A method and system for evaluating the suitability of a water intake well for recharge based on multi-dimensional detection and a comprehensive index model

Abstract

The present application relates to the technical field of water resources management, in particular to a kind of water well recharge suitability assessment method and system based on multidimensional detection and comprehensive index model, comprising the following steps: screening geological data to construct initial screening qualified water well set, scanning well shaft to identify damage and corrosion to obtain structural integrity data, carrying out ladder pressure test to analyze aquifer receiving capacity, analyzing water chemistry and suspended solids to assess plugging risk, combining environmental sensitivity to calculate weighted sum, dividing recommended category and establishing recharge suitability assessment list.In the present application, deep damage and corrosion conditions are identified by scanning water well wall and filter pipe throughout the section, deformation parts are accurately positioned to quantify structural integrity, water level response is monitored by using ladder pressure recharge test, aquifer permeability is calculated by inversion and real unit recharge is obtained, to ensure that screened well site has pressure-bearing structure stability and water quality chemical compatibility, effectively prolongs the service life of recharge project and protects groundwater ecological safety.

Description

Technical Field

[0001] This invention relates to the field of water resources management technology, and in particular to a method and system for assessing the suitability of water intake wells for reinjection based on a multi-dimensional detection and comprehensive index model. Background Technology

[0002] The field of water resource management technology involves the organization and supervision of the entire process of regional water resource development, utilization, conservation, protection, and optimal allocation. It mainly covers groundwater over-extraction management, artificial recharge project layout, water conservancy facility construction and maintenance, and hydrogeological environment monitoring and evaluation. The aim is to achieve groundwater extraction and recharge balance and curb geological problems such as land subsidence through scientific methods. Traditional methods for assessing the suitability of wells for recharge refer to agricultural or industrial wells undergoing transformation. These methods rely solely on the original well construction records to review well depth, pipe materials, and geological information, or on visual inspections of the wellhead appearance and the condition of supporting equipment by technical personnel. Some assessments obtain water output data through routine pumping tests and directly infer recharge capacity from this. Furthermore, in terms of water quality, they mainly test whether basic physicochemical indicators meet discharge standards, lacking dedicated in-situ testing and multi-factor coupled analysis methods for the actual blockage of downhole filter pipes, the integrity of the well wall structure, and the chemical compatibility of recharge water with the aquifer medium.

[0003] Current technologies rely solely on static archives and surface visual inspections to assess well conditions, neglecting the corrosion and deformation of underground pipes over time. Directly inferring reinjection capacity from pumping test data fails to reflect the unique hydraulic response under injection conditions, leading to biased assessments of acceptance potential. Merely testing basic physicochemical indicators cannot reveal the geochemical compatibility between reinjection water and the native medium. The lack of in-situ structural diagnosis and blockage risk analysis results in the blind selection of unsuitable well locations, easily causing irreversible blockage of aquifers, damage to well wall structure due to pressurized reinjection, and groundwater pollution caused by incompatible water chemical reactions. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention provides a method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model, comprising the following steps: S1: Obtain the well location coordinates, well construction date, and basic stratigraphic lithology data of the water intake wells in the area to be evaluated; compare the well location coordinates with the boundaries of geological disaster-prone areas and the impact range of pollution sources; delineate safe areas; and establish a preliminary set of qualified water intake wells. S2: Call the set of qualified water intake wells in the initial screening, scan the entire section of the water intake well wall and filter pipe, identify the location of the water intake well wall damage, the proportion of filter pipe blockage and corrosion status, measure the change of well diameter, locate the deformed parts, and obtain the structural integrity data of the water intake well. S3: Based on the structural integrity data of the water intake well, conduct a stepped pressurization reinjection test and gradually increase the reinjection pressure. Monitor the dynamic water level and reinjection flow rate data under the stable state of the steps, calculate the ratio of reinjection flow rate to water level rise, determine the unit reinjection volume, and obtain the quantitative index of the aquifer's reinjection acceptance capacity. S4: Based on the quantitative index of the aquifer recharge capacity associated with the water intake well location, collect recharge water source and groundwater samples for full water chemical analysis, calculate the Langerier saturation index and the Rezner stability index, detect the suspended solids concentration and particle size distribution in the recharge water, and obtain water quality blockage risk assessment index.

[0005] As a further aspect of the present invention, the set of qualified water intake wells includes basic attribute information of the water intake well location, safety area positioning data, and target aquifer type identification. The structural integrity status data of the water intake well includes the coordinates of the well wall damage points, filter pipe blockage and corrosion parameters, well radial deformation, and channel unobstructedness judgment value. The quantitative indicators of aquifer reinjection acceptance capacity include unit reinjection volume, permeability parameters, and water conduction capacity parameters. The water quality blockage risk assessment indicators include the Langerier saturation index, the Rezner stability index, the predicted value of calcium carbonate scaling trend, and suspended solids concentration and particle size parameters.

[0006] As a further aspect of the present invention, the specific steps of S1 are as follows: S101: Obtain the well location coordinates, well completion dates, and basic stratigraphic lithology data of the water intake wells in the area to be evaluated; call the boundary vector data of the geological hazard-prone area and the pollution source diffusion impact range layer; perform spatial overlay operation between the well location coordinates and the boundary vector data and layer of the geological hazard-prone area; identify the risky well locations falling within the boundary or range; delete the risky well locations and extract the remaining well location coordinates located in non-sensitive areas; map and bind the filtered coordinates with the well completion dates and basic stratigraphic lithology data to generate a basic well location data table for safe areas; S102: For the basic well location data table of the safety area, index the corresponding well maintenance record document, parse the operation and maintenance log and status description field in the document, compare whether there are operation records about well wall cracking, structural collapse or abandoned well sealing, perform logical negative filtering, remove record items with damage records or abandoned records, retain water intake well location information with normal operation and maintenance characteristics, and serialize and arrange the filtered water intake well location information to obtain the index set of candidate water intake well locations in good condition; S103: Based on the stratigraphic lithology data associated with the water intake index set of the candidate well locations in good condition, analyze the hydrogeological structural characteristics of the mining layer corresponding to the water intake well location, determine whether the mining layer is a phreatic aquifer closely connected with surface water or a confined aquifer with vertical permeability on the top plate, screen well locations that meet the openness or cross-flow recharge characteristics, and establish a preliminary set of qualified water intake wells.

[0007] As a further aspect of the present invention, the specific steps of S2 are as follows: S201: Call the set of qualified water intake wells in the initial screening, collect optical images or acoustic amplitude data of the entire section of the water intake well wall and filter pipe, perform image segmentation operation, extract the edge feature coordinates of cracks and perforations in the water intake well wall, count the pixel grayscale differences in the opening area of ​​the filter pipe and calculate the mesh blockage area ratio, quantify the degree of corrosion and erosion according to the roughness texture and reflectivity characteristics of the inner surface of the pipe wall, and vectorize and catalog the identified damage location points, blockage ratio and corrosion level parameters to generate a set of surface disease parameters for the well wall and filter pipe; S202: For the well section covered by the apparent defect parameter set of the well wall and filter pipe, perform continuous scanning measurement along the well axis to obtain the measured radial distance data array of the inner wall of the well. Perform the difference calculation between the measured data and the inner diameter reference value of the well design, screen the abnormal measurement points whose absolute value of radial deviation exceeds the preset deformation judgment threshold, locate the layer depth where plastic deformation occurs, and obtain the quantitative record of radial geometric deformation of the well. S203: Based on the radial geometric deformation quantification record of the well shaft, perform a water level excitation response test on the water intake well, collect discrete data points of the water level rise in the well over time after pumping stops, fit the water level recovery curve and calculate the water level rise slope per unit time, analyze the fluid exchange resistance coefficient of the well shaft and aquifer interface and determine the channel unobstructed level, call the apparent defect parameter set of the well wall and filter pipe, perform attribute association and weighted aggregation of defect parameters, deformation records and unobstructed level data, and obtain the structural integrity status data of the water intake well.

[0008] As a further aspect of the present invention, the specific steps of S3 are as follows: S301: Based on the structural integrity data of the water intake well, identify the pressure bearing limit of the well wall and set the starting pressure and pressurization step size of the stepped reinjection test. Control the reinjection pump to perform graded pressurized water injection operation. Continuously monitor the pressure fluctuation in the well under each pressure step until the variance is lower than the preset stability threshold. Simultaneously collect the bottom dynamic water level elevation and real-time reinjection flow data under the steady state stage, record the hydraulic element response sequence under pressure conditions, and generate a stepped steady-state hydraulic monitoring record. S302: Call the stepped steady-state hydraulic monitoring record, analyze the average flow rate and absolute water level under the stepped steady state, introduce the static water level data before the test to perform difference calculation to obtain the water level rise, perform the quotient calculation of reinjection flow rate and water level rise, construct a scatter plot of the relationship between flow rate and water level rise and identify the linear response interval, calculate the average ratio within the linear response interval, determine the parameter characterizing the water injection capacity of a single well per unit head, and obtain the unit reinjection volume efficiency characteristic value; S303: Perform hydrodynamic parameter inversion calculation on the time-varying data of flow and water level in the stepped steady-state hydraulic monitoring record, fit the solution that minimizes the deviation between the measured data points and the theoretical seepage equation, analyze the permeability coefficient and radial water conduction capacity parameters of the aquifer pore medium, perform numerical normalization and multi-dimensional attribute weighted aggregation on the radial water conduction capacity and the unit reinjection volume efficiency characteristic value, quantify the aquifer's capacity to accommodate reinjection fluid, and obtain a quantitative index of the aquifer's reinjection acceptance capacity.

[0009] As a further aspect of the present invention, in the process of determining the well pressure fluctuation until the variance is lower than the preset stability threshold, the preset stability threshold is limited to the fact that the statistical variance calculated from the well pressure monitoring data within the continuous sampling time window is not greater than the predetermined pressure allowable fluctuation limit, and the continuous sampling time window is a fixed duration and covers at least one complete pressure maintenance cycle. The starting pressure of the stepped reinjection test is limited to a safety margin ratio lower than the wellbore pressure limit, and the pressure increment step is limited to a constant pressure increment between adjacent pressure steps. The identification of the linear response interval is limited to a continuous data segment in the scatter plot of the relationship between flow rate and water level rise, which satisfies the monotonic correspondence between flow rate and water level rise and the correlation dispersion does not exceed a predetermined discrimination limit. The calculation of the ratio mean is limited to the arithmetic average of the quotient of the reinjection flow rate and the water level rise rate corresponding to the pressure condition within the linear response interval. The numerical normalization process is defined as mapping the radial water conduction capacity and the unit reinjection volume efficiency characteristic value to a unified dimensionless interval, and then performing multi-dimensional attribute weighted aggregation according to a preset weight coefficient.

[0010] As a further aspect of the present invention, the specific steps of S4 are as follows: S401: For the water intake well locations that are associated with the quantitative index of the aquifer recharge capacity, collect corresponding recharge water source and groundwater samples, perform full water chemical ion analysis, and measure pH value, calcium and magnesium ion concentration, alkalinity and total dissolved solids parameters. Substitute the measured data into the calculation formulas of Langerier saturation index and Rezsner stability index to perform numerical calculations, compare the calculation results with the calcium carbonate precipitation equilibrium benchmark value, determine the chemical scaling tendency of water quality in mixed environment, and generate calcium carbonate scaling trend prediction analysis value. S402: Call the calcium carbonate scaling trend prediction analysis value, extract the reinjection water source sample and perform laser particle size scanning and suspended solids gravimetric method test, measure the mass concentration value of insoluble solid particles in the fluid, count the distribution frequency of particle size in the differentiated micron range, draw the cumulative particle size distribution curve and extract the median particle size and maximum particle size characteristic parameters, quantify the physical transport resistance characteristics of exogenous particles in the porous medium of the aquifer, and obtain the suspended solids concentration and particle size distribution characteristic set; S403: Call the suspended solids concentration and particle size distribution feature set, perform dimensionless data processing to avoid parameter magnitude differences, perform multidimensional attribute weighted aggregation of chemical scaling index and physical blockage feature parameters, calculate the probability density or risk score of aquifer pore blockage caused by water quality factors, quantify the potential negative impact of reinjection water quality on formation permeability, and obtain water quality blockage risk assessment index.

[0011] As a further aspect of the present invention, the method further includes step S5: S5: Based on the water quality blockage risk assessment index, obtain the environmentally sensitive data of the water source protection area and ecological red line in the area where the water intake well is located, determine the weight ratio of the structural integrity status data of the water intake well and the quantitative index of the aquifer recharge acceptance capacity, calculate the weighted sum of the assessment items and compare it with the suitability grading standard range, divide the recommended categories of water intake wells, and establish a water intake well recharge suitability grading assessment list. The list of suitable water intake wells for reinjection includes environmental sensitivity level, weighted total score of assessment items, suitability classification results, and recommended utilization category.

[0012] As a further aspect of the present invention, the specific steps of S5 are as follows: S501: For the area to be evaluated, retrieve the delineated scope of the water source protection zone and the ecological red line vector layer, project the coordinates of the water intake wells onto the layer for spatial topology analysis, identify the positional relationship between the wells and the environmentally sensitive areas, quantify the environmental constraint level, and combine the risk rating of the water quality blockage risk assessment indicators to formulate a differentiated weighting strategy for the quantitative indicators of the structural integrity status data of the water intake wells and the aquifer recharge acceptance capacity, and generate a multi-dimensional assessment indicator weight allocation matrix. S502: Call the multidimensional evaluation index weight allocation matrix, combine the structural integrity parameter in the water intake well structure integrity status data, the hydraulic acceptance parameter in the aquifer recharge acceptance capacity quantitative index, and the blockage risk parameter in the water quality blockage risk assessment index, perform range transformation operation to map heterogeneous data to a unified numerical range, perform multiplication and linear accumulation operation of parameter normalization value and corresponding weight coefficient, calculate the quantitative score characterizing the matching degree of recharge project, and obtain the recharge suitability weighted index; S503: Project the weighted index of reinjection suitability onto the preset suitability grading standard interval model, perform numerical comparison, determine the preferred reinjection, restricted reinjection, or prohibited reinjection level of the water intake well, configure recommended category labels for the water intake well location based on the determination results, aggregate well location attribute information, original values ​​of key technical indicators and grading conclusions, serialize and encapsulate the data according to suitability priority, and establish a water intake well reinjection suitability grading evaluation list.

[0013] A suitability assessment system for water intake well reinjection based on a multi-dimensional detection and comprehensive index model includes: The well location screening module obtains the well location coordinates, well construction date and basic stratigraphic lithology data of the water intake wells in the area to be evaluated, compares them with the disaster pollution boundary to delineate the safe zone, eliminates maintenance records and damage records, screens open or confined aquifers, and establishes a set of qualified water intake wells in the initial screening. The structural integrity detection module scans the set of qualified water intake wells in the initial screening to identify damage and blockage, fits the well diameter to locate deformation, analyzes the water level recovery slope, and generates structural integrity status data of the water intake well. The hydraulic bearing capacity inversion module uses the data on the structural integrity of the intake well to perform step-by-step reinjection, collects steady-state water level and flow rate, calculates the ratio to determine the unit reinjection volume, and uses the Theis model to analyze permeability and hydraulic conductivity to generate a quantitative index of the aquifer's reinjection capacity. The water quality blockage assessment module collects water samples associated with the quantitative index of the aquifer recharge acceptance capacity, calculates the Langerier and Rezna indexes to predict scaling, detects the concentration and particle size of suspended solids, and generates water quality blockage risk assessment indicators. The suitability grading assessment module acquires environmentally sensitive data, determines the structural integrity status data of the water intake well, the quantitative index of the aquifer reinjection acceptance capacity, and the weight of the water quality blockage risk assessment index, calculates the sum, and establishes a water intake well reinjection suitability grading assessment list.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, the deep damage and corrosion of the well wall and filter pipe are identified by scanning the entire section, and the deformed parts are accurately located to quantify the structural integrity. A stepped pressurization recharge test is used to monitor the water level response, the aquifer permeability is calculated by inversion and the actual unit recharge volume is obtained, and the scaling trend is predicted by combining water chemical analysis and saturation index calculation. The risk of suspended solids blockage is assessed from the perspective of micro-particle size distribution. A multi-dimensional suitability classification system is constructed by comprehensively considering environmental sensitivity data to ensure that the selected well sites have the stability of the pressure-bearing structure and the chemical compatibility of the water quality, effectively extending the life of the recharge project and ensuring the ecological safety of groundwater. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0016] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0019] Please see Figure 1 This invention provides a method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model, comprising the following steps: S1: Obtain the well location coordinates, well completion date, and basic stratigraphic lithology data of the water intake wells in the area to be evaluated; compare the well location coordinates with the boundaries of geological disaster-prone areas and the impact range of pollution sources; delineate safe areas; review well maintenance records; delete water intake wells with damage records or that have been abandoned; screen well locations in open aquifers or confined aquifers with cross-flow recharge conditions; and establish a preliminary set of qualified water intake wells. S2: Call the set of qualified water intake wells in the initial screening, scan the entire section of the water intake well wall and filter pipe, identify the location of water intake well wall damage, the proportion of filter pipe blockage and corrosion, measure the change of well diameter, locate the deformed parts, analyze the shape of the water level recovery curve, determine the unobstructedness of the well channel, and obtain the structural integrity data of the water intake well. S3: Based on the structural integrity data of the intake well, conduct a stepped pressurization reinjection test and gradually increase the reinjection pressure. Monitor the dynamic water level and reinjection flow rate data under the stable state of the steps, calculate the ratio of reinjection flow rate to water level rise, determine the unit reinjection volume, invert the flow rate and water level data obtained from the monitoring, analyze the aquifer permeability and water conduction capacity parameters, and obtain quantitative indicators of the aquifer's reinjection acceptance capacity. S4: Based on the quantitative index of aquifer recharge capacity, water intake well locations are associated with the recharge water source and groundwater samples for full water chemical analysis. The Langerier saturation index and Rezner stability index are calculated to predict the calcium carbonate scaling trend. The concentration and particle size distribution of suspended solids in the recharge water are detected to obtain water quality blockage risk assessment index. S5: Based on the water quality blockage risk assessment index, obtain the environmentally sensitive data of the water source protection area and ecological red line in the area where the water intake well is located, determine the weight ratio of the water intake well body structural integrity status data and the quantitative index of aquifer recharge acceptance capacity, calculate the weighted sum of the assessment items and compare it with the suitability classification standard range, classify the recommended categories of water intake wells, and establish a water intake well recharge suitability classification assessment list. The initial screening of qualified water intake wells includes basic attribute information of the well location, safety zone location data, target aquifer type identification, and well structure integrity data, including coordinates of well wall damage points, filter pipe blockage and corrosion parameters, well radial deformation, and channel unobstructedness judgment value. Quantitative indicators of aquifer reinjection capacity include unit reinjection volume, permeability parameters, and water conductivity parameters. Water quality blockage risk assessment indicators include Langerier saturation index, Rezner stability index, calcium carbonate scaling trend prediction value, suspended solids concentration and particle size parameters. The water intake well reinjection suitability classification assessment list includes environmental sensitivity level, weighted total score of assessment items, suitability classification results, and recommended utilization category.

[0020] Please see Figure 2 The specific steps of S1 are as follows: S101: Obtain the well location coordinates, well completion dates, and basic stratigraphic lithology data of the water intake wells in the area to be evaluated; call the boundary vector data of the geological hazard-prone area and the pollution source diffusion impact range layer; perform spatial overlay operation between the well location coordinates and the boundary vector data and layer of the geological hazard-prone area; identify the risky well locations falling within the boundary or range; delete the risky well locations and extract the remaining well location coordinates located in non-sensitive areas; map and bind the filtered coordinates with the well completion dates and basic stratigraphic lithology data to generate a basic well location data table for safe areas; Using high-precision GPS positioning equipment or retrieving digital mining rights archives, the three-dimensional coordinate data of water wells in the area to be evaluated are obtained, including longitude, latitude, and wellhead elevation. Simultaneously, the well completion date record and borehole stratigraphic lithology columnar section data for each well are extracted from the geological bureau database. The geographic information processing environment is initialized, and the latest boundary vector data of geologically hazardous areas in the region is loaded. This data is stored in polygon shapefile format and covers high-risk areas for landslides, debris flows, and ground subsidence. A layer depicting the diffusion and impact range of industrial pollution sources is also loaded. This layer is based on the concentration contour envelope generated by a groundwater solute transport model. This process employs a ray casting algorithm or R-tree spatial indexing technology to map the coordinates of each water well to the aforementioned vector layer. In the spatial coordinate system, risks are identified by calculating the geometric inclusion relationship between points and polygons. This process calculates the shortest Euclidean distance from the well location coordinates to the boundary of the polygon in the geological hazard-prone area. If the point is located inside the polygon or the distance from the boundary is less than the preset safety buffer threshold, the well location is marked as a high-risk object. This process performs a deletion operation, removing the well locations marked as high-risk from the candidate list and retaining only the remaining well location coordinates located in non-sensitive areas. This process performs a data fusion operation, using the unique well number as the primary key, and connects and binds the filtered well location coordinates with the previously acquired well formation age and stratigraphic lithology data to a relational database to construct a comprehensive data view containing spatial and geological attributes, generating a structured basic well location data table for safe areas. In this process, the setting of the safety buffer threshold is based on the "Geological Hazard Risk Assessment Specification" and the actual site stability requirements. The process selects the sum of the geological hazard influence radius and the maximum possible sliding distance as the benchmark. For example, for landslide-prone areas, the safety buffer threshold is set at 300 meters beyond the leading edge of the landslide body. In the actual calculation example, the coordinates of a certain water intake well are (…). , The coordinates of the nearest point on the boundary of the geological disaster area are ( , This process calculates the Euclidean distance between two points, which involves adding the squares of the differences in the x-coordinates and y-coordinates and then taking the square root. The calculation process is as follows: Rice; due to Meters are smaller than the set value The safety buffer threshold is determined by the logic, which indicates that the well location is within the risk buffer zone. Therefore, the well location is removed from the safety zone basic well location data table. The advantage of the screening logic is that, through strict spatial geometric constraints, it avoids the risk of engineering failure caused by unstable surface environment from the source, and ensures that the remaining well locations have the external physical environment foundation for long-term operation.

[0021] S102: For the basic well location data table of the safety area, index the corresponding well maintenance record document, parse the operation and maintenance log and status description field in the document, compare whether there are operation records about well wall cracking, structural collapse or abandoned well sealing, perform logical negative filtering, remove record items with damage records or abandoned records, retain water intake well location information with normal operation and maintenance characteristics, serialize and arrange the filtered water intake well location information to obtain the index set of candidate water intake well locations in good condition; The process iterates through each well location index number in the table, and retrieves the corresponding full lifecycle well maintenance record document through the enterprise resource planning or document management interface. This process initiates a natural language processing flow to parse the unstructured text in the document, especially the operation and maintenance logs and status description fields. This process uses keyword matching technology based on regular expressions and semantic analysis algorithms to build a lexicon containing negative feature words such as "well wall rupture", "collapse", "sand inrush", "well sealing", and "abandonment". This process scans the log text line by line. Once a feature word or synonym variant in the lexicon is identified, a logical negation mechanism is triggered. Specifically, if there is a clear "abandoned" mark in the log or a record describing structural damage appears consecutively, the record item is marked as invalid. This process performs a filtering operation to completely remove record items carrying damaged records or abandonment tags, retaining only the water intake well location information with clean records and continuous normal operation and maintenance characteristics. This process serializes and arranges the selected compliant well location information, reorganizes the data structure according to administrative division or well number order, and generates a set of candidate water intake well locations in good condition.

[0022] S103: Based on the stratigraphic and lithological data associated with the water intake index set of candidate well locations in good condition, analyze the hydrogeological structural characteristics of the extraction layer corresponding to the water intake well location, determine whether the extraction layer is a phreatic aquifer closely connected with surface water or a confined aquifer with vertical permeability on the top plate, screen well locations that meet the openness or cross-flow recharge characteristics, and establish a preliminary set of qualified water intake wells. The process involves retrieving detailed stratigraphic and lithological data for each well, focusing on analyzing the hydrogeological structure characteristics of the extraction layer. This process analyzes the rock particle size distribution, sorting, and cementation degree in the lithological columnar section, combined with regional hydrogeological profiles, to determine whether the extraction layer is a phreatic or confined aquifer. For phreatic aquifers, the process checks the connectivity between the static water level depth and surface water. For confined aquifers, the process focuses on verifying the permeability coefficient of the overlying lithology to determine whether they have the conditions for cross-flow recharge. The process executes a screening logic, retaining well locations identified as having close hydrological connections with phreatic aquifers or confined aquifers with certain vertical permeability in the overlying strata that can receive cross-flow recharge from the overlying strata. These characteristics indicate that the aquifer has good openness and regeneration capacity, making it suitable for reinjection operations. The process then encapsulates well locations that meet the above hydrogeological conditions to establish a preliminary set of qualified water extraction wells. This judgment process involves determining the vertical permeability of the roof. This process sets a benchmark value for the permeability coefficient. Based on the aquifer overflow recharge theory, the vertical permeability coefficient of a weakly permeable layer must be greater than a certain order of magnitude to have effective recharge significance. Therefore, this process sets a threshold value for the vertical permeability coefficient. Meters / day. In a practical example, through a variable head permeability test on a clay sample from the top of a confined aquifer at a certain well location in the laboratory, the vertical permeability coefficient was measured to be [value missing]. Meters / day, this process will change the measured value meters / day and judgment threshold Comparing the values ​​in meters per day, because Logical judgment confirms that the roof has the ability to overflow and replenish water. Combined with the geological fact that the well location is in a pressure zone, the process determines that it meets the characteristics of overflow and replenish water and includes it in the initial screening of qualified water intake wells. This step, through quantitative hydrogeological parameter constraints, eliminates well locations in closed deep stagnant areas and dead water areas with extremely slow water circulation, ensuring the hydraulic absorption potential of subsequent reinjection projects.

[0023] Please see Figure 3 The specific steps of S2 are as follows: S201: Call the set of qualified water intake wells in the initial screening, collect optical images or acoustic amplitude data of the entire section of the water intake well wall and filter pipe, perform image segmentation operation, extract the edge feature coordinates of cracks and perforations in the water intake well wall, count the pixel grayscale differences in the opening area of ​​the filter pipe and calculate the mesh blockage area ratio, quantify the degree of corrosion and erosion based on the roughness texture and reflectivity characteristics of the inner surface of the pipe wall, and vectorize and catalog the identified damage location points, blockage ratio and corrosion level parameters to generate a set of surface disease parameters for the well wall and filter pipe; A downhole robot equipped with a high-definition panoramic camera and an ultrasonic scanning probe is lowered into the well to collect high-resolution data from the well wall and the entire filter pipe. For the acquired optical image data, image segmentation is performed using a U-Net convolutional neural network model based on deep learning. This model includes encoder and decoder paths. The encoder consists of four repeating convolutional blocks, each containing two... Convolutional layers, ReLU activation function, and a The max pooling layer is used to extract deep features of the image. The decoder part also contains four blocks, which gradually restore the spatial size of the feature map through deconvolution operation and splice it with the corresponding feature map of the encoder by skip connection to accurately identify crack and perforation areas. This process extracts the edge feature coordinates of the diseased area and calculates its distribution density on the well wall unfolded map. At the same time, for the filter pipe area, this process counts the pixel grayscale difference of the opening area, identifies the mesh covered by chemical precipitates or biofilms, and calculates the mesh blockage area ratio, that is, the total number of blocked mesh pixels divided by the total number of designed mesh pixels. In addition, this process uses acoustic wave amplitude data to analyze the energy attenuation and scattering characteristics of reflected waves, quantifies the roughness texture of the inner surface of the pipe wall, and combines the reflectivity characteristics to invert the degree of corrosion and erosion, which is divided into three levels: mild, moderate and severe, generating a set of surface disease parameters for the well wall and filter pipe.

[0024] S202: For the well section covered by the apparent defect parameter set of the well wall and filter pipe, perform continuous scanning measurement along the well axis to obtain the measured radial distance data array of the inner wall of the well. Perform the difference calculation between the measured data and the inner diameter benchmark value of the well design, screen the abnormal measurement points whose absolute value of radial deviation exceeds the preset deformation judgment threshold, locate the layer depth where plastic deformation occurs, and obtain the quantitative record of radial geometric deformation of the well. The downhole scanning equipment is controlled to perform continuous spiral scanning measurement along the well axis. This process involves high-frequency emission of laser or acoustic pulses to acquire a massive array of measured radial distance data from the inner wall of the wellbore, constructing a three-dimensional point cloud model of the wellbore. The process then retrieves the well completion design drawings to obtain the design inner diameter reference value. The process performs a difference calculation, subtracting the measured radial distance of each measuring point from the design radius to obtain the radial deviation value. This process filters out abnormal measuring points whose absolute radial deviation value exceeds a preset deformation judgment threshold. The deformation judgment threshold is set to 5% of the design radius or according to the casing anti-crushing strength specification. This process uses cluster analysis to combine consecutive abnormal measuring points, locates the specific layer depth where diameter contraction (plastic deformation leading to indentation) or diameter expansion (fracture leading to collapse), and calculates the deformation volume by integration to obtain a quantitative record of the radial geometric deformation of the wellbore.

[0025] S203: Based on the quantitative record of radial geometric deformation of the well shaft, perform a water level excitation response test on the water intake well, collect discrete data points of water level rise over time after pumping stops, fit the water level recovery curve and calculate the water level rise slope per unit time, analyze the fluid exchange resistance coefficient of the interface between the well shaft and the aquifer and determine the channel unobstructed level, call the apparent defect parameter set of the well wall and filter pipe, perform attribute association and weighted aggregation of defect parameters, deformation records and unobstructed level data, and obtain the structural integrity status data of the water intake well. A water level-induced response test is performed on the intake well. This process involves starting the pumping equipment to significantly lower the water level in the well, stopping the pumping, and using a high-frequency pressure sensor to collect discrete data points of the water level naturally recovering over time. This process uses the least squares method to fit the discrete points into a water level recovery curve and calculates the slope of the water level recovery per unit time in the initial recovery phase. According to hydraulic principles, this slope directly reflects the connectivity between the well shaft and the aquifer interface. This process analyzes the deviation between this slope and the theoretical standard recovery curve, calculates the fluid exchange resistance coefficient, and determines the channel unobstructed level (e.g., unobstructed, weakly blocked, strongly blocked). This process calls the set of apparent defects parameters of the well wall and filter pipe generated in step S201, and performs attribute association between the defect parameters identified by image recognition, the deformation records of geometric scanning, and the unobstructed level data of hydraulic testing. This process uses a weighted aggregation algorithm to assign corresponding weight coefficients to different types of defects, calculates a value that comprehensively reflects the health status of the well shaft, and obtains the structural integrity status data of the intake well. Table 1 lists the measured data and intermediate calculation results obtained in the above steps for a certain water intake well to be evaluated, which serve as the basis for the structural integrity assessment. Table 1: Example Table of Well Structure Integrity Inspection Data

[0026] As shown in Table 1, the physical state of the well site can be quantified through the aggregation of multi-dimensional detection data, for example... Congestion rate and radial deviation in millimeters (design radius) millimeters for millimeters, therefore (If the millimeter exceeds the threshold, it indicates that the well has obvious signs of aging and should be reduced in subsequent reinjection assessments.)

[0027] Please see Figure 4 The specific steps of S3 are as follows: S301: Based on the structural integrity data of the intake well, identify the pressure bearing limit of the well wall and set the starting pressure and pressurization step size of the stepped reinjection test. Control the reinjection pump to perform graded pressurized water injection operation. Continuously monitor the pressure fluctuation in the well under each pressure step until the variance is lower than the preset stability threshold. Simultaneously collect the bottom dynamic water level elevation and real-time reinjection flow data under the steady state stage, record the hydraulic element response sequence under pressure conditions, and generate a stepped steady-state hydraulic monitoring record. The pressure limit of the well wall is identified, and the starting pressure and pressurization step size of the stepped reinjection test are set based on this upper limit. The process controls the variable frequency reinjection pump to perform staged pressurization water injection. Starting from the starting pressure, the water injection pressure is increased step by step. At each pressure step, the process continuously monitors the pressure fluctuation data fed back by the pressure sensor in the well and calculates the pressure variance within the sliding time window in real time. When the pressure variance is lower than the preset stability threshold, it is determined that the current step has reached steady state. At this time, the process simultaneously collects the bottom water level elevation and real-time reinjection flow data under the steady state stage, records the hydraulic element response sequence under the pressure condition, and enters the next pressure step until the maximum set pressure is reached or the water level reaches the wellhead, generating a stepped steady-state hydraulic monitoring record. During the pressure stability determination process, a pressure variance stability threshold is set. This threshold is determined based on the sensor accuracy and the pressure transmission characteristics of the aquifer, and is set to a value of [value missing]. kPa square ( In a practical example, the sequence of five pressure readings over a continuous 10-minute period under a certain pressure gradient is as follows: kilopascals (kPa) are used to calculate the average of the sequence, which is the sum of the values ​​divided by the number of data points. kPa, this process calculates the square of the difference between each data point and the mean, sums them, and divides by the number of data points minus one (sample variance formula), as follows: ; This process will calculate the resulting variance. With stability threshold Comparison, because The logic determines that the current pressure state has reached a high level of stability, and then triggers a data lock command to record the current flow and water level data.

[0028] S302: Call the step steady-state hydraulic monitoring records, analyze the average flow rate and absolute water level under steady state of the steps, introduce the static water level data before the test to perform difference calculation to obtain the water level rise, perform the quotient calculation of reinjection flow rate and water level rise, construct a scatter plot of the relationship between flow rate and water level rise and identify the linear response interval, calculate the ratio mean within the linear response interval, determine the parameter characterizing the water injection capacity of a single well per unit head, and obtain the characteristic value of unit reinjection volume efficiency; The process involves analyzing the mean flow rate and absolute water level elevation under steady-state conditions for each stage. This process incorporates static water level data from before the experiment, performing a difference operation (subtracting the static water level elevation from the steady-state elevation) to obtain the water level rise. A division operation is then performed to calculate the quotient of the reinjection flow rate and the water level rise, which represents the unit water absorption rate. A scatter plot is constructed with the water level rise as the x-axis and the reinjection flow rate as the y-axis. Linear regression analysis identifies the linear response intervals in the scatter plot, representing the reinjection capacity under laminar flow conditions. The process calculates the mean ratio of data points within these linear response intervals to determine the parameters characterizing the injection capacity per unit head of a single well, thus obtaining the characteristic value of the unit reinjection efficiency.

[0029] S303: Perform hydrodynamic parameter inversion calculations on the time-varying data of flow and water level in the stepped steady-state hydraulic monitoring records, fit the solution that minimizes the deviation between the measured data points and the theoretical seepage equation, analyze the permeability coefficient and radial water conduction capacity parameters of the aquifer pore medium, perform numerical normalization and multi-dimensional attribute weighted aggregation on the radial water conduction capacity and the unit reinjection volume efficiency characteristic value, quantify the aquifer's capacity to accommodate reinjection fluid, and obtain quantitative indicators of the aquifer's reinjection acceptance capacity. The process involves performing hydrodynamic parameter inversion calculations. This process constructs a theoretical model based on the Theis unsteady flow equation or the Hantush overflow equation. The objective function is defined as the sum of squares of the differences between the measured drawdown and the theoretically calculated drawdown. This process employs the Levenberg-Marquardt optimization algorithm to iteratively adjust the hydraulic conductivity in the model. ) and water storage coefficient ( The process continues until the objective function value converges to a minimum. The optimal solution after convergence is extracted, which is to analyze the permeability coefficient and radial water conduction capacity parameters of the aquifer pore medium. Finally, the radial water conduction capacity and the aforementioned unit reinjection volume efficiency characteristic value are numerically normalized to eliminate the influence of dimensions. Multidimensional attribute weighted aggregation is performed according to preset weights to quantify the macroscopic carrying potential of the aquifer for reinjection fluid and obtain the quantitative index of the aquifer reinjection acceptance capacity. In this inversion and aggregation process, the specific logic for normalization and weighting is defined, assuming that the radial conductivity obtained from the inversion is... The characteristic value of unit recharge efficiency is This process obtains the maximum values ​​of these two parameters for wells within the region. and and minimum value and This process performs Min-Max normalization calculations; for example, for water conductance, the calculation... Obtain normalized value Similarly, we can obtain This process sets weighting coefficients, for example, the weight of water conductivity is 1. The unit recharge efficiency weight is In actual calculations, after normalization, a certain well... , This process performs a weighted summation operation, that is... This value (Or mapped to 74 points) is the quantitative index of the aquifer recharge acceptance capacity of this well. This index combines theoretical permeability and actual engineering water injection performance. The closer the value is to 1, the stronger the acceptance capacity. Experiments show that, compared with the single permeability coefficient method, the prediction accuracy of the recharge volume using this dual-parameter coupled evaluation method is improved by approximately [percentage missing]. .

[0030] Please see Figure 5 The specific steps of S4 are as follows: S401: For water intake wells that are associated with quantitative indicators of aquifer recharge capacity, collect corresponding recharge water sources and groundwater samples, perform full water chemical ion analysis, and measure pH value, calcium and magnesium ion concentration, alkalinity and total dissolved solids parameters. Substitute the measured data into the calculation formulas of Langerier saturation index and Rezsner stability index to perform numerical calculations, compare the calculation results with the calcium carbonate precipitation equilibrium benchmark value, determine the chemical scaling tendency of water quality in mixed environment, and generate calcium carbonate scaling trend prediction analysis value; Water samples intended for recharge and original groundwater samples from wells were collected. This process utilized ion chromatography and inductively coupled plasma mass spectrometry to perform total water chemical ion analysis, accurately determining pH, calcium ion concentration, magnesium ion concentration, and total alkalinity (as shown in the original text). The process involves measuring the total dissolved solids (TDS) and the water temperature of the sample. The measured data are then fed into the calculation logic for the Langerier Saturation Index (LSI) and the Rezner Stability Index (RSI). First, the intermediate parameter pHs (the saturated pH value of calcium carbonate) is calculated. This calculation involves summing the temperature coefficient, TDS correction factor, calcium hardness factor, and alkalinity factor. The process then calculates the LSI (measured pH value minus pHs) and the RSI (twice the pHs minus the measured pH value). The results are compared with the calcium carbonate precipitation equilibrium baseline (LSI=0, RSI=6) to determine the chemical scaling tendency of the water in the mixed environment. If the LSI is significantly greater than 0 and the RSI is less than 6, it is considered to have a strong scaling tendency, generating a calcium carbonate scaling trend prediction analysis value. Table 2: Water Quality Chemical Analysis and Scaling Risk Prediction Table

[0031] As shown in Table 2, by substituting the measured data such as pH and calcium ions into the logical operation, the LSI is obtained. Since LSI is positive ( The study clearly indicated that the water quality had a tendency to precipitate calcium carbonate in the underground environment, which provided a chemical basis for subsequent blockage risk assessment.

[0032] S402: Call the calcium carbonate scaling trend prediction analysis value, extract the reinjection water source sample and perform laser particle size scanning and suspended solids gravimetric method test, measure the mass concentration value of insoluble solid particles in the fluid, count the distribution frequency of particle size in the differentiated micron range, draw the cumulative particle size distribution curve and extract the median particle size and maximum particle size characteristic parameters, quantify the physical transport resistance characteristics of exogenous particles in the porous medium of the aquifer, and obtain the suspended solids concentration and particle size distribution characteristic set; Physical impurity analysis was performed on samples of the reinjected water source. This process involved scanning with a laser particle size analyzer combined with suspended solids gravimetric analysis. Water samples are filtered through a micron-sized filter membrane, dried, and weighed. The total dissolved solids (TSS) concentration in the fluid is measured. Simultaneously, a laser particle size analyzer analyzes the diffraction patterns of the particles on the laser beam to statistically analyze particle sizes within the differentiated micron-level range (e.g., ...). The distribution frequency of the particle size was determined, and the cumulative distribution curve of the particle size was plotted. The median particle size was then extracted. ) and maximum particle size ( Based on the principle of porous media filtration, when the particle size is greater than 1 / 3 of the pore throat diameter, bridging and clogging are likely to occur. This process combines the average pore size data of the aquifer to quantify the physical transport resistance characteristics of exogenous particulate matter in the porous media of the aquifer, and obtain the characteristic set of suspended solids concentration and particle size distribution.

[0033] S403: Call the suspended solids concentration and particle size distribution feature set, perform dimensionless data processing, avoid parameter magnitude differences, perform multidimensional attribute weighted aggregation of chemical scaling index and physical blockage feature parameters, calculate the probability density or risk score of aquifer pore blockage caused by water quality factors, quantify the potential negative impact of reinjection water quality on formation permeability, and obtain water quality blockage risk assessment indicators. Perform dimensionless processing on the data to avoid the correlation between concentration (mg / L) and particle size (mg / L). The process takes into account the magnitude difference between the aforementioned chemical indices (dimensionless) and uses a scoring mapping method. For example, TSS concentration is mapped to a 0-10 blockage potential score, and LSI index is mapped to a 0-10 scaling potential score. The process performs multi-dimensional attribute weighted aggregation of the chemical scaling index mapping score and the physical blockage characteristic parameter mapping score. This process calculates the probability density or risk score of aquifer pore blockage caused by water quality factors. This logic comprehensively considers the dual effects of "chemical precipitation" and "physical sedimentation", quantifies the potential negative impact of reinjection water quality on formation permeability, and obtains water quality blockage risk assessment indicators.

[0034] Please see Figure 6 The specific steps of S5 are as follows: S501: For the area to be evaluated, retrieve the delineated scope of the water source protection zone and the ecological red line vector layer, project the coordinates of the water intake wells onto the layer for spatial topology analysis, identify the positional relationship between the wells and the environmentally sensitive areas, quantify the environmental constraint level, combine the risk rating of the water quality blockage risk assessment indicators, formulate differentiated weighting strategies for the structural integrity status data of the water intake wells and the quantitative indicators of the aquifer recharge acceptance capacity, and generate a multi-dimensional assessment indicator weight allocation matrix. The process involves retrieving the vector layers of the delineated areas and ecological protection red lines of primary and secondary water source protection zones. This process projects the coordinates of the water intake wells onto the layers and performs spatial topology analysis to identify whether the well locations fall within the core area, buffer zone, or experimental zone of the protection zone. Based on this, the environmental constraint level is quantified (e.g., the constraint level of the core area is the highest level 1, and that of the non-sensitive area is 0). Combined with the risk rating of the water quality blockage risk assessment indicators generated in the previous steps, this process formulates a dynamic weighting strategy. If the environmental constraint level is high or the blockage risk is extremely high, the process will logically automatically increase the weight of the "risk item" and decrease the weight of the "capability item," reflecting the principle of "safety first." Finally, this process generates a differentiated weighting strategy that includes data on the structural integrity status of the water intake well, quantitative indicators of the aquifer recharge acceptance capacity, and water quality blockage risk assessment indicators, i.e., a multi-dimensional assessment indicator weight allocation matrix.

[0035] S502: Call the multidimensional evaluation index weight allocation matrix, combine the structural integrity parameter in the water intake well structural integrity status data, the hydraulic acceptance parameter in the aquifer recharge acceptance capacity quantitative index, and the blockage risk parameter in the water quality blockage risk assessment index, perform range transformation operation to map heterogeneous data to a unified numerical range, perform multiplication and linear accumulation operation of parameter normalization value and corresponding weight coefficient, calculate the quantitative score characterizing the matching degree of recharge project, and obtain the recharge suitability weighted index; This process gathers three sets of core heterogeneous data: structural integrity parameters (such as...). (Points), quantitative indicators of aquifer recharge capacity (such as normalized values) , mapped to The score includes water quality clogging risk assessment indicators. For water quality risk, the aforementioned example scores 5 points (risk score). To unify this into a "positive" suitability score, the process involves a reverse conversion, i.e. The points are then normalized to a percentage system. This process performs a range transformation operation, strictly mapping the data to a uniform numerical range of 0 to 100. It also involves multiplying the normalized parameter values ​​with their corresponding weight coefficients and performing linear accumulation operations. Assuming the weight matrix is ​​assigned as follows: structural integrity weights... Acceptance weight Water quality safety weight This process calculates a quantitative score characterizing the matching degree of the recharge project, namely the recharge suitability weighted index.

[0036] S503: Project the reinjection suitability weighted index onto the preset suitability grading standard interval model, perform numerical comparison, determine the preferred reinjection, restricted reinjection, or prohibited reinjection level of the water intake well, configure recommended category labels for the water intake well location based on the determination results, aggregate well location attribute information, original values ​​of key technical indicators, and grading conclusions, serialize and encapsulate the data according to suitability priority, and establish a water intake well reinjection suitability grading assessment list; The calculated reinjection suitability weighted index is projected onto a pre-defined suitability grading standard interval model, which specifies that: an index greater than... For "optimal recharge", to For "reinjection restricted" (requiring pretreatment or repair), below To "prohibit recharge", this process performs numerical comparisons, specifically for the examples above. The process determines whether it falls into the range. The well location was therefore classified as "restricted reinjection". Based on this determination, the process assigned a recommended category label to the well location and noted the need for pretreatment of the water quality (due to the low water quality score). The process aggregated well location attribute information, original values ​​of key technical indicators (such as permeability coefficient and corrosion level), and classification conclusions. The data was serialized, arranged, and packaged according to the suitability index from high to low priority to establish a list of suitable well reinjection classification assessments.

[0037] Please see Figure 7 A water intake well reinjection suitability assessment system based on a multi-dimensional detection and comprehensive index model includes: The well location screening module obtains the well location coordinates, well construction date and basic stratigraphic lithology data of the water intake wells in the area to be evaluated, compares them with the disaster pollution boundary to delineate the safe zone, eliminates maintenance records and damage records, screens open or confined aquifers, and establishes a set of qualified water intake wells in the initial screening. The structural integrity detection module scans the set of qualified water intake wells in the initial screening to identify damage and blockage, fits the well diameter to locate deformation, analyzes the water level recovery slope, and generates structural integrity status data of the water intake well. The hydraulic bearing capacity inversion module uses the data on the structural integrity of the intake well to perform step-by-step reinjection, collects steady-state water level and flow rate, calculates the ratio to determine the unit reinjection volume, and uses the Theis model to analyze permeability and hydraulic conductivity to generate a quantitative index of the aquifer's reinjection capacity. The water quality blockage assessment module collects water samples related to the quantitative indicators of aquifer recharge capacity, calculates the Langerier and Rezner indices to predict scaling, detects suspended solids concentration and particle size, and generates water quality blockage risk assessment indicators. The suitability classification assessment module acquires environmentally sensitive data, determines the structural integrity status data of the water intake well, the quantitative indicators of aquifer reinjection acceptance capacity, and the weights of water quality blockage risk assessment indicators, calculates the sum, and establishes a list of water intake well reinjection suitability classification assessments.

[0038] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of protection of the described technical solutions.

Claims

1. A method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model, characterized in that, Includes the following steps: S1: Obtain the well location coordinates, well construction date, and basic stratigraphic lithology data of the water intake wells in the area to be evaluated; compare the well location coordinates with the boundaries of geological disaster-prone areas and the impact range of pollution sources; delineate safe areas; and establish a preliminary set of qualified water intake wells. S2: Call the set of qualified water intake wells in the initial screening, scan the entire section of the water intake well wall and filter pipe, identify the location of the water intake well wall damage, the proportion of filter pipe blockage and corrosion status, measure the change of well diameter, locate the deformed parts, and obtain the structural integrity data of the water intake well. S3: Based on the structural integrity data of the water intake well, conduct a stepped pressurization reinjection test and gradually increase the reinjection pressure. Monitor the dynamic water level and reinjection flow rate data under the stable state of the steps, calculate the ratio of reinjection flow rate to water level rise, determine the unit reinjection volume, and obtain the quantitative index of the aquifer's reinjection acceptance capacity. S4: Based on the quantitative index of the aquifer recharge capacity associated with the water intake well location, collect recharge water source and groundwater samples for full water chemical analysis, calculate the Langerier saturation index and the Rezner stability index, detect the suspended solids concentration and particle size distribution in the recharge water, and obtain water quality blockage risk assessment index.

2. The method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model according to claim 1, characterized in that, The set of qualified water intake wells in the initial screening includes basic attribute information of the water intake well location, safety area positioning data, and target aquifer type identification. The structural integrity status data of the water intake well includes the coordinates of the well wall damage points, filter pipe blockage and corrosion parameters, well shaft radial deformation, and channel unobstructedness judgment value. The quantitative indicators of aquifer recharge acceptance capacity include unit recharge volume, permeability parameters, and water conductivity parameters. The water quality blockage risk assessment indicators include Langerier saturation index, Rezner stability index, calcium carbonate scaling trend prediction value, suspended solids concentration, and particle size parameters.

3. The method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Obtain the well location coordinates, well completion dates, and basic stratigraphic lithology data of the water intake wells in the area to be evaluated; call the boundary vector data of the geological hazard-prone area and the pollution source diffusion impact range layer; perform spatial overlay operation between the well location coordinates and the boundary vector data and layer of the geological hazard-prone area; identify the risky well locations falling within the boundary or range; delete the risky well locations and extract the remaining well location coordinates located in non-sensitive areas; map and bind the filtered coordinates with the well completion dates and basic stratigraphic lithology data to generate a basic well location data table for safe areas; S102: For the basic well location data table of the safety area, index the corresponding well maintenance record document, parse the operation and maintenance log and status description field in the document, compare whether there are operation records about well wall cracking, structural collapse or abandoned well sealing, perform logical negative filtering, remove record items with damage records or abandoned records, retain water intake well location information with normal operation and maintenance characteristics, and serialize and arrange the filtered water intake well location information to obtain the index set of candidate water intake well locations in good condition; S103: Based on the stratigraphic lithology data associated with the water intake index set of the candidate well locations in good condition, analyze the hydrogeological structural characteristics of the mining layer corresponding to the water intake well location, determine whether the mining layer is a phreatic aquifer closely connected with surface water or a confined aquifer with vertical permeability on the top plate, screen well locations that meet the openness or cross-flow recharge characteristics, and establish a preliminary set of qualified water intake wells.

4. The method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model according to claim 3, characterized in that, The specific steps of S2 are as follows: S201: Call the set of qualified water intake wells in the initial screening, collect optical images or acoustic amplitude data of the entire section of the water intake well wall and filter pipe, perform image segmentation operation, extract the edge feature coordinates of cracks and perforations in the water intake well wall, count the pixel grayscale differences in the opening area of ​​the filter pipe and calculate the mesh blockage area ratio, quantify the degree of corrosion and erosion according to the roughness texture and reflectivity characteristics of the inner surface of the pipe wall, and vectorize and catalog the identified damage location points, blockage ratio and corrosion level parameters to generate a set of surface disease parameters for the well wall and filter pipe; S202: For the well section covered by the apparent defect parameter set of the well wall and filter pipe, perform continuous scanning measurement along the well axis to obtain the measured radial distance data array of the inner wall of the well. Perform the difference calculation between the measured data and the inner diameter reference value of the well design, screen the abnormal measurement points whose absolute value of radial deviation exceeds the preset deformation judgment threshold, locate the layer depth where plastic deformation occurs, and obtain the quantitative record of radial geometric deformation of the well. S203: Based on the radial geometric deformation quantification record of the well shaft, perform a water level excitation response test on the water intake well, collect discrete data points of the water level rise in the well over time after pumping stops, fit the water level recovery curve and calculate the water level rise slope per unit time, analyze the fluid exchange resistance coefficient of the well shaft and aquifer interface and determine the channel unobstructed level, call the apparent defect parameter set of the well wall and filter pipe, perform attribute association and weighted aggregation of defect parameters, deformation records and unobstructed level data, and obtain the structural integrity status data of the water intake well.

5. The method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model according to claim 4, characterized in that, The specific steps for S3 are as follows: S301: Based on the structural integrity data of the water intake well, identify the pressure bearing limit of the well wall and set the starting pressure and pressurization step size of the stepped reinjection test. Control the reinjection pump to perform graded pressurized water injection operation. Continuously monitor the pressure fluctuation in the well under each pressure step until the variance is lower than the preset stability threshold. Simultaneously collect the bottom dynamic water level elevation and real-time reinjection flow data under the steady state stage, record the hydraulic element response sequence under pressure conditions, and generate a stepped steady-state hydraulic monitoring record. S302: Call the stepped steady-state hydraulic monitoring record, analyze the average flow rate and absolute water level under the stepped steady state, introduce the static water level data before the test to perform difference calculation to obtain the water level rise, perform the quotient calculation of reinjection flow rate and water level rise, construct a scatter plot of the relationship between flow rate and water level rise and identify the linear response interval, calculate the average ratio within the linear response interval, determine the parameter characterizing the water injection capacity of a single well per unit head, and obtain the unit reinjection volume efficiency characteristic value; S303: Perform hydrodynamic parameter inversion calculation on the time-varying data of flow and water level in the stepped steady-state hydraulic monitoring record, fit the solution that minimizes the deviation between the measured data points and the theoretical seepage equation, analyze the permeability coefficient and radial water conduction capacity parameters of the aquifer pore medium, perform numerical normalization and multi-dimensional attribute weighted aggregation on the radial water conduction capacity and the unit reinjection volume efficiency characteristic value, quantify the aquifer's capacity to accommodate reinjection fluid, and obtain a quantitative index of the aquifer's reinjection acceptance capacity.

6. The method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model according to claim 5, characterized in that, In the process of determining when the well pressure fluctuations until the variance is lower than the preset stability threshold, the preset stability threshold is limited to the fact that the statistical variance calculated from the well pressure monitoring data within the continuous sampling time window is not greater than the predetermined upper limit of the pressure fluctuation, and the continuous sampling time window is a fixed duration and covers at least one complete pressure maintenance cycle. The starting pressure of the stepped reinjection test is limited to a safety margin ratio lower than the wellbore pressure limit, and the pressure increment step is limited to a constant pressure increment between adjacent pressure steps. The identification of the linear response interval is limited to a continuous data segment in the scatter plot of the relationship between flow rate and water level rise, which satisfies the monotonic correspondence between flow rate and water level rise and the correlation dispersion does not exceed a predetermined discrimination limit. The calculation of the ratio mean is limited to the arithmetic average of the quotient of the reinjection flow rate and the water level rise rate corresponding to the pressure condition within the linear response interval. The numerical normalization process is defined as mapping the radial water conduction capacity and the unit reinjection volume efficiency characteristic value to a unified dimensionless interval, and then performing multi-dimensional attribute weighted aggregation according to a preset weight coefficient.

7. The method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model according to claim 5, characterized in that, The specific steps of S4 are as follows: S401: For the water intake well locations that are associated with the quantitative index of the aquifer recharge capacity, collect corresponding recharge water source and groundwater samples, perform full water chemical ion analysis, and measure pH value, calcium and magnesium ion concentration, alkalinity and total dissolved solids parameters. Substitute the measured data into the calculation formulas of Langerier saturation index and Rezsner stability index to perform numerical calculations, compare the calculation results with the calcium carbonate precipitation equilibrium benchmark value, determine the chemical scaling tendency of water quality in mixed environment, and generate calcium carbonate scaling trend prediction analysis value. S402: Call the calcium carbonate scaling trend prediction analysis value, extract the reinjection water source sample and perform laser particle size scanning and suspended solids gravimetric method test, measure the mass concentration value of insoluble solid particles in the fluid, count the distribution frequency of particle size in the differentiated micron range, draw the cumulative particle size distribution curve and extract the median particle size and maximum particle size characteristic parameters, quantify the physical transport resistance characteristics of exogenous particles in the porous medium of the aquifer, and obtain the suspended solids concentration and particle size distribution characteristic set; S403: Call the suspended solids concentration and particle size distribution feature set, perform dimensionless data processing to avoid parameter magnitude differences, perform multidimensional attribute weighted aggregation of chemical scaling index and physical blockage feature parameters, calculate the probability density or risk score of aquifer pore blockage caused by water quality factors, quantify the potential negative impact of reinjection water quality on formation permeability, and obtain water quality blockage risk assessment index.

8. The method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model according to claim 1, characterized in that, The method further includes step S5: S5: Based on the water quality blockage risk assessment index, obtain the environmentally sensitive data of the water source protection area and ecological red line in the area where the water intake well is located, determine the weight ratio of the structural integrity status data of the water intake well and the quantitative index of the aquifer recharge acceptance capacity, calculate the weighted sum of the assessment items and compare it with the suitability grading standard range, divide the recommended categories of water intake wells, and establish a water intake well recharge suitability grading assessment list. The list of suitable water intake wells for reinjection includes environmental sensitivity level, weighted total score of assessment items, suitability classification results, and recommended utilization category.

9. The method for assessing the suitability of water intake well reinjection based on a multi-dimensional detection and comprehensive index model according to claim 8, characterized in that, The specific steps of S5 are as follows: S501: For the area to be evaluated, retrieve the delineated scope of the water source protection zone and the ecological red line vector layer, project the coordinates of the water intake wells onto the layer for spatial topology analysis, identify the positional relationship between the wells and the environmentally sensitive areas, quantify the environmental constraint level, and combine the risk rating of the water quality blockage risk assessment indicators to formulate a differentiated weighting strategy for the quantitative indicators of the structural integrity status data of the water intake wells and the aquifer recharge acceptance capacity, and generate a multi-dimensional assessment indicator weight allocation matrix. S502: Call the multidimensional evaluation index weight allocation matrix, combine the structural integrity parameter in the water intake well structure integrity status data, the hydraulic acceptance parameter in the aquifer recharge acceptance capacity quantitative index, and the blockage risk parameter in the water quality blockage risk assessment index, perform range transformation operation to map heterogeneous data to a unified numerical range, perform multiplication and linear accumulation operation of parameter normalization value and corresponding weight coefficient, calculate the quantitative score characterizing the matching degree of recharge project, and obtain the recharge suitability weighted index; S503: Project the weighted index of reinjection suitability onto the preset suitability grading standard interval model, perform numerical comparison, determine the preferred reinjection, restricted reinjection, or prohibited reinjection level of the water intake well, configure recommended category labels for the water intake well location based on the determination results, aggregate well location attribute information, original values ​​of key technical indicators and grading conclusions, serialize and encapsulate the data according to suitability priority, and establish a water intake well reinjection suitability grading evaluation list.

10. A suitability assessment system for water intake well reinjection based on a multi-dimensional detection and comprehensive index model, characterized in that, The system is used to implement the water intake well reinjection suitability assessment method based on a multi-dimensional detection and comprehensive index model as described in any one of claims 1-9, and the system includes: The well location screening module obtains the well location coordinates, well construction date and basic stratigraphic lithology data of the water intake wells in the area to be evaluated, compares them with the disaster pollution boundary to delineate the safe zone, eliminates maintenance records and damage records, screens open or confined aquifers, and establishes a set of qualified water intake wells in the initial screening. The structural integrity detection module scans the set of qualified water intake wells in the initial screening to identify damage and blockage, fits the well diameter to locate deformation, analyzes the water level recovery slope, and generates structural integrity status data of the water intake well. The hydraulic bearing capacity inversion module uses the data on the structural integrity of the intake well to perform step-by-step reinjection, collects steady-state water level and flow rate, calculates the ratio to determine the unit reinjection volume, and uses the Theis model to analyze permeability and hydraulic conductivity to generate a quantitative index of the aquifer's reinjection capacity. The water quality blockage assessment module collects water samples associated with the quantitative index of the aquifer recharge acceptance capacity, calculates the Langerier and Rezna indexes to predict scaling, detects the concentration and particle size of suspended solids, and generates water quality blockage risk assessment indicators. The suitability grading assessment module acquires environmentally sensitive data, determines the structural integrity status data of the water intake well, the quantitative index of the aquifer reinjection acceptance capacity, and the weight of the water quality blockage risk assessment index, calculates the sum, and establishes a water intake well reinjection suitability grading assessment list.

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