Underwater production system leakage simulation method

Abstract

The invention provides a leakage simulation method for an underwater production system, relates to the technical field of offshore oil engineering, and aims to realize leakage process simulation with a rapid and vivid visual effect. According to the method, a multi-dimensional parameter matrix is established, and a leakage data set is generated through high-precision simulation of fluid simulation software; then, designing an efficient algorithm in the virtual reality engine to realize quick loading of a simulation data set; after a user sets parameters, the system selects an upper group of data and a lower group of data closest to the parameters in the data set and performs interpolation calculation so as to generate simulation results matched with the actual parameters; then, utilizing a shader, a particle system, an illumination model and the like in a virtual reality engine to express the simulation result; according to the method, the simulation speed is increased, highly vivid underwater leakage scene performance is provided, and the method is suitable for risk assessment, emergency drilling and educational training of an underwater production system.

Description

Technical Field

[0001] The invention relates to the technical field of offshore oil engineering, and in particular to a leakage simulation method for an underwater production system. Background Art

[0002] As global energy demand continues to grow, the number of underwater oil and gas production systems has increased year by year, and many of the equipment that has been put into use has been in use for more than ten years. This situation increases the risk of underwater production system leakage. The occurrence of underwater production system leakage accidents may cause significant damage to the ecological environment and economic interests. Therefore, effectively predicting and simulating the status and spread of underwater leakage incidents can facilitate the early and accurate deployment of disposal personnel and equipment, help reduce the impact of accidents, improve disposal efficiency, and reduce the adverse effects of leakage.

[0003] At present, in the simulation display process of underwater production system leakage, the commonly used methods are mainly divided into two categories: one is to write a physical simulation algorithm based on the fluid diffusion process. Although this method has a fast calculation speed, the accuracy is not stable within the parameter range, and it is difficult to accurately reflect the complex fluid behavior of all parameter ranges in the leakage process; the other is to use professional fluid simulation software for refined simulation. This method has obvious advantages in calculation accuracy, but the calculation speed is slow. The generated data usually needs to undergo complex post-processing before it can be visualized, and the existing post-processing methods are difficult to achieve realistic visual effects.

[0004] Therefore, there is an urgent need for a simulation method for underwater production system leakage, which can improve the simulation speed while ensuring the calculation accuracy and provide highly realistic visual representation to better support the risk assessment, emergency drills and decision support of underwater production system leakage. Summary of the invention

[0005] The purpose of the present invention is to provide a method for simulating leakage of an underwater production system, which improves the real-time response capability of the system while ensuring high accuracy through advance calculation and data interpolation, thereby realizing an efficient and realistic simulation display method.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides a method for simulating leakage of an underwater production system, comprising:

[0008] Simulation data point setting, including selecting and setting data points of multiple target parameters and constructing a multi-dimensional parameter matrix;

[0009] Fluid simulation software calculates data, including using fluid simulation software to simulate and calculate the fluid dynamic behavior of the leakage process on the constructed multi-dimensional parameter matrix, and generating a simulation data set;

[0010] Loading data into a virtual reality engine, including loading the simulation data set into the virtual reality engine to achieve dynamic real-time display;

[0011] Perform data calculations based on actual needs, including when the user inputs parameters, the system will select the two closest simulation data sets and generate new simulation results through interpolation calculations;

[0012] Data presentation is performed in a virtual reality engine, including simulation of the underwater environment and the diffusion behavior of oil and natural gas during leakage through a virtual reality engine.

[0013] Preferably, the simulation data point setting adopts a layered setting data point method, and the target parameters include the pressure at the leakage point, the cross-sectional area at the leakage point, the leakage flow rate, the water depth at the leakage point, and the seabed wave current.

[0014] Preferably, the fluid simulation software calculates data including:

[0015] Model building, including automatic construction of physical models of leak scenarios based on imported data;

[0016] Solver settings, including setting relevant parameters required for simulation calculation after the model is built;

[0017] Simulation parameter setting and calculation, importing the multi-dimensional parameter matrix into fluid simulation software and performing simulation calculation;

[0018] Data storage and management, after the simulation calculation is completed, all calculation results will be automatically saved in the database.

[0019] Preferably, the step of loading data in the virtual reality engine includes:

[0020] Integration of simulation database and VR engine, including importing optimized simulation data set into VR engine;

[0021] The loading algorithm is designed to dynamically select the simulation data set closest to the parameters set by the user and load it into the virtual reality environment.

[0022] Preferably, the loading algorithm adopts a space- and time-based progressive loading and a multi-threaded-based parallel processing method.

[0023] Preferably, the data calculation according to actual needs includes:

[0024] Parameter matching and nearest neighbor data selection, including that when the user sets specific leakage parameters in the virtual reality environment, the system first searches for two simulation data sets closest to the user input parameters in the pre-calculated multi-dimensional simulation data matrix;

[0025] Multi-dimensional interpolation calculation: the system uses a difference algorithm to perform multi-dimensional interpolation calculations on the data to generate a new data set;

[0026] Data loading optimization.

[0027] Preferably, the system first searches for two simulation data sets closest to the user input parameters in a pre-calculated multi-dimensional simulation data matrix, and the system uses a nearest neighbor search algorithm.

[0028] Preferably, the interpolation algorithm includes linear interpolation, bilinear interpolation or a high-order interpolation algorithm.

[0029] Preferably, the data loading optimization includes: parallel computing, data caching and optimization, adaptive interpolation and intelligent unloading mechanism.

[0030] Preferably, the data representation in the virtual reality engine includes simulating the leakage of the underwater production system through the shader, particle system, material system and lighting system in the virtual reality engine.

[0031] The underwater production system leakage simulation method provided by the present invention realizes the rapid response of simulation results by pre-calculating simulation data sets under a large number of parameter combinations, and dynamically loading and displaying them in a virtual reality environment. After the user adjusts the parameters, the system can perform data interpolation calculations and update the simulation scene in real time, significantly shortening the time from input to visualization. This real-time performance not only improves the operating efficiency, but also enhances the practicality of the system, especially in emergency situations where quick decision-making is required. Through the advanced functions of the virtual reality engine, a highly realistic effect is achieved in visual performance. With the help of customized shaders, particle emitters, material systems and lighting systems, users can intuitively observe the dynamic behavior of fluids during underwater leakage and their interaction with the environment. In particular, when simulating the leakage of oil and natural gas, the process of diffusion and mixing of these substances in water can be truly reproduced, which enhances the immersion and credibility of the simulation scene. This underwater production system leakage simulation method provides a safe and controllable environment for operators. The method can improve the intuitiveness and accuracy of simulation results, simulate various possible leakage events, and help operators familiarize themselves with and deal with potential risks in advance. Based on the simulation results, managers and operators can more accurately assess the impact of leakage accidents and formulate reasonable emergency plans, which provides an effective tool for the design, monitoring and maintenance of underwater production systems, thereby reducing the losses and risks caused by accidents. It has important engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 It is a flow chart of the underwater production system leakage simulation method of the present invention;

[0034] Figure 2 It is a flow chart of calculation data of fluid simulation software in the underwater production system leakage simulation method of the present invention;

[0035] Figure 3 The data calculation is performed according to actual needs in the underwater production system leakage simulation method of the present invention. DETAILED DESCRIPTION

[0036] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0037] The present invention provides a method for simulating leakage of an underwater production system, which sets initial simulation data points, calculates data using fluid simulation software, loads the data into virtual reality, performs data loading calculations according to actual needs, and finally performs data presentation in a virtual reality engine, thereby achieving effective simulation of leakage of an underwater production system. It can improve the simulation speed while ensuring the calculation accuracy, and provide highly realistic visual presentation, so as to better support risk assessment, emergency drills and decision support for leakage of underwater production systems.

[0038] The specific steps include:

[0039] S1. Simulation data point setting, including selecting and setting data points of multiple target parameters and constructing a multi-dimensional parameter matrix.

[0040] Specifically, in this embodiment, key data points are selected and set according to the physical characteristics and working environment of the underwater production system, and the typical scenario parameters that may occur during the leakage of the underwater oil and gas production system are reproduced as much as possible by identifying and setting the key data points that are crucial in the simulation process.

[0041] These key data points form a multi-dimensional matrix. These parameters not only cover their upper and lower limits, but also include several important points within this range to ensure comprehensive coverage of possible leakage scenarios. Specifically, the selection of parameter categories and the setting of the matrix are based on actual needs and leakage scenarios. The combination of parameters in this matrix can represent various typical situations. At the same time, by reasonably setting data points, the uniformity of parameters is guaranteed, thus providing effective support for subsequent work.

[0042] The simulation data point setting in this embodiment adopts a layered setting data point method. The data points mainly include the pressure at the leakage point, the cross-sectional area of ​​the leakage point, the leakage flow rate, the water depth at the leakage point and the seabed wave and current conditions, ensuring that possible leakage scenarios are covered and adjusting the parameter points according to the different complexities of the leakage scenarios.

[0043] Specifically, the pressure at the leakage point refers to the pressure at the leakage point of the underwater production system. The value range of this pressure is determined by the operating pressure of the conventional production system and the possible pressure at the wellhead. On the basis of the upper and lower limits, a point is selected every 1MPa to form a parameter of the matrix value. By setting different pressure ranges, the leakage characteristics and results under different pressure conditions can be simulated. The upper and lower limits of this parameter should be determined based on the actual operating pressure, and representative pressure points should be selected to reflect the impact of pressure fluctuations on the leakage process.

[0044] The cross-sectional area of ​​the leak determines the size of the leak and has a direct impact on the amount of leakage. By setting different cross-sectional area ranges, the effect of different apertures on the leak behavior can be simulated. The upper and lower limits of this parameter are determined based on common leak sizes and include multiple intermediate points to ensure that scenarios with different leak sizes can be reflected.

[0045] The leakage flow is calculated by the leakage flow under different conditions, which can dynamically simulate the diffusion speed and path of the leaked material. It is divided into leakage gas flow and leakage liquid flow. The two-phase leakage can exist separately or be freely combined within a certain range. The parameter range is 0 to the operating flow, and the value is uniform.

[0046] The depth of the leak affects the seabed pressure and temperature, and has an important impact on the leak behavior and diffusion pattern. Simulation data points are evenly set from 0 meters to the current maximum operating depth.

[0047] The submarine wave and current conditions include submarine internal wave and current and submarine ocean current. The existence of submarine internal wave and current will interfere with and affect the diffusion path of the leaked material. By simulating and setting different internal wave and current intensities and directions, it is possible to analyze their impact on the leakage diffusion behavior; ocean current conditions, the ocean current is one of the main factors affecting the diffusion and transportation of leaked materials in seawater. Considering the speed, direction and stability of the ocean current, set the range of variation of the ocean current parameters, and select key points for simulation. By setting the ocean current parameters, the diffusion path and final impact range of the leaked material under different ocean current conditions can be effectively simulated.

[0048] In a specific embodiment, the setting of simulation data points is the basis of the entire simulation method. The following are specific values ​​in this embodiment:

[0049] Leakage aperture: 1mm, 170mm, 340mm, 500mm;

[0050] Pressure at the leakage point: 5MPa, 10Mpa, 30Mpa, 60Mpa, 105Mpa;

[0051] Leakage flow rate: 2,000 cubic meters / day, 1.5 million cubic meters / day, 6 million cubic meters / day, 10 million cubic meters / day, 15 million cubic meters / day for gas, 0.50 cubic meters / day, 200 cubic meters / day, 600 cubic meters / day, 1000 cubic meters / day, 1300 cubic meters / day for liquid;

[0052] Water depth: 1 meter, 20 meters, 100 meters, 1000 meters, 2000 meters, 3000 meters

[0053] Wave and current velocity: internal wave velocity is 0, 0.5 m / s, 1 m / s, 1.5 m / s; ocean current velocity is 0, 0.5 m / s, 1 m / s, 1.5 m / s;

[0054] In a specific embodiment, the above parameter values ​​generate a data point matrix in a table format. Through the matrix, subsequent simulation calculations can perform a full range of leakage simulations based on different parameter combinations.

[0055] S2. Fluid simulation software calculates data, including using fluid simulation software to simulate the fluid dynamic behavior of the leakage process on the constructed multi-dimensional parameter matrix, performing simulation calculations on the fluid dynamic behavior of the leakage process, generating a simulation data set, and storing it in a database.

[0056] Among them, fluid simulation software calculation data refers to the use of professional fluid simulation calculation software, with the simulation data matrix selected in S1 as the basic parameters, to build a fluid model that matches the actual physical system, and based on a variety of solvers and numerical calculation methods, to perform simulation calculations and data collation to ensure the accuracy of the simulation results. Figure 2As shown, the specific steps include:

[0057] S21, building a model, including automatically building a physical model of the leakage scenario based on the imported data;

[0058] Specifically, the software automatically builds a physical model of the leakage scenario based on the imported data, including the initial state of the fluid, boundary conditions, physical properties (such as viscosity, density), etc. The model building process needs to ensure a high degree of consistency with the actual physical system to ensure the credibility of the simulation results.

[0059] S22, solver settings, including setting the relevant parameters required for simulation calculation after the model is built, such as time step, mesh division fineness, solver options, etc.

[0060] In a specific embodiment, the multidimensional data matrix set in step S1 is input into the fluid simulation software to construct a simulation model. The software generates a high-precision simulation data set by simulating the dynamic behavior of the fluid during the leakage process. During the simulation calculation, the physical properties of the fluid, such as viscosity and density, need to be taken into account, and the simulation parameters, such as the time step and the meshing fineness, are adjusted for different leakage scenarios to ensure the accuracy and efficiency of the simulation results. The simulation results include time series data of physical quantities such as velocity field, pressure field, and temperature field.

[0061] The leakage aperture, reservoir pressure, leakage volume, gas-oil ratio, crude oil viscosity, crude oil density, water depth, and wave velocity are combined in a matrix to provide data on underwater oil and gas leakage and diffusion distance and surface diffusion space within a 5km radius for building a simulation platform.

[0062] Among them, model building and solver settings include: using professional fluid simulation software ANSYS Fluent, which has the ability to handle complex fluid behaviors and accurately simulate the dynamic process of underwater leakage. Software configuration: Select an appropriate fluid solver and configure parameters such as calculation accuracy, time step, convergence criteria, etc. to ensure the reliability and calculation efficiency of the simulation results.

[0063] Constructing a simulation model includes geometric modeling, meshing, and physical property settings. Geometric modeling: In the fluid simulation software, first build a geometric model of the leakage scenario, including the structure of the leakage point, the definition of the water area, and the modeling of the surrounding environment (such as pipelines, seabed, etc.). Meshing: Mesh the geometric model, select the appropriate mesh type (such as hexahedral mesh or tetrahedral mesh), and perform local encryption near the leakage point to improve the calculation accuracy. The mesh division should take into account the balance between calculation accuracy and calculation amount. Physical property settings: Set the physical properties of the fluid, such as viscosity, density, temperature, etc. Set its physical property parameters according to the type of leaked material (such as oil, natural gas).

[0064] For multiphase fluids, the VOF (Volume of Fluid) model is used to handle them.

[0065] Select simulation model and solver: including:

[0066] Select simulation model: Select an appropriate simulation model according to the requirements of the leakage scenario. For example, use a turbulence model (such as the k-ε model or the k-ωSST model) to simulate the turbulent behavior of the fluid during the leakage process; use a multiphase flow model to handle the interaction between oil, gas and water mixed fluids;

[0067] Select solver: In fluid simulation, select a pressure-based solver (such as the SIMPLE algorithm) or a density-based solver, and set convergence criteria (such as a residual value lower than 1e-5) to ensure the stability of the calculation results.

[0068] S23, simulation parameter setting and calculation, importing the multi-dimensional parameter matrix into the fluid simulation software, and performing simulation calculation;

[0069] Specifically, the multidimensional data matrix generated in the simulation data point setting step is imported into the fluid simulation calculation software, and the data in the matrix is ​​automatically input as parameters by writing a parameter automatic setting script. The whole process of fluid diffusion from the leakage point to the outside is simulated during the leakage process, including the changes in the fluid's velocity field, pressure field, temperature field, and material concentration. The simulation calculation will generate a series of time series data, which records in detail the state and distribution of the fluid in the leakage scenario at each time step.

[0070] In a specific embodiment, the simulation parameter setting and calculation process uses the multidimensional parameter matrix generated by the simulation data point setting in the previous step as the input data of the fluid simulation software. Each set of parameters corresponds to a leakage scenario. These parameters will be input into the simulation software as initial conditions and boundary conditions. The values ​​in the parameters are used as initial conditions and boundary conditions. The initial conditions of the leakage point are set according to the input parameters, and the environmental boundary conditions are set, such as the speed and pressure at the water boundary, the speed direction of the ocean current, etc.

[0071] For open boundaries, you can set Pressure Outlet or Velocity Inlet conditions to ensure that fluid can flow freely out of or into the computational domain.

[0072] Run the simulation calculation and set the time step: According to the time scale of the leakage process, set a reasonable time step (such as 0.01 second). The time step should be small enough to capture the rapidly changing fluid behavior during the leakage process.

[0073] Simulation calculation: Start the simulation calculation and let the software calculate the dynamic behavior of the fluid during the leakage process according to the set initial conditions, boundary conditions and physical models. The calculation content includes: velocity field, calculating the velocity distribution of the leaked material in the water; pressure field, calculating the pressure distribution around the leak point; temperature field, calculating the temperature change of the leaked material; material diffusion: simulating the diffusion path and range of oil and natural gas in water.

[0074] S24. Data storage and management. After the simulation calculation is completed, all calculation results will be automatically saved in the database. The data stored in the database includes various key indicators of fluid motion and snapshots of the fluid state at each time step. Data storage is managed in a structured form to facilitate fast query and retrieval. The storage format must ensure the integrity and accuracy of the data while taking into account the efficiency of subsequent loading in the virtual reality system. Through effective management of the database, users can quickly extract the required simulation data according to actual needs and support a variety of application scenarios.

[0075] In a specific embodiment, simulation data output and storage, data format conversion, converting the simulation data set generated by the fluid simulation software into a format that the Unreal Engine can recognize. CSV (numeric data) or proprietary VDB format (volume data); data block processing: to facilitate dynamic loading, the simulation data set is divided into blocks according to spatial position and time series to reduce the amount of data loaded at a single time and optimize loading performance.

[0076] Result output: After the simulation calculation is completed, the time series data of key physical quantities such as flow rate, pressure, temperature, etc. can be exported. The data format can be selected in common CFD formats (such as VTK, CSV, etc.) for subsequent processing and analysis. Store data sets: Store the simulation results in the database and classify and organize the data. Each data set corresponds to a specific leakage scenario for subsequent virtual reality loading and interpolation calculations.

[0077] S3, loading data into the virtual reality engine, including loading the simulation data set into the virtual reality engine, and realizing dynamic real-time display through efficient data loading algorithm and reasonable loading frequency;

[0078] Specifically, the simulation database generated in step S2 is loaded into the virtual reality engine, and the dynamic data generated by the fluid simulation software is imported into the virtual reality system. The virtual reality system converts these data into a three-dimensional model through visualization technology and performs real-time rendering. By loading data in virtual reality, users can intuitively observe the leakage process and its impact range, thereby improving their understanding and analysis capabilities of the leakage phenomenon.

[0079] Specifically, this part includes the following core links:

[0080] S31. Integration of simulation database and virtual reality engine, importing optimized simulation data set into virtual reality engine.

[0081] To achieve this goal, an interface needs to be built to transfer data between the simulation database and the virtual reality engine. This interface is responsible for converting the multi-dimensional simulation data in the database into a format that the virtual reality engine can recognize, such as mesh data, material data, and physical properties. Through this integration, the virtual reality engine can directly access the simulation data, thereby achieving real-time simulation scene presentation.

[0082] S32. Design of loading algorithm. To ensure fast loading and smooth display of simulation data, an efficient data loading algorithm is designed and implemented. The algorithm can dynamically select the simulation data set closest to the parameters set by the user and load it into the virtual reality environment in a short time. The loading algorithm adopts multi-threading technology, space- and time-based progressive loading and multi-threaded parallel processing methods to reduce system resource consumption, optimize rendering performance, and improve data loading speed. At the same time, memory caching technology is used to pre-load commonly used data into memory to reduce data reading delays and improve display fluency.

[0083] In a specific embodiment, a simulation data set generated by fluid simulation software is imported into a virtual reality engine by constructing an interface. The virtual reality engine reads the simulation data by loading an algorithm.

[0084] In the process of integrating the simulation database with the virtual reality engine, multi-threading technology is used to improve the loading speed, and memory cache technology is used to reduce the delay in data reading. In order to optimize performance, the system supports progressive loading, prioritizes loading of key data within the user's field of view, and delays loading of data in distant scenes to ensure the smoothness of simulation display. Build a data loading interface, interface development: Develop a data loading interface to import simulation data into the runtime environment of the Unreal Engine. Write data loading scripts through Blueprint (Bluepr int) and C++ code to achieve seamless connection between simulation data and the Unreal Engine. The interface needs to have data parsing capabilities to parse various physical parameters in the data (such as flow rate, pressure, etc.)

[0085] In order to improve the loading speed, a memory cache mechanism can be introduced into the system to preload frequently used simulation data sets into memory to reduce the data reading delay during each loading. For large-scale simulation data, an appropriate cache size can be set to balance memory usage and performance. Multi-threaded data loading: In Unreal Engine, parallel loading of data is achieved through multi-threading technology. In addition to the main rendering thread, additional threads are used to handle the data reading, parsing, and loading process to avoid the loading operation affecting the rendering frame rate of the scene.

[0086] S4. Perform data calculations based on actual needs, including when the user inputs parameters, the system will select the two simulation data sets closest to it and generate new simulation results through interpolation calculations.

[0087] Specifically, for the specific parameters input by the user, since these parameters are usually not completely consistent with the key data points that have been calculated in step S2, interpolation calculations are required to obtain more accurate simulation results. The core of this step is to select two sets of simulation data sets that are closest to the user parameters in the multidimensional data matrix, perform interpolation calculations, and generate new simulation data. Through this dynamic data loading and calculation, the simulation system can respond to different engineering needs more flexibly.

[0088] In a specific embodiment, the user can input specific parameters, and the system selects the two closest sets of simulation data sets through the nearest neighbor search algorithm and performs interpolation calculations to generate simulation results that meet the actual parameters. The interpolation algorithm can select linear interpolation or high-order interpolation according to the complexity of the data to ensure a high degree of match between the calculation results and the actual situation. The interpolated data not only ensures the continuity of the simulation data, but also captures the impact of parameter changes on fluid behavior, thereby improving the credibility of the simulation results.

[0089] like Figure 3 As shown, the specific steps include:

[0090] S41, parameter matching and nearest neighbor data selection, including when the user sets specific leakage parameters in the virtual reality environment, the system first searches for two simulation data sets closest to the user input parameters in the pre-calculated multi-dimensional simulation data matrix; since the simulation data matrix is ​​discrete, the parameters set by the user are usually between two or more key data points, so it is necessary to select the two closest data sets.

[0091] The system uses the nearest neighbor search algorithm to quickly locate the two sets of simulation data sets that are closest to the user's parameters. These data sets may come from adjacent different parameter combinations, such as different pressures, flows, or oil, gas, and water ratios. Through this matching, the system can ensure that the selected data set is as close as possible to the conditions set by the user, thus providing a reliable basis for subsequent interpolation calculations.

[0092] In a specific embodiment, the user can input the pressure, flow rate, water depth and other parameters of the leakage point through the interface, and the system will parse the parameters input by the user and convert them into a numerical format that can be recognized by the computing system. These parameters will be used as input conditions for the next step of data calculation. Multidimensional data matching: Since the simulation parameters are multidimensional, the system needs to match not only the pressure, but also other parameters (such as flow rate, water depth, etc.) at the same time. Through the nearest neighbor search algorithm, the system can find multiple simulation data points closest to the user input in the multidimensional space.

[0093] S42, multi-dimensional interpolation calculation, the system performs multi-dimensional interpolation calculation on the data to generate a new data set. The interpolation algorithm includes linear interpolation, bilinear interpolation or high-order interpolation algorithm to ensure that the generated new data can highly match the parameters input by the user.

[0094] Specifically, after determining the two closest sets of simulation data sets, the system will perform multi-dimensional interpolation calculations on these data sets. The interpolation algorithm can use linear interpolation, bilinear interpolation, or high-order interpolation methods, depending on the dimension and complexity of the data set. Through interpolation calculations, the system can generate a new data set that more accurately reflects the leakage parameters set by the user.

[0095] The process of multidimensional interpolation involves calculating the data of each physical quantity (such as pressure field, velocity field, temperature field, etc.) one by one. The interpolated results not only maintain the continuity of the simulation data, but also capture the subtle effects of parameter changes on fluid behavior, thereby improving the accuracy and credibility of the simulation results.

[0096] In a specific embodiment, different interpolation methods are selected according to the physical characteristics of the parameters: linear interpolation: for simple parameter changes (such as water depth), a linear interpolation algorithm can be used to calculate new data; high-order interpolation: if the changes between data points are more complex, or the nonlinear characteristics are obvious, quadratic interpolation, cubic interpolation or other high-order interpolation methods can be used. For example, in the multidimensional space of pressure, flow, and water depth, Lagrange interpolation or spline interpolation is used to smoothly fit multiple data points to generate more accurate simulation data.

[0097] S43. Data loading optimization.

[0098] In order to maintain the smoothness of the virtual reality scene without sacrificing performance, this embodiment reasonably sets the frequency of data loading. The loading frequency depends on the real-time requirements of user interaction and the computing power of the hardware. By dynamically adjusting the loading frequency, the system can find the best balance between high interactivity and high visual performance. In actual applications, when the user changes the parameter settings, the system automatically adjusts the loading frequency according to the magnitude of the change. For example, larger parameter changes will trigger higher-frequency data loading to ensure timely updating of simulation results; while minor parameter changes will trigger lower-frequency loading to save computing resources.

[0099] In a specific embodiment, loading optimization is performed through a variety of methods, including parallel computing: using multi-threading technology and GPU acceleration to perform large-scale data calculations to ensure that the calculation results can be generated in real time; data caching and optimization: for commonly used parameter combinations, the system can calculate in advance and cache the results. When the user enters these commonly used parameters, the cached data is directly called instead of real-time calculations, thereby improving the system response speed; adaptive interpolation: in complex scenes, the accuracy of the interpolation algorithm can be dynamically adjusted according to the frequency of user operations and the complexity of parameter changes. When the parameters are adjusted frequently, the system can reduce the interpolation accuracy to increase the speed; when the user parameters are stable, high-precision calculations are performed again; intelligent unloading mechanism: when loading new data, the intelligent unloading mechanism automatically clears old data that is no longer needed to release memory resources. The system can determine which data should be unloaded and which data should be retained based on factors such as scene changes and user perspectives.

[0100] S5. Present data in a virtual reality engine, including simulating the underwater environment and the diffusion behavior of oil and natural gas during leakage through a virtual reality engine.

[0101] Specifically, the new simulation data obtained by interpolation calculation in step S4 is loaded into the virtual reality engine for visualization. Through shader writing, particle emitters, post-processing, material systems and lighting systems, the shaders, particle systems, material systems and lighting systems in the virtual reality engine are used to realistically simulate and reproduce the underwater environment and the behavior of oil and natural gas during the leakage process, and realize the dynamic simulation of complex phenomena such as underwater lighting, oil film diffusion, and bubble rise.

[0102] For example, the particle system is used to simulate the diffusion path of oil in water, the shader is used to adjust the transparency and refraction effect of the water body, and the lighting system is used to simulate the attenuation and scattering effect of underwater light. The system can also dynamically adjust the simulation parameters according to user interaction and update the display results in real time.

[0103] The specific steps include:

[0104] S51. Basic scene performance refers to the environmental state of the underwater production system. The production content includes scene model, lighting, and post-processing. After the scene model is imported, the lighting setting is performed, and the "intensity attenuation curve" of the light source is adjusted to make the light decrease with depth.

[0105] At the same time, add "Light Bloom" and "Volumetric Lighting" to the light source in the engine, so that the light will show a soft scattering effect in the water, creating an underwater atmosphere where the light gradually dissipates. Reset the refraction and reflection effects in the post-processing volume.

[0106] In the material editor, the creators need to use the "Screen Space Refraction" function of Unreal Engine. By setting the refractive index to simulate the bending of light in water, underwater objects appear to be distorted, thus achieving a realistic visual effect.

[0107] To further enhance the realism, add a "surface ripple" animation effect, which is achieved by "VertexOffset" technology to make the water surface ripple. Apply a Color Correction filter to the scene to simulate the color changes of water bodies at different depths, such as blue-green in shallow water to dark blue or black in deep water.

[0108] You can also adjust the hue of the scene through "Tint Adjustment" to make it closer to the natural underwater color. At the same time, suspended matter and particles are also typical elements of the underwater environment. The particle system of Unreal Engine allows the production staff to create suspended particle effects to simulate plankton or suspended particles in the water. These particles can float randomly and produce tiny shadows or halos according to the light intensity, increasing the three-dimensional sense of the scene.

[0109] S52. Underwater oil droplet performance, particle system selection: Use the Niagara particle system of the Unreal Engine to create particles representing oil molecules to simulate the rise and diffusion of oil in the water after a leak. Buoyancy and gravity settings: Apply appropriate buoyancy to the particles to make them rise in the water. Adjust the gravity effect to ensure that the particles rise to the surface of the water in an appropriate time. Diffusion process control: Simulate the diffusion process of oil in the water by setting the initial velocity and diffusion direction of the particles. The diffusion speed of the particles is closely related to the fluidity of the seawater. The effects of ocean currents and internal waves can be simulated through the "fluid volume" or "wind field" functions in the engine. Particle life and size change: Set the life cycle of the particles. As they gradually diffuse, the particles gradually become smaller and disappear, simulating the effect of the oil film gradually becoming thinner during the diffusion process.

[0110] Oil film material settings: Use the Unreal Engine's material editor to create an oil film material with high transparency and reflectivity. Simulate the reflection and refraction of light on the oil film, so that the oil film presents different visual effects under different lighting conditions. Dynamic oil film diffusion: Use dynamic UV mapping of the material to simulate the diffusion behavior of the oil film on the water surface. Use vertex animation or texture coordinate offset technology to make the oil film gradually expand over time while retaining certain details.

[0111] S53. Underwater natural gas performance, bubble particle system: Use particle emitters to create bubble effects to simulate the process of natural gas rising after leakage. The rising speed of bubbles should be set according to the water depth and buoyancy, and the particle system needs to support the generation and rise of multi-level bubbles. Bubble bursting effect: When bubbles approach the water surface, the bursting and dissipation effects of bubbles are simulated through particle life control and transparency changes.

[0112] In a specific embodiment, when the bubble approaches the water surface, the life cycle control of the particle system is used to simulate the process of bubble bursting and dissipation. The "transparency gradient" function is used to make the bubble gradually transparent and disappear when it bursts, thereby enhancing visual continuity.

[0113] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for simulating leakage of an underwater production system, characterized in that: include: Simulation data point setting, including selecting and setting data points of multiple target parameters and constructing a multi-dimensional parameter matrix; Fluid simulation software calculates data, including using fluid simulation software to simulate and calculate the fluid dynamic behavior of the leakage process on the constructed multi-dimensional parameter matrix, and generating a simulation data set; Loading data into a virtual reality engine, including loading the simulation data set into the virtual reality engine to achieve dynamic real-time display; Perform data calculations based on actual needs, including when the user inputs parameters, the system will select the two closest simulation data sets and generate new simulation results through interpolation calculations; Data presentation is performed in a virtual reality engine, including simulation of the underwater environment and the diffusion behavior of oil and natural gas during leakage through a virtual reality engine.

2. The underwater production system leakage simulation method according to claim 1, characterized in that: The simulation data point setting adopts a layered setting data point method, and the target parameters include the pressure at the leakage point, the cross-sectional area of ​​the leakage point, the leakage flow rate, the water depth at the leakage point, and the seabed wave current.

3. The underwater production system leakage simulation method according to claim 1 or 2, characterized in that: The fluid simulation software calculates data, including: Model building, including automatic construction of physical models of leak scenarios based on imported data; Solver settings, including setting relevant parameters required for simulation calculation after the model is built; Simulation parameter setting and calculation, importing the multi-dimensional parameter matrix into fluid simulation software and performing simulation calculation; Data storage and management, after the simulation calculation is completed, all calculation results will be automatically saved in the database.

4. The underwater production system leakage simulation method according to claim 1 or 2, characterized in that: The step of loading data in the virtual reality engine includes: Integration of simulation database and VR engine, including importing optimized simulation data set into VR engine; The loading algorithm is designed to dynamically select the simulation data set closest to the parameters set by the user and load it into the virtual reality environment.

5. The underwater production system leakage simulation method according to claim 4, characterized in that: The loading algorithm adopts a progressive loading method based on space and time and a parallel processing method based on multi-threading.

6. The underwater production system leakage simulation method according to claim 1 or 2, characterized in that: The data calculation according to actual needs includes: Parameter matching and nearest neighbor data selection, including that when the user sets specific leakage parameters in the virtual reality environment, the system first searches for two simulation data sets closest to the user input parameters in the pre-calculated multi-dimensional simulation data matrix; Multi-dimensional interpolation calculation: the system uses a difference algorithm to perform multi-dimensional interpolation calculations on the data to generate a new data set; Data loading optimization.

7. The underwater production system leakage simulation method according to claim 6, characterized in that: The system first searches for two simulation data sets closest to the user input parameters in a pre-calculated multi-dimensional simulation data matrix, and the system uses a nearest neighbor search algorithm.

8. The underwater production system leakage simulation method according to claim 6, characterized in that: The interpolation algorithm includes linear interpolation, bilinear interpolation or high-order interpolation algorithm.

9. The underwater production system leakage simulation method according to claim 6, characterized in that: The data loading optimization includes: parallel computing, data caching and optimization, adaptive interpolation and intelligent unloading mechanism.

10. The underwater production system leakage simulation method according to claim 1 or 2, characterized in that: The data representation in the virtual reality engine includes simulating leakage of the underwater production system through a shader, a particle system, a material system and a lighting system in the virtual reality engine.

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