Data processing method and platform based on three-dimensional hierarchical data model, and medium

Abstract

The embodiment of the invention provides a data processing method based on a three-dimensional hierarchical data model, a platform and a medium. The method comprises the following steps: firstly, acquiring multi-source hydrogeological data; classifying the data to obtain a first type of data and a second type of data; then, according to the three-dimensional hydrogeological hierarchical model, extracting a hierarchical association relationship of the two types of data; the first class data and the second class data are used for representing the incidence relation of the first class data and the second class data at different levels of geological observation angles; storing the first type of data in a relational database, and storing the second type of data in a non-relational database; and finally, according to the hierarchical association relationship, establishing a hydrogeological knowledge graph and storing the hydrogeological knowledge graph in an interactive coordination system. According to the method, after the multi-source hydrogeological data are classified, the incidence relations at different levels of geological observation angles are extracted and stored in the relational database and the non-relational database respectively, mapping between the databases is established by adopting the knowledge graph, the multi-source hydrogeological data are effectively integrated, and meanwhile query is facilitated.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and particularly relates to a data processing method, platform and medium based on a three-dimensional hierarchical data model. Background Art

[0002] With the deepening of hydrogeological research and the increasing richness of data acquisition means, a large amount of multi-source hydrogeological data has been continuously accumulated, covering data of different types, scales and sources. In order to better understand and analyze the complexity of the hydrogeological system and accurately predict the movement of groundwater, resource quantity and the interaction with the geological environment, etc., it is necessary to effectively integrate and deeply analyze these data.

[0003] Since multi-source hydrogeological data comes from different channels, traditional data processing methods are usually cumbersome and error-prone when integrating these data, and it is also difficult to query after integration. Summary of the Invention

[0004] In view of this, the present invention provides a data processing method, platform and medium based on a three-dimensional hierarchical data model, aiming to solve the problems that traditional data processing methods are usually cumbersome and error-prone when integrating these data, and it is also difficult to query after integration.

[0005] The first aspect of the embodiment of the present invention provides a data processing method based on a three-dimensional hierarchical data model, which is applied to a three-dimensional data management platform. The three-dimensional data management platform includes a relational database, a non-relational database and an interactive coordination system; a three-dimensional hierarchical data model is set in the interactive coordination system; the method includes:

[0006] Obtain multi-source hydrogeological data of a target area;

[0007] Classify the multi-source hydrogeological data to obtain first-class data and second-class data;

[0008] Extract the hierarchical association relationship between the first-class data and the second-class data according to the three-dimensional hydrogeological hierarchical model; wherein, the hierarchical association relationship is used to represent the association relationship between the first-class data and the second-class data from different hierarchical geological observation perspectives;

[0009] Store the first-class data in the relational database and store the second-class data in the non-relational database;

[0010] Establish a hydrogeological knowledge graph according to the hierarchical association relationship and store it in the interactive coordination system.

[0011] In a possible implementation manner, extracting the hierarchical association relationship between the first-class data and the second-class data according to the three-dimensional hydrogeological hierarchical model includes:

[0012] Divide the target area into multiple sub-areas;

[0013] For each sub-area, perform the following steps: Extract the first horizontal hierarchical association and the first vertical hierarchical association of the first type of data; Extract the second horizontal hierarchical association and the second vertical hierarchical association of the second type of data; Extract the third horizontal hierarchical association and the third vertical hierarchical association between the first type of data and the second type of data.

[0014] In a possible implementation, dividing the target area into multiple sub-areas includes:

[0015] Extract the geological structure features and hydrogeological boundary features in the multi-source hydrogeological data of the target area;

[0016] Divide the target area into multiple sub-areas according to the geological structure features and hydrogeological boundary features.

[0017] In a possible implementation, extracting the first horizontal hierarchical association and the first vertical hierarchical association of the first type of data includes:

[0018] Extract the horizontal direction stratigraphic lithology association features and horizontal flow association features in the first type of data as the first horizontal hierarchical association;

[0019] Extract the vertical direction stratigraphic structure association features, aquifer and aquitard configuration association features, and groundwater vertical recharge and discharge association features in the first type of data as the first vertical hierarchical association.

[0020] In a possible implementation, extracting the second horizontal hierarchical association and the second vertical hierarchical association of the second type of data includes:

[0021] Extract the hydrogeological phenomenon association features and image data association features in the second type of data as the second horizontal hierarchical association;

[0022] Extract the stratigraphic section description association features, hydrochemical association features, and hydrogeological phenomenon association features in the second type of data as the second vertical hierarchical association.

[0023] In a possible implementation, extracting the third horizontal hierarchical association and the third vertical hierarchical association between the first type of data and the second type of data includes:

[0024] Extract the first feature between the horizontal direction stratigraphic lithology and geological phenomena, and at the same time extract the second feature between the horizontal flow and image data; Take the first feature and the second feature as the third horizontal hierarchical association;

[0025] Extract the third feature between the vertical stratigraphic structure and the stratigraphic profile description, and at the same time extract the fourth feature between the aquifer and aquitard configuration, vertical recharge and discharge of groundwater, hydrochemistry, and hydrogeological phenomena; use the third feature and the fourth feature as the third vertical-level association.

[0026] In a possible implementation, according to the hierarchical association relationship, establish a hydrogeological knowledge graph, including:

[0027] Determine the data mapping between the first type of data stored in the relational database and the second type of data stored in the non-relational database according to the hierarchical association relationship, and establish a hydrogeological knowledge graph based on the data mapping.

[0028] In a possible implementation, a three-dimensional hydrogeological model is also set in the interactive coordination system, and the method further includes:

[0029] In response to a query operation for the three-dimensional hydrogeological model, query the first type of data corresponding to the query operation from the relational database, and at the same time retrieve the corresponding second type of data from the non-relational database according to the hydrogeological knowledge graph.

[0030] The second aspect of the embodiments of the present invention provides a three-dimensional data management platform, including a relational database, a non-relational database, and an interactive coordination system; a three-dimensional hierarchical data model is set in the interactive coordination system; the interactive coordination system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the data processing method based on the three-dimensional hierarchical data model in the first aspect above.

[0031] The third aspect of the embodiments of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the data processing method based on the three-dimensional hierarchical data model in the first aspect above.

[0032] The data processing method, platform and medium based on a three-dimensional hierarchical data model provided by the embodiments of the present invention first obtain multi-source hydrogeological data of a target area; then classify the multi-source hydrogeological data to obtain first-class data and second-class data; then extract the hierarchical association relationship between the first-class data and the second-class data according to the three-dimensional hydrogeological hierarchical model, where the hierarchical association relationship is used to represent the association relationship between the first-class data and the second-class data from different hierarchical geological observation perspectives; then store the first-class data in a relational database and store the second-class data in a non-relational database; finally, establish a hydrogeological knowledge graph according to the hierarchical association relationship and store it in an interactive coordination system. By classifying the multi-source hydrogeological data, extracting the association relationships from different hierarchical geological observation perspectives, storing them in a relational database and a non-relational database respectively, and using a knowledge graph to establish a mapping between the databases, the present invention effectively integrates the multi-source hydrogeological data and is also convenient for querying. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings without creative efforts based on these drawings.

[0034] Figure 1 is a flowchart of the implementation of the data processing method based on a three-dimensional hierarchical data model provided by the embodiments of the present invention;

[0035] Figure 2 is a schematic structural diagram of the data processing device based on a three-dimensional hierarchical data model provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0037] Figure 1 is a schematic structural diagram of a multi-source composite power supply ground electric vehicle provided by the embodiments of the present invention. As Figure 1As shown, in some embodiments, a data processing method based on a three-dimensional hierarchical data model is applied to a three-dimensional data management platform, which includes a relational database, a non-relational database, and an interaction coordination system; a three-dimensional hierarchical data model is set in the interaction coordination system; the method includes:

[0038] S110, obtaining multi-source hydrogeological data of a target area.

[0039] S120, classifying the multi-source hydrogeological data to obtain first-class data and second-class data.

[0040] S130, extracting the hierarchical association relationship between the first-class data and the second-class data according to the three-dimensional hydrogeological hierarchical model; wherein, the hierarchical association relationship is used to represent the association relationship between the first-class data and the second-class data from different hierarchical geological observation perspectives.

[0041] S140, storing the first-class data in the relational database and storing the second-class data in the non-relational database.

[0042] S150, establishing a hydrogeological knowledge graph according to the hierarchical association relationship and storing it in the interaction coordination system.

[0043] In the embodiments of the present invention, the multi-source hydrogeological data may come from the following channels:

[0044] Field on-site exploration: Organize a professional geological exploration team to obtain borehole data through drilling, record the position coordinates of the boreholes (latitude, longitude, altitude, etc.), the lithology description at different depths (such as the specific stratification of sandstone, shale, limestone, etc.), the buried depth of the groundwater level, the water temperature, etc.; conduct hydrogeological surveys on the surface, observe the outcrop position, flow rate, hydrochemical characteristics of springs, and the water levels, flow rates, and mutual relationships with surrounding groundwater of surface water bodies such as rivers and lakes, and make detailed records.

[0045] Application of geophysical exploration means: Use a variety of geophysical methods to collect data. For example, through seismic exploration, artificial seismic waves are emitted underground, and reflected wave signals are received to analyze information such as the structure, thickness of the strata, and interface characteristics between different strata; use electrical exploration to obtain the underground resistivity distribution according to the conductivity differences of different geological bodies underground, and then infer relevant hydrogeological parameters such as the location, scope, and water-richness of the aquifer.

[0046] Groundwater monitoring well network: Relying on the already laid groundwater monitoring wells, regularly (such as daily, weekly, monthly and other different frequencies, depending on the monitoring purpose and requirements) obtain water level dynamic change data and water quality monitoring data (including various ion concentrations, pH, total dissolved solids and other indicators), and record the basic information such as the geographical location, depth, and well structure of the monitoring wells to form a long-term series of groundwater dynamic observation data sets.

[0047] Collection of existing geological data: Collect the results of regional geological surveys conducted by geological departments and scientific research institutions in the past, including geological maps of different scales (which can intuitively reflect the distribution of strata, structural morphology, etc.) and geological reports (which elaborate on the regional geological evolution history, hydrogeological conditions, etc.); organize historical hydrogeological research materials, such as groundwater numerical simulation results and water resources evaluation reports in specific areas, and extract various types of data related to the current research.

[0048] Utilization of remote sensing data: With the help of satellite or aerial remote sensing technology, high-resolution remote sensing images are obtained. Through the interpretation and analysis of the images, the geomorphic features of the surface (such as mountains, plains, valleys and other terrain types), vegetation coverage (different vegetation types and distribution ranges), water distribution (rivers, lakes, wetlands, etc.) and other information are identified. This macro-level information helps to infer the hydrogeological conditions of the region. For example, the relationship between surface water bodies and surrounding geological landforms can be used to infer the source of groundwater recharge and the direction of runoff.

[0049] Laboratory analysis data integration: The collected water samples, rock samples and other samples are analyzed in professional laboratories to obtain detailed water chemical analysis results (such as the content of various trace elements in the water, isotope composition, etc., which can be used to trace the source of groundwater and the water-rock interaction process), rock physical and mechanical properties test data (porosity, permeability, compressive strength, etc., which are of great significance for studying the migration laws of groundwater in rocks), and these experimental analysis data are included in the overall data set.

[0050] In an embodiment of the present invention, classification rules are formulated based on factors such as the structural characteristics of hydrogeological data, data integrity requirements, and subsequent usage scenarios. For example, from the perspective of structural characteristics, data with a clear fixed structure and clearly defined field and table relationships are classified into one category; and data with a relatively flexible structure and difficult to represent with a fixed table structure are classified into another category. From the perspective of data integrity requirements, data that have extremely high requirements for accuracy and consistency and involve multi-table associations and complex business logic (such as data updates that require multiple related data to change synchronously) are classified into one category; relatively speaking, data that are not so strict with format specifications and association requirements are classified into another category. From the perspective of subsequent usage scenarios, data that are commonly used for precise queries, data analysis and calculations, and that must follow strict transaction processing can be classified into one category; data in flexible formats that are mainly used for quick browsing, reference, or auxiliary analysis are classified into another category.

[0051] Specifically, the following data can be classified as the first category of data:

[0052] Basic geological information data: including stratigraphic stratification data within the region, clearly recording the number, name, top and bottom surface depth, lithological characteristics and other information of each stratum. These data structures are fixed and need to be accurately associated. For example, changes in the top and bottom surface depth data of a certain stratum will affect the relevant parameters of its overlying and underlying strata, so it is suitable for relational database storage; there are also geological structure-related data, such as the shape of folds, axial position, two-wing occurrence, and detailed information such as the strike, dip, and fault distance of the fault. There are strict spatial geometric relationships and logical associations between them, which also belong to this category.

[0053] Basic groundwater attribute data: such as the basic information of groundwater monitoring wells (well number, coordinates, well completion time, depth, pipe diameter, etc.) and time series data such as water level and water temperature monitored over a long period of time. These data usually need to be accurately queried and statistically analyzed according to dimensions such as time and space, and the integrity and consistency of the data must be ensured when the data is updated (such as adding a new monitoring well, modifying the basic information of a monitoring well, etc.). Therefore, they are classified as the first type of data.

[0054] Data related to hydrogeological engineering: For example, pumping test data records the layout of pumping holes and observation holes (coordinates, depth, etc.), pumping flow, water level drop and other parameters. These data need to be strictly associated and processed in accordance with specifications during the calculation of hydrogeological parameters (such as the determination of permeability coefficient, hydraulic conductivity, etc.) and subsequent engineering design, water resources evaluation and other work, so they are classified as the first type of data.

[0055] The following data may be classified as Category 2 data:

[0056] Geological exploration descriptive data: detailed written descriptions of geological phenomena recorded by staff during field geological exploration (such as descriptions of the characteristics of a particular geological outcrop, on-site observation records of stratigraphic contact relationships, etc.), hand-drawn geological sketch maps (showing intuitive but irregular graphic information such as local geological structures and stratigraphic profile forms). The structures of these contents are relatively flexible and difficult to standardize with a fixed table structure. They are suitable for storage in a non-relational database for easy access, supplementation, and update at any time.

[0057] Image data: including regional geological images with different resolutions obtained through aerial photography and satellite remote sensing, as well as photos and videos of some geological phenomena taken on-site in the field. They are mainly used to visually display geological and geomorphic features and assist in analyzing regional hydrogeological conditions. Their formats and contents are diverse and are more suitable for management in a non-relational database environment for quick retrieval and browsing.

[0058] Expert experience and auxiliary reference data: such as expert comprehensive judgment opinions on regional hydrogeological conditions, hydrogeological case analysis materials of similar regions in history, etc. These data mostly exist in the form of documents, with free content forms and no strict structural characteristics. They can be classified into the second type of data for easy reference when needed to assist in the research and decision-making of hydrogeological problems.

[0059] In some embodiments, according to the three-dimensional hydrogeological hierarchical model, the hierarchical association relationships between the first type of data and the second type of data are extracted, including: dividing the target area into multiple sub-areas; for each sub-area, the following steps are performed: extracting the first horizontal hierarchical association and the first vertical hierarchical association of the first type of data; extracting the second horizontal hierarchical association and the second vertical hierarchical association of the second type of data; extracting the third horizontal hierarchical association and the third vertical hierarchical association between the first type of data and the second type of data.

[0060] In some embodiments, dividing the target area into multiple sub-areas includes: extracting the geological structure features and hydrogeological boundary features in the multi-source hydrogeological data of the target area; and dividing the target area into multiple sub-areas according to the geological structure features and hydrogeological boundary features.

[0061] In the embodiments of the present invention, through materials such as geological maps and geological exploration reports, the types of geological structures in the target area are determined, such as faults, folds, joints, etc. These structural information are digitized using GIS software. For example, fault lines are drawn as vector data, and their attributes such as strike, dip, and throw are recorded. For folds, information such as the position of the axial plane, the type of fold (such as anticline, syncline), and the occurrence of the two wings are determined. The characteristics of these geological structures are very crucial for dividing sub-areas because they will change the distribution of strata and hydrogeological conditions. Dividing sub-areas with faults as boundaries is a common method. Since the strata on both sides of a fault usually move, resulting in significant changes in hydrogeological characteristics such as the flow path of groundwater and the connectivity of aquifers, the two sides of the fault can be divided into different sub-areas. For folds, they are divided according to the range of their axial plane and two wings. For example, the core and two wings of an anticline are divided into different sub-areas respectively because the rocks in the core of the anticline are usually more fractured and have better permeability, while the stratigraphic structure and hydrogeological conditions of the two wings may be different.

[0062] In the embodiments of the present invention, the surface water basins are divided according to the watershed divide. The watershed divide is the boundary between adjacent basins. Water will flow into different water systems from both sides of the watershed divide, thus forming different surface water basins. For each surface water basin, factors such as its area size and the complexity of the water system are considered. If the basin area is large and the water system is complex, it can be further subdivided according to the basin range of the main tributaries. For example, for the basin of a large river, it can be divided into different sub-basins such as the upper, middle, and lower reaches because the hydrogeological conditions (such as the degree of interaction between groundwater and surface water) in different river sections may be different. The groundwater flow systems are divided according to the recharge area, runoff area, and discharge area of groundwater. These areas are determined by analyzing factors such as groundwater level data and the permeability of strata. For example, in the recharge area of groundwater in mountainous areas, precipitation infiltration is the main recharge source of groundwater, where the strata have good permeability and the water level is high; while in the discharge area of groundwater in plain areas, groundwater may be discharged through springs or artificial extraction, etc., and the water level is low. These different functional areas can be divided into different sub-areas to study the flow and transformation relationship of groundwater between different areas.

[0063] In some embodiments, the first horizontal hierarchical association and the first vertical hierarchical association of the first type of data are extracted, including: extracting the horizontal direction stratigraphic lithology association characteristics and horizontal flow association characteristics in the first type of data as the first horizontal hierarchical association; extracting the vertical direction stratigraphic structure association characteristics, the aquifer and aquitard configuration association characteristics, and the groundwater vertical recharge and discharge association characteristics in the first type of data as the first vertical hierarchical association.

[0064] In the embodiments of the present invention, on the same horizontal level, the first type of data includes information such as drilling data that can reflect the formation lithology. By analyzing this data, the distribution and variation of the formation lithology at different positions can be understood. For example, in a certain sub-region, from one side to the other side, it may be the case that the formation lithology gradually transitions from sandstone to shale and then changes to limestone. The arrangement, contact relationship, and respective characteristics of these formations with different lithologies in space (such as relatively good permeability of sandstone and the often water-blocking effect of shale, etc.) together constitute the horizontal formation lithology correlation characteristics. This correlation characteristic is crucial for studying the runoff situation of groundwater in the horizontal direction. Since the formations with different lithologies have different permeabilities, groundwater will preferentially flow along the formations with good permeability. Therefore, by sorting out the horizontal formation lithology correlation characteristics, the main runoff channels of groundwater in the horizontal direction and the areas where it may be blocked can be determined, which helps to analyze the horizontal flow law of groundwater in the region and its interaction relationship with the surrounding environment. Specifically, the horizontal formation lithology correlation characteristics can be summarized by compiling a formation lithology profile diagram and comparing the similarities and differences of the lithologies at the same horizontal height between adjacent profiles.

[0065] In the embodiments of the present invention, based on the data such as water levels and water temperatures recorded by the groundwater monitoring wells in the first type of data, combined with relevant information such as formation lithology and geological structure, the flow characteristics such as water level differences and water flow directions of groundwater at different positions in the sub-region are analyzed on the same horizontal level. For example, if the water levels of several adjacent monitoring wells show a certain high-low change, the groundwater at the higher water level will flow towards the lower water level. Considering factors such as formation permeability, the specific flow path of groundwater on this horizontal level and the hydraulic connection between different positions can be determined, and these form the horizontal flow correlation characteristics. Understanding the horizontal flow correlation characteristics helps to grasp the dynamic changes of groundwater in the region and the hydraulic connectivity in the horizontal direction between different regions. This is of great significance for studying the distribution of water resources, evaluating the available amount of water resources, and analyzing the impact of human activities (such as groundwater extraction, irrigation, etc.) on the horizontal flow of groundwater, and can provide a basis for the reasonable planning of water resource utilization and protection. Specifically, the horizontal flow correlation characteristics of groundwater can be clearly presented by means of numerical simulation or drawing equal water level diagrams, water flow vector diagrams, etc.

[0066] In the embodiments of the present invention, by recording the stratification of different depth strata in the first type of data (for example, borehole data clearly shows information such as the thickness, lithological changes of each stratum and their contact relationships, etc.), the characteristics and changes of each stratum from top to bottom in the vertical direction are analyzed. For example, observe whether the contact between the shallow loose sediment stratum and the deep bedrock stratum in a certain sub-region is conformable or unconformable. This contact relationship will affect the vertical migration of groundwater. For example, an unconformable contact may form a channel or an impermeable boundary for groundwater migration. The structural characteristics and mutual relationships of these strata in the vertical direction constitute the vertical stratigraphic structure correlation characteristics. Mastering the vertical stratigraphic structure correlation characteristics can help to deeply understand the occurrence and migration conditions of groundwater in the vertical direction. Because the stratigraphic structure determines whether groundwater can flow up and down between different strata and the ease of flow, it has a key guiding role in studying the vertical changes involved in the processes of groundwater recharge, runoff, and discharge, such as how precipitation infiltrates and recharges groundwater through different strata. Specifically, by comparing the stratigraphic data at different depths of multiple boreholes, a stratigraphic columnar diagram is drawn to clearly show the vertical changes of the strata at each borehole location, and characteristics such as the continuity or discontinuity of the strata and lithological alternation are analyzed to extract the vertical stratigraphic structure correlation characteristics; or a three-dimensional geological modeling software can be used. After importing the borehole data, a three-dimensional stratigraphic model is generated to more intuitively observe the vertical correlation of the stratigraphic structure.

[0067] In the embodiments of the present invention, based on the detailed parameter descriptions of aquifers and aquitards in the first type of data (such as the thickness, burial depth, and permeability coefficient of aquifers, and the lithology and water-resisting properties of aquitards), the blocking or leakage conditions between different aquifers through aquitards in the vertical direction are analyzed. For example, if there are multiple aquifers and the intermediate aquitard is thin and has certain water permeability in terms of lithology, then it is necessary to analyze the hydraulic connection between each aquifer through the aquitard, such as whether there is leakage recharge, etc. These configuration relationship and interaction characteristics between aquifers and aquitards in the vertical direction are the configuration correlation characteristics of aquifers and aquitards. Such correlation characteristics are very important for accurately grasping the migration law of groundwater in the vertical direction and the water volume exchange between different aquifers. When conducting groundwater resource evaluation, groundwater numerical simulation, and studying the mutual relationship between deep groundwater and shallow groundwater, etc., it is necessary to clearly understand the configuration correlation characteristics of aquifers and aquitards in order to reasonably analyze the dynamic changes of the groundwater system and the balance of water resources. Specifically, relevant parameter data of aquifers and aquitards can be sorted out, a table or cross-section can be established, the situation of aquitards between different aquifers can be compared, and the hydraulic connection between different aquifers can be analyzed in combination with groundwater level monitoring data, etc.; or groundwater numerical simulation software can be used to input the parameters of aquifers and aquitards, simulate the migration process of groundwater in the vertical direction, and then determine their configuration correlation characteristics.

[0068] In the embodiments of the present invention, by combining the groundwater level monitoring data at different depths in the first type of data and relevant data such as precipitation infiltration and evaporation excretion (these data can be directly measured or obtained through analysis and calculation), the recharge sources of groundwater in the vertical direction (such as atmospheric precipitation infiltrates into the shallow aquifer through the unsaturated zone) and the excretion methods (such as deep groundwater excretes upward through leakage or artificial extraction, etc.) are analyzed, and the recharge and excretion relationships of each layer of groundwater in the vertical direction are clarified. These relationships constitute the vertical recharge and excretion correlation characteristics of groundwater. Understanding the vertical recharge and excretion correlation characteristics of groundwater is indispensable for comprehensively understanding the circulation process of the groundwater system and the dynamic balance of water resources. It can help determine the recharge volume, excretion volume of groundwater in the region and the water volume conversion between different layers of groundwater, and provide key basis for aspects such as water resources management, formulating groundwater protection strategies, and analyzing the impact of changes in regional hydrogeological conditions on water resources. Specifically, meteorological data such as precipitation and evaporation, as well as groundwater level, water volume, etc. data at different depths can be collected, and by establishing a water balance equation, the changes in recharge and excretion volumes of each layer of groundwater at different time periods can be analyzed; or isotope tracing technology can be used to analyze the changes in the isotope composition of groundwater, trace the recharge sources and excretion paths of groundwater, and thus extract the vertical recharge and excretion correlation characteristics of groundwater.

[0069] Among them, the model structure of the three-dimensional hydrogeological hierarchical model specifically includes an input layer, a hidden layer, and an output layer.

[0070] The input layer receives rich hydrogeological data from different channels. Among them, the field geological exploration data includes detailed borehole information, such as the borehole location determined by precise longitude and latitude and altitude, as well as a meticulous description of the lithology of strata at different depths, such as the particle size of sandstone and the bedding characteristics of shale, and the precise measured value of the groundwater depth and the real-time monitoring data of water temperature; the spring emergence location obtained from the surface hydrogeological survey is positioned by high-precision positioning, the flow rate is measured by a professional flowmeter, and the hydrochemical characteristics cover various ion concentrations, pH and other indicators. The water level and flow rate data of surface water bodies such as rivers and lakes and the detailed records of their interaction with surrounding groundwater, such as the estimated recharge amount of groundwater to lakes.

[0071] Deep integration of geophysical exploration data: After the reflected wave signals transmitted by seismic exploration are processed, they are converted into digital information of the stratum structure, including the thickness distribution of strata, the clear definition of the interfaces between different strata, and the elastic wave velocity characteristics of strata, etc.; the underground resistivity distribution obtained by electrical exploration is presented in the form of a three-dimensional matrix, accurately reflecting the conductivity differences of different geological bodies, thus providing a key basis for inferring the location, scope and water-richness of aquifers, and its data accuracy can reach the meter level or even higher.

[0072] Dynamic incorporation of groundwater monitoring well network data: The long-term accumulated groundwater monitoring well data includes the dynamic change curves of water levels regularly monitored daily, weekly or monthly, which can clearly show the fluctuation trend of water levels over time, such as the seasonal rise and fall law of water levels; the water quality monitoring data covers a large number of chemical indicators, such as heavy metal ion concentrations, dissolved oxygen content, etc., and at the same time records the basic information such as the geographical location, depth, and well structure of the monitoring wells. These information are input in a standardized format to ensure the integrity and consistency of the data.

[0073] Comprehensive integration of existing geological data: The regional geological survey results of historical geological departments and scientific research institutions are based on geological maps at different scales, accurately depicting the details of the boundaries, strikes and tectonic forms of stratum distribution, such as the curvature of folds and the extension length of faults; the description of the regional geological evolution history in geological reports details the sedimentation and tectonic movement processes of strata from the geological time scale, and the general situation of hydrogeological conditions includes the formation, evolution and interaction relationship with the surrounding environment of the aquifer system. These data are input into the model after digital processing.

[0074] Macroscopic introduction of remote sensing data: High-resolution images obtained by satellite or aerial remote sensing technology are input in the form of a pixel matrix after professional preprocessing such as radiometric correction and geometric correction. The geomorphic features of the earth's surface are clearly presented in the images, such as the slope and aspect information of mountains, the flatness and scope definition of plains, and the topographic undulation and trend of valleys; the vegetation coverage is accurately quantified by vegetation indices, and different vegetation types and their distribution densities can be distinguished; the water body distribution can not only identify the locations and areas of rivers, lakes, wetlands, etc., but also obtain information such as the turbidity and eutrophication degree of water bodies through spectral analysis, providing a macroscopic perspective for inferring the hydrogeological conditions of the region.

[0075] Fine supplementation of laboratory analysis data: The hydrochemical analysis results obtained from the analysis of water samples and rock samples collected in a professional laboratory include the accurate contents of trace elements in water and the detailed ratios of isotope compositions. These data are measured by high-precision instruments, and the error is controlled within a very small range; the test data of the physical and mechanical properties of rocks, such as the porosity is accurately measured by mercury intrusion method or gas adsorption method, the permeability is measured by steady-state or transient permeability test devices, and the compressive strength is tested by a universal material testing machine, providing key parameter support for studying the migration law of groundwater in rocks.

[0076] The hidden layer consists of multiple levels, and each level contains a large number of neurons. In the first hidden layer, the neurons are fully connected to the input layer through learnable weights. For formation lithology data, the neurons can sensitively capture the characteristic patterns such as the texture, color, and mineral composition of different lithologies, and strengthen the recognition of key features through weight adjustment; for water level data, the neurons can extract the characteristics such as the short-term fluctuation frequency, long-term change trend, and seasonal cycle of the water level. As the data is transmitted between the hidden layers, the subsequent hidden layers further combine and abstract these primary features. In the middle hidden layer, the neurons will deeply fuse the formation structure features and groundwater flow features. For example, analyze the internal relationship between the dip angle of the formation, the water conductivity of the fault and the flow velocity and flow direction of groundwater in different formations, and continuously adjust the weights to optimize the expression of complex relationships, and gradually construct the representation of the correlation relationship from different levels of geological observation angles.

[0077] Synergistic application of activation functions and regularization techniques: In the hidden layer, advanced activation functions (such as ReLU, tanh, etc.) are used to introduce non-linear factors.

[0078] In the data classification task, the number of neurons in the output layer precisely corresponds to the data categories. The output of the neurons is converted into category probabilities through functions such as Softmax to clearly determine whether the data belongs to the first type of data (such as data with strong structure and used for precise analysis, including basic geological information data, basic groundwater attribute data, hydrogeological engineering-related data, etc.) or the second type of data (such as data with flexible structure and used as auxiliary reference, such as geological exploration descriptive materials, image data, expert experience, and auxiliary reference data, etc.). In the association relationship extraction task, the output layer generates numerical values or vectors representing the horizontal and vertical hierarchical associations between the first type of data and the second type of data. For example, for the horizontal association between formation lithology and geological phenomena, the output layer may output a precisely calculated degree of association value within the range of [0, 1], where 0 indicates no association and 1 indicates strong association. At the same time, it may also output a result containing a detailed association feature vector, such as the weight vector of the influence factors of lithology features on geological phenomena, to comprehensively reflect the tightness and specific association features between them. For vertical associations, such as the configuration of aquifers and aquitards and the vertical recharge and discharge associations of groundwater, the output layer outputs a quantitative value of the hydraulic connection between aquifers, a precise estimate of the recharge and discharge volume, and a comprehensive vector representation of relevant influencing factors, providing a highly accurate basis for subsequent data analysis and knowledge graph construction.

[0079] In some embodiments, extracting the second horizontal hierarchical association and the second vertical hierarchical association of the second type of data includes: extracting the hydrogeological phenomenon association feature and the image data association feature in the second type of data as the second horizontal hierarchical association; extracting the formation profile description association feature, the hydrochemical association feature, and the hydrogeological phenomenon association feature in the second type of data as the second vertical hierarchical association.

[0080] In the embodiments of the present invention, the second type of data covers various descriptions of hydrogeological phenomena recorded by geological exploration personnel in the field. At the same horizontal level, diverse hydrogeological phenomena will present at different positions, such as differences in weathering degrees at rock outcrops, different fracture development conditions, or differences in the positions and flow rates of groundwater outcrops, etc. By carefully sorting out the written descriptions, on-site records and other information of hydrogeological phenomena at different positions, analyzing their similarities, differences and interrelationships, the presented features are the associated features of hydrogeological phenomena. These features can help us understand the changes in hydrogeological conditions in the horizontal direction from the perspective of field observations. Different hydrogeological phenomena often imply differences in the interaction between groundwater and rocks, groundwater runoff and storage, etc. For example, if there are dense fractures and more groundwater seepage at the rock outcrop in a certain area, while there are fewer fractures and it is dry in the adjacent area, by comparing and analyzing these associated features of the phenomena, the flow trend, enrichment area and rock permeability of groundwater in the horizontal direction can be inferred, providing a basis for further grasping the overall hydrogeological pattern of the area.

[0081] Specifically, the text materials recorded in the field can be sorted and classified first, and the corresponding descriptions of hydrogeological phenomena can be marked according to different observation locations. Then, text analysis methods can be used to extract key information in the descriptions (such as fracture density, whether groundwater outcrops, etc.). By comparing the key information at different locations, qualitative analysis or constructing a simple scoring system (such as scoring according to the fracture development degree) can be used to measure their associated features; auxiliary materials such as sketches of hydrogeological phenomena drawn on-site can also be combined to visually observe the associated situation of phenomena at different positions.

[0082] In the embodiments of the present invention, the image data in the second type of data (such as aerial remote sensing images, photos of different regions taken in the field, etc.) contains rich surface information. At the same horizontal level, the images of different regions present various landform features, vegetation coverage conditions, surface water body distributions and other characteristics. By professionally interpreting, extracting features and analyzing these image data, the connections and variation rules between the image features of different regions are found, which are the associated features of the image data. For example, by observing a certain area with dense vegetation growth in a remote sensing image and sparse vegetation in the adjacent area, and combining with the surface water bodies and terrain undulations shown in the image, the associations between these features are comprehensively analyzed. The associated features of the image data help to understand the horizontal changes of hydrogeological conditions in the region from a macroscopic and intuitive perspective. The vegetation coverage is often closely related to hydrogeological elements such as the groundwater level and soil water content. The distribution and form of surface water bodies reflect the interaction state between surface water and groundwater, and the topographic and geomorphic features affect the runoff direction of groundwater, etc. Analyzing these associated features of the image data can assist in inferring the recharge, runoff and discharge paths of groundwater in the horizontal direction and the hydraulic connection between different regions, providing a multi-dimensional perspective for regional hydrogeological research.

[0083] Specifically, professional remote sensing image processing software and geographic information system (GIS) tools can be used to preprocess the image data (such as radiometric correction, geometric correction, etc.), and then relevant feature indicators are extracted. For example, the normalized difference vegetation index is calculated to measure the vegetation coverage degree, and the changes in the normalized difference vegetation index of different regions are analyzed; the features such as the boundaries and areas of surface water bodies in the image and the elements such as the slope and aspect of the terrain are observed. Spatial statistical analysis methods, such as spatial autocorrelation analysis (calculating the Moran index, etc.), are used to judge the spatial correlation of these features, and then the associated features of the image data are determined; thematic maps can also be made to visually display different features and directly compare and analyze the associations between different regions.

[0084] In the embodiments of the present invention, the second type of data includes geological sketch maps, on-site stratigraphic profile records and other materials, which detail the appearance characteristics (such as color, particle fineness, structural form, etc.) of strata at different depths from the surface to the underground and the contact relationships between strata (such as conformable contact, angular unconformable contact, etc.). By interpreting the stratigraphic profile description information in the vertical direction, analyzing the evolution laws, mutual influences between the characteristics of strata at different depths and their functional relationships with the vertical migration and occurrence of groundwater, the formed characteristics are the associated characteristics of stratigraphic profile description. For example, it can be seen from the geological sketch map that as the depth increases, the color of the strata gradually darkens, the particles become finer, and there is angular unconformable contact, which implies that the strata have experienced specific geological processes in the vertical direction and will also affect the vertical flow path and storage state of groundwater in this area. Understanding the associated characteristics of stratigraphic profile description is of great significance for deeply exploring the vertical migration mechanism of groundwater and its relationship with the surrounding strata. The structure and contact relationship of the strata determine whether groundwater can flow smoothly vertically, whether there are impermeable boundaries or leakage channels, etc. By analyzing these associated characteristics, a more accurate vertical flow model of groundwater can be constructed, the occurrence status of groundwater at different depths can be predicted, and the hydraulic connection between deep and shallow groundwater can be evaluated, providing a basis for the rational development and protection of groundwater resources.

[0085] Specifically, organize materials such as geological sketch maps and stratigraphic profile records according to different observation points, and compare the stratigraphic description information at different depths within the same sub-region. The method of stratigraphic correlation can be adopted. According to the similarities and differences in rock characteristics (color, particles, etc.), determine the continuity and changes of the strata and establish a stratigraphic sequence; for the stratigraphic contact relationship, based on professional geological judgment rules, analyze the influence of different contact types on the vertical migration of groundwater, and then summarize the associated characteristics of stratigraphic profile description. Three-dimensional geological modeling software can also be used to digitize the stratigraphic profile description information and perform three-dimensional visual display to more intuitively analyze the associated situation of stratigraphic characteristics in the vertical direction.

[0086] In the embodiments of the present invention, if there is a second type of data for hydrochemical analysis of water samples at different depths (including information such as the concentrations of various ions in water and isotope composition), by analyzing the variation laws of these hydrochemical characteristics with depth and their mutual relationships with formation lithology and groundwater flow conditions, the characteristics reflected are the hydrochemical correlation characteristics. For example, as the depth increases, the concentrations of certain specific ions in groundwater gradually increase. At the same time, by combining the formation lithology within this depth range (such as the presence of a rock layer rich in this ion) and the flow direction of groundwater (to judge the ion source and migration path), the water-rock interaction process between groundwater and the surrounding rocks in the vertical direction and the hydraulic connection between different aquifers can be sorted out. These characteristics and connections reflected in hydrochemistry are the hydrochemical correlation characteristics. The hydrochemical correlation characteristics can reveal the evolution process of groundwater in the vertical direction and its interaction with the surrounding environment from the perspective of chemical composition. Different hydrochemical characteristics can indicate important information such as the recharge source of groundwater, runoff path, and the intensity of water-rock interaction experienced. By analyzing these correlation characteristics, it helps to deeply understand the complexity of the groundwater system, such as judging whether there is a hydraulic connection between different aquifers, whether the groundwater is polluted, and the source and diffusion path of the pollution, providing a key basis for work such as water resource quality evaluation and groundwater pollution prevention and control.

[0087] Specifically, first, organize and standardize the hydrochemical analysis data at different depths to ensure the accuracy and comparability of the data. Then, use statistical analysis methods, such as plotting the curve of ion concentration change with depth to observe the change trend; adopt multivariate statistical methods such as principal component analysis (PCA) to extract the main change trends of hydrochemical components and their mutual relationships. Combine the formation lithology and groundwater flow conditions (such as aquifer location, water flow direction, etc.) in the first type of data, and determine the hydrochemical correlation characteristics through means such as comparative analysis and correlation research. For example, by analyzing the correlation between the concentration of a specific ion in water and a certain formation lithology, judge whether the ion comes from the water-rock interaction process of this formation, and then establish the hydrochemical correlation characteristics in the vertical direction.

[0088] In the embodiments of the present invention, by comprehensively considering various types of materials in the second type of data and analyzing the mutual relationships and changes of hydrogeological phenomena at different depths as a whole in the vertical direction (such as the outcrop situation of groundwater at different depths, the change of formation fragmentation degree with depth, the hydrochemical characteristics at different depths, etc.), the comprehensive characteristics presented are the vertical correlation characteristics of hydrogeological phenomena. For example, the on-site exploration records show that groundwater emerges in the form of a spring at a certain depth, and the formation at this depth has a high degree of fragmentation. At the same time, hydrochemical analysis indicates that there are obvious changes in the concentrations of certain ions in the groundwater here. By synthesizing these hydrogeological phenomena at different levels in the vertical direction and analyzing their internal relationships and the impacts on aspects such as the vertical migration and occurrence of groundwater, the vertical correlation characteristics of hydrogeological phenomena are formed. Such comprehensive correlation characteristics can comprehensively reflect the dynamic changes and internal relationships of hydrogeological conditions from the surface to the deep underground in the region, avoiding the limitations when analyzing groundwater from a single perspective (such as formation structure or hydrochemistry, etc.). It helps to construct a more complete and accurate vertical migration model of groundwater, understand more deeply the recharge, runoff, and discharge mechanisms of groundwater in the vertical direction, as well as the impacts of hydrogeological conditions at different depths on the quantity and quality of water resources, providing multi-faceted support for the research and solution of complex hydrogeological problems.

[0089] Specifically, integrate different types of the second type of data (on-site exploration records, image data, hydrochemical analysis data, etc.), and conduct hierarchical sorting and comparative analysis according to depth. Methods such as the geographically weighted regression (GWR) model can be used. This model can take into account the influence of spatial position (which can be understood as the vertical spatial position of depth here) on the variable relationship, incorporate relevant variables of hydrogeological phenomena at different depths (such as formation fragmentation degree, groundwater outcrop situation, ion concentration, etc.) into the model, analyze their mutual relationships at the vertical level, and extract the vertical correlation characteristics of hydrogeological phenomena that can reflect the changes and internal relationships of hydrogeological conditions from the surface to the deep underground in the sub-region; or a comprehensive cross-section can be drawn to visually display various hydrogeological phenomena at different depths, and qualitative analysis and summary can be carried out to extract relevant correlation characteristics.

[0090] In some embodiments, extract the third horizontal-level correlation and the third vertical-level correlation between the first type of data and the second type of data, including: extract the first feature between the formation lithology and geological phenomena in the horizontal direction, and at the same time extract the second feature between the horizontal flow and image data; take the first feature and the second feature as the third horizontal-level correlation; extract the third feature between the formation structure and the formation profile description in the vertical direction, and at the same time extract the fourth feature between the configuration of aquifers and aquitards, vertical recharge and discharge of groundwater, hydrochemistry, and hydrogeological phenomena; take the third feature and the fourth feature as the third vertical-level correlation.

[0091] In the embodiments of the present invention, the first type of data includes formation lithology information obtained through means such as drilling and geological mapping, showing what kinds of rocks the formations at different positions on the same horizontal plane are composed of, such as sandstone, shale, limestone, etc., as well as the distribution range and variation of these lithologies. Formations with different lithologies have different physical and chemical properties. For example, sandstone has relatively large porosity and good permeability, while shale often has small porosity and plays a role in water isolation. These characteristics affect the flow of groundwater and its interaction with the surrounding environment. The second type of data records various geological phenomena observed in the field, such as the weathering degree at the rock outcrop, the development of fractures, the emergence position and flow rate of groundwater, etc. These phenomena intuitively reflect the actual hydrogeological performance at different locations in the horizontal direction, presenting the result of the combined action of formation lithology and other factors.

[0092] The first feature between the formation lithology and geological phenomena in the horizontal direction is to link the inherent properties of the formation lithology with the corresponding manifestations of geological phenomena, and analyze the internal laws and mutual influence relationships existing between them. For example, when the formation lithology is sandstone and the fractures are relatively densely developed, phenomena such as the emergence of groundwater at the corresponding position or a relatively fast runoff speed can often be observed; while for a formation mainly composed of shale, the ground surface may be dry, with few fractures and no obvious groundwater runoff. The regular characteristics summarized through this kind of connection are the first feature. It helps to deeply understand the actual flow path, enrichment area of groundwater in the horizontal direction within the region, and the control effect of formations with different lithologies on hydrogeological phenomena. By clarifying the first feature, it is possible to more accurately infer possible geological phenomena based on the distribution of formation lithology, or conversely, infer the formation lithology situation from geological phenomena, providing a more intuitive and practical basis for the hydrogeological conditions of the research area, and also laying a foundation for subsequent work such as water resource evaluation and groundwater pollution prevention and control.

[0093] Specifically, first, sort out the information on formation lithology in the first type of data according to the horizontal position to form a formation lithology distribution layer; at the same time, label and classify the descriptions of geological phenomena in the second type of data according to the observation locations. Then, match the two at the same or similar horizontal positions so that each formation lithology area corresponds to the corresponding geological phenomenon record. For the matched data, compare the differences in geological phenomena corresponding to different lithologic formations. A table can be made to list different lithologies (such as sandstone, shale, limestone, etc.) and the corresponding common geological phenomena (such as the degree of fracture development, groundwater outcrop conditions, etc.), and analyze the frequency and correlation of their occurrences. For example, count the proportion of the number of times the groundwater outcrop phenomenon occurs in the sandstone formation within a certain range and compare it with the proportion of the number of times this phenomenon occurs in the shale formation. At the same time, combined with geological principles, comprehensively consider the influence of the physical properties of rocks (porosity, permeability, etc.) on geological phenomena, and summarize general regular characteristics, such as which lithology is likely to exhibit specific geological phenomena under what conditions. These regular characteristics are the first characteristics to be extracted.

[0094] Based on the water level, water temperature, etc. of groundwater monitoring wells in the first type of data and related information such as formation permeability and geological structure, the flow direction, flow velocity of groundwater and the hydraulic connection between different positions at the same horizontal level are analyzed. It reflects the dynamic change characteristics of groundwater in the horizontal direction. The image data (such as aerial remote sensing images, ground photos, etc.) in the second type of data contains rich surface information, such as the surface vegetation coverage, surface water body distribution, landform morphology (terrain undulation, slope, slope direction, etc.). These image features are potentially related to the horizontal flow of groundwater because the distribution and flow of groundwater will affect the surface ecological environment and the morphology of water bodies, etc.

[0095] The second feature between horizontal flow and image data is to explore the corresponding relationship and mutual influence between the horizontal flow of groundwater and the surface features shown in the image data. For example, areas with dense vegetation growth in the image often correspond to areas with high groundwater levels, relatively slow groundwater runoff and abundant water, because sufficient groundwater supply is conducive to vegetation growth; and changes in image features around surface water bodies (such as wetland vegetation at the edge of the water body, water color changes, etc.) can reflect the interaction between groundwater and surface water and the direction of groundwater discharge, etc. These connections and laws are the second features. From a macro and intuitive perspective, with the help of image data, a visualization method, we can further verify and enrich the understanding of the horizontal flow characteristics of groundwater. By extracting the second feature, we can use image data to quickly determine the approximate horizontal flow trend of groundwater in the region, the strength of hydraulic connections between different regions, etc., providing a convenient and effective method for quickly understanding regional hydrogeological conditions over a large area. At the same time, it is also helpful to conduct a comprehensive analysis of groundwater flow conditions and surface ecological environment, so as to better serve water resources management and ecological protection.

[0096] Specifically, the data on the horizontal flow of groundwater in the first category (such as the water level data of each monitoring well, the water flow direction vector, etc.) can be spatially matched and fused with the second category of image data (which can be achieved using the spatial analysis function of GIS software). The image data is preprocessed, such as radiation correction and geometric correction, to ensure the accuracy of the image data, and key image features related to groundwater (such as vegetation coverage, surface water body boundaries, etc.) are extracted, and these features are vectorized for subsequent analysis.

[0097] Correlation analysis and feature mining: Statistical analysis methods are used to measure the correlation between the horizontal flow characteristics of groundwater and the characteristics of image data. For example, the Pearson's correlation coefficient between the groundwater level data in different areas and the NDVI values ​​of the corresponding image areas is calculated. The formula is, where and are the sample values ​​of the water level data and NDVI values, respectively, and are their average values, and is the number of samples. By analyzing the size and positive and negative correlation coefficients, the degree of linear correlation between the two is determined. At the same time, combined with field surveys and professional hydrogeological knowledge, in-depth analysis is conducted on the correlated features to dig out the internal connections and laws between them, such as why the vegetation in areas with high water levels is dense, how surface water and groundwater interact with each other, etc. These connections and laws are the second features to be extracted.

[0098] The third horizontal hierarchical association synthesizes the first feature between the formation lithology and geological phenomena in the horizontal direction and the second feature between the horizontal flow and image data, aiming to comprehensively display the interconnections and synergistic relationships among hydrogeological elements on the same horizontal plane from different perspectives. It covers multiple links starting from the basic geological condition of formation lithology, to the manifestation of geological phenomena it triggers, to the actual horizontal flow of groundwater, and to the corresponding surface image feature reflections, constructing a complete horizontal hydrogeological association system, which can more systematically reflect the distribution law and variation characteristics of hydrogeological conditions in the horizontal plane of the region.

[0099] By integrating these two features into the third horizontal hierarchical association, it is possible to break through the limitations of a single data type and a single analysis perspective, and more comprehensively understand the occurrence, flow of groundwater in the horizontal direction, and its interaction with the surrounding environment. Whether it is for the overall evaluation of regional hydrogeological conditions or for analyzing and making decisions on specific practical problems such as water resource development and ecological environment protection, the third horizontal hierarchical association can provide richer and more accurate bases to help relevant personnel better grasp the complexity and integrity of the regional hydrogeological system in the horizontal direction.

[0100] The first type of data details the stratification of formations at different depths, including the thickness, lithological changes of each formation, and their contact relationships (such as conformable contact, angular unconformable contact, etc.). These information reflect the structural and arrangement characteristics of the formations in the vertical direction, which have a key impact on the vertical migration of groundwater. For example, conformably contacting formations may be more conducive to the continuous migration of groundwater, while angular unconformable contacts may form impermeable boundaries or change the flow path of water.

[0101] The formation profile descriptions in the second type of data mainly come from materials such as geological sketch maps and on-site formation profile records, presenting the appearance characteristics (such as color, particle fineness, structural form, etc.) of formations from the surface to different depths underground and an intuitive description of the contact relationships. It shows the vertical changes of formations from the perspective of on-site observation and description, and is an intuitive presentation of the actual situation of the formations.

[0102] The third feature between the vertical stratigraphic structure and the stratigraphic profile description is to compare, verify, and conduct correlation analysis on the relatively accurate and quantitative stratigraphic structure information in the first type of data and the vivid and intuitive stratigraphic profile description in the second type of data, and summarize the characteristics of their consistency, differences, and complementary relationships in the vertical direction. For example, through borehole data, it is determined that there is an angular unconformity contact of the strata at a certain depth, and obvious strata inclination and discontinuity can also be seen in the corresponding stratigraphic profile description. Moreover, the implications of both for the influence of this contact relationship on groundwater migration in the vertical direction are consistent. This consistency and mutual verification are part of the third feature. At the same time, if there are differences, analyzing whether they are caused by data accuracy problems or actual geological changes, etc., is also an important part of the third feature.

[0103] The aim is to improve the accuracy of understanding the vertical stratigraphic structure through the mutual verification and supplementation of data from different sources, more deeply understand the true structure and evolution process of the strata in the vertical direction, and then more accurately grasp the groundwater migration channels, water - resistant boundaries, and the interaction between groundwater and strata in the vertical direction. This has an important supporting role in aspects such as constructing an accurate groundwater vertical flow model, evaluating the amount of groundwater resources, and analyzing the relationship between deep and shallow groundwater, and helps to reduce the errors and one - sidedness that may be brought about by the interpretation of single data.

[0104] Specifically, first align the stratigraphic structure information in the first type of data (such as stratigraphic layer - by - layer data and contact relationship records at different depths at each borehole) with the stratigraphic profile description materials in the second type of data according to the same spatial position (which can be geographical coordinates or relative positions). Then compare the stratigraphic structure characteristics and profile description contents at the same vertical position, such as whether they are consistent in aspects such as the thickness of the strata, the name of the lithology, and the determination of the contact relationship.

[0105] For the existing differences, carefully analyze the reasons. If they are caused by different data acquisition methods (such as the limited accuracy of boreholes, while the stratigraphic profile description may be based on more detailed on - site observations), further explore the impact of such differences on understanding the stratigraphic structure and groundwater migration. Through a large number of comparative analysis examples, summarize general rules, that is, in which cases the two can well mutually verify, in which cases differences are likely to occur, and the actual geological significance represented by the differences, etc. These rule characteristics are the third feature to be extracted.

[0106] Aquifer and aquitard configuration: The first type of data provides detailed parameters of aquifers and aquitards, such as the location, thickness, permeability coefficient of aquifers, as well as information on the lithology and water-resisting properties of aquitards. These data depict the distribution, mutual relationship of aquifers and aquitards in the vertical direction, and their control over the vertical movement of groundwater, determining whether and how groundwater can flow between different aquifers, recharge, etc.

[0107] Also based on the first type of data and related meteorological, hydrological and other data, the recharge sources of groundwater in the vertical direction (such as atmospheric precipitation infiltrating into the shallow aquifer through the unsaturated zone) and discharge methods (such as deep groundwater discharging upward through leakage or artificial extraction, etc.) are analyzed, clarifying the water volume input-output relationship of groundwater in the vertical direction and the exchange process with the external environment.

[0108] The results of hydrochemical analysis in the second type of data show information such as the concentrations of various ions and isotope compositions in water samples at different depths, reflecting the water-rock interaction process that groundwater experiences in the vertical direction and the hydraulic connection between different aquifers. Because different hydrochemical characteristics can imply the source of groundwater, the flow path, and the intensity of interaction with surrounding rocks, etc.

[0109] Various hydrogeological phenomena observed in the field in the second type of data (such as the emergence of groundwater at different depths, the change of formation fragmentation degree with depth, etc.) intuitively reflect the occurrence and migration state of groundwater in the vertical direction and its interaction with the formation.

[0110] Taking these aspects into comprehensive consideration, the fourth characteristic is to explore the internal connection and co-variation law among them in the vertical direction. For example, how the configuration of aquifers and aquitards affects the vertical recharge and discharge process of groundwater, and how the vertical recharge and discharge of groundwater change the hydrochemical characteristics and trigger corresponding hydrogeological phenomenon changes; or how the change trend of hydrochemical characteristics reflects the hydraulic connection between aquifers and aquitards and the dynamic situation of groundwater vertical recharge and discharge, etc. These relationship characteristics of mutual influence and mutual restriction are the fourth characteristic.

[0111] In order to understand the complex operation mechanism of the groundwater system in the vertical direction more comprehensively and deeply, information from multiple dimensions such as geological structure (aquifer and aquitard configuration), water volume exchange (vertical recharge and discharge), chemical change (hydrochemistry), and actual performance (hydrogeological phenomena) are organically combined to construct a complete vertical hydrogeological correlation system. This helps to accurately grasp the evolution process of groundwater in the vertical direction, the mutual relationship between different aquifers, and the overall interaction between groundwater and the surrounding environment, providing a solid theoretical and practical basis for the rational development and utilization of groundwater resources, groundwater pollution prevention and control, and related hydrogeological research.

[0112] Specifically, the aquifer and aquitard configurations in the first type of data, the data related to the vertical recharge and discharge of groundwater, and the results of hydrochemical analysis and the description of hydrogeological phenomena in the second type of data are integrated and sorted according to the vertical depth to establish a multi-dimensional data set corresponding to different depths. Then, analyze the change trends and mutual relationships between the data in each dimension. For example, observe how the concentration of specific ions in groundwater changes with the change in the thickness of the aquifer, and whether there are changes in the corresponding groundwater outcrop phenomena, etc.

[0113] Model construction and law summary: Methods such as numerical simulation and statistical analysis can be used to construct models to further analyze their relationships. For example, establish a coupled model of vertical groundwater flow and hydrochemistry, input the parameters of the aquifer and aquitard and the recharge and discharge conditions, etc., simulate the changes in hydrochemical characteristics under different conditions, and compare and verify with the actually observed hydrochemical data and hydrogeological phenomena. Through a large number of analysis examples, general laws are summarized, such as under what aquifer and aquitard configurations specific hydrochemical characteristics and changes in hydrogeological phenomena will occur, and how they affect each other. These laws are the fourth feature to be extracted.

[0114] The third vertical-level association constructs a comprehensive and systematic vertical hydrogeological association framework by integrating the third feature between the vertical stratigraphic structure and the stratigraphic section description and the fourth feature between the aquifer and aquitard configurations, the vertical recharge and discharge of groundwater, hydrochemistry, and hydrogeological phenomena. It covers the mutual connections and interaction mechanisms in the vertical direction at multiple levels, from the basic description of the stratigraphic structure to the changes in the quantity and quality of groundwater and the manifestations of actual hydrogeological phenomena, and can completely present the complexity and dynamic change characteristics of the groundwater system in the vertical direction.

[0115] Using the third vertical-level association, it is possible to break through the limitations of analyzing a single vertical hydrogeological element in the past and deeply study the migration, occurrence of groundwater in the vertical direction, and its interaction laws with the surrounding environment from an overall and comprehensive perspective. When carrying out many aspects of work such as groundwater resource evaluation, formulating groundwater protection strategies, and analyzing the evolution of regional hydrogeological conditions, the third vertical-level association can provide comprehensive and accurate information support, which helps to make more scientific and reasonable decisions and research conclusions.

[0116] In some embodiments, according to the hierarchical association relationship, a hydrogeological knowledge graph is established, including: determining the data mapping between the first type of data stored in the relational database and the second type of data stored in the non-relational database according to the hierarchical association relationship, and establishing a hydrogeological knowledge graph based on the data mapping.

[0117] In the embodiments of the present invention, the common or related hydrogeological entities involved in the first type of data and the second type of data are matched. For example, in the first type of data, there is an entity of "monitoring well" which contains its detailed attribute information (coordinates, depth, etc.); in the second type of data, there may be descriptions of the geological phenomena around the monitoring well (such as the characteristics of nearby rock outcrops, the occurrence of groundwater, etc.). By identifying the "monitoring well" entity pointed to in common, a mapping relationship between the two is established. That is, the relevant records in the "monitoring well" table in the relational database are associated and mapped with all relevant documents, images and other materials in the non-relational database that mention the monitoring well, so as to prepare for reflecting the association between the monitoring well entity and its surrounding hydrogeological conditions in the subsequent atlas construction. For the formation entity, the formation stratification records (identified by formation numbers, etc.) in the first type of data correspond to the specific formations described in the geological sketch maps and formation profile records in the second type of data, and are matched and mapped according to the spatial position of the formations (depth range, etc.), so that the association relationship between different formations in terms of structure and actual performance can be accurately presented in the atlas.

[0118] In the embodiments of the present invention, the association between the attributes of the entities in the first type of data and the relevant descriptions in the second type of data is analyzed. Taking the aquifer as an example, the first type of data records the attributes of the aquifer such as its location, thickness, permeability coefficient, etc., and in the second type of data, there may be the characteristics of the aquifer reflected by the hydrochemical analysis of water samples (such as the relationship between the ion concentration in the water and the water-rock interaction of the aquifer rocks) and the occurrence of the aquifer at different depths observed in the on-site investigation, etc. Through the association of these attributes, a mapping from the aquifer attribute data in the relational database to the corresponding description data in the non-relational database is established. For example, when querying the situation of a certain aquifer in the atlas, not only can the structural attribute information be obtained, but also the associated information such as the hydrochemistry and actual hydrogeological phenomenon performance related to it can be seen. For the first type of data entity of pumping test which involves multiple attributes (pumping flow rate, drawdown, etc.), its attribute is associated and mapped with the geological response conditions (such as the settlement of the formation, the change of groundwater occurrence, etc.) around the pumping test site recorded in the second type of data, so as to comprehensively display the mutual influence relationship between the pumping test activity and the surrounding hydrogeological environment in the knowledge atlas.

[0119] Create graph nodes. First, convert the entities in the first type of data into graph nodes: Extract entity information such as "drilling holes", "monitoring wells", "strata", "aquifers", etc. from the relational database, and create corresponding nodes in the knowledge graph according to their respective unique identifiers (such as drilling hole numbers, well numbers, strata numbers, etc.). For example, for each drilling hole entity, create a node and add its relevant attributes (coordinates, final hole depth, records of lithologies of different strata at different depths in the drilling hole, etc.) as the attribute values of the node, so that each node can completely represent the corresponding entity and its basic characteristics, laying a foundation for establishing association relationships in the future. Taking the "stratum" node as an example, in addition to adding basic attributes such as stratum number and name, key attributes such as stratum thickness, top and bottom depths obtained from the first type of data can also be filled in to facilitate the intuitive display of the stratum structure characteristics in the graph and perform stratum-based association analysis.

[0120] Then convert the entities in the second type of data into graph nodes: Create nodes for the entities involved in different types of data such as geological phenomenon descriptions and image data in the second type of data. For example, different geological phenomena (such as rock outcrop fracture phenomena in a certain area, groundwater spring outcrops at specific locations, etc.) are respectively created as independent nodes, and the attributes of the nodes can include the description content of the phenomenon, the occurrence location (coordinate information can be associated and obtained from the relevant first type of data or directly extracted from the second type of data if there is a record), etc. For image data entities, create nodes and add attributes such as the name of the image, shooting time, shooting location, the area range corresponding to the image (which can be defined by geographical coordinates), etc. At the same time, a brief description of the image content (such as the image mainly shows the appearance characteristics of a certain stratum section) can be considered to be added to better reflect its association significance with other entities in the graph.

[0121] Edges are established based on the horizontal hierarchical association relationship: According to the data mapping between the formation lithology and geological phenomena in the horizontal direction, edges are created between the nodes representing formation lithology (such as the "sandstone formation" node) and the corresponding geological phenomenon nodes (such as the "fracture development phenomenon of rock outcrops in a certain area" node). The type of the edge can be defined as a "present" relationship, indicating that the formation lithology presents the corresponding geological phenomenon. At the same time, attributes can be added to the edge according to the actual situation, such as the probability of the occurrence of this phenomenon (obtained through statistical analysis of the occurrence frequency of similar phenomena in the relevant area), the degree of influence on the horizontal flow of groundwater (evaluated by combining professional knowledge and relevant data), etc., to more detailedly depict this horizontal association relationship. Based on the mapping between the horizontal flow and the image data, edges are established between the nodes representing the characteristics of groundwater horizontal flow (such as the "groundwater runoff path in a certain area" node, whose attributes include information such as the water flow direction and velocity) and the relevant nodes of the image data (such as the image node showing the surface vegetation coverage of this area). The type of the edge is set as an "association" relationship, reflecting the mutual connection between the groundwater flow and the image characteristics. Attributes can be added to the edge, such as the correlation coefficient between the two obtained through correlation analysis (such as the Pearson correlation coefficient, etc.), to intuitively reflect the tightness of the association.

[0122] Finally, edges are established based on the vertical hierarchical association relationship: According to the mapping between the formation structure and the formation profile description in the vertical direction, edges are created between the nodes representing the formation structure (such as the "stratification structure of a certain formation" node, which contains attributes such as the detailed thickness of each layer of the formation and the contact relationship) and the corresponding formation profile description nodes (such as the "description of the appearance characteristics of the formation profile in a certain area" node). The type of the edge is defined as a "corresponding" relationship, indicating the mutual verification and correspondence between the two. Attributes can be added to the edge, such as the result of data consistency verification (obtained by comparing and analyzing the degree of agreement or difference between the two in describing the formation characteristics), etc., to reflect the characteristics of this vertical association. Based on the association mapping between the aquifer and aquitard configuration, vertical recharge and discharge of groundwater, hydrochemistry and hydrogeological phenomena, multiple types of edges are created between the "aquifer" node, "aquitard" node and the nodes reflecting the vertical recharge and discharge situation of groundwater (such as the "precipitation infiltration recharges the shallow aquifer in a certain area" node), the nodes reflecting the hydrochemical characteristics (such as the "change in the concentration of specific ions in the water sample of a certain aquifer" node), and the nodes showing the relevant hydrogeological phenomena (such as the "groundwater emerges in the form of a spring at a certain depth" node), such as "influence", "cause", "reflect" and other relationship edges. The type of the edge is determined according to the actual causal relationship and interaction mechanism, and corresponding attributes (such as the magnitude of recharge, the change trend of ion concentration, etc.) are added to comprehensively construct the vertical hydrogeological association relationship network.

[0123] In some embodiments, a three-dimensional hydrogeological model is also provided in the interaction coordination system, and the method further includes: in response to a query operation for the three-dimensional hydrogeological model, querying a first type of data corresponding to the query operation from a relational database, and at the same time retrieving a corresponding second type of data from a non-relational database according to the hydrogeological knowledge graph.

[0124] In an embodiment of the present invention, if a BIM model or a VR scene of hydrogeology is displayed on the user side and the user clicks on a certain place in the model / scene, it is considered that a query operation has been performed. Query the first type of data corresponding to the query operation from the relational database and display it in the model / scene. At the same time, display brief information related to these first type of data according to the hydrogeological knowledge graph. If the user clicks on a certain piece of brief information, it is considered that the user needs to query a certain association relationship in the hydrogeological knowledge graph. At this time, retrieve the corresponding second type of data and display it.

[0125] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0126] Figure 2 It is a schematic structural diagram of a data processing device based on a three-dimensional hierarchical data model provided by an embodiment of the present invention. As Figure 2 shown, in some embodiments, a data processing device 2 based on a three-dimensional hierarchical data model includes:

[0127] An acquisition module 210, configured to acquire multi-source hydrogeological data of a target area;

[0128] A classification module 220, configured to classify the multi-source hydrogeological data to obtain a first type of data and a second type of data;

[0129] An extraction module 230, configured to extract the hierarchical association relationship between the first type of data and the second type of data according to the three-dimensional hydrogeological hierarchical model; wherein, the hierarchical association relationship is used to represent the association relationship between the first type of data and the second type of data from different hierarchical geological observation perspectives;

[0130] A storage module 240, configured to store the first type of data in a relational database and store the second type of data in a non-relational database;

[0131] An association module 250, configured to establish a hydrogeological knowledge graph according to the hierarchical association relationship and store it in the interaction coordination system.

[0132] Optionally, an extraction module 230 is configured to divide the target area into multiple sub-areas; for each sub-area, perform the following steps: extract the first horizontal hierarchical association and the first vertical hierarchical association of the first type of data; extract the second horizontal hierarchical association and the second vertical hierarchical association of the second type of data; extract the third horizontal hierarchical association and the third vertical hierarchical association between the first type of data and the second type of data.

[0133] Optionally, dividing the target area into multiple sub-areas includes: extracting the geological structure features and hydrogeological boundary features in the multi-source hydrogeological data of the target area; and dividing the target area into multiple sub-areas according to the geological structure features and hydrogeological boundary features.

[0134] Optionally, the extraction module 230 is configured to extract the horizontal-direction formation lithology association feature and the horizontal-flow association feature in the first type of data as the first horizontal hierarchical association; extract the vertical-direction formation structure association feature, the aquifer and aquitard configuration association feature, and the groundwater vertical recharge and discharge association feature in the first type of data as the first vertical hierarchical association.

[0135] Optionally, the extraction module 230 is configured to extract the hydrogeological phenomenon association feature and the image data association feature in the second type of data as the second horizontal hierarchical association; extract the formation profile description association feature, the hydrochemistry association feature, and the hydrogeological phenomenon association feature in the second type of data as the second vertical hierarchical association.

[0136] Optionally, the extraction module 230 is configured to extract the first feature between the horizontal-direction formation lithology and the geological phenomenon, and extract the second feature between the horizontal flow and the image data at the same time; use the first feature and the second feature as the third horizontal hierarchical association; extract the third feature between the vertical-direction formation structure and the formation profile description, and extract the fourth feature between the aquifer and aquitard configuration, the groundwater vertical recharge and discharge, the hydrochemistry, and the hydrogeological phenomenon at the same time; use the third feature and the fourth feature as the third vertical hierarchical association.

[0137] Optionally, a correlation module 250 is configured to determine the data mapping between the first type of data stored in the relational database and the second type of data stored in the non-relational database according to the hierarchical association relationship, and establish a hydrogeological knowledge graph based on the data mapping.

[0138] Optionally, a three-dimensional hydrogeological model is further provided in the interaction and coordination system. The device further includes: a query module, configured to query the first type of data corresponding to the query operation from the relational database in response to a query operation for the three-dimensional hydrogeological model, and at the same time retrieve the corresponding second type of data from the non-relational database according to the hydrogeological knowledge graph.

[0139] The data processing device based on the three-dimensional hierarchical data model provided in this embodiment can be used to execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here in this embodiment.

[0140] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not elaborated or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0141] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0142] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A data processing method based on a three-dimensional hierarchical data model, characterized in that: Applied to a three-dimensional data management platform, the three-dimensional data management platform includes a relational database, a non-relational database and an interactive coordination system; the interactive coordination system is provided with a three-dimensional hierarchical data model; the method includes: Obtain multi-source hydrogeological data for the target area; Classifying the multi-source hydrogeological data to obtain first-category data and second-category data; Extracting the hierarchical relationship between the first type of data and the second type of data according to the three-dimensional hydrogeological hierarchical model; wherein the hierarchical relationship is used to represent the relationship between the first type of data and the second type of data at different levels of geological observation angles; Storing the first category of data in the relational database, and storing the second category of data in the non-relational database; According to the hierarchical association relationship, a hydrogeological knowledge map is established and stored in the interactive coordination system.

2. The data processing method based on the three-dimensional hierarchical data model according to claim 1 is characterized in that: According to the three-dimensional hydrogeological hierarchical model, the hierarchical relationship between the first type of data and the second type of data is extracted, including: Dividing the target area into a plurality of sub-areas; For each sub-region, the following steps are performed: extracting the first horizontal level association and the first vertical level association of the first category of data; extracting the second horizontal level association and the second vertical level association of the second category of data; extracting the third horizontal level association and the third vertical level association between the first category of data and the second category of data.

3. The data processing method based on the three-dimensional hierarchical data model according to claim 2 is characterized in that: Divide the target area into multiple sub-areas, including: Extracting geological structural features and hydrological boundary features from multi-source hydrogeological data of the target area; The target area is divided into a plurality of sub-areas according to the geological structure characteristics and the hydrological boundary characteristics.

4. The data processing method based on the three-dimensional hierarchical data model according to claim 2 is characterized in that: Extracting the first horizontal level association and the first vertical level association of the first type of data, including: Extracting horizontal stratum lithology correlation features and horizontal flow correlation features from the first type of data as the first lateral hierarchical correlation; The vertical stratum structure correlation characteristics, aquifer and aquiclude configuration correlation characteristics, and groundwater vertical recharge and discharge correlation characteristics in the first type of data are extracted as the first longitudinal hierarchical correlation.

5. The data processing method based on the three-dimensional hierarchical data model according to claim 4 is characterized in that: Extracting the second horizontal level association and the second vertical level association of the second type of data includes: Extracting the correlation features of hydrogeological phenomena and image data in the second type of data as the second horizontal level correlation; The stratigraphic profile description correlation features, water chemistry correlation features, and hydrogeological phenomenon correlation features in the second type of data are extracted as the second vertical level correlation.

6. The data processing method based on the three-dimensional hierarchical data model according to claim 5 is characterized in that: Extracting the third horizontal level association and the third vertical level association between the first type of data and the second type of data, including: Extracting a first feature between horizontal strata lithology and geological phenomena, and simultaneously extracting a second feature between horizontal flow and image data; and associating the first feature and the second feature as the third horizontal hierarchical association; Extract the third feature between the vertical stratigraphic structure and the stratigraphic profile description, and simultaneously extract the fourth feature between the configuration of aquifers and impermeable layers, vertical recharge and discharge of groundwater, water chemistry and hydrogeological phenomena; associate the third feature and the fourth feature as the third vertical hierarchical association.

7. The data processing method based on the three-dimensional hierarchical data model according to claim 1 is characterized in that: According to the hierarchical association relationship, a hydrogeological knowledge map is established, including: According to the hierarchical association relationship, the data mapping between the first type of data stored in the relational database and the second type of data stored in the non-relational database is determined, and the hydrogeological knowledge map is established based on the data mapping.

8. The data processing method based on the three-dimensional hierarchical data model according to claim 1 is characterized in that: The interactive coordination system is also provided with a three-dimensional hydrogeological model, and the method further comprises: In response to a query operation for the three-dimensional hydrogeological model, first-category data corresponding to the query operation is queried from the relational database, and corresponding second-category data is retrieved from the non-relational database according to the hydrogeological knowledge graph.

9. A three-dimensional data management platform, comprising a relational database, a non-relational database and an interactive coordination system; the interactive coordination system is provided with a three-dimensional hierarchical data model; the interactive coordination system comprises a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the data processing method based on the three-dimensional hierarchical data model as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the data processing method based on the three-dimensional hierarchical data model as described in any one of claims 1 to 8 above are implemented.

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