Solid mineral resource reserve estimation system based on double-layer database

Abstract

The invention relates to the technical field of mineral resource exploration, in particular to a solid mineral resource reserve estimation system based on a double-layer database, which comprises a data acquisition module, a double-layer database module, a data processing module and a reserve estimation module, wherein the data acquisition module is used for collecting original exploration data of mineral resources, including geological exploration information, underground rock stratum data and measurement data; the double-layer database module comprises a first-layer database and a second-layer database; the data processing module is used for processing the data to remove invalid or abnormal data; and the reserve estimation module is used for estimating the reserves of the mineral resources. According to the method, efficient management of mineral resource data, accurate reserve estimation and intelligent mining scheme generation are realized through a double-layer database and a geometric modeling technology, the accuracy and actual exploitability of reserve estimation are improved, and reliable decision support is provided for resource development.

Description

Technical Field

[0001] The invention relates to the technical field of mineral resource exploration, and in particular to a solid mineral resource reserve estimation system based on a double-layer database. Background Art

[0002] In the existing field of mineral resource exploration and development, accurate reserve estimation is the key to mineral resource management and mining decisions. Traditional reserve estimation methods mostly rely on the superposition of two-dimensional data and manually calculate the volume and ore content of the ore body in combination with geological exploration information, resulting in incomplete data, low accuracy, and difficulty in adapting to the complex spatial distribution characteristics of the ore body. In addition, due to the lack of systematic management in the data collection and processing process, there are often problems such as data duplication, loss and delay, which not only reduces the accuracy of reserve estimation, but also prolongs the time of the entire estimation process, affecting the development efficiency of mineral resources.

[0003] The existing reserve estimation system has many deficiencies in solving complex ore body geometry and improving data accuracy. Specifically, traditional technology lacks flexible adaptability when facing different mining areas, physical properties of different ore bodies and mining difficulties, and cannot accurately handle the transmission and synchronization of multi-source data, resulting in poor data consistency. In addition, the existing system is not intelligent enough in generating mining plans, and it is difficult to provide optimized plans based on the characteristics of the ore body and mining feasibility, and lacks the ability to adjust dynamically. These technical difficulties not only limit the accuracy of reserve estimation, but also increase the cost and risk in the mining process. Therefore, it is of great practical significance to develop a solid mineral resource reserve estimation system based on a double-layer database. Summary of the invention

[0004] Based on the above purpose, the present invention provides a solid mineral resource reserve estimation system based on a double-layer database.

[0005] A solid mineral resource reserve estimation system based on a double-layer database comprises a data acquisition module, a double-layer database module, a data processing module and a reserve estimation module; wherein: Data acquisition module: used to collect original exploration data of mineral resources, including geological exploration information, underground rock formation data and measurement data; Two-layer database module: includes the first-layer database and the second-layer database, wherein the first-layer database is used to store the original exploration data, and the second-layer database is used to store the processed data; the two-layer database interacts through the data transmission protocol to achieve data synchronization and update; Data processing module: receives the raw data from the first-tier database and processes the data through data cleaning, denoising and normalization methods to remove invalid or abnormal data; the processed data is transmitted to the second-tier database for use by the reserve estimation module; Reserve estimation module: Based on the data in the second-level database, combined with the geometric model of the ore body and mining technology, the reserve of mineral resources is estimated and the estimation results are generated.

[0006] Optionally, the data acquisition module includes a geological exploration unit, a drilling unit and a measurement unit; wherein: Geological exploration unit: including geological exploration instruments, used to monitor and record geological exploration information of the mining area in real time, including ore layer distribution, ore grade, and ore body morphology data; Drilling unit: used to obtain underground rock data of the mining area through drilling equipment, including physical properties and chemical composition information of the ore body, wherein the physical properties include hardness and density, and the chemical composition information includes ore content; Measurement unit: used to conduct surface and underground measurements of the mining area and obtain measurement data of the mining area, including ore body coordinates, ore body depth, ore body thickness, and inclination parameters.

[0007] Optionally, the two-layer database module includes a first-layer database unit, a second-layer database unit, and a data transmission protocol unit; wherein: The first-layer database unit is used to receive the original exploration data from the data acquisition module and store all the data in a predetermined data format, which includes a structured data format and an unstructured data format; The second-layer database unit is connected to the first-layer database unit and is used to store the data processed by the data processing module, and organize and classify all the data according to different categories and attributes; Data transmission protocol unit: Ensure data consistency and real-time update in the first-layer and second-layer databases through data synchronization algorithms, version control, and timestamp management.

[0008] Optionally, the data transmission protocol unit specifically includes: Data synchronization algorithm subunit: used to ensure data consistency between the two databases. Specifically, it determines whether data needs to be updated by comparing the differences of the same data items in the two databases. Specifically, it compares the data records in the two databases. If it is found that the original data in the first database has changed, an update is triggered. Version control mechanism subunit: used to manage different versions of data records during data transmission and synchronization; the data version number will automatically increase by 1 each time the data is updated; Timestamp management subunit: used to attach a timestamp to each piece of data during transmission, indicating the update time of the data; each time the data is updated, the first-tier database will record the current timestamp and transmit it to the second-tier database for synchronization.

[0009] Optionally, the data processing module includes a data cleaning unit, a denoising unit and a normalization unit; wherein: Data cleaning unit: used to clean the original data and remove missing values, duplicate values ​​and outliers; De-noising unit: used to remove noise from raw data and filter out unnecessary information caused by measurement errors or external interference; Normalization unit: used to normalize the processed data, unify data of different dimensions, and analyze them under the same standard, thereby eliminating deviations caused by inconsistent data units.

[0010] Optionally, the denoising unit includes: Identify noise: First, identify the noise of the original data. Specifically, use the mean and standard deviation of the data to determine the noise range. If the data point deviates from the mean by more than the set threshold, the data point is considered to be noise. Noise smoothing: After noise identification, the raw data is smoothed using the moving average method to reduce the impact of measurement errors and external interference; Frequency domain filtering: After smoothing, the data is denoised using frequency domain filtering technology. First, the data is Fourier transformed to convert the data from the time domain to the frequency domain. Then, a frequency threshold is set and a low-pass filter is used to remove noise signals above the frequency threshold to retain valid data components. Dynamic threshold adjustment: Taking into account the volatility of data from different mining areas, the denoising unit is also equipped with a dynamic threshold adjustment mechanism, which is used to automatically calculate the optimal noise threshold for each data transmission based on the historical fluctuations of the data, so as to more accurately identify and remove noise; the dynamic adjustment formula is: ,in, is the noise recognition threshold after dynamic adjustment, is an adjustable coefficient, and are the mean and standard deviation of the current data set respectively.

[0011] Optionally, the reserve estimation module includes an ore body geometry modeling unit, a mining feasibility assessment unit, a mineral resource reserve calculation unit, and a reserve estimation result generation unit; wherein: Ore body geometric modeling unit: used to construct a three-dimensional geometric model of the ore body based on the data of ore body coordinates, ore body depth, ore body thickness and inclination parameters in the second-layer database. The three-dimensional geometric model of the ore body contains geometric information on the volume and distribution of the ore body, providing an intuitive spatial parameter basis for subsequent reserve estimation; Mining feasibility assessment unit: Based on the geometric model generated by the ore body geometric modeling unit and the information on the hardness, density and ore content of the ore body in the second-layer database, the unit conducts applicability analysis of mining technology, specifically assesses the technical difficulties and cost investment in the mining process, and determines the mining plan based on the actual mining conditions; Mineral resource reserve calculation unit: receives the geometric model data from the ore body geometric modeling unit and the mining plan from the mining feasibility assessment unit, and calculates the mineral resource reserves based on the ore body volume data and ore content information in the geometric model; Reserve estimation result generation unit: The reserve calculation results output by the mineral resource reserve calculation unit are summarized and formatted to generate the final reserve estimation report, including the total reserves of the ore body, mining technology recommendations and economic feasibility analysis.

[0012] Optionally, the ore body geometry modeling unit includes: 3D point cloud generation subunit: Generate 3D point cloud data of the ore body using the ore body coordinates and thickness information; expand the coordinate point of each ore body into a spatial point through the thickness and inclination parameters, and the generation formula is: ; ; ;in, is a point in a 3D point cloud, is the initial coordinate of the ore body, is the thickness of the ore body, is the inclination parameter, is the depth of the ore body, represent The sine of the inclination angle, represent cosine of the inclination angle; Spatial grid division subunit: Based on the generated 3D point cloud data, the ore body model is spatially gridded; the grid division subdivides the ore body area into a series of regular small cubes or small prism units; the volume of each grid unit is: ,in, and is the side length of the grid cell on the horizontal plane, is the height of the grid unit in the vertical direction, Represents the volume of a grid cell; Volume calculation subunit: Calculate the total volume of the ore body based on all the small units obtained by spatial grid division. The total volume is the sum of the volumes of all grid units. The calculation formula is: ,in, is the total volume of the ore body, For the The volume of a grid cell, is the total number of grid cells.

[0013] Optionally, the mining feasibility assessment unit includes: Ore body physical property analysis subunit: used to analyze the physical properties of the ore body; through the physical property data obtained from the second-level database, the physical parameters of the ore body are quantified; the hardness and density data are related to the mineability of the ore body through the following formula: ,in, Represents the mining adaptability coefficient of the ore body, is the hardness of the ore body, is the density of the ore body; The larger the value, the more difficult the ore body is to mine; Mining difficulty assessment subunit: used to calculate the mining adaptability coefficient based on the physical property analysis subunit , combined with the inclination and ore body depth Assess the mining difficulty; let the mining difficulty index be , the calculation formula is: ,in, is the maximum planned mining depth, is the inclination angle; if If it exceeds the set threshold, it is considered that the mining difficulty is high and the mining method needs to be adjusted; Cost analysis subunit: Based on the mining difficulty assessment, the mining cost is analyzed. Calculate; the formula is: ,in, is the equipment cost, For personnel costs, is the cost of safety measures; let the total mining cost be , the formula is: ,in, is the mineable area of ​​the ore body; Mining plan generation subunit: based on mining difficulty index and cost analysis results to generate a mining plan; if Low and If the budget is within the range, the conventional mining plan is selected; High or If the budget is exceeded, a segmented mining or reinforced mining plan will be adopted; the mining plan includes mining methods, equipment configuration and safety measures recommendations.

[0014] Optionally, the mineral resource reserve calculation unit includes: Ore content assessment subunit: Determine the grade of the ore based on the physical and chemical properties of the ore body , that is, the content of mineable ore per cubic meter of ore body, calculated as: ,in, is the total mass of the ore, is the total volume of the ore body; Reserve calculation subunit: based on the total effective volume of the ore body and ore content grade Calculate the mineral resource reserves; the calculation formula for mineral resource reserves is: ,in, For mineral resource reserves, is the density of ore, used to convert volume reserves to mass reserves; Mining recovery rate adjustment subunit: According to the mining plan generated by the mining feasibility assessment unit, the recovery rate of the reserve calculation results is adjusted to reflect the loss of ore in the actual mining process; the adjusted mineral resource reserves The calculation formula is: ,in, is the mining recovery coefficient, where .

[0015] Beneficial effects of the present invention: The present invention realizes the systematic management and efficient processing of mineral resource exploration data through a double-layer database architecture, ensures the integrity and consistency of data, and avoids the common data duplication and loss problems in traditional systems. The double-layer database module not only improves the data access efficiency through the synchronous storage of structured and unstructured data, but also provides a reliable data basis for the subsequent reserve estimation and the formulation of mining plans. The data processing module cleans, denoises and normalizes the original data, effectively improving the accuracy and reliability of the data and ensuring the data quality in the reserve estimation process.

[0016] The present invention uses geometric modeling technology to accurately model the three-dimensional spatial characteristics of the ore body, and combines it with a mining feasibility assessment unit to dynamically generate an adaptive mining plan based on the physical properties of the ore body and the mining difficulty, thereby significantly improving the accuracy and practicality of reserve estimation. The mining recovery rate adjustment mechanism further optimizes the calculation of actual recoverable reserves, making the estimation results closer to actual mining conditions, thereby reducing the cost and risk in the mining process, and providing scientific and effective decision-making support for the development of mineral resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A schematic diagram of a solid mineral resource reserve estimation system according to an embodiment of the present invention; Figure 2 Schematic diagram of a reserve estimation module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0020] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0021] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0022] like Figure 1-Figure 2 As shown, a solid mineral resource reserve estimation system based on a double-layer database includes a data acquisition module, a double-layer database module, a data processing module and a reserve estimation module; wherein: Data acquisition module: used to collect original exploration data of mineral resources, including geological exploration information, underground rock formation data and measurement data; the module stores the collected original exploration data in the first-level database for subsequent analysis; Two-layer database module: includes the first-layer database and the second-layer database, wherein the first-layer database is used to store the original exploration data, and the second-layer database is used to store the processed data; the two-layer database interacts through the data transmission protocol to achieve data synchronization and update; Data processing module: receives the raw data from the first-tier database and processes the data through data cleaning, denoising and normalization methods to remove invalid or abnormal data; the processed data is transmitted to the second-tier database for use by the reserve estimation module; Reserve estimation module: Based on the data in the second-level database, combined with the geometric model of the ore body and mining technology, the reserve of mineral resources is estimated and the estimation results are generated.

[0023] The data acquisition module includes a geological exploration unit, a drilling unit and a measurement unit; wherein: Geological exploration unit: including geological exploration instruments, used to monitor and record geological exploration information of the mining area in real time, including ore layer distribution, ore grade, and ore body morphology data; Drilling unit: used to obtain underground rock data of the mining area through drilling equipment, including physical properties and chemical composition information of the ore body. Physical properties include hardness and density, and chemical composition information includes ore content; Measurement unit: used to conduct surface and underground measurements of the mining area and obtain measurement data of the mining area, including ore body coordinates, ore body depth, ore body thickness, and inclination parameters. By integrating the above units, the original exploration data of mineral resources can be collected efficiently and accurately, and the collected data can be stored in the first-level database for subsequent data processing and reserve estimation.

[0024] The double-layer database module includes a first-layer database unit, a second-layer database unit, and a data transmission protocol unit; wherein: The first-level database unit is used to receive the original exploration data from the data acquisition module and store all the data in a predetermined data format, including structured data formats (such as CSV, SQL database tables) and unstructured data formats (such as JSON, XML formats), to ensure the integrity, retrievability and efficient storage of the data; for example, the ore layer distribution data can be stored in CSV format, the ore type and chemical composition data can be stored in SQL database tables, and the geological exploration information can be stored in JSON format, to ensure that the data can be efficiently extracted and processed in data query and subsequent analysis; The second-layer database unit is connected to the first-layer database unit and is used to store the data processed by the data processing module, and organize and classify all the data according to different categories and attributes. The second-layer database unit ensures the efficiency of data access through an efficient data storage structure, and provides it to the reserve estimation module for reserve estimation of mineral resources; Data transmission protocol unit: Ensure data consistency and real-time update in the first-layer and second-layer databases through data synchronization algorithms, version control, and timestamp management.

[0025] The data transmission protocol unit specifically includes: Data synchronization algorithm subunit: used to ensure data consistency between the two databases. Specifically, it determines whether data needs to be updated by comparing the differences of the same data items in the two databases. Specifically, it compares the data records in the two databases. If it is found that the original data in the first database has changed, an update is triggered. Version control mechanism subunit: used to manage different versions of data records during data transmission and synchronization to ensure that data changes are orderly and traceable; the data version number will automatically increase by 1 each time the data is updated; Timestamp management subunit: used to attach a timestamp to each piece of data during transmission to indicate the update time of the data; to ensure that there is no data misalignment or inconsistency when data is synchronized between databases; each time the data is updated, the first-layer database will record the current timestamp and transmit it to the second-layer database for synchronization; through the above subunits, the data transmission protocol unit can ensure the data consistency of the two-layer database, avoid data delay or loss, and ensure synchronous updates between databases.

[0026] The data processing module includes a data cleaning unit, a denoising unit and a normalization unit; wherein: Data cleaning unit: used to clean the original data and remove missing values, duplicate values ​​and outliers; De-noising unit: used to remove noise from raw data and filter out unnecessary information caused by measurement errors or external interference, thereby improving the reliability and accuracy of data and ensuring that data is not affected by noise in subsequent processing and analysis; Normalization unit: used to normalize the processed data, unify data of different dimensions, and analyze them under the same standard, thereby eliminating the deviation caused by inconsistent data units, ensuring that the data is comparable and convenient for further analysis; the above data cleaning, denoising and normalization processing effectively improves the quality and accuracy of the data, removes invalid and abnormal data, and provides reliable basic data for subsequent reserve estimation.

[0027] The denoising unit includes: Identify noise: First, identify the noise of the original data. Specifically, use the mean and standard deviation of the data to determine the noise range. If the data point deviates from the mean by more than the set threshold, the data point is considered to be noise. The noise identification formula is as follows: ,in, is the normalized value of the data point deviation from the mean, is the data point value, is the data mean, is the data standard deviation, is the set threshold; if If it exceeds the threshold, the data point is considered as noise; Noise smoothing: After noise identification, the raw data is smoothed using the moving average method to reduce the impact of measurement errors and external interference; specifically, a sliding window is used to locally smooth the data, and the window size is dynamically adjusted according to the volatility of the actual data; the moving average calculation formula is: ,in, is the smoothed data point, For the first data point value, is the sliding window size; this method reduces local fluctuations and smoothes out short-term errors caused by noise to ensure data continuity and stability; Frequency domain filtering: After smoothing, frequency domain filtering technology is used to remove noise from the data. First, the data is Fourier transformed to convert the data from the time domain to the frequency domain; then the frequency threshold is set, and the noise signal above the frequency threshold is removed through a low-pass filter to retain the valid data components; the Fourier transform formula is: ,in, is the representation of data in the frequency domain, is the time domain data, is the frequency; the filter retains the low-frequency signal and removes the high-frequency noise by setting the frequency threshold; Dynamic threshold adjustment: Taking into account the volatility of data from different mining areas, the denoising unit is also equipped with a dynamic threshold adjustment mechanism, which is used to automatically calculate the optimal noise threshold for each data transmission based on the historical fluctuations of the data, so as to more accurately identify and remove noise; the dynamic adjustment formula is: ,in, is the noise recognition threshold after dynamic adjustment, is an adjustable coefficient, and are the mean and standard deviation of the current data set respectively; through noise identification, smoothing, frequency domain filtering and dynamic threshold adjustment, the denoising unit can effectively deal with the common measurement errors and external interference in the process of mineral resource exploration, thereby improving the reliability and accuracy of the data; the introduction of dynamic threshold makes the denoising process more flexible and adaptable to the actual conditions of different mining areas, thereby improving the accuracy and efficiency of overall data processing.

[0028] The reserve estimation module includes an ore body geometry modeling unit, a mining feasibility assessment unit, a mineral resource reserve calculation unit, and a reserve estimation result generation unit; among which: Ore body geometric modeling unit: used to construct a three-dimensional geometric model of the ore body based on the data of ore body coordinates, ore body depth, ore body thickness and inclination parameters in the second-layer database. The three-dimensional geometric model of the ore body contains geometric information on the volume and distribution of the ore body, ensuring the accuracy and authenticity of the geometric modeling and providing an intuitive spatial parameter basis for subsequent reserve estimation; Mining feasibility assessment unit: Based on the geometric model generated by the ore body geometric modeling unit and the information on the hardness, density and ore content of the ore body in the second-layer database, the unit conducts an applicability analysis of the mining technology, specifically assesses the technical difficulties and cost investment in the mining process, and determines the mining plan based on the actual mining conditions, thereby improving the accuracy of reserve estimation; Mineral resource reserve calculation unit: receives the geometric model data from the ore body geometric modeling unit and the mining plan from the mining feasibility assessment unit, and calculates the mineral resource reserves based on the ore body volume data and ore content information in the geometric model; Reserve estimation result generation unit: The reserve calculation results output by the mineral resource reserve calculation unit are summarized and formatted to generate the final reserve estimation report, including the total reserves of the ore body, mining technology recommendations and economic feasibility analysis, to ensure that the estimation results are operational and instructive, and to provide detailed data support for the development of mineral resources.

[0029] The ore body geometry modeling elements include: 3D point cloud generation subunit: Generate 3D point cloud data of the ore body using the ore body coordinates and thickness information; expand the coordinate point of each ore body into a spatial point through the thickness and inclination parameters, and the generation formula is: ; ; ;in, is a point in a 3D point cloud, is the initial coordinate of the ore body, is the thickness of the ore body, is the inclination parameter, is the depth of the ore body, represent The sine of the inclination angle, represent The cosine value of the inclination angle; the point cloud data generated in this step can accurately describe the distribution of the ore body in three-dimensional space; Spatial grid division subunit: Based on the generated 3D point cloud data, the ore body model is spatially gridded; the grid division subdivides the ore body area into a series of regular small cubes or small prism units; the volume of each grid unit is: ,in, and is the side length of the grid cell on the horizontal plane, is the height of the grid unit in the vertical direction, Represents the volume of a grid unit; this spatial grid division can refine the ore body structure and improve the accuracy of geometric modeling; Volume calculation subunit: Calculate the total volume of the ore body based on all the small units obtained by spatial grid division. The total volume is the sum of the volumes of all grid units. The calculation formula is: ,in, is the total volume of the ore body, For the The volume of a grid cell, is the total number of grid cells; by summing up the volumes of all grid cells, the precise volume data of the ore body is obtained; through the above steps, the ore body geometry modeling unit can accurately and completely construct a three-dimensional geometric model of the ore body through three-dimensional point cloud generation, spatial grid division and volume calculation, providing a reliable spatial parameter basis for the reserve estimation module.

[0030] The mining feasibility assessment unit includes: Ore body physical property analysis subunit: used to analyze the physical properties of the ore body; through the physical property data obtained from the second-level database, the physical parameters of the ore body are quantified; the hardness and density data are related to the mineability of the ore body through the following formula: ,in, Represents the mining adaptability coefficient of the ore body, is the hardness of the ore body, is the density of the ore body; The larger the value, the more difficult the ore body is to mine; Mining difficulty assessment subunit: used to calculate the mining adaptability coefficient based on the physical property analysis subunit , combined with the inclination and ore body depth Assess the mining difficulty; let the mining difficulty index be , the calculation formula is: ,in, is the maximum planned mining depth, is the inclination angle; if If it exceeds the set threshold, it is considered that the mining difficulty is high and the mining method needs to be adjusted; Cost analysis subunit: Based on the mining difficulty assessment, the mining cost is analyzed. Calculate; the formula is: ,in, is the equipment cost, For personnel costs, is the cost of safety measures; let the total mining cost be , the formula is: ,in, is the exploitable area of ​​the ore body; this step can effectively estimate the possible cost input during the mining process; Mining plan generation subunit: based on mining difficulty index and cost analysis results to generate a mining plan; if Low and If the budget is within the range, the conventional mining plan is selected; High or If the budget is exceeded, a segmented mining or reinforced mining plan will be adopted; the mining plan includes mining methods, equipment configuration and safety measures to ensure mining efficiency and cost control; through the above steps, the mining feasibility assessment unit can comprehensively consider the physical properties of the ore body, mining difficulty and cost input, and generate the optimal mining plan that conforms to the actual situation to ensure the safety and economy of the mining process.

[0031] Mineral resource reserve calculation units include: Ore content assessment subunit: Determine the grade of the ore based on the physical and chemical properties of the ore body , that is, the content of mineable ore per cubic meter of ore body, calculated as: ,in, is the total mass of the ore, is the total volume of the ore body; the ore grade is obtained through chemical analysis and sampling testing to ensure the accuracy of the calculation process; Reserve calculation subunit: based on the total effective volume of the ore body and ore content grade Calculate the mineral resource reserves; the calculation formula for mineral resource reserves is: ,in, For mineral resource reserves, is the density of the ore, which is used to convert volume reserves into mass reserves; this formula accurately calculates the actual ore reserves in the ore body and ensures the accuracy of the reserve calculation results through the density parameter; Mining recovery rate adjustment subunit: According to the mining plan generated by the mining feasibility assessment unit, the recovery rate of the reserve calculation results is adjusted to reflect the loss of ore in the actual mining process; the adjusted mineral resource reserves The calculation formula is: ,in, is the mining recovery coefficient, where , whose value is determined according to the technical conditions in the mining plan and the specific conditions of the ore body, reflecting the proportion of actual recoverable reserves; through the above steps, the mineral resource reserve calculation unit can accurately calculate the actual recoverable reserves of the ore body based on the volume data and ore content in the geometric model, combined with the mining recovery rate, and provide a scientific basis for the development decision of mineral resources.

[0032] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0033] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A solid mineral resource reserve estimation system based on a double-layer database, characterized in that: It includes data acquisition module, double-layer database module, data processing module and reserve estimation module; among which: Data acquisition module: used to collect original exploration data of mineral resources, including geological exploration information, underground rock formation data and measurement data; Two-layer database module: includes the first-layer database and the second-layer database, wherein the first-layer database is used to store the original exploration data, and the second-layer database is used to store the processed data; the two-layer database interacts through the data transmission protocol to achieve data synchronization and update; Data processing module: receives the raw data from the first-tier database and processes the data through data cleaning, denoising and normalization methods to remove invalid or abnormal data; the processed data is transmitted to the second-tier database for use by the reserve estimation module; Reserve estimation module: Based on the data in the second-level database, combined with the geometric model of the ore body and mining technology, the reserve of mineral resources is estimated and the estimation results are generated.

2. A solid mineral resource reserve estimation system based on a double-layer database according to claim 1, characterized in that: The data acquisition module includes a geological exploration unit, a drilling unit and a measurement unit; wherein: Geological exploration unit: including geological exploration instruments, used to monitor and record geological exploration information of the mining area in real time, including ore layer distribution, ore grade, and ore body morphology data; Drilling unit: used to obtain underground rock data of the mining area through drilling equipment, including physical properties and chemical composition information of the ore body, wherein the physical properties include hardness and density, and the chemical composition information includes ore content; Measurement unit: used to conduct surface and underground measurements of the mining area and obtain measurement data of the mining area, including ore body coordinates, ore body depth, ore body thickness, and inclination parameters.

3. The solid mineral resource reserve estimation system based on a double-layer database according to claim 1 is characterized in that: The two-layer database module includes a first-layer database unit, a second-layer database unit and a data transmission protocol unit; wherein: The first-layer database unit is used to receive the original exploration data from the data acquisition module and store all the data in a predetermined data format, which includes a structured data format and an unstructured data format; The second-layer database unit is connected to the first-layer database unit and is used to store the data processed by the data processing module, and organize and classify all the data according to different categories and attributes; Data transmission protocol unit: Ensure data consistency and real-time update in the first-layer and second-layer databases through data synchronization algorithms, version control, and timestamp management.

4. A solid mineral resource reserve estimation system based on a double-layer database according to claim 3, characterized in that: The data transmission protocol unit specifically includes: Data synchronization algorithm subunit: used to ensure data consistency between the two databases. Specifically, it determines whether data needs to be updated by comparing the differences of the same data items in the two databases. Specifically, it compares the data records in the two databases. If it is found that the original data in the first database has changed, an update is triggered. Version control mechanism subunit: used to manage different versions of data records during data transmission and synchronization; the data version number will automatically increase by 1 each time the data is updated; Timestamp management subunit: used to attach a timestamp to each piece of data during transmission, indicating the update time of the data; each time the data is updated, the first-tier database will record the current timestamp and transmit it to the second-tier database for synchronization.

5. The solid mineral resource reserve estimation system based on a double-layer database according to claim 1 is characterized in that: The data processing module includes a data cleaning unit, a denoising unit and a normalization unit; wherein: Data cleaning unit: used to clean the original data and remove missing values, duplicate values ​​and outliers; De-noising unit: used to remove noise from raw data and filter out unnecessary information caused by measurement errors or external interference; Normalization unit: used to normalize the processed data, unify data of different dimensions, and analyze them under the same standard, thereby eliminating deviations caused by inconsistent data units.

6. A solid mineral resource reserve estimation system based on a double-layer database according to claim 5, characterized in that: The denoising unit comprises: Identify noise: First, identify the noise of the original data. Specifically, use the mean and standard deviation of the data to determine the noise range. If the data point deviates from the mean by more than the set threshold, the data point is considered to be noise. Noise smoothing: After noise identification, the raw data is smoothed using the moving average method to reduce the impact of measurement errors and external interference; Frequency domain filtering: After smoothing, the data is denoised using frequency domain filtering technology. First, the data is Fourier transformed to convert the data from the time domain to the frequency domain. Then, a frequency threshold is set and a low-pass filter is used to remove noise signals above the frequency threshold to retain valid data components. Dynamic threshold adjustment: Taking into account the volatility of data from different mining areas, the denoising unit is also equipped with a dynamic threshold adjustment mechanism, which is used to automatically calculate the optimal noise threshold for each data transmission based on the historical fluctuations of the data, so as to more accurately identify and remove noise; the dynamic adjustment formula is: ,in, is the noise recognition threshold after dynamic adjustment, is an adjustable coefficient, and are the mean and standard deviation of the current data set respectively.

7. The solid mineral resource reserve estimation system based on a double-layer database according to claim 1 is characterized in that: The reserve estimation module includes an ore body geometry modeling unit, a mining feasibility assessment unit, a mineral resource reserve calculation unit, and a reserve estimation result generation unit; wherein: Ore body geometric modeling unit: used to construct a three-dimensional geometric model of the ore body based on the data of ore body coordinates, ore body depth, ore body thickness and inclination parameters in the second-layer database. The three-dimensional geometric model of the ore body contains geometric information on the volume and distribution of the ore body, providing an intuitive spatial parameter basis for subsequent reserve estimation; Mining feasibility assessment unit: Based on the geometric model generated by the ore body geometric modeling unit and the information on the hardness, density and ore content of the ore body in the second-layer database, the unit conducts applicability analysis of mining technology, specifically assesses the technical difficulties and cost investment in the mining process, and determines the mining plan based on the actual mining conditions; Mineral resource reserve calculation unit: receives the geometric model data from the ore body geometric modeling unit and the mining plan from the mining feasibility assessment unit, and calculates the mineral resource reserves based on the ore body volume data and ore content information in the geometric model; Reserve estimation result generation unit: The reserve calculation results output by the mineral resource reserve calculation unit are summarized and formatted to generate the final reserve estimation report, including the total reserves of the ore body, mining technology recommendations and economic feasibility analysis.

8. The solid mineral resource reserve estimation system based on a double-layer database according to claim 7 is characterized in that: The ore body geometric modeling unit comprises: 3D point cloud generation subunit: Generate 3D point cloud data of the ore body using the ore body coordinates and thickness information; expand the coordinate point of each ore body into a spatial point through the thickness and inclination parameters, and the generation formula is: ; ; ;in, is a point in a 3D point cloud, is the initial coordinate of the ore body, is the thickness of the ore body, is the inclination parameter, is the ore body depth, represent The sine of the inclination angle, represent cosine of the inclination angle; Spatial grid division subunit: Based on the generated 3D point cloud data, the ore body model is spatially gridded; the grid division subdivides the ore body area into a series of regular small cubes or small prism units; the volume of each grid unit is: ,in, and is the side length of the grid cell on the horizontal plane, is the height of the grid unit in the vertical direction, Represents the volume of a grid cell; Volume calculation subunit: Calculate the total volume of the ore body based on all the small units obtained by spatial grid division. The total volume is the sum of the volumes of all grid units. The calculation formula is: ,in, is the total volume of the ore body, For the The volume of a grid cell, is the total number of grid cells.

9. A solid mineral resource reserve estimation system based on a double-layer database according to claim 8, characterized in that: The mining feasibility assessment unit comprises: Ore body physical property analysis subunit: used to analyze the physical properties of the ore body; through the physical property data obtained from the second-level database, the physical parameters of the ore body are quantified; the hardness and density data are related to the mineability of the ore body through the following formula: ,in, Represents the mining adaptability coefficient of the ore body, is the hardness of the ore body, is the density of the ore body; The larger the value, the more difficult the ore body is to mine; Mining difficulty assessment subunit: used to calculate the mining adaptability coefficient based on the physical property analysis subunit , combined with the inclination and ore body depth Assess the mining difficulty; let the mining difficulty index be , the calculation formula is: ,in, is the maximum planned mining depth, is the inclination angle; if If it exceeds the set threshold, it is considered that the mining difficulty is high and the mining method needs to be adjusted; Cost analysis subunit: Based on the mining difficulty assessment, the mining cost is analyzed. Calculate; the formula is: ,in, is the equipment cost, For personnel costs, is the cost of safety measures; let the total mining cost be , the formula is: ,in, is the mineable area of ​​the ore body; Mining plan generation subunit: based on mining difficulty index and cost analysis results to generate a mining plan; if Low and If the budget is within the budget, the conventional mining plan is selected; High or If the budget is exceeded, a segmented mining or reinforced mining plan will be adopted; the mining plan includes mining methods, equipment configuration and safety measures recommendations.

10. A solid mineral resource reserve estimation system based on a double-layer database according to claim 9, characterized in that: The mineral resource reserve calculation unit comprises: Ore content assessment subunit: Determine the grade of the ore based on the physical and chemical properties of the ore body , that is, the content of mineable ore per cubic meter of ore body, calculated as: ,in, is the total mass of the ore, is the total volume of the ore body; Reserve calculation subunit: based on the total effective volume of the ore body and ore content grade Calculate the mineral resource reserves; the calculation formula for mineral resource reserves is: ,in, For mineral resource reserves, is the ore density, used to convert volume reserves to mass reserves; Mining recovery rate adjustment subunit: According to the mining plan generated by the mining feasibility assessment unit, the recovery rate of the reserve calculation results is adjusted to reflect the loss of ore in the actual mining process; the adjusted mineral resource reserves The calculation formula is: ,in, is the mining recovery coefficient, where .

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