523 results about "Visualization model" patented technology

The invention discloses an MRI medical image correction method and system based on a convolutional neural network and a computer readable storage medium, and the method comprises the steps: obtaining a brain MRI medical image, and carrying out the preprocessing; extracting lesion features of the brain lacuna infarction from the preprocessed MRI medical image through a convolutional neural network, and positioning a lesion area of the brain lacuna infarction; performing detail enhancement on the lesion area of the cerebral lacuna infarction, segmenting the lesion area and optimizing a segmentation result; and carrying out artifact restoration on the segmented image, and generating a three-dimensional focus visualization model based on the restored image. According to the method, through processing in multiple aspects such as quality evaluation, lesion recognition, segmentation, artifact repair and three-dimensional visualization of the MRI image, the lesion area can be recognized more efficiently and accurately, the image quality is improved, and an efficient and accurate brain lacuna infarction diagnosis auxiliary tool is provided.

The invention relates to an electric quantity abnormity intelligent monitoring method considering event waves. The method comprises the following steps: S1, collecting event wave data through a sensor and an intelligent device; s2, using a time-frequency analysis algorithm to extract time sequence features and frequency spectrum features of the electric quantity demand related event waves; s3, constructing a training set according to the extracted time sequence features and frequency spectrum features, and training an electric quantity demand motivation analysis model constructed based on machine learning and deep learning; s4, constructing an electric quantity abnormity monitoring model, calibrating a basic rule through an event wave amplitude value and frequency domain energy, learning normal waveform characteristics through an auto-encoder by the abnormity detection model, and realizing intelligent electric quantity abnormity monitoring in combination with motivation analysis; and S5, constructing a hierarchical visualization model, and graphically displaying the electric quantity change reason, the event behavior and the abnormal early warning information. According to the invention, real-time monitoring and early warning of electric quantity abnormity are realized, and challenges of transient, steady and complex non-stationary events in an electric power system can be effectively handled.

The invention discloses a building outer wall leakage detection method and system, and belongs to the technical field of wall leakage detection. The method comprises the following steps: acquiring infrared thermal imaging, laser point cloud and multispectral imaging data, and generating a three-dimensional visual model with temperature information after environment temperature compensation correction, three-dimensional modeling and data fusion; and then extracting temperature characteristic parameters to identify an abnormal region, screening a to-be-verified region in combination with the building construction node coincidence degree and geometric parameters, and finally determining a leakage position through comparison of multispectral characteristic extraction and a preset leakage characteristic library. The system realizes full-process automatic detection by applying the method. According to the invention, temperature signal conduction limitation caused by insulation layer obstruction is broken through, the problem of misjudgment caused by a thermal bridge effect is solved through multi-source data fusion and spectral feature analysis, and the precision and reliability of leakage detection are improved.

The invention relates to the technical field of remote sensing image processing, and discloses an agricultural condition remote sensing image change detection method based on time sequence analysis, which comprises the following steps: acquiring an agricultural condition remote sensing image sequence through a multi-temporal remote sensing sensor, and extracting multi-scale fusion features by using a multi-modal data fusion network after registration and radiation correction of a space-time alignment algorithm. The time sequence decomposition model decomposes features, extracts time dynamic change features, and detects an abnormal change area based on an abnormal detection model of a variational auto-encoder. And optimizing the change area by a multi-objective optimization algorithm, and constructing a visual model to generate a high-resolution agricultural condition change distribution diagram. According to the method, multi-sensor data are fused, various algorithms and models are integrated, the problems of data processing, feature analysis, anomaly detection, result presentation and the like in agricultural condition remote sensing image change detection are effectively solved, the detection accuracy and efficiency are improved, and a precise basis is provided for agricultural production management.

The invention provides a high-precision soil three-dimensional surveying and mapping method based on radar detection, and the method comprises the steps: carrying out the radar data collection of target region soil, and enabling the radar data to comprise three-dimensional laser point cloud data collected by a laser radar and two-dimensional ground radar data collected by a ground detection radar; separating ground points from the three-dimensional laser point cloud data through an end-to-end trained semantic segmentation network, modeling a digital ground model, and matching and registering the two-dimensional ground radar data and the three-dimensional laser point cloud data through a filtering algorithm to generate a three-dimensional soil visualization model, and extracting soil attribute parameters from the three-dimensional soil visualization model, and generating a thematic map for reflecting soil physicochemical property spatial distribution of the target area. Through accurate acquisition and fusion expression of multi-dimensional, multi-scale and multi-temporal soil information, the precision, reliability and comprehensive application value of soil surveying and mapping can be well improved.

The invention relates to the technical field of three-dimensional image reconstruction, in particular to a VR-based three-dimensional reconstruction method and system for textile culture heritage, and the method comprises the steps: obtaining a multi-view image collection sequence of the textile culture heritage, carrying out the geometric topological feature extraction of the multi-view image collection sequence, generating a three-dimensional point cloud geometric model, and carrying out the reconstruction of the three-dimensional point cloud geometric model. Performing multi-resolution texture feature mapping processing on the three-dimensional point cloud geometric model to generate an initial three-dimensional model fusing geometric topological features and multi-resolution texture features; performing dynamic geometric optimization processing on the initial three-dimensional model based on preset VR display parameters to generate a target three-dimensional model after surface continuity correction; and performing dynamic matching processing on the target three-dimensional model and a preset VR interaction algorithm to generate a VR visual model with a multi-dimensional interaction attribute, and transmitting the VR visual model to a VR display terminal to perform three-dimensional space rendering, so that the three-dimensional reconstruction and interaction intelligence degree of the textile culture heritage can be improved in combination with a VR technology.

The invention relates to the technical field of building information modeling, and discloses a parameterized BIM modeling method, which comprises the following steps: step 1, acquiring specific design parameters of a modeling object in a project design requirement, marking key geometric parameters of the object, including length, width, height, volume and material characteristics, and defining units, physical meanings and application ranges of the parameters in a marking process, a basis is provided for subsequent entity model construction; and 2, based on the geometric parameters marked in the step 1, a solid model is constructed through a BIM modeling tool, and the solid model is a visual model with the shape, the size and the position determined through the geometric parameters in a three-dimensional space. The three-dimensional BIM model is dynamically generated and modified by modifying geometric parameters, model construction is more flexible and efficient due to introduction of parameterization logic, automatic adjustment and rapid iteration of the model are achieved, and the reusability of BIM modeling and the design efficiency of the building model are remarkably improved.

The invention belongs to the technical field of information communication, and discloses a twinborn technology-based intelligent substation optical fiber link 3D visualization method, which is characterized by comprising the following steps of 1, constructing an optical fiber path 3D visualization model, 2, carrying out twinborn simulation and intelligent auxiliary optical fiber alignment, and 3, carrying out twinborn simulation and intelligent auxiliary optical fiber alignment. And 3, constructing an optical fiber logic link intelligent identification and early warning system. The method has the beneficial technical effects that the efficiency is improved, errors are reduced, the safety management is enhanced, the fault response speed and accuracy are enhanced, the intelligent level of electric power capital construction is improved, the engineering safety is guaranteed, and the industrial technical progress is promoted.

The invention discloses an oil pipeline simulation analysis system, relates to the technical field of oil pipelines, and provides accurate data support for subsequent dynamic monitoring and pipeline cleaning decision by constructing a three-dimensional visual model and identifying wax precipitation temperature and deposition risk in time. Through the risk identification module, the system can analyze and calculate the wax precipitation temperature based on the oil product attribute data obtained in real time, and timely judge whether the deposition risk exists in the oil pipeline or not. After receiving a dynamic tracking instruction, the dynamic analysis module can obtain the deposition thickness of each position in a pipeline in real time and analyze the influence of oil temperature and flow velocity changes on deposition distribution, the analysis provides important input data for the pipe cleaning module, the deposition thickness and a heat loss coefficient are fitted through a deep learning technology, and the deposition thickness and the heat loss coefficient are matched with each other. The system may automatically calculate a delivery stability score. When the conveying stability score exceeds a set threshold value, the system can automatically start a pigging measure execution mechanism.

The invention relates to the technical field of electrical property detection, and discloses a graphene film surface property detection device, which comprises a data acquisition module used for acquiring electrical property data of the surface of a graphene film through a multi-point array electrode probe; the vector grid modeling module is used for constructing a vector grid model for representing the surface performance of the graphene film according to the electrical characteristic data; the iterative inversion calculation module is used for performing iterative inversion calculation on the vector grid model to determine the surface performance distribution of the graphene film; the parallel optimization fusion module is used for performing parallel processing and optimization fusion on the multi-scale performance data through a distributed computing framework; the three-dimensional visualization module is used for generating a three-dimensional visualization model of the surface performance of the graphene film according to the optimized and fused performance data; the problems of insufficient precision and low efficiency of a traditional detection method in graphene film performance detection are solved.

The invention discloses a micro-seismic monitoring-based deep hole blasting crack evolution evaluation method and system. The method comprises the following steps of: obtaining a spatio-temporal evolution process of crack extension and a final crack distribution characteristic; microseismic signals in the blasting process are collected in real time, the spatial-temporal evolution process of crack expansion and the final crack distribution characteristics are combined, the microseismic signals are preprocessed, and preprocessed microseismic waveform data are obtained; calculating a spatial position coordinate of the micro-seismic event, and generating a complete three-dimensional micro-seismic positioning image; drawing a fracture density cloud picture according to the generated complete three-dimensional micro-seismic positioning image in combination with the acquired spatial distribution density and energy release rate of the micro-seismic event; a three-dimensional visualization model of fracture evolution is established, and evaluation indexes are obtained; and establishing a comprehensive index system for crack evolution evaluation, carrying out weight distribution and quantitative scoring on evaluation indexes, generating a quantitative evaluation report of crack evolution, and completing deep hole blasting crack evolution evaluation. The accuracy and reliability of evaluation are improved.

The invention discloses a water conservancy project construction management system and method based on three-dimensional visualization, and belongs to the technical field of water conservancy projects, and the method specifically comprises the steps: collecting related data of a water conservancy project construction region, carrying out the preprocessing, obtaining first monitoring data, building a three-dimensional digital model of a water conservancy project based on the first monitoring data, and carrying out the construction of the water conservancy project. On the basis of the hydraulic engineering three-dimensional digital model, hydraulic engineering construction risks are evaluated in combination with hydraulic engineering construction historical data, and risk grades are divided and hydraulic engineering construction is dynamically managed according to risk evaluation; on the basis of a three-dimensional visual model, all-around and real-time risk monitoring and evaluation can be carried out on a construction site, through real-time data collection and analysis, potential safety hazards such as geological changes, equipment faults and earthwork collapse can be found in time, early warning and emergency treatment are carried out in advance, and safety accidents are effectively avoided.

The invention relates to the technical field of data visualization, in particular to a digital twinning-oriented workshop data visualization system, which comprises a heterogeneous data space-time stamp reconstruction module for acquiring a sensor data stream, an MES service data packet and an environment monitoring data set and generating a space-time aligned fusion data frame; the dynamic topology compensation modeling module is used for constructing a digital twin body with a time sequence attribute and outputting a dynamic topology relation matrix comprising a geometric deviation compensation value; the event-driven incremental rendering engine module is used for generating a visual model only updating a change part by adopting a difference region recognition technology, and outputting a three-dimensional visual interface with an abnormal coordinate mark; and the bidirectional feedback control channel module is used for analyzing the abnormal coordinate mark, generating an equipment parameter adjustment instruction set through a reverse path tracking algorithm, and transmitting the equipment parameter adjustment instruction set back to the physical equipment controller. According to the invention, a bidirectional feedback closed loop with a physical equipment controller is realized, and dynamic adjustment and adaptive control are supported.

A device may include an interface manager configured to implement a build interface, and to build a visual model in response to user operations on the build interface. A device may include a supply chain model creation component configured to determine a supply chain model in response to the visual model. A device may include a supply chain model execution component configured to operate the supply chain model as a digital twin of at least a portion of a physical supply chain, to interpret at least one physical supply chain execution value, and to provide a notification to a user of the supply chain command platform in response to a comparison of the supply chain model and the at least one physical supply chain execution value.

The invention discloses an intelligent auxiliary decision-making method and system for a bridge construction progress based on a multi-modal visual language model, belongs to the technical field of bridge engineering management, and solves the problems that when an existing multi-modal model is used for integrating static scene data and dynamic real-time data of a bridge construction site, the fusion degree is low, and the integration efficiency is high. And therefore, the problems of information incompleteness and cognition deficiency can be solved. The method comprises the following steps: acquiring bridge construction progress data, preprocessing the data, and training a constructed multi-modal bridge construction decision analysis model based on image-text information fusion; preprocessing bridge construction progress data acquired in real time, inputting the preprocessed data into the trained image-text information fused multi-modal bridge construction decision analysis model for analysis, and constructing a unified fusion expression model for feeding back the construction progress and quality in real time according to an instruction normalized visual model required by multi-level user tasks; and obtaining a bridge construction progress scene three-dimensional model. The method is used for intelligent auxiliary decision making of the bridge construction progress.

The invention discloses an urban building group energy flexible management digital platform and method, and the method comprises the steps: managing multi-source data through a data layer, including building environment, energy consumption, user willingness and power grid signals; the front-end module constructs a city visual model (CVM) and a building agent component based on an unreal engine, and realizes visual display and interactive operation of the energy system; the CVM covers four layers, namely a basic environment layer, a building layer, a mobile resource layer and an energy infrastructure layer; the building agent component realizes fine management of energy production, consumption, energy storage and power grid supply; the rear-end module is responsible for data processing, logical operation and algorithm execution, real-time data storage, resource scheduling and decision planning; the business function module comprises resource real-time monitoring, demand response management and resource configuration and planning deduction, and meets the requirements of short-term management and long-term planning. According to the invention, multi-scale interaction and refined operation are realized, the management granularity and the visualization effect are improved, and powerful support is provided for flexible management and low-carbon transformation of urban building groups.

The invention belongs to the technical field of geological engineering monitoring and multi-physics field intelligent sensing, and discloses a separation grouting slurry migration monitoring method and system, and the method comprises the steps: constructing an acoustics-optics-electricity-electromagnetism multi-physics field coupling monitoring system; a grouting hole and a monitoring drilling hole array are arranged in a target stratum, a distributed optical fiber sensor, a drilling hole ultrasonic imager, a resistivity measuring device and a transient electromagnetic detection device are installed, and a three-dimensional monitoring network is formed; synchronously acquiring sound field, light field, electric field and magnetic field data; four-field monitoring data and overlying strata multi-parameter observation data are fused, a coal seam mining three-dimensional overlying strata separation model is constructed, and a slurry diffusion three-dimensional visualization model is generated through numerical simulation; and based on the four-field monitoring response difference of the separation space before and after grouting, in combination with a monitoring frequency domain correction model of multiple indexes of grout diffusion, the diffusion range, compactness and filling effect of the grouting grout are evaluated, and abnormal early warning is triggered.

The invention provides a building change detection method and system based on a multi-source live-action three-dimensional model, and the method comprises the steps: obtaining the triangulation network topology data of a two-stage live-action three-dimensional model in a to-be-detected region, and carrying out the preprocessing and standardization processing; a plane-elevation layered registration technology is adopted for automatic registration, and coordinate unification without manual intervention is achieved; calculating and identifying a three-dimensional change area of the two-stage live-action three-dimensional model by using a spatial index difference, and optimizing the three-dimensional change area by adopting a multi-scale expansion-corrosion combination algorithm; filtering the optimized three-dimensional change area by using three-dimensional feature dual channels, and verifying the real building change; and generating a four-dimensional spatio-temporal result, and outputting a visual model including the elevation change value, the material type and the three-dimensional reconstruction parameters. According to the method, the problem that the subtle change of the building in a large-scale real scene model can be read by a machine is solved, and a high-reliability three-dimensional quantitative analysis tool is provided for urban illegal building monitoring and urban safety management.

The invention discloses an intelligent hospital logistics management platform, and relates to the technical field of logistics management. Comprising the following steps: establishing a hospital visual model through BIM, and adding a data acquisition device to a corresponding position of the visual model; performing type label setting on the data acquisition device according to the acquired data type, and then setting an attribute label according to the professional attribute of the target space where the data acquisition device is located; displaying corresponding equipment data according to the selected type tag and / or attribute tag; the method comprises the following steps: summarizing logistics information which comprises equipment data and repair data, identifying abnormal data in the equipment data, setting the corresponding equipment data as the abnormal data according to the content of the repair data, carrying out alarm processing on the abnormal data, processing according to position information, summarizing islanding logistics information, and sending the summarized islanding logistics information to a server; the service functions of logistics repair, alarm processing, energy analysis and the like of the whole hospital are undertaken, and the overall management level of the hospital is optimized.

The invention relates to the technical field of three-dimensional models, and discloses a GIS data-based low-altitude visual three-dimensional model automatic generation method, which comprises the following steps of: acquiring multi-source GIS vector data from an open geographic data source, performing standardized preprocessing through a data cleaning rule set, constructing a Cesium earth scene basic framework in a UE5 engine environment, and dynamically generating a city L2-level three-dimensional visualization model based on a preprocessed GIS data stream; when a low-altitude visual three-dimensional model is generated, a lightweight data format is adopted, data transmission efficiency and dynamic updating capability are improved, complex light environment changes can be adapted in real time, the problem of color distortion on the surface of the model is reduced, meanwhile, a visual angle deviation detection and correction mechanism is established, the geometric body edge distortion phenomenon is relieved, and the generation efficiency of the low-altitude visual three-dimensional model is improved. And the color rendition precision and the spatial positioning reliability of the low-altitude scene are improved.

The invention relates to the field of medical image processing and pathological diagnosis, aims to solve the problems that brain glioma multi-modal image fusion precision is low, heterogeneity feature and pathological association is weak, and visualization readability is poor, and provides a visualization method and device. The method comprises the steps of multi-modal image preprocessing and registration, regional adaptive multi-modal fusion, pathology association type heterogeneity feature quantification, multi-dimensional pathology visualization, and result verification and optimization. Images are rigidly registered and aligned through mutual information, features are enhanced by adopting a regional differentiation attention fusion algorithm, features are quantified through an improved LSSVM, pathological gold standards are associated, and a three-dimensional visualization model is constructed to visually present heterogeneity information. The device comprises a memory and a processor and can execute the method. According to the method, the heterogeneity evaluation accuracy and clinical readability are improved, treatment scheme optimization is assisted, and the method is suitable for accurate diagnosis and treatment scenes of brain glioma.

The embodiment of the invention discloses a building model rendering method and related equipment. The method comprises the following steps: when a rendering request is received, determining a rendering type of a building model in at least one to-be-rendered frame and a target component needing to be loaded based on the rendering request; screening out visual model data corresponding to the target component in a preset visual database, and identifying component attribute information of the target component in a preset graph database to generate a target rendering parameter; and loading the to-be-rendered frame, and rendering the building model in the to-be-rendered frame based on the rendering type and the target rendering parameter. Through the mode, the visual model data used for entity basic rendering is obtained from the preset visual database, the component attribute information used for entity attribute rendering is obtained from the preset graph database, so that the target rendering parameters are generated, and rendering is completed according to the target rendering parameters. Therefore, the integrity of the data required for rendering is ensured, and the rendering efficiency and the rendering quality are improved.

The invention discloses a visualization method and system for an oversized in-situ filling space under a composite roof, and belongs to the technical field of information processing. The method comprises the following steps: performing multi-angle data acquisition on a filling space under a composite roof structure to obtain original point cloud data; obtaining complete three-dimensional point cloud data based on the original point cloud data; preprocessing the three-dimensional point cloud data to obtain standard point cloud data; performing boundary contour recognition based on the standard point cloud data to obtain space boundary contour data; obtaining a spatial three-dimensional geometric model based on the spatial boundary contour data; performing section slicing based on the space coordinate range of the space three-dimensional geometric model, and obtaining size distribution data based on the obtained contour size parameters of the section; obtaining a total volume and a segmented volume of the filling space based on the size distribution data; and obtaining a three-dimensional visual model of the filling space based on the total volume and the segmented volume. The method provides reliable technical support for mine filling design and resource evaluation.

The invention provides an intelligent monitoring method and system for industrial silicon smelting stoking cover fire, and relates to the technical field of intelligent monitoring, and the method comprises the steps: carrying out the overall scanning of an industrial silicon smelting furnace and hearth materials through a laser scanning device, obtaining a point cloud data set, and constructing a smelting furnace three-dimensional model; performing multi-dimensional data acquisition to obtain a multi-dimensional data acquisition result; rendering to the smelting furnace three-dimensional model to obtain a smelting visual model; reading the monitoring index set, and monitoring to obtain a monitoring parameter set of the monitoring item set; performing smelting anomaly analysis, and extracting a first early warning level of the first monitoring anomaly item; and activating the industrial robot, and performing exception handling on the first monitoring exception item. The technical problems that in the prior art, industrial silicon smelting depends on manual driving of a forklift for fire covering, material pushing, auxiliary material adding, furnace ramming and other operations, and the safety risk of high-temperature radiation and scalding caused by high-temperature furnace material splashing exists are solved.

The invention discloses a digital integrated system of an LNG receiving station. Wherein the data fusion module comprises a multi-source heterogeneous data fusion engine and is used for collecting, storing and preprocessing data of an LNG receiving station; the model building module comprises a self-adaptive digital twinning modeling framework and is used for building digital twinning models of the LNG receiving station, and the models comprise a physical model, a machine learning model and a 3D visual model; the service module comprises an intelligent scene engine and a decision support subsystem driven by a knowledge graph; and the application module comprises an application development framework of a micro-service architecture and is used for developing an application oriented to a terminal user. Thus, efficient fusion and processing of multi-source heterogeneous data are realized through fusion of a multi-layer module architecture design and an advanced technology, and the data utilization rate and the real-time performance are greatly improved. And meanwhile, the intelligent decision-making capability of the system is remarkably enhanced, and various complex operation scenes and emergency situations can be effectively handled.

The invention relates to the field of model design, in particular to a dynamo and excel-based cross-software complex model accurate modeling method. The invention discloses a dynamo and excel-based cross-software complex model accurate modeling method. The method is characterized by being implemented according to the following steps in sequence: S1, understanding geometric feature extraction; s2, using a parameterized design tool; s3, carrying out data linkage and parametric modeling; s4, performing data interaction and batch creation; s5, performing three-dimensional visualization on the BIM data based on visual programming software; s6, model conversion and generation; and S7, carrying out cross-software model display based on a visual programming technology. The method is accurate in modeling.

Systems, methods, and other embodiments described herein relate to organizing and altering selected images from a style map with learning models through factoring style dimensions. In one embodiment, a method includes generating a style map by transforming and clustering information from an image dataset with a visualization model within a computation space having reduced dimensionality, and the style map includes style features derived from the image dataset. The method also includes comparing images selected from the style map using scores for dimensions associated with semantic attributes to form a comparison map. The method also includes mixing visual styles of the images from the comparison map with a generative model that computes representation interpolations within a latent space, the generative model outputting stylized images in an array. The method also includes communicating the array to a development system.

The invention relates to the technical field of liver surgery, and discloses a liver surgery planning system based on data fusion. The system comprises an image data fusion module, a three-dimensional model construction module, an operation path planning module, a risk assessment module and a scheme optimization module. The image data fusion module integrates CT and MRI images to generate a standardized image fusion model; a three-dimensional model building module generates a liver three-dimensional visual model according to the three-dimensional model; the operation path planning module plans an optimal resection path to form a preliminary operation path scheme; the risk assessment module assesses the surgical risk and generates a report; the scheme optimization module generates a final surgical planning scheme based on the report adjustment parameters. According to the system, through the multi-source data fusion and three-dimensional visualization technology, the liver structure and the tumor position are accurately presented, the operation path is scientifically planned, the operation risk is evaluated and avoided, the operation scheme is optimized, and accurate implementation of the liver operation is assisted.

The invention discloses a deep learning algorithm-based hydroelectric generating set maintenance disassembly planning method, and aims to solve the problems of high difficulty, low efficiency, resource waste and the like of large-scale hydroelectric generating set maintenance work. According to an original drawing, set equipment is subjected to three-dimensional modeling through SolidWorks software, and a three-dimensional visual model library containing equipment, maintenance tools and instruments and meters is constructed; then, determining disassembly information of the equipment to be disassembled, wherein the disassembly information comprises a disassembly priority sequence, a required tool and disassembly time; establishing a geometric constraint relationship between the equipment parts through the directed constraint graph and the constraint matrix; secondly, a disassembling sequence evaluation function is constructed by integrating quantitative indexes such as disassembling direction change, tool replacement, space movement distance and crane use conditions; finally, a deep learning algorithm is used for automatically optimizing and solving an optimal maintenance disassembly sequence; the maintenance efficiency of the hydroelectric generating set is effectively improved, time loss and resource waste are reduced, and the operation safety and efficiency of the hydroelectric generating set are improved.

The invention provides a geological envelope body automatic generation method. The method comprises the following steps: defining a target work area; performing sparse horizon picking of a top interface and a bottom interface on the geological envelope in the defined target work area to determine a top interface horizon, a bottom interface horizon and corresponding top interface and bottom interface data; based on the grid positions corresponding to all the pickup point positions of the top interface horizon and the bottom interface horizon, according to the range of the top interface data and the range of the bottom interface data, boundary lines of the geological envelope body at the top interface and the bottom interface in the target work area are determined; determining horizon depth values in all grid points of the top interface and the bottom interface; constructing a top interface boundary constraint and a bottom interface boundary constraint according to the horizon depth value and based on boundary lines of the geological envelope body at the top interface and the bottom interface to determine an intersection point between the top interface and the bottom interface of the envelope body so as to optimize the boundary lines of the geological envelope body at the top interface and the bottom interface; and generating a three-dimensional visualization model of the geological envelope based on the optimized boundary line.