Three-dimensional model construction method and system for underground water flow direction detection

Abstract

The invention discloses a three-dimensional model construction method and system for underground water flow direction detection, and the system comprises a data collection and transmission module, a data processing and fusion module, a geological modeling and water flow field generation module, a model verification and dynamic updating module, and a visualization and interaction module. The data processing and fusion module is used for multi-source data preprocessing, the geological modeling and water flow field generation module is used for constructing a three-dimensional geological structure model and generating an underground water flow field, the model verification and dynamic updating module is used for model result verification and real-time updating, and the visualization and interaction module is used for data three-dimensional display. The invention provides a multi-source coupled heterogeneous three-dimensional geologic body parameterized dynamic modeling algorithm to construct a three-dimensional geologic structure model, provides a heterogeneous groundwater space-time dynamic streamline tracking simulation algorithm to generate a groundwater flow field, and provides a better scheme for a three-dimensional model construction method and system for groundwater flow direction detection.

Description

Technical Field

[0001] This invention relates to the fields of geological modeling and hydrological numerical simulation, specifically to a method and system for constructing a three-dimensional model for detecting groundwater flow direction. Background Technology

[0002] Geological modeling technology is an interdisciplinary technique that transforms geological data into quantitative and visualized three-dimensional digital models through mathematical algorithms to accurately represent the spatial distribution and attribute distribution of underground structures. Geological modeling involves the cross-disciplinary integration of geology, surveying, geophysics, computer graphics, and spatial statistics. Its core is to utilize diverse and heterogeneous data such as borehole, outcrop, seismic exploration, and remote sensing data, and through Kriging interpolation, Delaunay triangulation, and implicit modeling algorithms, to transform geologists' knowledge and inferences into quantitative three-dimensional digital models. This overcomes the challenges of the invisibility and spatial heterogeneity of underground media, enabling the visualization and quantitative analysis of the spatial distribution and interrelationships of strata, structures, lithology, and physical properties. The collaboration of these technologies lays a solid technical foundation for the construction of three-dimensional geological structure models.

[0003] Hydrological numerical simulation technology is a core decision-making and analysis technique based on physical laws and mathematical methods. It uses computers to solve partial differential equations that control groundwater flow and solute transport, thereby quantitatively characterizing and predicting the spatiotemporal distribution and evolution of water resources under complex geological environments. Hydrological numerical simulation technology involves the cross-integration of groundwater dynamics, computational mathematics, and computer science. Its core is to use numerical discretization methods such as finite difference and finite element methods to transform the partial differential control equations describing groundwater flow and solute transport into a large-scale linear algebraic equation system. This system is then solved using efficient iterative algorithms and high-performance computing technology. This overcomes the analytical solution difficulties caused by the heterogeneity of aquifers and complex boundary conditions, and enables quantitative prediction and dynamic simulation of groundwater resource quantity, water quality evolution, and environmental impact. The continuous development of these technologies has laid a solid technical foundation for the generation of water flow fields and the dynamic simulation of groundwater flow direction. Summary of the Invention

[0004] To address the aforementioned problems, this invention aims to provide a method and system for constructing a three-dimensional model for detecting groundwater flow direction.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method and system for constructing a three-dimensional model for groundwater flow direction detection, comprising a data acquisition and transmission module, a data processing and fusion module, a geological modeling and flow field generation module, a model verification and dynamic update module, and a visualization and interaction module. The data acquisition and transmission module is used to acquire multi-source hydrogeological data. The data processing and fusion module is used to clean, transform, and fuse multi-source data. The geological modeling and flow field generation module includes a three-dimensional geological modeling unit and a groundwater flow field generation unit. The three-dimensional geological modeling unit proposes a parameterized dynamic modeling algorithm for multi-source coupled heterogeneous three-dimensional geological bodies to construct a three-dimensional geological structure model. The groundwater flow field generation unit proposes a non-homogeneous groundwater spatiotemporal dynamic streamline tracking simulation algorithm to calculate and generate the groundwater flow field. The model verification and dynamic update module includes a model verification and optimization unit and a dynamic update and prediction unit. The model verification and optimization unit is used to verify the simulation results of the model. The dynamic update and prediction unit is used for real-time updating and long-term prediction of the model. The visualization and interaction module is used for three-dimensional display of the data.

[0006] Furthermore, the data acquisition and transmission module is used to collect multi-source hydrogeological data. By using drones equipped with multispectral sensors or lidar, it can quickly collect large-scale, high-precision surface topographic data, precise coordinates of monitoring wells, and high-definition images of the surface environment. Through the wireless sensor network deployed in the monitoring wells, it can collect groundwater dynamic data in real time and automatically. The data is then remotely transmitted to the data center through IoT technology to ensure the timeliness of the data. It can also receive and integrate data from traditional geological exploration work to achieve unified access to multi-source heterogeneous data.

[0007] Furthermore, the data processing and fusion module is used to clean, transform, and fuse multi-source data, remove sensor outliers and duplicate data, unify the coordinate system of all data, accurately correlate discrete water level data with corresponding spatial coordinates to form spatialized data points, and generate a continuous and smooth water level distribution surface.

[0008] Furthermore, the 3D geological modeling unit proposes a parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies to construct a 3D geological structure model, connecting the same stratum interface of different boreholes to form the top and bottom plate surfaces of the strata, and transforming multiple stratum surfaces into 3D solid models through voxelization / boundary representation.

[0009] Furthermore, the parameterized dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies is as follows: First, the unified coordinate system processed by the data processing and fusion module is represented as... ,in, These are the X-axis coordinates in the new coordinate system after the transformation. These are the Y-axis coordinates in the new coordinate system after the transformation. To control the scaling factor in the X direction of the new coordinate system, To control the shearing factor of the Y value in the old coordinate system, To control the shearing factor of the X values ​​in the old coordinate system, To control the scaling factor in the Y direction of the new coordinate system, This represents the translation along the X-axis. This represents the translation along the Y-axis. Let X be the X-axis coordinate of the point to be transformed in the old coordinate system. The Y-axis coordinates of the points to be transformed in the old coordinate system are given. Then, each borehole is layered according to its formation ID, and the top / bottom elevations of each layer are extracted. The interface point set of the same formation is then processed. Constructing a triangular network for , ,in, For the set of stratigraphic interface points, The coordinates of the points are A single point, , , These are the three vertices of the triangular mesh. It is an irregular triangular network. Just passing through the point , , circumcircle, For intersection operations, For an empty set, insert virtual control points in the un-drilled region. , ,in, The elevation value of the virtual control point. The number of known points involved in the calculation. For the first The weights of the known points For the first The elevation values ​​of a known point. For virtual points With known points The Euclidean distance between them The attenuation coefficient is then used to stitch adjacent strata TINs together into a closed polyhedron to represent complex geological structures, i.e. , ,in, For the construction of a three-dimensional solid model, The total number of faces, The union operation is used to combine multiple faces into a solid. For the first A triangular mesh surface, Let be the set of vertices of the face. Let be the set of edges of the face. To obtain the topological information of the surface, the model domain is then divided into a voxel mesh, i.e. , ,in, For index voxel unit mesh, voxel unit The attribute value, For the land The code of the layer, voxel unit The coordinates of the center point, For the first Each geological entity is analyzed, and then complex geological structures are processed. Fault lines are interpreted through geological profiles, and fault surfaces are inserted into TINs to separate the strata on both sides. Lenses are locally densified using TINs, and the surface convexity is adjusted by control points. Finally, the stratigraphic closure is verified using the Euler-Poincaré formula. ,in, The total number of vertices in the triangular mesh. The total number of sides of the triangular mesh. The total number of faces of the triangular mesh. The number of connected 3D entities. The number of voids in the entity; to optimize the formation elevation, the TIN vertex position is adjusted based on the newly added boreholes. ,in, As vertices Elevation adjustment amount, For learning rate, For partial derivative operations, For the predicted elevation value, The observed elevation value, Perform square norm operations, and then assign hydrological properties to each volume element / surface element, i.e. , ,in, For grid cells Permeability coefficient in the x-direction, This is a lookup function that retrieves values ​​from an attribute database based on geological codes. This is the type keyword for the permeability coefficient attribute. For grid cells water storage rate, As the type keyword for water storage rate attribute, the parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies first introduces the gradient descent method to automatically adjust the elevation of the vertices of the triangular mesh based on newly added borehole data, and dynamically optimizes the model by incorporating new borehole data in real time / periodically. Then, the Euler-Poincaré formula is proposed for automated topology verification to quickly identify and quantify topological defects. Then, for the complex geological features of faults and lenses, multi-step refinement processing is adopted to avoid errors in the simulation of the flow field near the fault and improve the characterization of heterogeneity, thereby realizing the construction of a 3D geological structure model.

[0010] Furthermore, the groundwater flow field generation unit proposes a spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater to calculate and generate the groundwater flow field, dynamically simulating the flow direction and isostatic surfaces.

[0011] Furthermore, the specific algorithm for simulating the spatiotemporal dynamic streamlines of heterogeneous groundwater is as follows: First, the three-dimensional geological structure model constructed from three-dimensional geological modeling units is transformed into discretized computational units that can be processed by a computer, that is, the three-dimensional model region is divided into... A regular cuboid mesh element, wherein, This represents the total number of mesh elements in the x-direction of the model in three-dimensional space. This represents the total number of mesh elements in the y-direction of the model in three-dimensional space. Let be the total number of mesh elements in the z-direction of the model in 3D space, and let the coordinates of the center point of each mesh element be denoted as . ,in, , , ,in, The element number in the x-direction is the center point of the mesh cell. The element number in the y-direction is the center point of the mesh cell. The element number of the center point of the mesh element in the z-direction, for each mesh element. Assigning hydrogeological parameters, primarily permeability parameters , , and water storage rate ,in, Let be the permeability coefficient in the x-direction. Let be the permeability coefficient in the y-direction. Given the permeability coefficient in the z-direction, a discrete, parameterized three-dimensional grid system can be obtained. Then, the partial differential governing equations describing the three-dimensional unsteady flow motion of groundwater are established as follows: ,in, Let x be the component of the permeability coefficient in the x-direction. Let be the component of the permeability coefficient in the y-direction. Let be the component of the permeability coefficient in the z-direction. For the water head, Let be the spatial gradient of the water head in the x-direction. Let be the spatial gradient of the water head in the y-direction. Let be the spatial gradient of the water head in the z-direction. Flow rate per unit volume For water storage rate, Let be the rate of change of water head over time, and set boundary conditions, defining the water head boundary as . ,in, , , For spatial coordinates, For time variables, To determine the geometric location of the head boundary, For the boundary coordinates on and time Groundwater head The value, Let the head on the boundary be a function of the head distribution over time / space, and the constant flow boundary be... ,in, Permeability coefficient, Let be the gradient of the water head along the direction normal to the boundary. For time step index, i.e. ,in, For time step, To determine the geometric location of the constant flow boundary, The flow rate intensity function is given by the water-impermeable boundary. ,in, The location of the impermeable boundary is determined. Then, the partial differential equation is transformed into a large system of linear equations using a discretization method and solved. The derivative terms in the governing equations are approximated using a central difference scheme, and the differential equations are discretized into... ,in, , , For located and The permeability coefficient values ​​in the x, y, and z directions at the interface between two grid cells. For the current grid cell At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, The size of the mesh cell in the x-direction. Let be the size of the mesh element in the y-direction. Let Z be the size of the mesh element in the z-direction. For the current grid cell Flow rate per unit volume For the current grid cell water storage rate, For the current grid cell At time step water head value, For each grid cell, an equation is written for each time step. The linear equations of all grid points are combined to form a large sparse linear equation system. This system is then iteratively solved to obtain the three-dimensional head field at the discrete time step. From this three-dimensional head field, intuitive flow direction and velocity information are extracted. According to Darcy's law, the seepage velocity vector at any point in space is... In actual numerical calculations, The seepage velocity vector, Let be the permeability tensor. As the gradient operator, at the center of each grid cell, the average velocity vector of the pore water is... , , ,in, Let x be the component of the average velocity vector of pore water in the x-direction. Let be the component of the average velocity vector of pore water in the y-direction. Let Z be the component of the average velocity vector of pore water in the z-direction. In the velocity field, starting from a certain starting point... Initial streamline path The system of ordinary differential equations is , , ,in, For streamlined paths, Let be the position coordinates of the fluid particle in the x-direction. Let be the position coordinates of the fluid particle in the y-direction. Let be the position coordinates of the fluid particle in the z-direction. Let be the rate of change of position of the fluid particle along the x-direction. Let be the rate of change of position of the fluid particle along the y-direction. Let z be the rate of change of position of a fluid particle along the z-direction. For water volume seepage velocity in the direction, For water volume seepage velocity in the direction, For water volume The seepage velocity in the direction is obtained by solving the system of equations using numerical integration, resulting in streamlines, which are the trajectories of tracer particles moving with the water flow. The spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater proposes to introduce the harmonic mean formula to calculate interface parameters during the discretization of differential equations to solve the distortion in flow calculation at abrupt interface changes. Then, it proposes three boundaries: constant head, constant flow, and impermeable boundary, to solve the distortion caused by leakage at impermeable boundaries and dynamic river boundary responses. Finally, it proposes a system of ordinary differential equations of particle kinematics to adaptively track streamlines and reduce tracer transport time errors, thereby realizing the generation of groundwater flow field and dynamic simulation of groundwater flow direction.

[0012] Furthermore, the model validation and optimization unit is used to validate the simulation results of the model. By injecting artificial tracers / detecting environmental isotopes on-site, the accuracy of the flow direction and velocity is verified by comparing the actual monitoring data with the model's predicted transport paths and times.

[0013] Furthermore, the dynamic update and prediction unit is used for real-time updates and long-term predictions of the model. When new real-time monitoring data is received, the system can automatically trigger local model updates, quickly refresh the flow field map, achieve dynamic mapping like a digital twin, and predict future water level change trends based on historical water level data using time series analysis algorithms and machine learning models, and generate flow field prediction maps under different seasonal / climate scenarios.

[0014] Furthermore, the visualization and interaction module is used to present complex models and data in intuitive and easy-to-understand 3D graphics. It receives the streamline dataset output from the groundwater flow field generation unit and displays the spatial movement pattern of groundwater in all aspects through 3D visualization rendering. At the same time, users can click on any location to query the water level and water quality data at that location, drag the timeline to view the historical changes / future prediction animations of the flow field, and conduct risk analysis.

[0015] Compared with the prior art, the beneficial effects of the present invention are:

[0016] 1. This invention proposes a parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies to construct a 3D geological structure model. The innovation of this invention lies in the fact that the multi-source coupled heterogeneous 3D geological body parametric dynamic modeling algorithm first introduces the gradient descent method to automatically adjust the elevation of the vertices of the triangular mesh based on newly added borehole data, so as to dynamically optimize the model by incorporating new borehole data in real time / periodically. Then, it proposes the Euler-Poincaré formula for automated topology verification to quickly identify and quantify topological defects. Then, it adopts multi-step refinement processing for complex geological features such as faults and lenses to avoid errors in the simulation of flow fields near faults and improve the characterization of heterogeneity, thereby realizing the construction of a 3D geological structure model.

[0017] 2. A spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater is proposed to calculate and generate the groundwater flow field, dynamically simulate the flow direction, and the equipotential surface. The innovation of this invention lies in the fact that the spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater introduces the harmonic mean formula to calculate the interface parameters during the discretization process of the differential equation to solve the distortion of the flow calculation at the interface of abrupt change in the medium. Then, it proposes three boundaries of constant head, constant flow, and impermeable boundary to solve the distortion of leakage at the impermeable boundary and dynamic river boundary response. Finally, it proposes a set of ordinary differential equations of particle kinematics to adaptively track streamlines and reduce the tracer transport time error, thereby realizing the generation of the groundwater flow field and the dynamic simulation of the groundwater flow direction. Attached Figure Description

[0018] The invention will be further illustrated with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the invention. For those skilled in the art, other drawings can be obtained based on the following drawings without any creative effort.

[0019] Figure 1 This is a schematic diagram of the structure of the present invention. Detailed Implementation

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

[0021] A method and system for constructing a 3D model for groundwater flow direction detection includes a data acquisition and transmission module, a data processing and fusion module, a geological modeling and flow field generation module, a model verification and dynamic update module, and a visualization and interaction module. The data acquisition and transmission module is used to collect multi-source hydrogeological data. The data processing and fusion module is used to clean, transform, and fuse multi-source data. The geological modeling and flow field generation module includes a 3D geological modeling unit and a groundwater flow field generation unit. The 3D geological modeling unit proposes a parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies to construct a 3D geological structure model. The groundwater flow field generation unit proposes a spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater to calculate and generate the groundwater flow field. The model verification and dynamic update module includes a model verification and optimization unit and a dynamic update and prediction unit. The model verification and optimization unit is used to verify the simulation results of the model. The dynamic update and prediction unit is used for real-time updates and long-term predictions of the model. The visualization and interaction module is used for 3D display of the data.

[0022] Preferably, the data acquisition and transmission module is used to collect multi-source hydrogeological data. By using a drone equipped with a multispectral sensor or lidar, it can quickly collect large-scale, high-precision surface topographic data, accurate coordinates of monitoring wells, and high-definition images of the surface environment, providing a precise spatial geographic framework for the model. Through a wireless sensor network deployed in the monitoring wells, it can collect groundwater dynamic data in real time and automatically, including water level depth and water temperature, and remotely transmit the data to the data center through IoT technology to ensure the timeliness of the data. It can also receive and integrate data from traditional geological exploration work, such as borehole rock and soil layering information, stratum lithology, permeability coefficient, porosity, and other hydrogeological parameters, to achieve unified access to multi-source heterogeneous data.

[0023] Preferably, the data processing and fusion module is used to clean, transform and fuse multi-source data, remove sensor outliers and duplicate data, unify the coordinate system of all data, accurately correlate discrete water level data with corresponding spatial coordinates to form spatialized data points, and generate a continuous and smooth water level distribution surface.

[0024] Preferably, the three-dimensional geological modeling unit proposes a parametric dynamic modeling algorithm for multi-source coupled heterogeneous three-dimensional geological bodies to construct a three-dimensional geological structure model, connects the same stratum interface of different boreholes to form the top and bottom plate surfaces of the strata, and transforms multiple stratum surfaces into three-dimensional solid models through voxelization / boundary representation method, intuitively showing the spatial distribution relationship of unconfined aquifers, confined aquifers and impermeable layers.

[0025] Specifically, the parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies is as follows: First, the unified coordinate system processed by the data processing and fusion module is represented as... ,in, These are the X-axis coordinates in the new coordinate system after the transformation. These are the Y-axis coordinates in the new coordinate system after the transformation. To control the scaling factor in the X direction of the new coordinate system, To control the shearing factor of the Y value in the old coordinate system, To control the shearing factor of the X values ​​in the old coordinate system, To control the scaling factor in the Y direction of the new coordinate system, This represents the translation along the X-axis. This represents the translation along the Y-axis. Let X be the X-axis coordinate of the point to be transformed in the old coordinate system. The Y-axis coordinates of the points to be transformed in the old coordinate system are given. Then, each borehole is layered according to its formation ID, and the top / bottom elevations of each layer are extracted. The interface point set of the same formation is then processed. Constructing a triangular network for , ,in, This is the set of formation interface points, i.e., the set of elevation data for all borehole points. The coordinates of the points are A single point, , , These are the three vertices of the triangular mesh. It is an irregular triangular network. Just passing through the point , , circumcircle, For intersection operations, For an empty set, insert virtual control points in the un-drilled region. , ,in, The elevation value of the virtual control point. The number of known points involved in the calculation. For the first The weights of the known points For the first The elevation values ​​of a known point. For virtual points With known points The Euclidean distance between them The attenuation coefficient is then used to stitch adjacent strata TINs together into a closed polyhedron to represent complex geological structures, i.e. , ,in, For the construction of a three-dimensional solid model, The total number of faces, The union operation is used to combine multiple faces into a solid. For the first A triangular mesh surface, Let be the set of vertices of the face. Let be the set of edges of the face. To obtain the topological information of the surface, the model domain is then divided into a voxel mesh, i.e. , ,in, For index voxel unit mesh, voxel unit The attribute value, For the land The code of the layer, voxel unit The coordinates of the center point, For the first Each geological entity is analyzed, and then complex geological structures are processed. Fault lines are interpreted through geological profiles, and fault surfaces are inserted into TINs to separate the strata on both sides. Lenses are locally densified using TINs, and the surface convexity is adjusted by control points. Finally, the stratigraphic closure is verified using the Euler-Poincaré formula. ,in, The total number of vertices in the triangular mesh. The total number of sides of the triangular mesh. The total number of faces of the triangular mesh. The number of connected 3D entities. The number of voids in the entity; to optimize the formation elevation, the TIN vertex position is adjusted based on the newly added boreholes. ,in, As vertices Elevation adjustment amount, For learning rate, For partial derivative operations, For the predicted elevation value, The observed elevation value, Perform square norm operations, and then assign hydrological properties to each volume element / surface element, i.e. , ,in, For grid cells Permeability coefficient in the x-direction, This is a lookup function that retrieves values ​​from an attribute database based on geological codes. This is the type keyword for the permeability coefficient attribute. For grid cells water storage rate, As the type keyword for water storage rate attribute, the parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies first introduces the gradient descent method to automatically adjust the elevation of the vertices of the triangular mesh based on newly added borehole data, and dynamically optimizes the model by incorporating new borehole data in real time / periodically. Then, the Euler-Poincaré formula is proposed for automated topology verification to quickly identify and quantify topological defects. Then, for the complex geological features of faults and lenses, multi-step refinement processing is adopted to avoid errors in the simulation of the flow field near the fault and improve the characterization of heterogeneity, thereby realizing the construction of a 3D geological structure model.

[0026] Preferably, the groundwater flow field generation unit proposes a spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater to calculate and generate the groundwater flow field, dynamically simulating the flow direction and isostatic surfaces.

[0027] Specifically, the simulation algorithm for spatiotemporal dynamic streamline tracing in heterogeneous groundwater is as follows: First, the three-dimensional geological structure model constructed from three-dimensional geological modeling units is transformed into discretized computational units that can be processed by a computer, that is, the three-dimensional model region is divided into... A regular cuboid mesh element, wherein, This represents the total number of mesh elements in the x-direction of the model in three-dimensional space. This represents the total number of mesh elements in the y-direction of the model in three-dimensional space. Let be the total number of mesh elements in the z-direction of the model in 3D space, and let the coordinates of the center point of each mesh element be denoted as . ,in, , , ,in, The element number in the x-direction is the center point of the mesh cell. The element number in the y-direction is the center point of the mesh cell. The element number of the center point of the mesh element in the z-direction, for each mesh element. Assigning hydrogeological parameters, primarily permeability parameters , , and water storage rate ,in, Let be the permeability coefficient in the x-direction. Let be the permeability coefficient in the y-direction. Given the permeability coefficient in the z-direction, a discrete, parameterized three-dimensional grid system can be obtained. Then, the partial differential governing equations describing the three-dimensional unsteady flow motion of groundwater are established as follows: ,in, Let x be the component of the permeability coefficient in the x-direction. Let be the component of the permeability coefficient in the y-direction. Let be the component of the permeability coefficient in the z-direction. For the water head, Let be the spatial gradient of the water head in the x-direction. Let be the spatial gradient of the water head in the y-direction. Let be the spatial gradient of the water head in the z-direction. Flow rate per unit volume For water storage rate, Let be the rate of change of water head over time, and set boundary conditions, defining the water head boundary as . ,in, , , For spatial coordinates, For time variables, To determine the geometric location of the head boundary, For the boundary coordinates on and time Groundwater head The value, Let the head on the boundary be a function of the head distribution over time / space, and the constant flow boundary be... ,in, Permeability coefficient, Let be the gradient of the water head along the direction normal to the boundary. For time step index, i.e. ,in, For time step, To determine the geometric location of the constant flow boundary, The flow rate intensity function is given by the water-impermeable boundary. ,in, The location of the impermeable boundary is determined. Then, the partial differential equation is transformed into a large system of linear equations using a discretization method and solved. The derivative terms in the governing equations are approximated using a central difference scheme, and the differential equations are discretized into... ,in, , , For located and The permeability coefficient values ​​in the x, y, and z directions at the interface between two grid cells. For the current grid cell At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, The size of the mesh cell in the x-direction. Let be the size of the mesh element in the y-direction. Let Z be the size of the mesh element in the z-direction. For the current grid cell Flow rate per unit volume For the current grid cell water storage rate, For the current grid cell At time step water head value, For each grid cell, an equation is written for each time step. The linear equations of all grid points are combined to form a large sparse linear equation system. This system is then iteratively solved to obtain the three-dimensional head field at the discrete time step. From this three-dimensional head field, intuitive flow direction and velocity information are extracted. According to Darcy's law, the seepage velocity vector at any point in space is... In actual numerical calculations, The seepage velocity vector, Let be the permeability tensor. As the gradient operator, at the center of each grid cell, the average velocity vector of the pore water is... , , ,in, Let x be the component of the average velocity vector of pore water in the x-direction. Let be the component of the average velocity vector of pore water in the y-direction. This represents the z-component of the average pore water velocity vector. The velocity direction is the instantaneous flow direction of the groundwater at that point. In the velocity field, from a certain starting point... Initial streamline path The system of ordinary differential equations is , , ,in, For streamlined paths, Let be the position coordinates of the fluid particle in the x-direction. Let be the position coordinates of the fluid particle in the y-direction. Let be the position coordinates of the fluid particle in the z-direction. Let be the rate of change of position of the fluid particle along the x-direction. Let be the rate of change of position of the fluid particle along the y-direction. Let z be the rate of change of position of a fluid particle along the z-direction. For water volume seepage velocity in the direction, For water volume seepage velocity in the direction, For water volume The seepage velocity in the direction is obtained by solving the system of equations using numerical integration, resulting in streamlines, which are the trajectories of tracer particles moving with the water flow. The spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater proposes to introduce the harmonic mean formula to calculate interface parameters during the discretization of differential equations to solve the distortion in flow calculation at abrupt interface changes. Then, it proposes three boundaries: constant head, constant flow, and impermeable boundary, to solve the distortion caused by leakage at impermeable boundaries and dynamic river boundary responses. Finally, it proposes a system of ordinary differential equations of particle kinematics to adaptively track streamlines and reduce tracer transport time errors, thereby realizing the generation of groundwater flow field and dynamic simulation of groundwater flow direction.

[0028] Preferably, the model validation and optimization unit is used to validate the simulation results of the model. By injecting artificial tracers / detecting environmental isotopes on site, the accuracy of the flow direction and velocity is verified by comparing the actual monitoring data with the migration path and time predicted by the model. The simulated water level is compared with the measured water level, and the permeability coefficient and recharge parameters are automatically adjusted to make the model infinitely close to the real situation and complete the calibration.

[0029] Preferably, the dynamic update and prediction unit is used for real-time updates and long-term predictions of the model. When new real-time monitoring data is received, the system can automatically trigger local model updates, quickly refresh the flow field map, realize a dynamic mapping like a digital twin, and predict future water level change trends based on historical water level data using time series analysis algorithms and machine learning models, and generate flow field prediction maps under different seasonal / climate scenarios.

[0030] Preferably, the visualization and interaction module is used to present complex models and data in intuitive and easy-to-understand 3D graphics. It receives the streamline dataset output from the groundwater flow field generation unit, and through 3D visualization rendering, it fully displays the spatial movement law of groundwater. At the same time, users can click on any location to query the water level and water quality data at that location, and drag the timeline to view the historical changes / future prediction animations of the flow field and conduct risk analysis.

[0031] This paper proposes a method and system for constructing a 3D model for groundwater flow direction detection, which is used to accurately characterize the groundwater flow field and migration path. By integrating modules for data acquisition and transmission, data processing and fusion, geological modeling and flow field generation, model verification and dynamic updating, and visualization and interaction, a method and system for constructing a 3D model for groundwater flow direction detection is provided. A parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies is proposed to construct 3D geological structure models. The innovation of this invention lies in the fact that the parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies first introduces... The gradient descent method automatically adjusts the elevation of the vertices of the triangulation network based on newly added borehole data, dynamically optimizing the model by incorporating new borehole data in real-time / periodically. Then, the Euler-Poincaré formula is proposed for automated topology verification to quickly identify and quantify topological defects. Furthermore, multi-step refinement processing is employed for complex geological features such as faults and lenses to avoid errors in the flow field simulation near faults and improve the characterization of heterogeneity, thereby achieving the construction of a three-dimensional geological structure model. A spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater is proposed to calculate and generate the groundwater flow field, dynamically simulate flow direction, and isostatic surfaces. The innovation of this paper lies in its proposed spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater. It introduces a harmonic mean formula to calculate interface parameters during the discretization of differential equations to address the distortion in flow calculations at abrupt interface changes. Furthermore, it proposes a three-boundary approach—constant head, constant flow rate, and impermeable boundary—to address the distortion caused by impermeable boundary leakage and dynamic river boundary response. Finally, it proposes a set of ordinary differential equations of particle kinematics for adaptive streamline tracking and to reduce tracer transport time errors. This enables the generation of groundwater flow fields and the dynamic simulation of groundwater flow direction, effectively improving the performance of the three-dimensional model construction method and system for groundwater flow direction detection. This invention provides more comprehensive and accurate technical support for the construction of three-dimensional models for groundwater flow direction detection, and better decision support for intelligent and safe three-dimensional models for groundwater flow direction detection. Furthermore, this invention relates to geological modeling and hydrological numerical simulation technologies, which not only improves prediction accuracy and significantly reduces computational costs, but also optimizes the dynamic allocation of computational resources through collaborative work between algorithms. It provides a convenient and efficient method and system for constructing three-dimensional models for groundwater flow direction detection, contributing significant application value to the characterization of groundwater flow fields in the hydrogeology and environmental engineering industries.

[0032] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method and system for constructing a three-dimensional model for detecting groundwater flow direction, characterized in that, The system includes modules for data acquisition and transmission, data processing and fusion, geological modeling and groundwater flow field generation, model validation and dynamic updating, and visualization and interaction. The data acquisition and transmission module is used to collect multi-source hydrogeological data. The data processing and fusion module is used to clean, transform, and fuse multi-source data. The geological modeling and groundwater flow field generation module includes a 3D geological modeling unit and a groundwater flow field generation unit. The 3D geological modeling unit proposes a parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies to construct a 3D geological structure model. The groundwater flow field generation unit proposes a spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater to calculate and generate the groundwater flow field. The model validation and dynamic updating module includes a model validation and optimization unit and a dynamic updating and prediction unit. The model validation and optimization unit is used to validate the simulation results of the model. The dynamic updating and prediction unit is used for real-time updating and long-term prediction of the model. The visualization and interaction module is used for 3D display of the data.

2. The method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 1, characterized in that, The data acquisition and transmission module is used to collect multi-source hydrogeological data. By using drones equipped with multispectral sensors or lidar, it can quickly collect large-scale, high-precision surface topographic data, precise coordinates of monitoring wells, and high-definition images of the surface environment. Through the wireless sensor network deployed in the monitoring wells, it can collect groundwater dynamic data in real time and automatically. The data is then remotely transmitted to the data center through IoT technology to ensure the timeliness of the data. It can also receive and integrate data from traditional geological exploration work to achieve unified access to multi-source heterogeneous data.

3. The method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 1, characterized in that, The data processing and fusion module is used to clean, transform and fuse multi-source data, remove sensor outliers and duplicate data, unify the coordinate system of all data, accurately correlate discrete water level data with corresponding spatial coordinates to form spatialized data points, and generate a continuous and smooth water level distribution surface.

4. The method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 1, characterized in that, The 3D geological modeling unit proposes a parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies to construct a 3D geological structure model. It connects the same stratum interface of different boreholes to form the top and bottom plate surfaces of the strata. Multiple stratum surfaces are transformed into 3D solid models through voxelization / boundary representation.

5. The method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 4, characterized in that, The specific algorithm for parametric dynamic modeling of multi-source coupled heterogeneous 3D geological bodies is as follows: First, the unified coordinate system processed by the data processing and fusion module is represented as... ,in, These are the X-axis coordinates in the new coordinate system after the transformation. These are the Y-axis coordinates in the new coordinate system after the transformation. To control the scaling factor in the X direction of the new coordinate system, To control the shearing factor of the Y value in the old coordinate system, To control the shearing factor of the X values ​​in the old coordinate system, To control the scaling factor in the Y direction of the new coordinate system, This represents the translation along the X-axis. This represents the translation along the Y-axis. Let X be the X-axis coordinate of the point to be transformed in the old coordinate system. The Y-axis coordinates of the points to be transformed in the old coordinate system are given. Then, each borehole is layered according to its formation ID, and the top / bottom elevations of each layer are extracted. The interface point set of the same formation is then processed. Constructing a triangular network for , ,in, For the set of stratigraphic interface points, The coordinates of the points are A single point, , , These are the three vertices of the triangular mesh. It is an irregular triangular network. Just passing through the point , , circumcircle, For intersection operations, For an empty set, insert virtual control points in the un-drilled region. , ,in, The elevation value of the virtual control point. The number of known points involved in the calculation. For the first The weights of the known points For the first The elevation values ​​of a known point. For virtual points With known points The Euclidean distance between them The attenuation coefficient is then used to stitch adjacent strata TINs together into a closed polyhedron to represent complex geological structures, i.e. , ,in, For the construction of a three-dimensional solid model, The total number of faces, The union operation is used to combine multiple faces into a solid. For the first A triangular mesh surface, Let be the set of vertices of the face. Let be the set of edges of the face. To obtain the topological information of the surface, the model domain is then divided into a voxel mesh, i.e. , ,in, For index voxel unit mesh, voxel unit The attribute value, For the land The code of the layer, voxel unit The coordinates of the center point, For the first Each geological entity is analyzed, and then complex geological structures are processed. Fault lines are interpreted through geological profiles, and fault surfaces are inserted into TINs to separate the strata on both sides. Lenses are locally densified using TINs, and the surface convexity is adjusted by control points. Finally, the stratigraphic closure is verified using the Euler-Poincaré formula. ,in, The total number of vertices in the triangular mesh. The total number of sides of the triangular mesh. The total number of faces of the triangular mesh. The number of connected 3D entities. The number of voids in the entity; to optimize the formation elevation, the TIN vertex position is adjusted based on the newly added boreholes. ,in, As vertices Elevation adjustment amount, For learning rate, For partial derivative operations, For the predicted elevation value, The observed elevation value, Perform square norm operations, and then assign hydrological properties to each volume element / surface element, i.e. , ,in, For grid cells Permeability coefficient in the x-direction, This is a lookup function that retrieves values ​​from an attribute database based on geological codes. This is the type keyword for the permeability coefficient attribute. For grid cells water storage rate, As the type keyword for water storage rate attribute, the parametric dynamic modeling algorithm for multi-source coupled heterogeneous 3D geological bodies first introduces the gradient descent method to automatically adjust the elevation of the vertices of the triangular mesh based on newly added borehole data, and dynamically optimizes the model by incorporating new borehole data in real time / periodically. Then, the Euler-Poincaré formula is proposed for automated topology verification to quickly identify and quantify topological defects. Then, for the complex geological features of faults and lenses, multi-step refinement processing is adopted to avoid errors in the simulation of the flow field near the fault and improve the characterization of heterogeneity, thereby realizing the construction of a 3D geological structure model.

6. The method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 1, characterized in that, The groundwater flow field generation unit proposes a spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater to calculate and generate the groundwater flow field, and dynamically simulate the flow direction and isostatic surfaces.

7. The method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 6, characterized in that, The specific algorithm for simulating the spatiotemporal dynamic streamlines of heterogeneous groundwater is as follows: First, the three-dimensional geological structure model constructed from three-dimensional geological modeling units is transformed into discretized computational units that can be processed by a computer, that is, the three-dimensional model region is divided into... A regular cuboid mesh element, wherein, This represents the total number of mesh elements in the x-direction of the model in three-dimensional space. This represents the total number of mesh elements in the y-direction of the model in three-dimensional space. Let be the total number of mesh elements in the z-direction of the model in 3D space, and let the coordinates of the center point of each mesh element be denoted as . ,in, , , ,in, The element number in the x-direction is the center point of the mesh cell. The element number in the y-direction is the center point of the mesh cell. The element number of the center point of the mesh element in the z-direction, for each mesh element. Assigning hydrogeological parameters, primarily permeability parameters , , and water storage rate ,in, Let be the permeability coefficient in the x-direction. Let be the permeability coefficient in the y-direction. Given the permeability coefficient in the z-direction, a discrete, parameterized three-dimensional grid system can be obtained. Then, the partial differential governing equations describing the three-dimensional unsteady flow motion of groundwater are established as follows: ,in, Let x be the component of the permeability coefficient in the x-direction. Let be the component of the permeability coefficient in the y-direction. Let be the component of the permeability coefficient in the z-direction. For the water head, Let be the spatial gradient of the water head in the x-direction. Let be the spatial gradient of the water head in the y-direction. Let be the spatial gradient of the water head in the z-direction. Flow rate per unit volume For water storage rate, Let be the rate of change of water head over time, and set boundary conditions, defining the water head boundary as . ,in, , , For spatial coordinates, For time variables, To determine the geometric location of the head boundary, For the boundary coordinates on and time Groundwater head The value, Let the head on the boundary be a function of the head distribution over time / space, and the constant flow boundary be... ,in, Permeability coefficient, Let be the gradient of the water head along the direction normal to the boundary. For time step index, i.e. ,in, For time step, To determine the geometric location of the constant flow boundary, The flow rate intensity function is given by the water-impermeable boundary. ,in, The location of the impermeable boundary is determined. Then, the partial differential equation is transformed into a large system of linear equations using a discretization method and solved. The derivative terms in the governing equations are approximated using a central difference scheme, and the differential equations are discretized into... ,in, , , For located and The permeability coefficient values ​​in the x, y, and z directions at the interface between two grid cells. For the current grid cell At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, For grid cells At the current time step water head value, The size of the mesh cell in the x-direction. Let be the size of the mesh element in the y-direction. Let Z be the size of the mesh element in the z-direction. For the current grid cell Flow rate per unit volume For the current grid cell water storage rate, For the current grid cell At time step water head value, For each grid cell, an equation is written for each time step. The linear equations of all grid points are combined to form a large sparse linear equation system. This system is then iteratively solved to obtain the three-dimensional head field at the discrete time step. From this three-dimensional head field, intuitive flow direction and velocity information are extracted. According to Darcy's law, the seepage velocity vector at any point in space is... In actual numerical calculations, The seepage velocity vector, Let be the permeability tensor. As the gradient operator, at the center of each grid cell, the average velocity vector of the pore water is... , , ,in, Let x be the component of the average velocity vector of pore water in the x-direction. Let be the component of the average velocity vector of pore water in the y-direction. Let Z be the component of the average velocity vector of pore water in the z-direction. In the velocity field, starting from a certain starting point... Initial streamline path The system of ordinary differential equations is , , ,in, For streamlined paths, Let be the position coordinates of the fluid particle in the x-direction. Let be the position coordinates of the fluid particle in the y-direction. Let be the position coordinates of the fluid particle in the z-direction. Let be the rate of change of position of the fluid particle along the x-direction. Let be the rate of change of position of the fluid particle along the y-direction. Let z be the rate of change of position of a fluid particle along the z-direction. For water volume seepage velocity in the direction, For water volume seepage velocity in the direction, For water volume The seepage velocity in the direction is obtained by solving the system of equations using numerical integration, resulting in streamlines, which are the trajectories of tracer particles moving with the water flow. The spatiotemporal dynamic streamline tracking simulation algorithm for heterogeneous groundwater proposes to introduce the harmonic mean formula to calculate interface parameters during the discretization of differential equations to solve the distortion in flow calculation at abrupt interface changes. Then, it proposes three boundaries: constant head, constant flow, and impermeable boundary, to solve the distortion caused by leakage at impermeable boundaries and dynamic river boundary responses. Finally, it proposes a system of ordinary differential equations of particle kinematics to adaptively track streamlines and reduce tracer transport time errors, thereby realizing the generation of groundwater flow field and dynamic simulation of groundwater flow direction.

8. The method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 1, characterized in that, The model validation and optimization unit is used to validate the simulation results of the model. By injecting artificial tracers / detecting environmental isotopes in the field, the accuracy of the flow direction and velocity is verified by comparing the actual monitoring data with the migration path and time predicted by the model.

9. The method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 1, characterized in that, The dynamic update and prediction unit is used for real-time updates and long-term predictions of the model. When new real-time monitoring data is received, the system can automatically trigger local model updates, quickly refresh the flow field map, achieve dynamic mapping like a digital twin, and predict future water level change trends based on historical water level data using time series analysis algorithms and machine learning models, and generate flow field prediction maps under different seasonal / climate scenarios.

10. A method and system for constructing a three-dimensional model for detecting groundwater flow direction according to claim 1, characterized in that, The visualization and interaction module is used to present complex models and data in intuitive and easy-to-understand 3D graphics. It receives the streamline dataset output from the groundwater flow field generation unit and displays the spatial movement pattern of groundwater in all aspects through 3D visualization rendering. At the same time, users can click on any location to query the water level and water quality data, drag the timeline to view the historical changes / future prediction animations of the flow field, and conduct risk analysis.

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