Digital twinborn construction method and system of oil and gas pipeline and medium

Abstract

The invention relates to the technical field of oil and gas pipelines, in particular to a digital twin construction method and system of an oil and gas pipeline and a storage medium. The method comprises the following steps: acquiring an oil and gas pipeline three-dimensional model and an oil and gas pipeline sensing data set; performing data integration on the oil and gas pipeline sensing data set to obtain a pipeline monitoring data block set; carrying out microstructure analysis on the oil and gas pipeline to obtain a pipeline microstructure feature map; performing material model construction on the oil and gas pipeline based on the pipeline microstructure feature map to obtain a pipeline material digital mapping model; performing stress distribution simulation on the oil and gas pipeline based on the pipeline material digital mapping model to obtain a pipeline material stress distribution diagram; and performing multi-physics field coupling simulation on the oil and gas pipeline and the geology to obtain a geological environment dynamic interaction model. The real state of the oil and gas pipeline and the surrounding environment thereof can be reflected in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas pipelines, and particularly to a method, system, and storage medium for constructing a digital twin of an oil and gas pipeline. Background Art

[0002] Oil and gas pipelines usually pass through various complex geological environments, such as mountains, deserts, swamps, etc. These environments have a significant impact on the stress distribution and deformation characteristics of the pipelines. For example, in mountainous areas, pipelines need to adapt to steep terrain changes and geological activities, which can easily cause the pipelines to bear different stresses and deformations in different sections. In addition, the performance of pipelines also varies under different seasons and climate changes. For example, low temperatures in winter can easily increase the brittleness of materials, while high temperatures in summer can easily cause thermal expansion. Due to the variability of geological environments, it is difficult to accurately predict the operating state of pipelines through simple models. In terms of health state assessment, traditional oil and gas pipeline assessment methods mainly rely on empirical judgment and discrete monitoring data. This method often lacks a dynamic and accurate assessment of the overall performance of the pipeline system. For example, during the long-term operation of pipelines, defects such as internal corrosion and cracks will gradually develop, and traditional monitoring methods are difficult to capture these changes in real time. Summary of the Invention

[0003] Based on this, it is necessary for the present invention to provide a method, system, and medium for constructing a digital twin of an oil and gas pipeline to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for constructing a digital twin of an oil and gas pipeline includes the following steps:

[0005] Step S1: Obtain a three-dimensional model of the oil and gas pipeline and a perception data set of the oil and gas pipeline; integrate the perception data set of the oil and gas pipeline to obtain a pipeline monitoring data block set;

[0006] Step S2: Conduct a microscopic structure analysis of the oil and gas pipeline to obtain a microscopic structure feature map of the pipeline; construct a material model of the oil and gas pipeline based on the microscopic structure feature map of the pipeline to obtain a pipeline material digital mapping model; simulate the stress distribution of the oil and gas pipeline based on the pipeline material digital mapping model to obtain a pipeline material stress distribution map;

[0007] Step S3: Conduct a multi-physical field coupling simulation of the oil and gas pipeline and the geology to obtain a dynamic interaction model of the geological environment; perform physical inversion on the environment between the oil and gas pipeline and the geology based on the dynamic interaction model of the geological environment to obtain pipeline geological environment reconstruction data;

[0008] Step S4: Based on the stress distribution map of the pipeline material, establish a damage mechanism model for the oil and gas pipeline to obtain a pipeline damage mapping model; based on the pipeline monitoring data block set and the pipeline damage mapping model, conduct a risk assessment on the oil and gas pipeline to obtain an oil and gas pipeline risk index set;

[0009] Step S5: Based on the reconstructed data of the pipeline geological environment and the oil and gas pipeline risk index set, conduct real-time mapping on the three-dimensional model of the oil and gas pipeline to obtain a digital twin of the oil and gas pipeline.

[0010] By obtaining the three-dimensional model of the oil and gas pipeline and the perception data set, the present invention is no longer limited to the difficulties in sensor deployment and maintenance in remote mountainous areas and complex terrains, and can collect data on the pipeline and its surrounding environment more comprehensively. Through data integration, the problems of scattered data and difficult unified processing in traditional methods are solved, and the data processing efficiency is improved. Through microstructure analysis, the understanding of pipeline materials is deepened. Through stress distribution simulation, a stress distribution map of the pipeline material is obtained. Compared with traditional methods, it can more accurately simulate the stress distribution of the pipeline under different geological environments and climatic conditions. Through multi-physical field coupling simulation, the variability and complexity of the geological environment are fully considered, and the interaction between the pipeline and the geology can be more realistically reflected, improving the accuracy of geological environment simulation. Through physical inversion, the reconstructed data of the pipeline geological environment is obtained, making up for the deficiency of traditional methods in accurately predicting the operating state of the pipeline. Through damage mechanism modeling, the damage development law of the pipeline under different stress conditions can be analyzed in depth, which helps to detect potential damage hazards in advance. By combining the pipeline monitoring data block set and the pipeline damage mapping model for risk assessment, a dynamic and accurate assessment of the overall performance of the pipeline system is realized. Compared with traditional methods that rely on empirical judgment and discrete monitoring data, it can more comprehensively identify the risk factors of the pipeline. By constructing a digital twin of the oil and gas pipeline, the real state of the pipeline and its surrounding environment can be reflected in real time.

[0011] Preferably, the present invention also provides a digital twin construction system for an oil and gas pipeline, which is used to execute the digital twin construction method for an oil and gas pipeline as described above. The digital twin construction system for an oil and gas pipeline includes:

[0012] A data acquisition module, which is used to obtain the three-dimensional model of the oil and gas pipeline and the oil and gas pipeline perception data set; integrate the oil and gas pipeline perception data set to obtain a pipeline monitoring data block set;

[0013] A structure analysis module, which is used to conduct microstructure analysis on the oil and gas pipeline to obtain a pipeline microstructure feature map; establish a material model for the oil and gas pipeline based on the pipeline microstructure feature map to obtain a pipeline material digital mapping model; conduct stress distribution simulation on the oil and gas pipeline based on the pipeline material digital mapping model to obtain a stress distribution map of the pipeline material;

[0014] A geological inversion module, which is used to perform multi-physical field coupling simulation on the oil and gas pipeline and the geology to obtain a dynamic interaction model of the geological environment; and perform physical inversion on the environment between the oil and gas pipeline and the geology based on the dynamic interaction model of the geological environment to obtain pipeline geological environment reconstruction data;

[0015] A risk assessment module, which is used to build a damage mechanism model for the oil and gas pipeline based on the pipeline material stress distribution map to obtain a pipeline damage mapping model; and perform risk assessment on the oil and gas pipeline based on the pipeline monitoring data block set and the pipeline damage mapping model to obtain an oil and gas pipeline risk index set;

[0016] A real-time mapping module, which is used to perform real-time mapping on the three-dimensional model of the oil and gas pipeline based on the pipeline geological environment reconstruction data and the oil and gas pipeline risk index set to obtain a digital twin of the oil and gas pipeline.

[0017] In the present invention, the data acquisition module automatically acquires and integrates the oil and gas pipeline data, improving the data collection efficiency and ensuring the accuracy and integrity of the data. The structural analysis module delves into the microscopic level, precisely constructs the material model and simulates the stress distribution, making the pipeline structural analysis more meticulous. The geological inversion module accurately reconstructs the pipeline geological environment through multi-physical field coupling simulation and physical inversion, enhancing the pipeline's adaptability to complex geological conditions and reducing geological risks. The risk assessment module comprehensively considers the pipeline material stress and damage mechanism, comprehensively evaluates the pipeline risk, and makes the maintenance resource allocation more scientific and reasonable. The real-time mapping module dynamically updates the digital twin, reflecting the pipeline status in real time.

[0018] Preferably, a computer-readable storage medium stores a method for constructing a digital twin of an oil and gas pipeline as described above and can be loaded and executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Other features, objects, and advantages of the present invention will become more apparent by reading the following detailed description with reference to the accompanying drawings:

[0020] Figure 1 The flowchart of the steps of a method for constructing a digital twin of an oil and gas pipeline according to an embodiment is shown.

[0021] Figure 2 The detailed flowchart of step S26 according to an embodiment is shown.

[0022] Figure 3 The detailed flowchart of step S48 according to an embodiment is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The technical method of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative work belong to the scope of protection of the present invention.

[0024] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0025] It should be understood that although terms such as "first" and "second" may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed associated items.

[0026] To achieve the above object, please refer to Figures 1 to 3 , the present invention provides a method for constructing a digital twin of an oil and gas pipeline, including the following steps:

[0027] Step S1: Obtain the three-dimensional model of the oil and gas pipeline and the perception data set of the oil and gas pipeline; integrate the perception data set of the oil and gas pipeline to obtain a pipeline monitoring data block set;

[0028] Step S2: Analyze the microstructure of the oil and gas pipeline to obtain a pipeline microstructure feature map; construct a material model of the oil and gas pipeline based on the pipeline microstructure feature map to obtain a pipeline material digital mapping model; simulate the stress distribution of the oil and gas pipeline based on the pipeline material digital mapping model to obtain a pipeline material stress distribution map;

[0029] Step S3: Perform a multi-physical field coupling simulation on the oil and gas pipeline and the geology to obtain a geological environment dynamic interaction model; perform physical inversion on the environment between the oil and gas pipeline and the geology based on the geological environment dynamic interaction model to obtain pipeline geological environment reconstruction data;

[0030] Step S4: Based on the stress distribution map of the pipeline material, establish a damage mechanism model for the oil and gas pipeline to obtain a pipeline damage mapping model; based on the pipeline monitoring data block set and the pipeline damage mapping model, conduct a risk assessment on the oil and gas pipeline to obtain an oil and gas pipeline risk index set;

[0031] Step S5: Based on the reconstructed data of the pipeline geological environment and the oil and gas pipeline risk index set, conduct real-time mapping on the three-dimensional model of the oil and gas pipeline to obtain a digital twin of the oil and gas pipeline.

[0032] In this embodiment, the AutoCAD software is used to construct a three-dimensional model of the pipeline according to the design drawings, and the sensing data of the pipeline is collected in real time through a variety of sensors (such as pressure sensors, temperature sensors, vibration sensors) installed on the pipeline. Next, the sensing data set is integrated to obtain a pipeline monitoring data block set. Then, the image processing toolbox of MATLAB is used to analyze the pipeline surface image, extract microscopic structure features such as grain size, distribution and defects, and generate a pipeline microscopic structure feature map. Based on the microscopic structure feature map, the finite element analysis software ANSYS is used to construct a material model, input the physical parameters of the material (such as elastic modulus, yield strength, etc.), and establish a digital mapping model of the pipeline material. On this basis, stress distribution simulation is carried out to calculate the stress distribution of the pipeline under different working conditions, and a stress distribution map of the pipeline material is obtained. Then, the COMSOL Multiphysics software is used to conduct a multi-physical field coupling simulation of the oil and gas pipeline and the geology to obtain a geological environment dynamic interaction model. Then, based on this model, physical inversion is carried out, and the GeoProbe software is used to combine the seismic wave velocity data and resistivity data on site to invert the reconstructed data of the pipeline geological environment. Based on the stress distribution map of the pipeline material, damage mechanism modeling is carried out, and a custom damage model is written using MATLAB to simulate the damage development process of the pipeline under different stress conditions to obtain a pipeline damage mapping model. Finally, combining the pipeline monitoring data block set and the pipeline damage mapping model, a risk assessment is carried out on the oil and gas pipeline, comprehensively considering factors such as the stress state, damage degree and operating environment of the pipeline, and calculating the risk index set of the pipeline. And apply the reconstructed data of the pipeline geological environment and the risk index set to the three-dimensional model of the oil and gas pipeline, and use the Unity software for real-time dynamic visualization rendering to generate a digital twin of the oil and gas pipeline.

[0033] Preferably, step S1 includes the following steps:

[0034] Step S11: Obtain the design drawings of the oil and gas pipeline, and based on the design drawings of the oil and gas pipeline, construct a three-dimensional model of the oil and gas pipeline to obtain a three-dimensional model of the oil and gas pipeline;

[0035] Specifically, complete design drawings of the oil and gas pipeline can be obtained from the pipeline design unit. These drawings include detailed information such as the pipeline dimensions, materials, elbow positions, and support arrangements. Import the design drawings into a 3D modeling software in DWG or PDF format. For example, use the "Insert" function in Autodesk Inventor to import the DWG file as a reference base map. According to the dimensional data in the drawings, use the "Sketch" function of the software to draw the basic shape of the pipeline. For example, draw a pipeline main body with a diameter of 1000 mm and a length of 100 m. Then use the "Extrusion" command to convert the sketch into a 3D solid model. According to the detailed information of elbows, flanges, valves, etc. in the drawings, use commands such as "Revolve" and "Cut" in the software to add these features. For example, for a 90-degree elbow, use the "Revolve" command to create an arc segment with a radius of 500 mm on the pipeline main body. After the model is created, set the material properties for the pipeline model. Select the "Materials" tab, select the same material as the actual pipeline from the material library, such as API 5L X65 steel pipe, and set parameters such as its density and elastic modulus. Through the above steps, a 3D model of the oil and gas pipeline can be obtained.

[0036] Step S12: Perform multi-modal data acquisition on the oil and gas pipeline to obtain an initial oil and gas pipeline perception data set, where the multi-modal data acquisition includes pipeline internal and external pressure acquisition, pipeline surface and internal temperature acquisition, pipeline internal fluid flow velocity and flow rate acquisition, and gas leakage detection data acquisition;

[0037] Specifically, pressure sensors can be installed at key positions of the pipeline, such as the inlet, outlet, and intermediate monitoring points of the pipeline. For example, a pressure sensor of model Rosemount 3051 is selected, with a measurement range of 0 - 1000 psi and an accuracy of ±0.05%. The sensor data is transmitted to the data acquisition system in real time through a wireless data transmission module. Temperature sensors are installed on the surface and inside of the pipeline. For the surface temperature sensor, an infrared thermal imager such as FLIR E60 can be used, with a temperature measurement range of -20 to 650 °C and a resolution of up to 0.1 °C. For the internal temperature sensor, a thermocouple such as a K-type thermocouple can be used and installed on the inner wall of the pipeline, and the temperature data is recorded through a data collector. Ultrasonic flow meters and vortex flow meters are used to measure the flow velocity and flow rate of the fluid in the pipeline. For example, an ultrasonic flow meter of model Siemens SITRANS FUS1000 is selected, with a measurement range of 0 - 10 m / s and an accuracy of ±1%. The flow meter is installed on the straight section of the pipeline, and the flow velocity and flow rate data are recorded through the data acquisition system. A gas leak detector such as the Honeywell GDS-2000 series is installed, with a detection range of 0 - 100% LEL (lower explosion limit). The detector is installed near the flange connections and valves of the pipeline, and the leak data is transmitted to the monitoring system in real time through a wireless signal. Through the above steps, an initial oil and gas pipeline perception dataset can be obtained.

[0038] Step S13: Perform time synchronization calibration on the initial oil and gas pipeline perception dataset to obtain the oil and gas pipeline perception dataset;

[0039] Specifically, the initial oil and gas pipeline perception dataset can be imported into data processing software such as MATLAB or the Pandas library in Python. For example, data such as pipeline pressure, temperature, and flow velocity are stored in different data files respectively, such as CSV format files. Check whether the timestamp formats in each data file are consistent. If there are inconsistent situations, use the timestamp conversion function in the data processing software for unification. For example, use the datetime function in MATLAB to convert the timestamp to a unified format. Use the time synchronization algorithm in the data processing software to perform synchronization calibration on each data file. For example, in the Pandas library of Python, the merge function can be used to merge multiple data files according to the timestamp, and at the same time set the how='outer' parameter to retain the data at all time points. During the merging process, if there are timestamp mismatches, interpolation methods such as linear interpolation or nearest neighbor interpolation can be used for data filling. Through the above steps, the oil and gas pipeline perception dataset can be obtained.

[0040] Step S14: Divide the monitoring areas of the oil and gas pipeline based on the three-dimensional model of the oil and gas pipeline to obtain the monitoring area model of the oil and gas pipeline;

[0041] Specifically, the three-dimensional model of the oil and gas pipeline can be imported into professional CAD software, such as AutoCAD or SolidWorks. Open the model file, carefully analyze the structural layout of the pipeline, and identify the key parts and functional areas of the pipeline, such as the starting point, ending point, elbows, valves, and supports. According to the structural characteristics of the pipeline and the actual monitoring requirements, use the drawing tools of the CAD software to divide the monitoring areas of the pipeline. For example, divide the pipeline into several segments with a length of 100 meters, and each segment is used as a monitoring area. During the division process, geometric figure tools such as straight lines and arcs can be used to draw the boundary lines of the monitoring areas on the three-dimensional model, and a unique number or identifier, such as "Area 1", "Area 2", etc., is assigned to each area. In the CAD software, export the divided monitoring areas as a new model file, such as DWG or STL format. For example, use the "Export" function of AutoCAD to export each monitoring area as a DWG file respectively, and include the area number in the file name, such as "Area 1.dwg", "Area 2.dwg", etc. Associate the monitoring area model with the corresponding perception data. For example, in the data management system, create a database table to associate and store the number of each monitoring area with the corresponding perception data file path. Through the above steps, the monitoring area model of the oil and gas pipeline can be obtained.

[0042] Step S15: Perform regional data chunking on the perception data set of the oil and gas pipeline according to the monitoring area model of the oil and gas pipeline to obtain the pipeline monitoring data block set.

[0043] Specifically, the oil and gas pipeline perception dataset can be imported into data processing software, such as the Pandas library in Python. For example, data such as pipeline pressure, temperature, and flow rate are stored in a large CSV file, which contains columns such as timestamps, sensor locations, and measurement values. The oil and gas pipeline monitoring area model is imported into the data processing software. For example, the geopandas library in Python is used to read the geographical information file (such as GeoJSON format) of the monitoring area, which contains the boundary coordinates and numbers of each monitoring area. According to the sensor location information and the boundary coordinates of the monitoring area, the perception data is matched with the corresponding monitoring area. For example, in Pandas, the merge function is used to spatially associate the sensor location with the monitoring area model to obtain the monitoring area number to which each data point belongs. Then, the data is grouped according to the monitoring area number, and the groupby function is used to divide the dataset into multiple data blocks, with each data block corresponding to a monitoring area. The chunked data is exported as independent files. For example, the to_csv function in Pandas is used to export the data block of each monitoring area as a CSV file, and the area number is included in the file name, such as "area1_data.csv", "area2_data.csv", etc. Through the above steps, a pipeline monitoring data block set can be obtained.

[0044] By using the oil and gas pipeline design drawings to construct a 3D model, the present invention can accurately reflect the design parameters and structural layout of the pipeline, ensuring a high degree of consistency between the model and the actual pipeline. Through the monitoring area division, refined division can be carried out according to the different functions and key parts of the pipeline. Through multi-modal data acquisition, various key parameters and potential risk factors during pipeline operation can be captured in all directions. Through time synchronization calibration, the corresponding relationship of different modal data at the same time point can be ensured to be accurate. Through regional data chunking, the data is divided according to different regions of the pipeline. This makes data processing more efficient, facilitates parallel processing and analysis of data in each region, improves the speed and efficiency of data processing, and also provides convenience for personalized analysis of different regions, helping to quickly locate problem and risk areas.

[0045] Preferably, step S2 includes the following steps:

[0046] Step S21: Collect remote sensing images of the oil and gas pipeline to obtain remote sensing images of the oil and gas pipeline;

[0047] Specifically, an appropriate remote sensing platform can be selected according to the geographical location and monitoring requirements of the oil and gas pipeline. For example, a drone equipped with a high-resolution optical camera can be selected for low-altitude remote sensing image acquisition. The drone model can be DJI Phantom 4 Pro. Before the drone takes off, use flight planning software (such as DJI Flight Planner) to plan the flight route. According to the orientation and length of the oil and gas pipeline, set the flight altitude to 100 meters and the flight speed to 5 m / s to ensure that the drone can cover the entire pipeline area and capture sufficient overlapping images for subsequent image stitching and analysis. On the premise of ensuring flight safety, start the drone for the flight mission. The drone automatically flies along the preset route and captures the surface images of the pipeline and its surrounding areas. For example, during the flight, the drone takes a photo every 5 seconds to record information such as the landform, vegetation, and buildings along the pipeline. After the flight is completed, import the image data captured by the drone into image processing software, such as Pix4Dmapper or Agisoft Metashape. Use the automatic stitching function of the software to stitch multiple images into a complete remote sensing image, and at the same time perform distortion correction and color balance processing. Through the above steps, a clear remote sensing image of the oil and gas pipeline can be obtained.

[0048] Step S22: Obtain the oil and gas pipeline monitoring area model, and identify and label the surface-underground regions of the oil and gas pipeline monitoring area model based on the remote sensing image of the oil and gas pipeline to obtain the oil and gas pipeline zoning model;

[0049] Specifically, the remote sensing images of oil and gas pipelines can be imported into a Geographic Information System (GIS) software, such as ArcGIS or QGIS. At the same time, import the geographic information files of the oil and gas pipeline monitoring area model (such as in DWG or GeoJSON format) to ensure that the remote sensing images and the monitoring area model are superimposed and analyzed in the same coordinate system. In the GIS software, use the feature characteristics of the remote sensing images to identify the surface areas. For example, use image classification tools to divide the surface areas along the pipeline into different feature types, such as bare land, vegetation, water bodies, buildings, etc., according to the spectral and texture characteristics of the surface. The supervised classification method can be adopted. First, select a small number of training samples on the image, and then use classification algorithms (such as support vector machines or random forests) to classify the entire image. Combine the 3D model of the oil and gas pipeline and the monitoring area model to label the underground pipeline area. For example, in the GIS software, according to the pipeline's alignment and burial depth information, draw the contour line of the underground pipeline on the monitoring area model, and label the attributes such as the burial depth range and material of the pipeline. The 3D function of the GIS software can be used to superimpose the underground pipeline on the surface image in a transparent or semi-transparent manner. Integrate the surface area identification results and the underground area labeling information to generate an oil and gas pipeline zoning model. For example, in the GIS software, create a new layer, merge the vector data of the surface area and the underground area into this layer, and assign a unique identifier to each area, such as "Surface Area 1", "Underground Pipeline Area 2", etc.

[0050] Step S23: Perform hierarchical structure segmentation on the oil and gas pipeline zoning model to obtain a set of surface pipeline structure model blocks and a set of underground pipeline structure model blocks;

[0051] Specifically, the oil and gas pipeline zoning model can be imported into 3D modeling software such as SolidWorks or Autodesk Inventor. Open the model file to ensure that all parts of the model (such as surface pipelines, underground pipelines, supports, etc.) have been correctly imported and are displayed in the software interface. In the 3D modeling software, select a suitable segmentation tool for hierarchical structure segmentation. For example, in SolidWorks, the "Split Line" or "Split Surface" tool can be used to segment the model. First, select the "Split Line" tool, and then draw one or more split lines on the model interface to separate the surface pipeline from the underground pipeline. Perform the split operation along the drawn split line to divide the oil and gas pipeline zoning model into two parts: the surface pipeline structure and the underground pipeline structure. For example, in SolidWorks, after clicking the "Split" button, the software will automatically split the model into two independent model block sets according to the split line. After the split is completed, these two model block sets can be viewed and edited separately. Export the obtained surface pipeline structure model block set and underground pipeline structure model block set as independent file formats such as STL or STEP. For example, in Autodesk Inventor, select the "Export" function, export the surface pipeline structure model block set as an STL file named "Surface Pipeline Structure.stl", and export the underground pipeline structure model block set as another STL file named "Underground Pipeline Structure.stl". Through the above steps, the surface pipeline structure model block set and the underground pipeline structure model block set are finally obtained.

[0052] Step S24: Perform surface image acquisition on the corresponding pipeline area of the oil and gas pipeline according to the surface pipeline structure model block set to obtain the surface pipeline surface image set;

[0053] Specifically, a suitable image acquisition device can be selected according to the size and surface characteristics of the surface pipeline. For example, an industrial camera such as Vision Research Phantom Flex4K can be used. Set appropriate parameters in the image acquisition device. For example, set the camera resolution to 4096×2160 pixels, the frame rate to 30 frames per second, the aperture size to f / 5.6, the exposure time to 1 / 100 second, and the ISO value to 400. Install the image acquisition device on a stable bracket and aim it at the surface area of the surface pipeline for shooting. For example, place the camera above the pipeline, keep a vertical distance of about 50 cm from the pipeline surface, and continuously shoot along the pipeline's direction to ensure that the entire surface pipeline area is covered. During the shooting process, a light source device (such as an LED lamp) can be used to evenly illuminate the pipeline surface. Store the acquired surface pipeline surface images in the computer to obtain the surface pipeline surface image set.

[0054] Step S25: Collect underground soil parameters for the corresponding pipeline areas of the oil and gas pipelines according to the underground pipeline structure model block set to obtain the underground pipeline soil environment parameter set;

[0055] Specifically, appropriate measuring equipment can be selected according to the types of soil parameters to be collected. For example, to measure the temperature, humidity, and chemical composition of the soil, the following equipment can be used: Temperature sensor: such as the Thermistor temperature sensor, with a measurement range of -40 to 125 °C and an accuracy of ±0.1 °C. Humidity sensor: such as the Vaisala HUMICAP humidity sensor, with a relative humidity measurement range of 0 to 100% and an accuracy of ±2%. Soil chemical composition analyzer: such as the X-ray fluorescence spectrometer (XRF), which can quickly analyze the content of various elements in the soil, such as iron, manganese, copper, etc. According to the distribution of the underground pipeline structure model block set, measuring points are arranged along the pipeline. For example, a measuring point is arranged every 10 meters to ensure that the entire underground area of the pipeline can be covered. At each measuring point, according to the buried depth of the pipeline, a drill is used to extract soil samples, and the drilling depth should match the buried depth of the pipeline. For example, if the buried depth of the pipeline is 2 meters, the drilling depth should also be 2 meters. At each measuring point, the corresponding measuring equipment is used to collect soil parameters. For example, the temperature sensor and humidity sensor are inserted into the drill hole to record the temperature and humidity data of the soil. At the same time, the extracted soil samples are put into the XRF analyzer for the analysis of the soil chemical composition to obtain the content data of various elements in the soil. The collected soil parameter data is recorded and integrated. For example, a data recorder or a laptop is used to record the temperature, humidity, and chemical composition data of each measuring point, and these data are sorted into a unified database file, such as an Excel table or a CSV file. In the database, a unique identifier is assigned to each measuring point, such as "Measuring Point 1", "Measuring Point 2", etc., and the location information of the measuring point (such as longitude and latitude coordinates) is associated with the corresponding soil parameter data. Through the above steps, the underground pipeline soil environment parameter set can be obtained.

[0056] Step S26: Conduct a microscopic structure analysis of the oil and gas pipelines based on the surface pipeline surface image set and the underground pipeline soil environment parameter set to obtain the pipeline microscopic structure feature map;

[0057] Specifically, for the detailed implementation process of this embodiment, please refer to the sub-steps of Step S26.

[0058] Step S27: Construct a material model for the oil and gas pipelines based on the pipeline microscopic structure feature map to obtain the pipeline material digital mapping model, and simulate the stress distribution of the oil and gas pipelines based on the pipeline material digital mapping model to obtain the pipeline material stress distribution map.

[0059] Through surface - subsurface area identification and annotation, the present invention can intuitively and efficiently obtain surface environment information around the pipeline, such as topography and vegetation cover. This helps to adopt different monitoring strategies and methods for different regions, improving the pertinence and effectiveness of monitoring. Through surface image acquisition, information such as the appearance characteristics, corrosion conditions, and damage marks of the surface part of the pipeline can be detailedly recorded. Through subsurface soil parameter acquisition, the obtained subsurface pipeline soil environment parameter set covers key parameters such as soil temperature, humidity, and chemical composition. This provides basic information for the corrosion protection, stability analysis, and environmental adaptability assessment of subsurface pipelines, helping to more accurately understand the environmental conditions where the subsurface pipelines are located. Through microstructure analysis, various factors of the surface and subsurface parts of the pipeline can be comprehensively considered, such as the corrosion condition on the surface and the corrosiveness of the subsurface soil. The pipeline microstructure feature map shows the internal microstructure features of the pipeline material, such as grain size, distribution, and defects. By constructing a digital mapping model of the pipeline material, the actual microstructure and mechanical properties of the pipeline material can be more accurately reflected. Compared with traditional empirical models or simplified models, the reliability and prediction accuracy of the model are improved. Through stress distribution simulation, the stress state and distribution law of the pipeline under different working conditions can be more realistically reflected.

[0060] Preferably, step S26 includes the following steps:

[0061] Step S261: Extract the pipeline surface texture from each surface pipeline surface image in the surface pipeline surface image set to obtain the surface pipeline surface texture feature set;

[0062] Specifically, the surface pipeline surface image can be imported into image - processing software, such as the Image Processing Toolbox of MATLAB or OpenCV. According to the characteristics of the pipeline surface texture, a suitable texture extraction method is selected. For example, the gray - level co - occurrence matrix (GLCM) method can be used to extract texture features. GLCM can describe the gray - level relationship between pixel pairs in an image, such as contrast, uniformity, and energy. In the image - processing software, calculate the GLCM for each surface pipeline surface image and extract the corresponding texture features. For example, in MATLAB, use the graycomatrix function to calculate the GLCM of the image, and then use the graycoprops function to extract texture features. Assume that the offset parameter of GLCM is set as [0 1; - 1 1; - 1 0; - 1 - 1], indicating considering the pixel - pair relationship in four directions, and calculate the texture feature values such as contrast, uniformity, and energy for each image. Organize the extracted texture feature values into a data set, that is, the surface pipeline surface texture feature set. For example, create a table, take the texture feature values of each image as a row of data, and the column names include feature names such as image number, contrast, uniformity, and energy. Save this data set as a CSV file.

[0063] Step S262: Use the surface pipeline surface texture feature set to perform texture mapping reconstruction on the surface pipeline structure model block set to obtain the surface pipeline surface structure mapping set;

[0064] Specifically, the surface pipeline structure model block set can be imported into 3D modeling software such as 3ds Max or Blender. At the same time, the surface pipeline surface texture feature set is imported into the software to ensure that each model block corresponds to the corresponding texture feature data. For example, in 3ds Max, the "Import" function can be used to import the model file and the texture feature data file in CSV format. In the 3D modeling software, create texture mapping for each surface pipeline structure model block. According to the data in the texture feature set, select an appropriate texture map and map it to the surface of the model block. For example, use the "UVW Map" function in 3ds Max to create UV coordinates for the model block, and then select a texture map in the "Material Editor" and apply it to the material of the model block. Adjust the parameters of the texture mapping. For example, the scaling, rotation, and translation parameters of the texture can be adjusted to adapt to the size and shape of the model block. In Blender, the "Scale", "Rotation", and "Translation" parameters of the texture node can be adjusted in the "Shader Editor" to achieve an ideal texture mapping effect. After completing the texture mapping reconstruction, export the reconstructed surface pipeline surface structure model block as an independent file format such as OBJ or FBX format to form the surface pipeline surface structure mapping set. For example, in 3ds Max, select the "Export" function, export each model block as an OBJ file, and include the model block number or location information in the file name, such as "SurfaceBlock1.obj", "SurfaceBlock2.obj".

[0065] Step S263: Collect the service life of the oil and gas pipeline to obtain the pipeline service life data;

[0066] Specifically, the pipeline service life data can be obtained from the pipeline maintenance records, operation logs, or asset management databases.

[0067] Step S264: Collect historical meteorological data for the corresponding pipeline area of the oil and gas pipeline according to the underground pipeline structure model block set to obtain the underground pipeline environmental meteorological record set;

[0068] Specifically, the source of the historical meteorological data can be determined. Obtain the historical meteorological data of the pipeline along the line area from meteorological bureaus, meteorological data providers, or online meteorological databases.

[0069] Step S265: Collect the burial depths of each underground pipeline structure model block in the underground pipeline structure model block set to obtain the underground pipeline burial depth distribution set;

[0070] Specifically, an appropriate tool can be selected for collecting the burial depth data. For example, a ground penetrating radar (GPR) device such as the Noggin 250MHz GPR from Sensors&Software can be used. This device can penetrate the soil and detect the burial depth position of the underground pipeline. The GPR device is arranged along the pipeline for on-site data collection. For example, the GPR device is scanned at intervals of 1 meter along the pipeline's alignment, and the burial depth data of each scan point is recorded. During the collection process, ensure that the antenna of the device is perpendicular to the ground to obtain accurate burial depth information. The collected GPR data is imported into data processing software such as GPR-SLICE or EKKO_Project. Using the signal processing function of the software, the data is denoised, gain adjusted, and inverted to extract the burial depth information of the underground pipeline. For example, in GPR-SLICE, by setting appropriate gain and filtering parameters, the reflection signal of the pipeline can be clearly identified and its burial depth value can be measured. The processed burial depth data is organized into a data set, namely the underground pipeline burial depth distribution set. For example, a table is created, with the burial depth data of each model block as a row of data, and the column names including information such as the model block number, position coordinates, and burial depth value.

[0071] Step S266: Based on the pipeline service life data, the underground pipeline environmental meteorological record set, the underground pipeline burial depth distribution set, and the underground pipeline structure model block set, conduct material aging simulation on the corresponding pipeline area of the oil and gas pipeline to obtain the pipeline aging characteristic data set;

[0072] Specifically, a suitable material aging simulation software or tool can be selected. For example, a finite element analysis software (such as ABAQUS) can be used in combination with a material aging model for simulation. The pipeline service life data, the underground pipeline environmental meteorological record set, the underground pipeline burial depth distribution set, and the underground pipeline structure model block set are imported into the simulation software. For example, in ABAQUS, a new analysis model is created, the three-dimensional geometric model of the pipeline is associated with the corresponding material model, and the service life data, meteorological data, and burial depth data are imported as input parameters for the simulation. According to the characteristics of the pipeline material, a suitable material aging model is selected, and the corresponding parameters are set. For example, for steel pipe materials, a corrosion aging model can be selected, the corrosion rate parameter is set to 0.01 mm / a (millimeters per year), and the variation law of the corrosion rate is adjusted according to conditions such as temperature and humidity in the meteorological data. At the same time, considering the influence of the burial depth on material aging, a relationship function between the burial depth and the corrosion rate is set, such as the corrosion rate decreasing with the increase of the burial depth. The simulation software is started for material aging simulation. The software will calculate the material aging characteristics of the pipeline under different service lives, environmental conditions, and burial depth conditions, such as corrosion depth, strength attenuation, and toughness reduction, based on the input data and the set model parameters. For example, during the simulation, the software will simulate the corrosion process of the pipeline under different years, different temperature and humidity conditions, and calculate the aging characteristic data of each model block. After the simulation is completed, the obtained material aging characteristic data is exported as a data set, that is, the pipeline aging characteristic data set. For example, a table is created, and the aging characteristic data of each model block is used as a row of data, and the column names include information such as model block number, service life, corrosion depth, and strength attenuation rate. The data set is saved as an Excel file.

[0073] Step S267: Micro-corrosion morphology reconstruction is performed on the underground pipeline structure model block set according to the pipeline aging characteristic data set to obtain the underground pipeline micro-feature set;

[0074] Specifically, the Materialise 3-matic software can be used for micro-corrosion morphology reconstruction. The pipeline aging characteristic dataset is imported into the software, and the underground pipeline structure model block set is loaded. For example, in Materialise 3-matic, use the "Import" function to import the aging characteristic data file in CSV format, and at the same time load the three-dimensional model file of the pipeline (such as STL format). According to the aging characteristic data, set the reconstruction parameters of the micro-corrosion morphology. For example, according to the corrosion depth data, set the size and shape parameters of the corrosion pits. Assuming the corrosion depth is 0.5 mm, the radius of the corrosion pit can be set to 0.1 mm and the depth to 0.5 mm, and the distribution density of the corrosion pits is adjusted according to the variation law of the corrosion rate. Use the simulation function of the software to reconstruct the micro-corrosion morphology of the underground pipeline structure model block. For example, in Materialise 3-matic, use the "Simulation" function to simulate the corrosion process. The software will generate corresponding micro-features such as corrosion pits and cracks on the pipeline model according to the set parameters. After the reconstruction is completed, the reconstructed micro-features can be viewed and edited to ensure that they match the actual aging situation. Export the reconstructed micro-corrosion morphology data as the underground pipeline micro-feature set.

[0075] Step S268: Perform feature fusion on the surface pipeline surface structure mapping set and the underground pipeline micro-feature set to obtain the pipeline micro-structure feature map.

[0076] Specifically, the ITK-SNAP software can be used for feature fusion. The surface pipeline surface structure mapping set and the underground pipeline micro-feature set are imported into the software. For example, in ITK-SNAP, use the "Open" function to import the surface pipeline surface structure mapping image (such as PNG format) and the underground pipeline micro-feature data file (such as VTK format). According to the characteristics of the mapping set and the feature set, set the parameters of feature fusion. For example, select the fusion algorithm as "Alpha Blending", and set the fusion weight parameter to 0.5, indicating that the surface mapping image and the micro-feature image each account for 50% of the weight in the fusion result. At the same time, set the contrast and brightness parameters of the image. Use the fusion function of the software to fuse the surface pipeline surface structure mapping set and the underground pipeline micro-feature set. For example, in ITK-SNAP, click the "Fusion" button, and the software will fuse the two sets of data according to the set parameters to generate the pipeline micro-structure feature map.

[0077] Through texture extraction, the present invention can capture in detail the subtle texture changes on the surface of the pipeline, such as corrosion spots, cracks, etc. Through texture mapping reconstruction, the texture features on the pipeline surface can be combined with the three-dimensional structure to achieve intuitive visualization of the pipeline surface structure. This makes the state and features of the pipeline surface clearer and easier to understand, facilitating observation and analysis by technicians. By collecting multi-dimensional data such as the service life data of the pipeline, the underground pipeline environmental meteorological record set, and the underground pipeline burial depth distribution set, the environmental conditions and historical usage of the underground pipeline can be comprehensively understood. Through material aging simulation, the performance change laws of the pipeline material during long-term use can be predicted, such as the attenuation trends of strength, toughness, corrosion resistance, etc. Through microscopic corrosion morphology reconstruction, the microscopic corrosion features inside the pipeline can be detailedly displayed, such as corrosion pits, crack propagation, etc. Through feature fusion, the microscopic structural features of the pipeline can be comprehensively presented, including the surface texture of the ground and the internal corrosion morphology underground.

[0078] Preferably, step S3 includes the following steps:

[0079] Step S31: Collect soil components along the oil and gas pipeline to obtain data on the composition of the soil components along the line, and model the stress-strain relationship of the data on the composition of the soil components along the line to obtain a soil mechanical property model along the line;

[0080] Specifically, a soil drilling device can be used for soil sample collection. For example, a portable soil drill, such as the soil drilling kit of Eijkelkamp, can be selected to arrange sampling points along the oil and gas pipeline, with a sampling point set every 50 meters to ensure coverage of the entire length of the pipeline. At each sampling point, the soil drill is used to drill soil samples at different depths, including surface soil (0 - 30 cm), middle soil (30 - 60 cm), and deep soil (60 - 90 cm). The collected soil samples are placed in sealed sample bags, and the sampling location and depth information of each sample are recorded. The soil samples are sent to the laboratory for composition analysis. An X-ray fluorescence spectrometer (XRF) is used to analyze the elemental content in the soil, such as silicon, aluminum, iron, etc.; a particle size analyzer is used to determine the particle size distribution of the soil; a soil pH meter is used to measure the acidity and alkalinity of the soil, etc. For example, the Malvern Mastersizer 2000 particle size analyzer with a measurement range of 0.01 to 2000 microns can accurately determine the particle size distribution of the soil. According to the soil composition analysis results, a stress-strain relationship model of the soil is established using finite element analysis software (such as ANSYS). For example, a suitable soil constitutive model, such as the Mohr-Coulomb model, is selected, and parameters such as the internal friction angle and cohesion of the soil are input, and these parameters can be obtained according to the results of the direct shear test in the laboratory. In ANSYS, a three-dimensional model of the soil is created, and different stress conditions are applied for simulation to obtain the stress-strain relationship curve of the soil, thereby obtaining a soil mechanical property model along the line.

[0081] Step S32: Conduct resistivity measurement on the buried area of the oil and gas pipeline to obtain formation resistivity distribution data, and perform three-dimensional interpolation on the formation resistivity distribution data to obtain a formation electrical property model;

[0082] Specifically, a geological resistivity measurement instrument, such as the ABEM SAS1000 bipole resistivity measurement system, can be used to conduct resistivity measurement. Electrodes are arranged in the buried area of the oil and gas pipeline, and the Wenner four-electrode method is adopted for resistivity measurement. For example, electrodes are arranged along the pipeline route, with one electrode set every 10 meters to ensure uniform distance between electrodes. Connect the electrodes to the measurement instrument, start the measurement program, and record the resistivity values at each measurement point. For example, set the electrode spacing to 10 meters and the measurement depth to 30 meters, and record the resistivity data at different depths. Import the measured resistivity data into data processing software, such as Surfer or GMS (Geostatistical Modeling Software). Use the three-dimensional interpolation function of the software to perform interpolation on the resistivity data and generate a three-dimensional model of the formation resistivity distribution. For example, in Surfer, select the Kriging interpolation method, set the interpolation parameters, such as the variogram model as the spherical model and the interpolation grid as 1 m × 1 m × 1 m, to obtain a three-dimensional visualization map of the formation resistivity distribution. Based on the three-dimensional resistivity distribution model and combined with geological background information, establish a formation electrical property model. For example, according to the high and low resistivity values, different formation structures are identified. High resistivity areas may be sand layers, and low resistivity areas may be mud layers or aquifers. Combine these electrical properties with the geological structure to generate a formation electrical property model.

[0083] Step S33: Conduct seismic wave measurement along the oil and gas pipeline to obtain formation seismic wave velocity data, and perform ray tracing inversion on the formation seismic wave velocity data to obtain a formation elastic property model;

[0084] Specifically, a seismic wave measuring device can be used for seismic wave measurement, such as the SIR-3000 seismic reflector of Geometrics. Seismic wave survey lines are arranged along the oil and gas pipeline, and the common midpoint (CMP) measurement method is adopted. For example, survey lines are arranged along the pipeline direction, with a source point and a receiving point set every 10 meters to ensure that the survey lines cover the entire length of the pipeline. A seismic wave is excited using a source device (such as a hammering or explosive source), and the reflected wave signal is received by a geophone. For example, the source energy is set to 1000 joules, and the geophone spacing is 5 meters, and the seismic wave reflection data at different depths are recorded. The measured seismic wave data are imported into seismic data processing software, such as SeisPro or OpendTect. An inversion algorithm (such as tomographic inversion) is used to invert the seismic wave velocity data to obtain the seismic wave velocity distribution of the formation. For example, in SeisPro, inversion parameters, such as the initial velocity model and the number of inversion iterations, are set to obtain the P-wave velocity and S-wave velocity distribution maps of the formation. Based on the seismic wave velocity distribution data and combined with geological background information, a formation elastic characteristic model is established. For example, according to the relationship between the P-wave velocity and the S-wave velocity, parameters such as the elastic modulus (such as Young's modulus and Poisson's ratio) and density of the formation are calculated. These parameters are combined with the formation structure to generate a formation elastic characteristic model.

[0085] Step S34: Conduct hydrogeological monitoring on the observation area of the oil and gas pipeline to obtain the dynamic data of the groundwater level, and simulate the water flow field based on the dynamic data of the groundwater level to obtain a groundwater flow field model;

[0086] Specifically, hydrographic monitoring equipment such as groundwater level gauges and flow meters can be used to monitor the groundwater level and flow velocity in the observation area. For example, select the Solinst Levelogger groundwater level gauge with a measurement accuracy of ±0.01 m, which can record the changes in the groundwater level in real time; select the Hach FlowTracker flow meter with a measurement range of 0.1 to 10 m / s, which can accurately measure the flow velocity of groundwater. Arrange monitoring points in the observation area of the oil and gas pipeline, and set up groundwater level gauges and flow meters. For example, set up a monitoring point every 50 m. Start the monitoring equipment and collect the groundwater level and flow velocity data in real time. For example, set the sampling frequency of the groundwater level gauge to once per hour and the sampling frequency of the flow meter to once per minute, and record the time series data of the groundwater level and flow velocity. Import the collected hydrographic data into hydrographic simulation software such as MODFLOW or Visual MODFLOW. Use the hydrographic model function of the software to process and analyze the dynamic groundwater level data and identify the recharge and discharge areas of groundwater. Then conduct a water flow field simulation, set the boundary conditions, initial conditions and hydrographic parameters (such as permeability coefficient, storage coefficient, etc.) of the model, and simulate the flow process of groundwater in the observation area. For example, in MODFLOW, set the permeability coefficient to 0.01 m / day and the storage coefficient to 0.1 to simulate the flow direction and velocity distribution of groundwater. Generate a groundwater flow field model according to the simulation results.

[0087] Step S35: Perform electro-mechanical coupling on the formation electrical property model and the soil mechanical property model to obtain the electro-mechanical coupling field data around the pipeline, and perform solid-liquid coupling on the formation elastic property model and the groundwater flow field model to obtain the solid-liquid coupling field data around the pipeline;

[0088] Specifically, COMSOL Multiphysics can be used for electro-mechanical coupling. Import the formation electrical property model and soil mechanical property model into COMSOL. Set the physical conditions for electro-mechanical coupling in COMSOL. For example, select the "electro-mechanical coupling" module to couple the electric field and mechanical field. Set the coupling parameters, such as the relationship between the electric field strength and stress, and the influence coefficient of the electric field on soil mechanical properties. For example, assume that when the electric field strength is 1000 V / m, the elastic modulus of the soil increases by 10%, then set the corresponding coupling relationship in the software. Start COMSOL for electro-mechanical coupling analysis. The software will calculate the electro-mechanical coupling field data around the pipeline according to the set coupling conditions and model parameters, including electric field distribution, stress distribution, and displacement distribution, etc. For example, during the analysis, the software will simulate the influence of the electric field on soil stress and the feedback effect of soil stress on the electric field distribution to obtain detailed data of the coupling field. For example, export data such as electric field strength, stress distribution, and displacement distribution, and include position coordinates and time information in the file to form an electro-mechanical coupling field dataset around the pipeline. Import the formation elastic characteristic model and groundwater flow field model into the coupling analysis software. For example, import the seismic wave velocity distribution data of the elastic characteristic model and the flow velocity distribution data of the groundwater flow field model into OpenGeoSys. Set the physical conditions for solid-liquid coupling in the coupling analysis software. For example, select the "solid-liquid coupling" module to couple the formation deformation and groundwater flow. Set the coupling parameters, such as the relationship between the permeability coefficient and formation deformation, and the influence coefficient of groundwater flow on formation stress. For example, assume that when the formation deforms by 1 cm, the permeability coefficient increases by 5%, then set the corresponding coupling relationship in the software. Start the coupling analysis software for solid-liquid coupling analysis. The software will calculate the solid-liquid coupling field data around the pipeline according to the set coupling conditions and model parameters, including formation deformation, groundwater flow velocity, and pressure distribution, etc., export data such as formation deformation amount, groundwater flow velocity, and pressure distribution, and include position coordinates and time information in the file to form a solid-liquid coupling field dataset around the pipeline.

[0089] Step S36: Perform multi-field coupling on the oil and gas pipeline and the geology based on the electro-mechanical coupling field data and solid-liquid coupling field data around the pipeline to obtain a dynamic interaction model of the geological environment;

[0090] Specifically, ANSYS Multiphysics or COMSOL Multiphysics can be used for multi-field coupling. The electro-mechanical coupling field data and solid-liquid coupling field data around the pipeline are imported into the multi-field coupling analysis software. For example, in COMSOL Multiphysics, the electric field distribution, stress distribution data of the electro-mechanical coupling field, and the formation deformation, groundwater flow velocity, and pressure distribution data of the solid-liquid coupling field are imported. The physical conditions and boundary conditions for multi-field coupling are set in the software. For example, the "Multi-physics coupling" module is selected to couple the electric field, mechanical field, and fluid field. The coupling parameters are set, such as the influence coefficient of the electric field on formation deformation and the resistance coefficient of formation deformation to fluid flow. At the same time, the boundary conditions are set, such as the fixed boundary of the pipeline and the inflow and outflow boundaries of groundwater. The multi-field coupling analysis software is started for coupling analysis. The software will calculate the multi-field coupling effect between the oil and gas pipeline and the geology according to the set coupling conditions and model parameters, including the interaction and influence of the electric field, mechanical field, and fluid field. For example, during the analysis process, the software will simulate the influence of the electric field on formation deformation and fluid flow, as well as the feedback effects of formation deformation and fluid flow on the electric field and mechanical field, to obtain a dynamic interaction model of the geological environment.

[0091] Step S37: Physically invert the environment between the oil and gas pipeline and the geology based on the dynamic interaction model of the geological environment to obtain the reconstructed data of the pipeline geological environment.

[0092] Specifically, physical inversion software such as GeoProbe of Landmark or Echos of Paradigm can be used for inversion analysis. The dynamic interaction model of the geological environment and relevant geophysical observation data are imported into the inversion analysis software. For example, in GeoProbe, the dynamic interaction model of the geological environment and geophysical observation data such as seismic wave velocity data and resistivity data collected on site are imported. The parameters and algorithms for physical inversion are set in the software. For example, the inversion algorithm is selected as "least squares inversion" or "Bayesian inversion", and the initial model parameters, inversion iteration times, regularization parameters, etc. are set. At the same time, the objective function and constraint conditions for inversion are set, such as minimizing the error between the observed data and the model prediction data and satisfying the constraints of geological prior information. The physical inversion software is started for inversion analysis. The software will invert the dynamic interaction model of the geological environment according to the set inversion parameters and algorithms to obtain the reconstructed data of the pipeline geological environment.

[0093] Through stress-strain relationship modeling, the present invention can accurately describe the deformation and bearing capacity of soil under different stress conditions. The formation electrical property characteristic model obtained through three-dimensional interpolation can display in detail the electrical distribution characteristics of the formation, providing a basis for identifying different lithologies, aquifers, etc. in the formation; the formation elastic characteristic model obtained through ray tracing inversion can accurately reflect the elastic parameters of the formation, such as elastic modulus, Poisson's ratio, etc. The groundwater flow field model obtained through groundwater flow field simulation can dynamically display the flow state and distribution characteristics of groundwater. This helps to analyze the potential impact of groundwater on oil and gas pipelines, such as the change in pipeline buoyancy and soil erosion caused by the change in groundwater level. Through multi-field coupling, the interaction of multiple physical fields in the pipeline surrounding environment is fully considered, such as the coupling effect of electric field, force field, flow field, etc. Through physical inversion, the geological environment characteristics around the pipeline can be finely reconstructed, including formation structure, lithology distribution, groundwater flow, etc.

[0094] Preferably, step S4 includes the following steps:

[0095] Step S41: Identify the stress concentration areas in the pipeline material stress distribution diagram to obtain the pipeline stress hot spot distribution diagram;

[0096] Specifically, the stress concentration areas can be identified by MATLAB's Image Processing Toolbox or OpenCV. Import the pipeline material stress distribution diagram into the image processing software. For example, in MATLAB, use the imread function to read the image file of the stress distribution diagram, such as PNG or JPEG format, and convert it into a grayscale image. Preprocess the stress distribution diagram, including operations such as denoising and contrast enhancement. For example, use the medfilt2 function in MATLAB for median filtering denoising; then use the imadjust function to adjust the contrast of the image to make the stress concentration areas more obvious. Use image segmentation and edge detection algorithms to identify the stress concentration areas. For example, in MATLAB, use the edge function for edge detection to identify the edge areas in the stress distribution diagram; then use the regionprops function to calculate the area and shape characteristics of each edge area, and identify the areas with smaller area and irregular shape as the stress concentration areas. Assume that the area threshold of the stress concentration area is set to 100 pixels and the shape factor threshold is set to 0.5, and identify the areas that meet the conditions. Mark the identified stress concentration areas on the stress distribution diagram to generate the pipeline stress hot spot distribution diagram. For example, use the imshow function in MATLAB to display the stress distribution diagram, and use the rectangle function to draw a marking box in the stress concentration area to distinguish different stress hot spot areas with different colors.

[0097] Step S42: Based on the pipeline stress hot spot distribution map, conduct fatigue damage prediction on the oil and gas pipeline to obtain pipeline fatigue damage prediction data;

[0098] Specifically, fatigue analysis software such as FE-SAFE or nCode DesignLife can be used to conduct fatigue damage prediction. Import the pipeline stress hot spot distribution map and the fatigue characteristic data of the pipeline material into the fatigue analysis software. For example, in FE-SAFE, import the stress data of the stress hot spot distribution map, as well as material data such as the fatigue limit and fatigue life curve of the pipeline material. Set the parameters and conditions for fatigue analysis in the software. For example, select the fatigue analysis method as the "Miner's rule" or the "Paris formula", and set the number of cycles of fatigue analysis, load spectrum parameters, etc. At the same time, set the evaluation criteria for fatigue damage. For example, when the fatigue damage reaches 1, it indicates that the pipeline fails. Start the fatigue analysis software to conduct fatigue damage prediction. The software will calculate the fatigue damage values and fatigue lives of the pipeline in different stress concentration areas according to the stress hot spot distribution map and material characteristics. For example, during the analysis process, the software will simulate the fatigue crack propagation process in the stress concentration area under cyclic loading, and calculate the fatigue damage value and remaining fatigue life of each area. Organize the data obtained from fatigue damage prediction into a table or chart form, such as an Excel table or a fatigue damage distribution map. For example, create a table listing the fatigue damage values, fatigue lives, and failure probabilities of each stress concentration area; draw a fatigue damage distribution map, using different colors to represent areas with different fatigue damage degrees.

[0099] Step S43: Conduct electrochemical impedance spectroscopy testing on the oil and gas pipeline to obtain pipeline corrosion rate data;

[0100] Specifically, an electrochemical workstation can be used to perform electrochemical impedance spectroscopy (EIS) tests. For example, the Reference 3000 electrochemical workstation from Gamry Instruments can be used. A small sample is taken from the oil and gas pipeline and cut into a specimen with standard dimensions, such as a disc with a diameter of 10 mm and a thickness of 5 mm. The surface of the specimen is polished smooth. After cleaning and drying, it is used as the working electrode. At the same time, a platinum sheet is selected as the counter electrode, and a saturated calomel electrode (SCE) is used as the reference electrode. They are immersed in the electrolyte, such as 3.5% NaCl solution, together with the working electrode to simulate the corrosion conditions of the pipeline in the actual environment. Set the parameters for the EIS test in the software of the electrochemical workstation. For example, set the amplitude of the alternating current signal to 10 millivolts (mV), the frequency range to be from 0.01 hertz (Hz) to 100 kilohertz (kHz), and the scanning step size to be 10 points / decade. At the same time, set the potential window to be from -0.5 volts (V) to 0.5 volts (V) to ensure that the measured electrochemical impedance signal is within the effective range. Start the electrochemical workstation to perform the EIS test. The device will apply an alternating current signal to the working electrode and measure its impedance response. During the test, the device will automatically record the impedance values and phase angles at different frequencies to generate an impedance spectrum diagram, such as a Nyquist plot and a Bode plot. For example, in the Nyquist plot, the impedance spectrum appears as a semicircle, and the diameter of the semicircle is related to the corrosion rate. The larger the diameter, the faster the corrosion rate. According to the EIS test results, calculate the corrosion rate data of the pipeline. For example, by fitting the semicircle of the Nyquist plot, the corrosion impedance value (Rct) is obtained, and then the corrosion rate is calculated according to the relationship formula between Rct and the corrosion rate (v), which is v = k / Rct (where k is a constant). Record the calculated corrosion rate data in a data table, such as an Excel spreadsheet.

[0101] Step S44: Perform corrosion kinetics simulation on the oil and gas pipeline based on the pipeline corrosion rate data to obtain pipeline corrosion damage prediction data;

[0102] Specifically, CorrSim or Corrosion Engineering Suite can be used to predict and simulate corrosion damage. The corrosion rate data of the pipeline and the corrosion characteristic data of the pipeline material are imported into the corrosion kinetics simulation software. The parameters and conditions for corrosion kinetics simulation are set in the software. For example, the corrosion kinetics model is selected as "Tafel extrapolation method" or "Butler-Volmer equation", and the simulation time range, temperature change range, etc. are set. At the same time, the evaluation criteria for corrosion damage are set. For example, when the corrosion depth reaches a certain proportion of the pipeline wall thickness, it is regarded as damage. The corrosion kinetics simulation software is started for simulation. The software will calculate the corrosion damage value and corrosion depth of the pipeline under different time and temperature conditions according to the corrosion rate data and material characteristics. For example, during the simulation process, the software will simulate the rate change of the corrosion reaction and calculate the corrosion depth and corrosion damage degree of the pipeline at different time points. The data obtained from the corrosion kinetics simulation are sorted into table or chart forms, such as Excel tables or corrosion damage distribution maps. For example, create a table listing data such as corrosion damage values, corrosion depths, and damage probabilities under different time and temperature conditions; draw a corrosion damage distribution map, using different colors to represent areas with different corrosion damage degrees.

[0103] Step S45: Conduct a fracture toughness test on the oil and gas pipeline material to obtain the pipeline fracture toughness data, and based on the pipeline fracture toughness data, perform a crack propagation simulation on the oil and gas pipeline to obtain the pipeline crack propagation prediction data;

[0104] Specifically, a universal material testing machine and a fracture toughness testing device can be used for fracture toughness testing. For example, an Instron 5982 universal material testing machine is used to sample from oil and gas pipeline materials and prepare standard fracture toughness specimens, such as compact tension (CT) specimens or three-point bending (SEB) specimens. For example, a CT specimen with dimensions of 50 mm × 10 mm × 2 mm is prepared, and a crack is prefabricated in the middle of the specimen with a crack length of 5 mm. The specimen is installed on the fracture toughness testing device, a tensile or bending load is applied, and the load and displacement data during crack propagation are recorded until the specimen fractures. According to the test results, the fracture toughness value (KIC) of the pipeline material is calculated. For example, the formula KIC = (Pmax × Y) / (W × B) is used, where Pmax is the maximum load, Y is the crack length, W is the specimen width, and B is the specimen thickness. The calculated fracture toughness data are recorded in a data table, such as an Excel spreadsheet. Finite element analysis software is used for crack propagation simulation, such as ABAQUS or ANSYS. The three-dimensional model of the pipeline material is imported into the simulation software, and the crack propagation simulation parameters are set. For example, the initial position and length of the crack are set, the critical stress intensity factor (Kc) for crack propagation is set according to the fracture toughness data, and a crack propagation model is selected, such as the Paris formula or the COD (crack opening displacement) model. The simulation software is started for crack propagation simulation. The software will calculate the propagation path and speed of the crack under different load conditions according to the set parameters and material properties. For example, in ABAQUS, the "crack propagation analysis" function is used to simulate the crack propagation process in the pipeline material, and the crack propagation length and time data are recorded. The crack propagation data obtained from the simulation are organized into a table or chart form, such as an Excel spreadsheet or a crack propagation curve graph. For example, a table is created to list the crack propagation length and time data under different load conditions; a crack propagation curve graph is plotted with the time axis as the horizontal axis and the crack length as the vertical axis.

[0105] Step S46: Perform a fatigue-corrosion interaction simulation on the pipeline fatigue damage prediction data and the pipeline corrosion damage prediction data to obtain pipeline damage coupling data;

[0106] Specifically, COMSOL Multiphysics or ANSYS Multiphysics can be used to simulate the fatigue-corrosion interaction. The fatigue damage prediction data and corrosion damage prediction data of the pipeline are imported into the coupling analysis software. For example, in COMSOL, the fatigue damage data (such as fatigue life, damage degree) and corrosion damage data (such as corrosion rate, corrosion depth) are imported, and the parameters and conditions for the fatigue-corrosion interaction simulation are set in the software. For example, the coupling model is selected as the "fatigue-corrosion interaction model", and the coupling parameters are set, such as the influence coefficient of corrosion on fatigue life, the influence coefficient of fatigue on corrosion rate, etc. At the same time, the time range of the simulation, load spectrum parameters, etc. are set. The coupling analysis software is started to perform the fatigue-corrosion interaction simulation. The software will calculate the damage coupling effect of the pipeline under the combined action of fatigue and corrosion according to the set parameters and models. For example, during the simulation, the software will simulate the influence of corrosion on the fatigue crack propagation and the acceleration effect of the fatigue load on the corrosion rate, and obtain the damage coupling data of the pipeline. The damage coupling data obtained from the coupling simulation is organized into a table or chart form, such as an Excel table or a damage coupling distribution map. For example, a table is created to list the damage coupling values, failure probabilities, etc. under different times, loads, and corrosion conditions.

[0107] Step S47: Based on the pipeline crack propagation prediction data and the pipeline damage coupling data, the damage evolution of the oil and gas pipeline is carried out to obtain the pipeline damage evolution characteristic diagram, and the damage mapping modeling is carried out according to the pipeline damage evolution characteristic diagram to obtain the pipeline damage mapping model;

[0108] Specifically, ABAQUS or ANSYS can be used for damage evolution analysis. Import the pipeline crack propagation prediction data and pipeline damage coupling data into the finite element analysis software, and load the three-dimensional geometric model of the pipeline. Set the parameters and conditions for damage evolution analysis in the software. For example, select the damage evolution model as the "continuum damage mechanics model" and set the evolution parameters such as the damage growth rate and damage accumulation coefficient. At the same time, set the time step and total time of the simulation. Start the finite element analysis software for damage evolution analysis. The software will calculate the damage evolution process of the pipeline under the action of crack propagation and damage coupling according to the set parameters and model. For example, in ABAQUS, use the "damage evolution analysis" function to simulate the damage state of the pipeline at different time points, and record data such as the damage propagation path, damage degree, and failure probability. Organize the obtained damage evolution data into a damage evolution characteristic map. Use geographic information system (GIS) software for damage mapping modeling. Import the pipeline damage evolution characteristic map into the GIS software and load the geographic information data of the pipeline. For example, in ArcGIS, import the image file of the damage evolution characteristic map and load the geographic coordinate data of the pipeline (such as longitude and latitude coordinates), and set the parameters and conditions for damage mapping in the GIS software. For example, select the mapping model as the "spatial interpolation model" and set the interpolation parameters such as the interpolation method (such as Kriging interpolation or inverse distance weighted interpolation) and interpolation grid size. At the same time, set the attribute fields for damage mapping such as the damage degree and failure probability. Start the GIS software for damage mapping modeling. The software will spatially associate and map the pipeline damage evolution characteristic map with the geographic information to generate a pipeline damage mapping model.

[0109] Step S48: Based on the pipeline monitoring data block set and the pipeline damage mapping model, conduct a risk assessment on the oil and gas pipeline to obtain an oil and gas pipeline risk index set.

[0110] Specifically, for the detailed implementation process of this embodiment, please refer to the sub-steps of step S48.

[0111] Through stress concentration area identification, the present invention can accurately point out the area with the most serious stress concentration in the pipeline. By simulating the fatigue-corrosion interaction, it can comprehensively consider the damage situation of the pipeline under fatigue loads and corrosive environments. Through pipeline damage evolution, it can intuitively display the whole process of pipeline damage from initiation, propagation to final failure. Through damage mapping modeling, it can accurately reflect the state and characteristics of the pipeline at different damage stages. Through risk assessment, it can comprehensively quantify the risk factors of the pipeline, covering multiple aspects such as pipeline fatigue damage, corrosion damage, and crack propagation.

[0112] Preferably, step S48 includes the following steps:

[0113] Step S481: Obtain the oil and gas pipeline monitoring area model;

[0114] Specifically, the oil and gas pipeline monitoring area model obtained in step S14 can be extracted from the database.

[0115] Step S482: Perform spatial registration and fusion on the oil and gas pipeline monitoring area model and the pipeline damage mapping model to obtain the pipeline damage area model;

[0116] Specifically, ArcGIS or QGIS can be used for spatial registration and fusion. Import the oil and gas pipeline monitoring area model and the pipeline damage mapping model into the GIS software. In the GIS software, perform spatial registration on the monitoring area model and the damage mapping model. For example, using the "Spatial Adjustment" function in ArcGIS, select the "Control Point Registration" method, and by selecting the corresponding control points (such as the starting point and ending point of the pipeline) in the two models, align the spatial coordinates of the damage mapping model with the spatial coordinates of the monitoring area model. On the basis of spatial registration, perform a fusion operation on the monitoring area model and the damage mapping model. For example, in ArcGIS, use the "Merge" or "Overlay" function to fuse the damage attribute information (such as damage degree, failure probability, etc.) of the damage mapping model with the area attribute information of the monitoring area model to generate the pipeline damage area model.

[0117] Step S483: Perform regional segmentation on the pipeline damage area model to obtain a set of pipeline damage area model blocks;

[0118] Specifically, ArcGIS or QGIS can be used for regional segmentation. Import the pipeline damage area model into the GIS software and set the parameters and conditions for regional segmentation in the GIS software. For example, according to the monitoring area division and damage characteristics of the pipeline, select the "damage degree" or "failure probability" attribute field as the segmentation basis, and set the segmentation threshold. For example, regions with a damage degree greater than 50% or a failure probability greater than 20% are segmented separately to identify areas with more severe damage. Start the GIS software for regional segmentation operations. For example, in ArcGIS, use the "Select" function to select the damage areas that meet the set segmentation conditions; then use the "Split" function to split these areas from the overall model to generate independent damage area model blocks. Each segmented model block will contain its own geometric structure and damage attribute information.

[0119] Step S484: Evaluate the failure probability of each pipeline damage area model block in the set of pipeline damage area model blocks to obtain a set of pipeline structure risk indicators;

[0120] Specifically, in MATLAB, the damage attribute data of each damaged area model block can be imported, such as the degree of damage, crack length, and corrosion depth. The parameters and models for failure probability assessment are set in the evaluation tool. For example, the probability model is selected as "Weibull distribution" or "lognormal distribution", and the model parameters are set, such as the shape parameter and scale parameter. These parameters can be estimated based on historical data or expert experience. At the same time, the evaluation conditions are set, such as load conditions and environmental conditions, to simulate the failure risk in actual operation. The risk assessment tool is started for failure probability assessment. For example, in MATLAB, a custom risk assessment script is run, and according to the damage data and probability model, the failure probability of each damaged area model block is calculated. During the assessment process, the software will consider the cumulative effect and interaction of the damage to obtain the failure probability values of each model block under different conditions. The failure probability data obtained from the assessment is sorted into a pipeline structure risk index set. For example, a table is created to list the identifier, failure probability value, and risk level information of each damaged area model block; the risk level is classified according to the failure probability value, such as high risk (failure probability greater than 50%), medium risk (failure probability between 20% and 50%), and low risk (failure probability less than 20%).

[0121] Step S485: Based on the pipeline monitoring data block set, multi-parameter risk assessment is carried out on each pipeline damaged area model block in the pipeline damage model block set to obtain a pipeline operation risk index set, and the pipeline structure risk index set and the pipeline operation risk index set are recorded as the oil and gas pipeline risk index set.

[0122] Specifically, the data of the pipeline monitoring data block set and the pipeline damage model block set can be integrated into the evaluation tool. For example, in Python, import the file of the monitoring data block set (such as in CSV format), which contains parameters such as pressure, temperature, and flow rate; at the same time, import the data of the damage model block set, which contains attributes such as damage degree, crack length, and corrosion depth. Set the parameters and models for multi-parameter risk assessment in the evaluation tool. For example, select the risk assessment model as "multi-factor risk matrix", and set the evaluation parameters such as pressure, temperature, flow rate, damage degree, and crack length. Set the weight and threshold for each parameter. For example, assume the weight of pressure is 0.3, the weight of temperature is 0.2, and the weight of damage degree is 0.5, and set the corresponding thresholds, such as the pressure threshold is 10 MPa, the temperature threshold is 80 °C, and the damage degree threshold is 30%. Start the evaluation tool to conduct multi-parameter risk assessment. For example, in Python, run the custom risk assessment script, and calculate the operation risk value of each pipeline damage area model block according to the monitoring data and damage data. During the evaluation process, the software will comprehensively consider the influence of multiple parameters to obtain the operation risk level of each model block under different conditions. Organize the evaluated operation risk data into a pipeline operation risk index set. For example, create a table listing the identifier, operation risk value, and risk level information of each pipeline damage area model block; classify the risk level according to the operation risk value, such as high risk (risk value greater than 80%), medium risk (risk value between 50% and 80%), and low risk (risk value less than 50%). Import the data of the pipeline structure risk index set and the pipeline operation risk index set into the integration tool. For example, in Excel, import the Excel table files of the two index sets. In the integration tool, use the "merge" function to merge the data of the two index sets according to the identifier of the pipeline damage area model block to generate a new data table containing the comprehensive information of the structure risk index and the operation risk index. Organize the integrated risk index data into an oil and gas pipeline risk index set.

[0123] Through spatial registration and fusion, the present invention can accurately correspond the damage information to the three-dimensional spatial position of the pipeline. This enables the risk assessment to be carried out for the specific damage area of the pipeline, improving the pertinence and accuracy of the assessment, and helping to identify the key parts of the pipeline that require the most attention and maintenance. Through regional segmentation, the pipeline can be divided into smaller evaluation units. Through failure probability assessment, the failure possibility of the pipeline structure in the damage area can be quantified. Through multi-parameter risk assessment, various risk factors in pipeline operation, such as pressure, temperature, and flow rate, are comprehensively considered. This makes the assessment of pipeline operation risk more comprehensive and accurate, and can more truly reflect the risk status of the pipeline in actual operation.

[0124] Preferably, step S5 includes the following steps:

[0125] Step S51: Extract boundary conditions from the reconstructed pipeline geological environment data to obtain a pipeline geological environment boundary condition set;

[0126] Specifically, Geographic Information System (GIS) software can be used for boundary condition extraction. Import the reconstructed pipeline geological environment data into the GIS software. In the GIS software, identify the boundary conditions of the geological environment. For example, by analyzing the geological structure layer, identify boundary conditions such as stratigraphic interfaces, fault lines, and river boundaries. Use the "selection" function of GIS to select the layers or features of these boundary conditions, and extract their geometric shapes and attribute information. Extract the identified boundary condition data to form a pipeline geological environment boundary condition set. For example, in ArcGIS, use the "export" function to export the boundary condition layer as an independent Shapefile or CSV file, which contains information such as the coordinates, types, and attributes of the boundary conditions. For example, the file can contain the coordinate points of the stratigraphic interface, the type of the fault line (such as normal fault or reverse fault), and the width of the river boundary, etc.

[0127] Step S52: Perform real-time dynamic visualization rendering on the three-dimensional model of the oil and gas pipeline according to the pipeline geological environment boundary condition set to obtain a pipeline environment interaction model;

[0128] Specifically, Unity or Unreal Engine can be used for real-time dynamic rendering. Import the three-dimensional model of the oil and gas pipeline and the pipeline geological environment boundary condition set into the visualization rendering software. In the visualization rendering software, set the rendering parameters and interaction functions. For example, set the lighting parameters, such as the position, intensity, and color of the light source; set the material parameters, such as the texture, color, and transparency of the pipeline and the geological environment. At the same time, set the interaction functions, such as allowing users to rotate, zoom, and move the model through the mouse or touch screen. Start the visualization rendering software for real-time dynamic rendering. The software will render the interaction scene between the three-dimensional model of the oil and gas pipeline and the geological environment in real time according to the set rendering parameters and interaction functions. For example, in Unity, use the "Play" function to start the rendering, and users can see the dynamic changes of the pipeline in different geological environments, such as the bending of the pipeline at the stratigraphic interface and the displacement near the fault line. For example, export a video to show the dynamic interaction process of the pipeline in the geological environment, including the stress distribution, deformation situation of the pipeline, and its interaction with the geological environment.

[0129] Step S53: Perform risk feature mapping on the pipeline environment interaction model according to the oil and gas pipeline risk index set to obtain a digital twin of the oil and gas pipeline.

[0130] Specifically, Tableau or Power BI can be used for risk feature mapping. The oil and gas pipeline risk index set and the pipeline environment interaction model are imported into the mapping tool. For example, in Tableau, an Excel spreadsheet file of the risk index set containing data such as structural risk values, operating risk values, and failure probabilities is imported. At the same time, a 3D data file of the pipeline environment interaction model in formats such as STL or FBX is imported, and the parameters and visualization styles of the risk feature mapping are set in the mapping tool. For example, the mapping parameter "risk level" is selected, and the risk levels are classified according to the failure probability values in the risk index set, and the visualization styles are set. For example, color coding is used to represent different risk levels, with high-risk areas shown in red, medium-risk areas shown in yellow, and low-risk areas shown in green. The mapping tool is started for risk feature mapping. The software will map the data in the risk index set to the pipeline environment interaction model according to the set parameters and styles, generating a digital twin of the oil and gas pipeline. For example, in Tableau, the "Spatial Analysis" function is used to combine the risk level data with the spatial location of the pipeline model to generate a 3D visualization model with risk features.

[0131] Through boundary condition extraction, the present invention can accurately reflect the boundary features and constraint conditions of the pipeline surrounding environment. This provides an accurate environmental matching basis for the dynamic visualization rendering of the 3D model of the oil and gas pipeline, enabling the digital twin to better adapt to and simulate the actual geological environment, and improving the environmental adaptability and authenticity of the digital twin. Through real-time dynamic visualization rendering, the interaction between the pipeline and the surrounding environment can be displayed in real time. Through risk feature mapping, the risk information of the pipeline can be intuitively displayed on the digital twin. This enables managers to clearly identify the risk areas and risk levels of the pipeline, timely discover potential safety hazards, and improve the risk warning ability of the digital twin.

[0132] Preferably, the present invention also provides a digital twin construction system for an oil and gas pipeline, which is used to execute the digital twin construction method for an oil and gas pipeline as described above. The digital twin construction system for an oil and gas pipeline includes:

[0133] A data acquisition module, which is used to obtain the 3D model of the oil and gas pipeline and the oil and gas pipeline perception data set; integrate the oil and gas pipeline perception data set to obtain a pipeline monitoring data block set;

[0134] A structural analysis module, which is used to perform microscopic structural analysis on the oil and gas pipeline to obtain a pipeline microscopic structure feature map; construct a pipeline material digital mapping model based on the pipeline microscopic structure feature map; simulate the stress distribution of the oil and gas pipeline based on the pipeline material digital mapping model to obtain a pipeline material stress distribution map;

[0135] The geological inversion module is used to perform multi-physical field coupling simulation on the oil and gas pipeline and the geology to obtain a dynamic interaction model of the geological environment; based on the dynamic interaction model of the geological environment, physical inversion is performed on the environment between the oil and gas pipeline and the geology to obtain reconstructed data of the pipeline geological environment;

[0136] The risk assessment module is used to build a damage mechanism model for the oil and gas pipeline based on the pipeline material stress distribution map to obtain a pipeline damage mapping model; based on the pipeline monitoring data block set and the pipeline damage mapping model, risk assessment is performed on the oil and gas pipeline to obtain a set of risk indicators for the oil and gas pipeline;

[0137] The real-time mapping module is used to perform real-time mapping on the three-dimensional model of the oil and gas pipeline based on the reconstructed data of the pipeline geological environment and the set of risk indicators for the oil and gas pipeline to obtain a digital twin of the oil and gas pipeline.

[0138] Preferably, a computer-readable storage medium stores a method for constructing a digital twin of an oil and gas pipeline that can be loaded and executed by a processor as described above.

[0139] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the application document are intended to be included in the present invention.

[0140] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for constructing a digital twin of an oil and gas pipeline, characterized in that: The following steps are involved: Step S1: obtaining a three-dimensional model of an oil and gas pipeline and an oil and gas pipeline perception data set; integrating the oil and gas pipeline perception data set to obtain a pipeline monitoring data block set; Step S2: Performing microstructural analysis on the oil and gas pipeline to obtain a microstructural characteristic map of the pipeline; constructing a material model for the oil and gas pipeline based on the microstructural characteristic map of the pipeline to obtain a digital mapping model of the pipeline material; performing stress distribution simulation on the oil and gas pipeline based on the digital mapping model of the pipeline material to obtain a stress distribution map of the pipeline material; Step S3: Perform multi-physical field coupling simulation on the oil and gas pipeline and the geology to obtain a dynamic interaction model of the geological environment; perform physical inversion on the environment between the oil and gas pipeline and the geology based on the dynamic interaction model of the geological environment to obtain pipeline geological environment reconstruction data; Step S4: Based on the pipeline material stress distribution diagram, damage mechanism modeling is performed on the oil and gas pipeline to obtain a pipeline damage mapping model; based on the pipeline monitoring data block set and the pipeline damage mapping model, risk assessment is performed on the oil and gas pipeline to obtain an oil and gas pipeline risk indicator set; Step S5: Based on the pipeline geological environment reconstruction data and the oil and gas pipeline risk indicator set, the three-dimensional model of the oil and gas pipeline is mapped in real time to obtain a digital twin of the oil and gas pipeline.

2. The method for constructing a digital twin of an oil and gas pipeline according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: obtaining an oil and gas pipeline design drawing, and constructing a three-dimensional model of the oil and gas pipeline based on the oil and gas pipeline design drawing to obtain a three-dimensional model of the oil and gas pipeline; Step S12: performing multimodal data collection on the oil and gas pipeline to obtain an initial oil and gas pipeline sensing data set, wherein the multimodal data collection includes collection of internal and external pressures of the pipeline, collection of surface and internal temperatures of the pipeline, collection of velocity and flow of the fluid in the pipeline, and collection of gas leakage detection data; Step S13: performing time synchronization calibration on the initial oil and gas pipeline sensing data set to obtain the oil and gas pipeline sensing data set; Step S14: dividing the oil and gas pipeline into monitoring areas based on the three-dimensional model of the oil and gas pipeline to obtain a monitoring area model of the oil and gas pipeline; Step S15: regional data blocks are performed on the oil and gas pipeline sensing data set according to the oil and gas pipeline monitoring regional model to obtain a pipeline monitoring data block set.

3. The method for constructing a digital twin of an oil and gas pipeline according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: collecting remote sensing images of the oil and gas pipeline to obtain remote sensing images of the oil and gas pipeline; Step S22: obtaining an oil and gas pipeline monitoring area model, and performing surface-underground area identification and labeling on the oil and gas pipeline monitoring area model according to the oil and gas pipeline remote sensing image to obtain an oil and gas pipeline zoning model; Step S23: performing hierarchical structure segmentation on the oil and gas pipeline partition model to obtain a surface pipeline structure model block set and an underground pipeline structure model block set; Step S24: collecting surface images of corresponding pipeline areas of the oil and gas pipelines according to the surface pipeline structure model block set to obtain a surface pipeline surface image set; Step S25: collecting underground soil parameters of the corresponding pipeline area of ​​the oil and gas pipeline according to the underground pipeline structure model block set to obtain an underground pipeline soil environment parameter set; Step S26: performing microstructure analysis on the oil and gas pipeline based on the surface image set of the surface pipeline and the soil environmental parameter set of the underground pipeline to obtain a pipeline microstructure feature map; Step S27: constructing a material model for the oil and gas pipeline based on the pipeline microstructure characteristic map to obtain a pipeline material digital mapping model, and simulating the stress distribution of the oil and gas pipeline based on the pipeline material digital mapping model to obtain a pipeline material stress distribution map.

4. The method for constructing a digital twin of an oil and gas pipeline according to claim 3, characterized in that: Step S26 includes the following steps: Step S261: extracting pipeline surface texture from each surface pipeline image in the surface pipeline image set to obtain a surface pipeline surface texture feature set; Step S262: reconstructing the surface pipeline structure model block set by texture mapping using the surface pipeline surface texture feature set to obtain the surface pipeline surface structure mapping set; Step S263: collecting the usage time of the oil and gas pipeline to obtain pipeline service life data; Step S264: collecting historical meteorological data of the corresponding pipeline area of ​​the oil and gas pipeline according to the underground pipeline structure model block set to obtain an underground pipeline environmental meteorological record set; Step S265: collecting the buried depth of each underground pipeline structure model block in the underground pipeline structure model block set to obtain an underground pipeline buried depth distribution set; Step S266: performing material aging simulation on the corresponding pipeline area of ​​the oil and gas pipeline based on the pipeline service life data, the underground pipeline environmental meteorological record set, the underground pipeline burial depth distribution set and the underground pipeline structure model block set to obtain a pipeline aging characteristic data set; Step S267: reconstructing the microscopic corrosion morphology of the underground pipeline structure model block set according to the pipeline aging characteristic data set to obtain the underground pipeline microscopic feature set; Step S268: performing feature fusion on the surface structure mapping set of the surface pipeline and the microscopic feature set of the underground pipeline to obtain a pipeline microscopic structure feature map.

5. The method for constructing a digital twin of an oil and gas pipeline according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: collecting soil components along the oil and gas pipeline to obtain soil component composition data along the pipeline, and modeling the stress-strain relationship of the soil component composition data along the pipeline to obtain a soil mechanical property model along the pipeline; Step S32: measuring the resistivity of the buried area of ​​the oil and gas pipeline to obtain formation resistivity distribution data, and performing three-dimensional interpolation on the formation resistivity distribution data to obtain a formation electrical characteristic model; Step S33: performing seismic wave measurement along the oil and gas pipeline to obtain formation seismic wave velocity data, and performing ray tracing inversion on the formation seismic wave velocity data to obtain a formation elastic characteristic model; Step S34: Perform hydrological monitoring on the oil and gas pipeline observation area to obtain groundwater level dynamic data, and perform water flow field simulation based on the groundwater level dynamic data to obtain a groundwater flow field model; Step S35: performing electrical-mechanical coupling on the formation electrical characteristic model and the soil mechanical characteristic model to obtain electrical-mechanical coupling field data around the pipeline, and performing solid-liquid coupling on the formation elastic characteristic model and the groundwater flow field model to obtain solid-liquid coupling field data around the pipeline; Step S36: Based on the electric-mechanical coupling field data around the pipeline and the solid-liquid coupling field data around the pipeline, multi-field coupling is performed on the oil and gas pipeline and the geology to obtain a dynamic interaction model of the geological environment; Step S37: Based on the geological environment dynamic interaction model, physical inversion is performed on the environment between the oil and gas pipeline and the geology to obtain pipeline geological environment reconstruction data.

6. The method for constructing a digital twin of an oil and gas pipeline according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: identifying stress concentration areas on the pipeline material stress distribution map to obtain a pipeline stress hotspot distribution map; Step S42: performing fatigue damage prediction on the oil and gas pipeline based on the pipeline stress hot spot distribution map to obtain pipeline fatigue damage prediction data; Step S43: performing electrochemical impedance spectroscopy test on the oil and gas pipeline to obtain pipeline corrosion rate data; Step S44: performing corrosion dynamics simulation on the oil and gas pipeline according to the pipeline corrosion rate data to obtain pipeline corrosion damage prediction data; Step S45: performing a fracture toughness test on the oil and gas pipeline material to obtain pipeline fracture toughness data, and performing a crack propagation simulation on the oil and gas pipeline based on the pipeline fracture toughness data to obtain pipeline crack propagation prediction data; Step S46: performing fatigue-corrosion interaction simulation on pipeline fatigue damage prediction data and pipeline corrosion damage prediction data to obtain pipeline damage coupling data; Step S47: performing damage evolution on the oil and gas pipeline based on the pipeline crack propagation prediction data and the pipeline damage coupling data to obtain a pipeline damage evolution characteristic diagram, and performing damage mapping modeling based on the pipeline damage evolution characteristic diagram to obtain a pipeline damage mapping model; Step S48: Perform risk assessment on the oil and gas pipeline based on the pipeline monitoring data block set and the pipeline damage mapping model to obtain an oil and gas pipeline risk indicator set.

7. The method for constructing a digital twin of an oil and gas pipeline according to claim 6, characterized in that: Step S48 includes the following steps: Step S481: Obtaining an oil and gas pipeline monitoring area model; Step S482: spatially registering and fusing the oil and gas pipeline monitoring area model with the pipeline damage mapping model to obtain a pipeline damage area model; Step S483: performing region segmentation on the pipeline damage region model to obtain a pipeline damage region model block set; Step S484: performing failure probability assessment on each pipeline damage area model block in the pipeline damage area model block set to obtain a pipeline structure risk index set; Step S485: Based on the pipeline monitoring data block set, a multi-parameter risk assessment is performed on each pipeline damage area model block in the pipeline damage model block set to obtain a pipeline operation risk indicator set, and the pipeline structure risk indicator set and the pipeline operation risk indicator set are recorded as an oil and gas pipeline risk indicator set.

8. The method for constructing a digital twin of an oil and gas pipeline according to claim 1, characterized in that: Step S5 includes the following steps: Step S51: extracting boundary conditions from pipeline geological environment reconstruction data to obtain a pipeline geological environment boundary condition set; Step S52: performing real-time dynamic visualization rendering on the three-dimensional model of the oil and gas pipeline according to the pipeline geological environment boundary condition set to obtain a pipeline environment interaction model; Step S53: Perform risk feature mapping on the pipeline environment interaction model according to the oil and gas pipeline risk indicator set to obtain the oil and gas pipeline digital twin.

9. A digital twin construction system for oil and gas pipelines, characterized in that: For executing the digital twin construction method of the oil and gas pipeline according to claim 1, the digital twin construction system of the oil and gas pipeline comprises: The data acquisition module is used to obtain the three-dimensional model of the oil and gas pipeline and the oil and gas pipeline perception data set; integrate the oil and gas pipeline perception data set to obtain the pipeline monitoring data block set; The structural analysis module is used to perform microstructural analysis on the oil and gas pipeline to obtain a microstructural feature map of the pipeline; construct a material model for the oil and gas pipeline based on the microstructural feature map of the pipeline to obtain a digital mapping model of the pipeline material; and simulate the stress distribution of the oil and gas pipeline based on the digital mapping model of the pipeline material to obtain a stress distribution map of the pipeline material. The geological inversion module is used to conduct multi-physical field coupling simulation of oil and gas pipelines and geology to obtain a dynamic interaction model of the geological environment; based on the dynamic interaction model of the geological environment, the environment between the oil and gas pipelines and geology is physically inverted to obtain pipeline geological environment reconstruction data; The risk assessment module is used to model the damage mechanism of the oil and gas pipeline based on the pipeline material stress distribution diagram to obtain the pipeline damage mapping model; to conduct risk assessment on the oil and gas pipeline based on the pipeline monitoring data block set and the pipeline damage mapping model to obtain the oil and gas pipeline risk indicator set; The real-time mapping module is used to perform real-time mapping of the three-dimensional model of the oil and gas pipeline based on the pipeline geological environment reconstruction data and the oil and gas pipeline risk indicator set to obtain the digital twin of the oil and gas pipeline.

10. A computer-readable storage medium storing a method for constructing a digital twin of an oil and gas pipeline as claimed in any one of claims 1 to 8 that can be loaded and executed by a processor.

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