High salinity mine underground water reinjection risk assessment method and system

Abstract

The application discloses a kind of high salinity mine groundwater reinjection risk assessment method and system, it is related to the technical field of data analysis.The sequence of water injection rhythm, rhythm difference value and diffusion range overlap analysis are constructed, the suspected interference well pair that possible interwell interference exists is effectively identified;By extracting the intersection of water injection time to form interference intersection area, and combining factors such as pressure change, flow fluctuation and overlapping duration, the interference intensity value is quantitatively calculated, and finally the resonance risk index is formed and used to evaluate whether the injectability of the target area under the current reinjection mode is qualified.The method can identify and evaluate the regional stress superposition and propagation risk caused by injection rate, frequency and rhythm control difference in advance under the complex working condition that multiple reinjection wells share the same aquifer system, so as to effectively avoid the stress interference resonance hidden problems such as permeability loss of control, boundary pressure breakthrough and well area anomaly caused by multiple well coordinated injection.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, specifically to a method and system for risk assessment of groundwater reinjection in high-mineralization mines. Background Technology

[0002] In the current mining area water resource management system, the underground reinjection capacity of high-salinity mine water is directly related to the safe disposal efficiency of mine water resources, the operational stability of underground structures, and the sustainable operation capacity of the regional reinjection system. Generally, when assessing the underground reinjection capacity of high-salinity mine water, simulation analysis is conducted before reinjection based on the established water injection behavior pattern and the actual layout structure of the high-salinity mine to determine whether the underground reinjection capacity of the high-salinity mine water is qualified. In this way, the best water injection method with the fastest water injection efficiency and without affecting the stability of the underground structure of the high-salinity mine can be selected.

[0003] However, in actual reinjection of high-salinity mine water, with the expansion of injection well scale and the promotion of collaborative operation mechanisms in mining areas, the aforementioned method of evaluating the reinjection capacity of individual high-salinity mine water independently has gradually revealed its insufficient understanding of the synergistic injection effect of multiple wells. Especially when multiple reinjection wells share the same aquifer system, differences in injection volume, frequency, and pressure regulation strategies among wells can easily lead to complex stress superposition and propagation paths underground, inducing regional stress interference resonance phenomena. This can result in hidden risks such as local permeability runaway, boundary pressure breakthrough, and abnormal well operation. These resonance problems, due to their high degree of concealment, high explosiveness, and difficulty in prediction within conventional evaluation systems, have become a key bottleneck restricting the safe reinjection of high-salinity mine water. Summary of the Invention

[0004] The purpose of this invention is to address the issue mentioned in the background section, where the existing evaluation methods struggle to identify underground interference resonance phenomena caused by inter-well stress superposition, which has become a key bottleneck restricting the safe reinjection of high-salinity mine water. To address this issue, a risk assessment method and system for groundwater reinjection in high-mineralization mines is proposed.

[0005] A first aspect of this invention provides a method for risk assessment of groundwater reinjection in high-mineralization mines, the method comprising: S1: Based on the water injection behavior data of each reinjection well in the target area under the current reinjection mode, form the water injection rhythm sequence of each reinjection well; S2: Calculate the difference in water injection rhythm between any two reinjection wells based on the water injection rhythm sequence; S3: Obtain the water diffusion range of each reinjection well and filter the set of suspected interfering well pairs based on the difference in water injection rhythm; S4: For the set of suspected interfering well pairs, extract the intersection of water injection time of each well pair in the diffusion overlap area to form a set of interference intersection areas; S5: Calculate the interference intensity value of each intersection area based on the state information of each intersection area in the set of interference intersection areas; S6: Summarize the interference intensity values ​​of each intersection area to obtain the resonance risk index, and evaluate whether the target area is qualified for reinjection under the current reinjection method based on the preset threshold.

[0006] Optionally, in step S2, the step of calculating the difference in water injection rhythm between any two reinjection wells based on the water injection rhythm sequence is as follows: Align the water injection rhythm sequence of each reinjection well with a uniform time step to construct a water injection status time sequence for each reinjection well. Each time step includes a water injection status marker, corresponding flow rate value, and pressure value. For any two reinjection wells, extract the water injection behavior vector corresponding to the same time step in their water injection state time series, and calculate the behavior difference value for each time step. The behavior difference value consists of three items: water injection difference, flow rate difference, and pressure difference. The behavioral difference values ​​at each time step are accumulated over the entire time series to obtain the difference in water injection rhythm between the two corresponding reinjection wells.

[0007] Optionally, in step S3, the step of obtaining the water diffusion range of each reinjection well and screening the set of suspected interfering well pairs based on the difference in water injection rhythm is as follows: Based on the aquifer permeability parameters, lithological boundaries, and historical water injection response radii recorded in the geological data, the water injection diffusion boundary of each reinjection well is determined, and a corresponding diffusion circular area is constructed with the wellhead as the center. For any two reinjection wells, determine whether their diffusion circular regions overlap spatially. If they overlap, mark them as having overlapping diffusion ranges. Extract the rhythm difference value of each well pair and set the rhythm difference threshold; Well pairs that simultaneously meet the conditions of having a rhythm difference value less than the rhythm difference threshold and overlapping diffusion ranges will be included in the set of suspected interfering well pairs.

[0008] Optionally, S4: For the set of suspected interfering well pairs, the steps to extract the intersection of water injection times of each well pair within the diffusion overlap area to form a set of interfering convergence areas are as follows: For any well pair in the set of suspected interfering well pairs, extract the water injection time period information for each well, which includes the water injection start time and the water injection end time. Determine whether there is an overlapping time interval on the water injection time axis for this well pair. If there is an overlap, then determine that the overlapping time interval is the intersection of the water injection time of this well pair. The intersection of the water injection times is associated and bound with the diffusion overlap area corresponding to the well pair, and defined as an interference convergence area; Repeat the above operation for all suspected interfering well pairs to form a set of interfering convergence areas.

[0009] Optionally, in step S5, the step of calculating the interference intensity value of each intersection region based on the state information of each intersection region in the interference intersection region set is as follows: Calculate the superimposed driving gradient index and potential differential pressure cyclone channel index of the injection field in each intersection region of the interference intersection region set. Add the superimposed driving gradient index and potential differential pressure cyclone channel index of the injection field to obtain the interference intensity value of each intersection region.

[0010] Optionally, the calculation steps for the gradient exponent driven by the superposition of the water injection field are as follows: For the two reinjection wells corresponding to the interference convergence area, the water injection path in the main underground seepage direction is extracted respectively, and three consecutive reference points are selected at equal intervals in each path to form two consecutive water injection path segments. For each injection path segment corresponding to each of the two reinjection wells, calculate the difference in direction angles between the two segments in each injection path, divide the absolute value of the difference in direction angles by two, and obtain the local disturbance direction amplitude of the injection path segment of the corresponding reinjection well. Using the center point of the intersection area as a reference point, calculate the direction vector formed by the tangent directions of the water injection paths of the two reinjection wells at the reference point, and calculate the magnitude of the difference between the two direction vectors, which is recorded as the first magnitude value. Calculate the magnitude of the sum between the two direction vectors, which is recorded as the second magnitude value. Divide the first magnitude value by the second magnitude value, and use the ratio as the degree of convergence of the water injection paths of the two wells at the intersection point. Calculate the absolute value of the difference between the amplitudes of the local disturbance directions of the two water injection paths, and take the reciprocal of the absolute value of the difference plus one as the synergy value of the water injection paths of the two wells in terms of disturbance trend; The absolute difference between the water injection path convergence degree value and the synergy value is used as the numerator, and the absolute difference between the water injection path convergence degree value and the synergy value plus the value 1 is used as the denominator to obtain the water injection field superposition driving gradient index. The result of the water injection field superposition driving gradient index is a dimensionless quantity between 0 and 1. The larger the value, the easier it is for the intersection area to form a stress concentration area driven by cross water injection in the structural direction.

[0011] Optionally, the calculation steps for the potential differential pressure cyclone channel index are as follows: Path point set selection: Taking the geometric center of each interference intersection area as the reference point, extend evenly from the center of the intersection area to both sides along the water injection path direction of the first reinjection well and the second reinjection well, and set a path point every unit distance until it exceeds the boundary of the intersection area, forming the first path point set and the second path point set respectively. Constructing local three-point path segments: In the first set of path points and the second set of path points, each set of three adjacent path points forms a local path segment, forming multiple consecutive three-point segment structures. Each three-point segment represents the local direction of the path in that segment. Rotation change value calculation: For each three-point segment, first calculate the spatial direction vectors of the two segments before and after, then calculate the angle between the two vectors, and divide the angle by 180 to obtain the standardized rotation change value, which is used as the degree of rotation disturbance of the path segment. The result ranges from 0 to 1. Rotation difference sequence generation: Compare the rotation change values ​​of the three point segments at corresponding positions in the first path point set and the second path point set one by one. For each pair of positions, calculate the absolute value of the difference between the rotation change values ​​of the two paths, and record it as the rotation difference value of the pair of path segments. Then divide the rotation difference value by the sum of the rotation change values ​​of the two paths plus one to obtain the normalized rotation difference value, forming a rotation difference sequence. Candidate cyclone point identification: In the cyclone difference sequence, all positions with normalized cyclone difference values ​​greater than 0.4 are selected and identified as candidate path points with potential differential pressure cyclone trends, forming a candidate cyclone point set; Path offset calculation: For each candidate loop point, two reinjection wells are connected to the point to construct two differential pressure propagation paths; the angle between these two paths and the main permeation direction of the interference intersection area is calculated, and the angle value is divided by 180 to obtain the standardized path offset value; then the absolute value of the difference between the offset values ​​of the two paths is divided by the sum of the two plus one to obtain the path propagation difference degree of the loop point. Cyclone twist intensity calculation: Multiply the normalized cyclone difference value of each candidate cyclone point by the path propagation difference degree to obtain the cyclone twist factor at that position; then divide the product value by the product value plus one to obtain the cyclone twist intensity value of each cyclone point. Exponential fusion output: The cyclone torsion intensity values ​​of all candidate cyclone points are fused. The fusion method is as follows: for each intensity value, subtract its value from one to obtain the inverse residual term. Multiply all the inverse residual terms in turn to obtain the product result. Then subtract the product result from one to obtain the final potential differential pressure cyclone channel index. The potential differential pressure cyclone channel index is a dimensionless quantity between 0 and 1. The larger the value, the easier it is for the internal structure of the interference convergence area to form a differential pressure retention structure with enhanced coupling between path rotation anomaly and directional propagation difference, thus having a higher risk of continuous interference.

[0012] Optionally, S6: The steps of summarizing the disturbance intensity values ​​of each intersection area to obtain the resonance risk index, and determining whether the target area has acceptable underground reinjection capacity under the current reinjection configuration based on a preset threshold are as follows: The steps for summarizing the interference intensity values ​​of each intersection area to obtain the resonance risk index, and evaluating whether the re-injection capability of the target area under the current re-injection method is qualified according to the preset threshold are as follows: Based on the interference intensity values ​​of all intersection areas, calculate the average interference intensity value and the standard deviation of the interference intensity value; add the average interference intensity value and the standard deviation value to obtain the resonance risk index; the larger the resonance risk index value, the more the overall interference under the current reinjection configuration has both the problem of high average intensity and the significant characteristic of uneven interference between regions. The resonance risk index is compared with the preset threshold. If the resonance risk index is not greater than the preset threshold, the target area is qualified for reinjection under the current reinjection method. The current reinjection method is directly used as the final reinjection method for each high-mineralization mine water in the target area. If the resonance risk index exceeds the preset threshold, the target area's re-betting capability under the current re-betting method is deemed unqualified. The re-betting method will then be reset until the re-betting capability corresponding to the new method is deemed qualified.

[0013] A second aspect of this invention provides a risk assessment system for groundwater reinjection in high-mineralization mines, the system comprising: Sequence module: Based on the water injection behavior data of each reinjection well in the target area under the current reinjection mode, it forms the water injection rhythm sequence of each reinjection well; Rhythm Difference Module: Calculates the difference in water injection rhythm between any two reinjection wells based on the water injection rhythm sequence; Suspected interference module: Obtain the water diffusion range of each reinjection well and filter the set of suspected interference well pairs based on the difference in water injection rhythm; Interference convergence module: For suspected interfering well pairs, extract the intersection of water injection time of each well pair in the diffusion overlap area to form an interference convergence area set; Interference Intensity Module: Calculates the interference intensity value of each intersection region based on the state information of each intersection region in the interference intersection region set; Evaluation module: Summarizes the interference intensity values ​​of each intersection area to obtain the resonance risk index, and evaluates whether the target area's re-injection capability is qualified under the current re-injection method based on preset thresholds.

[0014] The beneficial effects of this invention are: This invention proposes a risk assessment method and system for groundwater reinjection in high-mineralization mines. By constructing an injection rhythm sequence, analyzing rhythm differences, and examining the overlap of diffusion ranges, it effectively identifies suspected interfering well pairs that may have inter-well interference. By extracting the intersection of injection times to form interference convergence areas, and combining factors such as pressure changes, flow fluctuations, and overlap duration, the interference intensity value is quantified, ultimately forming a resonance risk index to evaluate whether the reinjection capacity of the target area is up to standard under the current reinjection method. This method overcomes the limitations of existing evaluations based on single-well static parameters. It can identify and assess in advance the regional stress superposition and propagation risks caused by differences in injection volume, frequency, and rhythm control in complex operating conditions where multiple reinjection wells share the same aquifer system. This effectively avoids latent stress interference resonance problems such as runaway permeability, boundary pressure breakthroughs, and well area anomalies caused by multi-well coordinated injection, providing more reliable risk assessment support for high-mineralization mine water reinjection projects. Attached Figure Description

[0015] Figure 1 A flowchart illustrating a risk assessment method for groundwater reinjection in high-mineralization mines, provided as an embodiment of the present invention. Detailed Implementation

[0016] To further illustrate the technical means and effects adopted by the present invention in order to achieve the intended purpose, the following detailed description is provided in conjunction with the accompanying drawings and preferred embodiments, based on the specific implementation methods, structures, features and effects of the present invention.

[0017] This invention provides a method for risk assessment of groundwater reinjection in highly mineralized mines. See also... Figure 1 , Figure 1 A flowchart illustrating a risk assessment method for groundwater reinjection in high-salinity mines, provided as an embodiment of the present invention. The method includes the following steps: S1: Based on the water injection behavior data of each reinjection well in the target area under the current reinjection mode, form the water injection rhythm sequence of each reinjection well; S2: Calculate the difference in water injection rhythm between any two reinjection wells based on the water injection rhythm sequence; S3: Obtain the water diffusion range of each reinjection well and filter the set of suspected interfering well pairs based on the difference in water injection rhythm; S4: For the set of suspected interfering well pairs, extract the intersection of water injection time of each well pair in the diffusion overlap area to form a set of interference intersection areas; S5: Calculate the interference intensity value of each intersection area based on the state information of each intersection area in the set of interference intersection areas; S6: Summarize the interference intensity values ​​of each intersection area to obtain the resonance risk index, and evaluate whether the target area is qualified for reinjection under the current reinjection method based on the preset threshold.

[0018] This invention provides a risk assessment method for groundwater reinjection in high-mineralization mines. By constructing an injection rhythm sequence, analyzing rhythm differences, and examining the overlap of diffusion ranges, it effectively identifies potential interfering well pairs. Interference convergence areas are formed by extracting the intersection of injection times, and the interference intensity is quantified by combining factors such as pressure changes, flow fluctuations, and overlap duration. Finally, a resonance risk index is generated to evaluate the reinjectability of the target area under the current reinjection method. This method overcomes the limitations of existing evaluations based on single-well static parameters. It can identify and assess the regional stress superposition and propagation risks caused by differences in injection volume, frequency, and rhythm control in complex conditions where multiple reinjection wells share the same aquifer system. This effectively avoids latent stress interference resonance problems such as runaway permeability, boundary pressure breakthroughs, and well area anomalies caused by multi-well coordinated injection, providing more reliable risk assessment support for high-mineralization mine water reinjection projects.

[0019] In one embodiment, the step of forming the water injection rhythm sequence of each reinjection well in step S1 based on the water injection behavior data corresponding to the current reinjection mode of each reinjection well in the target area is as follows: In step S1, based on the water injection behavior data of each reinjection well in the target area under the current reinjection mode, a water injection rhythm sequence for each reinjection well is formed. The purpose of this step is to analyze the rhythm of water injection behavior in each reinjection well to identify potential interference patterns during inter-well coordinated injection. The water injection behavior data mainly includes, but is not limited to: water injection start and end times, water injection duration, water injection flow rate variation curve, water injection pressure variation, whether there are intermittent start and stop times, the time interval between each injection, and water injection segment switching records (if segmented injection is used). The specific method for forming the water injection rhythm sequence is as follows: the water injection behavior data is sliced ​​at fixed time steps (e.g., every 5 minutes or every 30 minutes), and the water injection status (e.g., whether water is injected, water injection rate, pressure change direction, etc.) is extracted within each time step and encoded into a time series, such as represented in triplets as (whether water is injected, instantaneous flow rate, instantaneous pressure). For example, if a reinjection well has a stable injection phase from 0:00 to 1:00, a non-injection phase from 1:00 to 1:30, and a high-pressure injection phase from 1:30 to 2:00, then its injection rhythm sequence can be roughly represented as: [(1, Q1, P1), (1, Q1, P1), (0, 0, 0), (1, Q2, P2),], where Q1 and P1 are the average flow rate and pressure during stable injection, and Q2 and P2 are the characteristic values ​​during the high-pressure injection phase. This behavioral data can be obtained from simulations of the current reinjection method in various high-mineralization mines. By constructing such an injection rhythm sequence, not only can the injection pattern of each well in different time periods be completely preserved, but it can also provide a structured and comparable data basis for subsequent identification of rhythm differences and screening of well pairs with interference risks, thereby improving the accuracy and targeting of resonance risk assessment.

[0020] In one embodiment, specifically in step S2, to accurately measure the temporal coordination and differences in water injection behavior between any two reinjection wells, it is necessary to calculate the water injection rhythm difference value based on their respective water injection rhythm sequences. Specifically, firstly, the water injection rhythm sequences of each reinjection well are aligned according to a uniform time step (e.g., every 10 minutes) to obtain a water injection state time sequence with a consistent structure. The data structure for each time step includes three fields: whether water is being injected (1 or 0), the water injection flow rate Q at that moment, and the water injection pressure P. Next, for any pair of wells (e.g., well A and well B), the water injection behavior vectors (1, Q1, P1) and (0, Q2, P2) of the two wells are extracted at each time step, and their behavior difference value is calculated, specifically defined as: Difference Value. ,in These are preset weight parameters, which are generally limited based on the specific circumstances, and generally... The sum of these values ​​equals 1; this is used to regulate the influence of each indicator on the overall difference. Taking 100 time steps as an example, each time step yields a behavioral difference value. These 100 difference values ​​are then summed and normalized to obtain the water injection rhythm difference value between well A and well B. Performing the same calculation on all possible well pairs yields an n×n rhythm difference matrix, where n is the total number of reinjection wells. This rhythm difference matrix not only provides a quantitative basis for subsequent identification of well pairs at risk of coordinated interference but also effectively eliminates irrelevant well pairs with large rhythm differences, improving the accuracy of interference identification and the specificity of the evaluation. For example, if the difference value between well A and well B is much smaller than that between well A and well C, it indicates a high probability of synchronized interference between A and B, requiring further monitoring of their diffusion overlap and temporal convergence in the next step.

[0021] The greatest advantage of calculating the difference in water injection rhythm using the above method is that it can simultaneously incorporate three key physical behavioral dimensions—whether water is injected, water injection flow rate, and water injection pressure—into a time series comparison framework. Under a unified time step, it gradually analyzes the differences in water injection status between any two wells within the same time period. It considers the state difference between water injection and no water injection, while also preserving subtle changes in water injection intensity (flow rate) and water injection driving force (pressure). This avoids the bias of a single dimension dominating the difference judgment and prevents some wells from being mistakenly identified as having the same rhythm even though their flow rates are similar, but the water injection timing is misaligned or the pressure difference is significant.

[0022] In one embodiment, it should be noted that in step S3, to accurately determine which reinjection wells have potential spatial interference relationships, it is first necessary to determine the water injection diffusion range of each reinjection well based on geological data. Specifically, based on aquifer permeability parameters (such as permeability coefficient K, water storage coefficient S), lithological boundaries (such as impermeable interlayers, fault locations), and water pressure response radii monitored in historical water injection tests, the maximum water injection influence radius of each well within a given water injection duration t is calculated. The diffusion radius can be calculated using the following formula: ,in, Indicates the first The water diffusion radius of the injection well. The value is the permeability coefficient of the aquifer where the well is located (unit: m / d). This is the typical duration of the water injection cycle for this well (unit: d (day)). The water storage coefficient is dimensionless. This is an empirical correction coefficient (typically between 0.8 and 1.2, considering formation heterogeneity and adjustment coefficients). This formula originates from the fundamental theory of groundwater movement and can robustly estimate the influence range of the injection boundary. Taking well A as an example, if the aquifer permeability coefficient K = 4.5 m / d, the storage coefficient S = 0.002, the injection period t = 2 days, and we take the empirical coefficient C = 1, then: Therefore, the water injection diffusion boundary of well A can be modeled as a circular region with a radius of 67.08 meters centered at the wellhead coordinates. All reinjection wells construct their own water injection diffusion circles in this way. Subsequently, for any two wells (such as well A and well B), their water injection diffusion circles are spatially overlapped. If the geometric distance between the two circles is less than the sum of their radii, it is determined that there is an overlap in the diffusion area, and it is recorded as a diffusion intersection well pair. Based on this, the rhythm difference value of the well pair obtained in the previous step is compared with a preset rhythm difference threshold (e.g., 0.25). If the rhythm difference value of the well pair is lower than the threshold and the diffusion circles overlap, the well pair is included in the set of suspected interfering well pairs.

[0023] Well pairs selected through the above method not only meet the premise of similar water injection rhythms and temporal resonance, but also the spatial interference path condition of overlapping diffusion boundaries. Thus, they constitute high-risk well pairs with physical interaction potential. Compared with methods that rely solely on geographical distance or experience, this method is more adaptable and is especially suitable for use in mining environments with complex reinjection well layouts and strong geological heterogeneity.

[0024] In one embodiment, it should be noted that in step S4, the purpose is to further identify from the screened suspected interfering well pairs the specific locations and times where water injection activities may overlap within the same time period and the same underground space area, thus forming the so-called interference convergence area. Specifically, firstly, for any well pair (e.g., well A and well B) in the set of suspected interfering well pairs, the water injection time period information of the two wells is extracted, namely the start time and end time of water injection. For example, well A is 10:00–12:00 and well B is 11:00–13:00. Then the water injection time periods of the two wells overlap in the time interval of 11:00–12:00. The judgment method is: if the start and end times of water injection of the two wells intersect on the time axis, then the intersection time period is the water injection time intersection of the well pair. Next, the intersection of the water injection times is bound to the diffusion overlap area identified in step S3 for wells A and B, forming an interference convergence area. This indicates that within this spatial range and time period, there is a convergence risk of synchronous water injection by the two wells, potentially causing stress interference. All suspected interfering well pairs are processed one by one using the above method, ultimately forming a set of interference convergence areas. This set not only accurately locates the spatiotemporal intersection of the well pair interference behavior but also provides accurate data input for subsequent refined quantitative calculations based on interference intensity. Unlike judgments based solely on a single spatial or temporal dimension, this method, through the joint constraint of temporal intersection and spatial overlap, ensures that the interference convergence area has a real physical possibility of interference, avoiding misjudging well pairs with staggered water injection or spatial isolation as resonance risks, thereby effectively improving the accuracy of risk identification.

[0025] In one embodiment, it should be noted that the data involved in the calculation of the gradient index driven by the superimposed water injection field is mainly obtained through a combination of groundwater hydrogeological modeling and historical water injection operation data inversion: First, a groundwater main permeability direction field model of the study area is constructed based on geological exploration and well logging data to clarify the water injection channels and seepage paths of each reinjection well between multiple aquifers; Second, the collected reinjection well operation parameters (such as water injection flow rate, water injection pressure, and wellhead dynamic liquid level) are used for fitting analysis with groundwater monitoring point data (such as microseismic response, ground subsidence monitoring, and water level changes in adjacent wells). The actual water injection path of each well is identified by using numerical inversion algorithms (such as inversion-type seepage simulation), and the coordinates of path nodes are extracted in the model to construct equally spaced path segments. The direction angle and tangent direction vector of the water injection path can be calculated from the spatial coordinate difference between nodes, and the coordinates of the center point of the intersection area are automatically identified by the spatial intersection or minimum distance point of the two reinjection paths. Finally, all the direction angles, direction vectors, path positions and spatial geometric relationships required for calculation can be extracted from the above modeling and inversion results, ensuring that the index calculation is based on the spatiotemporal characteristics of the actual underground water injection structure and has engineering operability.

[0026] It should be noted that the superimposed gradient index of the injection field is used to measure the structural tension relationship between the injection paths of multiple reinjection wells in a certain interference convergence area along the main underground seepage direction. Specifically, it reflects whether these paths form a cross-driving pattern with high convergence and low synergy in the convergence area. Its essence is a measure of the degree of potential stress superposition and concentration. The larger the index, the more the injection path directions of the two reinjection wells at the convergence point tend to converge (i.e., the direction angle is smaller, and the flow converges). However, the disturbance trends within their respective paths (represented by the local path direction angle changes) are significantly different, and the synergy is low. This combination of convergent injection of structural tension and trend misalignment can easily form an unsustainable injection stress concentration state in the convergence area, thereby inducing sudden changes in osmotic pressure, hydraulic fracture deflection, or regional hydraulic short circuit. For example, if two wells inject water in almost parallel directions (with a small angle between their direction vectors) near their intersection area, but their paths contain varying degrees of broken lines (e.g., well A's path is relatively gentle, while well B's path has abrupt changes), this can lead to frequent fluctuations in injection pressure and unstable driving direction in the local area, thus forming a core zone of stress superposition and intensified disturbance. Therefore, when the gradient exponent increases due to the superposition of the injection field, it means that the area has a strong potential for concentrated disturbance and is a key area of ​​concern for the risk of mutual interference during later reinjection. It needs to be identified and warned of in the early analysis stage.

[0027] It should be noted that the core advantage of calculating the superimposed gradient exponent of the water injection field using the above method lies in its simultaneous consideration of the directional geometric characteristics of the water injection path within the interference convergence region (i.e., the degree of convergence) and the introduction of local inconsistency information of the path disturbance trend (i.e., synergy). Both are achieved through quantitative calculation of spatial vector relationships and path structural changes, avoiding the one-dimensional defects of traditional methods that rely solely on path angles or distance metrics to roughly assess the disturbance trend. Specifically, the ratio of the magnitude of the difference in the directional vectors to the magnitude of the sum can characterize whether the two paths exhibit convergence, offsetting, or deviation at the intersection point, reflecting whether the water injection vectors have a convergence trend in structure. The difference between the magnitudes of the disturbance directions can reveal the difference in the severity of the changes in the broken lines of the path segments. Its reciprocal form means that the more consistent the disturbance, the greater the synergy value, thereby suppressing meaningless resonance judgments. Finally, using the relative difference between convergence and synergy, rather than their absolute magnitude, as the exponent input effectively avoids the instability caused by local numerical amplification or scaling.

[0028] It should be noted that the various calculation data involved in the calculation of the potential differential pressure cyclone channel index mainly come from the fusion analysis results of the actual operation data and geological modeling data of the high-salinity mine water injection monitoring system. Specifically, the geometric center of the interference intersection area and the direction of the water injection path required for selecting the path point set can be obtained from the well network layout map, water injection monitoring logs, and underground seepage characteristic model. The direction of the water injection path is determined by combining the well location coordinates and seepage simulation results. The unit distance is set according to the actual modeling grid scale, and the path point coordinates are generally extracted from the water injection path grid profile output by geological modeling software such as Petrel and Surfer. The coordinates of the path point set required for constructing local three-point segments can be directly extracted from the above path point list. The spatial vector of the line connecting the three points is calculated by the three-dimensional coordinate difference. The angle calculation in the rotation change value is based on the cosine formula between vectors. All angle transformation and normalization processing is performed based on standard geometric transformation. The main seepage direction comes from the existing groundwater dynamics modeling results in the well area. It is usually determined by the direction of the pressure difference contour line or the hydraulic head gradient field, which is clearly given in the modeling tool. The angle calculation of the path connecting the cycloid points requires calling the measurement tool in the GIS or CAD system to obtain the deflection degree between the main seepage axis and the cycloid.

[0029] It should be noted that the Potential Differential Pressure Cyclone Channel Index is a quantitative indicator used to measure the enhanced coupling trend between path cyclone anomalies and differential pressure propagation direction in the interference convergence area between underground reinjection wells. Its core purpose is to determine whether a cyclone-like or vortex-type differential pressure retention structure is likely to form within this area. The essence of this index lies in the integrated assessment of the degree of cyclone disturbance and the consistency of directional deviation of two reinjection paths in spatial orientation. If the paths simultaneously exhibit strong cyclone abrupt changes (sudden changes in path direction) and significant inconsistencies in propagation direction in certain areas, it indicates that the area is highly likely to experience a hydrodynamic differential pressure cyclone phenomenon. That is, the differential pressures transmitted by different paths overlap and interfere with each other in space, causing the differential pressure to be unable to diffuse effectively and resulting in retention. This significantly enhances the local interference effect and may even form a continuous pressure disturbance backflow zone during the reinjection process, thereby affecting the pressure balance and diffusion efficiency of the entire system. For example, in a region where disturbances converge, two paths should diffuse in parallel. However, due to geological structure or insufficient control of the water injection path, significant differences in vortex direction and shifts in the angle of propagation direction occur. This structure easily induces a vortex-like structure, causing the injected water flow to oscillate repeatedly locally, forming a pressure differential vortex zone. This, in turn, enhances the persistence of the disturbance and the local risk. Therefore, the larger the potential pressure differential vortex channel index, the more significant the difference in vortex direction disturbance and path propagation. This means that the region is more likely to experience nonlinear diffusion or disturbance transmission behavior dominated by non-target paths. This disturbance behavior deviates from the expected diffusion model, thus causing non-target-dependent effects on the system. In other words, the path assumptions in the model prediction process no longer hold, and control strategies are prone to failure, leading to control results deviating from the target. Therefore, the larger the index, the higher the dependence of the current region on water injection behavior and non-target disturbance paths generated by model predictions, and the greater the risk.

[0030] It should be noted that the advantage of calculating the potential differential pressure cyclone channel index using the above method is that it can accurately identify the local differential pressure accumulation trend caused by multi-path non-cooperative propagation in the interference convergence area by starting from the coupling of detailed changes in path structure and directional differences. Compared with the traditional evaluation method based solely on path length, path overlap ratio, or geometric distance, this method introduces a joint consideration mechanism of cyclone change value and path offset degree. It can not only capture the small deflection between paths in local direction, but also measure whether this deflection has produced substantial offset and distortion in the propagation direction, thus constructing a more physically meaningful cyclone distortion intensity. In addition, the identification of candidate cyclone points is based on the threshold screening mechanism of normalized cyclone difference value, which can effectively avoid misjudging weak disturbances as high-risk structures. The final index fusion step adopts the reverse residual product fusion strategy. This mechanism has a stronger coupling enhancement identification ability than the traditional weighted summation method. That is, when multiple cyclone points all show high distortion intensity, their superposition effect will be amplified exponentially, which is closer to the dynamic evolution process of multi-path interference mutually reinforcing each other and causing differential pressure retention in reality.

[0031] In one embodiment, it should be noted that in step S6, by quantifying the interference intensity of all interference convergence areas, the system stability and interference risk of the entire well area under the current reinjection method are comprehensively evaluated, and the engineering feasibility and safety of the method are ultimately determined. Specifically, firstly, the interference intensity value corresponding to each interference convergence area needs to be extracted. This value has been calculated in the previous steps using multi-dimensional indicators such as the degree of convergence of water injection paths, disturbance synergy, and pressure differential cyclicity, reflecting the potential disturbance coupling intensity of each local area under the current water injection configuration. Subsequently, the system summarizes these interference intensity values. The first step is to calculate its average value, that is, the sum of the interference intensity values ​​of all convergence areas divided by the total number of convergence areas, to obtain the overall average interference level. The second step is to calculate the standard deviation of the interference intensity, that is, the square of the difference between each interference intensity value and the average value. These squared values ​​are accumulated and divided by the number of convergence areas, and then the square root is taken. The resulting standard deviation reflects the uniformity of the distribution of interference values ​​among the regions. The larger the standard deviation, the more significant the local interference concentration. The mean and standard deviation are added together to obtain a fusion index, namely the resonance risk index. The larger the value, the stronger the overall disturbance and the greater the risk of local resonance under the current reinjection method. The system sets a resonance risk threshold based on historical operating experience, field tests, or structural bearing capacity limits. The calculated resonance risk index is compared with this threshold. If the value is not higher than the threshold, it means that the overall system disturbance under this configuration is controllable and reasonably distributed. The current reinjection method is then considered as the final operating configuration for the target area and no further adjustment is needed. If the resonance risk index exceeds the threshold, it means that the current configuration has a significant risk of amplified disturbance and does not have the stability and safety for long-term operation. In this case, the reinjection method needs to be reset, including but not limited to adjusting the combination of injection wells, changing the injection time schedule, modifying injection pressure or flow parameters, and even partially closing some easily resonant wells. The resonance risk index is then recalculated according to the aforementioned process until it falls into the safe range. Only then can the new configuration be considered to have acceptable underground reinjection capability. For example, if an assessment reveals six intersecting interference zones with interference intensities of 0.30, 0.32, 0.29, 0.35, 0.31, and 0.80, respectively, and the calculated average is 0.395 with a standard deviation of 0.18, then the resonance risk index is 0.575. If the on-site threshold is 0.50, the current configuration is deemed unqualified and requires optimization. After optimization, if the strong interference zone's intensity decreases to 0.40 due to time and pressure adjustments, the resonance risk index drops to 0.45, and the configuration is deemed acceptable. This mechanism not only achieves a unified assessment of reinjection safety from both overall and local perspectives but also enables dynamic assessment of the "reinjectability capability" defined in the current scheme.

[0032] Based on the same inventive concept, this invention also provides a risk assessment system for groundwater reinjection in high-mineralization mines, comprising: Sequence module: Based on the water injection behavior data of each reinjection well in the target area under the current reinjection mode, it forms the water injection rhythm sequence of each reinjection well; Rhythm Difference Module: Calculates the difference in water injection rhythm between any two reinjection wells based on the water injection rhythm sequence; Suspected interference module: Obtain the water diffusion range of each reinjection well and filter the set of suspected interference well pairs based on the difference in water injection rhythm; Interference convergence module: For suspected interfering well pairs, extract the intersection of water injection time of each well pair in the diffusion overlap area to form an interference convergence area set; Interference Intensity Module: Calculates the interference intensity value of each intersection region based on the state information of each intersection region in the interference intersection region set; Evaluation module: Summarizes the interference intensity values ​​of each intersection area to obtain the resonance risk index, and evaluates whether the target area's re-injection capability is qualified under the current re-injection method based on preset thresholds.

[0033] This invention provides a risk assessment system for groundwater reinjection in high-mineralization mines. By constructing an injection rhythm sequence, analyzing rhythm differences, and examining the overlap of diffusion ranges, it effectively identifies potential interfering well pairs. Interference convergence areas are formed by extracting the intersection of injection times, and the interference intensity is quantified by considering factors such as pressure changes, flow fluctuations, and overlap duration. This results in a resonance risk index, which is used to evaluate the reinjectability of the target area under the current reinjection method. This method overcomes the limitations of existing evaluations based on single-well static parameters. It can identify and assess the regional stress superposition and propagation risks caused by differences in injection volume, frequency, and rhythm control in complex conditions where multiple reinjection wells share the same aquifer system. This effectively avoids latent stress interference resonance problems such as runaway permeability, boundary pressure breakthroughs, and well area anomalies caused by multi-well coordinated injection, providing more reliable risk assessment support for high-mineralization mine water reinjection projects.

[0034] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention should still fall within the scope of the claims of the present invention.

Claims

1. A method for risk assessment of groundwater reinjection in high-salinity mines, characterized in that, Includes the following steps: Based on the water injection behavior data of each reinjection well in the target area under the current reinjection mode, a water injection rhythm sequence for each reinjection well is formed; Calculate the difference in water injection rhythm between any two reinjection wells based on the water injection rhythm sequence. Obtain the water diffusion range of each reinjection well, and filter out a set of suspected interfering well pairs based on the difference in water injection rhythm; For suspected interfering well pairs, the intersection of water injection times of each well pair in the diffusion overlap area is extracted to form an interference convergence area set; Based on the state information of each intersection region in the set of interference intersection regions, calculate the interference intensity value of each intersection region; The interference intensity values ​​of each intersection area are summarized to obtain the resonance risk index, and the re-injection capability of the target area under the current re-injection method is evaluated according to the preset threshold.

2. The method for risk assessment of groundwater reinjection in high-salinity mines according to claim 1, characterized in that, The steps for calculating the difference in water injection rhythm between any two reinjection wells based on the water injection rhythm sequence are as follows: Align the water injection rhythm sequence of each reinjection well with a uniform time step to construct a water injection status time sequence for each reinjection well. Each time step includes a water injection status marker, corresponding flow rate value, and pressure value. For any two reinjection wells, extract the water injection behavior vector corresponding to the same time step in their water injection state time series, and calculate the behavior difference value for each time step. The behavior difference value consists of three items: water injection difference, flow rate difference, and pressure difference. The behavioral difference values ​​at each time step are accumulated over the entire time series to obtain the difference in water injection rhythm between the two corresponding reinjection wells.

3. The method for risk assessment of groundwater reinjection in high-salinity mines according to claim 1, characterized in that, The steps for screening suspected interfering well pairs are as follows: Obtain the water diffusion boundary of each reinjection well, and construct the corresponding diffusion circular area with the wellhead as the center; For any two reinjection wells, determine whether their diffusion circular regions overlap spatially. If they overlap, mark them as having overlapping diffusion ranges. Extract the rhythm difference value of each well pair, and include well pairs that simultaneously meet the conditions of having a rhythm difference value less than the rhythm difference threshold and having overlapping diffusion ranges into the set of suspected interference well pairs.

4. The method for risk assessment of groundwater reinjection in high-salinity mines according to claim 1, characterized in that, For a set of suspected interfering well pairs, the steps to extract the intersection of water injection times for each well pair within the diffusion overlap area and form a set of interfering convergence areas are as follows: For any well pair in the set of suspected interfering well pairs, extract the water injection time period information for each well, which includes the water injection start time and the water injection end time. Determine whether there is an overlapping time interval on the water injection time axis for this group of well pairs. If there is an overlap, determine that the overlapping time interval is the intersection of the water injection time of the corresponding well pairs. The intersection of water injection times is associated with the diffusion overlap area corresponding to the well pair, and bound as an interference convergence area; Repeat the operation on all suspected interfering well pairs to form a set of interfering convergence areas.

5. The method for risk assessment of groundwater reinjection in high-salinity mines according to claim 1, characterized in that, The steps for calculating the interference intensity value of each intersection region based on the state information within the interference intersection region set are as follows: Calculate the superimposed driving gradient index and potential differential pressure cyclone channel index of the injection field in each intersection region of the interference intersection region set. Add the superimposed driving gradient index and potential differential pressure cyclone channel index of the injection field to obtain the interference intensity value of each intersection region.

6. The method for risk assessment of groundwater reinjection in high-salinity mines according to claim 5, characterized in that, The calculation steps for the gradient exponent driven by the superposition of the water injection field are as follows: For the two reinjection wells corresponding to the interference convergence area, the water injection path in the main underground seepage direction is extracted respectively, and three consecutive reference points are selected at equal intervals in each path to form two consecutive water injection path segments. For each injection path segment corresponding to each of the two reinjection wells, calculate the difference in direction angles between the two segments in each injection path, divide the absolute value of the difference in direction angles by two, and obtain the local disturbance direction amplitude of the injection path segment of the corresponding reinjection well. Using the center point of the intersection area as a reference point, calculate the direction vector formed by the tangent directions of the water injection paths of the two reinjection wells at the reference point, and calculate the magnitude of the difference between the two direction vectors, which is recorded as the first magnitude value. Calculate the magnitude of the sum between the two direction vectors, which is recorded as the second magnitude value. Divide the first magnitude value by the second magnitude value, and use the ratio as the degree of convergence of the water injection paths of the two wells at the intersection point. Calculate the absolute value of the difference between the amplitudes of the local disturbance directions of the two water injection paths, and take the reciprocal of the absolute value of the difference plus one as the synergy value of the water injection paths of the two wells in terms of disturbance trend; The absolute difference between the convergence degree value and the synergy value of the water injection path is used as the numerator, and the sum of the absolute difference between the convergence degree value and the synergy value of the water injection path and the value of 1 is used as the denominator to obtain the superimposed driving gradient index of the water injection field.

7. The method for risk assessment of groundwater reinjection in high-salinity mines according to claim 5, characterized in that, The calculation steps for the potential differential pressure cyclone index are as follows: Using the geometric center of each interference convergence area as a reference point, the path is extended evenly from the center of the convergence area to both sides along the water injection path of the first reinjection well and the second reinjection well, with a path point set at every unit distance until it exceeds the boundary of the convergence area, thus forming the first path point set and the second path point set respectively. In the first set of path points and the second set of path points, each set of three adjacent path points forms a local path segment, forming multiple consecutive three-point segment structures. Each three-point segment represents the local direction of the path in that segment. For each three-point segment, first calculate the spatial direction vectors of the two segments before and after, then calculate the angle between the two vectors, and divide the angle by 180 to obtain the standardized rotation change value. Compare the rotation change values ​​of the three point segments at corresponding positions in the first path point set and the second path point set one by one. For each pair of positions, calculate the absolute value of the difference between the rotation change values ​​of the two paths and record it as the rotation difference value of the pair of path segments. Then divide the rotation difference value by the sum of the rotation change values ​​of the two paths plus one to obtain the normalized rotation difference value, forming a rotation difference sequence. The potential differential pressure cyclone channel index is calculated based on the cyclone difference sequence.

8. The method for risk assessment of groundwater reinjection in high-salinity mines according to claim 7, characterized in that, The steps for calculating the potential differential pressure cyclone channel index based on the rotational difference sequence are as follows: In the rotational difference sequence, all positions with normalized rotational difference values ​​greater than 0.4 are selected and identified as candidate path points with potential differential pressure cyclicity trends, forming a candidate cyclicity point set; For each candidate gyroscope point, two reinjection wells are connected to the point to construct two differential pressure propagation paths. The angle between these two paths and the main permeation direction of the interference intersection area is calculated, and the angle value is divided by 180 to obtain the standardized path offset value. The absolute value of the difference between the offset values ​​of the two paths is then divided by the sum of the two and one to obtain the degree of path propagation difference of the gyroscope point. Multiply the normalized rotation direction difference value of each candidate cyclone point by the path propagation difference degree to obtain the cyclone twist factor at that location; then divide the product value by the product value plus one to obtain the cyclone twist intensity value of each cyclone point. For each cyclone torsion intensity value, subtract the value from it to obtain the inverse residual term. Multiply all the inverse residual terms in sequence to obtain the product. Subtract the product from it to obtain the potential differential pressure cyclone channel index.

9. The method for risk assessment of groundwater reinjection in high-salinity mines according to claim 1, characterized in that, The steps for summarizing the interference intensity values ​​of each intersection area to obtain the resonance risk index, and evaluating whether the re-injection capability of the target area under the current re-injection method is qualified according to the preset threshold are as follows: Calculate the average interference intensity value and the standard deviation of the interference intensity value based on the interference intensity values ​​of all intersection areas; The resonance risk index is obtained by adding the average interference intensity value to the standard deviation value. The resonance risk index is compared with the preset threshold. If the resonance risk index is not greater than the preset threshold, the target area is qualified for reinjection under the current reinjection method. The current reinjection method is directly used as the final reinjection method for each high-mineralization mine water in the target area. If the resonance risk index is greater than the preset threshold, the target area is not qualified for re-injection under the current re-injection method. The re-injection method will be reset until the re-injection capability corresponding to the re-injection method is qualified.

10. A risk assessment system for groundwater reinjection in high-salinity mines, used to implement the risk assessment method for groundwater reinjection in high-salinity mines as described in any one of claims 1-9, characterized in that, The system includes: Sequence module: Based on the water injection behavior data of each reinjection well in the target area under the current reinjection mode, it forms the water injection rhythm sequence of each reinjection well; Rhythm Difference Module: Calculates the difference in water injection rhythm between any two reinjection wells based on the water injection rhythm sequence; Suspected interference module: Obtain the water diffusion range of each reinjection well and filter the set of suspected interference well pairs based on the difference in water injection rhythm; Interference convergence module: For suspected interfering well pairs, extract the intersection of water injection time of each well pair in the diffusion overlap area to form an interference convergence area set; Interference Intensity Module: Calculates the interference intensity value of each intersection region based on the state information of each intersection region in the interference intersection region set; Evaluation module: Summarizes the interference intensity values ​​of each intersection area to obtain the resonance risk index, and evaluates whether the target area's re-injection capability is qualified under the current re-injection method based on preset thresholds.

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