System capable of being used for calculating salt lake brine storage resource quantity

Abstract

The invention relates to the field of salt lake brine mineral resource on-line evaluation, and discloses a salt lake brine storage resource quantity calculation system, which comprises a data acquisition module used for acquiring drilling data, groundwater dynamic monitoring data and meteorological data of a salt lake mining area; the data management module is used for carrying out storage, cleaning, classification management and statistical analysis on the collected data; and the three-dimensional modeling module is used for constructing a three-dimensional model of the halogen storage layer based on the geological data and optimizing the model to describe the irregular spatial form of the halogen storage layer. By integrating data acquisition, three-dimensional modeling, dynamic monitoring and reserve calculation, efficient and dynamic management of the brine storage layer resource reserves is achieved, compared with the prior art, the reserve calculation precision, the dynamic updating capacity and the automation level are improved, and the defects that brine storage layer form description is rough, parameter processing is inaccurate, and annual report generation is tedious are overcome.

Description

Technical Field

[0001] The present invention relates to the field of online evaluation of mineral resources in salt lake brine, and specifically to a system that can be used for calculating the storage resources of salt lake brine. Background Art

[0002] Salt lake brine resources are important mineral resources, and the calculation of their reserves is of great significance for scientific planning and reasonable exploitation. At present, mining enterprises generally use the traditional geological block method to calculate the reserves of salt lake brine resources. By dividing geological blocks and combining statistical parameters such as the thickness of the brine storage layer, the horizontal projection area, and porosity or specific yield, the resource reserves are estimated. This method is widely used in mineral resource management and has a certain theoretical basis. However, with the expansion of the mining scale in the mining area and the intensification of resource dynamic changes, its limitations have become increasingly prominent.

[0003] In the prior art, the geological block method has great limitations in reserve calculation. First, its description of the spatial shape of the brine storage layer is relatively rough, approximating the brine storage layer only with regular cuboids, which does not adapt to the complex geometric characteristics of the brine storage layer, resulting in calculation results deviating from the actual situation. Second, the processing of geological parameters such as porosity or specific yield mostly relies on average values or weighted average values, while ignoring the spatial non-uniformity of these parameters. Especially in mining areas with a large range of parameter changes, the calculation errors are significant. In addition, the prior art cannot achieve dynamic monitoring and real-time update of resource reserves, and cannot timely reflect the dynamic changes in resource reserves caused by water level changes or mining activities, lacking real-time performance in management decisions. Finally, the reserve calculation results are mostly generated manually in a summary manner, which is time-consuming and prone to errors, and it is difficult to meet the requirements of automation, accuracy, and visualization of reserve annual reports in modern mining areas. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a system that can be used for calculating the storage resources of salt lake brine, which solves the problems of rough description of the spatial shape of the brine storage layer, inaccurate processing of geological parameters, lack of dynamic monitoring and real-time update capabilities of resource reserves, and low efficiency in generating reserve annual reports in the prior art.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A system that can be used for calculating the storage resources of salt lake brine, comprising: A data acquisition module, used for acquiring borehole data, groundwater dynamic monitoring data, and meteorological data of the salt lake mining area; A data management module, used for storing, cleaning, classifying, managing, and statistically analyzing the acquired data; A three-dimensional modeling module, used for constructing a three-dimensional model of the brine storage layer based on geological data and optimizing the model to describe the irregular spatial shape of the brine storage layer; The reserve calculation module is used to calculate the storage resource volume based on the 3D model, supporting fixed block calculation and custom block calculation; The dynamic monitoring and data update module is used to adjust geological parameters and the 3D model according to real-time monitoring data; The annual reserve report generation module is used to generate the annual resource reserve report based on the reserve calculation results.

[0006] Preferably, the borehole data collected by the data collection module includes porosity, specific yield, borehole depth, and lateral distribution data of the brine-bearing layer, the groundwater dynamic monitoring data includes water level changes and production well flow data, and the meteorological data includes precipitation and temperature data.

[0007] Preferably, the data management module fills in the missing geological data using the interpolation algorithm and adjusts the geological parameters in the database in real time through the update of dynamic monitoring data.

[0008] Preferably, the 3D modeling module constructs a 3D grid model of the brine-bearing layer using geostatistical methods, and optimizes the spatial shape of the brine-bearing layer in combination with borehole data and brine-bearing layer parameters to accurately describe the inhomogeneity of the brine-bearing layer.

[0009] Preferably, the reserve calculation module calculates the storage resource volume through the following method: The fixed block calculation method is based on the horizontal projected area of the block, the thickness of the brine-bearing layer, and the porosity or specific yield for calculation; the custom block calculation method calculates the resource volume after obtaining relevant parameters by specifying an arbitrary-shaped area in the mining area by the user.

[0010] Preferably, the fixed block calculation result in the reserve calculation module is obtained through the following steps: Obtain the horizontal projected area of the block; Determine the average retained thickness of the block; Determine the porosity or specific yield of the block; Calculate the storage resource volume after combining the above parameters.

[0011] Preferably, the custom block calculation method in the reserve calculation module calculates the reserve by selecting the mining area specified by the user, automatically generating a 3D model of the block, and extracting the layered information.

[0012] Preferably, the dynamic monitoring and data update module adjusts the brine-bearing layer model parameters in real time according to the groundwater level and meteorological change data, and triggers the reserve calculation module to recalculate.

[0013] Preferably, the annual reserve report generation module supports generating a simple annual resource reserve report, and the content of the annual report includes basic information of the mining area, reserve estimation method, reserve calculation results, and trend chart.

[0014] Preferably, the system adopts a B / S architecture. Users can access the system through a browser, select the fixed block section or the custom block section calculation method in the reserve calculation module, and directly generate the annual reserve report after completing the reserve calculation.

[0015] The present invention provides a system that can be used for calculating the storage resources of salt lake brine, and has the following beneficial effects: 1. By adopting a combined technical solution integrating data acquisition, dynamic monitoring, three-dimensional modeling and reserve calculation, the present invention realizes the full-process digital processing of the reserve of the brine storage layer. Through data transfer and linkage operations between modules, it achieves the technical effects of quickly, efficiently and accurately accounting for the mineral resources of the mining area. Compared with the prior art that relies on manual calculation and decentralized data processing, it solves the problems of low efficiency, large calculation errors and difficulty in dynamically reflecting the change of reserves.

[0016] 2. By adopting the real-time regulation function of the dynamic monitoring and data update module, and combining meteorological data and the change of mining flow, the present invention dynamically adjusts the thickness and geological parameters of the brine storage layer, realizes the dynamic management of the reserve calculation, and achieves the technical effects of updating the reserve of the mining area at any time and accurately mastering the change of resources. Compared with the prior art that can only statically account for reserves, it effectively solves the problems of weak real-time data processing ability and difficulty in meeting the actual dynamic management needs of the mining area.

[0017] 3. By combining the three-dimensional modeling module with the geostatistical method, the present invention optimizes the description of the irregular shape of the brine storage layer, uses grid division and interpolation algorithms for accurate modeling, ensures that the model is highly consistent with the geological characteristics of the real mining area, and achieves the technical effects of improving the spatial description accuracy of the brine storage layer and the accuracy of reserve calculation. Compared with the prior art that simply relies on geometric approximation calculation, it significantly solves the problems of rough model and large resource accounting errors.

[0018] 4. Through the annual reserve report generation module, combining reserve calculation and dynamic change analysis, the present invention automatically generates a formatted annual report document including reserve distribution maps, dynamic curve charts and reserve statistical tables. Through modular generation technology, it achieves the effect of quickly, accurately and completely outputting the annual report. Compared with the cumbersome operations of manually summarizing data and compiling annual reports in the prior art, it solves the problems of complex process, long time consumption and difficulty in flexibly adjusting content in the traditional method. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is the system architecture diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0021] Please refer to the attached Figure 1 , the embodiment of the present invention provides a system that can be used for calculating the storage resources of salt lake brine, including: A data acquisition module for acquiring borehole data, groundwater dynamic monitoring data, and meteorological data of the salt lake mining area; In this embodiment, the data acquisition module mainly realizes the acquisition and preprocessing of three types of data, namely borehole data, groundwater dynamic monitoring data, and meteorological data.

[0022] Borehole data acquisition In this embodiment, the borehole data is an indispensable key data source for calculating the salt lake brine reserves. The acquisition of borehole data is generally completed by professional geological drilling equipment and obtained through on-site measurement. The acquired borehole data includes: Borehole number and coordinates: These data are used to locate the specific position of the borehole in the mining area and provide a basis for the subsequent modeling of the spatial distribution.

[0023] Borehole depth and thickness of the brine-bearing layer: The depth reflects the total distance penetrated by the borehole, and the thickness of the brine-bearing layer is one of the core parameters for calculating the resource reserves.

[0024] Porosity (φ): Generally, the porosity reflects the proportion of the space in the brine-bearing layer that can store brine and is expressed as a percentage.

[0025] Specific yield (μ): The specific yield refers to the ability of the brine in the brine-bearing layer to effectively flow out and is also expressed as a percentage.

[0026] The borehole data is usually distributed at a certain borehole density according to the geological exploration plan of the salt lake mining area. As an option, an interpolation algorithm can be used to fill the data gaps in the un-drilled areas. Specifically, by using parameters such as the porosity and specific yield of the existing boreholes and combining with the geological structure characteristics of the mining area, the possible parameter values in the adjacent areas are calculated. These interpolation results will provide an important supplement for the subsequent reserve calculation.

[0027] Groundwater dynamic monitoring data acquisition In this embodiment, the groundwater dynamic monitoring data is mainly automatically acquired by the monitoring equipment installed in the mining area and regularly transmitted to the system database. The monitoring data includes: Water level change data: used to reflect the dynamic storage level of brine in the brine reservoir. Water level data will fluctuate with factors such as seasonal changes and mining intensity in the mining area.

[0028] Well flow: Record the daily brine extraction volume of each well in the mining area. These data are crucial for dynamically updating the reserve calculation results.

[0029] In a possible implementation, the monitoring device can be set to collect data at a fixed time. For example, the monitoring frequency can be set to multiple samplings per day to obtain a more accurate dynamic change curve.

[0030] To facilitate data processing, the collected water level and flow data will be recorded in the database in time series and associated with the drilling data to achieve dynamic reserve calculation.

[0031] Meteorological data collection Meteorological data is one of the external factors that affect the change of salt lake brine reserves. In this embodiment, the collection of meteorological data is completed through a meteorological station, which mainly includes: Precipitation: Precipitation in the salt lake area directly affects the dynamic reserves of brine. Data is generally recorded in millimeters per day.

[0032] Evaporation: Evaporation is an important factor in the loss of brine resources. The evaporation dish device at the weather station can quantitatively record the changes in evaporation.

[0033] Air temperature: Air temperature data has an indirect impact on the hydrological cycle of salt lakes and the dynamic balance of brine resources.

[0034] As an option, the frequency of meteorological data collection can be adjusted according to seasonal changes. For example, in the dry season, the frequency of collection can be appropriately increased to increase the data density in order to provide more accurate external environmental data for reserve changes.

[0035] Data preprocessing and transmission The collected data needs to be preliminarily processed to ensure the standardization and integrity of the data. In this embodiment, data preprocessing includes the following steps: Data formatting: Convert all data into a unified standard format. For example, the coordinates of the borehole data are in latitude and longitude format, and the water level data is in meters (m).

[0036] Data verification: Check the integrity of the collected data and remove abnormal values. For example, if the porosity data of a borehole exceeds the reasonable range, the system will prompt that the data is abnormal and require re-collection.

[0037] Data transmission: The preprocessed data is transmitted to the data management module through the system interface as input for subsequent modeling and calculation.

[0038] Connection of Data with Subsequent Modules After the data transmission completed by the data acquisition module, it directly enters the data management module. Generally, the acquisition module stores the data in the database through real-time transmission. For dynamic monitoring data, the system can automatically trigger the model update of the 3D modeling module and simultaneously adjust the input parameters for reserve calculation.

[0039] For example, assuming that the water level in a certain mining area has dropped by 10% within a week, the system will adjust the thickness parameter of the brine storage layer based on the new water level data and update the reserve calculation result.

[0040] Extended Implementation Methods In some embodiments, the data acquisition module can also expand the acquisition of other environmental data, such as the salinity concentration or chemical composition of the salt lake. Specifically, by installing an on-line chemical analyzer to record the composition ratio of the brine (such as the concentration of potassium, sodium, and magnesium ions), these data can provide additional support for the resource quality assessment of the mining area.

[0041] In addition, in a possible implementation method, the acquisition module can be combined with the UAV monitoring system to obtain the terrain change data on the surface of the mining area. This method can assist in optimizing the borehole distribution and provide additional spatial morphological information for the 3D modeling of the brine storage layer.

[0042] The data management module is used to store, clean, classify, manage, and statistically analyze the acquired data; In this embodiment, the data management module mainly includes four aspects of functions: data storage, data cleaning, data formatting, and data statistical analysis.

[0043] Data Storage In this embodiment, the acquired data is first stored in a relational database. The design structure of the database is divided into multiple tables, and each table stores different types of data, including borehole data tables, dynamic monitoring data tables, and meteorological data tables. Specifically: The borehole data table records parameters such as the number, coordinates, depth, porosity, and specific yield of each borehole. The borehole number is used to identify a single borehole, and the coordinate information reflects the geographical location of the borehole. Depth and porosity are important parameters for subsequent reserve calculation.

[0044] The dynamic monitoring data table mainly stores the time series data of the underground water level change and the flow rate of the production well. These data are indexed by time stamps and associated with the borehole data for subsequent dynamic update of the reserve calculation result.

[0045] The meteorological data table stores the changes in environmental factors such as precipitation, evaporation, and temperature. As an option, the meteorological data can be associated with the dynamic monitoring data table to analyze the impact of meteorological conditions on the brine reserve.

[0046] In a possible implementation, the database is designed to support a dynamic data storage structure with real-time updates. Through predefined automatic triggers, rapid data entry and updates can be completed while the acquisition module transmits data.

[0047] Data cleaning The data management module comprehensively cleans the stored data to ensure data integrity and accuracy. In this embodiment, the process of data cleaning mainly includes the following steps: First, check the integrity of all data fields. For example, for borehole data, ensure that all boreholes have filled in necessary fields such as numbers, coordinates, and depths. If a missing item is found, it is marked as abnormal data.

[0048] Secondly, handle outliers. For example, when the porosity or specific yield of a certain borehole exceeds a reasonable range (such as porosity greater than 100% or less than 0%), the system will automatically mark the data as abnormal and notify the user for correction.

[0049] Finally, use an interpolation algorithm to fill in the missing data. Specifically, the interpolation algorithm calculates an approximate value of the missing data through spatial interpolation based on the geological parameters of adjacent boreholes. As an option, the Kriging interpolation method can be used, which can fully consider the spatial distribution characteristics of the data, thereby improving the accuracy of the interpolation results.

[0050] Data formatting In this embodiment, to ensure that the data can be correctly called by subsequent modules, the data management module formats all data. Generally, all coordinate data are represented in latitude and longitude format, and the unit is unified in decimal format. For example, the borehole coordinate "35°30′N" will be converted to the form of "35.5°".

[0051] For time series data, it is uniformly recorded in timestamp format to facilitate rapid query and sorting of dynamic data. For example, water level change data is recorded in the format of "YYYY-MM-DD HH:MM:SS" and associated with the corresponding borehole number.

[0052] As an option, the data management module also supports normalizing geological parameters. For example, the values of porosity and specific yield are uniformly converted to the range of 0 to 1 for standardized input in subsequent model calculations.

[0053] Data statistical analysis After the data management module completes data storage and cleaning, it will perform statistical analysis on some core parameters to provide necessary support for the 3D modeling and reserve calculation modules. In this embodiment, the content of statistical analysis includes but is not limited to the following points: Statistically analyze the minimum, maximum, average, and standard deviation of the porosity and specific yield of each borehole. These statistical data can reflect the distribution range of the geological parameters of the brine-bearing formation.

[0054] Calculate the distribution characteristics of the thickness of the brine-bearing formation for each borehole in the mining area and generate a distribution curve graph. This curve graph is used to optimize the horizon division in 3D modeling.

[0055] Conduct trend analysis on the dynamic monitoring data. For example, statistically analyze the average decline rate of the water level over a certain period of time to provide a basis for calculating the dynamic reserves.

[0056] In a possible implementation, the data management module can also perform cross-analysis on meteorological data and dynamic monitoring data. For example, analyze the relationship between precipitation and the change of the groundwater level to provide support for subsequent resource management.

[0057] Connection of data with subsequent modules After being processed by cleaning, formatting, and statistical analysis, the data management module stores all the data in a standardized structure and transfers it to the 3D modeling module. Generally, the data management module transmits parameter data, including borehole coordinates, thickness of the brine-bearing formation, porosity, and specific yield, to the modeling module through the system interface.

[0058] As an option, the data management module can also directly trigger the calculation of the 3D modeling module. For example, when the change of the water level in the dynamic monitoring data table exceeds the set threshold, the system will automatically update the thickness parameter of the brine-bearing formation and notify the modeling module to regenerate the 3D model.

[0059] In addition, the data management module supports multiple calls of data. For example, when the reserve calculation module needs to re-analyze the data of a certain area, it can directly query the corresponding parameters from the database and automatically update the calculation results.

[0060] Extended implementation In some embodiments, the data management module can add multi-dimensional analysis functions. For example, it can calculate the proportion of resource reserves in different areas of the mining area, or conduct horizontal comparison of the geological parameters of multiple mining areas to provide a more in-depth decision-making basis for scientific mining planning.

[0061] In addition, the data management module can also expand the real-time visualization function. For example, use the GIS system to overlay the borehole data and dynamic monitoring data on the mining area map to intuitively display the distribution of geological parameters of each borehole and the change of the water level.

[0062] Through the above detailed technical solutions, those skilled in the art can completely reproduce the implementation of the data management module according to the disclosed content and seamlessly connect it to the entire reserve calculation system to provide reliable data support for subsequent modeling and calculation.

[0063] A 3D modeling module, which is used to construct a 3D model of the brine storage layer based on geological data and optimize the model to describe the irregular spatial morphology of the brine storage layer; In this embodiment, the 3D modeling module mainly completes four stages: data preparation, mesh generation, spatial interpolation, and model optimization.

[0064] Data preparation In this embodiment, the 3D modeling module obtains the processed standardized data from the data management module as the input for modeling. These data mainly include parameters such as borehole coordinates, brine storage layer thickness, porosity, and specific yield. Specifically: The borehole coordinate data is used to determine the spatial distribution range of the brine storage layer. Generally, all borehole data will be integrated into a geological database for subsequent input calls in modeling.

[0065] The brine storage layer thickness data reflects the longitudinal distribution characteristics of the brine storage layer at different borehole positions and serves as the basic data for the longitudinal slices of the model.

[0066] The porosity and specific yield data are used for parametric expression of the model attributes. These data exist in a point-like distribution form, and the values in the un-drilled areas of the model are calculated through interpolation algorithms.

[0067] As an option, in the data preparation stage, the system can also integrate meteorological and water level change data to analyze the morphological changes of the brine storage layer under dynamic conditions. For example, when the water level monitoring data indicates a decrease in the water level, the system will use the new brine storage layer thickness as the input to generate an updated 3D model.

[0068] Mesh generation In this embodiment, the 3D modeling module uses the mesh generation method to perform spatial discretization on the mining area to construct the spatial framework of the brine storage layer. Specifically: In a possible implementation, the system uses the Delaunay triangular mesh generation algorithm to connect the borehole coordinate points to form triangular meshes. The characteristic of the Delaunay algorithm is that it can maximize the minimum value of the interior angles of the triangles, thereby ensuring the uniformity and stability of the mesh generation.

[0069] Generally, the horizontal mesh generation is based on the horizontal projection range of the boreholes, and the vertical mesh generation is based on the brine storage layer thickness data. To more accurately reflect the thickness changes of the brine storage layer, the vertical meshes are usually further refined to form multiple equally spaced slices.

[0070] As an option, for the mesh generation of the boundary area, the system uses the Voronoi method for processing. This method can divide the boundary points into multiple small polygon units, thereby more accurately describing the shape characteristics of the mining area boundary.

[0071] Spatial interpolation In this embodiment, the 3D modeling module uses the spatial interpolation method to predict and calculate the geological parameters of the un-drilled area to fill the data gaps in the model. Specifically: For porosity and specific yield, the system uses the Kriging interpolation method. This method is an optimal linear unbiased interpolation algorithm based on geostatistics, which can fully consider the spatial correlation of geological parameters during the interpolation process.

[0072] During the interpolation process, the system first calculates the semi-variogram function between the drilled data. Generally, the semi-variogram function reflects the correlation of geological parameters with the change of spatial distance. For example, when the distance between two drill holes is relatively close, the difference in their porosity values is usually small.

[0073] Through the semi-variogram function, the system generates a spatial prediction model and uses this model to perform interpolation calculations on the porosity and specific yield of the un-drilled area. The interpolation results are combined with the existing data to form a complete geological parameter distribution map.

[0074] As a possible implementation, for areas with large height variations, such as the edge of the brine storage layer, the system can add a weight factor during the interpolation process to improve the adaptability of the model to complex terrains.

[0075] Model optimization After the 3D modeling module initially constructs the brine storage layer model, it is necessary to optimize the model to improve its accuracy and adaptability. In this embodiment, the model optimization is mainly reflected in the following two aspects: Horizontal optimization. For the characteristic that the brine storage layer is horizontally uneven, the system improves the resolution of the model by adjusting the grid density. For example, in areas with a large drilling density, the system will generate smaller grid cells to more accurately describe the local geological characteristics.

[0076] Vertical optimization. For the characteristic that the thickness of the brine storage layer is uneven, the system corrects the model by dynamically updating the data. For example, when the dynamic monitoring data shows that the water level of a certain drill hole has dropped, the system will adjust the vertical height value of the grid corresponding to this drill hole in real time.

[0077] As an option, meteorological data can also be combined for analysis during the model optimization process. For example, under the long-term evaporation effect, the upper thickness of the brine storage layer may gradually decrease. The system updates the thickness value through dynamic monitoring data and corrects the model.

[0078] Output of model results and connection with subsequent modules In this embodiment, the optimized 3D model is transmitted to the reserve calculation module through a standardized data interface. Generally, the transmitted model data includes the spatial form (grid coordinates) of the brine storage layer and the attribute parameters (porosity, specific yield, etc.) of each grid cell.

[0079] As an option, the system can also output the visualization result of the 3D model. For example, project the model onto the mining area map through GIS software to intuitively display the spatial distribution of the brine storage layer and the changes in geological parameters.

[0080] In the subsequent reserve calculation process, the reserve calculation module can directly call the attribute data of the 3D model. For example, when calculating the reserves of a certain block, the system will calculate the resource reserves of the area according to the grid cell area, thickness and geological parameters of the block.

[0081] Extended implementation methods In some embodiments, the 3D modeling module can expand more modeling functions. For example, a groundwater flow model in the mining area can be added to analyze the flow direction and velocity of the brine inside the brine storage layer. This function can be realized by combining hydrological monitoring data and the spatial model of the brine storage layer.

[0082] In addition, in a possible implementation, the 3D modeling module can support joint modeling of multiple mining areas. For example, for the brine storage layers of adjacent mining areas, the system can generate a comprehensive 3D model across regions to more comprehensively evaluate the regional resource reserves.

[0083] Through the above detailed technical solutions, those skilled in the art can reproduce the 3D modeling module completely according to the disclosed content of the present invention and seamlessly integrate it into the overall system to provide accurate spatial model support for reserve calculation.

[0084] A reserve calculation module for calculating the stored resource volume according to a 3D model, supporting fixed block calculation and custom block calculation; In this embodiment, the implementation of the reserve calculation module includes calculation method selection, parameter extraction, reserve calculation process and dynamic adjustment mechanism. Calculation method selection In this embodiment, the reserve calculation module provides two calculation methods for users: fixed block calculation and custom block calculation.

[0085] Generally, fixed block calculation is used to estimate the reserves of regular blocks already divided in the mining area. This calculation method is suitable for mining area management personnel to conduct routine resource verification on specific areas. As an option, the block division of fixed block calculation is based on the existing geological zoning plan of the mining area, usually a regular rectangular or polygonal area.

[0086] Custom block segment calculation allows users to arbitrarily select the calculation area in the 3D model. Specifically, users can use the interface tool to delineate block segments of any shape in the model, and the module will automatically extract the spatial data and geological parameters of this area and perform reserve calculation. This method is suitable for fine calculation of irregular or local areas.

[0087] Parameter extraction In this embodiment, the reserve calculation module obtains the spatial form and geological parameters required for reserve calculation through the standardized interface provided by the 3D modeling module. Specifically: The module first extracts the horizontal projection area (S) and the thickness of the brine storage layer (H) data of the block segment from the 3D model. The horizontal projection area reflects the distribution range of the block segment on the mining area plane, and the thickness of the brine storage layer is an important longitudinal parameter for reserve calculation.

[0088] Subsequently, the module extracts the porosity (φ) and specific yield (μ) data of the block segment. These data are used to reflect the water storage capacity and water production capacity of the brine storage layer and are the core geological parameters for reserve estimation.

[0089] In a possible implementation, for multiple grid cells within the block segment, the module uses the weighted average method to calculate the average porosity and specific yield of the block segment. For example, when a certain block segment consists of multiple grid cells, the module performs weighted calculation according to the volume weights of each grid cell to improve the accuracy of the parameters.

[0090] Reserve calculation process In this embodiment, the reserve calculation module estimates reserves based on the following formula: R = S × H × φ R ′ = S × H × μ Where: R: Porosity reserve, representing the potential storage volume of brine in the brine storage layer; R ′ : Specific yield reserve, representing the exploitable amount of brine in the brine storage layer; S: Horizontal projection area of the block segment; H: Average thickness of the brine storage layer of the block segment; φ: Average porosity of the block segment (expressed as a percentage); μ: Average specific yield of the block segment (expressed as a percentage).

[0091] Specifically, the module will sequentially complete the following steps during calculation: Calculate the horizontal projection area S of the target block segment. Generally, the module directly extracts the projection boundary from the 3D model and calculates its area through numerical integration methods.

[0092] Determine the average thickness H of the brine storage layer in the target block section. As an option, the module calculates its weighted average by statistically analyzing the thickness data of all grid cells within the block section.

[0093] Extract the average porosity φ and specific yield μ of the target block section. The module generates the average values for calculation by performing weighted statistics on the geological parameter data within the block section.

[0094] Substitute the above parameters into the reserve calculation formula to calculate the porosity reserve R and the specific yield reserve R respectively. ′ 。

[0095] Dynamic adjustment mechanism In this embodiment, the reserve calculation module supports real-time adjustment of the calculation results based on dynamic monitoring data. For example, when the groundwater monitoring data shows a significant decline in the water level of a certain block section, the module will trigger the dynamic update mechanism to recalculate the thickness H of the brine storage layer in that block section. Specifically: The module first extracts the latest water level change value from the dynamic monitoring data table and superimposes and adjusts it with the original brine storage layer thickness data. For example, if the original thickness of a certain block section is H 0 , and the water level decline is ΔH, then the updated thickness H ′ is: H′ = H 0 - ΔH Subsequently, the module substitutes the adjusted thickness value into the reserve calculation formula to recalculate the reserve values R and R of that block section. ′ This dynamic adjustment mechanism can reflect the real-time changes of the brine storage layer and provide more accurate data support for the management of mining area resources.

[0096] Output of calculation results and connection with subsequent modules In this embodiment, after the reserve calculation module completes the calculation, it will output the reserve data to the reserve annual report generation module. Generally, the output data includes the horizontal projection area, brine storage layer thickness, porosity reserve, and specific yield reserve of each block section, etc.

[0097] As an option, the module can also output a visualization chart of the calculation results. For example, the module generates an isogram or bar chart of the reserve distribution in a certain mining area and attaches it to the output data for subsequent analysis.

[0098] When connecting with the reserve annual report generation module, the module supports generating reserve statistical data on an annual or quarterly basis and automatically summarizing it into the input format of the annual report for direct invocation by the annual report module.

[0099] Extended implementation methods In some embodiments, the reserve calculation module can expand its calculation functions. For example, the calculation function for the reserves of salt substances in the salt lake mining area can be added, and by combining the concentration data of components such as potassium and magnesium in the brine storage layer, the reserves of these substances can be calculated. This function can be achieved by adding input parameters for component concentrations in the module.

[0100] In addition, in a possible implementation, the reserve calculation module supports joint calculations for multiple mining areas. For example, users can select block sections of multiple mining areas, and the system will automatically summarize the reserve data of all block sections to generate cross-regional reserve statistics.

[0101] Through the above detailed technical solutions, those skilled in the art can completely reproduce the reserve calculation module according to the disclosed content of the present invention and seamlessly integrate it into the entire system to provide efficient and accurate reserve calculation support for the resource management of the salt lake mining area.

[0102] The dynamic monitoring and data update module is used to adjust geological parameters and three-dimensional models according to real-time monitoring data; In this embodiment, the implementation of the dynamic monitoring and data update module includes four stages: dynamic data collection, dynamic parameter analysis, model update, and reserve calculation trigger.

[0103] Dynamic data collection In this embodiment, the dynamic monitoring and data update module is connected to on-site monitoring equipment in the mining area to achieve automatic collection of groundwater level, production well flow rate, and meteorological change data.

[0104] Generally, groundwater level monitoring data is obtained through water level gauges installed in monitoring wells in the mining area. The water level gauges collect data at fixed time intervals, for example, recording the current water level value every hour, and the data unit is "meter". These data are stored in the system database in a time series and associated with the numbers of corresponding boreholes or monitoring wells.

[0105] The production well flow rate data is automatically recorded by flow meters installed at the wellheads. The flow meters monitor the hourly brine production volume, with the unit of "cubic meters per hour". As an option, the system can also summarize the data of multiple flow meters in real time to calculate the total production volume of the entire mining area.

[0106] The meteorological change data is collected by meteorological stations in the mining area. Specifically, the meteorological stations record the daily precipitation (unit: millimeter), daily evaporation (unit: millimeter), and average temperature (unit: degree Celsius). The meteorological data combined with the water level monitoring data can be used to analyze the impact of external environmental changes on the dynamic characteristics of the brine storage layer.

[0107] In a possible implementation, the dynamic monitoring and data update module can also receive regional meteorological data provided by a third party. These data can be used as a supplement to the meteorological station data to provide more comprehensive information for model adjustment.

[0108] Dynamic parameter analysis In this embodiment, after receiving the monitoring data, the dynamic monitoring and data update module will perform real-time analysis on the data and compare it with historical data to identify the change trend of key parameters.

[0109] Generally, for water level monitoring data, the module will calculate the average water level change of a certain monitoring point within a set time period. For example, when the continuous monitoring data is [H 1 , H 2 , H 3 , … H n , the module calculates the average value of the water level change ΔH avg : Where: H i : The i-th water level monitoring value; n: The number of monitoring times.

[0110] For the extraction well flow rate data, the module will calculate the total extraction volume Q and the average extraction rate per unit time Where: q j : The extraction flow rate in the j-th time period; T: The total monitoring time.

[0111] The meteorological data generates the water balance parameter ΔW through comprehensive calculation of precipitation and evaporation: ΔW = P - E Where: P: Daily precipitation; E: Daily evaporation.

[0112] The results of these parameter analyses will be directly used for the adjustment of the subsequent three-dimensional model and reserve calculation module.

[0113] Model update In this embodiment, the dynamic monitoring and data update module will trigger the automatic update operation of the three-dimensional modeling module according to the analysis results to adjust the spatial form and geological parameters of the brine storage layer.

[0114] Generally, the module will first according to the latest water level change value ΔH avg, update the thickness parameter of the brine storage layer. For example, for the three-dimensional grid cell corresponding to a certain monitoring point, the original thickness of the brine storage layer is H 0 , then the updated thickness H ′ is: H′ = H 0 + ΔH avg For porosity and specific yield, the module will update them by combining dynamic monitoring data and the historical change trend of geological parameters through linear regression or interpolation methods. For example, when the historical data of porosity in a certain area shows a gradual decrease over time, the module will predict the porosity value at the current moment based on the trend

[0115] As an option, during the model update process, the module can also adjust the surface height of the brine storage layer according to meteorological data. For example, when the long-term evaporation causes the upper surface of the brine storage layer to move downward, the module will correct the longitudinal coordinate values of the relevant grid cells

[0116] The annual reserve report generation module is used to generate the annual report of resource reserves according to the reserve calculation results

[0117] In this embodiment, the implementation of the annual reserve report generation module includes four stages: data sorting, template generation, report generation, and visualization display. Data sorting In this embodiment, the annual reserve report generation module first sorts out the calculation results output by the reserve calculation module and the dynamic monitoring module. Specifically Generally, the module will summarize the reserve data of each mining block section, including the horizontal projection area S, the thickness H of the brine storage layer, the porosity reserve R, and the specific yield reserve R ′ . These data are passed in from the reserve calculation module through a standardized interface, and the module classifies and summarizes them, and generates a corresponding statistical table according to the mining block section number

[0118] As an option, the module will also generate a reserve change trend table according to the water level change data provided by the dynamic monitoring module. For example, the module will calculate the reserve change amount ΔR and the change rate ΔR / R of a certain mining block section in the past year. Such data are recorded through time series and combined with other information in the annual report to reflect the dynamic change of reserves

[0119] In a possible implementation manner, the module will perform cross-regional integration of the reserve data of multiple mining areas. For example, when multiple mining areas share the same underground water resources, the module will summarize the total reserve data of all mining areas and calculate the dynamic change trend of the total reserves

[0120] Template generation In this embodiment, the annual reserve report generation module adopts a templated structure to automatically generate a formatted report document. Generally, the content of the annual report includes the following parts Basic information of the mining area, including the name of the mining area, geographical location, borehole distribution, distribution map of monitoring wells, etc. This part of the content is obtained from the data management module and the 3D modeling module.

[0121] Reserve calculation method, including the description of the reserve calculation formula, parameter definition, and calculation results. Specifically, the module will generate the corresponding calculation result description according to the following formula: R = S × H × φ R' = S × H × μ Where the meanings of S, H, φ, and μ are the same as those defined in the reserve calculation module.

[0122] Statistical table of mining area resource reserves, including the reserve data of each block section and the summary result of the total reserves. As an option, this part of the content can also include the statistical analysis of the mining volume of the mining area resources, such as the comparison data between the total mining volume of the mining area and the current remaining reserves.

[0123] Dynamic change analysis, including the reserve change trend, water level change curve, and related charts. This part of the content is generated by the time series data provided by the dynamic monitoring module, aiming to reflect the dynamic characteristics of the resource reserves.

[0124] During the template generation process, the module will customize the content of the annual report according to the parameters set by the user. For example, the user can choose whether to include the dynamic change analysis part or adjust the display format of the statistical table.

[0125] Report generation In this embodiment, after the reserve annual report generation module completes the template generation, it will automatically generate an annual report document according to the template and the sorted data. Specifically: Generally, the module will output the report document in Word format for the user to directly edit and print. As an option, the module can also support generating a report document in PDF format to ensure the format stability of the document.

[0126] The module will insert each part of the content into the document one by one according to the template structure. For example, the module will insert the description of the basic information of the mining area at the beginning of the document, insert the reserve calculation method and calculation results in the main text, and append the dynamic change analysis and visualization charts at the end of the document.

[0127] In a possible implementation, the module will support the multi-language output of the report content. For example, the user can choose to generate the report in English or other language versions to meet different usage requirements.

[0128] Visualization display In this embodiment, the reserve annual report generation module supports various forms of visual data display, aiming to make the content of the annual report more intuitive and easy to understand. Generally, the visual content includes the following categories: 3D model display of the mining area. The module generates static images or dynamic animations of the 3D shape of the mining area based on the model data provided by the 3D modeling module, for visually displaying the spatial distribution characteristics of the brine storage layer.

[0129] Reserve distribution map. The module generates an isogram of the reserve distribution in the mining area according to the results of the reserve calculation module, reflecting the reserve differences in different regions.

[0130] Dynamic change curve graph. The module generates water level change curves, reserve change curves and related trend graphs according to the time series data provided by the dynamic monitoring module. Such charts can visually reflect the dynamic characteristics of the reserves.

[0131] In a possible implementation, the module also supports generating interactive visualization content. For example, by exporting an interactive report in HTML format, users can view the reserve distribution map, dynamic curve graph and other visualization content through a web page.

[0132] Connection with the previous module The reserve annual report generation module needs to cooperate closely with the reserve calculation module and the dynamic monitoring module to ensure the accuracy and timeliness of the annual report content.

[0133] Generally, after each reserve calculation is completed, the module will automatically call the latest results of the reserve calculation module to update the reserve statistical table in the annual report. For the dynamic change analysis part, the module will obtain the water level change and extraction volume data of the dynamic monitoring module in real time to update the relevant curve graphs and change trend tables.

[0134] As an option, the module also supports users to manually trigger the annual report generation operation. For example, when users need to generate a quarterly reserve report, they can input time parameters through the interface, and the module will generate the corresponding report content according to the data within that time period.

[0135] Extended implementation In some embodiments, the reserve annual report generation module can expand the multi-user collaborative editing function. For example, when multiple users need to edit different parts of the same report, the module will automatically synchronize all modified contents to ensure the consistency of the final generated report version.

[0136] In addition, in a possible implementation, the module can also integrate an online approval function. For example, the module can automatically upload the generated annual report document to the enterprise's internal approval system, and users can directly review and sign the report through the system.

[0137] Through the above detailed technical solutions, those skilled in the art can completely reproduce the reserve annual report generation module according to the disclosed content of the present invention and seamlessly integrate it into the entire system, providing comprehensive support for the resource management of mining enterprises.

[0138] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A system for calculating the amount of brine storage resources in salt lakes, characterized in that: include: Data acquisition module, used to collect drilling data, groundwater dynamic monitoring data and meteorological data in salt lake mining areas; Data management module, used for storage, cleaning, classification management and statistical analysis of collected data; A 3D modeling module is used to construct a 3D model of the brine reservoir based on geological data and optimize the model to describe the irregular spatial morphology of the brine reservoir; The reserve calculation module is used to calculate the storage resource volume based on the 3D model, supporting fixed block calculation and custom block calculation; Dynamic monitoring and data updating module, used to adjust geological parameters and 3D models according to real-time monitoring data; The reserve annual report generation module is used to generate the resource reserve annual report based on the reserve calculation results.

2. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The drilling data collected by the data acquisition module include porosity, water supply, drilling depth and lateral distribution data of brine reservoir, the groundwater dynamic monitoring data include water level change and production well flow data, and the meteorological data include precipitation and temperature data.

3. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The data management module uses an interpolation algorithm to complete the missing geological data and adjusts the geological parameters in the database in real time by updating the dynamic monitoring data.

4. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The three-dimensional modeling module uses a geostatistical method to construct a three-dimensional grid model of the brine reservoir, and optimizes the spatial morphology of the brine reservoir in combination with drilling data and brine reservoir parameters to accurately describe the heterogeneity of the brine reservoir.

5. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The reserve calculation module calculates the storage resource volume by the following method: The fixed block calculation method is based on the horizontal projection area of ​​the block, the thickness of the brine reservoir and the porosity or water supply degree; The custom block calculation method calculates the resource volume after obtaining relevant parameters in any shape area of ​​the mining area specified by the user.

6. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The calculation results of the fixed block in the reserve calculation module are obtained by the following steps: Get the horizontal projection area of ​​the block segment; Determine the average retained thickness of the block segment; Determine the porosity or water supply of the block; The above parameters are combined to calculate the storage resource amount.

7. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The custom block calculation method in the reserve calculation module automatically generates a three-dimensional model of the block by selecting a mining area specified by the user, and calculates the reserves after extracting the layer information.

8. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The dynamic monitoring and data updating module adjusts the brine reservoir model parameters in real time according to the groundwater level and meteorological change data, and triggers the reserve calculation module to recalculate.

9. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The reserve annual report generation module supports the generation of a simple annual report on resource reserves, the contents of which include basic information on the mining area, reserve estimation methods, reserve calculation results and trend charts.

10. A system for calculating the amount of salt lake brine storage resources according to claim 1, characterized in that: The system adopts a B / S architecture. Users access the system through a browser and select a fixed block segment or a custom block segment calculation method in the reserve calculation module. After completing the reserve calculation, the reserve annual report can be directly generated.

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