A method and system for analyzing mining strategies of underground water source well groups

Abstract

The present invention discloses a method and system for analyzing mining strategies of underground water source well groups, belonging to the field of smart water technology; the method and system are used to solve the technical problems of poor flexibility in mining supervision and poor reliability of autonomous management of different mining wells in underground water source well groups in existing solutions; periodic mining data monitoring, statistics and processing are implemented for the mining of different mining wells in underground water source well groups to obtain corresponding mining node monitoring sequences, which can realize periodic monitoring and data statistics of the mining of different mining wells; the mining node monitoring sequences corresponding to different mining nodes of different mining wells are processed to obtain the corresponding node monitoring influence and analyze them, which can periodically determine the local monitoring influence status corresponding to the mining nodes of the mining wells and adaptively perform local mining control and supervision adjustment, thereby improving the flexibility of mining supervision of different mining wells and the reliability of autonomous management.

Description

Technical Field

[0001] The present invention relates to the field of smart water technology, and in particular to a method and system for analyzing exploitation strategies of a group of wells in a groundwater source. Background Art

[0002] The exploitation strategy for groundwater source well groups needs to comprehensively consider multiple factors such as hydrogeological conditions, environmental protection, socio-economic needs, and sustainable development. The exploitation strategy includes scientific planning and layout, stratified exploitation, rotational exploitation and recuperation, dynamic monitoring and management, environmental protection and ecological water replenishment, etc.

[0003] During the implementation process of the existing groundwater source well group mining strategy analysis plan, it is impossible to implement periodic supervision and analysis of the mining of different mining wells in the groundwater source well group, and to adaptively and dynamically adjust the subsequent supervision and mining of different mining wells according to the analysis results, resulting in poor flexibility in the mining supervision of different mining wells in the groundwater source well group and poor reliability of autonomous management. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for analyzing the exploitation strategy of a groundwater source well group, so as to solve the technical problems of poor flexibility in the supervision of exploitation of different exploited wells in a groundwater source well group and poor reliability of autonomous management in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for analyzing the exploitation strategy of a well group in a groundwater source area, comprising:

[0007] Through the preset basic monitoring cycle, basic periodic mining node monitoring statistics are implemented for the mining of underground water source well groups, and different mining node monitoring data of different mining wells in the well group are processed separately and integrated to obtain the mining node monitoring sequence of the mining wells;

[0008] The data of the mining node monitoring sequence is calculated to obtain the corresponding node monitoring influence, and the local monitoring influence state corresponding to the mining node of the mining well is determined according to the monitoring instruction influence, and the implementation of the subsequent mining nodes of the mining well is optimized and controlled according to the local monitoring influence state;

[0009] Integrate the node monitoring influence of the same mining nodes of different mining wells and analyze to obtain the overall monitoring influence status corresponding to adjacent mining nodes, and optimize the overall mining control of the subsequent implementation of the overall mining of the well group in the groundwater source area according to the overall monitoring influence status;

[0010] Among them, when integrating the node monitoring influences obtained by processing different mining water wells at the same mining node, the evaluation sequence corresponding to the adjacent mining water wells at the same mining node is obtained;

[0011] Perform traversal statistics on the evaluation sequence. If the values ​​of the elements in the evaluation sequence are all 0, then associate the adjacent mining wells with the overall mining impact mark N1;

[0012] If the values ​​of the elements in the evaluation sequence are not all 0, the adjacent production wells are associated with the overall production impact identifier N2; N1 and N2 are the total number of elements with values ​​of 0 in the evaluation sequence;

[0013] The above integrated analysis is further repeated for the node monitoring impact between the production water wells at different adjacent production distances, and the production water wells are grouped and classified according to the same overall impact identifier. According to the classification results, the same production control plan is implemented for the subsequent production of the same type of production water wells.

[0014] Preferably, the exploitation wells at different locations in the well group of the groundwater source in the same area are numbered and marked, and the corresponding exploitation start time points are obtained according to the number monitoring of the exploitation wells;

[0015] According to the mining time points corresponding to different mining wells, the preset monitoring indicators of different mining nodes are monitored and counted in turn, and the different monitoring indicator data of the monitoring statistics are associated with the numbers of the mining wells to which they belong and sorted and combined in sequence to obtain the mining node monitoring sequence corresponding to the mining wells.

[0016] Preferably, the monitoring indicators include several water quality monitoring items, water well extraction depth and water depth.

[0017] Preferably, when calculating the data of the mining node monitoring sequence corresponding to different mining nodes of different mining wells, the data of several water quality monitoring items in the mining node monitoring sequence are compared and screened with the corresponding standard monitoring range in turn, and the water quality monitoring items that do not belong to the label monitoring range are counted and marked as abnormal monitoring items; the abnormal impact value corresponding to the abnormal monitoring item is obtained and marked as Yi, i = 1, 2, 3, ..., n; n is a positive integer; i is a different abnormal monitoring item, and n is the total number of abnormal monitoring items;

[0018] And, the water well mining depth Hc and water depth Hs in the mining node monitoring sequence are obtained, and the node monitoring influence degree η corresponding to the mining node of the corresponding mining well is calculated.

[0019] Preferably, the calculation formula of the node monitoring influence η is: Where exp() is an exponential function with the natural constant e as the base, and B is the standard mining threshold corresponding to the mining node.

[0020] Preferably, when performing data analysis on the node monitoring influence, the node monitoring influence is input into a node monitoring influence identification model for data analysis and outputting a corresponding node monitoring influence identifier;

[0021] The node monitoring impact flag includes a value of 0, 1, or 2, which respectively indicates that the corresponding local monitoring impact state is normal, the local monitoring impact state is slightly abnormal, or the local monitoring impact state is severely abnormal.

[0022] Preferably, the local monitoring influence state of the exploitation water well at the corresponding exploitation node is generated and prompted according to the node monitoring influence identifier, and the node monitoring influence identifiers corresponding to different exploitation nodes of the exploitation water well are sorted and combined to obtain a node monitoring influence sequence;

[0023] In addition, a corresponding first-level mining control plan or a second-level mining control plan is generated according to the node monitoring impact identifier with a value of 1 or 2, and the basic monitoring period is adjusted to the first-level monitoring period or the second-level monitoring period according to the node monitoring impact identifier with a value of 1 or 2 to implement first-level periodic or second-level periodic mining node monitoring statistics for the subsequent mining of groundwater source well groups.

[0024] Preferably, the expression of the node monitoring impact identification model is: Where Y1 and Y2 are the minimum and maximum node monitoring impact thresholds.

[0025] Preferably, the difference between the node monitoring influences of adjacent production water wells corresponding to the same production node is calculated and marked as an evaluation difference; all evaluation differences of adjacent production water wells corresponding to different production nodes are sorted and combined to obtain an evaluation sequence.

[0026] The present invention also discloses a mining strategy analysis system for underground water source well groups, comprising:

[0027] The mining node monitoring data processing module is used to implement basic periodic mining node monitoring statistics for the mining of the underground water source well group through a preset basic monitoring period, and to process the different mining node monitoring data of different mining wells in the well group respectively and integrate them to obtain the mining node monitoring sequence of the mining wells to which they belong;

[0028] The mining node monitoring data analysis and control module is used to calculate the data of the mining node monitoring sequence to obtain the corresponding node monitoring influence, and determine the local monitoring influence state corresponding to the mining node of the mining well according to the monitoring instruction influence, and perform local mining optimization control on the implementation of subsequent mining nodes of the mining well according to the local monitoring influence state;

[0029] The mining node monitoring data integration and control module is used to integrate the node monitoring influence of the same mining node of different mining wells and analyze and obtain the overall monitoring influence status corresponding to adjacent mining nodes, and carry out overall mining optimization control on the subsequent implementation of the overall mining of the groundwater source well group according to the overall monitoring influence status.

[0030] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0031] The present invention implements periodic mining data monitoring, statistics and processing on the mining of different mining wells in the groundwater source well group to obtain a corresponding mining node monitoring sequence, which can not only realize the periodic monitoring and data statistics of the mining of different mining wells, but also provide reliable monitoring data support for the subsequent mining status analysis corresponding to different mining wells and the subsequent mining management and control.

[0032] The present invention processes the mining node monitoring sequences corresponding to different mining nodes of different mining water wells to obtain the corresponding node monitoring influence and analyze it, so as to periodically determine the local monitoring influence status corresponding to the mining nodes of the mining water wells and adaptively perform local mining control and supervision adjustment, thereby improving the flexibility of mining supervision of different mining water wells and the reliability of autonomous management. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The present invention will be further described below in conjunction with the accompanying drawings.

[0034] Figure 1 The present invention is a flowchart of a method for analyzing the exploitation strategy of a groundwater source well group.

[0035] Figure 2 This is a module block diagram of a groundwater source well group mining strategy analysis system of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary operation and maintenance personnel in this field without creative work are within the scope of protection of the present invention.

[0037] Example 1: Figure 1 As shown, the present invention is a method for analyzing the exploitation strategy of a well group in a groundwater source area, comprising:

[0038] The basic periodic mining node monitoring and statistics of the mining of the underground water source well group are implemented through the preset basic monitoring cycle. The unit of the basic monitoring cycle is hours. The specific value can be flexibly set according to the local regulations, the purpose of the well and the risk factors that may affect the water quality. The mining node is determined after the water is mined from the mining well, and the monitoring data of different mining nodes of different mining wells in the well group are processed separately and integrated to obtain the mining node monitoring sequence of the mining wells to which they belong; including:

[0039] The water wells in different locations of the well group of groundwater sources in the same area are numbered and marked, and the corresponding mining start time points are obtained according to the number monitoring of the mining wells. The unit of the mining start time point is accurate to the hour;

[0040] According to the mining time points corresponding to different mining wells, monitoring statistics are performed according to the preset monitoring indicators of different mining nodes in turn, and the different monitoring indicator data of the monitoring statistics are associated with the numbers of the mining wells to which they belong and are sorted and combined in turn to obtain the mining node monitoring sequence corresponding to the mining wells;

[0041] Among them, the monitoring indicators include several water quality monitoring items, well extraction depth and water depth;

[0042] Specifically, water quality monitoring items include, but are not limited to, pH, hardness, alkalinity, total dissolved solids, heavy metals, and organic matter;

[0043] In the embodiment of the present invention, by implementing periodic mining data monitoring, statistics and processing on the mining of different mining wells in the well group of the groundwater source, a corresponding mining node monitoring sequence is obtained, which can not only realize the periodic monitoring and data statistics of the mining of different mining wells, but also provide reliable monitoring data support for the subsequent mining status analysis corresponding to different mining wells and the subsequent mining control;

[0044] The data of the mining node monitoring sequence is calculated to obtain the corresponding node monitoring influence, and the local monitoring influence state corresponding to the mining node of the mining well is determined according to the monitoring instruction influence, and the implementation of the subsequent mining nodes of the mining well is optimized and controlled according to the local monitoring influence state; including:

[0045] When calculating the data of the mining node monitoring sequence corresponding to different mining nodes of different mining wells, the data of several water quality monitoring items in the mining node monitoring sequence are compared and screened with the corresponding standard monitoring range in turn. The standard monitoring range is determined according to the existing standard requirement data range of the corresponding water quality monitoring item. The water quality monitoring items that do not belong to the label monitoring range are counted and marked as abnormal monitoring items; the abnormal impact value corresponding to the abnormal monitoring item is obtained and marked as Yi, i = 1, 2, 3, ..., n; n is a positive integer; i is a different abnormal monitoring item, and n is the total number of abnormal monitoring items;

[0046] The steps for obtaining the abnormal impact value include:

[0047] The abnormal monitoring item is searched and matched with the abnormal monitoring item impact table, and the abnormal impact value associated with the sample monitoring item that is the same as the abnormal monitoring item in the abnormal monitoring item impact table is obtained. The abnormal monitoring item impact table pre-stores a number of different sample monitoring items and their associated abnormal impact values. Different sample monitoring items are pre-set and associated with a corresponding abnormal impact value. The abnormal impact value is used to digitally represent the abnormal impact corresponding to the sample monitoring item. The specific value of the abnormal impact value can be determined by the staff in this field according to the actual mining requirement data and work experience;

[0048] The abnormal impact value can not only digitally represent the abnormal impact of the abnormal monitoring item, but also provide reliable digital data support for the subsequent integrated calculation of different abnormal monitoring items;

[0049] And, obtain the water well mining depth Hc and water depth Hs in the mining node monitoring sequence, and use the formula Calculate the node monitoring influence η of the corresponding mining well at the mining node; where exp() is an exponential function with the natural constant e as the base, B is the standard mining threshold corresponding to the mining node, and the standard mining threshold can be determined based on the minimum or median value of all node monitoring influences corresponding to the historical mining wells, or determined according to actual mining requirement data;

[0050] It should be explained that the node monitoring influence is a numerical value used to digitally represent the impact of mining abnormalities on the corresponding mining nodes of the mining wells; the greater the node monitoring influence, the greater the corresponding mining abnormality impact;

[0051] When performing data analysis on the node monitoring influence, the node monitoring influence is input into the node monitoring influence identification model for data analysis and outputs the corresponding node monitoring influence identifier. The node monitoring influence identification model is established based on the isolation forest algorithm and combined with the minimum node monitoring influence threshold and the maximum node monitoring influence threshold;

[0052] Among them, the expression of the node monitoring impact identification model is: Wherein, Y1 and Y2 are the minimum value of the node monitoring influence threshold and the maximum value of the node monitoring influence threshold; the minimum value of the node monitoring influence threshold and the maximum value of the node monitoring influence threshold can be determined based on the median and mean values ​​of all the node monitoring influences corresponding to the historical mining wells of the mining construction party;

[0053] The node monitoring impact flag includes a value of 0, 1, or 2, which respectively indicates that the corresponding local monitoring impact state is normal, the local monitoring impact state is slightly abnormal, or the local monitoring impact state is severely abnormal;

[0054] It should be noted that by processing the node monitoring influence degree to obtain the corresponding node monitoring influence identifier, it is possible to digitally represent the local monitoring influence status of the exploited water well at the corresponding exploitation node, and provide reliable specific monitoring processing data support for the subsequent exploitation control of the exploited water well, thereby improving the diversity of corresponding monitoring data processing and utilization of the exploited water well at different exploitation nodes;

[0055] According to the node monitoring impact identifier, the local monitoring impact status of the exploited water well at the corresponding exploitation node is generated and prompted. At the same time, the node monitoring impact identifiers corresponding to different exploitation nodes of the exploited water well are sorted and combined to obtain the node monitoring impact sequence; the node monitoring impact sequence can provide reliable local monitoring data support for the subsequent integration and classification of different exploited water wells;

[0056] And, according to the node monitoring impact identifier with a value of 1 or 2, a corresponding primary exploitation control plan or a secondary exploitation control plan is generated respectively, and according to the node monitoring impact identifier with a value of 1 or 2, the basic monitoring period is adjusted to the primary monitoring period or the secondary monitoring period respectively to implement primary periodic or secondary periodic exploitation node monitoring statistics for the subsequent exploitation of the well group in the groundwater source area;

[0057] Among them, the comprehensiveness and strictness of the first-level mining control plan are lower than those of the second-level mining control plan; comprehensiveness refers to the total number of indicators of mining control. The more indicators are controlled, the better the corresponding comprehensiveness; strictness refers to the strictness of the control of the corresponding indicators of mining control. The stricter the indicator control, the better the corresponding strictness; mining control includes but is not limited to pollution source investigation and elimination, maintenance and repair of well structure, physical treatment, and chemical treatment;

[0058] In addition, the duration of the first-level monitoring cycle is shorter than that of the basic monitoring cycle, and the duration of the first-level monitoring cycle is shorter than that of the second-level monitoring cycle; adjusting the first-level monitoring cycle or the second-level monitoring cycle realizes the flexible and adaptive adjustment of the monitoring cycle, so as to implement targeted supervision and analysis of the exploited water wells with different abnormal influences;

[0059] In the embodiment of the present invention, the mining node monitoring sequences corresponding to different mining nodes of different mining water wells are processed to obtain the corresponding node monitoring influence and analyze it, so that the local monitoring influence status corresponding to the mining nodes of the mining water wells can be periodically determined and local mining control and supervision adjustments can be adaptively performed, thereby improving the flexibility of mining supervision of different mining water wells and the reliability of autonomous management.

[0060] Integrate the node monitoring influence of the same mining nodes of different mining wells and analyze to obtain the overall monitoring influence status corresponding to adjacent mining nodes, and optimize the overall mining control of the subsequent implementation of the overall mining of the well group in the groundwater source area according to the overall monitoring influence status; including:

[0061] When integrating the node monitoring influences obtained from different mining wells at the same mining node, the difference between the node monitoring influences corresponding to the same mining node of adjacent mining wells is calculated and marked as the evaluation difference; all the evaluation differences corresponding to the adjacent mining wells at different mining nodes are sorted and combined to obtain an evaluation sequence;

[0062] Perform traversal statistics on the evaluation sequence. If the values ​​of the elements in the evaluation sequence are all 0, generate a mining impact consistency instruction and associate the adjacent mining wells with the mining overall impact identifier N1;

[0063] If the values ​​of the elements in the evaluation sequence are not all 0, an inconsistent mining impact instruction is generated and the adjacent mining wells are associated with the overall mining impact identifier N2; N1 and N2 are the total number of elements with values ​​of 0 in the evaluation sequence respectively;

[0064] The above integrated analysis is further repeated for the node monitoring impact between the production water wells at different adjacent production distances, and the production water wells are grouped and classified according to the same overall impact identifier. The same production control plan is implemented for the subsequent production of the same type of production water wells based on the classification results.

[0065] Different from the existing technical solutions, which implement independent mining monitoring and analysis for different mining wells in the well group of the groundwater source, the correlation between different mining wells is not processed and analyzed, resulting in data islands between the mining wells affected by the same mining water source, which in turn affects the overall supervision effect of the mining of different mining wells in the well group of the groundwater source;

[0066] In the implementation of the present invention, by integrating the node monitoring influence degrees of the same mining nodes of different mining wells and analyzing to obtain the overall monitoring influence status corresponding to the adjacent mining nodes and the corresponding overall mining influence identification, the same mining control plan can be implemented for the subsequent mining of the same type of mining wells according to the overall mining impact identification, breaking the data islands between the mining wells affected by the same mining water source, and improving the overall supervision effect of the mining of different mining wells in the groundwater source well group.

[0067] Example 2: Figure 2 As shown, the present invention is a mining strategy analysis system for underground water source well groups, comprising:

[0068] The mining node monitoring data processing module is used to implement basic periodic mining node monitoring statistics for the mining of the underground water source well group through a preset basic monitoring period, and to process the different mining node monitoring data of different mining wells in the well group respectively and integrate them to obtain the mining node monitoring sequence of the mining wells to which they belong;

[0069] The mining node monitoring data analysis and control module is used to calculate the data of the mining node monitoring sequence to obtain the corresponding node monitoring influence, and determine the local monitoring influence state corresponding to the mining node of the mining well according to the monitoring instruction influence, and perform local mining optimization control on the implementation of subsequent mining nodes of the mining well according to the local monitoring influence state;

[0070] The mining node monitoring data integration and control module is used to integrate the node monitoring influence of the same mining node of different mining wells and analyze and obtain the overall monitoring influence status corresponding to adjacent mining nodes, and carry out overall mining optimization control on the subsequent implementation of the overall mining of the groundwater source well group according to the overall monitoring influence status.

[0071] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0072] In the several embodiments provided by the present invention, it should be understood that the disclosed system and method can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0073] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0075] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the basic features of the present invention.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary operation and maintenance personnel in the field should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for analyzing the exploitation strategy of a well group in a groundwater source area, characterized in that: include: Through the preset basic monitoring cycle, basic periodic mining node monitoring statistics are implemented for the mining of underground water source well groups, and different mining node monitoring data of different mining wells in the well group are processed separately and integrated to obtain the mining node monitoring sequence of the mining wells; The data of the mining node monitoring sequence is calculated to obtain the corresponding node monitoring influence, and the local monitoring influence state corresponding to the mining node of the mining well is determined according to the node monitoring influence, and the implementation of the subsequent mining nodes of the mining well is optimized and controlled according to the local monitoring influence state; Among them, when calculating the data of the mining node monitoring sequence corresponding to different mining nodes of different mining water wells, the data of several water quality monitoring items in the mining node monitoring sequence are compared and screened with the corresponding standard monitoring range in turn, and the water quality monitoring items that do not belong to the standard monitoring range are counted and marked as abnormal monitoring items; the abnormal impact value corresponding to the abnormal monitoring item is obtained and marked as Yi, i=1, 2, 3, ..., n; n is a positive integer; i is a different abnormal monitoring item, and n is the total number of abnormal monitoring items; And, the water well mining depth Hc and water depth Hs in the mining node monitoring sequence are obtained, and the node monitoring influence η corresponding to the corresponding mining well at the mining node is calculated; the calculation formula of the node monitoring influence η is: ; In the formula, exp() is an exponential function with the natural constant e as the base, and B is the standard mining threshold corresponding to the mining node; When performing data analysis on the node monitoring influence, the node monitoring influence is input into the node monitoring influence identification model for data analysis and outputs the corresponding node monitoring influence identifier; the expression of the node monitoring influence identification model is: ; In the formula, Y1 and Y2 are the minimum and maximum values ​​of the node monitoring impact threshold; The node monitoring impact flag includes a value of 0, 1, or 2, which respectively indicates that the corresponding local monitoring impact state is normal, the local monitoring impact state is slightly abnormal, or the local monitoring impact state is severely abnormal; Integrate the node monitoring influence of the same mining nodes of different mining wells and analyze to obtain the overall monitoring influence status corresponding to adjacent mining nodes, and optimize the overall mining control of the subsequent implementation of the overall mining of the well group in the groundwater source area according to the overall monitoring influence status; Among them, when integrating the node monitoring influences obtained by processing different mining water wells at the same mining node, the difference between the node monitoring influences corresponding to the same mining node of adjacent mining water wells is calculated and marked as the evaluation difference; all the evaluation differences corresponding to the adjacent mining water wells at different mining nodes are sorted and combined to obtain the evaluation sequence; Perform traversal statistics on the evaluation sequence. If the values ​​of the elements in the evaluation sequence are all 0, then associate the adjacent mining wells with the overall mining impact mark N1; If the values ​​of the elements in the evaluation sequence are not all 0, the adjacent production wells are associated with the overall production impact identifier N2; N1 and N2 are the total number of elements with values ​​of 0 in the evaluation sequence; The above integrated analysis is further repeated for the node monitoring impact between the production water wells at different adjacent production distances, and the production water wells are grouped and classified according to the same overall impact identifier. The same production control plan is implemented for the subsequent production of the same type of production water wells based on the classification results.

2. The method for analyzing the exploitation strategy of a groundwater source well group according to claim 1, characterized in that: Number and mark the water wells at different locations in the well group of groundwater source in the same area, and obtain the corresponding start time of mining according to the number of the water wells; According to the mining time points corresponding to different mining wells, the preset monitoring indicators of different mining nodes are monitored and counted in turn, and the different monitoring indicator data of the monitoring statistics are associated with the numbers of the mining wells to which they belong and sorted and combined in sequence to obtain the mining node monitoring sequence corresponding to the mining wells.

3. The method for analyzing the exploitation strategy of a groundwater source well group according to claim 2, characterized in that: The monitoring indicators include several water quality monitoring items, well extraction depth and water depth.

4. The method for analyzing the exploitation strategy of a groundwater source well group according to claim 1, characterized in that: According to the node monitoring influence identifier, the local monitoring influence state of the mining well at the corresponding mining node is generated and prompted, and at the same time, the node monitoring influence identifiers corresponding to different mining nodes of the mining well are sorted and combined to obtain the node monitoring influence sequence; In addition, a corresponding first-level mining control plan or a second-level mining control plan is generated according to the node monitoring impact identifier with a value of 1 or 2, and the basic monitoring period is adjusted to the first-level monitoring period or the second-level monitoring period according to the node monitoring impact identifier with a value of 1 or 2 to implement first-level periodic or second-level periodic mining node monitoring statistics for the subsequent mining of groundwater source well groups.

5. A system for analyzing the exploitation strategy of a well group in a groundwater source area, using the method for analyzing the exploitation strategy of a well group in a groundwater source area as claimed in any one of claims 1 to 4, characterized in that: include: The mining node monitoring data processing module is used to implement basic periodic mining node monitoring statistics for the mining of the underground water source well group through a preset basic monitoring period, and to process the different mining node monitoring data of different mining wells in the well group respectively and integrate them to obtain the mining node monitoring sequence of the mining wells to which they belong; The mining node monitoring data analysis and control module is used to calculate the data of the mining node monitoring sequence to obtain the corresponding node monitoring influence, and determine the local monitoring influence state corresponding to the mining node of the mining well according to the node monitoring influence, and perform local mining optimization control on the implementation of subsequent mining nodes of the mining well according to the local monitoring influence state; The mining node monitoring data integration and control module is used to integrate the node monitoring influence of the same mining node of different mining wells and analyze and obtain the overall monitoring influence status corresponding to adjacent mining nodes, and carry out overall mining optimization control on the subsequent implementation of the overall mining of the groundwater source well group according to the overall monitoring influence status.

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