Method for deducing migration trajectory of oil pipeline leakage pollutants in multiphase medium

Abstract

The application relates to the field of pollutant diffusion simulation, in particular to a method for deducing the migration track of a pollutant leaked from an oil pipeline in a multiphase medium, which comprises the following steps: obtaining multidimensional simulation working condition data in a target area, and constructing a river hydrodynamic model and a migration and diffusion model of the pollutant in the multiphase medium; the river hydrodynamic model takes a convection-diffusion equation as a control equation and is used for describing the oil film diffusion and oil particle drift process of the pollutant in the river; the migration and diffusion model is used for simulating the vertical infiltration process of the pollutant in the soil, the migration of the pollutant in the underground water, and calculating the exchange flux of the underground water and the surface water at an interactive interface; the exchange flux is taken as a source term of the river hydrodynamic model, and the hydrodynamic condition calculated by the river hydrodynamic model is taken as a boundary condition of the migration and diffusion model, so as to obtain a soil-river integrated coupling model; and based on the soil-river integrated coupling model, the migration track of the pollutant in the multiphase medium is deduced.

Description

Technical Field

[0001] This application relates to the field of pollutant diffusion simulation technology, and more specifically, to a method for extrapolating the migration trajectory of pollutants leaking from oil pipelines in multiphase media. Background Technology

[0002] As vital arteries for energy transportation, oil pipelines often traverse sensitive water bodies such as rivers and lakes. In the event of a leak, petroleum pollutants can rapidly enter the surrounding environment, posing a serious threat to soil, groundwater, and surface water ecosystems.

[0003] Specifically, regarding soil pollution, toxic components in crude oil (such as benzene compounds and polycyclic aromatic hydrocarbons) can adsorb onto soil particles, clogging pores, damaging soil structure, inhibiting microbial activity, and leading to long-term degradation of soil ecological functions. Regarding groundwater pollution, pollutants migrate vertically into aquifers through the vadose zone of the soil, forming pollution plumes that are difficult to control. These plumes then slowly spread with the groundwater flow field, seriously threatening the safety of downstream drinking water sources. This type of pollution is highly concealed and cumulative, making remediation extremely difficult. Regarding surface water pollution, whether the leak point is directly located in a river or pollutants enter surface water bodies through the subsurface flow exchange between soil and groundwater, an oil film will form on the water surface, preventing the water from reoxygenating, causing a sharp drop in dissolved oxygen, resulting in the death of a large number of aquatic organisms. Furthermore, the oil film spreads rapidly with the water flow, causing the pollution area to continue to expand.

[0004] Currently, pollution diffusion simulation and pollution source tracing technologies are core supports for emergency response and control of oil pipeline leaks. However, existing technologies still face several bottlenecks that urgently need to be overcome. First, in pollution diffusion simulation, traditional models often treat soil, groundwater, and surface water as isolated systems, neglecting the continuous migration and exchange of pollutants at different media interfaces. This makes it difficult to accurately reflect the multi-phase coupled diffusion patterns of pollutants after a pipeline leak, leading to significant discrepancies between predicted results and actual pollution conditions. Second, in source tracing technologies, traditional methods rely heavily on reverse engineering of downstream detection data or inference from human experience. This is not only time-consuming and inaccurate, but also highly susceptible to environmental interference, especially under multi-source pollution or complex hydrogeological conditions, making it difficult to quickly pinpoint the true leak source. Therefore, existing technologies cannot meet the urgent need for accurate prediction and rapid, efficient source tracing of multi-media coupled diffusion patterns in the event of a sudden leak. Summary of the Invention

[0005] In view of this, this application provides a method for extrapolating the migration trajectory of pollutants leaking from oil pipelines in multiphase media, so as to achieve high-precision simulation of the migration process of pollutants in multiphase media, and on this basis, to achieve rapid and accurate source tracing of the leak.

[0006] The technical solution provided in this application is as follows: Methods for extrapolating the transport trajectories of contaminants leaking from oil pipelines in multiphase media include: Multi-dimensional simulated operating condition data within the target area are acquired to construct a river hydrodynamic model and a pollutant migration and diffusion model in a multiphase medium. The river hydrodynamic model uses the convection-diffusion equation as the governing equation to describe the oil film diffusion process and oil particle drift process of pollutants in the river. The migration and diffusion model is used to simulate the vertical infiltration process of pollutants in the soil based on the Green-Ampt equation, simulate the migration of pollutants in groundwater based on the convection-dispersion equation, and calculate the exchange flux between groundwater and surface water at the interface. Using the exchange flux as the source term of the river hydrodynamic model and the hydrodynamic conditions calculated by the river hydrodynamic model as the boundary conditions of the migration and diffusion model, the river hydrodynamic model and the migration and diffusion model are coupled to obtain an integrated soil-river coupled model. Based on the aforementioned integrated soil-river model, the transport trajectories of pollutants in multiphase media are extrapolated.

[0007] In one possible implementation, the multi-dimensional simulation data includes hydrological and meteorological data, geographic information data, soil environmental baseline and pollution detection data, and groundwater environmental baseline and pollution detection data. The hydrological and meteorological data includes wind direction angle, wind speed at a preset height above the water surface, and surface water flow velocity. The geographic information data includes the latitude and longitude coordinates of the target area. The soil environmental baseline and pollution detection data includes pollutant concentration in the soil, pollution range, and soil wetting front depth. The groundwater environmental baseline and pollution detection data includes groundwater pollutant concentration, groundwater flow velocity, groundwater flow rate, groundwater recharge area, and groundwater discharge into rivers.

[0008] In one possible implementation, the oil film diffusion process of pollutants in the river is characterized by changes in the oil film diameter; the oil film diffusion process is divided into a gravity-inertial force stage, a gravity-viscosity stage, and a viscosity-surface tension stage according to the time scale after the leak. The description of the oil film diffusion process of pollutants in rivers includes: establishing the kinetic equations corresponding to the oil film diameter at each stage; Specifically, during the gravity-inertia stage, the oil film diameter changes with the time of oil spill; during the gravity-viscosity stage, the oil film diameter changes with the dynamic viscosity of water; and during the viscosity-surface tension stage, the oil film diameter changes with the density of water, the surface tension between air and water minus the surface tension between oil and water, and the surface tension between oil and air.

[0009] In one possible implementation, the oil particle drift process of pollutants in the river is characterized by changes in the position of the oil particles; these changes are determined based on the initial position of the oil film, the wind drift velocity, and the wind direction angle.

[0010] One possible implementation involves simulating the vertical infiltration process of pollutants in soil based on the Green-Ampt formula, including calculating the infiltration amount, saturated hydraulic conductivity, and penetration time of pollutants in the soil; wherein the infiltration amount is determined based on the difference between the oil phase wetting layer thickness and the water content of the oil phase; the saturated hydraulic conductivity is determined based on the relative permeability of the oil phase and the viscosity correction coefficient; and the penetration time is determined based on the retardation factor, the actual flow velocity of water in the soil, and the oil phase wetting layer thickness.

[0011] In one possible implementation, the migration of pollutants in groundwater is simulated based on the convection-dispersion equation, in which the rate of change of pollutant concentration over time is determined by the effective porosity of the soil, the dispersion coefficient in each direction, the rate of change of pollutant concentration along the corresponding direction, the actual flow velocity of groundwater in each direction, and the concentration change of pollutants along the corresponding direction.

[0012] In one possible implementation, the exchange flux between groundwater and surface water at the interface is determined by the product of groundwater discharge and the concentration of groundwater pollutants at the interface; The groundwater pollutant concentration at the interface is determined based on the pollution concentration at the corresponding location of the groundwater, the actual flow velocity of the groundwater, the groundwater dispersion coefficient, and the horizontal distance from the soil-groundwater interface to the riverbed.

[0013] In one possible implementation, based on the integrated soil-river coupling model, the transport trajectory of pollutants in multiphase media is extrapolated, including outputting the diffusion range, concentration distribution, and transport trajectory of pollutants; wherein, the concentration distribution is jointly determined by the groundwater pollutant concentration, groundwater recharge area, initial surface water concentration, surface water flow rate, and groundwater flow rate.

[0014] In one possible implementation, after extrapolating the transport trajectory of pollutants in a multiphase medium, the method further includes: Carbon isotope analysis was performed on the collected contaminated oil samples. The obtained isotope data was compared with the carbon isotope fingerprint spectrum of the regional pipeline to identify the leaking pipeline. Based on the mutation point detection algorithm, mutation points in petroleum hydrocarbon concentration are identified and marked to determine the leakage area of ​​pollutants; Acquire image data of the leak area and construct a three-dimensional model of the leak area based on the deduced pollutant migration trajectory; Based on the abrupt change in petroleum hydrocarbon concentration, reverse particle tracing is performed in the three-dimensional model to inversely deduce the location of the upstream leakage source of the pollutants.

[0015] In one possible implementation, after tracing the location of the upstream leakage source of the pollutant, the method further includes: The dynamic process of pollutant diffusion, the abrupt change point of petroleum hydrocarbon concentration, and the location of the upstream leakage source obtained by reverse deduction are marked in the three-dimensional model; By utilizing a deep learning-based intelligent leak source assessment algorithm, the confidence level of leak points is evaluated based on multi-dimensional operating condition data, and an emergency decision report is output.

[0016] Compared with the prior art, the technical solution provided in this application has the following beneficial effects: This application constructs an integrated soil-river coupled model, fusing river hydrodynamic models with pollutant migration and diffusion models in soil and groundwater. This overcomes the limitations of single-medium simulation and achieves high-precision, full-chain dynamic extrapolation of pollutant transport trajectories in multiphase media of surface water, vadose zone, and groundwater. Simultaneously, by combining carbon isotope fingerprint comparison and concentration abrupt change point identification technology, it can quickly locate leaking pipelines and accurately extrapolate the upstream leak source location. Furthermore, relying on 3D scene models and deep learning intelligent judgment algorithms, it transforms the complex pollution diffusion process into an intuitive visualization and quantitative confidence assessment, providing scientific, efficient, and accurate technical support for rapid source tracing, situation assessment, and emergency decision-making in the event of sudden oil pipeline leaks. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the method for extrapolating the migration trajectory of leaking pollutants in a multiphase medium, as provided in Embodiment 1 of this application.

[0018] Figure 2 This is a schematic diagram of the trajectory deduction module provided in Embodiment 2 of this application.

[0019] Figure 3 This is a schematic diagram of the traceability module provided in Embodiment 2 of this application. Detailed Implementation

[0020] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the embodiments of this application. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0021] Example 1 See Figure 1This is a flowchart illustrating the method for extrapolating the migration trajectory of contaminants leaking from an oil pipeline in a multiphase medium, as provided in Embodiment 1 of this application. Figure 1 As shown, the specific implementation steps of the above method include: Step 101: Obtain multi-dimensional simulated operating condition data for pollutant trajectory extrapolation within the target area.

[0022] The aforementioned multi-dimensional simulation data covers multiple aspects, including hydrology, meteorology, geography, soil, and groundwater, providing a comprehensive data foundation for constructing a high-fidelity model. Specifically, the multi-dimensional simulation data includes, but is not limited to, hydrological and meteorological data, geographic information data, soil environmental baseline and pollution detection data, and groundwater environmental baseline and pollution detection data.

[0023] In some embodiments, the aforementioned hydrometeorological data includes at least wind direction angle, wind speed at a height of 10 meters above the water surface, and surface water flow velocity. The aforementioned geographic information data must at least include the latitude and longitude coordinates of the target area. The aforementioned soil environmental baseline and pollution monitoring data must at least include the concentration of pollutants in the soil, the extent of pollution, and the depth of the soil wetting front. The aforementioned groundwater environmental baseline and pollution monitoring data must at least include the concentration of groundwater pollutants and the groundwater flow velocity. Groundwater flow Groundwater recharge area The amount of groundwater discharged into rivers .

[0024] Step 102: Based on the above multi-dimensional simulation data, construct a river hydrodynamic model and a model for the migration and diffusion of pollutants in multiphase media.

[0025] In this embodiment of the application, based on the multi-dimensional simulated working condition data obtained in step S101, differentiated sub-models are constructed and coupled for different migration paths of pollutants after leakage, forming an integrated soil-river coupled model.

[0026] Specifically, the governing equations of the above-mentioned river hydrodynamic model adopt the convection-diffusion equation to describe the self-diffusion process and drift process of pollutants in the river.

[0027] The aforementioned convection-diffusion equation is specifically expressed as follows: (1) In the formula, h Indicates water depth. t Indicates time, x Represents the horizontal coordinate. Represents the convection velocity in the x-direction. This represents the convection velocity in the y-direction. S Indicates the source term strength.

[0028] The aforementioned self-diffusion process, specifically the oil film diffusion process, is characterized by changes in the oil film diameter. Based on the timescale following the leak, this process is divided into three stages: the gravity-inertial force stage, the gravity-viscosity stage, and the viscosity-surface tension stage. The oil film expansion diameter in each stage is described by the corresponding kinetic equations.

[0029] Specifically, during the gravity-inertial force stage, the oil film diameter is expressed as: (2) In the formula, The diameter of the oil film. It is the acceleration due to gravity. The initial oil film volume, For the time of the oil spill, This is an empirical coefficient.

[0030] During the gravity-viscosity phase, the oil film diameter is expressed as: (3) In the formula, This is an empirical coefficient. This is the dynamic viscosity of water.

[0031] During the viscosity-surface tension phase, the oil film diameter is expressed as: (4) In the formula, The density of water, The surface tension between air and water minus the surface tension between oil and water and the surface tension between oil and air. This is an empirical coefficient.

[0032] The aforementioned drift process is tracked using the Lagrange method to measure the motion of oil particles, with the velocity of each particle determined by the surface flow velocity. tidal current velocity and wind drift speed Vector synthesis, in which the position of the particles changes over time, is determined by kinematic equations.

[0033] Among them, the aforementioned tidal current velocity , represented as: (5) The equation for the position change of drifting oil particles is expressed as: (6) In the formula, and This is the initial position of the oil film. , For the flow rate of the tide, The wind speed is 10 meters above the water level. The wind direction angle, This is the wind drift coefficient.

[0034] The aforementioned migration and diffusion model specifically includes a sub-model describing the vertical infiltration of pollutants in the soil, a convection-dispersion sub-model in groundwater, and a migration sub-model at the interface between groundwater and surface water.

[0035] For pollutants entering the soil-groundwater system, the Green-Ampt formula is first used to simulate their vertical infiltration process in the vadose zone of the soil, and the infiltration rate, saturated hydraulic conductivity, and breakthrough time are calculated. Specifically, the Green-Ampt formula is used to simulate the vertical infiltration process in the vadose zone of the soil, expressed as: (7) In the formula, The saturated water conductivity of the oil phase, For moistening and suction power, The thickness of the oil phase wetting layer. It refers to the thickness of surface pollutants. f This represents the actual infiltration rate.

[0036] The cumulative infiltration amount is expressed as: (8) In the formula, Due to the difference in water content in the oil phase, . This is the saturated water content. This represents the initial moisture content.

[0037] The formula for saturated hydraulic conductivity is expressed as: (9) In the formula, The saturated water conductivity of the oil phase, The relative permeability of the oil phase. This is the viscosity correction factor. The dynamic viscosity of water, This refers to the dynamic viscosity of petroleum.

[0038] The pollutant penetration time is expressed as: (10) In the formula, To penetrate time, As a blocking factor, This represents the actual flow velocity of water in the soil.

[0039] The convection-dispersion equation for the diffusion of pollutants in groundwater is as follows: (11) In the formula, For pollutant concentration, For time, , , The dispersion coefficient is a single-direction coefficient. This represents the actual flow velocity of groundwater. λ The effective porosity of the soil. This represents the rate of change of pollutant concentration over time. For the concentration gradient along x How fast the direction changes, For the concentration gradient along y How fast the direction changes, For the concentration gradient along z The speed of change of direction. For pollutant concentration along x Concentration changes in direction For pollutant concentration along y Concentration changes in direction For pollutant concentration along z Concentration changes in direction.

[0040] After pollutants enter groundwater, their migration is controlled by the aforementioned three-dimensional convection-dispersion equations. When groundwater is discharged into rivers, the exchange flux of pollutants at the groundwater-surface water interface is determined by the groundwater discharge rate. groundwater pollutant concentration at the interface The product is determined, and is expressed as: (12) In the formula, For exchange flux, This refers to the amount of groundwater discharged into rivers. The concentration of groundwater pollutants at the interface is determined by the concentration upstream. The parameters are obtained and expressed as: (13) In the formula, This represents the pollution concentration at a certain location in the groundwater. This represents the actual flow velocity of groundwater. The groundwater dispersion coefficient, , which is the horizontal distance from the soil-groundwater interface to the riverbed.

[0041] Step 103: Using the above-mentioned exchange flux as the source term of the river hydrodynamic model, and using the hydrodynamic conditions calculated by the river hydrodynamic model as the boundary conditions of the migration and diffusion model, the river hydrodynamic model and the migration and diffusion model are coupled to obtain the soil-river integrated coupled model.

[0042] Specifically, the key to the coupling lies in the flux exchange at the interface. The groundwater discharge flux to the river calculated by the migration and diffusion model will be input as a source term into the river hydrodynamic model. Simultaneously, changes in hydrodynamic conditions such as river water level will also affect the pressure field and discharge calculation of the groundwater model as boundary conditions. This two-way dynamic coupling constitutes the "soil-river integrated coupling model" of this application. This model can dynamically simulate the exchange of matter and energy between pollutants in the vadose zone, aquifer, and surface water.

[0043] Step 104: Based on the above integrated soil-river model, the transport trajectory of pollutants in multiphase media is deduced.

[0044] By running the integrated soil-river coupling model established based on the above steps, we can obtain the spatiotemporal distribution data and dynamic migration trajectory of pollutants in soil, groundwater, and surface water, including information such as the spatiotemporal distribution of pollutant concentration, the extent of pollution plume expansion, and key migration paths.

[0045] The concentration distribution of pollutants in rivers is determined by the initial concentration in surface water, the pollutant flux from upstream inflow, and groundwater discharge, as shown below: (14) In the formula, The concentration of pollutants in groundwater. Initial concentration of surface water , This refers to the flow rates of surface water and groundwater.

[0046] Compared with the prior art, the technical solution provided in Embodiment 1 of this application has the following beneficial effects: This application constructs a river hydrodynamic model and a pollutant migration and diffusion model in a multiphase medium, respectively. Using the exchange flux at the groundwater-surface water interface and river water level and hydrodynamic conditions as bidirectional coupling source and boundary conditions, an integrated soil-river coupled model is established. This scheme overcomes the limitations of traditional single-medium fragmented simulations, realistically reproducing the dynamic interactive feedback process between pollutant vertical infiltration in soil, groundwater migration, and river surface water diffusion. It achieves full-chain, high-precision dynamic extrapolation of pollutant transport trajectories in multiphase media, thus providing more reliable and environmentally sound technical support for predicting the pollution range, accurately tracing the source, and scientifically formulating emergency response plans for oil pipeline leaks.

[0047] Example 2 Based on the technical solution disclosed in Embodiment 1, Embodiment 2 of this application further supplements a feature tracing system for implementing the method described in Embodiment 1 and performing tracing on this basis.

[0048] Specifically, the aforementioned feature tracing system includes a trajectory deduction module and a tracing module. Among them, such as... Figure 2 As shown, the trajectory deduction module also includes a working condition simulation unit 201, a diffusion model building unit 202, and a trajectory deduction unit 203.

[0049] The aforementioned working condition simulation unit 201 is connected to the sensor group and data interface, and is responsible for collecting, storing and managing the multi-dimensional simulated working condition data described in step S101.

[0050] The aforementioned diffusion model building unit 202 is specifically used to call relevant algorithms in the model library to automatically or assist the user in building and coupling the river hydrodynamic model and migration diffusion model described in step S102, and finally generate an integrated soil-river coupled model.

[0051] The aforementioned trajectory extrapolation unit 203 is specifically used to run the integrated coupled model, perform numerical calculations, and output the diffusion range, concentration distribution, and migration trajectory of pollutants.

[0052] like Figure 3 As shown, the aforementioned tracing module is data-connected to the trajectory extrapolation unit 203 for modular interaction. Specifically, the aforementioned tracing module also includes a visual acquisition unit 301, a data transmission unit 302, and a control and processing unit 303.

[0053] Specifically, the aforementioned visual acquisition unit 301 further includes an acquisition layer 3011 and a preprocessing layer 3012. The acquisition layer 3011 acquires high-definition images of the leak area using devices such as drones and cameras. The preprocessing layer 3012 performs spatiotemporal alignment and preliminary integration of the images with the data from the operational simulation unit 201.

[0054] The aforementioned data transmission unit 302 specifically includes a feature extraction layer 3021 and a model layer 3022. The feature extraction layer 3021 is specifically used to perform core source tracing analysis. On one hand, it performs carbon isotope analysis (such as...) on the collected oil samples. , The system analyzes and compares the data with a regional pipeline database to quickly pinpoint the pipeline at fault. Simultaneously, it performs time-series and spatial gradient analysis on the hydrocarbon concentration data along the pipeline output by trajectory simulation unit 203. Using a mutation point detection algorithm, it automatically identifies and marks "hydrocarbon concentration mutation points" where concentration values ​​abnormally increase. These points indicate the leakage area of ​​pollutants, i.e., the location where they converge. The aforementioned model layer 3022 integrates the pollutant transport trajectory, 3D terrain data, and images from the visual acquisition unit 301 output by the trajectory simulation module to construct a high-precision 3D model of the leakage area. Based on the pipeline and "mutation points" identified by feature extraction layer 3021, reverse particle tracing is performed in this model to inversely deduce the location of potential upstream leakage sources of the pollutants.

[0055] The aforementioned control and processing unit 303 further includes a visualization layer 3031 and a decision layer 3032. The visualization layer 3031 visually projects and labels information such as the dynamic process of pollutant diffusion, identified "mutation points," and the leak source location obtained through reverse deduction onto a three-dimensional model. The decision layer 3032 incorporates a deep learning-based intelligent leak source assessment model. This model integrates the outputs of the feature extraction layer and the model layer to assess the confidence level of multiple potential leak points, ultimately providing the most probable leak source location and its probability, and generating an emergency decision report containing pollution diffusion predictions and source tracing results.

[0056] Compared with the prior art, the technical solution provided in Embodiment 2 of this application has the following beneficial effects: (1) Improve the realism and accuracy of the simulation: By constructing an integrated soil-river coupling model, the system simulation of the continuous migration process of pollutants in the multiphase medium of "soil-groundwater-river" was realized for the first time, overcoming the defect of traditional methods that treat each environmental medium separately.

[0057] (2) Improve the efficiency and accuracy of source tracing: The innovative dual source tracing mechanism combines “source comparison” based on carbon isotope fingerprints with “path identification” based on concentration mutation points, and couples forward trajectory deduction with reverse location tracking, which can quickly and accurately lock the leakage source, significantly outperforming traditional manual or single critical reasoning methods.

[0058] (3) Provide comprehensive decision support: This application ultimately transforms abstract simulation data and complex source tracing processes into intuitive situational information through a visual interface and intelligent analysis, providing strong technical support for on-site emergency command, resource scheduling and the formulation of pollution control measures.

[0059] Although embodiments of this application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for estimating the migration trajectory of pollutants leaking from an oil pipeline in a multiphase medium, characterized in that, include: Multi-dimensional simulated operating condition data within the target area are acquired to construct a river hydrodynamic model and a pollutant migration and diffusion model in a multiphase medium. The river hydrodynamic model uses the convection-diffusion equation as the governing equation to describe the oil film diffusion process and oil particle drift process of pollutants in the river. The migration and diffusion model is used to simulate the vertical infiltration process of pollutants in the soil based on the Green-Ampt equation, simulate the migration of pollutants in groundwater based on the convection-dispersion equation, and calculate the exchange flux between groundwater and surface water at the interface. Using the exchange flux as the source term of the river hydrodynamic model and the hydrodynamic conditions calculated by the river hydrodynamic model as the boundary conditions of the migration and diffusion model, the river hydrodynamic model and the migration and diffusion model are coupled to obtain an integrated soil-river coupled model. Based on the aforementioned integrated soil-river model, the transport trajectories of pollutants in multiphase media are extrapolated.

2. The method for extrapolating the migration trajectory of leaked pollutants in a multiphase medium in an oil pipeline according to claim 1, characterized in that, The multi-dimensional simulation data includes hydrological and meteorological data, geographic information data, soil environmental baseline and pollution detection data, and groundwater environmental baseline and pollution detection data. The hydrological and meteorological data includes wind direction angle, wind speed at a preset height above the water surface, and surface water flow velocity. The geographic information data includes the latitude and longitude coordinates of the target area. The soil environmental baseline and pollution detection data includes pollutant concentration in the soil, pollution range, and soil wetting front depth. The groundwater environmental baseline and pollution detection data includes groundwater pollutant concentration, groundwater flow velocity, groundwater flow rate, groundwater recharge area, and groundwater discharge into rivers.

3. The method for extrapolating the migration trajectory of pollutants leaking from oil pipelines in multiphase media according to claim 1, characterized in that, The oil film diffusion process of pollutants in the river is characterized by changes in the oil film diameter; the oil film diffusion process is divided into three stages based on the time scale after leakage: gravity-inertial force stage, gravity-viscosity stage, and viscosity-surface tension stage. The description of the oil film diffusion process of pollutants in rivers includes: establishing the kinetic equations corresponding to the oil film diameter at each stage; Specifically, during the gravity-inertia stage, the oil film diameter changes with the time of oil spill; during the gravity-viscosity stage, the oil film diameter changes with the dynamic viscosity of water; and during the viscosity-surface tension stage, the oil film diameter changes with the density of water, the surface tension between air and water minus the surface tension between oil and water, and the surface tension between oil and air.

4. The method for extrapolating the migration trajectory of pollutants leaking from oil pipelines in multiphase media according to claim 1, characterized in that, The oil particle drift process of pollutants in rivers is characterized by changes in the position of oil particles; these changes are determined based on the initial position of the oil film, wind drift velocity, and wind direction angle.

5. The method for extrapolating the migration trajectory of pollutants leaking from oil pipelines in multiphase media according to claim 1, characterized in that, The vertical infiltration process of pollutants in soil is simulated based on the Green-Ampt formula, including calculating the infiltration amount, saturated hydraulic conductivity, and breakthrough time of pollutants in the soil. The infiltration amount is determined based on the difference between the oil phase wetting layer thickness and the water content of the oil phase. The saturated hydraulic conductivity is determined based on the relative permeability of the oil phase and the viscosity correction coefficient. The breakthrough time is determined based on the retardation factor, the actual flow velocity of water in the soil, and the oil phase wetting layer thickness.

6. The method for extrapolating the migration trajectory of leaked pollutants in a multiphase medium in an oil pipeline according to claim 1, characterized in that, The migration of pollutants in groundwater is simulated based on the convection-dispersion equation. In the convection-dispersion equation, the rate of change of pollutant concentration over time is determined by the effective porosity of the soil, the dispersion coefficient in each direction, the rate of change of pollutant concentration along the corresponding direction, the actual flow velocity of groundwater in each direction, and the concentration change of pollutants along the corresponding direction.

7. The method for extrapolating the migration trajectory of pollutants leaking from oil pipelines in multiphase media according to claim 1, characterized in that, The exchange flux between groundwater and surface water at the interface is determined by the product of groundwater discharge and the concentration of groundwater pollutants at the interface; The groundwater pollutant concentration at the interface is determined based on the pollution concentration at the corresponding location of the groundwater, the actual flow velocity of the groundwater, the groundwater dispersion coefficient, and the horizontal distance from the soil-groundwater interface to the riverbed.

8. The method for extrapolating the migration trajectory of pollutants leaking from oil pipelines in multiphase media according to claim 1, characterized in that, Based on the integrated soil-river coupling model, the transport trajectory of pollutants in multiphase media is extrapolated, including the output of the pollutant diffusion range, concentration distribution, and transport trajectory; wherein, the concentration distribution is jointly determined by the groundwater pollutant concentration, groundwater recharge area, initial surface water concentration, surface water flow rate, and groundwater flow rate.

9. The method for extrapolating the migration trajectory of leaked pollutants in a multiphase medium in an oil pipeline according to claim 1, characterized in that, After extrapolating the transport trajectory of pollutants in a multiphase medium, the method further includes: Carbon isotope analysis was performed on the collected contaminated oil samples. The obtained isotope data was compared with the carbon isotope fingerprint spectrum of the regional pipeline to identify the leaking pipeline. Based on the mutation point detection algorithm, mutation points in petroleum hydrocarbon concentration are identified and marked to determine the leakage area of ​​pollutants; Acquire image data of the leak area and construct a three-dimensional model of the leak area based on the deduced pollutant migration trajectory; Based on the abrupt change in petroleum hydrocarbon concentration, reverse particle tracing is performed in the three-dimensional model to inversely deduce the location of the upstream leakage source of the pollutants.

10. The method for extrapolating the migration trajectory of leaked pollutants in a multiphase medium in an oil pipeline according to claim 9, characterized in that, After locating the upstream leakage source of the pollutants, the method further includes: The dynamic process of pollutant diffusion, the abrupt change point of petroleum hydrocarbon concentration, and the location of the upstream leakage source obtained by reverse deduction are marked in the three-dimensional model; By utilizing a deep learning-based intelligent leak source assessment algorithm, the confidence level of leak points is evaluated based on multi-dimensional operating condition data, and an emergency decision report is output.

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