Three-dimensional digital twin modeling method, system and equipment taking reservoir as object and medium

Abstract

The invention discloses a three-dimensional digital twin modeling method, system, equipment and medium taking a reservoir as an object, and relates to the technical field of reservoir monitoring, and the method comprises the steps: constructing a three-dimensional space model facing a reservoir entity, and forming a visual simulation environment; accessing multi-source data related to reservoir operation, and establishing a unified data aggregation and management mechanism; integrating a real-time operation state in the three-dimensional space model, and dynamically mapping perception information and business activities of the reservoir; and based on a set analysis model and a determination rule, carrying out intelligent processing on the reservoir operation data, identifying potential risks and generating an early warning result. According to the invention, by establishing a multi-type analysis model and a judgment rule system, real-time calculation and risk identification are carried out on key indexes, intelligent early warning of risks such as emergencies, trend anomalies and historical extreme value overrun is realized, and the risk prevention and control capability of the reservoir is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of reservoir monitoring technology, and in particular to a three-dimensional digital twin modeling method, system, equipment and medium for reservoirs. Background Technology

[0002] Reservoirs, as crucial infrastructure for water resource regulation, flood control, and ecological protection, undertake multiple functions including water storage, irrigation, water supply, power generation, and flood control. They are a key support for national water security and the stable operation of the social economy. Especially against the backdrop of frequent floods and severe droughts, the scientific scheduling and safe operation of reservoirs play an irreplaceable role in safeguarding people's lives and property. Furthermore, with the intensification of urbanization and climate change, reservoirs face increasingly complex operating environments, leading to continuously rising management challenges. Timely monitoring of reservoir operational status, scientific analysis of risks and hazards, and accurate dissemination of early warning information have become core issues that urgently need to be addressed in modern reservoir management.

[0003] Current reservoir management primarily relies on manual inspections and decentralized automatic monitoring systems, which suffer from the following significant shortcomings in practical applications: Data fragmentation and system isolation: While various monitoring devices (such as water level gauges, rain gauges, and video surveillance) are widely deployed, information is largely isolated, lacking a unified integration platform, making unified data display and collaborative analysis difficult. Delayed and slow-responding early warning mechanisms: Most reservoirs still use static thresholds to trigger warnings, lacking dynamic and comprehensive assessments of rainfall, water levels, and operational conditions, resulting in delayed early warning responses and difficulty in timely coverage of high-risk areas or populations. Limited visualization and insufficient perception capabilities: Current systems mostly use two-dimensional charts, failing to accurately represent real-world scenarios. The lack of three-dimensional visualization limits comprehensive understanding of reservoir structure, geographical environment, and equipment deployment. Extensive and incomplete closed-loop inspection and maintenance management: Daily inspections and facility maintenance rely heavily on paper or decentralized records, lacking closed-loop coordination in task assignment, process monitoring, and hazard handling, impacting inspection quality and efficiency. The lack of a unified dispatch and risk decision support platform makes it impossible to quickly integrate multi-source information to form a unified situational awareness map in the face of extreme weather or sudden flood events. This results in low efficiency and incomplete coverage of dispatch instructions, which can easily lead to response delays.

[0004] To address the technical deficiencies and application pain points of existing reservoir management methods, this invention proposes a three-dimensional digital twin method for reservoirs, constructing an intelligent reservoir management platform that integrates multiple technologies such as GIS, IoT, big data, artificial intelligence, and 3D modeling. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the problem that this invention aims to solve is that current reservoir management mainly relies on manual inspections and decentralized automatic monitoring systems. In practical applications, there are problems such as data fragmentation, system isolation, lagging early warning mechanisms, slow response, limited visualization level, insufficient perception capabilities, and lack of three-dimensional visualization support.

[0007] To address the aforementioned technical problems, this invention provides the following technical solution: a three-dimensional digital twin modeling method for reservoirs, comprising: constructing a three-dimensional spatial model of the reservoir entity to form a visual simulation environment with real geographical coordinates and structural features; accessing multi-source data related to reservoir operation and establishing a unified data aggregation and management mechanism; integrating real-time operating status into the three-dimensional spatial model to dynamically map the reservoir's perception information and business activities; intelligently processing the reservoir operation data based on a set analysis model and judgment rules to identify potential risks and generate early warning results; presenting the early warning results in conjunction with the three-dimensional model and pushing the information to the system platform; displaying the overall situation of the reservoir in a three-dimensional scene through visualization to control the reservoir's operating status.

[0008] As a preferred embodiment of the three-dimensional digital twin modeling method for reservoirs described in this invention, the construction of a three-dimensional spatial model for the reservoir entity includes: using Geographic Information System (GIS) technology as the underlying spatial support to model and reconstruct the natural geographical environment of the target reservoir area, generating a three-dimensional terrain model with elevation attributes; based on the three-dimensional terrain model, combined with water conservancy engineering design drawings and construction archive information, using three-dimensional modeling tools to perform refined modeling of the engineering entities within the reservoir management area, constructing a three-dimensional spatial model with structural and spatial attributes.

[0009] As a preferred embodiment of the three-dimensional digital twin modeling method for reservoirs described in this invention, the establishment of a unified data aggregation and management mechanism includes: formulating a unified data classification and attribute model for multi-source data from different sources and formats, clarifying the field definitions, unit specifications, time identifiers, and spatial coordinates of each type of data, and unifying the semantics of heterogeneous data; deploying data access adapters to support differentiated acquisition strategies for different data sources, performing unified preprocessing on all accessed data before it is entered into the database, and distributing the processed data to the corresponding database according to data type; adding multiple tags to each piece of data during the data entry process, constructing a multi-dimensional index system, and supporting multi-dimensional fast query and retrieval.

[0010] As a preferred embodiment of the three-dimensional digital twin modeling method for reservoirs described in this invention, the dynamic mapping of reservoir perception information and business activities includes mapping multi-source operational data that has been uniformly aggregated and managed to the corresponding three-dimensional model objects according to key identification fields, and bidirectionally binding data with three-dimensional primitives; for real-time monitoring data, by establishing dynamic data channels with each corresponding monitoring point in the model, the attribute display and visual status update are driven in real time, and business activities are overlaid on the three-dimensional scene in a graphical manner, so as to link and display the business situation with the physical structure.

[0011] As a preferred embodiment of the three-dimensional digital twin modeling method for reservoirs described in this invention, the following steps are taken: the judgment rules are based on reservoir safety operation standards and historical operation data, setting static and dynamic threshold rules for different monitoring objects; the identification of potential risks and generation of early warning results includes integrating AI algorithms and time-series data mining technology, combining real-time monitoring data streams, performing trend prediction, anomaly detection, and rate of change analysis on the operating status, and identifying potential hidden dangers or sudden changes; when the analysis model detects data anomalies or exceeds the set threshold, the system automatically triggers the early warning generation process to form structured early warning information.

[0012] As a preferred embodiment of the three-dimensional digital twin modeling method for reservoirs described in this invention, the step of linking the early warning results with the three-dimensional model includes the system automatically binding the generated structured early warning information to the corresponding objects or regions of the three-dimensional model according to the identification fields, and highlighting the early warning status in the three-dimensional digital twin scene using a highlighting identifier.

[0013] As a preferred embodiment of the three-dimensional digital twin modeling method for reservoirs described in this invention, the step of displaying the overall status of the reservoir in a three-dimensional scene through visualization means includes constructing a comprehensive reservoir visualization interface and integrating multiple monitoring layers to dynamically display real-time data and status changes in the three-dimensional scene.

[0014] To address the aforementioned technical problems, this invention provides the following technical solution: a system for three-dimensional digital twin modeling of reservoirs, comprising: a model construction module, a data management module, a mapping and early warning module, and an information push and visualization module; the model construction module constructs a three-dimensional spatial model of the reservoir entity, forming a visualized simulation environment with real geographical coordinates and structural features; the data management module accesses multi-source data related to reservoir operation and establishes a unified data aggregation and management mechanism; the mapping and early warning module integrates real-time operating status in the three-dimensional spatial model, dynamically maps the reservoir's perception information and business activities, and intelligently processes the reservoir operation data based on a set analysis model and judgment rules, identifying potential risks and generating early warning results; the information push and visualization module presents the early warning results in conjunction with the three-dimensional model and pushes information to the system platform, displaying the overall situation of the reservoir in the three-dimensional scene through visualization, and controlling the reservoir's operating status.

[0015] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of a three-dimensional digital twin modeling method for a reservoir as described above.

[0016] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a three-dimensional digital twin modeling method for a reservoir as described above.

[0017] The beneficial effects of this invention are as follows: Based on GIS and 3D modeling technology, this invention constructs a digital twin model of the reservoir that is consistent with the real geographic coordinates, fully restores the reservoir and its surrounding environment and engineering structure, realizes the spatial visualization expression from natural elements to engineering facilities, and improves the information integration capability and on-site perception capability of reservoir management.

[0018] This invention establishes a multi-type analysis model and judgment rule system to perform real-time calculation and risk identification of key indicators such as water level, rainfall, flow rate, and seepage pressure, thereby achieving intelligent early warning of risks such as emergencies, trend anomalies, and exceeding historical extreme values, effectively improving the risk prevention and control capabilities of reservoirs.

[0019] This invention embeds early warning information into a three-dimensional model for intuitive presentation, enhances the perception effect through graphic flashing, color highlighting, and dynamic overlay, and supports pushing early warning instructions to relevant responsible persons through various means such as SMS, APP, and broadcast, ensuring timely and accurate information transmission. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a three-dimensional digital twin modeling method for a reservoir as an object in Example 1. Detailed Implementation

[0022] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0023] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0024] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides a method for three-dimensional digital twin modeling of a reservoir, including, as follows: Figure 1 As shown:

[0025] Step 1: Construct a three-dimensional spatial model of the reservoir entity to form a visual simulation environment with real geographical coordinates and structural features.

[0026] Specifically, using Geographic Information System (GIS) technology as the underlying spatial support, and based on remote sensing image data, digital elevation model (DEM), topographic maps and field survey results, the natural geographical environment of the target reservoir area is modeled and reconstructed to generate a three-dimensional terrain scene with elevation attributes.

[0027] Based on the aforementioned three-dimensional terrain model, and combined with water conservancy engineering design drawings and construction archive information, Building Information Modeling (BIM) or three-dimensional modeling tools are used to perform detailed modeling of engineering entities within the reservoir management area, including but not limited to the dam body, spillway, water diversion culvert, gate system, gatehouse, electrical control equipment, management rooms and supporting facilities, etc., to construct a three-dimensional object model with structural and spatial attributes.

[0028] By unifying coordinates and registering spatially, the natural environment model and the engineering structure model are integrated into the same three-dimensional coordinate system, forming a full-element three-dimensional digital space for the reservoir that supports dynamic data binding and interactive control. This enables the simulation representation of the reservoir entity and provides a three-dimensional visual foundation for subsequent functions such as real-time mapping of operation monitoring information, status visualization, and scheduling simulation.

[0029] Step 2: Access multi-source data related to reservoir operation and establish a unified data aggregation and management mechanism.

[0030] Specifically, relying on a unified data access service framework, it accesses multiple types of sensing data and business data covering the entire process of reservoir operation. The data sources include, but are not limited to, automatic monitoring equipment, video image systems, manual inspection systems, and external authoritative data sources.

[0031] Data from the automatic monitoring equipment is collected and uploaded in real time via IoT interface protocols (such as MQTT, TCP / IP, etc.), covering key indicators such as rainfall, water level, flow rate, dam deformation, seepage and pressure, equipment operating status, and reservoir capacity changes.

[0032] The video image data is obtained by connecting to the front-end monitoring system to obtain video streams and image snapshots of the reservoir and its surrounding monitoring points. It supports access to single-screen, multi-screen and video wall display modes, and provides remote control and video playback capabilities.

[0033] Manual inspection data is entered through mobile terminals or web platforms, including inspection plans, routes, inspection results, and graphic records, forming a structured business dataset.

[0034] External authoritative data includes weather forecasts from the National Meteorological Center, meteorological, hydrological, flood information, and forecasts released by the Ministry of Water Resources and water management platforms at all levels. These data are collected periodically and automatically stored in the database through API interfaces or data subscriptions.

[0035] Based on data access, a unified data aggregation and management mechanism is established. For sensing data (such as water level, rainfall, video stream, image, flow rate, seepage pressure, etc.), business data (such as inspection records, alarm events, operation and maintenance plans), and external data (such as weather forecasts, hydrological information, etc.) from different sources and formats, a unified data classification and attribute model is formulated to clarify the field definition, unit specification, time identifier and spatial coordinates of each type of data, so as to achieve semantic unification of heterogeneous data.

[0036] Design and deploy data access adapters to support differentiated acquisition strategies for different data sources: For real-time sensor data, access is achieved through IoT gateways and edge computing modules, using protocols such as MQTT, CoAP, and HTTP; for video image data, video platforms are connected via standard protocols such as RTSP and GB28181 to achieve unified transcoding and distribution of streaming media; for external interface data, information from authoritative external data sources is periodically retrieved through open APIs or Web services, and data format conversion and filtering are performed; for manually uploaded data, such as inspection forms and multimedia content, unified structured parsing and database entry are achieved through form engines or mobile terminal interfaces.

[0037] All incoming data undergoes format validation, missing data completion, anomaly removal, and time alignment via a unified data preprocessing module before being stored, ensuring data quality and time-series consistency. Abnormal data is logged with its source and anomaly type for subsequent backtracking analysis.

[0038] The processed data is distributed to relational databases (such as PostgreSQL and MySQL) or time-series databases (such as InfluxDB and TimescaleDB) according to data type. Video and image data are stored uniformly in object storage systems or media servers, and business log information is stored in log databases (such as Elasticsearch). At the same time, some key indicator data is pushed to caching middleware (such as Redis) to support high-frequency access.

[0039] During the data entry process, multiple tags such as reservoir identification code, spatial location, data type, and collection time are added to each data entry to build a multi-dimensional index system. This system supports fast querying and retrieval by dimensions such as reservoir, equipment, time period, and monitoring indicators, thereby improving data availability and system response efficiency.

[0040] The aggregated data is encapsulated into API services, providing standardized data query interfaces, real-time subscription interfaces, and data push interfaces for unified access by subsequent business modules such as analysis model calls, 3D scene driving, and early warning engine triggering, thus building a platform-level data resource middleware.

[0041] Step 3: Integrate real-time operating status into the three-dimensional spatial model to dynamically map the reservoir's sensing information and business activities.

[0042] Specifically, the multi-source operational data that has been uniformly aggregated and managed is mapped to the corresponding 3D model objects according to key identification fields such as spatial location information and equipment number, so as to achieve two-way binding between data and 3D primitives.

[0043] For real-time monitoring data, such as water level, rainfall, flow rate, seepage pressure, and equipment status, dynamic data channels are established with the corresponding monitoring points and facility components (such as gates, dams, hoists, and sensors) in the model to drive the real-time display of their attributes and updates of their visual status, such as color changes, icon flashing, and deformation animations.

[0044] Business activities such as alarm events, video images, and manual inspection results are overlaid on a 3D scene in a graphical way to realize the linkage display of business status and physical structure. For example, when a sensor malfunctions, the device icon is highlighted in the 3D model and real-time alarm information and historical curves pop up.

[0045] Users can click on any facility, equipment, or area in the 3D model to query its current status parameters, historical data trends, related image information, and processing records. They can also jump to the related analysis, report, or business processing interface to achieve the integration of data display and business operation.

[0046] The system supports the time-series reconstruction function of data display, which can play back any period of time to present the multi-dimensional changes in the reservoir's operating status during that period, providing visual support for event tracing and risk assessment.

[0047] Through a dynamic data mapping mechanism, the 3D spatial model not only has display functions, but also real-time interaction, monitoring and perception, and business-driven capabilities, forming the core operating carrier of the digital twin platform.

[0048] Step 4: Based on the established analysis model and judgment rules, intelligently process the reservoir operation data, identify potential risks, and generate early warning results.

[0049] Specifically, a multi-type analysis model and judgment rule system will be constructed. Based on the needs of reservoir safety operation and management, multi-dimensional analysis models and judgment logics for different monitoring objects will be established in advance. Model types include, but are not limited to:

[0050] Water level trend model: used to identify sudden changes in water level and exceedance of warning levels in a short period of time.

[0051] Rainfall-water level correlation model: Analyzing the relationship between heavy rainfall and rapid water level response.

[0052] Diagnostic model for dam seepage pressure and deformation: a comprehensive assessment of dam health status based on threshold and trend changes.

[0053] Traffic anomaly model: Determines if the inbound / outbound traffic exceeds the limit.

[0054] Intrusion detection model: used to identify abnormal video behaviors such as people / vehicles crossing boundaries or illegally approaching.

[0055] Because the intrusion detection judgment process is quite complex, it is further explained here that the working mechanism of the intrusion detection model can be a regional intrusion detection early warning. Specifically, within the field of view of the camera monitoring, the user can arbitrarily set the warning area and warning line. When a moving object (person or vehicle) enters the warning area, moves within the warning area, or crosses the set warning line, the intrusion detection model triggers an alarm based on the collected video and marks the moving target with an alarm box, and the monitoring screen displays the alarm information.

[0056] Flexible setting of warning zones or warning lines: Users can set warning zones or warning lines of any shape and direction according to the actual application needs. Warning zones can support up to 10-sided polygons. Users can set up to 3 warning zones and 3 warning lines simultaneously in a single monitoring scenario. Warning zones or lines can intersect and overlap, and the various intrusion detection functions do not affect each other. Multiple moving target intrusions can be identified and alarmed simultaneously.

[0057] In another optional embodiment, the intrusion detection model can also work by formulating behavior analysis and alarm display rules based on the actions of people in the video. Supported behavior analysis types include: tripwire intrusion, area intrusion, loitering detection, video anomalies, fence crossing, etc. When there is abnormal behavior in the area that meets the detection rules, an alarm is immediately sent to the monitoring platform to remind the on-duty personnel to pay attention and take further action. It can automatically detect behaviors such as crossing a given warning line from left to right or from right to left, automatically detect behaviors such as climbing over fence warning lines, entering or leaving an area, and automatically detect behaviors such as people or vehicles entering (leaving) a designated warning area. It issues alarms for the above intrusion behaviors, records and automatically generates alarm information and sends it to the relevant responsible persons.

[0058] The judgment rules are based on reservoir safety operation standards and historical operation data, and set static and dynamic threshold rules for different monitoring objects.

[0059] Real-time acquisition and formatting of operational data: The latest reservoir operation data, including parameters such as water level, rainfall, flow rate, seepage pressure, deformation, and equipment status, is retrieved from a unified data aggregation and management system and then standardized.

[0060] Perform model calculations and anomaly detection: Input standardized data into various analysis models for real-time calculation and processing, and output the following results: whether the current state is abnormal, abnormal indicators and their deviations, time trend analysis results (such as the rate of water level rise), and risk scores (such as rule-based scoring or model confidence). For video behavior analysis, perform image recognition or behavior recognition algorithms to determine whether risky behaviors such as boundary crossing or intrusion are constituted.

[0061] Determine the warning status and generate structured warning information: When the model output meets the preset warning rules, the system automatically determines that it is in a warning status and generates structured warning information, including: warning type, warning level, corresponding monitoring point and spatial location, current monitoring value, threshold, exceedance range, trigger time and suggested handling measures, etc.

[0062] Classified management of early warning levels and support for situation tracking and trend assessment: Integrating AI algorithms and time series data mining technology, combined with real-time monitoring data streams, it performs trend prediction, anomaly detection and rate of change analysis on the operating status, and identifies potential hidden dangers or sudden changes.

[0063] Step 5: Link the early warning results with the 3D model and push the information to the system platform. Use visualization to display the overall situation of the reservoir in the 3D scene and manage the operation status of the reservoir.

[0064] Specifically, the system binds early warning information to 3D model objects: It automatically binds the generated structured early warning information to the corresponding objects or areas in the 3D model, based on identifier fields such as reservoir name, monitoring point number, or spatial coordinates. For example, abnormal rainfall early warnings are bound to the rainfall monitoring point model; seepage pressure early warnings are bound to the dam monitoring section model; and intrusion early warnings are bound to the camera layer model of the monitored area.

[0065] Once a model object is bound to an alert, it will be in an "alert activated" state, and detailed alert content and real-time values ​​will be displayed.

[0066] Graphical visualization: The platform uses color highlighting, icon flashing, and animation overlay to prominently display the warning status in a 3D digital twin scene. For example, water levels exceeding flood limits are displayed with a bright red water level line; abnormal equipment icons flash as a warning; and the border of the intrusion area flashes dynamically. In addition, users can click on any warning point to bring up a detailed information panel to view information such as trigger time, exceeding limit value, handling suggestions, and historical trends.

[0067] Information push to the system platform includes the following methods: Based on the warning level, notification strategy, and target list set within the platform, the system automatically pushes information through various means: SMS notification: sending key information via SMS to the dam safety responsible person, the "three responsible persons" for flood control of small reservoirs, etc.; APP pop-up: generating a strong reminder pop-up in the mobile application; Web platform reminder: triggering an alarm pop-up or sound prompt on the web platform; Video broadcast linkage: triggering voice playback on the broadcast terminal or video wall linkage switching; the warning push supports "classification and grading" and "assigned personnel and positions" to achieve direct information delivery and clear responsibility.

[0068] The system automatically records all push logs of early warning information, including push time, recipient, push method, delivery status, processing feedback, etc. It supports: querying by early warning type, time period, and recipient; statistics on push response rate and average delivery time for various types of early warnings; and automatic generation of early warning response reports to provide data basis for subsequent performance evaluation and management review.

[0069] In another optional embodiment, the platform can also provide an independent business information management interface for each reservoir, supporting the input and maintenance of information including basic reservoir information, engineering characteristics, registration, safety assessment, flood control responsibilities, management organization, personnel composition, and system management.

[0070] Managers can access and edit information about the reservoirs under their jurisdiction based on their permissions. All information is linked to the spatial model, enabling integrated display of maps and data. The platform supports importing historical archives, forming a complete digital archive system for reservoir operation.

[0071] The platform can also embed a business data dashboard module to display real-time statistics on core indicators such as equipment operation status, number of anomalies, inspection coverage, hazard handling rate, and maintenance completion rate. It supports filtering and comparative analysis by time, task type, reservoir level, and other dimensions, and outputs the results in various forms such as charts, lists, or map annotations. Business data can be exported to PDF, Excel, report charts, and other formats for easy archiving or submission to higher-level units.

[0072] The visualization of the overall situation of the reservoir in a 3D scene includes:

[0073] Construct a comprehensive visualization interface for the reservoir and integrate multiple monitoring layers: In the digital twin platform, construct a comprehensive display interface that includes map views, statistical panels, chart components, and video footage, integrating and displaying reservoir operation-related information in the form of layers; the integrated layers include reservoir boundary maps, hydrological maps, hydraulic engineering structure diagrams, sensor distribution maps, early warning maps, video monitoring maps, radar cloud maps, gate status maps, etc.; support the opening, closing, transparency adjustment, and overlay control of layers to achieve multi-dimensional situational visualization.

[0074] Dynamically display real-time data and status changes in a 3D scene: dynamically project real-time operating data onto a 3D model, color-code and animation enhancement for key monitoring points, such as: water level lines dynamically changing with reservoir water level; equipment status distinguished by icon color for online, offline, and abnormal states; gate opening and closing status directly reflected in 3D; support for flashing prompts and automatic pop-up of real-time alarm layers when events are triggered.

[0075] Enables data linkage, chart overlay, and multi-scale layered browsing: Based on 3D visualization, it overlays statistical charts such as line charts, bar charts, and pie charts to display changes in reservoir rainfall, water level, reservoir capacity, and warning frequency; supports linked clicking between charts and models, allowing users to locate corresponding 3D areas or devices by clicking on chart elements, achieving synchronous jumps between "map-data-object"; supports filtering and display based on administrative divisions, reservoir levels, management units, etc., with the map automatically locating and adjusting the viewpoint, facilitating users to flexibly view the status of reservoir groups in large or localized areas.

[0076] Provides user interaction and operation functions to assist in command and dispatch and situation analysis: It supports users to interact with the model in the 3D scene by clicking, swiping, and selecting, so as to: query monitoring data and historical trends; view video monitoring screens; mark key areas and add notes; initiate remote control commands (such as video redirection, broadcasting, etc.); The system also provides an event playback function, which allows users to select any time period and replay the process of reservoir status changes during that period according to the timeline, to assist in emergency review and decision optimization.

[0077] Example 2, the second embodiment of the present invention, differs from the first embodiment in that it provides a three-dimensional digital twin modeling system for a reservoir, comprising a model building module, a data management module, a mapping and early warning module, and an information push and visualization module. The model building module constructs a three-dimensional spatial model of the reservoir entity, forming a visualized simulation environment with real geographical coordinates and structural features. The data management module accesses multi-source data related to reservoir operation, establishing a unified data aggregation and management mechanism. The mapping and early warning module integrates real-time operating status within the three-dimensional spatial model, dynamically mapping the reservoir's perceived information and business activities. Based on a set analysis model and judgment rules, it intelligently processes the reservoir's operating data, identifies potential risks, and generates early warning results. The information push and visualization module integrates the early warning results with the three-dimensional model and pushes information to the system platform. Through visualization, it displays the overall situation of the reservoir in the three-dimensional scene, enabling control over the reservoir's operating status.

[0078] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0079] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0080] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0081] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented in combination with any of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0082] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for three-dimensional digital twin modeling of a reservoir, characterized in that: include, Construct a three-dimensional spatial model of the reservoir entity to form a visual simulation environment with real geographical coordinates and structural features; Access multi-source data related to reservoir operation and establish a unified data aggregation and management mechanism; The real-time operating status is integrated into the three-dimensional spatial model, dynamically mapping the reservoir's sensing information and business activities; Based on the established analysis model and judgment rules, the reservoir operation data is intelligently processed to identify potential risks and generate early warning results. The early warning results are presented in conjunction with the 3D model, and the information is pushed to the system platform. The overall situation of the reservoir is displayed in the 3D scene through visualization, and the operation status of the reservoir is controlled.

2. The three-dimensional digital twin modeling method for a reservoir as described in claim 1, characterized in that: The construction of the three-dimensional spatial model for the reservoir entity includes using Geographic Information System (GIS) technology as the underlying spatial support to model and reconstruct the natural geographical environment of the area where the target reservoir is located, and generate a three-dimensional terrain model with elevation attributes. Based on the aforementioned three-dimensional terrain model, and combined with water conservancy engineering design drawings and construction archive information, three-dimensional modeling tools are used to refine the engineering entities within the reservoir management area, constructing a three-dimensional spatial model with structural and spatial attributes.

3. The three-dimensional digital twin modeling method for a reservoir as described in claim 2, characterized in that: The establishment of a unified data aggregation and management mechanism includes formulating a unified data classification and attribute model for multi-source data from different sources and formats, clarifying the field definitions, unit specifications, time identifiers and spatial coordinates of each type of data, and unifying the semantics of heterogeneous data; Deploy data access adapters to support differentiated collection strategies for different data sources. All access data undergoes unified preprocessing before being stored in the database, and the processed data is distributed to the corresponding database according to data type. During the data import process, multiple tags are added to each data entry to build a multi-dimensional index system, supporting fast multi-dimensional querying and retrieval.

4. The three-dimensional digital twin modeling method for a reservoir as described in claim 3, characterized in that: The dynamic mapping of reservoir perception information and business activities includes mapping multi-source operation data that has been uniformly aggregated and managed to the corresponding three-dimensional model objects according to key identification fields, and bidirectionally binding data with three-dimensional primitives. For real-time monitoring data, dynamic data channels are established with the corresponding monitoring points in the model to drive the real-time display of attributes and updates of visual status. Business activities are overlaid on the three-dimensional scene in a graphical way, and the business situation and physical structure are displayed in a linked manner.

5. The three-dimensional digital twin modeling method for a reservoir as described in claim 4, characterized in that: The judgment rules are based on reservoir safety operation standards and historical operation data, and set static and dynamic threshold rules for different monitoring objects. The process of identifying potential risks and generating early warning results includes integrating AI algorithms and time-series data mining technology, combining real-time monitoring data streams, performing trend prediction, anomaly detection and rate of change analysis on the operating status, and identifying potential hidden dangers or sudden changes. When the analysis model detects abnormal data or exceeds a set threshold, the system automatically triggers the early warning generation process to form structured early warning information.

6. The three-dimensional digital twin modeling method for a reservoir as described in claim 5, characterized in that: The step of linking the early warning results with the 3D model includes the system automatically binding the generated structured early warning information to the corresponding objects or areas of the 3D model according to the identification fields, and highlighting the early warning status in the 3D digital twin scene using a highlighting identifier.

7. The three-dimensional digital twin modeling method for a reservoir as described in claim 6, characterized in that: The method of displaying the overall status of the reservoir in a three-dimensional scene through visualization includes constructing a comprehensive visualization interface for the reservoir and integrating multiple monitoring layers to dynamically display real-time data and status changes in the three-dimensional scene.

8. A three-dimensional digital twin modeling system for a reservoir, employing the three-dimensional digital twin modeling method for a reservoir as described in any one of claims 1 to 7, characterized in that: It includes a model building module, a data management module, a mapping and early warning module, and an information push and visualization module; The model building module constructs a three-dimensional spatial model of the reservoir entity, forming a visual simulation environment with real geographical coordinates and structural features; The data management module accesses multi-source data related to reservoir operation and establishes a unified data aggregation and management mechanism. In the three-dimensional spatial model, the mapping and early warning module integrates real-time operating status, dynamically maps the reservoir's sensing information and business activities, and intelligently processes the reservoir's operating data based on the set analysis model and judgment rules to identify potential risks and generate early warning results. The information push and visualization module will link the early warning results with the 3D model and push the information to the system platform. It will also use visualization to display the overall situation of the reservoir in the 3D scene and control the operation status of the reservoir.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the three-dimensional digital twin modeling method for a reservoir as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the three-dimensional digital twin modeling method for a reservoir as described in any one of claims 1 to 7.

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