A Geomechanics Data Visualization Method and System Based on a Hybrid Data Model

Abstract

The present invention relates to the technical field of geomechanics data research, and in particular to a geomechanics data visualization method and system based on a hybrid data model. Its technical solutions include data collection and collation, hybrid data model construction, visualization algorithm design and application, and visualization result display and interaction. Data collection and collation: Collect geomechanics data including geological structure data, rock mechanics parameter data, and in-situ stress data. The present invention can help geologists more deeply understand the complex relationship between geological structure evolution and rock mechanics behavior, and provide strong data visualization support for the development of geological theories; it can predict geological risks in advance, optimize engineering design schemes, and improve engineering safety and economic benefits; through the accurate visualization and in-depth analysis of geomechanics data, it can more accurately evaluate the possibility of disasters occurring and the potential impact range, providing key technical support for disaster warning and prevention measure formulation.

Description

Technical Field

[0001] The present invention relates to the technical field of geomechanics data research, and particularly relates to a method and system for visualizing geomechanics data based on a hybrid data model. Background Art

[0002] In geomechanics research, the data sources are extensive and complex, including geological structure data, rock mechanics parameter data, in-situ stress data, etc. Traditional data visualization methods often have some defects. For example, a single data model is difficult to comprehensively and accurately express the multi-dimensional characteristics of geomechanics data, resulting in the loss of data details; when dealing with large-scale geomechanics data, the visualization efficiency is low, and the key information in the data cannot be quickly and effectively displayed; the mining of the correlation relationship between different types of data is insufficient, making the geomechanics analysis not deep and comprehensive enough.

[0003] Therefore, this application proposes a method and system for visualizing geomechanics data based on a hybrid data model. Summary of the Invention

[0004] The purpose of the present invention is to address the problem that the geomechanics data analysis in the background art is not deep and comprehensive enough, and to propose a method and system for visualizing geomechanics data based on a hybrid data model.

[0005] In a first aspect, this application provides a method for visualizing geomechanics data based on a hybrid data model, including the following steps:

[0006] S1. Data collection and arrangement: Collect geomechanics data including geological structure data, rock mechanics parameter data, and in-situ stress data;

[0007] S2. Construction of a hybrid data model, specifically including:

[0008] S201. Data classification and preprocessing: Classify geomechanics data into discrete data and continuous data, perform coding processing on the discrete data, and perform normalization processing on the continuous data according to a formula;

[0009] S202. Construction of a discrete data model: Use a data structure based on graph theory to construct a discrete data model, with geological structures and fault discrete elements as nodes, construct edges according to their spatial relationships, and set geological structure type codes and position coordinate attributes for the nodes;

[0010] S203. Construction of a continuous data model: Use a three-dimensional spatial grid model to represent continuous data, determine the spatial range of the geological body and divide it into small cube units, and fill the continuous data into the corresponding units according to the spatial position;

[0011] S204. Model Association: Establish an indexing mechanism to associate the discrete data model with the continuous data model;

[0012] S3. Visualization Algorithm Design and Application, specifically including:

[0013] Multi-scale Visualization:

[0014] Set the macro-scale threshold range as [0, 0.3], and use simplified geometric figures to display the overall outline of the geological structure and the large-scale in-situ stress trend. The figure is drawn based on the geological structure node position information in the discrete data model and the macro in-situ stress trend data in the continuous data model;

[0015] Set the meso-scale threshold range as (0.3, 0.7], and use a semi-transparent surface to represent the surface of the geological body. Map the continuous data to the surface color and texture and label the key structure information of the discrete data. The surface is constructed based on the geological structure boundary information in the discrete data model and the rock mechanics parameter data in the continuous data model;

[0016] Set the micro-scale threshold range as (0.7, 1], and use volume rendering technology to visualize the small cube units in the continuous data model. Map the rock mechanics property data to color and transparency. The volume rendering is performed according to the data association visualization algorithm based on ray tracing;

[0017] S4. Visualization Result Display and Interaction: Develop a visualization software platform, which includes a data import module, a model construction module, a visualization setting module, an interactive operation module, and a data query module. Each module works together to achieve the visualization and interactive operation functions of geomechanics data.

[0018] Optionally, the normalization formula is:

[0019] ;

[0020] Wherein, is the normalized value, is the original data value, and are the minimum and maximum values in this data type respectively.

[0021] Optionally, in the step S3, the data association visualization algorithm: adopt the data association visualization algorithm based on ray tracing, and the formula is:

[0022] ;

[0023] ;

[0024] ;

[0025] Among them, is the final pixel color value at the screen coordinates and is the number of sampling points for ray tracing, is the position of the ray at the th sampling point, and are the sampling step sizes, is the transmittance of the ray from the starting point to the sampling point and is the extinction coefficient of the medium on the ray propagation path and is the illumination intensity at the sampling point and is the object color at the sampling point The object color at the sampling point is jointly determined by discrete data and continuous data, and the correlation between discrete data and continuous data is demonstrated through the propagation process of the ray in the mixed data model.

[0026] Optionally, the data import module specifically includes:

[0027] Design a user interface to provide a file selection dialog box that supports multiple common geomechanics data file formats;

[0028] The background program automatically calls the corresponding parsing function according to the selected file format to read the data into memory, and processes the data according to the data classification and preprocessing rules to construct a discrete data list and a continuous data array.

[0029] Optionally, the model construction module specifically includes:

[0030] Use the processed discrete data to construct a discrete data model based on graph theory, including creating node objects and setting geological structure type codes and position coordinate attributes, and creating edge objects according to spatial relationships and associating them with the corresponding nodes;

[0031] Create a three-dimensional space grid object, determine the range and resolution, fill the data in the continuous data array into the corresponding grid cells, and establish an index association with the discrete data model.

[0032] Optionally, the visualization setting module specifically includes:

[0033] Provide a multi-scale visualization switching button and call the corresponding visualization function according to the selected scale threshold range;

[0034] In the macroscopic scale visualization setting, allow users to customize the display attributes such as the color, size, and transparency of the simplified geometric graphics, as well as the style and annotation information of the in-situ stress direction arrows;

[0035] The mesoscopic scale visualization setting interface provides functions for selecting surface color mapping schemes, uploading and adjusting texture images, and setting the font, size, and color of discrete structural information annotations;

[0036] Microscopic scale visualization settings allow users to adjust the transfer function parameters of volume rendering, including the color-data value mapping curve and the transparency-data value mapping curve.

[0037] Optionally, the interaction operation module specifically includes:

[0038] Implement the mouse wheel zoom function. By listening to the mouse wheel event, adjust the camera's field of view range according to the scrolling direction and amplitude;

[0039] Press and drag the left mouse button to implement the pan operation. Update the camera's position coordinates according to the calculated mouse drag displacement;

[0040] Press and drag the right mouse button to implement the rotation operation. Adjust the camera's rotation angle according to the mouse drag angle information.

[0041] Optionally, the data query module specifically includes:

[0042] When the user clicks on any position in the visualization interface, obtain the three-dimensional coordinate information corresponding to the click position;

[0043] Search in the hybrid data model according to the coordinate information, and query the node information of the discrete data model and the data values in the grid cells of the continuous data model where the position is located;

[0044] Display the query results to the user in the form of a pop-up window or an information panel, including the data name, value, and brief description.

[0045] In a second aspect, the present application provides a geomechanical data visualization system based on a hybrid data model, including:

[0046] A data classification and preprocessing unit for receiving geomechanical data, classifying it into discrete data and continuous data, performing encoding processing on the discrete data, performing normalization processing on the continuous data, and the normalization processing is based on the normalization formula:

[0047] ;

[0048] Execute;

[0049] A hybrid data model construction unit that constructs a discrete data model based on graph theory, uses geological structures and fault discrete elements as nodes, constructs edges according to spatial relationships, and at the same time constructs a continuous data model using a three-dimensional spatial grid model, and establishes an index association between the two;

[0050] A visualization algorithm execution unit sets a multi-scale threshold range, which is divided into a macro scale [0, 0.3], a meso scale (0.3, 0.7], and a micro scale (0.7, 1]. At the macro scale, a simplified geometric figure is used to display the overall contour of the geological structure and the large-scale in-situ stress trend. At the meso scale, a semi-transparent surface is used to represent the surface of the geological body and map continuous data to display the differences in rock mechanics parameters, and key structural information of discrete data is marked. At the micro scale, volume rendering technology is used to visually display the internal mechanical properties of rocks for the small cube units in the continuous data model, and the correlation between discrete data and continuous data is shown through the propagation process of light in the mixed data model;

[0051] A visualization system function module integration unit includes a data import module, a visualization setting module, an interactive operation module, and a data query module.

[0052] Optionally, in the visualization system function module integration unit,

[0053] The data import module has a designed user interface and provides a file selection dialog box that supports multiple common geological mechanics data file formats. The background program can automatically call the corresponding parsing function according to the selected file format to read the data into memory and process the data according to the data classification and preprocessing rules to construct a discrete data list and a continuous data array;

[0054] The visualization setting module can provide multi-scale visualization switching buttons, call the corresponding visualization function according to the selected scale threshold range, and allow the user to perform corresponding visualization settings at different scales. For example, in the macro scale visualization setting, the user is allowed to customize the display attributes of the color, size, and transparency of the simplified geometric figure, as well as the style and annotation information of the in-situ stress direction arrow. The meso scale visualization setting interface provides functions for selecting a surface color mapping scheme, uploading and adjusting texture images, and setting the font, size, and color of the discrete structural information annotation. The micro scale visualization setting allows the user to adjust the transfer function parameters of volume rendering, including the color-data value mapping curve and the transparency-data value mapping curve;

[0055] The interactive operation module implements the mouse wheel zoom function. By listening to the mouse wheel event, the camera field of view range is adjusted according to the scrolling direction and amplitude. Pressing and dragging the left mouse button realizes the pan operation, and the camera position coordinates are updated according to the calculated mouse drag displacement. Pressing and dragging the right mouse button realizes the rotation operation, and the camera rotation angle is adjusted according to the mouse drag angle information;

[0056] When the user clicks on any position in the visualization interface, the data query module obtains the three-dimensional coordinate information corresponding to the click position, searches in the hybrid data model based on the coordinate information, queries the node information of the discrete data model where the position is located and the data values in the grid cells of the continuous data model, and displays the query results to the user in the form of a pop-up window or an information panel, including the data name, value, and brief description.

[0057] Compared with the prior art, the present application includes at least one of the following beneficial technical effects:

[0058] Through data classification and preprocessing, complex and diverse geomechanical data can be effectively sorted out and standardized. Whether it is discrete geological structure data or continuous rock mechanics parameters and in-situ stress data, they can exist in a unified and suitable form for calculation and analysis, laying a foundation for subsequent accurate modeling. The construction and association of the discrete data model and the continuous data model break the limitations of the traditional single data model, closely combine the spatial distribution of geological structures with the physical properties of rocks, making the data expression more comprehensive and three-dimensional, greatly improving the integrity of the understanding of geological bodies, and helping to more accurately grasp the complex relationships and laws inside geological bodies.

[0059] In terms of visualization effects, the overall geological structure and large-scale in-situ stress situation are presented in a simple and intuitive simplified geometric figure, enabling researchers to quickly have a macroscopic and overall understanding of the research area, quickly locate key areas and trend directions, and provide a direction for further in-depth analysis.

[0060] On the mesoscopic scale, translucent surfaces are used to delicately display the secondary structures inside the geological body and the changes in rock mechanics parameters. Combined with discrete data annotation, the details and local characteristics inside the geological body can be clearly presented, helping to analyze the relationship between local geological phenomena and mechanical properties.

[0061] On the microscopic scale, by using volume rendering technology to penetrate into the microscopic world inside the rock, based on the data correlation visualization algorithm based on ray tracing, the mechanical property data of the rock is vividly mapped into colors and transparencies, accurately revealing the internal connection between the microscopic structure and mechanical properties of the rock, and providing a powerful means for in-depth study of the microscopic mechanical mechanism of the rock.

[0062] Through the collaborative work of each module in the visualization system function module integration unit, a powerful and convenient operation experience is provided for users. The versatility of the data import module ensures that various sources and formats of geomechanical data can be widely accepted, reducing the threshold for data acquisition. The rich functions of the visualization setting module enable users to flexibly customize visualization effects according to specific research needs or personal preferences. Whether it is the display style of macroscopic graphics or the parameter adjustment of microscopic volume rendering, they can be controlled at will, enhancing the adaptability of the system to different application scenarios.

[0063] The present invention can help geologists better understand the complex relationship between geological structure evolution and rock mechanical behavior, providing strong data visualization support for the development of geological theories; it can predict geological risks in advance, optimize engineering design plans, improve engineering safety and economic benefits; through the accurate visualization and in-depth analysis of geomechanical data, it can more accurately assess the possibility of disasters and the potential impact range, providing key technical support for disaster warning and prevention measure formulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a schematic structural diagram of a geomechanical data visualization method and system based on a hybrid data model;

[0065] Figure 2 It is a schematic structural diagram of a geomechanical data visualization method and system based on a hybrid data model. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0066] The technical solutions of the present invention will be further described below in conjunction with the drawings and specific embodiments.

[0067] Embodiment 1

[0068] As Figure 1 shown, a geomechanical data visualization method based on a hybrid data model proposed by the present invention includes four steps: data collection and collation, hybrid data model construction, visualization algorithm design and application, and visualization result display and interaction. Each step will be described in detail below.

[0069] I. Data collection and collation

[0070] First, various types of geomechanical data are widely collected, including geological structure data such as fault distribution and fold morphology, rock mechanical parameter data such as elastic modulus, Poisson's ratio, compressive strength, and in-situ stress data such as magnitude and direction. These data may come from various channels such as geological exploration reports, on-site measurement instruments, laboratory test results, and existing geological databases. The collected data is preliminarily sorted and verified to ensure the accuracy and integrity of the data.

[0071] II. Hybrid data model construction

[0072] Data classification and preprocessing: Geomechanical data is divided into two categories: discrete data and continuous data. Discrete data such as geological structure types and fault numbers are encoded. Different types of faults are respectively encoded as 1, 2, 3, and different geological structures including anticlines and synclines are also given specific codes so that the computer can identify and process them.

[0073] For continuous data, the elastic modulus of the rock and the in-situ stress values are normalized. Let a continuous data value be , the minimum value in this data type be , and the maximum value be . Then the normalization formula is:

[0074] ;

[0075] Through normalization, the numerical range of continuous data is uniformly mapped between 0 and 1, facilitating subsequent calculations and visualization processing.

[0076] Discrete data model construction: A discrete data model is constructed using a graph-theory-based data structure. Geological structures and fault discrete elements are used as nodes of the graph. Each independent fault segment is a node, and the core area of each fold is also used as a node. Then, the edges of the graph are constructed based on the spatial relationships between these elements. If two faults intersect or are adjacent in space, an edge is established between the nodes representing these two faults; if a fold structure is spatially associated with a certain fault and the fault passes through the fold, an edge is constructed between the corresponding nodes. At the same time, attributes are set for each node, including the geological structure type code (such as the previous encoding) and the position coordinate information (determined by the coordinate positioning method in the geographic information system).

[0077] Continuous data model construction: A three-dimensional spatial grid model is used to represent continuous data. First, the spatial range of the geological body to be studied is determined. For example, a three-dimensional spatial region is determined based on the geographical boundary of the exploration area and the research depth. Then, this region is divided into several small cube units, and the division accuracy can be set according to the data detail and visualization requirements. For example, the side length of each small cube unit can be set to 1 meter, 5 meters, or other appropriate length units. The continuous data is filled into the corresponding small cube units according to its corresponding spatial positions. The rock elastic modulus data at a certain position is stored in the small cube unit corresponding to that position, thus constructing a distribution model of continuous data in three-dimensional space.

[0078] Model association: Through the establishment of an indexing mechanism, the discrete data model and the continuous data model are associated and integrated. In this way, in subsequent operations, it is convenient to quickly locate the data in the relevant continuous data model according to the geological structure information in the discrete data model, and vice versa, realizing information interaction and collaborative work between the two data models.

[0079] III. Visualization Algorithm Design and Application

[0080] Multi-scale Visualization

[0081] Set the multi-scale threshold range, and divide the visualization of geomechanics data into macro-scale, meso-scale, and micro-scale. The macro-scale threshold range is [0, 0.3]. At this scale, the overall outline of geological structures and large-scale in-situ stress trends are mainly shown. Simplified geometric figures are used for visualization. For example, large polygons are used to represent the general shape of geological bodies, and arrows are used to represent the directions of the main in-situ stresses. The drawing of these simplified geometric figures is based on the geological structure node position information in the discrete data model and the macro in-situ stress trend data in the continuous data model. For example, the length and direction of the arrow are determined according to the average magnitude and direction of the in-situ stress in the region, and the vertex coordinates of the polygon are determined according to the general range of the geological body.

[0082] The meso-scale threshold range is (0.3, 0.7]. At this scale, some secondary structures inside geological structures and local in-situ stress changes are shown. Translucent surfaces are used to represent the surface of geological bodies. The construction of the surface is based on the geological structure boundary information in the discrete data model and the rock mechanics parameter data in the continuous data model. By mapping the continuous data (rock elastic modulus) to the color and texture of the surface, in the area with a larger elastic modulus, the surface color can be set to a darker color (red represents the high elastic modulus area), and at the same time, the density of the texture can be set according to the data change to represent the difference in rock mechanics parameters. And key structure information in the discrete data, including fault names and fold types, is marked on the surface. The marking position is determined according to the node position in the discrete data model, and the marking style (font, size, color) can be set according to requirements.

[0083] The micro-scale threshold range is (0.7, 1]. At this scale, the mechanical properties and microstructural information inside the rock are shown in detail. For each small cube unit in the continuous data model, according to the stored data, volume rendering technology is used for visualization. Data such as the elastic modulus and porosity of the rock are mapped to different colors and transparencies. Areas with a higher porosity are set to a higher transparency, and areas with a larger elastic modulus are set to a brighter color (yellow represents the high elastic modulus micro-region). The volume rendering technology determines the final display effect through the calculation of the light propagation of each small cube unit, specifically based on the data association visualization algorithm based on ray tracing.

[0084] Data association visualization algorithm

[0085] The data association visualization algorithm based on ray tracing is adopted to mine the association relationship between discrete data and continuous data. The algorithm formula is:

[0086] ;

[0087] ;

[0088] ;

[0089] wherein, is the final pixel color value at the screen coordinate position, is the number of sampling points for ray tracing, is the position of the ray at the th sampling point, and are the sampling step sizes, is the transmittance of the ray from the starting point to the sampling point position, is the extinction coefficient of the medium along the ray propagation path position, is the illumination intensity at the sampling point position, The object color at the sampling point is jointly determined by discrete data and continuous data, and the association relationship between discrete data and continuous data is demonstrated through the propagation process of the ray in the hybrid data model.

[0090] wherein, is the final pixel color value at the screen coordinate position, that is, the color finally displayed at this coordinate position on the screen, and it is obtained by comprehensively calculating the information of each sampling point passed by the ray during the ray tracing process. is the number of sampling points for ray tracing. In order to accurately simulate the propagation effect of the ray in the geological body, it is necessary to perform sampling calculations at multiple points along the ray direction. The more sampling points, the more accurate the calculation result, but the greater the computational amount, and it can be adjusted according to actual needs and system performance. is the ray at the The positions of the sampling points are obtained by adding the product of the sampling step length and the sampling sequence number to the starting point coordinates. The sum is the sampling step length, which determines the distance interval between the sampling points and affects the accuracy and computational efficiency of ray tracing. $\tau$ is the transmittance of the light ray from the starting point to the sampling point, indicating the attenuation degree of the light ray when passing through the medium (geological body) during propagation. It is calculated by an exponential function, where $\mu$ is the extinction coefficient of the medium on the light ray propagation path. The extinction coefficient is related to the material composition and density factors of the geological body. Different rock types and geological structure regions may have different extinction coefficients. The longer the distance the light ray propagates, the lower the transmittance, that is, the weaker the light ray. $I$ is the light intensity at the sampling point, simulating the light influence received by the light ray at this point. For example, the light is stronger on the surface of the geological body and weaker inside. The setting of the light intensity can enhance the realism of the visualization effect. $C$ is the object color at the sampling point, which is determined by both discrete data and continuous data. For example, the geological structure type in the discrete data may affect the basic tone of the object color. The fault area is set to a blue tone, and the fold area is set to a green tone. The rock mechanics parameters in the continuous data, including the elastic modulus and porosity, further adjust the brightness and saturation details of the color. Through the propagation process of the light ray in the hybrid data model, when the light ray encounters the geological structure in the discrete data model, the light ray is reflected, refracted, and blocked according to the attributes of the geological structure. When the light ray encounters a fault, reflection and refraction may occur, changing the propagation direction. At the same time, the color and transparency of the area where the light ray passes are determined according to the data in the continuous data model, so as to intuitively display the correlation relationship between different types of data.

[0091] IV. Visualization Result Display and Interaction

[0092] Visualization Software Platform Operation

[0093] Develop a dedicated visualization software platform and integrate the above - constructed hybrid data model and the designed visualization algorithm into the platform. The platform has a user - friendly interface, including function modules such as data import, model construction, visualization settings, and interactive operations. After the user imports the sorted geomechanical data into the platform, the platform automatically constructs the hybrid data model according to the previous steps and performs multi - scale visualization and data - associated visualization settings according to the user's needs.

[0094] Interactive Function Use

[0095] Use the interactive tools provided by the platform, such as zooming, panning, and rotating functions, to operate on the visualization results. Zoom in by rolling the mouse wheel forward to view the details of the geomechanics data; roll backward to zoom out and view the overall overview. Press and drag the left mouse button to pan the image for easy observation of data in different areas. Press and drag the right mouse button to rotate the image around different axes to view the distribution of geological structures and rock mechanics parameters from different angles.

[0096] Data query and analysis

[0097] On the visualization interface, the user can click on any position, and the platform will automatically query the detailed geomechanics data information at that position. Through the hybrid data model indexing mechanism established previously, quickly obtain the discrete data model node information (such as geological structure type, related description) where the position is located and the data values in the grid cells of the continuous data model (such as rock elastic modulus, in-situ stress value). The query results will be presented to the user in an intuitive way, such as popping up an information window or displaying the data details in a specific area of the interface, including the data name, value, and brief description, to help the user deeply understand the specific situation of geomechanics data at different positions, so as to conduct further geological analysis and research.

[0098] Embodiment 2

[0099] As Figure 2 shown, this embodiment provides a geomechanics data visualization system based on a hybrid data model, including a data classification and preprocessing unit, a hybrid data model construction unit, a visualization algorithm execution unit, and a visualization system function module integration unit.

[0100] Among them, the data classification and preprocessing unit is used to receive geomechanics data, classify it into discrete data and continuous data, perform coding processing on the discrete data, and perform normalization processing on the continuous data. The normalization processing is based on the normalization formula:

[0101] ;

[0102] Execute;

[0103] In addition, the hybrid data model construction unit constructs a discrete data model based on graph theory, uses geological structures and fault discrete elements as nodes, constructs edges according to spatial relationships, and at the same time constructs a continuous data model using a three-dimensional spatial grid model, and establishes an index association between the two.

[0104] It should be noted that the visualization algorithm execution unit sets a multi-scale threshold range, which is divided into the macro scale [0, 0.3], the meso scale (0.3, 0.7], and the micro scale (0.7, 1]. At the macro scale, simplified geometric shapes are used to display the overall outline of the geological structure and the large-scale in-situ stress trend. At the meso scale, a semi-transparent surface is used to represent the surface of the geological body and map continuous data to display the differences in rock mechanics parameters, and key structural information of discrete data is marked. At the micro scale, volume rendering technology is used to visually display the internal mechanical properties of the rock for the small cube units in the continuous data model, and the correlation between discrete data and continuous data is shown through the propagation process of light in the mixed data model;

[0105] In the visualization system function module integration unit, it includes a data import module, a visualization settings module, an interactive operation module, and a data query module. The following is a detailed description of each module.

[0106] The data import module has a designed user interface and provides a file selection dialog box that supports multiple common geological mechanics data file formats. The background program can automatically call the corresponding parsing function according to the selected file format to read the data into memory, and process the data according to the data classification and preprocessing rules to construct a discrete data list and a continuous data array;

[0107] The visualization settings module can provide multi-scale visualization switching buttons, call the corresponding visualization function according to the selected scale threshold range, and allow users to perform corresponding visualization settings at different scales. In the macro scale visualization settings, users are allowed to customize the display attributes such as the color, size, and transparency of the simplified geometric shape, as well as the style and annotation information of the in-situ stress direction arrow. The meso scale visualization settings interface provides functions for selecting the surface color mapping scheme, uploading and adjusting texture images, and setting the font, size, and color of the discrete structural information annotation. The micro scale visualization settings allow users to adjust the transfer function parameters of volume rendering, including the color-data value mapping curve and the transparency-data value mapping curve;

[0108] The interactive operation module implements the mouse wheel zoom function. By listening to the mouse wheel event, the camera field of view range is adjusted according to the scroll direction and amplitude. Pressing and dragging the left mouse button realizes the pan operation, and the camera position coordinates are updated according to the calculated mouse drag displacement. Pressing and dragging the right mouse button realizes the rotation operation, and the camera rotation angle is adjusted according to the mouse drag angle information;

[0109] When the user clicks on any position in the visualization interface, the data query module obtains the three-dimensional coordinate information corresponding to the click position, searches in the hybrid data model based on the coordinate information, queries the node information of the discrete data model and the data values in the grid cells of the continuous data model where the position is located, and displays the query results to the user in the form of a pop-up window or an information panel, including the data name, value, and brief description.

[0110] In this system, through the data classification and preprocessing unit, the geomechanical data is effectively classified and standardized, which can ensure the standardization and consistency of the data and lay a solid foundation for subsequent accurate analysis and visualization. The hybrid data model construction unit skillfully integrates discrete and continuous data, accurately presents the internal relationship between geological structures and rock mechanical parameters, comprehensively shows the overall structure and local details of the geological body, and greatly improves the integrity and accuracy of data expression.

[0111] In this embodiment, the multi-scale threshold setting and corresponding visualization strategy of the visualization algorithm execution unit can quickly grasp the overall picture of the geological structure and the large-scale in-situ stress trend at the macroscopic scale, deeply analyze the internal structure of the geological body and the distribution of rock mechanical properties at the mesoscopic scale, and carefully explore the internal micro-mechanical mechanism of the rock at the microscopic scale, effectively improving the visualization efficiency, helping users quickly focus on key information, and meeting the diverse needs of data display in different research and application scenarios.

[0112] Through the cooperation of each module in the visualization system function module integration unit, the convenient data acquisition and preliminary processing function of the data import module facilitates the rapid input and collation of data; the powerful personalized setting ability of the visualization setting module enables users to flexibly adjust the visualization effect according to specific needs, enhancing the adaptability and usability of the system; the smooth zooming, panning, and rotating functions of the interactive operation module provide users with an interactive experience of observing geomechanical data from multiple angles and in all directions, helping to deeply understand the data connotation; the efficient information retrieval and display function of the data query module allows users to instantly obtain detailed data information at a specific position, providing strong support for accurate analysis and decision-making.

[0113] Through data classification and preprocessing, complex and diverse geomechanical data can be effectively sorted out and standardized. Whether it is discrete geological structure data or continuous rock mechanical parameters and in-situ stress data, they can exist in a unified and suitable form for calculation and analysis, laying a foundation for subsequent accurate modeling. The construction and association of the discrete data model and the continuous data model break the limitations of the traditional single data model, closely combine the spatial distribution of geological structures with the physical properties of rocks, make the data expression more comprehensive and three-dimensional, greatly improve the integrity of the understanding of the geological body, and help to more accurately grasp the complex relationships and laws inside the geological body.

[0114] In terms of visualization effects, the overall geological structure and large-scale in-situ stress situation are presented in the form of simple and intuitive simplified geometric figures, enabling researchers to quickly gain a macroscopic and overall understanding of the research area, quickly locate key areas and trend directions, and provide direction guidance for further in-depth analysis.

[0115] On the mesoscopic scale, translucent surfaces are used to delicately display the secondary structures inside geological bodies and the changes in rock mechanical parameters. Combined with discrete data annotation, the details and local characteristics inside geological bodies are clearly presented, which helps to analyze the relationship between local geological phenomena and mechanical properties.

[0116] On the microscopic scale, volume rendering technology is used to penetrate into the microscopic world inside rocks. Based on the data correlation visualization algorithm for ray tracing, the mechanical property data of rocks are vividly mapped into colors and transparencies, accurately revealing the internal connection between the microscopic structure and mechanical properties of rocks, and providing a powerful means for in-depth study of the microscopic mechanical mechanism of rocks. This multi-scale progressive visualization meets the requirements of different research depths and accuracies from macroscopic to microscopic, greatly improves the efficiency and effectiveness of data visualization, and avoids analysis difficulties caused by data detail loss or information overload.

[0117] Through the coordinated work of each module in the visualization system function module integration unit, a powerful and convenient operation experience is provided for users. The versatility of the data import module ensures that various sources and formats of geomechanical data can be widely accepted, reducing the threshold for data acquisition. The rich functions of the visualization settings module enable users to flexibly customize visualization effects according to specific research needs or personal preferences. Whether it is the display style of macroscopic graphics or the parameter adjustment of microscopic volume rendering, users can control it at will, enhancing the adaptability of the system to different application scenarios. The convenience of the interactive operation module, such as functions like mouse wheel zooming, left button panning, and right button rotation, allows users to observe and explore geomechanical data from any angle and distance as if they were operating a geological model in a real scenario, greatly enhancing the flexibility and depth of data exploration and helping to discover geological laws and characteristics hidden behind the data. The efficiency of the data query module enables users to quickly obtain detailed data information when they focus on a specific location. Whether it is discrete geological structure attributes or continuous rock mechanical parameter values, they can be presented immediately, providing a reliable basis for accurate analysis and decision-making, and greatly improving the work efficiency in geological research and engineering applications.

[0118] The present invention can help geologists better understand the complex relationship between geological structure evolution and rock mechanical behavior, providing strong data visualization support for the development of geological theories; in the field of geological engineering, such as oil exploration, mine exploitation, underground engineering construction, etc., it can help engineers predict geological risks in advance, optimize engineering design plans, and improve engineering safety and economic benefits; in the prevention and control of geological disasters, through the accurate visualization and in-depth analysis of geomechanical data, it can more accurately evaluate the possibility of disaster occurrence and the potential impact range, providing key technical support for disaster early warning and the formulation of prevention and control measures. In summary, the geomechanical data visualization method and system based on the hybrid data model have irreplaceable important value in many geological-related fields, strongly promoting the development and progress of geological science and engineering technology.

[0119] The above specific embodiments are only several alternative embodiments of the present invention. Based on the technical solution of the present invention and the relevant inspirations of the above embodiments, those skilled in the art can make various alternative improvements and combinations to the above specific embodiments.

Claims

1. A geomechanics data visualization method based on a hybrid data model, characterized in that, It includes the following steps: S1. Data collection and collation: Collect geomechanical data including geological structure data, rock mechanics parameter data, and in-situ stress data; S2. Construction of a hybrid data model, specifically including: S201. Data classification and preprocessing: Classify geomechanical data into discrete data and continuous data, perform encoding processing on discrete data, and perform normalization processing on continuous data according to a formula; S202. Construction of a discrete data model: Use a data structure based on graph theory to construct a discrete data model, with geological structures and fault discrete elements as nodes, construct edges according to their spatial relationships, and set geological structure type codes and position coordinate attributes for the nodes; S203. Construction of a continuous data model: Use a three-dimensional spatial grid model to represent continuous data, determine the spatial range of the geological body and divide it into small cube units, and fill the continuous data into the corresponding units according to the spatial position; S204. Model association: Establish an indexing mechanism to associate the discrete data model with the continuous data model; S3. Visualization algorithm design and application, specifically including: Multi-scale visualization: Set the macro-scale threshold range to [0, 0.3], and use simplified geometric graphics to display the overall outline of the geological structure and the large-scale in-situ stress trend. The graphics are drawn based on the geological structure node position information in the discrete data model and the macro in-situ stress trend data in the continuous data model; Set the meso-scale threshold range to (0.3, 0.7], use a semi-transparent surface to represent the surface of the geological body, map the continuous data to the surface color and texture and label the key structure information of the discrete data. The surface is constructed based on the geological structure boundary information in the discrete data model and the rock mechanics parameter data in the continuous data model; Set the micro-scale threshold range to (0.7, 1], and use volume rendering technology to visualize the small cube units in the continuous data model, map the rock mechanics characteristic data to color and transparency, and the volume rendering is carried out according to the data association visualization algorithm based on ray tracing; S4. Visualization result display and interaction: Develop a visualization software platform, which includes a data import module, a model construction module, a visualization setting module, an interactive operation module, and a data query module. Each module works together to achieve the visualization and interactive operation functions of geomechanical data.

2. The geomechanical data visualization method based on a hybrid data model according to claim 1, characterized in that, [[ID=]13]The normalization formula is: ； Among them, is the normalized value, is the original data value, and are the minimum and maximum values in this data type, respectively.

3. A geomechanics data visualization method based on a hybrid data model according to claim 1, characterized in that ； ； ； Among them, is the final pixel color value at the screen coordinates , is the number of sampling points for ray tracing is the position of the ray at the th sampling point and are the sampling step sizes is the transmittance of the ray from the starting point to the sampling point , is the extinction coefficient of the medium along the ray propagation path , is the illumination intensity at the sampling point , is the object color at the sampling point which is jointly determined by discrete data and continuous data, and shows the correlation between discrete data and continuous data through the propagation process of the ray in the hybrid data model.

4. A geomechanics data visualization method based on a hybrid data model according to claim 1, characterized in that In step S3, the data association visualization algorithm: Use a data association visualization algorithm based on ray tracing, and the formula is: The data import module specifically includes: Design a user interface and provide a file selection dialog box that supports multiple common geomechanical data file formats; 5. A method for visualizing geomechanical data based on a hybrid data model according to claim 1, characterized in that, The background program automatically calls the corresponding parsing function according to the selected file format to read the data into memory, and processes the data according to the data classification and preprocessing rules, and constructs a discrete data list and a continuous data array. The model construction module specifically includes: Use the processed discrete data to construct a discrete data model based on graph theory, including creating node objects and setting geological structure type codes and position coordinate attributes, and creating edge objects according to spatial relationships and associating the corresponding nodes; Create a three-dimensional spatial grid object, determine the range and resolution, fill the data in the continuous data array into the corresponding grid cells, and establish an index association with the discrete data model.

6. A geomechanics data visualization method based on a hybrid data model according to claim 1, characterized in that The visualization setting module specifically includes: Provide multi-scale visualization switching buttons, and call the corresponding visualization functions according to the selected scale threshold range; In the macroscopic scale visualization setting, allow users to customize the display attributes of the color, size, and transparency of the simplified geometric figures, as well as the style and annotation information of the in-situ stress direction arrows; The mesoscopic scale visualization setting interface provides functions for selecting surface color mapping schemes, uploading and adjusting texture images, and setting the font, size, and color of discrete structural information annotations; The microscopic scale visualization setting allows users to adjust the transfer function parameters of volume rendering, including the color-data value mapping curve and the transparency-data value mapping curve.

7. A method for visualizing geomechanics data based on a hybrid data model according to claim 1, characterized in that, The interactive operation module specifically includes: Implement the mouse wheel zoom function. By listening to the mouse wheel event, adjust the camera's field of view according to the scroll direction and amplitude; Press and drag the left mouse button to implement the pan operation, and update the camera position coordinates according to the calculated mouse drag displacement; Press and drag the right mouse button to implement the rotation operation, and adjust the camera's rotation angle according to the mouse drag angle information.

8. A method for visualizing geomechanical data based on a hybrid data model according to claim 1, characterized in that The data query module specifically includes: When the user clicks on any position in the visualization interface, obtain the three-dimensional coordinate information corresponding to the click position; Search in the hybrid data model according to the coordinate information, and query the node information of the discrete data model and the data value in the grid cell of the continuous data model at that position; Display the query results to the user in the form of a pop-up window or an information panel, including the data name, value, and brief description.

9. A geomechanics data visualization system based on a hybrid data model, characterized in that, It includes: The data classification and preprocessing unit is used to receive geomechanics data, classify it into discrete data and continuous data, perform encoding processing on the discrete data, perform normalization processing on the continuous data, and the normalization processing is carried out according to the normalization formula: ； Execute; The hybrid data model construction unit constructs a discrete data model based on graph theory, uses geological structures and fault discrete elements as nodes, constructs edges according to spatial relationships, and at the same time constructs a continuous data model using a three-dimensional spatial grid model, and establishes an index association between the two; The visualization algorithm execution unit sets multi-scale threshold ranges, which are divided into the macroscopic scale [0, 0.3], the mesoscopic scale (0.3, 0.7], and the microscopic scale (0.7, 1]. At the macroscopic scale, simplified geometric figures are used to display the overall outline of geological structures and large-scale in-situ stress trends. At the mesoscopic scale, semi-transparent surfaces are used to represent the surface of geological bodies and map continuous data to show the differences in rock mechanics parameters and annotate key structural information of discrete data. At the microscopic scale, volume rendering technology is used to visualize the small cube units in the continuous data model to show the internal mechanical properties of rocks, and the relationship between discrete data and continuous data is shown through the propagation process of light in the hybrid data model; The visualization system function module integration unit includes a data import module, a visualization setting module, an interactive operation module, and a data query module.

10. A geomechanics data visualization system based on a hybrid data model according to claim 9, characterized in that, In the functional module integration unit of the visualization system, the data import module has a designed user interface and provides a file selection dialog box that supports multiple common geomechanics data file formats. The background program can automatically call the corresponding parsing function according to the selected file format to read the data into memory, and process the data according to the data classification and preprocessing rules to construct a discrete data list and a continuous data array; the visualization setting module can provide multi-scale visualization switching buttons, call the corresponding visualization function according to the selected scale threshold range, and allow the user to perform corresponding visualization settings at different scales. These settings include allowing the user to customize the display attributes of the color, size, and transparency of the simplified geometric figure, as well as the style and annotation information of the in-situ stress direction arrow in the macroscopic scale visualization setting. The mesoscopic scale visualization setting interface provides functions for selecting the surface color mapping scheme, uploading and adjusting texture images, and setting the font, size, and color of the discrete structural information annotation. The microscopic scale visualization setting allows the user to adjust the transfer function parameters of the volume rendering, including the color-data value mapping curve and the transparency-data value mapping curve; the interaction operation module implements the mouse wheel zoom function. By listening to the mouse wheel event, it adjusts the camera view range according to the scroll direction and amplitude. Pressing and dragging the left mouse button realizes the pan operation, and updates the camera position coordinates according to the calculated mouse drag displacement. Pressing and dragging the right mouse button realizes the rotation operation, and adjusts the camera rotation angle according to the mouse drag angle information; when the user clicks on any position in the visualization interface, the data query module obtains the three-dimensional coordinate information corresponding to the click position, searches in the hybrid data model according to the coordinate information, queries the node information of the discrete data model and the data value in the grid cell of the continuous data model where the position is located, and displays the query results to the user in the form of a pop-up window or an information panel, including the data name, value, and brief description.

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