Oil and gas field ground and underground integrated construction method with three-dimensional model fused with mechanism model

Abstract

The invention belongs to the technical field of oil and gas fields, and particularly relates to an oil and gas field ground and underground integrated construction method with a three-dimensional model fused with a mechanism model, which comprises the following specific steps of: comprehensively combing an existing mature commercial software model and a mechanism model established based on an equipment process operation principle; functions, application ranges and data characteristics of all the models are determined; and determining boundary conditions among different mechanism models. According to the method, for the closed-loop interaction problem of field facilities and virtual objects, integrated coupling between models and between the models and data is achieved, dynamic closed-loop, data support and real-time interaction are completed in a virtual space, a technical foundation is laid for simulation, prediction and optimization of the virtual models on twin entities, and the method has the advantages of being high in practicability and wide in application range. Therefore, fine management and control of the whole oil and gas field production process are realized, and the whole oil and gas field production process can be comprehensively and accurately simulated and optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas fields, and specifically provides a method for constructing an integrated ground and underground oil and gas field by fusing a three-dimensional model with a mechanism model. Background Art

[0002] Oil and gas field development refers to formulating a reasonable development plan for an oil and gas field with industrial value based on detailed exploration results and necessary production development tests, and then carrying out construction and commissioning to ensure the long-term production of the oil and gas field according to the predetermined production capacity and economic effects.

[0003] Under the existing oil and gas field development mode, the data of each link are independent of each other, and there is a lack of an effective closed-loop interaction mechanism between on-site facilities and virtual objects, resulting in difficulties in comprehensively and accurately simulating and optimizing the entire oil and gas field production process. Therefore, a method for constructing an integrated ground and underground oil and gas field by fusing a three-dimensional model with a mechanism model is invented. Summary of the Invention

[0004] To solve the above technical problems, according to one aspect of the present invention, the following technical solutions are provided:

[0005] A method for constructing an integrated ground and underground oil and gas field by fusing a three-dimensional model with a mechanism model, which includes the following specific steps:

[0006] S1, Data transfer and coupling between mechanism models:

[0007] S11: Comprehensively sort out the existing mature commercial software models and mechanism models established based on the operating principles of equipment processes, and clarify the functions, applicable scopes, and data characteristics of each model;

[0008] S12: Determine the boundary conditions between different mechanism models, clarify the starting and ending points of data transfer between models, as well as the physical meaning of the data;

[0009] S13: Develop standard formats and specifications for data input and output to ensure the accurate transmission and understanding of data between different models;

[0010] S14: Based on the standardized data interface, establish a data transfer method between mechanism models to achieve information sharing and collaborative operation between models, and achieve "underground - aboveground" integrated coupling;

[0011] S2, Coupling between AI models and mechanism models:

[0012] S21: Deeply analyze common AI algorithm types and their application modes in the oil and gas field, and summarize their advantages, disadvantages, and applicable scenarios;

[0013] S22: Based on the characteristics of AI algorithms and mechanism models, establish multiple mechanism-AI model coupling modes, and determine the hierarchical structure under different coupling modes;

[0014] S23: Develop a standardized docking method for mechanism-AI data coupling, standardize the processes, formats, and interfaces of data transmission, ensure that the mechanism model and the big data model can work together, and provide technical support for the construction of the full-process dynamic model of oil and gas fields;

[0015] S3, Coupled dynamic interaction between the simulation model and the 3D model:

[0016] S31: Build a coupling framework between the simulation model and the 3D model, determine the logical relationship and transmission path of data interaction, and the simulation model includes a mechanism model and an AI data model;

[0017] S32: Design the data interaction interface between models, and formulate interaction modes, including real-time data push and event-driven interaction, to ensure that data can be transmitted between the two models in a timely and accurate manner;

[0018] S33: Evaluate the performance of the data transmission protocol, including transmission delay and data packet loss rate indicators, and improve the efficiency and stability of data transmission by optimizing protocol parameters to achieve visual interaction of the digital twin model.

[0019] As a preferred solution of the method for constructing an integrated surface and subsurface of an oil and gas field by fusing a mechanism model with a 3D model according to the present invention, wherein: the specific steps of S14 are as follows:

[0020] S141: After completing model sorting, boundary definition, and data standardization, design standardized data interfaces for different mechanism models according to unified data formats and specifications to ensure the generality of the data input and output interfaces of each model;

[0021] S142: Develop a detailed data transfer process, and clarify the sequence and trigger conditions of data transfer between various mechanism models at different stages of oil and gas field production;

[0022] S143: After developing a detailed data transfer process, conduct joint debugging tests on different mechanism models. By simulating the actual production scenarios of oil and gas fields, check whether the data transfer between models is accurate and whether the coupling mechanism can operate normally;

[0023] S144: Establish a feedback and optimization mechanism, collect the problems feedback by users during the use process, and find out the deficiencies of the coupling mechanism through the analysis of model operation data. Continuously optimize the data interface, transmission middleware, and data transfer process to adapt to various changes and requirements in the oil and gas field production process.

[0024] As a preferred embodiment of the method for constructing an integrated surface and subsurface of an oil and gas field with a three-dimensional model fusion mechanism model of the present invention, wherein: the specific steps of S21 are as follows:

[0025] S211: Comprehensively collect AI algorithm materials currently applicable to the oil and gas field, and deeply understand the basic principles, mathematical models, applicable scenarios, advantages and limitations of each algorithm;

[0026] S212: Sort out the application scenarios of AI algorithms in various links of oil and gas field exploration, development, production and management; in the exploration link, AI algorithms can be used for seismic data interpretation to identify potential oil and gas reservoir locations; in the development stage, AI can be used to predict reservoir dynamics and optimize production plans; in the production process, it can be used for equipment fault diagnosis to ensure production continuity; at the management level, it can assist in production scheduling and resource allocation; by sorting out the application scenarios, the application methods and objectives of AI algorithms in different business scenarios can be clarified;

[0027] S213: Study the combination methods of AI algorithms and mechanism models in different application scenarios;

[0028] S214: Based on the collected materials and analysis results, select appropriate data sets and evaluation indicators to evaluate the performance and effects of different AI algorithms in oil and gas field application scenarios, and the evaluation indicators include accuracy, recall rate, mean square error, and mean absolute error;

[0029] S215: Summarize the application modes of AI algorithms in the oil and gas field, summarize the experiences of successful cases and the lessons of failed cases, analyze the applicable conditions, advantages and limitations of different application modes, and provide references for the subsequent coupling of AI models and mechanism models.

[0030] As a preferred embodiment of the method for constructing an integrated surface and subsurface of an oil and gas field with a three-dimensional model fusion mechanism model of the present invention, wherein: the specific steps of S22 are as follows:

[0031] S221: First, widely collect and deeply study successful cases and practical experiences of the coupling of AI models and mechanism models in the oil and gas field and other industrial fields at home and abroad to analyze common coupling modes. Then, combined with the characteristics of oil and gas field production, including data characteristics, process flow, and business requirements, evaluate the applicability of each coupling mode. Among them, the common coupling modes include series coupling mode, parallel coupling mode, and embedded coupling mode. In the series coupling mode, the output of the mechanism model is used as the input of the AI model, and the AI model further processes it to obtain the final result. In the parallel coupling mode, the mechanism model and the AI model run in parallel, and the results of the two are integrated through a specific fusion strategy. In the embedded coupling mode, the AI model is embedded in a specific link of the mechanism model to optimize and simulate the local process.

[0032] S222: Have in-depth communication with the oil and gas field production management team and engineering and technical personnel to clarify the specific goals to be achieved by the coupling of the AI model and the mechanism model.

[0033] S223: According to the selected coupling mode, build a coupling hierarchical framework for the AI model and the mechanism model. If the series coupling mode is adopted, determine the sequence of the mechanism model and the AI model, and design the interfaces and formats for data transfer between the models. If the parallel coupling mode is adopted, plan the respective task divisions of the mechanism model and the AI model, as well as the methods and levels of result fusion. If the embedded coupling mode is adopted, determine the specific location and action mode of the AI model embedded in the mechanism model.

[0034] S224: Based on the built coupling hierarchical framework, select representative oil and gas field production scenarios and data sets to conduct simulation experiments. Through the simulation experiments, verify the effectiveness and stability of the coupling mode and the hierarchical framework.

[0035] S225: First, establish a normalized evaluation mechanism, regularly collect the operation data and business feedback of the model, and then use appropriate evaluation indicators to quantitatively evaluate the performance of the coupling model. Once it is found that the model performance declines or cannot meet the business requirements, analyze the reasons in time and optimize the coupling mode and the hierarchical framework targeted.

[0036] As a preferred solution of the method for constructing the integration of the surface and subsurface of an oil and gas field by fusing a three-dimensional model and a mechanism model according to the present invention, wherein: the specific steps of S23 are as follows:

[0037] S231: Conduct a comprehensive review of the data sources, types, formats, and storage methods of the AI model and the mechanism model, understand the characteristics of data dimensions, data volume, and data update frequency, and draw a data asset map to provide a clear data panoramic view for subsequent standardized docking.

[0038] S232: Develop a unified data standard specification based on the sorting results;

[0039] S233: Design a data interface between the AI model and the mechanism model according to the data standard specification;

[0040] S234: Develop a data docking module based on the data interface design. The docking module is responsible for realizing data transmission and conversion between the AI model and the mechanism model;

[0041] S235: Integrate and test the developed data docking module with the AI model and the mechanism model, and optimize the data docking module according to the test results;

[0042] S236: First establish a monitoring mechanism for data coupling to monitor the status of data transmission, data quality, and model performance indicators in real time, and then set warning thresholds to be able to issue alarms in a timely manner when data transmission anomalies or data quality degradation problems occur.

[0043] As a preferred solution of the method for constructing an integrated surface and underground oil and gas field with a three-dimensional model fusion mechanism model according to the present invention, wherein: the specific steps of S31 are as follows:

[0044] S311: Conduct a comprehensive review of the existing simulation models and three-dimensional models;

[0045] S312: Preprocess the model data according to the sorting results;

[0046] S313: Design a coupling framework for the simulation model and the three-dimensional model based on the coupling objectives and model characteristics. First, determine the data transmission method between the models, then plan the data transmission frequency, determine whether it is real-time transmission or scheduled transmission according to the application scenario, and then design the coupling logical structure to clarify the responsibilities and interaction processes of the simulation model and the three-dimensional model during the coupling process;

[0047] S314: Develop a coupling interface and a data transmission module between the simulation model and the three-dimensional model based on the coupling framework design;

[0048] S315: Integrate the developed coupling interface and module with the simulation model and the three-dimensional model, and simulate different oil and gas field production scenarios to comprehensively verify the integrated model;

[0049] S316: Optimize and adjust the coupling system according to the model verification results;

[0050] S317: First establish a normalized maintenance mechanism to regularly check the operating status of the coupling interface and module and repair the faults that occur in a timely manner.

[0051] As a preferred solution of the method for constructing the integrated surface and subsurface of oil and gas fields with a three-dimensional model fusion mechanism model of the present invention, wherein: the specific steps of S32 are as follows:

[0052] S321: Select appropriate interactive interface technologies according to business requirements, data flow, and the technical architecture of the project;

[0053] S322: Formulate detailed specifications for the interactive interface, including URL design of the interface, data formats of requests and responses, and data transmission protocols;

[0054] S323: Design diverse interactive modes based on business requirements and user expectations;

[0055] S324: Present the designed interactive interface and modes in the form of a flowchart to clearly show the entire process of user operations, data transmission, and model responses;

[0056] S325: Develop the interactive interface and corresponding functional modules according to the design specifications and flowchart;

[0057] S326: Integrate and test the interactive interface and functional modules with the simulation model and three-dimensional model to simulate real business scenarios and check the stability and fluency of the entire interactive system.

[0058] As a preferred solution of the method for constructing the integrated surface and subsurface of oil and gas fields with a three-dimensional model fusion mechanism model of the present invention, wherein: the specific steps of S33 are as follows:

[0059] S331: Determine evaluation indicators based on data transmission delay, data packet loss rate, throughput, and connection stability;

[0060] S332: First, construct simulation models and three-dimensional models similar to actual applications to ensure that the data generation and processing logics of the models are consistent with real scenarios. Then, use professional network simulation software to simulate different network environments to test the performance of the protocol under different network conditions. After that, deploy data collection tools to collect various indicator data during the data transmission process;

[0061] S333: First, set different data volumes for transmission tests to evaluate the performance of the protocol under different data scales. Then, simulate multiple network scenarios such as high bandwidth and low latency, low bandwidth and high latency, and random packet loss to test the adaptability of the protocol. After that, simulate multiple users performing interactive operations simultaneously to test the performance of the protocol in concurrent scenarios;

[0062] S334: Execute tests in the built test environment according to the designed test cases. During the testing process, use data acquisition tools to collect data on various evaluation metrics in real time. For each test case, repeat the test multiple times to obtain stable and reliable data;

[0063] S335: First, identify the bottleneck links affecting protocol performance through analysis of the test data, and then study the correlation relationships between different factors;

[0064] S336: First, adjust the relevant parameters of the protocol according to the analysis results, and then compress the transmitted data to reduce the data transmission volume;

[0065] S337: Optimize and implement the protocol according to the relevant parameters of the protocol. After the implementation is completed, test again according to the test cases to verify the optimization effect, and compare the performance index data before and after optimization to evaluate the effectiveness of the optimization strategy;

[0066] S338: Establish a continuous monitoring mechanism to monitor the performance metrics of the protocol in real time.

[0067] Compared with the prior art:

[0068] In view of the closed-loop interaction problem between on-site facilities and virtual objects, the present invention realizes the integrated coupling between models (3D models, mechanism models, big data models, etc.) and between models and data (production data, simulation data), completes dynamic closed-loop, data support and real-time interaction in the virtual space, lays a technical foundation for realizing the simulation, prediction and optimization of virtual models for twin entities, and thus realizes the refined management and control of the entire oil and gas field production process. Based on this, it is possible to comprehensively and accurately simulate and optimize the entire oil and gas field production process. Detailed implementation manners

[0069] To make the objectives, technical solutions and advantages of the present invention clearer, the following will further describe the implementation manners of the present invention in detail.

[0070] The present invention provides a method for constructing an integrated oil and gas field surface and underground by fusing a 3D model with a mechanism model, including the following specific steps:

[0071] S1. Data transfer and coupling between mechanism models:

[0072] S11: Comprehensively sort out the existing mature commercial software models and mechanism models established based on the operating principles of equipment processes, and clarify the functions, application scopes and data characteristics of each model;

[0073] S12: Determine the boundary conditions between different mechanism models, clarify the starting and ending points of data transfer between models, and the physical meaning of the data;

[0074] S13: Develop standard formats and specifications for data input and output to ensure accurate transmission and understanding of data between different models.

[0075] S14: Based on the standardized data interfaces, establish a data transfer method between mechanism models to achieve information sharing and collaborative computing among models and achieve "underground - aboveground" integrated coupling.

[0076] The specific steps of S14 are as follows:

[0077] S141: After completing model sorting, boundary definition, and data standardization, design standardized data interfaces for different mechanism models according to the unified data format and specifications to ensure the universality of the data input and output interfaces of each model.

[0078] S142: Develop a detailed data transfer process to clarify the sequence and triggering conditions of data transfer between various mechanism models at different stages of oil and gas field production.

[0079] S143: After developing the detailed data transfer process, conduct joint debugging tests on different mechanism models. By simulating the actual production scenarios of oil and gas fields, check whether the data transfer between models is accurate and whether the coupling mechanism can operate normally.

[0080] S144: Establish a feedback and optimization mechanism. Collect the problems feedback by users during the use process, and through the analysis of model operation data, find out the deficiencies of the coupling mechanism, and continuously optimize the data interface, transmission middleware, and data transfer process to adapt to various changes and requirements in the oil and gas field production process.

[0081] S2: Coupling of AI models and mechanism models:

[0082] S21: Deeply analyze common AI algorithm types and their application modes in the oil and gas field, and summarize their advantages, disadvantages, and applicable scenarios.

[0083] The specific steps of S21 are as follows:

[0084] S211: Comprehensively collect AI algorithm materials currently applicable to the oil and gas field, and deeply understand the basic principles, mathematical models, applicable scenarios, advantages, and limitations of each algorithm.

[0085] S212: Sort out the application scenarios of AI algorithms in all aspects of oil and gas field exploration, development, production, and management; in the exploration link, AI algorithms can be used for seismic data interpretation to identify potential oil and gas reservoir locations; in the development stage, AI can be used to predict reservoir dynamics and optimize production plans; during the production process, it can be used for equipment fault diagnosis to ensure production continuity; at the management level, it can assist in production scheduling and resource allocation; through sorting out the application scenarios, the application methods and goals of AI algorithms in different business scenarios can be clarified;

[0086] S213: Study the combination methods of AI algorithms and mechanism models in different application scenarios;

[0087] S214: Based on the collected data and analysis results, select appropriate data sets and evaluation indicators to evaluate the performance and effects of different AI algorithms in oil and gas field application scenarios. The evaluation indicators include accuracy, recall rate, mean square error, and mean absolute error;

[0088] S215: Summarize the application modes of AI algorithms in the oil and gas field, generalize the experiences of successful cases and lessons of failed cases, analyze the applicable conditions, advantages, and limitations of different application modes, and provide references for the subsequent coupling of AI models and mechanism models;

[0089] S22: According to the characteristics of AI algorithms and mechanism models, establish multiple mechanism-AI model coupling modes and determine the hierarchical structures under different coupling modes;

[0090] The specific steps of S22 are as follows:

[0091] S221: First, widely collect and deeply study successful cases and practical experiences of the coupling of AI models and mechanism models in the oil and gas field and other industrial fields at home and abroad to analyze common coupling modes, and then, combined with the characteristics of oil and gas field production, including data characteristics, process flow, and business requirements, evaluate the applicability of each coupling mode; among them, the common coupling modes include series coupling mode, parallel coupling mode, and embedded coupling mode; in the series coupling mode, the output of the mechanism model is used as the input of the AI model, and the AI model further processes it to obtain the final result; in the parallel coupling mode, the mechanism model and the AI model run in parallel, and the results of the two are integrated through specific fusion strategies; in the embedded coupling mode, the AI model is embedded in specific links of the mechanism model to optimize and simulate local processes;

[0092] S222: Conduct in-depth communication with the oil and gas field production management team and engineering and technical personnel to clarify the specific goals to be achieved by the coupling of AI models and mechanism models;

[0093] S223: Based on the selected coupling mode, build the coupling hierarchical framework of the AI model and the mechanism model. If the series coupling mode is adopted, determine the sequence of the mechanism model and the AI model, and design the interfaces and formats for data transfer between the models. If the parallel coupling mode is adopted, plan the respective task divisions of the mechanism model and the AI model, as well as the methods and levels of result fusion. If the embedded coupling mode is adopted, determine the specific location and action mode of the AI model embedded in the mechanism model.

[0094] S224: Based on the built coupling hierarchical framework, select representative oil and gas field production scenarios and datasets, and conduct simulation experiments. Through the simulation experiments, verify the effectiveness and stability of the coupling mode and the hierarchical framework.

[0095] S225: First, establish a normalized evaluation mechanism, regularly collect the operation data and business feedback of the model, and then use appropriate evaluation indicators to quantitatively evaluate the performance of the coupling model. Once it is found that the model performance declines or fails to meet the business requirements, analyze the reasons in a timely manner and conduct targeted optimization of the coupling mode and the hierarchical framework.

[0096] S23: Develop a standardized docking method for mechanism-AI data coupling, standardize the processes, formats, and interfaces of data transmission, ensure that the mechanism model and the big data model can work together, and provide technical support for the construction of the full-process dynamic model of the oil and gas field.

[0097] The specific steps of S23 are as follows:

[0098] S231: Comprehensively sort out the data sources, types, formats, and storage methods of the AI model and the mechanism model, understand the characteristics of data dimensions, data volumes, and data update frequencies, and draw a data asset map to provide a clear data panoramic view for subsequent standardized docking.

[0099] S232: Based on the sorting results, formulate unified data standard specifications.

[0100] S233: According to the data standard specifications, design the data interface between the AI model and the mechanism model.

[0101] S234: Based on the data interface design, develop a data docking module, and the docking module is responsible for realizing the data transmission and conversion between the AI model and the mechanism model.

[0102] S235: Integrate and test the developed data docking module with the AI model and the mechanism model, and optimize the data docking module according to the test results.

[0103] S236: First, establish a monitoring mechanism for data coupling to monitor the status of data transmission, data quality, and model performance indicators in real time. Then, set warning thresholds so that alarms can be issued in a timely manner when data transmission anomalies or data quality degradation problems occur;

[0104] S3. Coupled dynamic interaction between the simulation model and the 3D model:

[0105] S31: Build a coupling framework between the simulation model and the 3D model, and determine the logical relationship and transmission path of data interaction. The simulation model includes a mechanism model and an AI data model;

[0106] The specific steps of S31 are as follows:

[0107] S311: Conduct a comprehensive review of the existing simulation model and 3D model;

[0108] S312: Preprocess the model data according to the review results;

[0109] S313: Based on the coupling objectives and model characteristics, design a coupling framework for the simulation model and the 3D model. First, determine the data transmission method between the models, then plan the data transmission frequency, determine whether it is real-time transmission or scheduled transmission according to the application scenario, and then design the coupling logical structure to clarify the responsibilities and interaction processes of the simulation model and the 3D model during the coupling process;

[0110] S314: Develop a coupling interface and a data transmission module between the simulation model and the 3D model according to the coupling framework design;

[0111] S315: Integrate the developed coupling interface and module with the simulation model and the 3D model, and simulate different oil and gas field production scenarios to comprehensively verify the integrated model;

[0112] S316: Optimize and adjust the coupling system according to the model verification results;

[0113] S317: First, establish a normalized maintenance mechanism, and then regularly check the running status of the coupling interface and module, and repair the faults that occur in a timely manner;

[0114] S32: Design an interaction interface for data between the models and formulate an interaction mode, including real-time data push and event-driven interaction, to ensure that data can be transmitted between the two models in a timely and accurate manner;

[0115] The specific steps of S32 are as follows:

[0116] S321: Select a suitable interaction interface technology according to the business requirements, data flow direction, and technical architecture of the project;

[0117] S322: Develop a detailed specification for the interaction interface, including the URL design of the interface, the data formats of requests and responses, and the data transmission protocol;

[0118] S323: Design diverse interaction modes based on business requirements and user expectations;

[0119] S324: Present the designed interaction interface and modes in the form of a flowchart to clearly show the entire process of user operations, data transmission, and model responses;

[0120] S325: Develop the interaction interface and corresponding functional modules according to the design specifications and flowchart;

[0121] S326: Integrate and test the interaction interface and functional modules with the simulation model and 3D model to simulate real business scenarios and check the stability and fluency of the entire interaction system;

[0122] S33: Evaluate the performance of the data transmission protocol, including transmission delay and data packet loss rate metrics, and improve the efficiency and stability of data transmission by optimizing protocol parameters to achieve visual interaction of the digital twin model;

[0123] The specific steps of S33 are as follows:

[0124] S331: Determine the evaluation metrics based on data transmission delay, data packet loss rate, throughput, and connection stability;

[0125] S332: First, build a simulation model and 3D model similar to the actual application to ensure that the data generation and processing logic of the model are consistent with the real scenario. Then, use professional network simulation software to simulate different network environments to test the performance of the protocol under different network conditions. After that, deploy data collection tools to collect various metric data during the data transmission process;

[0126] S333: First, set different data volumes for transmission testing to evaluate the performance of the protocol under different data scales. Then, simulate multiple network scenarios such as high bandwidth and low latency, low bandwidth and high latency, and random packet loss to test the adaptability of the protocol. After that, simulate multiple users interacting simultaneously to test the performance of the protocol in a concurrent scenario;

[0127] S334: Execute tests in the built test environment according to the designed test cases. During the test process, use data collection tools to collect the data of various evaluation metrics in real-time. For each test case, repeat the test multiple times to obtain stable and reliable data;

[0128] S335: First, find out the bottleneck links affecting the protocol performance through the analysis of test data, and then study the correlation between different factors;

[0129] S336: First, adjust the relevant parameters of the protocol according to the analysis results, and then compress the transmitted data to reduce the data transmission volume;

[0130] S337: Optimize and implement the protocol according to the relevant parameters of the protocol. After the implementation is completed, test again according to the test cases, verify the optimization effect, and compare the performance index data before and after the optimization to evaluate the effectiveness of the optimization strategy;

[0131] S338: Establish a continuous monitoring mechanism to monitor the performance indicators of the protocol in real time.

[0132] Although the present invention has been described above with reference to the embodiments, various improvements can be made thereto and components thereof can be replaced with equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the disclosed embodiments of the present invention can be combined with each other in any way, and the cases of these combinations are not exhaustively described in this specification only for the sake of saving space and resources. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. An integrated construction method for surface and underground of oil and gas fields based on a three-dimensional model fusion mechanism model, characterized in that The specific steps are as follows: S1, Data transfer and coupling between mechanism models: S11: Comprehensively sort out existing mature commercial software models and mechanism models established based on the operating principles of equipment processes, and clarify the functions, application scopes, and data characteristics of each model; S12: Determine the boundary conditions between different mechanism models, clarify the starting and ending points of data transfer between models, and the physical meaning of the data; S13: Develop standard formats and specifications for data input and output to ensure accurate transmission and understanding of data between different models; S14: Based on the standardized data interface, establish a data transfer method between mechanism models to achieve information sharing and collaborative operation between models, and achieve "underground - aboveground" integrated coupling; S2, Coupling of AI models and mechanism models: S21: Deeply analyze common types of AI algorithms and their application modes in the oil and gas field, and summarize their advantages, disadvantages, and applicable scenarios; S22: According to the characteristics of AI algorithms and mechanism models, establish multiple mechanism - AI model coupling modes, and determine the hierarchical structure under different coupling modes; S23: Develop a standardized docking method for mechanism - AI data coupling, standardize the process, format, and interface of data transmission, ensure that mechanism models and big data models can work together, and provide technical support for the construction of a dynamic model for the entire process of the oil and gas field; S3, Coupled dynamic interaction between simulation models and 3D models: S31: Build a coupling framework between simulation models and 3D models, determine the logical relationship and transmission path of data interaction, and the simulation models include mechanism models and AI data models; S32: Design an interaction interface for data between models, and develop interaction modes, including real - time data push and event - driven interaction, to ensure that data can be transferred between the two models in a timely and accurate manner; S33: Evaluate the performance of the data transmission protocol, including transmission delay and data packet loss rate indicators, and improve the efficiency and stability of data transmission by optimizing protocol parameters to achieve visual interaction of the digital twin model.

2. The integrated construction method of surface and underground of oil and gas fields for a three-dimensional model fusion mechanism model according to claim 1, characterized in that The specific steps of S14 are as follows: S141: After completing model sorting, boundary definition, and data standardization, design a standardized data interface for different mechanism models according to the unified data format and specification to ensure the generality of the data input and output interfaces of each model; S142: Develop a detailed data transfer process to clarify the sequence and triggering conditions of data transfer between various mechanism models at different stages of oil and gas field production; S143: After developing a detailed data transfer process, conduct joint debugging tests on different mechanism models. By simulating the actual production scenario of the oil and gas field, check whether the data transfer between models is accurate and whether the coupling mechanism can operate normally; S144: Establish a feedback and optimization mechanism, collect problems feedback by users during the use process, and find out the deficiencies of the coupling mechanism through the analysis of model operation data. Continuously optimize the data interface, transmission middleware, and data transfer process to adapt to various changes and requirements in the oil and gas field production process.

3. The method for constructing an integrated surface and subsurface of an oil and gas field for a three-dimensional model fusion mechanism model according to claim 1, wherein, The specific steps of S21 are as follows: S211: Comprehensively collect AI algorithm materials currently applicable to the oil and gas field domain, and deeply understand the basic principles, mathematical models, applicable scenarios, advantages, and limitations of each algorithm; S212: Sort out the application scenarios of AI algorithms in all aspects of oil and gas field exploration, development, production, and management; In the exploration link, AI algorithms can be used for seismic data interpretation to identify potential oil and gas reservoir locations; In the development stage, AI can be used to predict reservoir dynamics and optimize production plans; During the production process, it can be used for equipment fault diagnosis to ensure production continuity; At the management level, it can assist in production scheduling and resource allocation; By sorting out the application scenarios, the application methods and goals of AI algorithms in different business scenarios can be clarified; S213: Study the combination methods of AI algorithms and mechanism models in different application scenarios; S214: Based on the collected materials and analysis results, select appropriate data sets and evaluation indicators to evaluate the performance and effects of different AI algorithms in oil and gas field application scenarios. The evaluation indicators include accuracy, recall rate, mean square error, and mean absolute error; S215: Summarize the application modes of AI algorithms in the oil and gas field domain, generalize the experiences of successful cases and lessons of failed cases, analyze the applicable conditions, advantages, and limitations of different application modes, and provide references for the subsequent coupling of AI models and mechanism models.

4. The method for constructing an integrated surface and subsurface of an oil and gas field for a three-dimensional model fusion mechanism model according to claim 1, wherein, The specific steps of S22 are as follows: S221: First, widely collect and deeply study successful cases and practical experiences of the coupling of AI models and mechanism models in the oil and gas field domain and other industrial fields to analyze common coupling modes. Then, combined with the characteristics of oil and gas field production, including data characteristics, technological processes, and business requirements, evaluate the applicability of each coupling mode; Among them, the common coupling modes include series coupling mode, parallel coupling mode, and embedded coupling mode; In the series coupling mode, the output of the mechanism model is used as the input of the AI model, and the AI model further processes it to obtain the final result; In the parallel coupling mode, the mechanism model and the AI model run in parallel, and the results of the two are integrated through specific fusion strategies; In the embedded coupling mode, the AI model is embedded in specific links of the mechanism model to optimize and simulate local processes; S222: Conduct in-depth communication with the oil and gas field production management team and engineering and technical personnel to clarify the specific goals to be achieved by the coupling of AI models and mechanism models; S223: According to the selected coupling mode, build a coupling hierarchical framework for AI models and mechanism models. If the series coupling mode is adopted, determine the sequence of the mechanism model and the AI model, and design the interfaces and formats for data transfer between the models; If the parallel coupling mode is adopted, plan the respective task divisions of the mechanism model and the AI model, as well as the methods and levels of result fusion; If the embedded coupling mode is adopted, determine the specific location and action mode of the AI model embedded in the mechanism model; S224: Based on the established coupling hierarchical framework, select representative oil and gas field production scenarios and datasets to conduct simulation experiments. Through the simulation experiments, verify the effectiveness and stability of the coupling mode and hierarchical framework; S225: First, establish a normalized evaluation mechanism, regularly collect the operation data and business feedback of the model, and then use appropriate evaluation indicators to quantitatively evaluate the performance of the coupling model. Once it is found that the model performance deteriorates or fails to meet business requirements, analyze the reasons in a timely manner and conduct targeted optimization of the coupling mode and hierarchical framework.

5. A method for constructing an integrated on - surface and underground oil and gas field based on a three - dimensional model fusion mechanism model according to claim 1, characterized in that, The specific steps of S23 are as follows: S231: Comprehensively sort out the data sources, types, formats, and storage methods of the AI model and the mechanism model, understand the characteristics of data dimensions, data volume, and data update frequency, and draw a data asset map to provide a clear data panoramic view for subsequent standardized docking; S232: According to the sorting results, formulate a unified data standard specification; S233: Design a data interface between the AI model and the mechanism model according to the data standard specification; S234: Develop a data docking module according to the data interface design. The docking module is responsible for realizing data transmission and conversion between the AI model and the mechanism model; S235: Integrate and test the developed data docking module with the AI model and the mechanism model, and optimize the data docking module according to the test results; S236: First, establish a monitoring mechanism for data coupling to monitor the status of data transmission, data quality, and model performance indicators in real time, and then set warning thresholds to be able to issue alarms in a timely manner when data transmission anomalies and data quality degradation problems occur.

6. The method for constructing an integrated surface and subsurface of an oil and gas field for a three-dimensional model fusion mechanism model according to claim 1, characterized in that, The specific steps of S31 are as follows: S311: Comprehensively sort out the existing simulation models and 3D models; S312: Preprocess the model data according to the sorting results; S313: Based on the coupling objectives and model characteristics, design a coupling framework for the simulation model and the 3D model. First, determine the data transmission method between the models, then plan the data transmission frequency, determine whether it is real-time transmission or scheduled transmission according to the application scenario, and then design the coupling logic structure to clarify the responsibilities and interaction processes of the simulation model and the 3D model in the coupling process; S314: Develop a coupling interface and a data transmission module between the simulation model and the 3D model according to the coupling framework design; S315: Integrate the developed coupling interface and module with the simulation model and the 3D model, and simulate different oil and gas field production scenarios to comprehensively verify the integrated model; S316: Optimize and adjust the coupling system according to the model verification results; S317: First, establish a normalized maintenance mechanism, regularly check the operation status of the coupling interface and module, and repair the faults that occur in a timely manner.

7. A method for constructing an integrated surface and subsurface of an oil and gas field for a three-dimensional model fusion mechanism model according to claim 1, characterized in that, The specific steps of S32 are as follows: S321: Select appropriate interactive interface technologies according to business requirements, data flow, and the technical architecture of the project; S322: Formulate detailed specifications for the interactive interface, including the URL design of the interface, the data formats of requests and responses, and the data transmission protocol; S323: Design diverse interactive modes based on business requirements and user expectations; S324: Present the designed interaction interface and mode in the form of a flowchart to clearly show the entire process of user operations, data transmission, and model responses; S325: Develop the interaction interface and corresponding functional modules according to the design specifications and flowchart; S326: Integrate and test the interaction interface and functional modules with the simulation model and 3D model to simulate real business scenarios and check the stability and fluency of the entire interaction system.

8. The method for constructing an integrated surface and underground oil and gas field of a three-dimensional model fusion mechanism model according to claim 1, characterized in that, The specific steps of S33 are as follows: S331: Determine the evaluation metrics based on data transmission latency, packet loss rate, throughput, and connection stability; S332: First, construct a simulation model and 3D model similar to the actual application to ensure that the data generation and processing logic of the model are consistent with the real scenario. Then, use professional network simulation software to simulate different network environments to test the performance of the protocol under different network conditions. After that, deploy data collection tools to collect various metric data during the data transmission process; S333: First, set different data volumes for transmission testing to evaluate the performance of the protocol under different data scales. Then, simulate multiple network scenarios such as high bandwidth and low latency, low bandwidth and high latency, and random packet loss to test the adaptability of the protocol. After that, simulate multiple users performing interactive operations simultaneously to test the performance of the protocol in a concurrent scenario; S334: Execute the tests in the established test environment according to the designed test cases. During the testing process, use data collection tools to collect the data of various evaluation metrics in real time. For each test case, repeat the test multiple times to obtain stable and reliable data; S335: First, identify the bottleneck links affecting the protocol performance through the analysis of the test data, and then study the correlation between different factors; S336: First, adjust the relevant parameters of the protocol according to the analysis results, and then perform compression processing on the transmitted data to reduce the data transmission volume; S337: Implement the optimization of the protocol according to the relevant parameters of the protocol. After the implementation is completed, perform the tests again according to the test cases to verify the optimization effect, and compare the performance metric data before and after optimization to evaluate the effectiveness of the optimization strategy; S338: Establish a continuous monitoring mechanism to monitor the performance metrics of the protocol in real time.