Roof aquifer water yield property partitioning method, device and equipment and storage medium

Abstract

The invention provides a roof aquifer water yield partitioning method, device and equipment and a storage medium, and belongs to the field of geological research, and the method comprises the steps: determining a plurality of main control factors affecting the water yield of an aquifer, and constructing a thematic map of each main control factor; the subjective weight of each main control factor is calculated by adopting an analytic hierarchy process, the objective weight of each main control factor is calculated by adopting a variable coefficient method, and the comprehensive weight of each main control factor is calculated through a combined weight formula based on the subjective weight and the objective weight; and performing normalization processing on thematic map data of each main control factor, performing weighted stacking on thematic maps of each main control factor after normalization according to a comprehensive weight to generate a water yield property index map, and performing partitioning on the water yield property of the aquifer by adopting a natural discontinuous classification method according to the water yield property index map to obtain a water yield property partitioning map. In this way, the area with the high water yield property can be recognized to provide a scientific basis for drainage design, the area with the low water yield property can be divided to guide arrangement of the mining working face, and resource waste is avoided.

Description

Technical Field

[0001] This invention belongs to the field of geological research, and specifically relates to a method, apparatus, equipment and storage medium for water-bearing zoning of a top aquifer. Background Technology

[0002] In coal mining and other underground engineering operations, assessing the water-bearing capacity of roof aquifers and predicting the risk of water inrush are crucial for ensuring construction safety and production efficiency. Traditionally, understanding roof aquifers has relied primarily on limited data and empirical judgment from the geological exploration phase. This method has significant uncertainties and limitations. Specifically, while geological exploration can provide some stratigraphic information, the sparse distribution of exploration points and limited exploration depth often make it difficult to fully reflect the differences in water-bearing capacity of aquifers in different regions. Furthermore, empirical judgment is easily influenced by subjective factors; different experts may interpret the same geological conditions differently, thus affecting the accuracy and reliability of the prediction results.

[0003] With the development of technology, although some prediction methods based on physical models have emerged, these methods often require a large amount of basic data and complex calculation processes, and are quite sensitive to the model's assumptions. Once the actual conditions do not match the assumptions, the prediction results may deviate significantly. Especially under complex geological conditions, such as areas with well-developed faults and folds, traditional methods are even more inadequate for accurately assessing the water-bearing capacity and the risk of water inrush from aquifers.

[0004] Furthermore, existing technologies often lack systematic quantitative analysis methods when dealing with the combined effects of multiple factors, making it difficult to accurately measure the contribution of each factor to the water-bearing capacity of aquifers, thus affecting the accuracy and practicality of prediction results. Therefore, developing a method that can comprehensively consider multiple geological factors and achieve quantitative evaluation and zonal prediction is of great significance for improving the safety production level of underground engineering projects such as coal mines. Summary of the Invention

[0005] To address the aforementioned problems, this invention provides a method, apparatus, device, and storage medium for classifying the water-bearing properties of a top aquifer.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for zoning the water-bearing capacity of a top aquifer, the method comprising: Several key factors affecting the water-bearing capacity of the roof aquifer were identified, and corresponding thematic maps were constructed based on historical data of each key factor. The subjective weights of each controlling factor are calculated using the analytic hierarchy process (AHP), and the objective weights of each controlling factor are calculated using the coefficient of variation method. Based on the subjective and objective weights, the comprehensive weights of each controlling factor are calculated using a combined weight formula. The thematic map data of each main control factor are normalized. The normalized thematic maps of each main control factor are then spatially weighted and superimposed according to the comprehensive weight to generate a water-bearing index map. Based on the water-bearing index map, the water-bearing capacity of the top aquifer is divided into zones using the natural discontinuity classification method to obtain a water-bearing zone map.

[0007] Optionally, the main controlling factors include sand-to-soil ratio, flushing fluid consumption, core recovery rate, lithological structure index, and aquifer thickness; the thematic maps constructed for each main controlling factor include: The sand-to-land ratio thematic map is drawn based on the ratio of the total sandstone thickness to the total stratum thickness, calculated from borehole lithology data. The thematic map of flushing fluid consumption is drawn based on data on flushing fluid leakage during drilling operations; The core recovery rate thematic map is drawn based on borehole core recovery rate data; The thematic map of lithological structure index is drawn based on the lithological structure index formula, which is: ; in, It is a lithological structure index. The thickness of the coarse sandstone, The thickness is medium sandstone. The thickness of the fine sandstone For the thickness of siltstone, For structural coefficients; The thematic map of aquifer thickness is drawn directly based on aquifer thickness data revealed by boreholes.

[0008] Optionally, the calculation of the subjective weights of each controlling factor using the analytic hierarchy process includes: A hierarchical model is established by taking water abundance as the target layer and the multiple main controlling factors as the criterion layer. Using the 1-9 scale method, the importance of each controlling factor in the criterion layer is compared pairwise to construct a judgment matrix; Calculate the consistency ratio CR of the judgment matrix. If CR < 0.1, the judgment matrix passes the consistency test; otherwise, it is reconstructed. Solve the judgment matrix that passes the test to obtain the subjective weights of each controlling factor.

[0009] Optionally, the calculation of the objective weights of each controlling factor using the coefficient of variation method includes: The coefficient of variation for each controlling factor is calculated using the following formula: ; The coefficients of variation are normalized to obtain the objective weights of each controlling factor, calculated using the following formula: ; in, Let be the coefficient of variation of the i-th controlling factor. Let be the standard deviation of the i-th controlling factor. The average value of the i-th controlling factor. The number of controlling factors.

[0010] Optionally, the calculation of the comprehensive weight of each controlling factor through the combined weight formula includes: ; in, The objective weight of the i-th controlling factor; This is the preference coefficient; denoted as the subjective weight of the i-th controlling factor.

[0011] Optionally, the normalization formula is: ; in, The data is after normalization; The values ​​before normalization; This represents the maximum value of the thematic map data corresponding to the main controlling factor; This represents the minimum value of the thematic map data corresponding to the main controlling factor.

[0012] Optionally, the step of spatially weighting and overlaying the normalized thematic maps of each main controlling factor according to the comprehensive weight to generate a water-rich index map includes: The normalized thematic maps of each controlling factor are converted into raster data layers with the same geographic coordinates and spatial resolution. The cell value of each raster layer is multiplied by its corresponding comprehensive weight. Then, all weighted raster layers are added at the cell level to generate the final water abundance index raster map.

[0013] A top aquifer water-bearing zoning device, the device comprising: The generation module is used to identify multiple key factors affecting the water-bearing capacity of the top aquifer and to construct corresponding thematic maps based on historical data of each key factor. The determination module is used to calculate the subjective weight of each controlling factor using the analytic hierarchy process (AHP), calculate the objective weight of each controlling factor using the coefficient of variation method, and calculate the comprehensive weight of each controlling factor based on the subjective and objective weights using a combined weight formula. The classification module is used to normalize the thematic map data of each main control factor. The normalized thematic maps of each main control factor are then weighted and superimposed according to the comprehensive weight to generate a water-bearing index map. Based on the water-bearing index map, the water-bearing capacity of the top aquifer is divided into zones using the natural discontinuity classification method to obtain a water-bearing zone map.

[0014] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for zoning the water-bearing capacity of a top aquifer.

[0015] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method for zoning the water-bearing properties of a top aquifer.

[0016] The water-bearing capacity zoning method for aquifers in the top plate provided by this invention has the following beneficial effects: This invention constructs a multi-level analytical structure model, combining the analytic hierarchy process (AHP) and the coefficient of variation method, to achieve quantitative evaluation and weight allocation of various geological factors, thus improving the systematicness and scientific rigor of the analysis. By performing weighted overlay calculations on normalized thematic layers of each controlling factor, high-precision water-bearing zoning prediction results are obtained. This method can not only effectively identify areas with strong water-bearing potential, providing a scientific basis for coal mine drainage design, but also accurately delineate areas with weak water-bearing potential, guiding the rational layout of mining faces, avoiding resource waste, and providing strong support for the safe production of underground engineering projects such as coal mines, demonstrating significant economic and social benefits. Attached Figure Description

[0017] To more clearly illustrate the embodiments and design schemes of the present invention, the accompanying drawings required for this embodiment will be briefly described below. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart of a method for zoning the water-bearing capacity of a top aquifer according to an exemplary embodiment of the present invention.

[0019] Figure 2 This is a thematic map of sand and soil ratio provided by the present invention according to an exemplary embodiment.

[0020] Figure 3 This is a diagram illustrating the consumption of flushing fluid according to an exemplary embodiment of the present invention.

[0021] Figure 4 This is a thematic map of core recovery rate provided by the present invention according to an exemplary embodiment.

[0022] Figure 5 This is a thematic map of lithological structure index provided by the present invention according to an exemplary embodiment.

[0023] Figure 6This is a thematic diagram of aquifer thickness provided by the present invention according to an exemplary embodiment.

[0024] Figure 7 This is a hierarchical structure model diagram of the main controlling factors provided by the present invention according to an exemplary embodiment.

[0025] Figure 8 This is a zoning diagram of the water-bearing capacity of a top aquifer according to an exemplary embodiment of the present invention.

[0026] Figure 9 This is a diagram showing the correspondence between inspection holes and water-rich integrated zones according to an exemplary embodiment of the present invention.

[0027] Figure 10 This is a block diagram of a top aquifer water-bearing zoning device provided by the present invention according to an exemplary embodiment. Detailed Implementation

[0028] To enable those skilled in the art to better understand and implement the technical solutions of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention.

[0029] The technical solutions provided by the various embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0030] First, this invention provides a method for zoning the water-bearing capacity of an aquifer in its top plate, specifically as follows: Figure 1 As shown, it includes the following steps: S101. Identify the main controlling factors affecting the water-bearing capacity of the roof aquifer, and construct corresponding thematic maps based on the historical data of each main controlling factor.

[0031] In this step, we first identify several key factors influencing the water-bearing capacity of aquifers. The water-bearing capacity of the top aquifer is influenced by a combination of factors, such as regional tectonics, cumulative sandstone thickness, sandstone lithology, and occurrence conditions. Based on actual drilling and pumping data in the study area and referencing previous research, this paper conducts a comprehensive analysis of the study area. Five key elements were selected as evaluation indicators for the water-bearing capacity of the top aquifer: aquifer thickness, flushing fluid consumption, core recovery rate, lithological structure index, and sand-to-soil ratio. Thematic maps of each key controlling factor were then created.

[0032] The sand-to-stratum ratio is the ratio of the total thickness of sandstone to the total thickness of the formation. Therefore, this sand-to-stratum ratio thematic map is drawn based on the ratio of the total thickness of sandstone to the total thickness of the formation, calculated from borehole lithology data. A higher sand-to-stratum ratio indicates better connectivity between pores, less resistance to groundwater flow, and smoother movement within the pores. This results in higher formation permeability, enabling rapid recharge from external water sources and better circulation of groundwater within a certain range, thus enhancing the formation's water-bearing capacity. This paper uses lithology data from the roof boreholes of 50 previous boreholes in the study area to create the sand-to-stratum ratio thematic map, as shown below. Figure 2 As shown.

[0033] When drilling encounters water-rich strata, a large amount of flushing fluid enters the formation through the pores and fissures of the rock, where it is diluted or carried away by groundwater, resulting in a significant increase in flushing fluid consumption. This indicates that the formation has good permeability and water storage capacity; therefore, this thematic map of flushing fluid consumption is based on flushing fluid loss data during borehole construction. In poorly water-rich strata, the rock has fewer and smaller pores and fissures, making it difficult for flushing fluid to penetrate the formation. Fluid mainly forms a mud cake around the borehole, providing some sealing, thus the flushing fluid consumption is relatively small. This paper collects and statistically analyzes flushing fluid loss data from 50 previous boreholes in the roof of the study area and creates a thematic map of flushing fluid consumption during drilling in the roof strata, as shown below. Figure 3 As shown.

[0034] Poor core integrity and lower recovery rate indicate more fractured rock strata, more developed joints and fissures, better water storage and conductivity, and stronger water-bearing capacity; conversely, a higher integrity indicates better water recovery. Therefore, this core recovery rate thematic map is based on borehole core recovery rate data. This paper statistically analyzes the core recovery rate data of the top plate boreholes in the study area and creates a borehole core recovery rate thematic map, as shown below. Figure 4 As shown.

[0035] Sandstone in aquifers is more water-bearing than mudstone and siltstone, and different grain sizes of sandstone have different effects on the water-bearing capacity of the aquifer. Based on this, the "lithological structure index" is used to characterize the influence of aquifer lithology on its water-bearing capacity; aquifers with higher lithological structure indices have better water-bearing capacity. This paper analyzes lithological data from 50 previous roof boreholes in the study area and creates a thematic map of the lithological structure index, such as... Figure 5 As shown. This thematic map of lithological structure index is drawn based on the lithological structure index formula, which is: ; in, The lithological structure index is m. Thickness of coarse sandstone, in meters. The thickness of the medium sandstone is in meters. The thickness of the fine sandstone is in meters. The thickness of the siltstone is in meters. The structural coefficient is determined according to Table 1.

[0036] Table 1 Structural Coefficient Values

[0037] Aquifer thickness reflects the size of the aquifer's water storage space. Thicker aquifers provide ample space for groundwater storage, enabling them to hold larger amounts of water and possess stronger water-bearing capacity. Larger aquifer thickness is usually accompanied by more pores, fissures, or solution fissures, forming a good water flow channel network, which is conducive to the movement and storage of groundwater within the aquifer, thus increasing its water-bearing capacity. The greater the aquifer thickness, the greater the water content and the better the water-bearing capacity; therefore, this aquifer thickness thematic map is directly based on aquifer thickness data revealed by boreholes. This paper statistically analyzes the aquifer thickness data of the roof of 50 previous boreholes in the study area and draws a thematic map of the roof sandstone aquifer thickness, as shown below. Figure 6 As shown.

[0038] S102. The subjective weight of each controlling factor is calculated using the analytic hierarchy process (AHP), and the objective weight of each controlling factor is calculated using the coefficient of variation method. Based on the subjective and objective weights, the comprehensive weight of each controlling factor is calculated using a combined weight formula.

[0039] In this step, the subjective weights of each controlling factor are first calculated. A hierarchical model is established using water abundance as the target layer and the multiple controlling factors as the criterion layer. A 1-9 scale is used to compare the pairwise importance of each controlling factor in the criterion layer, constructing a judgment matrix. The consistency ratio (CR) of this judgment matrix is ​​calculated. When CR < 0.1, the judgment matrix passes the consistency test; otherwise, it is reconstructed. The judgment matrices that pass the test are solved to obtain the subjective weights of each controlling factor.

[0040] For example, the Analytic Hierarchy Process (AHP) quantifies multi-factor indicators through steps such as building a hierarchical model, constructing a judgment matrix, determining weights, and performing consistency checks, thereby achieving a quantitative evaluation of system objectives.

[0041] Step 1: Establish the AHP hierarchical structure model.

[0042] First, the research objectives are analyzed to determine the hierarchical relationships between various factors, constructing a top-down hierarchical structure. Based on the previously identified key water-bearing factors—aquifer thickness, flushing fluid consumption, core recovery rate, lithological structure index, and sand-to-soil ratio—a hierarchical structure model is comprehensively determined according to the principles and calculation steps of the Analytic Hierarchy Process (AHP). Figure 7 As shown.

[0043] Step 2: Construct the judgment matrix.

[0044] This paper mainly adopts a scoring evaluation method. Through expert experience and comprehensive consideration of various influencing factors, the importance of each main controlling factor affecting the water-bearing capacity of the aquifer is subjectively scored. According to the contribution to water-bearing capacity, the factors are compared in pairs and the level is determined according to their importance. as elements With elements The importance comparison results are as follows: factors i and j are assigned a value of 1 if they are equally important, 3 if they are slightly important, 5 if they are relatively important, 7 if they are very important, and 9 if they are extremely important. The median values ​​of 2, 4, 6, and 8 represent the median values ​​of adjacent judgments. The results are shown in Table 2.

[0045] Table 2. Scaling table for determining matrix elements

[0046] After establishing the judgment matrix, a consistency check is required to determine its logical validity. This can be done by calculating the consistency ratio (CR). Generally, if CR < 0.1, the judgment matrix is ​​considered to have passed the consistency check. The calculation formula is as follows: ; ; ; in, The largest eigenvalue, The number of dimensions, As a consistency indicator, It is a random consistency indicator.

[0047] The calculated consistency ratio of the judgment matrix, CR = 0.0376 < 0.1, indicates that the consistency of the judgment matrix meets the requirements and passes the consistency test. The influence weights of each main control factor on the water-bearing capacity evaluation are shown in Table 3.

[0048] Table 3. Weights of each controlling factor based on the AHP method.

[0049] Next, the objective weights of each controlling factor are calculated. This invention uses the coefficient of variation method to calculate the objective weights of each controlling factor. When assigning weights using the coefficient of variation method, the main focus is on measuring the differences between various observations. This weighting method helps ensure improved accuracy of the analysis, emphasizing variables crucial to decision-making, thus making the weight allocation more reasonable and scientific. The coefficient of variation method is a relatively objective method that can objectively reflect changes in indicator data.

[0050] The coefficient of variation for each controlling factor is calculated using the following formula: ; The coefficient of variation is normalized to obtain the objective weights of each controlling factor. The calculation formula is as follows: ; in, Let be the coefficient of variation of the i-th controlling factor. Let be the historical standard deviation of the i-th controlling factor. The historical average value of the i-th controlling factor. The number of controlling factors.

[0051] The weights of the main controlling factors of the roof water-bearing capacity in the study area were calculated based on the principle and method of the coefficient of variation, as shown in Table 4.

[0052] Table 4. Weights of each controlling factor based on the coefficient of variation method.

[0053] Finally, the weights calculated by the two methods mentioned above are combined to calculate the combined weight of the i-th controlling factor. The formula is: ; in, The objective weight of the i-th controlling factor; This is the preference coefficient; denoted as the subjective weight of the i-th controlling factor.

[0054] Based on the subjective and objective weights calculated using the analytic hierarchy process and the coefficient of variation method, the comprehensive weights of the main controlling factors of water-bearing capacity of the roof in the study area are calculated according to the formula, as shown in Table 5.

[0055] Table 5. Overall weight of each controlling factor

[0056] S103. Normalize the thematic map data of each main control factor, and spatially weight and superimpose the normalized thematic maps of each main control factor according to the comprehensive weight to generate a water-bearing index map. Based on the water-bearing index map, the water-bearing capacity of the aquifer is divided into zones using the natural discontinuity classification method to obtain a water-bearing zone map.

[0057] Because the main control factors have different representations, dimensions, and numerical ranges, they are not conducive to the superposition of various indicators. Therefore, to ensure data comparability and statistical significance, this step first needs to eliminate the influence of different dimensions of the main control factors. Thus, the data for each main control factor are normalized, unifying all data to the (0,1) range for statistical analysis. The specific transformation method is as follows: ; in, The data is after normalization; The values ​​before normalization; This represents the maximum value of the thematic map data corresponding to the main controlling factor; This represents the minimum value of the thematic map data corresponding to the main controlling factor.

[0058] Based on the quantitative characterization of aquifer water-bearing control elements, geographic information system spatial analysis technology is used to perform weighted overlay calculations on normalized thematic layers of each main control factor.

[0059] For example, the normalized thematic maps of each controlling factor are converted into raster data layers with the same geographic coordinates and spatial resolution. The cell value of each raster layer is multiplied by its corresponding comprehensive weight. Then, all weighted raster layers are added at the cell level to generate the final water abundance index raster map.

[0060] For example, the normalized thematic vector layers (such as contour maps or zoning maps) of each controlling factor (such as sand-to-soil ratio, flushing fluid consumption, etc.) are converted into raster data format using the "feature to raster" function or similar tools on the GIS platform. During this process, a unified geographic coordinate system and projected coordinate system must be set for all layers, and the same spatial resolution (i.e., pixel size, e.g., 30m x 30m) must be specified to ensure that the spatial extent and alignment of all raster layers are completely consistent. Next, using the GIS "raster calculator" or "map algebra" tool, a weighted calculation is performed on the comprehensive weight of each controlling factor determined in step (d) (e.g., the comprehensive weight of aquifer thickness is 0.214). Specifically, the normalized raster layer (denoted as Layer_i) of each controlling factor is used as input, and the formula Weighted... i =Layer i *W i Perform the calculation, where W i This step assigns a comprehensive weight to the factor. A weighted raster layer is generated for each factor. Finally, the "raster calculator" is used again to perform cell-level addition on all the weighted raster layers obtained in the previous step. The GIS adds the values ​​of corresponding positions in all weighted layers pixel by pixel, ultimately generating a continuous raster layer where each cell value represents a comprehensive water abundance index—the water abundance index map. Higher values ​​on this map indicate a stronger water abundance potential for that spatial location. Through these steps, quantitative information on multi-source, multi-dimensional controlling factors is comprehensively modeled within a unified spatial framework, providing an accurate data foundation for core zoning prediction.

[0061] Based on this, the natural discontinuity classification method in geostatistics was applied to zon the water-bearing capacity of the roof aquifer. Based on limited previous pumping test data of the roof, and according to the pre-defined grading standards, the study area generally falls between weakly and moderately water-bearing. However, due to the large mining area and significant differences in existing unit yield, a more refined division was made. The water-bearing capacity of the entire mining area was divided into three zones from weakest to strongest: extremely weakly water-bearing (0.00-0.45), weakly water-bearing (0.46-0.65), and moderately water-bearing (0.66-1.00). This resulted in a zoning map of the roof aquifer's water-bearing capacity, as shown below. Figure 8 As shown.

[0062] Depend on Figure 8 It can be seen that the red top sandstone with moderate water-bearing capacity is mainly distributed in the central and western parts of the study area, accounting for about 7.75% of the total area; the orange top sandstone with weak water-bearing capacity is mainly concentrated in the northwest and a small part of the central part of the study area, accounting for 62.50% of the total area; and finally, the green area with extremely weak water-bearing capacity accounts for 29.75% of the total area.

[0063] The magnitude of the unit inflow directly reflects the water-bearing capacity of an aquifer and is the ultimate indicator for verifying the water-bearing strength of an aquifer. Combined with... Figure 9 The measured unit yield and water-bearing zoning results show that boreholes JZB4 and JZB5 have a unit yield greater than 0.1 L / (s·m), placing them in a moderately water-bearing zone; boreholes J1, J2, and X502 have relatively small unit yields, basically corresponding to a very weakly water-bearing zone; the remaining boreholes correspond to a weakly water-bearing zone. Boreholes with large unit yields are generally located in moderately water-bearing areas, while boreholes with smaller unit yields are generally located in weakly water-bearing areas. The comparison of the zoning results in Table 6 indicates that the comprehensive water-bearing zoning results are consistent with the measured unit yield distribution, and the evaluation results are relatively accurate.

[0064] Table 6 Comparison of Water-Abundance Prediction Results

[0065] Using the above method, this invention constructs a multi-level analytical structure model, combining the analytic hierarchy process (AHP) and the coefficient of variation method, to achieve quantitative evaluation and weight allocation of various geological factors, thus improving the systematicness and scientific rigor of the analysis. By performing weighted overlay calculations on normalized thematic layers of each main control factor, high-precision water-bearing zoning prediction results are obtained. This method can not only effectively identify areas with strong water-bearing potential, providing a scientific basis for coal mine drainage design, but also accurately delineate areas with weak water-bearing potential, guiding the rational layout of mining faces, avoiding resource waste, and providing strong support for the safe production of underground engineering projects such as coal mines, demonstrating significant economic and social benefits.

[0066] Secondly, the present invention also provides a top plate aquifer water-bearing zoning device, such as... Figure 10 As shown, it includes: The generation module 201 is used to determine multiple main controlling factors affecting the water-bearing capacity of the top aquifer and to construct corresponding thematic maps based on the historical data of each main controlling factor. The module 202 is used to calculate the subjective weight of each controlling factor using the analytic hierarchy process (AHP), calculate the objective weight of each controlling factor using the coefficient of variation method, and calculate the comprehensive weight of each controlling factor based on the subjective and objective weights using a combined weight formula. The classification module 203 is used to normalize the thematic map data of each main control factor, and then weight and superimpose the thematic maps of each main control factor according to the comprehensive weight to generate a water-bearing index map. Based on the water-bearing index map, the water-bearing capacity of the top aquifer is divided into zones using the natural discontinuity classification method to obtain a water-bearing zone map.

[0067] Using the aforementioned apparatus, this invention constructs a multi-level analytical structure model, combining the analytic hierarchy process (AHP) and the coefficient of variation method (COP), to achieve quantitative evaluation and weight allocation of various geological factors, thereby improving the systematicness and scientific rigor of the analysis. By performing weighted overlay calculations on normalized thematic layers of each controlling factor, high-precision water-bearing zoning prediction results are obtained. This method can not only effectively identify areas with strong water-bearing potential, providing a scientific basis for coal mine drainage design, but also accurately delineate areas with weak water-bearing potential, guiding the rational layout of mining faces, avoiding resource waste, and providing strong support for the safe production of underground engineering projects such as coal mines, demonstrating significant economic and social benefits.

[0068] The present invention also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 The steps of the provided method for zoning the water-bearing capacity of the top aquifer.

[0069] This invention also provides a computer device. At the hardware level, the computer device includes a processor, an internal bus, a network interface, memory, and non-volatile memory, and may also include other hardware required for various operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then executes it to achieve the above-mentioned functions. Figure 1 The steps of the provided method for zoning the water-bearing capacity of the top aquifer.

[0070] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0072] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0073] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0074] It should be noted that the specific embodiments described above enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although the present invention has been described in detail in this specification, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention; and all technical solutions and improvements that do not depart from the spirit and scope of the present invention are covered within the protection scope of the patent of the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for zoning the water-bearing capacity of a top aquifer, characterized in that, The method includes: Several key factors affecting the water-bearing capacity of the roof aquifer were identified, and corresponding thematic maps were constructed based on historical data of each key factor. The subjective weights of each controlling factor are calculated using the analytic hierarchy process (AHP), and the objective weights of each controlling factor are calculated using the coefficient of variation method. Based on the subjective and objective weights, the comprehensive weights of each controlling factor are calculated using a combined weight formula. The thematic map data of each main control factor are normalized. The normalized thematic maps of each main control factor are then spatially weighted and superimposed according to the comprehensive weight to generate a water-bearing index map. Based on the water-bearing index map, the water-bearing capacity of the top aquifer is divided into zones using the natural discontinuity classification method to obtain a water-bearing zone map.

2. The method according to claim 1, characterized in that, The main controlling factors include sand-to-soil ratio, flushing fluid consumption, core recovery rate, lithological structure index, and aquifer thickness; the thematic maps constructed for each main controlling factor include: The sand-to-land ratio thematic map is drawn based on the ratio of the total sandstone thickness to the total stratum thickness, calculated from borehole lithology data. The thematic map of flushing fluid consumption is drawn based on data on flushing fluid leakage during drilling operations; The core recovery rate thematic map is drawn based on borehole core recovery rate data; The thematic map of lithological structure index is drawn based on the lithological structure index formula, which is: ； in, It is the lithological structure index. The thickness of the coarse sandstone, The thickness is medium sandstone. The thickness is fine sandstone. For the thickness of siltstone, For structural coefficients; The thematic map of aquifer thickness is drawn directly based on aquifer thickness data revealed by boreholes.

3. The method according to claim 1, characterized in that, The subjective weights of each controlling factor calculated using the analytic hierarchy process include: A hierarchical model is established by taking water abundance as the target layer and the multiple main controlling factors as the criterion layer. Using the 1-9 scale method, the importance of each controlling factor in the criterion layer is compared pairwise to construct a judgment matrix; Calculate the consistency ratio CR of the judgment matrix. If CR < 0.1, the judgment matrix passes the consistency test; otherwise, it is reconstructed. Solve the judgment matrix that passes the test to obtain the subjective weights of each controlling factor.

4. The method according to claim 1, characterized in that, The objective weights of each controlling factor calculated using the coefficient of variation method include: The coefficient of variation for each controlling factor is calculated using the following formula: ； The coefficients of variation are normalized to obtain the objective weights of each controlling factor, calculated using the following formula: ； in, Let be the coefficient of variation of the i-th controlling factor. Let be the historical standard deviation of the i-th controlling factor. The historical average value of the i-th controlling factor is... The number of controlling factors.

5. The method according to claim 1, characterized in that, The calculation of the comprehensive weight of each controlling factor using the combined weight formula includes: ； in, The objective weight of the i-th controlling factor; This is the preference coefficient; denoted as the subjective weight of the i-th controlling factor.

6. The method according to claim 1, characterized in that, The formula for the normalization process is: ； in, The data is after normalization; The value before normalization; This represents the maximum value of the thematic map data corresponding to the main controlling factor; This represents the minimum value of the thematic map data corresponding to the main controlling factor.

7. The method according to claim 1, characterized in that, The step of spatially weighting and superimposing the normalized thematic maps of each main controlling factor according to the comprehensive weight to generate a water-rich index map includes: The normalized thematic maps of each controlling factor are converted into raster data layers with the same geographic coordinates and spatial resolution. The cell value of each raster layer is multiplied by its corresponding comprehensive weight. Then, all weighted raster layers are added at the cell level to generate the final water abundance index raster map.

8. A top aquifer water-bearing zoning device, characterized in that, The device includes: The generation module is used to identify multiple key factors affecting the water-bearing capacity of the top aquifer and to construct corresponding thematic maps based on historical data of each key factor. The determination module is used to calculate the subjective weight of each controlling factor using the analytic hierarchy process (AHP), calculate the objective weight of each controlling factor using the coefficient of variation method, and calculate the comprehensive weight of each controlling factor based on the subjective and objective weights using a combined weight formula. The classification module is used to normalize the thematic map data of each main control factor. The normalized thematic maps of each main control factor are spatially weighted and superimposed according to the comprehensive weight to generate a water-bearing index map. Based on the water-bearing index map, the water-bearing capacity of the top aquifer is divided into zones using the natural discontinuity classification method to obtain a water-bearing zone map.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 7.

10. A computer device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in any one of claims 1 to 7.

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