A method and system for evaluating the impact of coal seam mining on groundwater flow field.

Abstract

This invention relates to the field of numerical simulation technology, and in particular to a method and system for evaluating the impact of coal seam mining on groundwater flow field. The method includes: S1, establishing a hydrogeological conceptual model of a designated mining area; S2, using Visual MODFLOW software, establishing a numerical model based on the pre-established hydrogeological conceptual model of the designated mining area; S3, using actual observation data of the designated mining area to identify and verify the numerical model, obtaining an identified and verified numerical model; S4, using the verified numerical model to predict the impact of coal seam mining on groundwater flow field, obtaining prediction results; S5, based on the prediction results, evaluating the impact of coal seam mining on groundwater flow field in the designated mining area.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation technology, and in particular to a method and system for evaluating the impact of coal seam mining on groundwater flow field. Background Technology

[0002] The impact assessment of coal seam mining on groundwater flow fields is a crucial aspect of environmental protection and sustainable development in mining areas. Coal mining involves groundwater extraction, discharge, and dewatering at the working face, all of which affect the groundwater flow field. Evaluating the impact of coal seam mining on groundwater flow fields helps mine managers understand the extent of the impact of mining activities on the groundwater system and formulate corresponding environmental protection and water resource management measures to protect the sustainable use of groundwater resources. By evaluating the impact of coal seam mining on groundwater flow fields, changes in groundwater levels, flow direction, and water quality can be predicted, allowing for timely measures to avoid or mitigate the adverse effects of coal mining activities on groundwater resources. However, evaluating the impact of coal seam mining on groundwater flow fields requires accurate predictions of these impacts. Currently, however, the predictions of the impact of coal seam mining on groundwater flow fields are inaccurate, leading to inaccurate assessments as well.

[0003] Therefore, there is an urgent need for an evaluation method and system for the impact of coal seam mining on groundwater flow field. Summary of the Invention

[0004] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a method and system for evaluating the impact of coal seam mining on the groundwater flow field.

[0005] To achieve the above objectives, the main technical solutions adopted by the present invention include:

[0006] In a first aspect, embodiments of the present invention provide a method for evaluating the impact of coal seam mining on groundwater flow fields, comprising:

[0007] S1. Establish a hydrogeological conceptual model of the designated mining area;

[0008] S2. Using Visual MODFLOW software, establish a numerical model based on the pre-established hydrogeological conceptual model of the designated mining area;

[0009] S3. Using actual observation data from the designated mining area, identify and verify the numerical model to obtain the identified and verified numerical model;

[0010] S4. Using the validated numerical model, predict the impact of coal seam mining on the groundwater flow field and obtain the prediction results.

[0011] S5. Based on the prediction results, evaluate the impact of coal seam mining in the designated mining area on the groundwater flow field.

[0012] Preferably, S1 specifically includes:

[0013] S1-1. Determine the boundary range of the hydrogeological conceptual model;

[0014] S1-2. The boundary conditions of the specified mining area are generalized to obtain the generalized boundary conditions; among them, the generalized boundary conditions include: flow boundary conditions, river boundary conditions, and zero flow boundary conditions.

[0015] S1-3. The aquifers in the designated mining area are generalized to obtain the hydrogeological conceptual model of the designated mining area.

[0016] Preferably, the aquifers in the designated mining area are generalized, specifically including: vertically generalizing the groundwater in the designated mining area into 7 layers, from top to bottom: a Quaternary pore-filled aquifer composed of Holocene and Upper Pleistocene Salausu Formation sand layers; an impermeable layer composed of Quaternary Middle Pleistocene Lishi Formation clay and Neogene Baode Formation clay; a Jurassic Middle Series weathered layer aquifer; a Jurassic Middle Series Anding-Zhiluo Formation aquifer; and a Jurassic Middle Series 2... -2 The Yan'an Formation aquifer above the coal seam; Middle Jurassic Yan'an Formation 2 -2 Coal seam aquifer; 2 -2 The Jurassic Yan'an Formation aquifer lies below the coal seam.

[0017] Preferably, S2 specifically includes:

[0018] S21. Based on the hydrogeological conceptual model of the designated mining area, the groundwater flow in the designated mining area is defined as a heterogeneous, isotropic, three-dimensional spatial structure, and unstable seepage region.

[0019] The mathematical model expression for groundwater flow in the designated mining area is as follows:

[0020] ;

[0021] Wherein, Ω represents the seepage zone; H represents the aquifer water level elevation; and Z represents the elevation of the bottom plate of the unconfined aquifer. River boundary conditions; The flow boundary conditions for the seepage region; q represents the zero-flow boundary condition for the seepage region; q represents the unit width seepage flow rate on the flow boundary; H0(x, y, z) represents the initial water level of the aquifer; n represents the normal direction outside the boundary; K represents the aquifer permeability coefficient; W represents the vertical recharge or discharge intensity above the unconfined surface; μ represents the specific yield of the unconfined aquifer; and Ss represents the unit release rate of the confined aquifer.

[0022] S22. Spatial discretization is performed on the specified mining area to obtain a numerical model;

[0023] The spatial discretization method involves automatically dividing the water-bearing medium in the seepage area using an equal-interval effective difference discretization method. The coordinate axis direction is consistent with the geographic coordinate direction, with the X direction being due east, the Y direction being due north, and the Z direction being vertically upward.

[0024] Preferably, S3 specifically includes:

[0025] The actual observation data of the specified mining area within the specified first time period are determined, the numerical model is identified and verified, and in the process of identification and verification, the groundwater level corresponding to the specified historical time of the specified mining area is used as the initial flow field, and the inflow and outflow boundaries of each source and sink term are input into the corresponding boundary grid in the form of wells. By fitting the flow field near the boundary, the distribution of boundary inflow and outflow is adjusted.

[0026] The source and sink term processing in the numerical model includes:

[0027] The atmospheric precipitation infiltration recharge in the numerical model is calculated using formula (1);

[0028] Wherein, formula (1) is:

[0029] ;

[0030] Among them, a i P is the atmospheric precipitation infiltration recharge coefficient for the i-th pre-divided calculation zone within the seepage region. i A represents the precipitation in the pre-defined calculation zone i within the seepage region; i The area of ​​the i-th pre-divided computational zone in the seepage region;

[0031] The amount of condensate replenishment in the desert area is calculated using formula (2);

[0032] Formula (2) is as follows:

[0033] Q 凝 =M 凝 ·F 凝 ·t 凝 ;

[0034] Among them, M 凝 Modulus for condensate supply; F 凝 The area where condensate replenishment occurs; t 凝 This refers to the time when condensate replenishment occurs annually.

[0035] The amount of agricultural irrigation return water replenishment is calculated using formula (3);

[0036] The formula (3) is:

[0037] ;

[0038] Where, β i G represents the regression replenishment coefficient for irrigation of the i-th type of farmland; i For the gross irrigation quota of the i-th type of farmland; F i Let i be the irrigated area of ​​the i-th type of farmland;

[0039] In the numerical model, a first preset value is set for the ultimate evaporation depth of the mining area;

[0040] The lateral flow rate during the identification and verification period is calculated using Darcy's law based on the hydraulic gradient of the flow field at the flow boundary, the aquifer thickness, and the permeability coefficient at the boundary. The inflow and outflow rates at each boundary are input into the corresponding boundary grid in the form of points using the well flow sub-package. By fitting the flow field near the boundary, the distribution of the inflow and outflow rates at the boundary is appropriately adjusted.

[0041] The amount of water exchanged between river water and groundwater is calculated using formula (4);

[0042] Formula (4) is as follows:

[0043] ;

[0044] Where K' is the vertical permeability coefficient of the riverbed; M is the thickness of the riverbed sediments; A is the seepage area of ​​the river channel; H r River water level; H ij Groundwater level; C r The leakage intensity of the river;

[0045] The groundwater extraction volume of the designated mining area is determined as the second pre-set value.

[0046] Preferably, the prediction results in S4 include: a first indicator, a second indicator, a third indicator, and a fourth indicator;

[0047] The first indicator is the change in groundwater level; the second indicator is the change in groundwater flow velocity; the third indicator is the change in groundwater flow direction; and the fourth indicator is the risk value of groundwater pollution.

[0048] Preferably, the first preset value is 2.8m.

[0049] Preferably, S5 specifically includes:

[0050] For any indicator in the prediction results, if the indicator is within the normal range (a, b) corresponding to that indicator, then the indicator is determined to be normal.

[0051] Preferably, S5 specifically includes:

[0052] If the indicator is outside the normal range (a, b) corresponding to the indicator, and the indicator is not less than b, then the warning value of the indicator is determined to be (the indicator - b) / (ba).

[0053] If the indicator is outside the normal range (a, b) corresponding to the indicator, and the indicator is not greater than a, then the warning value of the indicator is determined to be (a - the indicator) / (ba).

[0054] Based on the warning value corresponding to each indicator in the prediction result, the total warning value corresponding to the prediction result is determined, and a warning message is issued when the total warning value exceeds a preset threshold.

[0055] Preferably,

[0056] The total warning value corresponding to the prediction result is determined by formula (5);

[0057] The formula (5) is:

[0058] Total warning value = w1 * warning value corresponding to the first indicator + w2 * warning value corresponding to the second indicator + w3 * warning value corresponding to the third indicator + w4 * warning value corresponding to the fourth indicator;

[0059] When the indicator is normal, the corresponding warning value is 0;

[0060] w1 is the first pre-set weight coefficient; w2 is the second pre-set weight coefficient; w3 is the third pre-set weight coefficient; and w4 is the fourth pre-set weight coefficient.

[0061] On the other hand, this embodiment also provides an evaluation system for the impact of coal seam mining on groundwater flow field, including:

[0062] At least one processor; and

[0063] At least one memory communicatively connected to the processor, wherein the memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute an evaluation method for the impact of coal seam mining on groundwater flow field, as described above.

[0064] The beneficial effects of this invention are as follows: The method and system for evaluating the impact of coal seam mining on the groundwater flow field of this invention, by using Visual MODFLOW software, establishes a numerical model based on a pre-established hydrogeological conceptual model of a designated mining area; then, using actual observation data of the designated mining area, the numerical model is identified and verified to obtain an identified and verified numerical model; furthermore, the verified numerical model is used to predict the impact of coal seam mining on the groundwater flow field, and the prediction results are obtained. Compared with the prior art, it can obtain an accurate assessment of the impact of coal seam mining on the groundwater flow field. Attached Figure Description

[0065] Figure 1 This is a flowchart of an evaluation method for the impact of coal seam mining on groundwater flow field according to the present invention.

[0066] Figure 2 This is a schematic diagram of the boundary range in this embodiment;

[0067] Figure 3 This is a plan view of the simulated seepage region in this embodiment;

[0068] Figure 4 This is a diagram of the initial flow field of the untreated water in the simulated seepage zone in this embodiment.

[0069] Figure 5 This is the initial flow field diagram of the weathered fracture aquifer in the simulated seepage region in this embodiment;

[0070] Figure 6 This embodiment identifies the groundwater flow field diagram at the end of the identification period;

[0071] Figure 7-1 This is a schematic diagram of the dynamic fitting curve of the groundwater level in the long observation hole with the pre-set label Q1 in the simulated seepage area in this embodiment.

[0072] Figure 7-2 This is a schematic diagram of the dynamic fitting curve of groundwater level in long observation holes labeled G1-Q in the simulated seepage area in this embodiment.

[0073] Figure 7-3 This is a schematic diagram of the dynamic fitting curve of the groundwater level in the long observation hole labeled G2-Q, which is pre-set in the simulated seepage area in this embodiment.

[0074] Figure 7-4 This is a schematic diagram of the dynamic fitting curve of the groundwater level in the long observation hole with the pre-set label BK9 in the simulated seepage area in this embodiment.

[0075] Figure 7-5 This is a schematic diagram of the dynamic fitting curve of the groundwater level in the long observation hole with the pre-set label G1 in the simulated seepage area in this embodiment.

[0076] Figure 8 This is a zoning diagram of the unconfined aquifer parameters in this embodiment;

[0077] Figure 9 This is a zoning diagram of the aquifer parameters of the Anding-Zhiluo Formation in this embodiment;

[0078] Figure 10 This is a zoning diagram of the aquifer parameters of the Yan'an Formation in this embodiment. Detailed Implementation

[0079] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0080] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present invention can be understood more clearly and thoroughly, and that the scope of the present invention can be fully conveyed to those skilled in the art.

[0081] See Figure 1 This embodiment provides a method for evaluating the impact of coal seam mining on groundwater flow field, including:

[0082] S1. Establish a hydrogeological conceptual model of the designated mining area; wherein, S1 specifically includes:

[0083] S1-1. Determine the boundary range of the hydrogeological conceptual model.

[0084] S1-2. The boundary conditions of the specified mining area are generalized to obtain the generalized boundary conditions; among which, the generalized boundary conditions include: flow boundary conditions, river boundary conditions, and zero flow boundary conditions.

[0085] See Figure 2 In the boundary range diagram of this embodiment, the northeastern part of the hydrogeological conceptual model is the groundwater recharge area, which is generalized as a flow boundary condition; the southwestern part is the Yuxi River and its tributaries, which is generalized as a river boundary condition; the southeastern part is the watershed, which is generalized as a zero flow boundary condition; according to the groundwater flow field of the designated mining area, the northwestern part of the hydrogeological conceptual model is orthogonal to the groundwater isostatic line, which is generalized as a zero flow boundary condition.

[0086] S1-3. The aquifers in the designated mining area are generalized to obtain the hydrogeological conceptual model of the designated mining area.

[0087] Specifically, the aquifers in the designated mining area are generalized, including: vertically, the groundwater in the designated mining area is generalized into 7 layers, from top to bottom: the Quaternary pore-filled aquifer composed of Holocene and Upper Pleistocene Salausu Formation sand layers; the impermeable layer composed of Quaternary Middle Pleistocene Lishi Formation clay and Neogene Baode Formation clay; the Jurassic Middle Series weathered layer aquifer; the Jurassic Middle Series Anding-Zhiluo Formation aquifer; and the Jurassic Middle Series 2... -2 The Yan'an Formation aquifer above the coal seam; Middle Jurassic Yan'an Formation 2 -2 Coal seam aquifer; 2 -2 The Jurassic Yan'an Formation aquifer below the coal seam (50m below the coal seam).

[0088] Hydrogeological conceptual models (HTMs) are theoretical frameworks or mathematical models that describe the structure and behavior of groundwater systems. Based on an understanding of geology, hydrology, and hydrogeological processes, they are used to simulate groundwater flow and the dynamic changes of hydrogeological systems. The functions of HTMs include: simulating hydrogeological processes, predicting groundwater levels, analyzing water resource sustainability, studying groundwater flow direction and pathways, assessing the impact of groundwater on the surrounding environment, analyzing groundwater pollution propagation, and supporting engineering project planning. Overall, HTMs, through the simulation and analysis of groundwater systems, provide an understanding of groundwater behavior and hydrogeological processes, offering a scientific basis for decisions in water resource management, environmental protection, and engineering planning.

[0089] S2. Using Visual MODFLOW software, establish a numerical model based on the pre-established hydrogeological conceptual model of the designated mining area;

[0090] S3. Using actual observation data from the designated mining area, identify and verify the numerical model to obtain the identified and verified numerical model;

[0091] S4. Using the validated numerical model, predict the impact of coal seam mining on the groundwater flow field and obtain the prediction results.

[0092] In this embodiment, the prediction of the impact of coal seam mining on the groundwater flow field using a validated numerical model can be carried out through the following steps: First, determine the coal seam mining plan, including mining method, mining time, and mining area. Second, update the parameters in the numerical model based on the actual mining situation, such as the location of the mining face, coal seam water content, and permeability. Third, simulate the impact of coal seam mining on the groundwater flow field using the updated model parameters. Fourth, simulate changes in groundwater level and groundwater flow velocity during the mining process according to the mining plan and time period. Fifth, analyze and predict the impact of coal seam mining on the groundwater flow field based on the simulation results, paying attention to changes in groundwater level, trends in groundwater flow velocity, and groundwater recharge attenuation. Sixth, assess the degree of impact of coal seam mining on groundwater resources based on the prediction results and make optimizations and adjustments. Consideration can be given to adjusting the mining plan, adding drainage systems, and implementing water recharge measures to mitigate groundwater resource losses. Through these steps, the validated numerical model can predict the impact of coal seam mining on the groundwater flow field, providing scientific basis and guidance for the rational utilization and management of groundwater resources.

[0093] The results of predicting the impact of coal seam mining on the groundwater flow field can include: Groundwater level changes: Predicting potential changes in groundwater level during coal seam mining, including the magnitude of the drop in groundwater level in the mining area and the impact on surrounding groundwater levels. Groundwater velocity changes: Predicting the impact of coal seam mining on groundwater velocity within the simulated area, which may manifest as an increase or decrease in groundwater velocity and a change in flow direction. Groundwater quality changes: Predicting the potential impact of coal seam mining on groundwater quality, particularly the potential impact of chemicals released into the groundwater during mining on surrounding groundwater quality. Recharge attenuation analysis: Analyzing the impact of coal seam mining on groundwater recharge and predicting the attenuation of groundwater recharge caused by mining. Drainage effect assessment: Evaluating the design and effectiveness of the drainage system, including predicting the system's control effect on groundwater level and groundwater velocity.

[0094] S5. Based on the prediction results, evaluate the impact of coal seam mining in the designated mining area on the groundwater flow field.

[0095] In this embodiment, S2 specifically includes:

[0096] S21. Based on the hydrogeological conceptual model of the designated mining area, the groundwater flow in the designated mining area is defined as a heterogeneous, isotropic, three-dimensional spatial structure, and unstable seepage region.

[0097] The mathematical model expression for groundwater flow in the designated mining area is as follows:

[0098] ;

[0099] Where Ω represents the seepage zone; H represents the aquifer water level elevation (m); and Z represents the elevation of the bottom plate of the unconfined aquifer (m). River boundary conditions; The flow boundary conditions for the seepage region; The boundary condition is zero flow rate in the seepage region; q is the unit width seepage flow rate (m) on the flow boundary. 2 / d); H0(x, y, z) is the initial water level of the aquifer (m); n is the direction of the outer normal of the boundary; K is the aquifer permeability coefficient (m / d); W is the vertical recharge or discharge intensity above the unconfined aquifer; μ is the specific yield of the unconfined aquifer (dimensionless); Ss is the unit release rate of the confined aquifer (1 / m).

[0100] S22. Spatial discretization is performed on the specified mining area to obtain a numerical model.

[0101] The spatial discretization method involves automatically dividing the water-bearing medium in the seepage area using an equal-interval effective difference discretization method. The coordinate axis direction is consistent with the geographic coordinate direction, with the X direction being due east, the Y direction being due north, and the Z direction being vertically upward.

[0102] In this embodiment, the automatic subdivision uses a 200m × 200m equally spaced grid, divided into 161 rows and 122 columns, with 5 layers vertically. The solute prediction region is further refined to a 10m × 10m equally spaced grid. Figure 3 This is a plan view of the simulated seepage region, which includes active and inactive cells.

[0103] In this embodiment, when a user uses Visual MODFLOW software to build a numerical model, the user will follow these steps:

[0104] In Visual MODFLOW, users create a new project and select an appropriate coordinate system and units. Within the project, they define the model's basic properties, such as start and end times, and time steps. The process of importing the conceptual model into Visual MODFLOW may include importing geological layers, hydrogeological parameters, boundary conditions, and other information. Visual MODFLOW automatically generates a mesh for the numerical model based on the geographical and hydrogeological characteristics of the mining area. Users can also choose the mesh fineness to balance computational accuracy and efficiency. Users set the boundary conditions for the numerical model, including specifying the boundaries, sources, and sinks of the groundwater model. They specify the initial conditions of the model, i.e., the groundwater level distribution at the start of the simulation. Users select appropriate numerical simulation methods and parameters. Visual MODFLOW provides various numerical simulation methods, such as the finite difference method or the finite element method, as well as adjustment parameters for model stability and accuracy. Finally, the numerical simulation is run using Visual MODFLOW. The software simulates the behavior of the groundwater system over a specified time period based on the defined conceptual model, boundary conditions, and initial conditions. After running, the simulation results are stored in an output file. The simulation results are then analyzed using the visualization tools provided by Visual MODFLOW. This may include viewing water level maps, streamline diagrams, and groundwater velocity maps. Users can better understand the dynamic changes in the groundwater system.

[0105] In a specific application of this embodiment, S3 specifically includes:

[0106] Determine the actual observation data for a specified first time period in a designated mining area, identify and verify the numerical model, and during the identification and verification process, incorporate the specified historical time data for the designated mining area.

[0107] The corresponding groundwater level is used as the initial flow field, and the inflow and outflow boundaries of each source and sink term are input into the corresponding boundary grid in the form of wells. By fitting the flow field near the boundary, the distribution of boundary inflow and outflow is adjusted.

[0108] The first designated time period for the specified mining area is the identification period for the numerical model of the simulation area, determined based on actual groundwater observation data. Specifically, measured data from May 2017 to April 2022 for the specified mining area are used for simulation identification. Furthermore, the historical time specified in this embodiment is May 2014; therefore, the groundwater level in May 2014 is used as the initial flow field reference. Figure 4 , Figure 5 .

[0109] The source and sink term processing in the numerical model includes:

[0110] The atmospheric precipitation infiltration recharge in the numerical model is calculated using formula (1);

[0111] Wherein, formula (1) is:

[0112] ;

[0113] Among them, a i The atmospheric precipitation infiltration recharge coefficient for the i-th pre-divided calculation zone in the seepage region (0.36 for sandy beaches, 0.20 for dune sandy areas, and 0.30 for river valleys); P i Precipitation (mm / a) for the i-th pre-divided calculation zone within the seepage region; A i The area (m²) of the i-th pre-divided computational zone in the seepage region. 2 ).

[0114] In numerical models, atmospheric precipitation infiltration refers to the process by which precipitation from the atmosphere enters the groundwater system through the Earth's surface. This process is crucial for the replenishment of the groundwater system, as it is a key component of the groundwater cycle.

[0115] The amount of condensate replenishment in the desert area is calculated using formula (2);

[0116] Formula (2) is as follows:

[0117] Q 凝 =M 凝 ·F 凝 ·t 凝 ;

[0118] Where: M 凝 Condensate supply modulus (m) 3 / d·m 2 ); F 凝 The area (m²) where condensate replenishment occurs 2 ); t 凝 The time (d) during which condensate recharge occurs annually; condensate recharge and precipitation recharge are both input into the model using the recharge module.

[0119] Condensation water replenishment in desert areas refers to the water replenishment method in desert regions where water vapor in the atmosphere condenses into water droplets or beads and is deposited on the earth's surface.

[0120] The amount of agricultural irrigation return water replenishment is calculated using formula (3);

[0121] The formula (3) is:

[0122] ;

[0123] Where, β i Let G be the regression replenishment coefficient for irrigation of the i-th type of farmland (0.35 for irrigated land and 0.28 for plain water land);i The gross irrigation quota (m) for the i-th type of farmland 3 / a·mu); F i Let represent the irrigated area of ​​the i-th type of farmland; the irrigation water infiltration replenishment is input into the model using the recharge module.

[0124] Agricultural irrigation return water replenishment refers to the amount of water introduced through agricultural irrigation, some of which is absorbed by plants and evaporates, while the rest seeps into the soil and eventually enters the groundwater system. This water replenishment is an important method of groundwater system replenishment.

[0125] In the numerical model, the first preset value is set for the limit evaporation depth of the mining area; in this embodiment, evaporation discharge is handled by the EVT subroutine package, and the limit evaporation depth of the simulated area is taken as 2.8m according to the hydrogeological survey results of the project.

[0126] The lateral flow rate during the identification and verification period is calculated using Darcy's law based on the hydraulic gradient of the flow field at the flow boundary, the aquifer thickness, and the permeability coefficient at the boundary. The inflow and outflow rates at each boundary are input into the corresponding boundary grid in the form of points using the Wellflow Subpackage (WEL). By fitting the flow field near the boundary, the distribution of the inflow and outflow rates at the boundary is appropriately adjusted.

[0127] The amount of water exchanged between river water and groundwater is calculated using formula (4);

[0128] Formula (4) is as follows:

[0129] ;

[0130] Where K' is the vertical permeability coefficient of the riverbed (m / d); M is the thickness of the riverbed sediments (m); and A is the seepage area of ​​the river channel (m²). 2 ); H r River water level (m); H ij Groundwater level (m); C r The leakage intensity of the river (m) 2 / d); The exchange rate between river and groundwater was simulated and analyzed using the River module in Modflow.

[0131] The exchange between river water and groundwater is often referred to as river-groundwater interaction or riverbed seepage. This exchange is significant in hydrogeology because it affects the water dynamics, water quality distribution, and ecosystem health of river and groundwater systems.

[0132] The groundwater extraction volume of the designated mining area is determined as the second pre-set value. In this embodiment, manual extraction mainly involves water extraction for human and livestock use and well irrigation. Based on the survey statistics of population, livestock, and cultivated land area, combined with water quota data, the groundwater extraction volume of the designated mining area is determined to be 354,700 m³. 3 / a.

[0133] Numerical model identification and verification involves addressing the uncertainty of whether the established numerical model can represent the geological body under study. This requires inputting various parameters and conditions needed for the simulation into different modules, running the model multiple times, adjusting hydrogeological parameters, equilibrium terms, and boundary conditions, and fitting the measured groundwater levels from the same period until the fitting results are within the allowable error range. In this embodiment, measured data from the Jinjitan Coal Mine from May 2017 to April 2022 were used for simulation identification, combining the calculation results with the analysis of geological conditions to achieve the best fitting effect. Figure 6 To identify the groundwater flow field map at the end of the period. From Figure 7-1 , Figure 7-2 , Figure 7-3 , Figure 7-4 , Figure 7-5 As can be seen, the calculated values ​​of groundwater level and flow field generally follow the same trend as the measured values, with small fitting errors, indicating that the numerical model performs well overall. The groundwater flow field at the end of the identification period is used as the initial groundwater flow field for the model to predict coal mining.

[0134] The Quaternary groundwater recharge and discharge balance at the end of the identification period (April 2022) was obtained through numerical modeling, as shown in Table 1. The current groundwater recharge is 94,116,500 m³ / a, the total discharge is 95,532,600 m³ / a, and the balance difference is -1,416,100 m³ / a. 3 / a.

[0135] Table 1

[0136]

[0137] The geological and hydrogeological conditions of the simulated seepage area are relatively simple. Based on a comprehensive analysis of the pumping test results (including permeability coefficient, storage coefficient, specific yield, and unit yield), aquifer distribution patterns, flow field characteristics, and differences in geological conditions, the parameters and zones of the simulated seepage area are determined through numerical model identification and verification. These zones include unconfined aquifers, weakly permeable layers, the Anding Formation-Zhiluo Formation, the Yan'an Formation, and 2... -2 Coal seam and other aquifer parameters zoning, such as Figure 8 — Figure 10 The parameter values ​​for each partition are shown in Table 2.

[0138] Table 2

[0139]

[0140] The prediction results in S4 include: a first indicator, a second indicator, a third indicator, and a fourth indicator;

[0141] The first indicator is the change in groundwater level; the second indicator is the change in groundwater flow velocity; the third indicator is the change in groundwater flow direction; and the fourth indicator is the risk value of groundwater pollution.

[0142] In practical applications of this embodiment, S5 specifically includes:

[0143] For any indicator in the prediction results, if the indicator is within the normal range (a, b) corresponding to that indicator, then the indicator is determined to be normal.

[0144] If the indicator is outside the normal range (a, b) corresponding to the indicator, and the indicator is not less than b, then the warning value of the indicator is determined to be (the indicator - b) / (ba).

[0145] If the indicator is outside the normal range (a, b) corresponding to the indicator, and the indicator is not greater than a, then the warning value of the indicator is determined to be (a - the indicator) / (ba).

[0146] Based on the warning value corresponding to each indicator in the prediction result, the total warning value corresponding to the prediction result is determined, and a warning message is issued when the total warning value exceeds a preset threshold.

[0147] The total warning value corresponding to the prediction result is determined by formula (5).

[0148] The formula (5) is:

[0149] Total warning value = w1 * warning value corresponding to the first indicator + w2 * warning value corresponding to the second indicator + w3 * warning value corresponding to the third indicator + w4 * warning value corresponding to the fourth indicator.

[0150] When the indicator is normal, the corresponding warning value is 0.

[0151] w1 is the first pre-set weight coefficient; w2 is the second pre-set weight coefficient; w3 is the third pre-set weight coefficient; and w4 is the fourth pre-set weight coefficient.

[0152] By comparing the relationship between each indicator and its normal range, the system calculates the warning value for each indicator and, taking into account the weight of each indicator, calculates the total warning value. If the total warning value exceeds a preset threshold, the system will issue a warning message. Therefore, it can more comprehensively and holistically evaluate the rationality of the prediction results and help to identify various potential problems in the process.

[0153] By determining whether each indicator is within the normal range, anomalies or deviations from normal conditions can be detected promptly. For abnormal indicators, corresponding warning values ​​are calculated, quantifying the degree of deviation. This provides a more specific understanding of the severity of anomalies, helping to quickly assess the urgency of the problem. Furthermore, considering that different indicators may have varying importance, weighting coefficients are introduced, allowing for greater emphasis on monitoring key system performance when calculating the overall warning value. This helps to more accurately capture significant changes in the process.

[0154] This embodiment presents a method and system for evaluating the impact of coal seam mining on groundwater flow field. By employing Visual MODFLOW software, a numerical model is established based on a pre-established hydrogeological conceptual model of a designated mining area. Then, actual observation data from the designated mining area is used to identify and verify the numerical model, resulting in a verified numerical model. Furthermore, the verified numerical model is used to predict the impact of coal seam mining on the groundwater flow field, yielding prediction results. Compared to existing technologies, this method provides a more accurate assessment of the impact of coal seam mining on the groundwater flow field.

[0155] On the other hand, this embodiment also provides an evaluation system for the impact of coal seam mining on groundwater flow field, including: at least one processor; and at least one memory communicatively connected to the processor, wherein the memory stores program instructions that can be executed by the processor, and the processor can execute the evaluation method for the impact of coal seam mining on groundwater flow field as described in any of the embodiments in the first embodiment by calling the program instructions.

[0156] In the description of this invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0157] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0158] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first and second features are in direct contact, or that they are in indirect contact through an intermediate medium. Furthermore, "above," "over," or "on top" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," or "beneath" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0159] In the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0160] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make modifications, alterations, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for evaluating the impact of coal seam mining on groundwater flow field, characterized in that, include: S1. Establish a hydrogeological conceptual model of the designated mining area; S2. Using Visual MODFLOW software, establish a numerical model based on the pre-established hydrogeological conceptual model of the designated mining area; S3. Using actual observation data from the designated mining area, identify and verify the numerical model to obtain the identified and verified numerical model; S4. Using the validated numerical model, predict the impact of coal seam mining on the groundwater flow field and obtain the prediction results. S5. Based on the prediction results, evaluate the impact of coal seam mining in the designated mining area on the groundwater flow field; S1 specifically includes: S1-1. Determine the boundary range of the hydrogeological conceptual model; S1-2. The boundary conditions of the specified mining area are generalized to obtain the generalized boundary conditions; among which, the generalized boundary conditions include: flow boundary conditions and river boundary conditions. S1-3. Generalize the aquifers in the designated mining area to obtain the hydrogeological conceptual model of the designated mining area; Specifically, the aquifers in the designated mining area are generalized, including: vertically, the groundwater in the designated mining area is generalized into 7 layers, from top to bottom: the Quaternary pore-filled aquifer composed of Holocene and Upper Pleistocene Salausu Formation sand layers; the impermeable layer composed of Quaternary Middle Pleistocene Lishi Formation clay and Neogene Baode Formation clay; the Jurassic Middle Series weathered layer aquifer; the Jurassic Middle Series Anding-Zhiluo Formation aquifer; and the Jurassic Middle Series 2... -2 The Yan'an Formation aquifer above the coal seam; Middle Jurassic Yan'an Formation 2 -2 Coal seam aquifer; 2 -2 The Jurassic Yan'an Formation aquifer below the coal seam; The prediction results in S4 include: a first indicator, a second indicator, a third indicator, and a fourth indicator; The first indicator is the change in groundwater level; the second indicator is the change in groundwater flow velocity; the third indicator is the change in groundwater flow direction; and the fourth indicator is the groundwater pollution risk value. The first preset value is 2.8m. The total warning value corresponding to the prediction result is determined by formula (5); The formula (5) is: Total warning value = w1 * warning value corresponding to the first indicator + w2 * warning value corresponding to the second indicator + w3 * warning value corresponding to the third indicator + w4 * warning value corresponding to the fourth indicator; When the indicator is normal, the corresponding warning value is 0; w1 is the first pre-set weight coefficient; w2 is the second pre-set weight coefficient; w3 is the third pre-set weight coefficient; and w4 is the fourth pre-set weight coefficient.

2. The method according to claim 1, characterized in that, S2 specifically includes: S21. Based on the hydrogeological conceptual model of the designated mining area, the groundwater flow in the designated mining area is determined as a heterogeneous, isotropic, three-dimensional unsteady seepage region. The mathematical model expression for groundwater flow in the designated mining area is as follows: ； Wherein, Ω represents the seepage zone; H represents the aquifer water level elevation; and Z represents the elevation of the bottom plate of the unconfined aquifer. River boundary conditions; Γ3 represents the flow boundary condition for the seepage region; Γ3 represents the zero flow boundary condition for the seepage region; q represents the unit width seepage flow on the flow boundary; H0(x, y, z) represents the initial water level of the aquifer; n represents the normal direction outside the boundary; K represents the aquifer permeability coefficient; W represents the vertical recharge or discharge intensity above the unconfined aquifer surface; μ represents the specific yield of the unconfined aquifer; S s This refers to the unit water release rate of a confined aquifer. S22. Spatial discretization is performed on the specified mining area to obtain a numerical model; The spatial discretization method involves automatically dividing the water-bearing medium in the seepage area using an equal-interval effective difference discretization method. The coordinate axis direction is consistent with the geographic coordinate direction, with the X direction being due east, the Y direction being due north, and the Z direction being vertically upward.

3. The method according to claim 2, characterized in that, S3 specifically includes: The actual observation data of the specified mining area within the specified first time period are determined, the numerical model is identified and verified, and in the process of identification and verification, the groundwater level corresponding to the specified historical time of the specified mining area is used as the initial flow field, and the inflow and outflow boundaries of each source and sink term are input into the corresponding boundary grid in the form of wells. By fitting the flow field near the boundary, the distribution of boundary inflow and outflow is adjusted. The source and sink term processing in the numerical model includes: The atmospheric precipitation infiltration recharge in the numerical model is calculated using formula (1); Wherein, formula (1) is: ； Among them, a i P is the atmospheric precipitation infiltration recharge coefficient for the i-th pre-divided calculation zone within the seepage region. i A represents the precipitation in the pre-defined calculation zone i within the seepage region; i The area of ​​the i-th pre-divided computational zone in the seepage region; The amount of condensate replenishment in the desert area is calculated using formula (2); Formula (2) is as follows: Q 凝 =M 凝 ·F 凝 ·t 凝 ; Where: M 凝 Modulus for condensate supply; F 凝 The area where condensate replenishment occurs; t 凝 This refers to the time when condensate replenishment occurs annually. The amount of agricultural irrigation return water replenishment is calculated using formula (3); The formula (3) is: ； Where, β i G represents the regression replenishment coefficient for irrigation of the i-th type of farmland; i For the gross irrigation quota of the i-th type of farmland; F i Let i be the irrigated area of ​​the i-th type of farmland; In the numerical model, the maximum evaporation depth of a specified mining area is set to a first preset value; The lateral flow rate during the identification and verification period is calculated using Darcy's law based on the hydraulic gradient of the flow field at the flow boundary, the aquifer thickness, and the permeability coefficient at the boundary. The inflow and outflow rates at each boundary are input into the corresponding boundary grid in the form of points using the well flow sub-package. By fitting the flow field near the boundary, the distribution of the inflow and outflow rates at the boundary is appropriately adjusted. The amount of water exchanged between river water and groundwater is calculated using formula (4); Formula (4) is as follows: ； Where K' is the vertical permeability coefficient of the riverbed; M is the thickness of the riverbed sediments; A is the seepage area of ​​the river channel; H r River water level; H ij Groundwater level; C r The leakage intensity of the river; The groundwater extraction volume of the designated mining area is determined as the second pre-set value.

4. The method according to claim 3, characterized in that, S5 specifically includes: For any indicator in the prediction results, if the indicator is within the normal range (a, b) corresponding to that indicator, then the indicator is determined to be normal.

5. The method according to claim 4, characterized in that, S5 specifically includes: If the indicator is outside the normal range (a, b) corresponding to the indicator, and the indicator is not less than b, then the warning value of the indicator is determined to be (the indicator - b) / (ba). If the indicator is outside the normal range (a, b) corresponding to the indicator, and the indicator is not greater than a, then the warning value of the indicator is determined to be (a - the indicator) / (ba). Based on the warning value corresponding to each indicator in the prediction result, the total warning value corresponding to the prediction result is determined, and a warning message is issued when the total warning value exceeds a preset threshold.

6. An evaluation system for the impact of coal seam mining on groundwater flow field, characterized in that, include: At least one processor; as well as At least one memory communicatively connected to the processor, wherein the memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute the evaluation method for the impact of coal seam mining on groundwater flow field as described in any one of claims 1-5.

Images