Regional three-dimensional geological data management system and evaluation method

Abstract

The application belongs to the technical field of geographic information, and specifically discloses a regional three-dimensional geological data management system and an evaluation method, which comprises the following modules: a data acquisition module, which is used for generating standard geological data according to unified space-time reference; a regional division module, which is used for dividing polygonal sub-regions according to the distribution of drill holes; a three-dimensional modeling module, which is used for constructing a three-dimensional geological body model based on voxel units; an electronic map module, which is used for the interaction and judgment of arbitrary polygon selection and depth interval; a time series prediction module, which is used for predicting the change of geological parameters by using weighted moving average and correlation parameter correction; and a statistical evaluation module, which is used for generating a quantitative report containing present situation statistics and trend prediction. The application realizes the space-time unification of historical and real-time data, and can quantitatively calculate regional groundwater level and soil physical and mechanical indexes through sub-region division and correlation parameter correction, thereby providing forward-looking reference for engineering construction feasibility study, site planning, preliminary exploration and the like.

Description

Technical Field

[0001] This invention belongs to the field of geographic information technology, and specifically relates to a regional three-dimensional geological data management system and evaluation method. Background Technology

[0002] Geological parameters include borehole coordinates and elevations, stratigraphic depths, lithological descriptions, and physical and mechanical properties. For regional three-dimensional geological parameters, the data volume is enormous and is usually stored in the form of Excel spreadsheets or text files. When users want to access geological data for a certain area, they need to open multiple Excel files one by one according to the paper archive catalog or electronic file list, and then manually filter out the boreholes and corresponding stratigraphic parameters for that area based on the coordinate range.

[0003] In practical storage, Excel spreadsheets from different sources often employ custom field orders and naming rules, lacking a unified coordinate benchmark and data format. When geological parameters within a specific geographical area are needed, users must manually calculate the coordinate range and open each file individually, making rapid spatial positioning and automatic filtering across files impossible, resulting in extremely low data retrieval efficiency. Furthermore, existing storage methods only retain static measurement data at discrete time points, failing to establish a continuous sequence of parameter changes over time. Therefore, it is impossible to predict the future evolution trends of geological parameters such as groundwater level changes and soil strength decay. Summary of the Invention

[0004] The purpose of this invention is to overcome the deficiencies in the existing technology and provide a regional three-dimensional geological data management system and evaluation method.

[0005] In a first aspect, the present invention provides a regional three-dimensional geological data management system, a data acquisition module for collecting historical geological data and real-time monitoring data, and performing a unified spatiotemporal benchmark conversion on the historical geological data to generate standard geological data with unified spatial coordinates and time markers. The standard geological data includes at least the spatial coordinates and elevation of borehole locations, physical and mechanical parameters of stratigraphic interfaces, and acquisition time. The region division module, connected to the data acquisition module, divides the region to which the standard geological data belongs into several polygonal sub-regions according to the spatial distribution of the borehole points. A 3D modeling module, connected to the data acquisition module, generates continuous stratigraphic surfaces based on the stratigraphic layering information of each borehole, and discretizes the spatial region between adjacent stratigraphic surfaces into voxel units. Each voxel unit records the geological parameters of its respective stratigraphic layer; a regional 3D geological model is constructed based on the voxel units. The electronic map module, connected to the area division module, is used to load the boundary layer, borehole point distribution layer and stratigraphic boundary layer of the sub-region onto the standard electronic map. For any polygonal selection area and depth range selected by the user on the standard electronic map, it determines the borehole points and stratigraphic layer information contained within the polygonal selection area. The time series prediction module, connected to the data acquisition module, is used to read historical measurement values ​​of the same type of geological parameters in the same sub-region at different time points, calculate the rate of change, and use the weighted moving average method to predict the parameter values ​​at a specified future time. When there are correlated parameters, the predicted values ​​are corrected according to the historical correlation coefficient, and the prediction results are output. The statistical evaluation module is connected to the electronic map module and the time series prediction module respectively. It receives the polygonal selection area and the specified depth range selected by the user on the map, obtains the geotechnical physical and mechanical parameters of the sub-region covered by the polygonal selection area, and obtains the prediction results of the corresponding parameters of the sub-region output by the time series prediction module, and generates a quantitative evaluation report containing the current statistical characteristics and future prediction trends.

[0006] A further embodiment is that the 3D modeling module also includes an incremental update unit. When new borehole data is added to the data acquisition module, the incremental update unit recalculates the voxel units in the polygonal sub-region where the new borehole is located and the adjacent sub-regions, and generates locally updated voxel units to replace the original voxel units.

[0007] A further solution is that the process by which the electronic map module identifies the sub-regions covered by the arbitrary polygon selection area drawn by the user is as follows: obtain the coordinates of the vertices of the polygon formed by the user's continuous clicks on the map, call the polygon overlay analysis algorithm, traverse all sub-regions, calculate the overlap area between the current polygon selection area and each sub-region, mark the sub-regions with an overlap area greater than zero as covered sub-regions, and send the borehole and stratigraphic layer data associated with the covered sub-regions to the statistical evaluation module.

[0008] A further solution is that the process of dividing the region to be evaluated into several polygonal sub-regions by the region division module is as follows: taking all the drilling points as a set of discrete points on the plane, connecting the perpendicular bisectors of the lines connecting adjacent drilling points, forming a convex polygon corresponding to each drilling point, such that the distance from any point in the convex polygon to that drilling point is less than the distance to other drilling points, and using the generated convex polygon as the boundary of the sub-region.

[0009] A further embodiment is that the time series prediction module includes: The historical data reading unit is used to extract a sequence of historical measurement values ​​of the same type of geological parameter in the same sub-region, sorted by time, from the data acquisition module. The rate of change calculation unit is used to calculate the rate of change of adjacent time points in the historical measurement value sequence, and to perform a weighted moving average of the most recent N rates of change to obtain the current average rate of change. The closer the measurement value is to the current time, the higher the weight. The correlation parameter correction unit is used to store historical correlation coefficients between different types of geological parameters within the same sub-region. When a second type of parameter is associated with the current predicted parameter, the current average rate of change of the second type of parameter is read, and the deviation between the measured ratio and the historical correlation coefficient is calculated. If the deviation exceeds a preset threshold, the current average rate of change is corrected. The correction process is as follows: ; in The current average rate of change, Historical correlation coefficient This is the measured ratio. For the rate of change of the associated parameter, This is a correction factor; The prediction value calculation unit is used to calculate the predicted value at a specified future time based on the average rate of change output by the rate of change calculation unit or the correlation parameter correction unit, and the most recent measurement value.

[0010] A further approach is to use the historical correlation coefficient as the ratio between the rate of change of the target parameter and the rate of change of the associated parameter. The calculation process is as follows: select multiple time points within the historical period, calculate the rate of change of the target parameter and the rate of change of the associated parameter in each time interval, as well as the ratio of the rate of change of the target parameter to the rate of change of the associated parameter, and use the arithmetic mean of the ratios as the historical correlation coefficient between the target parameter and the associated parameter within the sub-region.

[0011] A further proposed solution is that the statistical evaluation module includes: The depth analysis unit is used to receive the start and end depths specified by the user, traverse the physical and mechanical parameters of different strata interfaces of each borehole in the covered sub-region, filter out the strata whose top and bottom depth ranges overlap with the user-specified depth range, and extract the physical and mechanical parameter values ​​of the strata according to the proportion of the overlap thickness to the total thickness of the strata. The weighted statistical unit is used to calculate the statistical weight of borehole samples within each sub-region by the proportion of the area covered by the polygonal selection area. The report generation unit calculates the geophysical and mechanical parameters of the polygonal selected area based on the statistical weights of the borehole samples, the predicted values ​​and prediction periods output by the time series prediction module, and fills in the data according to the preset report template to generate a quantitative evaluation report.

[0012] A second aspect of the present invention provides a regional three-dimensional geological evaluation method, which applies the above-mentioned regional three-dimensional geological data management system and includes the following steps: Step 1: Collect historical geological data and real-time monitoring data through the data acquisition module, and perform a unified spatiotemporal benchmark conversion on the historical geological data to generate standard geological data with unified spatial coordinates and time markers; Step 2: The region to be evaluated is divided into several polygonal sub-regions according to the spatial distribution of the borehole points using the region division module. Step 3: The three-dimensional modeling module generates continuous stratigraphic surfaces based on the stratigraphic layering information of each borehole, and discretizes the spatial region between adjacent stratigraphic surfaces into voxel units, and constructs a regional three-dimensional geological body model based on the voxel units. Step 4: Load the sub-region boundary layer, borehole point distribution layer and stratum boundary layer on the standard electronic map through the electronic map module; receive any polygonal selection area and depth range selected by the user on the standard electronic map; determine the borehole points and stratum layer information contained in the polygonal selection area; and send the borehole and stratum layer data associated with the covered sub-region to the statistical evaluation module. Step 5: Read the historical measurement values ​​of the same type of geological parameters in the same sub-region at different time points through the time series prediction module, calculate the rate of change, and use the weighted moving average method to predict the parameter values ​​at a specified future time. When there are related parameters, the predicted values ​​are corrected according to the historical correlation coefficient, and the prediction results are output to the statistical evaluation module. Step 6: Receive the geotechnical physical and mechanical parameters of the sub-region covered by the polygonal selection area sent by the electronic map module through the statistical evaluation module, and the prediction results of the corresponding parameters of the sub-region output by the time series prediction module, and generate a quantitative evaluation report containing current statistical characteristics and future prediction trends.

[0013] A further proposed solution is that step 5, in which the prediction result is output, includes the following steps: Step 5.1: Extract the historical measurement sequence of the same type of geological parameter in the same sub-region, sorted by time, from the data acquisition module; Step 5.2: Calculate the rate of change of adjacent time points in the historical measurement value sequence, and perform a weighted moving average on the most recent N rates of change to obtain the current average rate of change, wherein the measurement value closer to the current time has a higher weight; Step 5.3: Store the historical correlation coefficients between different types of geological parameters within the same sub-region. When a second type of parameter is associated with the current predicted parameter, read the current average rate of change of the second type of parameter, calculate the deviation between the measured ratio and the historical correlation coefficient, and if the deviation exceeds a preset threshold, correct the current average rate of change. The correction process is as follows: ; in The current average rate of change, Historical correlation coefficient This is the measured ratio. For the rate of change of the associated parameter, This is a correction factor; Step 5.4: The prediction value calculation unit calculates the predicted value at a specified future time based on the corrected average rate of change and the most recent measurement value. The calculation process is as follows: ; in, For predicted values, This is the most recent measurement. To measure time, Predicting moments for the future.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention transforms historical geological data from different benchmarks into a unified spatiotemporal model, divides the evaluation area into several sub-regions based on borehole distribution, and analyzes the variation patterns of parameters using historical monitoring data within each sub-region. By calculating the rate of change of historical measurements of the same type of geological parameter within the same sub-region and applying a weighted moving average, and by correcting the predicted values ​​using historical correlation coefficients of related parameters, key indicators such as groundwater level and soil strength can be quantitatively predicted at a specified future time. This allows preliminary geotechnical investigations to move beyond static data and anticipate changes in site conditions, providing a forward-looking reference for the design of investigation plans.

[0015] This invention displays all borehole data, after undergoing unified coordinate and elevation transformation, directly on a standard electronic map showing borehole locations and sub-region boundaries. Users only need to delineate the proposed site on the map, and the system automatically identifies all boreholes within that area, along with their corresponding stratigraphic layers and geotechnical test data, eliminating the need for manual sifting through multiple Excel spreadsheets or filtering through individual files. This map-based interactive approach significantly reduces data collection time during the initial exploration phase, allowing engineers to focus more on the geological analysis itself. Users can draw any irregular polygonal selection area on the standard electronic map, specifying any starting and ending depth below the surface. The system automatically determines the statistical weight of borehole samples based on the overlap area between the selected area and each sub-region, and simultaneously extracts parameter values ​​weighted by the thickness of each stratum within the specified depth range. Finally, it automatically calculates the geotechnical parameters within the area and generates standardized statistical reports. This improves the accuracy and efficiency of batch evaluation of geological conditions in irregular sites and at specific depth ranges.

[0016] This invention can also provide geological feasibility analysis for the site selection of linear engineering projects such as highways and railways. Specifically, after the user imports the route, the system automatically identifies the sub-regions covered by the route, extracts information such as lithology, fault structures, and adverse geological bodies along the route, and generates an analysis report by combining the changing trends of key parameters given by the time series prediction module. This allows for rapid understanding of the geological conditions along the route during the planning stage of project site selection, reasonable avoidance of geological disaster risks, and optimization of route selection schemes, thereby reducing potential risks and subsequent change costs in project construction. Attached Figure Description

[0017] The following figures are for illustrative purposes only and are not intended to limit the scope of the invention, wherein: Figure 1 : A block diagram showing the connection between the modules of this invention; In the diagram: 1. Data acquisition module; 2. Region division module; 3. 3D modeling module; 4. Electronic map module; 5. Time series prediction module; 6. Statistical evaluation module; 7. Incremental update unit; 8. Historical data reading unit; 9. Change rate calculation unit; 10. Correlation parameter correction unit; 11. Predicted value calculation unit; 12. Deep analysis unit; 13. Weighted statistics unit; 14. Report generation unit. Detailed Implementation

[0018] To make the objectives, technical solutions, design methods, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0019] Example 1 like Figure 1As shown, this embodiment provides a regional three-dimensional geological data management system. The system specifically includes a data acquisition module 1, a region division module 2, a three-dimensional modeling module 3, an electronic map module 4, a time-series prediction module 5, and a statistical evaluation module 6. The data acquisition module 1 is responsible for collecting historical geological data and real-time monitoring data from various raw materials, performing unified spatiotemporal benchmark conversion on this data, standardizing field naming and units, and generating standard geological data with unified spatial coordinates and precise time stamps. This data at least covers the planar coordinates and elevations of borehole locations, the top and bottom depths of each stratum, and their physical and mechanical parameters. The region division module 2 is connected to the data acquisition module 1. Based on the distribution of all borehole locations on the plane, it intelligently divides the entire area to be evaluated into multiple non-overlapping polygonal sub-regions. The geological features within each sub-region are represented by the borehole locations within it. The 3D modeling module 3 connects to the data acquisition module 1. Utilizing the stratigraphic information from each borehole, it generates continuous, smooth top and bottom stratigraphic surfaces using an interpolation algorithm. Then, the 3D spatial region between two adjacent stratigraphic surfaces is discretized into a large number of regularly arranged voxel units. Each voxel unit records various geological parameters of the stratigraphic layer at that location. Finally, these voxels are stacked to form a visualized regional 3D geological model. The electronic map module 4 connects to the region division module 2. It overlays and displays sub-region boundary layers, borehole location distribution layers, and stratigraphic boundary layers on standard electronic maps such as Gaode and Google Maps. Users can freely draw polygonal selection areas of arbitrary shapes on the map and specify a depth range. The electronic map module 4 determines which boreholes are contained within the polygonal selection area and the corresponding stratigraphic information, extracting the relevant data for subsequent evaluation. The time-series prediction module 5 is connected to the data acquisition module 1. For the same type of geological parameter (such as groundwater depth or pore water pressure) within the same sub-region, it first calculates the rate of change between adjacent time points, and then uses a weighted moving average method to predict the parameter value at a future time. If there is another type of parameter with a physical correlation to this parameter (such as rainfall and groundwater level), the predicted value is further corrected using the historical correlation coefficient, thus outputting a more reliable prediction result. The statistical evaluation module 6 is connected to the electronic map module 4 and the time-series prediction module 5 respectively. It receives the polygonal selection area and its specified depth range selected by the user on the map, obtains the geotechnical physical and mechanical parameters of each sub-region covered by the selection area, and obtains the future predicted values ​​of the corresponding parameters for these sub-regions given by the time-series prediction module 5. Finally, it automatically generates a quantitative evaluation report. The report includes the statistical characteristics of the current geological parameters (mean, variance, confidence interval, etc.) as well as the trend curves and numerical predictions of key indicators over a future period.

[0020] Building upon the aforementioned system, the 3D modeling module 3 introduces an incremental update unit 7. When a new borehole is added to the data acquisition module 1, the incremental update unit 7 does not perform a global reconstruction of the entire model. Instead, it only recalculates the voxel elements within the polygonal sub-region where the new borehole is located, as well as adjacent sub-regions sharing the boundary with it. The newly generated voxel elements then replace the existing ones. For example, in a highway engineering geological survey, modeling of 100 boreholes was initially completed, and then 5 more boreholes were added. The incremental update unit 7 only recalculates the voxel elements within the adjacent sub-regions of these 5 boreholes, significantly improving the system response speed during dynamic data updates.

[0021] Furthermore, when identifying the sub-regions covered by the arbitrary polygon selection area drawn by the user, the electronic map module 4 employs a spatial overlay analysis process. Specifically, the electronic map module 4 obtains the screen coordinates of each vertex of the polygon formed by the user's continuous clicks on the map and converts them into geographic coordinates. Then, it calls the polygon overlay analysis algorithm to traverse all sub-regions within the system, calculating the overlap area between the currently drawn polygon selection area and each sub-region polygon. As long as the overlap area is greater than zero, the sub-region is marked as an overlay sub-region, and all boreholes and their stratigraphic layering data associated with these overlay sub-regions are sent to the statistical evaluation module 6.

[0022] In the above, the specific method used by the region partitioning module 2 to divide the area to be evaluated into several polygonal sub-regions adopts the Thiessen polygon principle in computational geometry. Using all borehole locations as a discrete set of points in a plane, the set is triangulated using Delaunay triangulation. The perpendicular bisectors of the lines connecting adjacent boreholes are then constructed. These perpendicular bisectors intersect and enclose each borehole, forming a convex polygon. The geometric property of this convex polygon is that the planar distance from any point within the polygon to that borehole is less than the planar distance to any other borehole. The resulting sub-region boundaries naturally reflect the spatial control range of the boreholes, allowing the geological parameters of each sub-region to be most reasonably represented by the borehole data within it.

[0023] To achieve quantitative prediction of future geological parameter changes, this embodiment further refines the internal structure of the time-series prediction module 5. This module includes a historical data reading unit 8, a rate of change calculation unit 9, a correlation parameter correction unit 10, and a predicted value calculation unit 11. The historical data reading unit 8 is used to extract a sequence of measured values ​​of the same type of geological parameter arranged in chronological order within the same sub-region from the data acquisition module 1. The rate of change calculation unit 9 then calculates the rate of change between two adjacent time points in the sequence, and then performs a weighted moving average on the most recent N rates of change, where the measurement value closer to the current time is assigned a higher weight. For example, when N=4, the weights can be assigned as 0.5, 0.3, 0.15, and 0.05, thereby obtaining the current weighted average rate of change. The correlation parameter correction unit 10 internally stores the historical correlation coefficients between different types of geological parameters within the same sub-region. The historical correlation coefficient Used to reflect the average proportional relationship between the rates of change of the two parameters; when there is a second type of parameter that is physically related to the current predicted parameter, the associated parameter correction unit 10 reads the current average rate of change of the second type of parameter. Calculate the measured ratio and its correlation coefficient with historical data. Compare; if there is a deviation If the preset threshold is exceeded, the correction formula will be applied. The current average rate of change is corrected, where The correction coefficient is selected within the range of 0.5-1.2 based on parameter sensitivity. The predicted value calculation unit 11 calculates the predicted value based on the finally determined average rate of change (after correction). Or uncorrected ) and the most recent actual measurement value According to the formula Calculate the future specified time. Predicted value In this embodiment, the historical correlation coefficient This is defined as the arithmetic mean of the proportional relationship between the rate of change of the target parameter and the rate of change of the associated parameter. During calculation, multiple time points are selected within a historical period, and the rates of change of the target parameter and the associated parameter are calculated for each time interval. The ratio of these two ratios within each interval is then calculated, and finally, these ratios are arithmetically averaged. For example, if the two associated parameters are groundwater level and rainfall, seven valid ratios are obtained: 0.32, 0.35, 0.29, 0.34, 0.31, 0.33, and 0.30. Their arithmetic mean is 0.32, meaning the proportionality coefficient between the rate of change of groundwater level and the rate of change of rainfall in this sub-region is 0.32. In other words, for every 1 mm increase in rainfall, the groundwater level rises by an average of approximately 0.32 mm.

[0024] To perform accurate statistical analysis on the user-selected spatial range and depth interval, the statistical evaluation module 6 in this embodiment further includes a depth analysis unit 12, a weighted statistics unit 13, and a report generation unit 14. The depth analysis unit 12 receives the user-specified starting and ending depths (e.g., from 5 meters to 10 meters below the surface), then traverses the different stratigraphic interfaces of each borehole within all covered sub-regions, filtering out stratigraphic layers whose top and bottom depth intervals overlap with the user-specified depth interval. The physical and mechanical parameter values ​​of these layers are then extracted by weighting the overlap thickness according to its proportion to the total thickness of the layer. The weighted statistics unit 13 calculates the statistical weight of the borehole samples within each sub-region based on the proportion of the area covered by the polygonal selection area. If a sub-region is 80% covered and contains two boreholes, each borehole has a weight of 40%. Based on the statistical weights of these borehole samples, the report generation unit 14 calculates the weighted average, standard deviation, and other statistical quantities of each geotechnical physical and mechanical parameter within the polygonal selection area. It also incorporates the predicted values ​​and prediction periods output by the time series prediction module 5. Finally, it automatically fills in the data and charts according to the preset standardized report template to generate a complete quantitative evaluation report.

[0025] Example 2 Based on Example 1, this example provides a regional three-dimensional geological evaluation method, including the following steps: Step 1: Collect historical geological data and real-time monitoring data through data acquisition module 1, and perform a unified spatiotemporal benchmark conversion on the historical geological data to generate standard geological data with unified spatial coordinates and time markers.

[0026] Step 2: Based on the spatial distribution of borehole points, the area to be evaluated is divided into several polygonal sub-regions by the area division module 2.

[0027] Step 3: The 3D modeling module 3 generates continuous stratigraphic surfaces based on the stratigraphic layering information of each borehole, and discretizes the spatial regions between adjacent stratigraphic surfaces into voxel units, and constructs a regional 3D geological body model based on the voxel units.

[0028] Step 4: Load the sub-region boundary layer, borehole point distribution layer and stratigraphic boundary layer on the standard electronic map through the electronic map module 4. Receive any polygonal selection area and depth range selected by the user on the standard electronic map, determine the borehole points and stratigraphic layer information contained within the polygonal selection area, and send the borehole and stratigraphic layer data associated with the covered sub-region to the statistical evaluation module 6.

[0029] Step 5: Read the historical measurement values ​​of the same type of geological parameters in the same sub-region at different time points through the time series prediction module 5, calculate the rate of change, and use the weighted moving average method to predict the parameter values ​​at a specified future time. When there are related parameters, the predicted values ​​are corrected according to the historical correlation coefficient, and the prediction results are output to the statistical evaluation module 6.

[0030] Step 6: Receive the geotechnical physical and mechanical parameters of the sub-region covered by the polygonal selection area sent by the electronic map module 4 through the statistical evaluation module 6, and the prediction results of the corresponding parameters of the sub-region output by the time series prediction module 5, and generate a quantitative evaluation report containing current statistical characteristics and future prediction trends.

[0031] When using the above method for prediction, the specific process of outputting the prediction result in step 5 further includes the following steps: Step 5.1: Extract the historical measurement sequence of the same type of geological parameters in the same sub-region, sorted by time, from the data acquisition module 1 through the historical data reading unit 8.

[0032] Step 5.2: Calculate the rate of change of adjacent time points in the historical measurement value sequence through the rate of change calculation unit 9, and perform a weighted moving average on the most recent N rates of change to obtain the current average rate of change, where the measurement value closer to the current time has a higher weight.

[0033] Step 5.3: The historical correlation coefficients between different types of geological parameters within the same sub-region are stored through the correlation parameter correction unit 10. When a second type of parameter is associated with the current predicted parameter, the current average rate of change of the second type of parameter is read, and the measured ratio is calculated. and its correlation coefficient with historical data. Compare; if there is a deviation If the preset threshold is exceeded, the correction formula will be applied. The current average rate of change is corrected, where This is a correction factor.

[0034] Step 5.4, the predicted value calculation unit 11 calculates the value based on the corrected average rate of change. and the most recent measurement value Using linear formula Calculate a specified future time. Predicted value .

[0035] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A regional three-dimensional geological data management system, characterized in that, include: The data acquisition module is used to collect historical geological data and real-time monitoring data, and to perform a unified spatiotemporal benchmark conversion on the historical geological data to generate standard geological data with unified spatial coordinates and time markers. The standard geological data includes at least the spatial coordinates and elevation of the borehole locations, the physical and mechanical parameters of the stratigraphic interfaces, and the acquisition time. The region division module, connected to the data acquisition module, divides the region to which the standard geological data belongs into several polygonal sub-regions according to the spatial distribution of the borehole points. A 3D modeling module, connected to the data acquisition module, generates continuous stratigraphic surfaces based on the stratigraphic layering information of each borehole, and discretizes the spatial region between adjacent stratigraphic surfaces into voxel units. Each voxel unit records the geological parameters of its respective stratigraphic layer; a regional 3D geological model is constructed based on the voxel units. The electronic map module, connected to the area division module, is used to load the boundary layer, borehole point distribution layer and stratigraphic boundary layer of the sub-region onto the standard electronic map. For any polygonal selection area and depth range selected by the user on the standard electronic map, it determines the borehole points and stratigraphic layer information contained within the polygonal selection area. The time series prediction module, connected to the data acquisition module, is used to read historical measurement values ​​of the same type of geological parameters in the same sub-region at different time points, calculate the rate of change, and use the weighted moving average method to predict the parameter values ​​at a specified future time. When there are correlated parameters, the predicted values ​​are corrected according to the historical correlation coefficient, and the prediction results are output. The statistical evaluation module is connected to the electronic map module and the time series prediction module respectively. It receives the polygonal selection area and the specified depth range selected by the user on the map, obtains the geotechnical physical and mechanical parameters of the sub-region covered by the polygonal selection area, and obtains the prediction results of the corresponding parameters of the sub-region output by the time series prediction module, and generates a quantitative evaluation report containing the current statistical characteristics and future prediction trends.

2. A regional three-dimensional geological data management system according to claim 1, characterized in that, The 3D modeling module also includes an incremental update unit. When new borehole data is added to the data acquisition module, the incremental update unit recalculates the voxel units in the polygonal sub-region where the new borehole is located and the adjacent sub-regions, and generates locally updated voxel units to replace the original voxel units.

3. A regional three-dimensional geological data management system according to claim 2, characterized in that, The process by which the electronic map module identifies the sub-regions covered by the arbitrary polygon selection area drawn by the user is as follows: obtain the coordinates of the vertices of the polygon formed by the user's continuous clicks on the map, call the polygon overlay analysis algorithm, traverse all sub-regions, calculate the overlap area between the current polygon selection area and each sub-region, mark the sub-regions with an overlap area greater than zero as covered sub-regions, and send the borehole and stratigraphic layer data associated with the covered sub-regions to the statistical evaluation module.

4. A regional three-dimensional geological data management system according to claim 3, characterized in that, The process by which the region division module divides the region to be evaluated into several polygonal sub-regions is as follows: taking all borehole locations as a set of discrete points on a plane, connecting the perpendicular bisectors of the lines connecting adjacent boreholes, forming a convex polygon corresponding to each borehole, such that the distance from any point in the convex polygon to that borehole is less than the distance to other boreholes, and using the generated convex polygon as the boundary of the sub-region.

5. A regional three-dimensional geological data management system according to claim 4, characterized in that, The time series prediction module includes: The historical data reading unit is used to extract, from the data acquisition module, a sequence of historical measurement values ​​of the same type of geological parameter in the same sub-region, sorted by time. The rate of change calculation unit is used to calculate the rate of change of adjacent time points in the historical measurement value sequence, and to perform a weighted moving average of the most recent N rates of change to obtain the current average rate of change. The closer the measurement value is to the current time, the higher the weight. The correlation parameter correction unit is used to store historical correlation coefficients between different types of geological parameters within the same sub-region. When a second type of parameter is associated with the current predicted parameter, the current average rate of change of the second type of parameter is read, and the deviation between the measured ratio and the historical correlation coefficient is calculated. If the deviation exceeds a preset threshold, the current average rate of change is corrected. The correction process is as follows: ； in The current average rate of change, Historical correlation coefficient This is the measured ratio. For the rate of change of the associated parameter, This is a correction factor; The prediction value calculation unit is used to calculate the predicted value at a specified future time based on the average rate of change output by the rate of change calculation unit or the correlation parameter correction unit, and the most recent measurement value.

6. A regional three-dimensional geological data management system according to claim 5, characterized in that, The historical correlation coefficient is the proportional relationship between the rate of change of the target parameter and the rate of change of the associated parameter. The calculation process is as follows: select multiple time points within the historical period, calculate the rate of change of the target parameter and the rate of change of the associated parameter in each time interval, as well as the ratio of the rate of change of the target parameter and the rate of change of the associated parameter, and take the arithmetic mean of the ratios as the historical correlation coefficient between the target parameter and the associated parameter in the sub-region.

7. A regional three-dimensional geological data management system according to claim 6, characterized in that, The statistical evaluation module includes: The depth analysis unit is used to receive the start and end depths specified by the user, traverse the physical and mechanical parameters of different strata interfaces of each borehole in the covered sub-region, filter out the strata whose top and bottom depth ranges overlap with the user-specified depth range, and extract the physical and mechanical parameter values ​​of the strata according to the proportion of the overlap thickness to the total thickness of the strata. The weighted statistical unit is used to calculate the statistical weight of the borehole samples in each sub-region based on the proportion of the area covered by the polygonal selection area. The report generation unit calculates the geophysical and mechanical parameters of the polygonal selected area based on the statistical weights of the borehole samples, the predicted values ​​and prediction periods output by the time series prediction module, and fills in the data according to the preset report template to generate a quantitative evaluation report.

8. A regional three-dimensional geological evaluation method, characterized in that, The application of the regional three-dimensional geological data management system according to any one of claims 1-7 includes the following steps: Step 1: Collect historical geological data and real-time monitoring data through the data acquisition module, and perform a unified spatiotemporal benchmark conversion on the historical geological data to generate standard geological data with unified spatial coordinates and time markers; Step 2: The region to be evaluated is divided into several polygonal sub-regions according to the spatial distribution of the borehole points using the region division module. Step 3: The three-dimensional modeling module generates continuous stratigraphic surfaces based on the stratigraphic layering information of each borehole, and discretizes the spatial region between adjacent stratigraphic surfaces into voxel units, and constructs a regional three-dimensional geological body model based on the voxel units. Step 4: Load the sub-region boundary layer, borehole point distribution layer and stratum boundary layer on the standard electronic map through the electronic map module; receive any polygonal selection area and depth range selected by the user on the standard electronic map; determine the borehole points and stratum layer information contained in the polygonal selection area; and send the borehole and stratum layer data associated with the covered sub-region to the statistical evaluation module. Step 5: Read the historical measurement values ​​of the same type of geological parameters in the same sub-region at different time points through the time series prediction module, calculate the rate of change, and use the weighted moving average method to predict the parameter values ​​at a specified future time. When there are related parameters, the predicted values ​​are corrected according to the historical correlation coefficient, and the prediction results are output to the statistical evaluation module. Step 6: Receive the geotechnical physical and mechanical parameters of the sub-region covered by the polygonal selection area sent by the electronic map module through the statistical evaluation module, and the prediction results of the corresponding parameters of the sub-region output by the time series prediction module, and generate a quantitative evaluation report containing current statistical characteristics and future prediction trends.

9. A regional three-dimensional geological evaluation method according to claim 1, characterized in that, Step 5, in which the prediction result is output, includes the following steps: Step 5.1: Extract the historical measurement sequence of the same type of geological parameter in the same sub-region, sorted by time, from the data acquisition module; Step 5.2: Calculate the rate of change of adjacent time points in the historical measurement value sequence, and perform a weighted moving average on the most recent N rates of change to obtain the current average rate of change, wherein the measurement value closer to the current time has a higher weight; Step 5.3: Store the historical correlation coefficients between different types of geological parameters within the same sub-region. When a second type of parameter is associated with the current predicted parameter, read the current average rate of change of the second type of parameter, calculate the deviation between the measured ratio and the historical correlation coefficient, and if the deviation exceeds a preset threshold, correct the current average rate of change. The correction process is as follows: ； in The current average rate of change, Historical correlation coefficient This is the measured ratio. For the rate of change of the associated parameter, This is a correction factor; Step 5.4: The prediction value calculation unit calculates the predicted value at a specified future time based on the corrected average rate of change and the most recent measurement value. The calculation process is as follows: ； in, For predicted values, This is the most recent measurement. To measure time, Predicting moments for the future.

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