Mineral resource exploration and exploitation economic management system

Abstract

The invention relates to the technical field of mineral resource management, and particularly discloses a mineral resource exploration and mining economic management system which comprises an exploration management module, a mining planning and operation management module, an economic and financial management module, a supply chain and logistics management module and a mine ecological restoration and sustainable development module. According to the method, geological modeling and an intelligent algorithm are adopted, mining area resource distribution can be accurately predicted, unnecessary exploration work is reduced, and exploration efficiency is improved; through intelligent data analysis, the layout of drilling points can be optimized, the exploration cost can be reduced, the accuracy of resource estimation is ensured, a reliable decision basis is provided for mine enterprises, an intelligent scheduling algorithm and a path optimization model are combined, the mining sequence and the transportation route are reasonably planned, the ore loss is reduced, and the mine recovery rate is improved; by intelligently analyzing the ore body grade and the geologic structure, an optimal mining scheme can be formulated, waste is reduced, the utilization rate of mineral resources is improved, and meanwhile the overall operation efficiency of a mining area is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of mineral resource management, and in particular relates to an economic management system for mineral resource exploration and mining. Background Art

[0002] In the existing technology, the economic management system for mineral resource exploration and mining faces a series of organizational and management challenges. Traditional mineral resource exploration mainly relies on manual geological exploration and empirical judgment, which is not only inefficient but also difficult to accurately predict the resource distribution in the mining area. Due to the lack of advanced geological modeling technology and intelligent algorithm support, exploration work often requires a large amount of drilling operations, which not only increases exploration costs, but also may cause unnecessary damage to the mining environment.

[0003] In this regard, the inventor proposes an economic management system for mineral resource exploration and mining to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a mineral resource exploration and mining economic management system to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A mineral resource exploration and mining economic management system, comprising:

[0007] Exploration management module, used to collect and analyze geological data to obtain mineral resource reserve assessment results;

[0008] The mining planning and operation management module is used to formulate a mining plan based on the mineral resource reserve assessment results, and to schedule and manage mining equipment and personnel to obtain the optimal production strategy;

[0009] An economic and financial management module is used to perform cost analysis and revenue forecasting based on the optimal production strategy to obtain economic benefit evaluation results;

[0010] A supply chain and logistics management module, used to optimize the transportation and supply chain management of mineral products based on the economic benefit evaluation results to obtain supply chain optimization results;

[0011] The mine ecological restoration and sustainable development module is used to evaluate the environmental impact of the mining area based on the supply chain optimization results, and to formulate an ecological restoration plan to obtain an ecological recovery plan.

[0012] Preferably, the exploration management module includes:

[0013] Geological data acquisition unit, used to collect remote sensing mapping, geophysical exploration, geochemical exploration, and drilling geological data;

[0014] A geological database is used to store and manage the geological data and calculate the mineral reserves in combination with historical data to obtain the mineral resource reserve assessment results;

[0015] The Kriging interpolation method for calculating mineral reserves performs spatial interpolation based on drilling data, predicts the grade distribution of unsampled points inside the ore body, and calculates the ore body reserves. The expression of the Kriging interpolation method is:

[0016]

[0017] Where Z*(x): predicted grade at position x;

[0018] Z(xi): the grade of the i-th sampling point;

[0019] λi: interpolation weight, calculated based on the covariance matrix;

[0020] n: total number of sampling points.

[0021] Preferably, the mining planning and operation management module includes:

[0022] An intelligent scheduling unit, used to formulate an optimal mining path based on the mineral resource reserve assessment results and schedule mining equipment in real time;

[0023] The safety and environment monitoring unit is used to monitor the gas, dust and hydrological environment data in the mining area and optimize the formation of the optimal production strategy.

[0024] Preferably, the optimal mining path is based on an A* search algorithm, which is used to find the optimal mining path inside the mine and minimize the transportation distance and time cost. The A* search algorithm formula is:

[0025] f(n)=g(n)+h(n)

[0026] Where: f(n): estimated cost from the starting point to the target;

[0027] g(n): actual mining cost from the starting point to the current point;

[0028] h(n): Heuristic function that estimates the shortest path from the current point to the target.

[0029] Preferably, the economic and financial management module includes:

[0030] A cost analysis unit, used to calculate the cost of each mining link, and perform dynamic cost optimization based on the optimal production strategy to obtain an optimized cost allocation plan;

[0031] The market forecasting unit is used to make market price forecasts based on the optimized cost allocation scheme, and to conduct benefit evaluation in combination with policy analysis to obtain the economic benefit evaluation result.

[0032] Preferably, the dynamic cost optimization is implemented by linear programming, and the optimal cost allocation scheme is solved based on parameters such as mining area production cost, market price, labor cost, etc. The formula of the linear programming is:

[0033] Objective function:

[0034]

[0035] Constraints:

[0036]

[0037] Where C: total cost;

[0038] ci: cost of the i-th production link;

[0039] xi: resource input in the i-th link;

[0040] R: Total budget.

[0041] Preferably, the supply chain and logistics management module includes:

[0042] A transportation optimization unit, used to calculate the optimal transportation route based on the economic benefit evaluation result, and optimize the mineral product supply chain to obtain the supply chain optimization result;

[0043] The blockchain traceability unit is used to track the entire chain of circulation information of mineral products from mining to end users, and improve the transparency and compliance of the supply chain optimization results.

[0044] Preferably, the optimal transportation route uses the Dijkstra algorithm to calculate the shortest transportation route of ore from the mine to the processing plant or port, and the formula of the Dijkstra algorithm is:

[0045] d(v)=min(d(v),d(u)+w(u,v))

[0046] Where: d(v): the shortest path from the starting point to the node v;

[0047] d(u): the shortest path from the starting point to the previous node u;

[0048] w(u,v): transportation cost from node u to node v.

[0049] Preferably, the mine ecological restoration and sustainable development module includes:

[0050] An environmental impact assessment unit, used to assess the impact of mining on the environment based on the supply chain optimization result and generate an environmental assessment report;

[0051] A reclamation planning unit, used to formulate a mine reclamation and water resources management plan based on the environmental assessment report, establish a water pollution diffusion model, and obtain an ecological restoration plan;

[0052] The water pollution diffusion model uses the Advance-Diffusion equation to predict the diffusion of pollutants in the mining area and evaluate the ecological impact. The formula of the Advance-Diffusion equation is:

[0053]

[0054] Where: C: pollutant concentration;

[0055] t: time;

[0056] v: water velocity vector;

[0057] D: diffusion coefficient;

[0058] Pollutant gradient.

[0059] Preferably, the system also includes a data analysis and decision support module, which is used to perform data integration analysis based on the mineral resource reserve assessment results, the optimal production strategy, the economic benefit assessment results, the supply chain optimization results and the ecological restoration plan, and generate mining investment and production optimization decisions.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] (1) The present invention adopts geological modeling and intelligent algorithms to accurately predict the distribution of resources in the mining area, reduce unnecessary exploration work, and improve exploration efficiency. Through intelligent data analysis, the layout of drilling points can be optimized, the exploration cost can be reduced, and the accuracy of resource estimation can be ensured, providing a reliable decision-making basis for mining enterprises.

[0062] (2) The present invention combines intelligent scheduling algorithms and path optimization models to rationally plan mining sequences and transportation routes, reduce ore losses, and improve mine recovery rates; through intelligent analysis of ore grade and geological structure, the optimal mining plan can be formulated to reduce waste, improve the utilization rate of mineral resources, and at the same time improve the overall operational efficiency of the mining area; through intelligent equipment management, maintenance prediction and production optimization, the system can effectively reduce equipment failure rates, reduce unplanned downtime, and improve the overall production capacity of the mine. In addition, the system optimizes energy allocation, reduces production energy consumption, improves economic benefits, and makes mine operations more efficient and stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 The present invention is a block diagram of the economic management system for mineral resource exploration and mining. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] Embodiment 1:

[0066] See also Figure 1 As shown, a mineral resource exploration and mining economic management system includes:

[0067] Exploration management module, used to collect and analyze geological data to obtain mineral resource reserve assessment results;

[0068] The exploration management module includes:

[0069] Geological data acquisition unit, used to collect remote sensing mapping, geophysical exploration, geochemical exploration, and drilling geological data;

[0070] A geological database is used to store and manage the geological data and calculate the mineral reserves in combination with historical data to obtain the mineral resource reserve assessment results;

[0071] The Kriging interpolation method for calculating mineral reserves performs spatial interpolation based on drilling data, predicts the grade distribution of unsampled points inside the ore body, and calculates the ore body reserves. The expression of the Kriging interpolation method is:

[0072]

[0073] Where Z*(x): predicted grade at position x;

[0074] Z(xi): the grade of the i-th sampling point;

[0075] λi: interpolation weight, calculated based on the covariance matrix;

[0076] n: total number of sampling points;

[0077] Through the Kriging interpolation method, the grade distribution of the entire mining area is predicted based on limited drilling data, which improves exploration accuracy and optimizes mineral assessment results;

[0078] The mining planning and operation management module is used to formulate a mining plan based on the mineral resource reserve assessment results, and to schedule and manage mining equipment and personnel to obtain the optimal production strategy;

[0079] The mining planning and operation management module includes:

[0080] An intelligent scheduling unit, used to formulate an optimal mining path based on the mineral resource reserve assessment results and schedule mining equipment in real time;

[0081] The safety and environment monitoring unit is used to monitor the gas, dust and hydrological environment data in the mining area to ensure safe production and optimize the formation of the optimal production strategy.

[0082] Specifically, the optimal mining path is based on the A* search algorithm, which is used to find the optimal mining path inside the mine and minimize the transportation distance and time cost. The A* search algorithm formula is:

[0083] f(n)=g(n)+h(n)

[0084] Where: f(n): estimated cost from the starting point to the target;

[0085] g(n): actual mining cost from the starting point to the current point;

[0086] h(n): heuristic function that estimates the shortest path from the current point to the target;

[0087] By calculating the shortest transportation route, the ore handling time is reduced and production efficiency is improved;

[0088] An economic and financial management module is used to perform cost analysis and revenue forecasting based on the optimal production strategy to obtain economic benefit evaluation results;

[0089] The economic and financial management module includes:

[0090] A cost analysis unit, used to calculate the cost of each mining link, and perform dynamic cost optimization based on the optimal production strategy to obtain an optimized cost allocation plan;

[0091] The market forecasting unit is used to make market price forecasts based on the optimized cost allocation scheme, and to conduct benefit evaluation in combination with policy analysis to obtain the economic benefit evaluation result.

[0092] Specifically, the dynamic cost optimization is implemented by linear programming, and the optimal cost allocation scheme is solved based on parameters such as mining area production cost, market price, and labor cost. The formula of the linear programming is:

[0093] Objective function:

[0094]

[0095] Constraints:

[0096]

[0097] Where C: total cost;

[0098] ci: cost of the i-th production link;

[0099] xi: resource input in the i-th link;

[0100] R: total budget;

[0101] By calculating the optimal cost allocation, we can improve the efficiency of capital utilization and obtain the economic benefit evaluation results;

[0102] A supply chain and logistics management module, used to optimize the transportation and supply chain management of mineral products based on the economic benefit evaluation results to obtain supply chain optimization results;

[0103] The supply chain and logistics management module includes:

[0104] A transportation optimization unit, used to calculate the optimal transportation route based on the economic benefit evaluation result, and optimize the mineral product supply chain to obtain the supply chain optimization result;

[0105] The blockchain traceability unit is used to track the entire chain of circulation information of mineral products from mining to end users, and improve the transparency and compliance of the supply chain optimization results.

[0106] Specifically, the optimal transportation route uses the Dijkstra algorithm to calculate the shortest transportation route of ore from the mine to the processing plant or port. The formula of the Dijkstra algorithm is:

[0107] d(v)=min(d(v),d(u)+w(u,v))

[0108] Where: d(v): the shortest path from the starting point to the node v;

[0109] d(u): the shortest path from the starting point to the previous node u;

[0110] w(u,v): transportation cost from node u to node v;

[0111] Reduce transportation costs and optimize supply chain management by calculating the shortest path;

[0112] The mine ecological restoration and sustainable development module is used to evaluate the environmental impact of the mine area based on the supply chain optimization results, and formulate an ecological restoration plan to obtain an ecological restoration plan;

[0113] The mine ecological restoration and sustainable development module includes:

[0114] An environmental impact assessment unit, used to assess the impact of mining on the environment based on the supply chain optimization result and generate an environmental assessment report;

[0115] A reclamation planning unit, used to formulate a mine reclamation and water resources management plan based on the environmental assessment report, establish a water pollution diffusion model, and obtain an ecological restoration plan;

[0116] The water pollution diffusion model uses the Advance-Diffusion equation to predict the diffusion of pollutants in the mining area and evaluate the ecological impact. The formula of the Advance-Diffusion equation is:

[0117]

[0118] Where: C: pollutant concentration;

[0119] t: time;

[0120] v: water velocity vector;

[0121] D: diffusion coefficient;

[0122] Contaminant gradients;

[0123] Optimize environmental protection management plans by predicting the spread of water pollution in mining areas.

[0124] Specifically, the system also includes a data analysis and decision support module, which is used to perform data integration analysis based on the mineral resource reserve assessment results, the optimal production strategy, the economic benefit assessment results, the supply chain optimization results and the ecological restoration plan, and generate mining investment and production optimization decisions.

[0125] As can be seen from the above, this system uses geological modeling and intelligent algorithms to accurately predict the distribution of mining resources, reduce unnecessary exploration work, and improve exploration efficiency. Through intelligent data analysis, the layout of drilling points can be optimized, exploration costs can be reduced, and the accuracy of resource estimation can be ensured, providing a reliable decision-making basis for mining companies;

[0126] This system combines intelligent scheduling algorithms and path optimization models to rationally plan mining sequences and transportation routes, reduce ore loss, and improve mine recovery rates. Through intelligent analysis of ore grade and geological structure, the optimal mining plan can be formulated to reduce waste, improve the utilization rate of mineral resources, and improve the overall operational efficiency of the mining area;

[0127] Through intelligent equipment management, maintenance prediction and production optimization, this system can effectively reduce equipment failure rate, reduce unplanned downtime, and improve the overall production capacity of the mine. In addition, the system optimizes energy allocation, reduces production energy consumption, improves economic benefits, and makes mine operations more efficient and stable.

[0128] This system combines intelligent logistics scheduling with supply chain optimization algorithms to rationally arrange the transportation and inventory management of mineral products, reduce logistics costs, and improve delivery efficiency. At the same time, the system can dynamically adjust transportation strategies, reduce supply chain uncertainties, ensure that mineral products can be delivered to the target market in a timely and safe manner, and enhance the overall supply chain collaboration capabilities.

[0129] Embodiment 2:

[0130] Large open pit mining optimization

[0131] The mineral reserve assessment of an open-pit mine shows that the mine contains 350 million tons of ore with an average grade of 2.8%. The mine operation faces the following problems:

[0132] The exploration accuracy is insufficient and the grade distribution of some ore layers is unclear.

[0133] The mining route planning is unreasonable and the ore transportation cost is too high.

[0134] There is waste in cost management and operating expenses remain high

[0135] 1. Basic Information

[0136] The basic data of a mining area are as follows:

[0137] Mineral reserves: 350 million tons

[0138] Average ore grade: 2.8%

[0139] Mining depth: Maximum 400m

[0140] Transportation cost: 4-8 yuan / ton

[0141] Market price fluctuation: 520~580 yuan / ton

[0142] 2. System application process

[0143] (1) Exploration management optimization (ore body modeling based on Kriging interpolation method) Input data:

[0144] Drilling quantity: 1000

[0145] Sampling depth: 0-400m

[0146] Ore layer grade data (partial):

[0147] Drilling number Depth(m) grade(%) P1 50 2.5 P2 80 3.0 P3 120 2.7 ... ... ...

[0148] Calculation method:

[0149] Use Kriging interpolation method to predict ore grade:

[0150]

[0151] in:

[0152] Z*(x) is the predicted grade value at position x

[0153] λi is the weight

[0154] Z(xi) is the grade of the known sampling point

[0155] Calculation results:

[0156] Estimated ore reserves: 345 million tons

[0157] Calculated grade average 2.82% (error reduced by 5%)

[0158] Optimization effect:

[0159] Improved the grade assessment accuracy by 5%, providing an accurate basis for mining;

[0160] (2) Mining route optimization (transportation route optimization based on A* search algorithm) Input data:

[0161] Mine sites: A, B, C, D

[0162] Transportation cost (yuan / ton):

[0163] Transport route Distance(m) Cost (yuan / ton) A→B 500 5 B→C 300 4 C→D 700 6 A→D 900 8

[0164] Optimize calculation:

[0165] A* search algorithm calculates the transportation path:

[0166] f(n)=g(n)+h(n)where:

[0167] g(n) is the current cost

[0168] h(n) is the estimated shortest path

[0169] Calculate the optimal transport route:

[0170] A→B→C→D

[0171] Total transportation costs reduced by 12% (annual savings of approximately RMB 20 million)

[0172] (3) Cost optimization (linear programming)

[0173] Input data:

[0174] Equipment maintenance cost: 20 million yuan

[0175] Labor cost: 50 million yuan

[0176] Transportation cost: 100 million yuan

[0177] Other costs: RMB 80 million

[0178] Total budget: 250 million yuan

[0179] Optimize calculation:

[0180] Objective function:

[0181]

[0182] Calculation results:

[0183] Under the premise of ensuring the normal operation of the mine, the cost structure was optimized, and the total operating cost decreased by 8%, saving 20 million yuan annually;

[0184] (4) Supply chain optimization (transportation network optimization based on Dijkstra algorithm)

[0185] Input data:

[0186] Transport plan 1: mining area → wharf → refinery

[0187] Transport plan 2: Mine → Warehouse → Refinery

[0188] Calculate the path:

[0189] d(v)=min(d(v),d(u)+w(u,v))

[0190] Calculate the optimal path:

[0191] Option 2: Reduce transportation costs by 5%, saving RMB 15 million per year

[0192] (5) Ecological restoration optimization (pollution diffusion model)

[0193] Input data:

[0194] Initial concentration of pollutants in mining area water: C0 = 5.2 mg / L

[0195] Precipitation: 800mm / year

[0196] Water diffusion coefficient: D = 0.1

[0197] Calculation formula:

[0198]

[0199] Calculation results:

[0200] After 10 years, the pollutant concentration dropped to 1.2 mg / L, which meets environmental protection standards.

[0201] From the above, we can see that based on intelligence, data-driven and optimized algorithms, it covers key links such as exploration, mining, operation, sales, supply chain and environmental governance, provides comprehensive management support, improves the efficiency of mineral resource utilization, optimizes economic benefits, and promotes the sustainable development of the mining industry.

[0202] Embodiment three:

[0203] Intelligent operation and management of small and medium-sized underground mines:

[0204] 1. Background Information

[0205] An underground mine with an ore reserve of 10 million tons. The main problems are:

[0206] The mining sequence of the ore bodies is unreasonable, resulting in waste of resources.

[0207] Economic returns are unstable and market prices fluctuate greatly.

[0208] Optimize the drainage system in the mine area to reduce the impact of pollution.

[0209] 2. System application process

[0210] (1) Optimizing the mining sequence of the ore body (dynamic programming)

[0211] Input data:

[0212] Ore body area: Z1, Z2, Z3

[0213] Grade (%): Z1 (2.5%), Z2 (3.2%), Z3 (2.9%)

[0214] Mining cost (yuan / ton): Z1 (300), Z2 (250), Z3 (280)

[0215] Calculation formula:

[0216] V t =max(V t-1 +R t -C t )

[0217] Calculation results:

[0218] Prioritize mining Z2, and increase revenue by 8%;

[0219] (2) Market price forecast (ARIMA model)

[0220] Input data:

[0221] Ore price (yuan / ton): 450, 470, 490, 510, 530 Forecast price for one year

[0222] Calculation formula:

[0223] Y t =φ 1 Y t-1 +φ 2 Y t-2 +ε t Yt: price of mineral products at time t;

[0224] φi: autoregressive coefficient;

[0225] ε t : white noise term;

[0226] By predicting future prices, we can optimize sales strategies and increase economic benefits; prediction results:

[0227] After 6 months, the price is 570 yuan / ton, and the profit increases by 10%;

[0228] (3) Mine drainage optimization (pollution diffusion model)

[0229] Input data:

[0230] Initial concentration of water pollutants: C0 = 4.5 mg / L

[0231] Target concentration: 2.0 mg / L

[0232] Calculation results:

[0233] Pollutant concentrations will drop to 1.8mg / L within 6 years, meeting emission standards;

[0234] From the above, we can see that the system can effectively improve:

[0235] Mineral exploration accuracy, error reduced by 5%;

[0236] The mining route was optimized and the transportation cost was reduced by 12%;

[0237] Optimize operating costs and reduce expenditures by RMB 20 million;

[0238] The accuracy of market forecasts has been improved, and sales revenue has increased by 10%;

[0239] Environmental governance has met standards, with pollutant concentrations reduced by 65%;

[0240] It is applicable to mining areas of different sizes and can improve resource utilization, economic benefits and sustainable development capabilities.

[0241] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A mineral resource exploration and mining economic management system, characterized in that: include: Exploration management module, used to collect and analyze geological data to obtain mineral resource reserve assessment results; The mining planning and operation management module is used to formulate a mining plan based on the mineral resource reserve assessment results, and to schedule and manage mining equipment and personnel to obtain the optimal production strategy; An economic and financial management module is used to perform cost analysis and revenue forecasting based on the optimal production strategy to obtain economic benefit evaluation results; A supply chain and logistics management module, used to optimize the transportation and supply chain management of mineral products based on the economic benefit evaluation results to obtain supply chain optimization results; The mine ecological restoration and sustainable development module is used to evaluate the environmental impact of the mining area based on the supply chain optimization results, and to formulate an ecological restoration plan to obtain an ecological recovery plan.

2. The economic management system for mineral resource exploration and mining according to claim 1 is characterized in that: The exploration management module includes: Geological data acquisition unit, used to collect remote sensing mapping, geophysical exploration, geochemical exploration, and drilling geological data; A geological database is used to store and manage the geological data and calculate the mineral reserves in combination with historical data to obtain the mineral resource reserve assessment results; The Kriging interpolation method for calculating mineral reserves performs spatial interpolation based on drilling data, predicts the grade distribution of unsampled points inside the ore body, and calculates the ore body reserves. The expression of the Kriging interpolation method is: Where Z*(x): predicted grade at position x; Z(xi): the grade of the i-th sampling point; λi: interpolation weight, calculated based on the covariance matrix; n: total number of sampling points.

3. The economic management system for mineral resource exploration and mining according to claim 1 is characterized in that: The mining planning and operation management module includes: An intelligent scheduling unit, used to formulate an optimal mining path based on the mineral resource reserve assessment results and schedule mining equipment in real time; The safety and environment monitoring unit is used to monitor the gas, dust and hydrological environment data in the mining area and optimize the formation of the optimal production strategy.

4. A mineral resource exploration and mining economic management system according to claim 3, characterized in that: The optimal mining path is based on the A* search algorithm, which is used to find the optimal mining path inside the mine and minimize the transportation distance and time cost. The A* search algorithm formula is: f(n)=g(n)+h(n) Where: f(n): estimated cost from the starting point to the target; g(n): actual mining cost from the starting point to the current point; h(n): Heuristic function that estimates the shortest path from the current point to the target.

5. The economic management system for mineral resource exploration and mining according to claim 1, characterized in that: The economic and financial management module includes: A cost analysis unit, used to calculate the cost of each mining link, and perform dynamic cost optimization based on the optimal production strategy to obtain an optimized cost allocation plan; The market forecasting unit is used to make market price forecasts based on the optimized cost allocation scheme, and to conduct benefit evaluation in combination with policy analysis to obtain the economic benefit evaluation result.

6. A mineral resource exploration and mining economic management system according to claim 5, characterized in that: The dynamic cost optimization is implemented by linear programming, and the optimal cost allocation scheme is solved based on parameters such as mining area production cost, market price, and labor cost. The formula of the linear programming is: Objective function: Constraints: Where C: total cost; ci: cost of the i-th production link; xi: resource input in the i-th link; R: Total budget.

7. The economic management system for mineral resource exploration and mining according to claim 1 is characterized in that: The supply chain and logistics management module includes: A transportation optimization unit, used to calculate the optimal transportation route based on the economic benefit evaluation result, and optimize the mineral product supply chain to obtain the supply chain optimization result; The blockchain traceability unit is used to track the entire chain of circulation information of mineral products from mining to end users, and improve the transparency and compliance of the supply chain optimization results.

8. The economic management system for mineral resource exploration and mining according to claim 7 is characterized in that: The optimal transportation route uses the Dijkstra algorithm to calculate the shortest transportation route of ore from the mine to the processing plant or port. The formula of the Dijkstra algorithm is: d(v)=min(d(v),d(u)+w(u,v)) Where: d(v): the shortest path from the starting point to the node v; d(u): the shortest path from the starting point to the previous node u; w(u,v): transportation cost from node u to node v.

9. The economic management system for mineral resource exploration and mining according to claim 1, characterized in that: The mine ecological restoration and sustainable development module includes: An environmental impact assessment unit, used to assess the impact of mining on the environment based on the supply chain optimization result and generate an environmental assessment report; A reclamation planning unit, used to formulate a mine reclamation and water resources management plan based on the environmental assessment report, establish a water pollution diffusion model, and obtain an ecological restoration plan; The water pollution diffusion model uses the Advance-Diffusion equation to predict the diffusion of pollutants in the mining area and evaluate the ecological impact. The formula of the Advance-Diffusion equation is: Where: C: pollutant concentration; t: time; v: water velocity vector; D: diffusion coefficient; Pollutant gradient.

10. The economic management system for mineral resource exploration and mining according to claim 1, characterized in that: The system also includes a data analysis and decision support module for performing data integration analysis based on the mineral resource reserve assessment results, the optimal production strategy, the economic benefit assessment results, the supply chain optimization results and the ecological restoration plan, and generating mining investment and production optimization decisions.

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