area where the grid to be refined is located includes: For the grid in the region, four edge nodes and one center node are added to the grid, and then the new nodes and the original grid nodes are combined to form four refined grid elements.

5. The method according to claim 2, characterized in that The storing of the grid data of the second grid set includes: According to different refinement levels, each level of grid is stored separately; Wherein, in each single-layer grid structure of the first storage space, each layer of grid is regarded as a uniform grid of a corresponding refinement level resolution; The second storage space stores the labels of the grid points of the single-layer grid, wherein the grid points that actually exist in the second grid set store index values, and the grid points that do not exist are marked as -1.

6. The method according to claim 5, characterized in that The performing differentiation on the second grid in the second grid set includes: Determine whether to fill in points on the second grid; In response to determining to fill in points on the second grid, missing grid points are interpolated using existing grid points, and fill-in difference is performed.

7. The method according to claim 6, characterized in that The determining whether to fill in points on the second grid includes: For the point T to be differentiated, determine whether the grid points of the same level in the neighborhood of point T are missing; If missing, make sure to fill in the missing grid points.

8. The method according to claim 7, characterized in that In response to determining to fill in points on the second grid, interpolating missing grid points using existing grid points includes: If the missing grid points are located on the grid line, fill in the missing grid points based on the points at both ends of the grid line segment; If the missing grid point is located at the grid center, the missing grid point is filled in based on the points on the grid line of the grid where the grid center is located.

9. The method according to claim 7, characterized in that In response to determining to fill in points on the second grid, interpolating missing grid points using existing grid points includes: If the missing grid point is located at the center of the 3D grid body, the missing point on the grid line of the 3D grid is completed based on the existing points on the grid line of the 3D grid to obtain the line point of the 3D grid; Based on the online points of the 3D grid, the missing points located at the center of the 3D grid are filled.

10. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 9.

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