An automated geological BIM modeling method and system

Abstract

The application discloses an automatic geological BIM modeling method, adopts space topology theory and machine learning principle to develop auxiliary layering technology, can quickly and reliably help to complete geological layering of drilling logging data, adopts discrete mathematical theory to develop targeted discrete topology data structure, constrained smooth fitting modeling technology and curved surface follow-up grid technology, develops complete space arbitrary form curved surface intersection algorithm and closing technology based on space topology theory and three-dimensional curved surface grid technology, realizes intersection and complete closing between arbitrary geological interfaces, and lays a solid foundation for geological unit body division and volume calculation, conversion of a geological model and a numerical calculation model, and the like, and adopts the technology of combining SaaS mode-based geological BIM modeling to draw a 3D scene and a model, relies on computer three-dimensional technology, and realizes complete programming of the intersection closing and grid optimization process, so that the closed model achievement submission efficiency is greatly improved.

Description

Technical Field

[0001] This invention relates to the field of BIM modeling technology, specifically to an automated geological BIM modeling method and system. Background Technology

[0002] BIM technology is widely used in the construction engineering field, especially in the design and operation phases. As a data technology applied to engineering design, construction, and management, BIM stores and integrates data and information through three-dimensional models. Currently, it primarily serves collaborative work between different disciplines throughout the entire building lifecycle, providing effective support for improving project management. Therefore, introducing geological BIM to model geological bodies can not only create high-precision geological bodies but also meet the requirement of including engineering attribute information within the geological bodies. For this reason, the geological body model can be completed using structural BIM-related professional software.

[0003] Currently, domestic geological BIM modeling software mainly includes two methods:

[0004] 1) Develop geological BIM modules based on general CAD platforms, such as AutoCAD in the United States, Bentley MicroStation platform, and Catia platform in France. However, this approach cannot achieve high-quality geological BIM modeling.

[0005] 2) Based on the French GoCAD pure geological modeling software, because this software was developed for the petroleum industry, it has poor integration with the design and analysis of the geological exploration industry.

[0006] Currently, the main types of 3D geological body modeling include: (1) modeling based on coordinate location information, i.e., geometric modeling, which is often generated from the geometric coordinate information of boreholes, profiles, etc.; (2) modeling based on data values ​​in spatial location, i.e., attribute modeling, where attributes include geophysical indicators, resource content (mineral grade), pollution level, etc. Because there are many methods for obtaining attribute data, there is a problem of multi-disciplinary data fusion. At present, 3D geology is shifting from an early focus on morphological modeling to a focus on both morphological and attribute modeling, while also paying more attention to the integration of models with professional applications, moving towards the direction of geological BIM.

[0007] Given the increasing demand for information technology in geotechnical engineering, timely research and development of geological BIM software can bring new business growth points to enterprises, significantly increasing economic benefits and market competitiveness.

[0008] Therefore, we need to propose an automated geological BIM modeling method and system. Summary of the Invention

[0009] The purpose of this invention is to provide an automated geological BIM modeling method and system. It employs spatial topology theory and machine learning principles to develop an auxiliary layering technology, which can quickly and reliably assist in the geological layering of borehole logging data. It solves the technical bottleneck of rapid modeling of arbitrarily complex geological bodies and is key to achieving complete "forward modeling" and updating geological models during construction. It enables the intersection and complete closure between arbitrary geological interfaces, thus laying a solid foundation for geological unit division and volume calculation, as well as the conversion between geological models and numerical calculation models. It can automatically create three-dimensional geological models in batches based on borehole exploration results, thereby solving the problems mentioned in the background technology.

[0010] To achieve the above objectives, the present invention provides the following technical solution: an automated geological BIM modeling method, comprising the following steps: S1, using spatial topology theory and machine learning principles to divide the standard sequence of boreholes and collect borehole logging data; S2, organizing the collected data using a combination of various constraint strategies, and then modeling the geological body to obtain a model, wherein the combination of various constraint strategies includes fuzzy control point constraints, fuzzy control distance constraints, fuzzy control point plane constraints, and DSI data attribute constraints; S3, processing the model based on spatial topology theory, three-dimensional surface meshing technology, and intersection-closure algorithm. The following steps are performed: S4. A geological model with a completely closed 3D model is obtained through line processing. The intersection and closure algorithm includes a trimming algorithm and a mesh optimization algorithm. S5. Based on the spatial discrete topological relationship data structure and the architecture technology of integrating graphics and data, geological attributes are integrated with the 3D model to obtain a corrected model. S6. Professional geological data from geological mapping, drilling, geophysical exploration, and geochemical exploration are fused into the corrected model to obtain a fused model. S7. Based on the triangular mesh edge exchange algorithm, the fused model is updated synchronously. S8. Based on the modeling, display, and interaction methods of WebGL technology, the fused model is deeply processed to obtain a standardized geological model.

[0011] Preferably, the borehole standard stratification includes the following steps: A1. Generate initial stratification results based on spatial topology theory and machine learning principles, and automatically provide the initial stratification using an algorithm; A2. Repeatedly adjust the stratification in the intermediate result table, calculate various reference indicators in real time, and display the rationality and consistency of the data under the current stratification through various charts; A3. Adjust and store the appropriate data in the database.

[0012] Preferably, when modeling the geological body, the geological interface is regarded as a discretized discontinuous interface, and the geological points and borehole data revealed by geological exploration are used as constraints. The discrete smooth interpolation algorithm obtains the optimal geological interface that meets the constraints by solving the optimal solution of the global roughness function under these constraints.

[0013] Preferably, the cropping algorithm includes the following steps: B1, calculate intersections: the sides intersect with the triangles, or the triangles intersect with each other; B2, connect the intersection lines: based on the positional relationship of the intersection lines, or using spatial geometric relationships; B3, refine and surface the inner triangles of each intersecting triangle: using the triangle boundaries and intersection lines as constraints, perform triangle division under limited constraints;

[0014] Preferably, the mesh optimization algorithm includes the following steps: C1. Accurately record the correspondence between the intersection edges in different faces, and first perform the optimization of the intersection lines, with the two related faces being optimized simultaneously; C2. Perform the optimization outside the intersection lines inside each face.

[0015] Preferably, the spatial discrete topological relationship is as follows: the geological body outline is broken down into spatial points, and the connection relationship between these points is recorded, which together determine the object outline; the spatial points and the connection relationship are independent of each other, allowing one element to be changed at will without affecting the other, and changing one of them can change the object shape.

[0016] Preferably, the professional geological data includes point-to-line constraints; the point in the point-to-line constraint specifically refers to a discrete point, and when using point-to-line or surface constraints, the point is also called a control point; a node refers to a point on a line or a point on a triangulation network in a surface, and a control node specifically refers to a node whose spatial position remains unchanged when interpolating a line or surface; a control point refers to a point used to constrain a line, or a point used to constrain a surface, or a node in a line; point or line-to-surface constraints: as the exploration progresses and the collected data increases, there are deviations between the constructed model and geological interface and the newly added data, which can be modified and updated by using point or line-to-surface constraints; face-to-face constraints: when the spatial position of one surface constrains another surface, the nodes in the constrained surface can only be converted into discrete points before constraining the other surface.

[0017] On the other hand, this invention proposes an automated geological BIM modeling system, comprising:

[0018] The data collection module is used to divide the standard sequence of boreholes using spatial topology theory and machine learning principles, and to complete the collection of borehole logging data.

[0019] The constraint module is used to process the collected data using a variety of constraint combination strategies, and then to model the geological body to obtain the model. The various constraint combination strategies include fuzzy control point constraints, fuzzy control distance constraints, fuzzy control point plane constraints, and DSI data attribute constraints.

[0020] The 3D modeling module is used to process the model based on spatial topology theory, 3D surface meshing technology, and intersection closure algorithm to obtain a geological model with a completely closed 3D model. The intersection closure algorithm includes a trimming algorithm and a mesh optimization algorithm.

[0021] The correction module is used to integrate geological attributes with 3D models based on spatial discrete topological relationship data structures and a framework technology that integrates graphics and data to obtain a corrected model.

[0022] The fusion module is used to integrate specialized geological data from geological mapping, drilling, geophysical exploration, and geochemical exploration into the correction model to obtain a fused model.

[0023] The update module is used to synchronously update the fusion model based on the triangular network edge-swapping algorithm.

[0024] The modeling module is used for modeling, displaying, and interacting with WebGL technology, and it performs in-depth processing of the fused model to obtain a standardized geological model.

[0025] Compared with the prior art, the beneficial effects of the present invention are:

[0026] This invention employs spatial topology theory and machine learning principles to divide standard sequence borehole layers and collect borehole logging data. The collected data is then processed using various constraint combination strategies, followed by geological body modeling to obtain a model. These constraint combination strategies include fuzzy control point constraints, fuzzy control distance constraints, fuzzy control point plane constraints, and DSI data attribute constraints. Based on spatial topology theory, 3D surface meshing technology, and intersection-closure algorithms, the model is processed to obtain a fully closed 3D geological model. The intersection-closure algorithms include trimming algorithms and mesh optimization algorithms. Based on spatial discrete topological relational data structures and a framework technology integrating graphics and data, geological attributes are integrated with the 3D model to obtain a corrected model. Professional geological data from geological mapping, drilling, geophysical exploration, and geochemical exploration are fused into the corrected model to obtain a fused model. Based on the triangular mesh edge-exchange algorithm, the fused model is synchronously updated. Finally, based on WebGL technology for modeling, display, and interaction, the fused model undergoes in-depth processing to obtain a standardized geological model. To address the practical problems that soil layering results cannot guarantee the reliability of three-dimensional space and cannot meet the data quality requirements of three-dimensional modeling, an auxiliary layering technology was developed using spatial topology theory and machine learning principles. This technology can quickly and reliably help complete the geological layering of borehole logging data. Based on spatial topology theory and three-dimensional curved surface mesh technology, a complete algorithm for intersecting and closing curved surfaces of arbitrary spatial shapes was developed. This technology enables the intersection and complete closure between arbitrary geological interfaces, thus laying a solid foundation for the division of geological units and volume calculation, as well as the conversion between geological models and numerical calculation models. Attached Figure Description

[0027] Figure 1 This is a flowchart of the method of the present invention;

[0028] Figure 2 This is a technical roadmap for the standard sequence division of boreholes in this invention;

[0029] Figure 3 This is a schematic diagram illustrating the clipping and mesh optimization techniques of this invention;

[0030] Figure 4 This is a technical schematic diagram illustrating the cropping and mesh optimization techniques of this invention.

[0031] Figure 5 This is a schematic diagram illustrating the discrete and topological aspects of the present invention;

[0032] Figure 6 This is a schematic diagram of the point constraint lines of the present invention;

[0033] Figure 7 This is a diagram illustrating the implementation principle and technical roadmap of the point constraint line in this invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Please see Figure 1-7 This invention provides an automated geological BIM modeling method, comprising the following steps:

[0036] S1. The standard sequence of boreholes was divided using spatial topology theory and machine learning principles, and borehole logging data was collected.

[0037] Specifically, borehole standard sequence division: In response to the practical problem that soil stratification results cannot guarantee the reliability of three-dimensional space and cannot meet the data quality requirements of three-dimensional modeling, auxiliary sequence division based on spatial topology theory and machine learning principles is adopted to complete the standard sequence division of borehole logging data.

[0038] In S1, the standard borehole stratification includes the following steps: A1. Generate initial stratification results based on spatial topology theory and machine learning principles, and automatically provide the initial stratification using algorithms; A2. Repeatedly adjust the stratification in the intermediate results table, calculate various reference indicators in real time, and display the rationality and consistency of the data under the current stratification through various charts; A3. Adjust and store the appropriate data in the database.

[0039] S2. The collected data is processed using a combination of various constraint strategies, and then geological body modeling is performed to obtain the model. The combination of various constraint strategies includes fuzzy control point constraints, fuzzy control distance constraints, fuzzy control point plane constraints, and DSI data attribute constraints.

[0040] Specifically, site interpolation algorithms and automatic stratigraphic connections: For discrete smooth interpolation algorithms (i.e., DSI interpolation) for geological body modeling, we have developed a variety of constraint combination techniques to serve the accuracy control in the modeling and data interpolation process. These constraint combination techniques include fuzzy control point constraints, fuzzy control distance constraints, fuzzy control point plane constraints, and DSI data attribute constraints.

[0041] In S2, the geological interface is regarded as a discretized discontinuous interface, and the geological points and borehole data revealed by geological exploration are used as constraints. The discrete smooth interpolation algorithm obtains the optimal geological interface that meets the constraints by solving the optimal solution of the global roughness function under these constraints.

[0042] DSI interpolation is an interpolation theory based on discrete mathematics. DSI has the following advantages:

[0043] First, it can directly model using almost any data format without the need to construct auxiliary profiles, and instead ensures the model's accuracy and geological rationality through constraints;

[0044] Second, it can easily construct complex models, such as multi-valued lens bodies and cave models, as well as overburden models, which Kriging interpolation method struggles to handle.

[0045] Third, DSI modeling is a continuous process of improvement and correction, which is completely consistent with the exploration and understanding process of geological bodies. The one-time "dead" grid modeling method cannot meet this requirement.

[0046] Fourth, it can construct discontinuous models, such as fault models. The DSI method can easily complete this type of modeling, while the Kriging interpolation method has difficulty in handling this type of problem.

[0047] Fifth, DSI constraints can be diverse, and multiple constraints of the same type can appear at the same location. DSI technology can also comprehensively fit the location of a point based on different weight factors of the same type of constraints. For example, in geophysical modeling, comprehensive modeling can be performed based on the data interpreted by different geophysical methods and the confidence weight factor of the geophysical method.

[0048] Define a three-dimensional geological discrete model Where Ω represents all the nodes that make up the model, and N is the neighborhood set of each node. C is the n-order vector attribute function for each node, and C is the constraint for each node.

[0049] Define function

[0050]

[0051] Where R(φ) is the global roughness function, and ρ(φ) is the global constraint violation function. It is a constraint factor. It is a balancing factor.

[0052] DSI solution In practice, it means minimizing the function R*(φ), that is... Therefore, we obtain

[0053]

[0054] in:

[0055]

[0056]

[0057]

[0058]

[0059]

[0060]

[0061] in This is the constraint coefficient.

[0062] Based on the actual constraints, constraint coefficients under different conditions can be obtained, and then the optimal solution can be obtained iteratively using the above formula. The values ​​are then used to finally fit a geometric model that meets the constraints.

[0063] S3. Based on spatial topology theory, three-dimensional surface meshing technology, and cross-cutting closure algorithm, the model is processed to obtain a geological model of a completely closed three-dimensional model. The cross-cutting closure algorithm includes a trimming algorithm and a mesh optimization algorithm.

[0064] Specifically, a sectioning operation model based on a 3D model is created: based on spatial topology theory and 3D surface meshing technology, an intersection closure algorithm is developed and implemented. The intersection closure algorithm includes a trimming algorithm and a mesh optimization algorithm to solve the practical problem of 3D model sectioning operation, realize the submission of closed geological models with arbitrarily complex geological intersection relationships, and obtain a completely closed geological model.

[0065] In S3, the pruning algorithm includes the following steps:

[0066] B1. Calculate intersections: the intersection of a side with a triangle, or the intersection of two triangles;

[0067] B2. Connecting lines: Based on the positional relationship of the intersecting line segments, or by utilizing spatial geometric relationships;

[0068] B3. Refine and surface the inner triangles of each intersecting triangle: Use the triangle boundaries and intersection lines as constraints to perform triangle division under limited constraints;

[0069] The grid optimization algorithm includes the following steps:

[0070] C1. Accurately record the correspondence between the intersection edges in different faces, first perform the intersection optimization, and then perform the optimization on the two related faces simultaneously;

[0071] C2. Perform optimization outside the intersection line within each face.

[0072] The trimming algorithm possesses the capability to perform intersection operations on arbitrarily complex geological intersection relationships and obtains a common-node intersection mesh model, overcoming the global challenge of intersection operations between discrete meshes. By leveraging the intersection closure of the trimming algorithm, a closed model submission can be achieved while fully preserving the accuracy of the geological model.

[0073] The mesh optimization algorithm optimizes the intersecting computational mesh model while maximizing the accuracy of the geological model, overcoming the technical bottleneck of converting geological models into numerical computation models. Based on computer 3D technology, the intersecting closure and mesh optimization processes are fully programmed, greatly improving the efficiency of submitting closed model results and possessing significant engineering application value.

[0074] S4. Based on the spatial discrete topological relationship data structure and the architecture technology of integrating graphics and data, geological attributes are integrated with the three-dimensional model to obtain a corrected model.

[0075] Specifically, the integration of geological attributes and 3D models: the integration of graphics and data ensures the compatibility between geological attributes and 3D models, and the development of a data structure based on spatial discrete topological relationships and an architecture technology for the integration of graphics and data;

[0076] In S4, spatial discrete topological relationships are defined as follows: the outline of a geological body is broken down into spatial points (discrete) and the connection relationships between these points (topology) are recorded, which together determine the outline of the object. The spatial points and the connection relationships are independent of each other (discrete), allowing one element to be changed at will without affecting the other. Changing one of them can change the shape of the object.

[0077] Figure 4 This schematically illustrates the meaning of discrete and topological. Figure 4 The leftmost diagram represents the most basic unit of a discrete, topological data structure: a single point. It is worth noting that:

[0078] 1. Each point is described by its spatial location using (X, Y, Z) values;

[0079] Second, each point can carry a custom index, which is equivalent to the coordinates (X, Y, Z);

[0080] 3. Multiple points are allowed to form a collection.

[0081] Points carry custom index values ​​in a way equivalent to coordinate values, which is the foundation of attribute modeling and professional analysis.

[0082] S5. Integrate professional geological data from geological mapping, drilling, geophysical exploration, and geochemical exploration into the correction model to obtain the fused model.

[0083] Specifically, multi-disciplinary geological model fusion: effectively integrate professional geological data from geological mapping, drilling, geophysical exploration, and geochemical exploration to improve the accuracy and reliability of the model, with a focus on developing multi-disciplinary fusion modeling technologies for point-to-line constraints, point or line-to-surface constraints, and face-to-face constraints;

[0084] Constraint modeling is one of the important technologies for data fusion.

[0085] In S5, point-to-line constraints: a point specifically refers to a discrete point. When using point-to-line or surface constraints, a point is also called a control point; a node refers to a point on a line or a point on a triangulation network in a surface. Control nodes specifically refer to nodes that maintain their spatial position when interpolating a line or surface; control points refer to points used to constrain lines, points used to constrain surfaces, or nodes in a line.

[0086] Point or line-area constraints: As exploration progresses and data collection increases, discrepancies may arise between the established models and geological interfaces and newly added data. Point or line-area constraints can be used to modify and update the models and geological interfaces.

[0087] Face-to-face constraint: When the spatial position of one face constrains another face, the nodes in the constraining face can only be converted into discrete points before constraining the other face.

[0088] S6. Based on the triangular network edge-swapping algorithm, the fusion model is updated synchronously.

[0089] Specifically, geological model editing and geotechnical analysis: Develop a triangulation edge-exchange algorithm to achieve simultaneous updates of strata in two-dimensional profiles and three-dimensional models within a preset range;

[0090] To improve the accuracy and rationality of geological interfaces, a triangulation edge-exchange algorithm was developed to achieve the synchronous updating of strata in two-dimensional profiles and three-dimensional models within a preset range.

[0091] To address geological phenomena such as pinch-outs and fault cutting, a rapid simulation technology for discontinuous interfaces based on computer graphics was developed.

[0092] To address the irregular spatial distribution of geological body attribute information, a grid partitioning technique based on an attribute-containing geological model was developed.

[0093] Based on a closed geological model, a method using tetrahedral and hexahedral meshes for spatial filling was developed to meet the requirements of converting the geological model into a numerical model for calculation.

[0094] Based on a closed geological model, it is very convenient to submit and display the solid model, display the three-dimensional profile solid volume, and calculate the earthwork volume.

[0095] This method enables the direct output of geological models into mainstream numerical software models, such as FLAC3D, 3DEC, and ANSYS.

[0096] S7. A modeling, display, and interaction method based on WebGL technology is used to obtain a standardized geological model through in-depth processing of the fused model.

[0097] Specifically, geological BIM modeling based on the SaaS model: To facilitate real-time modeling, viewing, and lightweight sharing of geological data, a modeling, display, and interaction method based on WebGL technology was developed, including the creation, display, and cross-sectional interaction of 3D models in a browser. This addresses the shortcomings of traditional workflows in geological modeling, such as reliance on specific software, inconvenience in sharing, and difficulty in multi-person collaboration.

[0098] In S7, WebGL is a 3D graphics protocol that provides hardware-accelerated 3D rendering for HTML5 Canvas. Web developers can leverage the system's graphics card to smoothly display 3D scenes and models in the browser, and also create complex navigation and data visualizations. The WebGL standard eliminates the hassle of developing dedicated rendering plugins for web pages and can be used to create website pages with complex 3D structures.

[0099] WebGL relies on a new drawing mechanism called shaders. Shaders provide a flexible and powerful way to draw two-dimensional or three-dimensional graphics, and all WebGL implementations must use them. Shaders are not only powerful but also more complex; they cannot be manipulated with a single simple drawing command.

[0100] Currently, the scope of BIM has been extended to geological exploration, and its integration with office management is required, broadening the traditional scope of BIM work and introducing new technical requirements. The core requirements include:

[0101] 1) Requirements of geological exploration institutes for 3D modeling technology in response to the irregularity and uncertainty of geological body morphology;

[0102] 2) Geological body attribute information (such as wave velocity, static probe value, etc.) is an integral part of the geological body and is distributed throughout the geological body. External database recording methods cannot reflect this inherent characteristic, and attribute expression puts forward new requirements for program data structure.

[0103] 3) Given the inherent differences between the morphology and properties of geological bodies and their superstructures, the interface between the two becomes an unavoidable issue;

[0104] 4) Cross-disciplinary collaboration: Emphasizing data interfaces and collaboration between geological exploration and superstructure;

[0105] Due to the inherent characteristics of natural geological bodies and geological work, geological body modeling needs to be based on discrete mathematics theory. Therefore, this application chose discrete smooth interpolation (DSI) theory for modeling and data processing. At the same time, this application studies an important component of the information system of the construction industry, which is also the most technically challenging and least mature link.

[0106] Currently, similar products on the market are mainly based on a client / server architecture, which has the following shortcomings: weak professional collaboration, weak data management capabilities, complex upgrades and maintenance, high single-machine performance requirements, high professional requirements for users, insufficient intelligence, and a high barrier to entry. The SaaS-based geological BIM modeling software system proposed in this application can avoid the costs and risks associated with software deployment, avoid software processing and costs, and at the same time ensure high levels of system functionality, stability, and data security.

[0107] This invention also provides an automated geological BIM modeling system, comprising:

[0108] The data collection module is used to divide the standard sequence of boreholes using spatial topology theory and machine learning principles, and to complete the collection of borehole logging data.

[0109] The constraint module is used to process the collected data using a variety of constraint combination strategies, and then to model the geological body to obtain the model. The various constraint combination strategies include fuzzy control point constraints, fuzzy control distance constraints, fuzzy control point plane constraints, and DSI data attribute constraints.

[0110] The 3D modeling module is used to process the model based on spatial topology theory, 3D surface meshing technology, and intersection closure algorithm to obtain a geological model with a completely closed 3D model. The intersection closure algorithm includes a trimming algorithm and a mesh optimization algorithm.

[0111] The correction module is used to integrate geological attributes with 3D models based on spatial discrete topological relationship data structures and a framework technology that integrates graphics and data to obtain a corrected model.

[0112] The fusion module is used to integrate specialized geological data from geological mapping, drilling, geophysical exploration, and geochemical exploration into the correction model to obtain a fused model.

[0113] The update module is used to synchronously update the fusion model based on the triangular network edge-swapping algorithm.

[0114] The modeling module is used for WebGL-based modeling, display, and interaction methods, and for deep processing of fused models to obtain standardized geological models.

[0115] In some other embodiments, the automated geological BIM modeling system may also include:

[0116] This includes a specification module for specifying standard module files, wherein each component in the standard module file contains component parameter information and additional information;

[0117] An encoding module is used to assign a unique first-class code to each component in the standard module file;

[0118] The storage module is used to store standard module files with first-class encoding into the standard library;

[0119] The construction module is used to create project assembly files, import the component parameter information of the standard module file and the first type of code corresponding to each component into the project assembly file, construct each component corresponding to the parameter information in the project assembly file to form a standard module file, and assign a unique second type of code to these components;

[0120] The mapping module is used to establish a mapping relationship between components in the standard module files within the standard library and components in the project assembly files by mapping the first type of encoding to the second type of encoding;

[0121] The import module is used to import additional information of components from standard module files in the standard library into a component when additional information needs to be assigned to a component in the project assembly file, through a mapping relationship.

[0122] The "Select Module" command retrieves the standard module files imported from the same project assembly file, allowing you to select individual or all of these standard module files.

[0123] The operation module is used to obtain commands for moving, rotating, or modifying component parameter information and additional information of simultaneously selected standard module files, and to simultaneously select, move, rotate, or modify component parameter information and additional information of these standard module files.

[0124] In this embodiment, addressing the practical problem that soil layer stratification results cannot guarantee the reliability of three-dimensional space and cannot meet the data quality requirements of three-dimensional modeling, an auxiliary stratification technology is developed using spatial topology theory and machine learning principles. This technology can quickly and reliably help complete the geological stratification of borehole logging data. Based on spatial topology theory and three-dimensional curved surface mesh technology, a complete spatial arbitrary shape curved surface intersection algorithm and closure technology are developed, realizing the intersection and complete closure between arbitrary geological interfaces. This lays a solid foundation for the division of geological units and volume calculation, as well as the conversion between geological models and numerical calculation models.

[0125] In addition, this application embodiment also provides a terminal device, which includes a processor, a memory, and a bus. The memory stores machine-readable instructions that the processor can execute. When the terminal device is running, the processor communicates with the memory through the bus, and the processor executes the machine-readable instructions to perform the steps of the above-described automated geological BIM modeling method.

[0126] Furthermore, this application embodiment also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the above-described automated geological BIM modeling method.

[0127] Specifically, the storage medium can be a general-purpose storage medium, such as a portable disk or hard disk. When the computer program on the storage medium is run, it can execute the aforementioned automated geological BIM modeling method.

[0128] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An automated geological BIM modeling method, characterized in that: Includes the following steps: S1. The standard sequence of borehole layers is divided using spatial topology theory and machine learning principles, and borehole logging data is collected. S2. The collected data is organized using a combination of various constraint strategies, and then geological body modeling is performed to obtain the model. The combination of various constraint strategies includes fuzzy control point constraints, fuzzy control distance constraints, fuzzy control point plane constraints, and DSI data attribute constraints. S3. Based on spatial topology theory, three-dimensional surface meshing technology, and cross-cutting closure algorithm, the model is processed to obtain a geological model with a completely closed three-dimensional model. The cross-cutting closure algorithm includes a trimming algorithm and a mesh optimization algorithm. S4. Based on the spatial discrete topological relationship data structure and the architecture technology of integrating graphics and data, geological attributes are integrated with the three-dimensional model to obtain a corrected model; S5. Integrate professional geological data from geological mapping, drilling, geophysical exploration, and geochemical exploration into the correction model to obtain the fused model; S6. Based on the triangular network edge-swapping algorithm, the fusion model is updated synchronously; S7. A modeling, display, and interaction method based on WebGL technology is used to obtain a standardized geological model through in-depth processing of the fused model.

2. The automated geological BIM modeling method according to claim 1, characterized in that: The standard sequence division of boreholes includes the following steps: A1. Based on spatial topology theory and machine learning principles, generate initial stratification results and automatically provide initial stratification using algorithms; A2. Repeatedly adjust the stratification in the intermediate results table, calculate various reference indicators in real time, and display the rationality and consistency of the data under the current stratification through various charts; A3. Adjust the data entry process to ensure it is appropriate.

3. The automated geological BIM modeling method according to claim 1, characterized in that: In the geological body modeling, the geological interface is regarded as a discretized discontinuous interface, and the geological points and borehole data revealed by geological exploration are used as constraints. The discrete smooth interpolation algorithm obtains the optimal geological interface that meets the constraints by solving the optimal solution of the global roughness function under these constraints.

4. The automated geological BIM modeling method according to claim 1, characterized in that: The cropping algorithm includes the following steps: B1. Calculate intersections: the intersection of a side with a triangle, or the intersection of two triangles; B2. Connecting lines: Based on the positional relationship of the intersecting line segments, or by utilizing spatial geometric relationships; B3. Refine and surface the inner triangles of each intersecting triangle: Use the triangle boundaries and intersection lines as constraints to perform triangle division under limited constraints; The grid optimization algorithm includes the following steps: C1. Accurately record the correspondence between the intersection edges in different faces, first perform the intersection optimization, and then perform the optimization on the two related faces simultaneously; C2. Perform optimization outside the intersection line within each face.

5. The automated geological BIM modeling method according to claim 1, characterized in that: The spatial discrete topological relationship is as follows: the outline of a geological body is broken down into spatial points, and the connection relationships between these points are recorded. These points together determine the outline of the object. The spatial points and the connection relationships are independent of each other, allowing one element to be changed at will without affecting the other. Changing one of them can change the shape of the object.

6. The automated geological BIM modeling method according to claim 1, characterized in that: The professional geological data includes point-to-line constraints; the point in the point-to-line constraint specifically refers to a discrete point. When using point-to-line or surface constraints, the point is also called a control point; the node refers to a point on a line or a point on a triangular network in a surface. The control node specifically refers to a node whose spatial position remains unchanged when interpolating a line or surface; the control point refers to a point used to constrain a line, a point used to constrain a surface, or a node in a line. Point or line-area constraints: As exploration progresses and data collection increases, discrepancies may arise between the established models and geological interfaces and newly added data. Point or line-area constraints can be used to modify and update the models and geological interfaces. Face-to-face constraint: When the spatial position of one face constrains another face, the nodes in the constraining face can only be converted into discrete points before constraining the other face.

7. An automated geological BIM modeling system, characterized in that, include: The data collection module is used to divide the standard sequence of boreholes using spatial topology theory and machine learning principles, and to complete the collection of borehole logging data. The constraint module is used to process the collected data using a variety of constraint combination strategies, and then to model the geological body to obtain the model. The various constraint combination strategies include fuzzy control point constraints, fuzzy control distance constraints, fuzzy control point plane constraints, and DSI data attribute constraints. The 3D modeling module is used to process the model based on spatial topology theory, 3D surface meshing technology, and intersection closure algorithm to obtain a geological model with a completely closed 3D model. The intersection closure algorithm includes a trimming algorithm and a mesh optimization algorithm. The correction module is used to integrate geological attributes with 3D models based on spatial discrete topological relationship data structures and a framework technology that integrates graphics and data to obtain a corrected model. The fusion module is used to integrate specialized geological data from geological mapping, drilling, geophysical exploration, and geochemical exploration into the correction model to obtain a fused model. The update module is used to synchronously update the fusion model based on the triangular network edge-swapping algorithm. The modeling module is used for modeling, displaying, and interacting with WebGL technology, and it performs in-depth processing of the fused model to obtain a standardized geological model.

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