Deep confined water recharge well plugging degree composite evaluation method

Abstract

The application discloses a kind of deep confined water backfill well plugging degree composite evaluation methods, three-dimensional evaluation system covering well filter layer permeability coefficient, well loss dynamic response, unit water level backfill flow is constructed, combined with weighted geometric mean algorithm effectively analyzes the non-linear coupling relationship of multiple parameters, introduce space-time dynamic parameter matrix, innovatively time-space variable such as backfill flow, water level dynamic, well body structure parameter is included in evaluation model, the real-time dynamic tracking of plugging evolution process is realized, and the dynamic adaptability of evaluation model is enhanced.The method provides a scientific decision-making basis for groundwater overexploitation management and other scenarios, and through a multidimensional evaluation mechanism, maintenance strategies can be significantly optimized, the effective service period of backfill wells is extended, and especially under complex geological conditions, it shows excellent environmental adaptability, provides systematic technical support for deep water backfill engineering, and has important practical significance for water safety and ecological restoration engineering.

Description

Technical Field

[0001] This invention relates to the field of groundwater recharge technology, and in particular to a composite assessment method for the degree of blockage in deep confined water recharge wells. Background Technology

[0002] Accurate assessment of the degree of blockage in deep confined aquifer recharge wells is crucial for controlling groundwater over-extraction and preventing seawater intrusion. It can improve recharge efficiency, ensure the stability of the freshwater-saline interface, reduce maintenance costs, extend well lifespan, and contribute to the construction of a groundwater security system.

[0003] Currently, existing technical methods for assessing the degree of blockage in deep confined water recharge wells mainly fall into two categories: one is an assessment method based on a single index, which judges the blockage by monitoring changes in a single parameter such as the recharge flow attenuation rate and the rate of rise in the well water level; the other is a traditional offline detection method, such as measuring the permeability coefficient of soil samples around the well in the laboratory or conducting on-site pumping tests, and combining the test data to analyze the degree of blockage.

[0004] Current technologies use a single indicator to assess the degree of blockage, ignoring the inherent correlation between "permeability coefficient change - dynamic response of well loss and recharge flow rate - flow rate per unit water level." This fails to fully reflect the complex mechanisms of blockage and easily misjudges flow rate decreases caused by other factors (such as aquifer pressure changes) as blockage, resulting in biased assessment results. Traditional methods involve complex and time-consuming laboratory measurements and field pumping tests, often requiring several days to weeks for a single test, making real-time dynamic monitoring of blockage levels difficult and lagging behind the actual needs of engineering control. The lack of integrated analysis of dynamic data such as recharge well water level, monitoring well water level, and real-time flow rate makes it difficult to distinguish between "well casing filter hole blockage" and "aquifer pore blockage," leading to a lack of targeted remediation measures. These shortcomings have been exposed in engineering practices such as deep water recharge test sites. Summary of the Invention

[0005] To address the aforementioned problems, this invention proposes a comprehensive assessment method for the degree of blockage in deep confined water replenishment wells. This method comprehensively assesses the degree of blockage in replenishment wells by considering the dynamic response of permeability coefficient changes, well loss and replenishment flow rate, and the intrinsic correlation between flow rate per unit water level. Based on the assessment results, the causes of blockage are identified.

[0006] This invention is implemented as follows:

[0007] A comprehensive assessment method for the degree of blockage in deep confined water replenishment wells, comprising the following steps:

[0008] Step 1: Collect initial data for the confined water replenishment well;

[0009] The initial data for the replenishment well includes the overall permeability coefficient K of the replenishment well obtained through pumping tests, and the inner radius of the replenishment well. Well wall thickness Distance between monitoring well and replenishment well (At least two monitoring wells should be installed).

[0010] Step 2: Obtain real-time data from the confined water replenishment well;

[0011] Real-time data for replenishment wells includes replenishment flow rate. well water level H w (T), monitoring well water levels H2(T), H3(T).

[0012] Step 3, calculate the flow rate of the replenishment well into the aquifer:

[0013] By replenishing the water injection flow and replenishment well water level H w (T) The flow rate of the replenishment well entering the aquifer is obtained. .

[0014] Step 4: Calculate the blockage degree index of the replenishment well from multiple dimensions:

[0015] S41, Calculating the degree of blockage in replenishment wells from the perspective of well filter layer permeability coefficient. :

[0016] By analyzing the water level response of the replenishment well and the monitoring well, the permeability coefficient K(T) of the entire replenishment system was calculated using the Dubuis equation.

[0017] Based on the relationship between the permeability coefficients of the replenishment well filter layer, the system, and the aquifer, the permeability coefficient of the replenishment well filter layer is derived. ;

[0018] Finally, the permeability coefficients of the replenishment well filter layer are compared between the initial and current times to calculate the current degree of blockage. ;

[0019] S42, Calculate the degree of blockage in the replenishment well from the perspective of the dynamic response of the relationship between well loss and replenishment flow rate. :

[0020] Real-time monitoring of the water levels in two monitoring wells, recording the distance between each monitoring well and the replenishment well, and constructing an aquifer water level response curve by combining the water levels in the monitoring wells and the distances to the replenishment wells;

[0021] By analyzing the relationship between the curve and distance, and the outer radius of the replenishment well, the water level on the outer wall of the replenishment well can be derived. Then, the well loss due to the difference in water level inside and outside the replenishment well is obtained. ;

[0022] The local seepage efficiency coefficient of the well body is obtained by the ratio of the square of the backfill flow rate to the well loss. Finally, by comparing the value of this indicator at the initial time with the current time, the degree of blockage in the current replenishment well is determined. ;

[0023] S43, Calculating the degree of blockage in replenishment wells from the perspective of replenishment flow rate per unit water level rise. :

[0024] Unit water level rise replenishment flow This refers to the recharge flow rate corresponding to a 1m increase in water level within the recharge well, calculated by comparing the initial and current times. The value is used to calculate the degree of blockage in the replenishment well at the current moment;

[0025] Step 5, calculate the composite index ;

[0026] A weighted geometric average method is used to calculate a composite index of the degree of blockage in replenishment wells, which scientifically integrates information from multiple parameters to improve the accuracy of the assessment.

[0027] Step 6: Incorporate the calculated data into the evaluation data model:

[0028] By incorporating real-time data, including water level replenishment flow, replenishment well water level, and monitoring well water level, as well as calculated blockage degree indicators, into the evaluation model, the real-time dynamic tracking of the blockage evolution process is provided to support operation and maintenance decisions.

[0029] Furthermore, in step 3, the replenishment well enters the aquifer flow rate. The calculation formula is as follows:

[0030] (1).

[0031] Furthermore, in step S41, the permeability coefficient K(T) of the recharge system is calculated using the following formula:

[0032] (2).

[0033] Furthermore, in step S41, the permeability coefficient K1(T) of the replenishment well filter layer is calculated using the following formula:

[0034] (3).

[0035] Furthermore, in step S41, the degree of blockage in the replenishment well is calculated from the perspective of the permeability coefficient of the well filter layer. The calculation formula is as follows:

[0036] (4)

[0037] Wherein, K1(0) is the permeability coefficient of the filter media layer in the initial stage of reinjection.

[0038] Furthermore, in step S42, the water level on the outer wall of the replenishment well... The calculation formula is as follows:

[0039] (5).

[0040] Furthermore, in step S42, the local seepage efficiency coefficient of the well body... The calculation formula is as follows:

[0041] (6).

[0042] Furthermore, in step S42, the degree of blockage in the replenishment well is calculated from the perspective of the dynamic response of the relationship between well loss and replenishment flow rate. The calculation formula is as follows:

[0043] (7)

[0044] Furthermore, in step S43, the well blockage degree index is replenished from the perspective of the replenishment flow rate per unit water level rise. The calculation formula is as follows:

[0045] (8)

[0046] Where q is the recharge flow rate per unit water level rise, and the formula for calculating q(T) is as follows:

[0047] (9)

[0048] Where s(T) is the height of the water level rise in the replenishment well at time T.

[0049] Furthermore, in step 5, the composite index The calculation formula is as follows:

[0050] (10)

[0051] Where α, β, and χ are weighting indices.

[0052] The beneficial effects of this invention are: a composite assessment method for the degree of blockage in deep confined water replenishment wells breaks through the limitations of traditional single-parameter assessment, constructs a three-dimensional assessment system covering the permeability coefficient of the well filter layer, the dynamic response of well loss, and the replenishment flow rate per unit water level, and effectively analyzes the nonlinear coupling relationship of multiple parameters by combining the weighted geometric average algorithm, which significantly improves the accuracy of blockage assessment.

[0053] By introducing a spatiotemporal dynamic parameter matrix, the evaluation model innovatively incorporates spatiotemporal variables such as recharge flow rate, water level dynamics, and well structure parameters, enabling real-time dynamic tracking of the blockage evolution process and enhancing the dynamic adaptability of the evaluation model.

[0054] At the engineering practice level, this method provides a scientific basis for decision-making in scenarios such as groundwater over-extraction management. Through a multi-dimensional evaluation mechanism, it can significantly optimize maintenance strategies and extend the effective service cycle of replenishment wells. In particular, it demonstrates excellent environmental adaptability under complex geological conditions, providing systematic technical support for deep water replenishment projects. It has important practical significance for ensuring water security and ecological restoration projects.

[0055] The present invention will be further explained in detail below with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0056] Figure 1 This is a schematic diagram illustrating the assessment of well blockage degree in the well filter layer based on the present invention;

[0057] Figure 2 This is a schematic diagram illustrating the dynamic response of the relationship between well damage and replenishment flow rate in this invention to assess the degree of blockage in replenishment wells;

[0058] Figure 3 This is a flowchart of a composite assessment method for the degree of blockage in deep confined water replenishment wells. Detailed Implementation

[0059] This embodiment presents a comprehensive assessment method for the degree of blockage in deep confined water replenishment wells. The core steps are as follows: Figure 3 As shown, the method steps are as follows:

[0060] Step 1: Collect initial data for the confined water replenishment well;

[0061] The initial data for the replenishment well includes the overall permeability coefficient K of the replenishment well (obtained through pumping experiments) and the inner radius of the replenishment well. Well wall thickness Distance between monitoring well and replenishment well (At least two monitoring wells should be installed).

[0062] Step 2: Obtain real-time data from the confined water replenishment well;

[0063] Real-time data for replenishment wells includes replenishment flow rate. well water level H w (T), monitoring well water levels H2(T), H3(T).

[0064] Step 3, calculate the flow rate of the replenishment well into the aquifer:

[0065] By replenishing the water injection flow and replenishment well water level H w (T) The flow rate of the replenishment well entering the aquifer is obtained. The calculation formula is as follows:

[0066] (1).

[0067] Step 4: Calculate the blockage degree index of the replenishment well from multiple dimensions:

[0068] S41, Calculating the degree of blockage in replenishment wells from the perspective of well filter layer permeability coefficient. :

[0069] The well filter media layer is a crucial channel for replenishment water to seep into the aquifer from the well casing. Its permeability coefficient directly determines the ease with which water flows through the filter media and is a fundamental indicator for judging whether blockage has occurred and its severity. The permeability coefficient of the well filter media layer can directly reflect the blockage status of the filter media layer, such as... Figure 1 As shown;

[0070] Under ideal conditions, the permeability coefficient of the filter media layer in an unblocked replenishment well is equal to that of the aquifer initially.

[0071] (2)

[0072] in, It is the initial permeability coefficient of the well filter media layer. It is the permeability coefficient value of the aquifer. It is the initial permeability coefficient value of the entire system obtained from the pumping test.

[0073] During the recharge process, the permeability coefficient of the entire system is first calculated using the Dubuis equation based on the water level response of the recharge well and the monitoring well. Then, the permeability coefficient of the replenishment well is obtained by relating it to the permeability coefficient of the entire system and the aquifer. The calculation formula is as follows:

[0074] (3)

[0075] (4)

[0076] in, M is the thickness of the aquifer;

[0077] Finally, by comparing the permeability coefficient of the filter layer in the replenishment well at the initial time and the current time, the degree of blockage in the replenishment well at the current time is calculated. The calculation formula is as follows:

[0078] (5)

[0079] In the formula, These are the permeability coefficient values ​​of the well filter layer at the initial stage of reinjection and at time T, respectively.

[0080] S42, Calculate the degree of blockage in the replenishment well from the perspective of the dynamic response of the relationship between well loss and replenishment flow rate. :

[0081] Well loss refers to the head loss that occurs as water flows from the replenishment source through the well casing, well wall, and filter layer into the aquifer. The dynamic response of well loss in relation to replenishment flow rate reflects the impact of blockage on the water level difference inside and outside the replenishment well. Its dynamic changes can reflect the blockage status of the water flow channels inside and around the replenishment well in real time, making it a core indicator for dynamic monitoring of blockage. It is related to the energy consumption and operational efficiency of the replenishment project. The dynamic response of well loss in relation to replenishment flow rate reflects the change in resistance during the interaction between the well structure and the aquifer, indirectly reflecting the impact of blockage on the water flow path. Figure 2 As shown;

[0082] Well damage is caused by the difference in water levels inside and outside the well. (T), the calculation formula is as follows:

[0083] (6)

[0084] Real-time monitoring of water levels in two monitoring wells By combining the water level of the monitoring well and its distance from the replenishment well, an aquifer water level response curve can be constructed. Then, based on the outer radius of the replenishment well The water level on the outer wall of the replenishment well can be obtained. (T).

[0085] Water level response curve [ The relationship between the distance to the replenishment well and the distance to the well is as follows: Using two monitoring wells to monitor water levels and distance Given parameters A and B, the calculation formula is as follows:

[0086]

[0087] (7)

[0088] Substitute the relation available The calculation formula is as follows:

[0089] (8)

[0090] Local seepage efficiency coefficient of well body The formula for calculating the degree of blockage in a replenishment well is as follows:

[0091] (9)

[0092] Comparing the initial time and the current time The current moment's blockage level index for the replenishment well is calculated using the following formula:

[0093] (10)

[0094] S43, Calculating the degree of blockage in replenishment wells from the perspective of replenishment flow rate per unit water level rise. :

[0095] The recharge flow rate per unit water level rise refers to the recharge flow rate corresponding to a 1m increase in water level within the recharge well. Under the same recharge flow rate, the more severe the well blockage, the greater the rise in water level within the recharge well; it reflects the impact of blockage on recharge efficiency and provides a basis for judging the blockage status of the well. The calculation formula is as follows:

[0096] (11)

[0097] By comparing the initial time and the current time The current moment's blockage level index for the replenishment well is calculated using the following formula:

[0098] (14)

[0099] Step 5, calculate the composite index ;

[0100] When constructing a composite index for the degree of blockage in replenishment wells, a weighted geometric average method is used for calculation. This method can effectively integrate three different dimensions of blockage degree indicators, and by flexibly setting the weights of each indicator, a more comprehensive and accurate integrated assessment of the blockage status can be achieved.

[0101] Its advantages are: first, it enhances the robustness of the assessment results and weakens the interference of extreme values ​​on the overall judgment; second, it has a wide range of applications and can adapt to the assessment needs of replenishment systems of varying complexity. The final output composite index provides a reliable basis for subsequent maintenance, repair, and management decisions for replenishment wells. The calculation formula is as follows:

[0102] (15)

[0103] Where α, β, and χ are weighting indices.

[0104] Changes in the permeability coefficient directly reflect the decrease in permeability caused by blockage of the well filter layer. It is a direct physical characterization of the degree of blockage and plays a key role in the efficiency of replenishment wells. Therefore, it should account for a high proportion in the weighting allocation.

[0105] The dynamic response of the relationship between well loss and flow rate reflects the effect of blockage on the water level difference inside and outside the replenishment well. When the flow rate is constant, the increase in well loss means that the replenishment well needs to consume more energy to maintain the replenishment flow rate. This is directly related to the energy consumption and operating efficiency of the replenishment project. Therefore, the dynamic response of the relationship between well loss and replenishment flow rate should also be given high weight.

[0106] In comparison, although the unit water level replenishment flow can also reflect the impact of blockage on replenishment efficiency, this impact is relatively indirect. It mainly establishes the relationship between replenishment flow and water level rise. Therefore, its weight can be slightly lower than the first two indicators.

[0107] From a realistic physics perspective, the relative weights of these three indicators are ranked as follows: Based on the analysis of the physical meaning, a preliminary weight value is assigned. The specific weights can be adjusted according to the actual situation.

[0108] Step 6: Incorporate the calculated data into the evaluation data model:

[0109] By incorporating real-time data such as water level replenishment flow, replenishment well water level, and monitoring well water level, as well as calculated blockage degree indicators into the evaluation model, the real-time dynamic tracking of the blockage evolution process is provided to support operation and maintenance decisions.

[0110] The model can be based on composite indicators Qualitative analysis of the degree of blockage in replenishment wells can be based more on the permeability coefficient of the well filter media layer. Dynamic response index of the relationship between well loss and replenishment flow rate Unit water level replenishment flow rate index The comprehensive changes are used to determine the cause and direction of blockage, and to distinguish the causes such as blockage of well casing filter holes, blockage of well wall biofilm, and blockage of aquifer pores (e.g., large decrease in permeability coefficient + small increase in well loss = blockage of filter material pores; small decrease in permeability coefficient + large increase in well loss = blockage of well wall biofilm, etc.).

[0111] Through this dynamic tracking and precise diagnosis, the model can output core information such as the development trend of blockages, key influencing factors, and specific causes of blockages, providing direct data support for operation and maintenance decisions. For example, it can determine the optimal timing for well cleaning, assess whether the effect of blockage repair meets standards, and optimize subsequent recharge operation parameters, aligning with the actual needs of "precise diagnosis and targeted repair" in groundwater recharge projects, ensuring the long-term stable operation of recharge wells. Finally, it should be noted that the above is only used to illustrate the technical solution of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solution of the present invention (such as the application of various formulas, the order of steps, etc.) without departing from the spirit and scope of the present invention.

Claims

1. A composite assessment method for the degree of blockage in deep confined water replenishment wells, characterized in that, The evaluation method steps are as follows: Step 1: Collect initial data for the confined water replenishment well; The initial data for the replenishment well includes the overall permeability coefficient K of the replenishment well obtained through pumping tests, and the inner radius of the replenishment well. Well wall thickness And the distance between each of the at least two monitoring wells and the replenishment well. ; Step 2: Obtain real-time data from the confined water replenishment well; Real-time data for replenishment wells includes replenishment flow rate. well water level Monitoring well water level ; Step 3, calculate the flow rate of the replenishment well into the aquifer: By replenishing the water injection flow and replenishment well water level The flow rate of the replenishment well into the aquifer was obtained. ; Step 4: Calculate the blockage degree index of the replenishment well from multiple dimensions: S41, Calculating the degree of blockage in replenishment wells from the perspective of well filter layer permeability coefficient. : The permeability coefficient of the entire recharge system was calculated using the Jubilee equation based on the water level responses of the recharge and monitoring wells. ; Based on the relationship between the permeability coefficients of the replenishment well filter layer, the system, and the aquifer, the permeability coefficient of the replenishment well filter layer is derived. ; Finally, the permeability coefficients of the replenishment well filter layer are compared between the initial and current times to calculate the current degree of blockage. ; S42, Calculate the degree of blockage in the replenishment well from the perspective of the dynamic response of the relationship between well loss and replenishment flow rate. : Real-time monitoring of the water levels in two monitoring wells, recording the distance between each monitoring well and the replenishment well, and constructing an aquifer water level response curve by combining the water levels in the monitoring wells and the distances to the replenishment wells; By analyzing the relationship between the curve and distance, and the outer radius of the replenishment well, the water level on the outer wall of the replenishment well can be derived. Then, the well loss due to the difference in water level inside and outside the replenishment well is obtained. ; The local seepage efficiency coefficient of the well body is obtained by the ratio of the square of the backfill flow rate to the well loss. Finally, the local seepage efficiency coefficients of the well body at the initial time and the current time are compared. Determine the current degree of blockage in the replenishment well. ; S43, Calculating the degree of blockage in replenishment wells from the perspective of replenishment flow rate per unit water level rise. : The recharge flow rate q per unit water level rise refers to the recharge flow rate corresponding to a 1m increase in water level within the recharge well. This is determined by comparing the initial and current times. The value is used to calculate the degree of blockage in the replenishment well at the current moment; Step 5, calculate the composite index ; A weighted geometric average method is used to calculate a composite index of the degree of blockage in replenishment wells, which scientifically integrates information from multiple parameters to improve the accuracy of the assessment. Step 6: Incorporate the calculated data into the evaluation data model: By incorporating real-time data, including water level replenishment flow, replenishment well water level, and monitoring well water level, as well as calculated blockage degree indicators, into the evaluation model, the real-time dynamic tracking of the blockage evolution process is provided to support operation and maintenance decisions.

2. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step 3, the replenishment well enters the aquifer flow rate. The calculation formula is as follows: （1）。 3. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step S41, the permeability coefficient K(T) of the recharge system is calculated using the following formula: （2） Where M is the thickness of the aquifer.

4. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step S41, the permeability coefficient K1(T) of the replenishment well filter layer is calculated using the following formula: (3) in, , is the aquifer permeability coefficient.

5. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step S41, the degree of blockage in the replenishment well is calculated from the perspective of the permeability coefficient of the well filter layer. The calculation formula is as follows: (4) in, It is the permeability coefficient of the filter media layer in the initial stage of reinjection.

6. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step S42, the water level on the outer wall of the replenishment well... The calculation formula is as follows: (5)。 7. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step S42, the local seepage efficiency coefficient of the well body The calculation formula is as follows: (6) in, To compensate for well damage caused by the difference in water levels inside and outside the well.

8. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step S42, the degree of blockage in the replenishment well is calculated from the perspective of the dynamic response of the relationship between well loss and replenishment flow rate. The calculation formula is as follows: (7) in, The initial local seepage efficiency coefficient of the well body.

9. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step S43, the well blockage degree index is replenished from the perspective of the replenishment flow rate per unit water level rise. The calculation formula is as follows: (8) Where q is the flow rate replenished per unit rise in water level. The formula for calculating q(T) is the initial water level rise replenishment flow rate per unit increase in water level. (9) Where s(T) is the height of the water level rise in the replenishment well at time T.

10. The composite assessment method for the degree of blockage in deep confined water replenishment wells according to claim 1, characterized in that, In step 5, the composite index The calculation formula is as follows: (10) Where α, β, and χ are weighting indices.

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