Coupling prediction method and terminal equipment based on existing tunnel inversion of water inflow

Abstract

This invention discloses a coupled prediction method and terminal equipment for water inflow based on the inversion of existing tunnels, belonging to the field of water conservancy and hydropower engineering technology. It can solve the problem that existing water inflow prediction methods cannot achieve dynamic and accurate assessment of the total water inflow during the phased construction of tunnel groups. The method includes: S1, determining all associated tunnels of the tunnel to be predicted, and selecting one tunnel with a stable decreasing water inflow as the existing tunnel, and the remaining tunnels as the preceding tunnels; S2, determining the equivalent permeability coefficient of the rock mass of the existing tunnel, and determining the first maximum water inflow of the tunnel to be predicted and the second maximum water inflow of the preceding tunnels; S3, constructing the first decreasing water inflow function of the existing tunnel and the second decreasing water inflow function of the preceding tunnels; S4, determining the predicted value of the total water inflow of the tunnel to be predicted at the prediction time based on the first decreasing water inflow function, the second decreasing water inflow function, and the first maximum water inflow. This invention is used for tunnel water inflow prediction.

Description

Technical Field

[0001] This invention relates to a coupled prediction method and terminal equipment for water inflow based on the inversion of existing tunnels, belonging to the field of water conservancy and hydropower engineering technology. Background Technology

[0002] Tunnel complexes are a core construction form for major projects such as water conservancy and hydropower, long-distance water conveyance, mountain-crossing transportation, and mine roadways. Water inrush hazards are a key risk factor restricting construction safety, schedule, and project cost. Accurate water inrush volume prediction is the technical basis for water inrush prevention, drainage optimization, and grouting scheme formulation. Currently, domestic and international water inrush volume prediction methods are mainly divided into three categories: empirical formula methods (such as Dupuit formula, Forchheimer formula, and methods by Hiroshi Oshima and Honmei Sato), which are simple in form and quick to calculate; numerical simulation methods can characterize complex seepage fields, but require high parameter accuracy and modeling workload; and engineering analogy methods rely on existing databases and are limited by the similarity of projects.

[0003] The existing methods for predicting water inflow have the following common technical bottlenecks: (1) They rely on borehole pumping tests or indoor rock sample tests to obtain permeability parameters, which can only reflect the permeability characteristics of a limited range around the borehole or at the scale of rock blocks. They are difficult to characterize the spatial variation characteristics of permeability at the scale of tens to hundreds of meters along the exploration tunnel and the tunnel. For heterogeneous rock masses that pass through multi-lithological zones, structural fracture zones, and densely jointed zones, the use of a single equivalent permeability coefficient cannot distinguish the seepage contribution of each geological unit, which leads to the prominent problem of "using points to represent the surface" and significant prediction errors. (2) The prediction of attenuated water inflow relies on idealized theoretical models. For example, Sato's attenuation formula is based on the assumption of homogeneous, isotropic, and continuous porous media, which cannot be adapted to the heterogeneity of actual rock masses and the dynamic changes in drainage conditions during construction. A large amount of field measurement data shows that there is a systematic deviation between the theoretical prediction curve and the actual attenuation curve, and the engineering applicability is insufficient. (3) The existing “single tunnel prediction” paradigm is based on the calculation of natural constant groundwater level. It neither quantifies the cumulative dewatering effect of the drainage of the preceding tunnel on the regional groundwater potential energy field, nor clarifies the dynamic superposition relationship of water inflow caused by the difference in construction sequence. It cannot characterize the hydrological synergy effect under the condition of multi-tunnel collaborative construction, which leads to the systematic overestimation of the water inflow of the subsequent tunnel due to the neglect of the previous dewatering and drawdown. Therefore, it is impossible to achieve dynamic and accurate assessment of the total water inflow of the tunnel group in stages of construction. Summary of the Invention

[0004] This invention provides a coupled prediction method and terminal equipment for water inflow based on the inversion of existing tunnels, which can solve the problem that existing water inflow prediction methods cannot achieve dynamic and accurate assessment of the total water inflow during the phased construction of tunnel groups.

[0005] On the one hand, the present invention provides a coupled prediction method for water inflow based on the inversion of existing tunnels, the method comprising:

[0006] S1. Determine all associated tunnels of the tunnel to be predicted, and select one tunnel with a stable decrease in water inflow from the associated tunnels as the existing tunnel, and the remaining tunnels as the preliminary tunnels.

[0007] S2. Based on the geometric parameters and stable inflow of the existing tunnel, determine the equivalent permeability coefficient of the rock mass of the existing tunnel, and based on the equivalent permeability coefficient of the rock mass, determine the first maximum inflow of the tunnel to be predicted and the second maximum inflow of the tunnel in advance.

[0008] S3. Based on the water inflow monitoring sequence of the existing tunnel, construct a first attenuated water inflow function for the existing tunnel, and based on the first attenuated water inflow function and the second maximum water inflow, construct a second attenuated water inflow function for the pilot tunnel.

[0009] S4. Determine the predicted total inflow of the tunnel to be predicted at the prediction time based on the first attenuated inflow function, the second attenuated inflow function, and the first maximum inflow.

[0010] Optionally, determining the equivalent permeability coefficient of the rock mass of the existing tunnel based on its geometric parameters and stable inflow rate in step S2 specifically includes:

[0011] Continuous hydrological monitoring is performed on the existing tunnel, and the total inflow volume when the fluctuation range of the total inflow volume of the existing tunnel is less than a preset threshold within a preset time period is taken as the stable inflow volume.

[0012] Substituting the geometric parameters of the existing tunnel and the stable inflow rate into the empirical formula of the Oshima Hiroshi method, the equivalent permeability coefficient of the rock mass of the existing tunnel is obtained by inversion.

[0013] Optionally, in step S2, determining the first maximum inflow of the tunnel to be predicted and the second maximum inflow of the tunnel under construction based on the equivalent permeability coefficient of the rock mass specifically includes:

[0014] The first distance between the groundwater level and the bottom of the tunnel to be predicted and the second distance between the groundwater level and the bottom of the tunnel under the drainage and dewatering effect are determined respectively;

[0015] Substituting the first distance, the equivalent permeability coefficient of the rock mass, and the cross-sectional radius of the tunnel to be predicted into the empirical formula of the Oshima Hiroshi method, the first maximum inflow of the tunnel to be predicted is obtained.

[0016] Substituting the second distance, the equivalent permeability coefficient of the rock mass, and the cross-sectional radius of the pilot tunnel into the empirical formula of the Oshima Hiroshi method, the second maximum inflow of the pilot tunnel is obtained.

[0017] Optionally, the first distance between the groundwater level and the bottom of the tunnel to be predicted and the second distance between the groundwater level and the bottom of the tunnel under drainage are determined, specifically including:

[0018] The first cumulative drawdown depth of the tunnel to be predicted and the second cumulative drawdown depth of the tunnel under the drainage and dewatering action are determined respectively.

[0019] The first distance between the groundwater level and the bottom of the tunnel to be predicted is determined based on the first cumulative drawdown, and the second distance between the groundwater level and the bottom of the tunnel to be constructed is determined based on the second cumulative drawdown.

[0020] Optionally, in step S3, constructing a first attenuated inflow function for the existing tunnel based on the existing tunnel's inflow monitoring sequence specifically includes:

[0021] Using time as the independent variable and the measured water inflow as the dependent variable, the water inflow monitoring sequence of the existing tunnel is fitted with a natural exponential function to obtain the first decaying water inflow function of the existing tunnel.

[0022] Optionally, in step S3, constructing the second attenuation inflow function of the pilot tunnel based on the first attenuation inflow function and the second maximum inflow specifically includes:

[0023] Extract the attenuation coefficient of the first attenuated inflow function;

[0024] Using the second maximum inflow rate as the initial amplitude parameter, and utilizing the attenuation coefficient and the initial amplitude parameter, a second attenuated inflow rate function in the form of a natural exponential function is constructed.

[0025] Optionally, S4 specifically includes:

[0026] Based on the first attenuation inflow function, calculate the first attenuation inflow prediction value of the existing tunnel at the predicted time, and based on the second attenuation inflow function, calculate the second attenuation inflow prediction value of the preceding tunnel at the predicted time.

[0027] Calculate the sum of the first attenuated inflow prediction value, the second attenuated inflow prediction value, and the first maximum inflow, and use the sum as the total inflow prediction value of the tunnel to be predicted at the prediction time.

[0028] Optionally, determining the equivalent permeability coefficient of the rock mass of the existing tunnel based on its geometric parameters and stable inflow rate in step S2 specifically includes:

[0029] The existing tunnel is divided into multiple first geological sections according to geological conditions, and the stable water inflow of each first geological section is determined.

[0030] Based on each stable inflow rate and the geometric parameters of the existing tunnel, the equivalent permeability coefficient of the rock mass corresponding to the first geological section is determined.

[0031] Optionally, in step S2, determining the first maximum inflow of the tunnel to be predicted and the second maximum inflow of the tunnel under construction based on the equivalent permeability coefficient of the rock mass specifically includes:

[0032] The tunnel to be predicted is divided into multiple second geological sections according to geological conditions, and the tunnel in advance is divided into multiple third geological sections according to geological conditions. The first geological section, the second geological section and the third geological section correspond one-to-one.

[0033] Based on the equivalent permeability coefficient of the rock mass in each first geological section, the water inflow of the first section corresponding to the second geological section and the water inflow of the second section corresponding to the third geological section are determined respectively.

[0034] The sum of the water inflow of the first section of all second geological sections is taken as the first maximum water inflow of the tunnel to be predicted, and the sum of the water inflow of the second section of all third geological sections is taken as the second maximum water inflow of the tunnel to be constructed.

[0035] On the other hand, the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the inflow coupling prediction method based on existing tunnel inversion as described above.

[0036] The beneficial effects that this invention can produce include:

[0037] The present invention provides a coupled prediction method for water inflow based on the inversion of existing tunnels. By reusing existing exploration tunnels as test carriers, using stable water inflow to invert the equivalent permeability coefficient of the rock mass, and relying on the measured data of existing tunnels within the same hydrogeological unit, an exponential decay function is fitted and an analogy is used to construct a prior tunnel decay model. Based on the actual field patterns, the method extrapolates and predicts, which greatly improves the engineering adaptability and reliability of the water inflow prediction.

[0038] This invention provides a novel method for coupled prediction of water inflow based on existing tunnel inversion, employing a "segmented isolation monitoring method." Monitoring sections are established in different geological zones within the exploration tunnel (i.e., the existing tunnel) to independently measure the water inflow in each section and invert the equivalent permeability coefficient of the rock mass corresponding to that geological zone. This allows for precise zonal assignment of key parameters, solving the problem of "representing the whole by a single point," and achieving precise zonal matching and assignment of the equivalent permeability coefficient of the rock mass with geological conditions, effectively improving the spatial accuracy of water inflow prediction for heterogeneous rock masses. Simultaneously, this invention introduces the concept of dynamic drainage water level, quantifies the cumulative drawdown of the preceding tunnel, determines the actual head conditions of the subsequent construction tunnel, overcomes the limitations of calculating natural constant head, and achieves accurate prediction of the initial maximum water inflow. Attached Figure Description

[0039] Figure 1 A flowchart of the inflow volume coupling prediction method based on existing tunnel inversion provided in an embodiment of the present invention;

[0040] Figure 2 This is a schematic diagram of water inflow monitoring in the geological exploration tunnel of the Shanshan pumped storage power station, provided as an embodiment of the present invention. Detailed Implementation

[0041] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0042] This invention provides a coupled prediction method for water inflow based on the inversion of existing tunnels, such as... Figure 1 As shown, the method includes:

[0043] S1. Determine all associated tunnels of the tunnel to be predicted, and select one tunnel with a stable decrease in water inflow from the associated tunnels as the existing tunnel, and the remaining tunnels as the pilot tunnels.

[0044] The exploration tunnel, which has already been excavated during the feasibility study phase of the hydropower project, is used as an existing tunnel, eliminating the need for excavating additional test tunnels. This exploration tunnel, along with the existing tunnel and the tunnel to be predicted, belongs to the same hydrogeological unit, thus ensuring good comparability in terms of stratum permeability characteristics and hydrogeological boundary conditions.

[0045] S2. Based on the geometric parameters and stable inflow of the existing tunnel, determine the equivalent permeability coefficient of the rock mass of the existing tunnel, and based on the equivalent permeability coefficient of the rock mass, determine the first maximum inflow of the tunnel to be predicted and the second maximum inflow of the tunnel to be constructed.

[0046] S2 determines the equivalent permeability coefficient of the rock mass of the existing tunnel based on its geometric parameters and steady inflow rate, specifically including:

[0047] (1) Conduct continuous hydrological monitoring of existing tunnels, and take the total water inflow of existing tunnels when the fluctuation range of total water inflow within a preset time period is less than the preset threshold as the stable water inflow.

[0048] (2) Substitute the geometric parameters and steady inflow of the existing tunnel into the empirical formula of the Oshima Hiroshi method to obtain the equivalent permeability coefficient of the rock mass of the existing tunnel.

[0049] The preset duration and preset threshold mentioned above are pre-set values, which can be set by those skilled in the art according to actual conditions. This embodiment of the invention does not limit these settings. For example, the preset duration can be 24 hours; the preset threshold can be 5%.

[0050] In practical applications, existing tunnels can be renovated in a standardized manner first: remove silt and deposits on the tunnel floor and sidewalls; conduct a comprehensive investigation of tunnel wall seepage characteristics and accurately mark key seepage exposure locations such as structural fracture zones and densely jointed zones; set up dynamic water level monitoring points at key hydrogeological sections inside the tunnel to obtain the benchmark monitoring parameters required for subsequent calculations.

[0051] The system maps the spatial locations of all water inflow points within the exploration tunnel (i.e., the existing tunnel), and records the seepage patterns (including concentrated streams, fissure seepage, and saturation surfaces). Water inflow monitoring devices are installed at each water inflow point, and a standard measuring weir is constructed at the main drainage channel at the tunnel entrance. Continuous hydrological monitoring is conducted; after the total water inflow fluctuation within the tunnel is less than 5% for 24 hours, the total water inflow of the tunnel under this stable state is recorded. As a stable inflow rate, it is also the core input data for subsequent parameter inversion.

[0052] According to the "Specifications for Hydrogeological Investigation of Hydropower Projects" (NB / T 10236-2019), the obtained stable inflow rate will be... Combining the key geometric parameters of the exploration tunnel (including the distance from the groundwater level to the bottom of the tunnel under natural conditions) Cross-sectional radius Substituting the values ​​into the empirical formula of the Oshima method, the equivalent permeability coefficient of the rock mass within the controlled area of ​​the exploration tunnel was obtained through inversion calculation. This coefficient comprehensively characterizes the overall permeability of the surrounding rock of the tunnel.

[0053] The empirical formula for the above-mentioned Oshima Hiroshi method is expressed as follows:

[0054] ;

[0055] in, This represents the maximum flow rate. This is the conversion factor, typically taken as 0.86; The rock mass permeability coefficient; This is the distance from the groundwater level to the bottom of the tunnel. The cross-sectional radius; The diameter of the cross section. .

[0056] In S2, the first maximum inflow rate of the tunnel to be predicted and the second maximum inflow rate of the tunnel to be constructed are determined based on the equivalent permeability coefficient of the rock mass, respectively. Specifically, this includes:

[0057] (1) Determine the first distance between the groundwater level and the bottom of the tunnel to be predicted and the second distance between the groundwater level and the bottom of the tunnel under the drainage and dewatering action.

[0058] Specifically: First, determine the first cumulative drawdown of the tunnel to be predicted and the second cumulative drawdown of the tunnel under the drainage and dewatering action; then, determine the first distance between the groundwater level and the bottom of the tunnel to be predicted based on the first cumulative drawdown, and determine the second distance between the groundwater level and the bottom of the tunnel under the second cumulative drawdown based on the second cumulative drawdown.

[0059] (2) Substitute the first distance, the equivalent permeability coefficient of the rock mass and the cross-sectional radius of the tunnel to be predicted into the empirical formula of the Oshima Hiroshi method to obtain the first maximum inflow of the tunnel to be predicted.

[0060] (3) Substitute the second distance, the equivalent permeability coefficient of the rock mass and the cross-sectional radius of the tunnel into the empirical formula of the Oshima method to obtain the second maximum inflow of the tunnel.

[0061] In the initial stage after tunnel excavation, the free face of the tunnel wall is formed, and the groundwater stored in the surrounding rock is rapidly released into the tunnel under the action of water head pressure, forming the initial maximum inflow. When predicting the first maximum inflow of the tunnel to be predicted, the drainage and dewatering effect of related tunnels is considered, and the distance from the dynamic groundwater level to the tunnel bottom is used. calculate:

[0062] ;

[0063] ;

[0064] in, The distance from the groundwater level to the bottom of the tunnel during the predicted tunnel excavation under the dewatering effect is the first distance. The predicted depth of the tunnel floor slab; This refers to the depth of the groundwater level under natural conditions. This is the first cumulative dredging and depth reduction; The rate of water level drop; This represents the cumulative drainage time.

[0065] When multiple preceding tunnels exist, the cumulative drawdown is the sum of the drawdowns generated by the independent actions of each associated tunnel:

[0066] ;

[0067] in, This represents the total number of associated tunnels; For the first The rate of water level drop in the associated tunnels; For the first The cumulative drainage time of each associated tunnel.

[0068] The obtained equivalent permeability coefficient of the rock mass First distance and cross-sectional radius By inputting the empirical formula of Hiroshi Oshima's method into the forward calculation, the maximum water inflow of the tunnel to be predicted at the initial stage of excavation is obtained. That is, the first maximum inflow.

[0069] Similarly, the above method can be used to determine the second cumulative drawdown depth of the pilot tunnel and the second distance between the groundwater level and the bottom of the pilot tunnel, thereby predicting the second maximum inflow of water into the pilot tunnel.

[0070] In another embodiment of the present invention, S2 specifically includes:

[0071] (1) Divide the existing tunnel into multiple first geological sections according to the geological conditions, and determine the stable water inflow of each first geological section.

[0072] (2) Determine the equivalent permeability coefficient of the rock mass corresponding to the first geological section based on each stable inflow and the geometric parameters of the existing tunnel.

[0073] (3) The tunnel to be predicted is divided into multiple second geological sections according to the geological conditions, and the tunnel in advance is divided into multiple third geological sections according to the geological conditions. The first geological section, the second geological section and the third geological section correspond one to one.

[0074] (4) Based on the equivalent permeability coefficient of the rock mass in each first geological section, determine the water inflow of the first section corresponding to the second geological section and the water inflow of the second section corresponding to the third geological section.

[0075] (5) The sum of the first section water inflow of all second geological sections shall be taken as the first maximum water inflow of the tunnel to be predicted, and the sum of the second section water inflow of all third geological sections shall be taken as the second maximum water inflow of the tunnel to be constructed.

[0076] In this invention, a segmented isolation monitoring method is adopted for heterogeneous conditions where exploration tunnels traverse multi-lithological zones and structural zones of different grades. Monitoring sections are set up in each typical geological section (such as intact rock mass areas, fractured areas, and fault-affected zones). Based on the monitoring data of each geological section, the equivalent permeability coefficient of the rock mass in the corresponding geological section is determined. , , ...). By accurately assigning values ​​to the equivalent permeability coefficient of the rock mass in different zones, the permeability parameters are highly matched with the geological conditions, solving the parameter value deviation caused by the traditional method of "representing the whole by a point", and significantly improving the spatial accuracy of water inflow prediction in heterogeneous rock masses.

[0077] S3. Based on the existing tunnel's water inflow monitoring sequence, construct the first attenuated water inflow function for the existing tunnel, and based on the first attenuated water inflow function and the second maximum water inflow, construct the second attenuated water inflow function for the pilot tunnel.

[0078] S3 constructs the first attenuation inflow function of the existing tunnel based on the existing tunnel inflow monitoring sequence, specifically including:

[0079] Using time as the independent variable and measured water inflow as the dependent variable, the water inflow monitoring sequence of the existing tunnel is fitted with a natural exponential function to obtain the first decaying water inflow function of the existing tunnel.

[0080] During continuous drainage of the tunnel, without strong external replenishment, the groundwater around the tunnel gradually forms a drawdown cone centered on the tunnel, causing the hydraulic head pressure and hydraulic gradient to continuously decrease, and the inflow rate to exhibit a non-linear decay characteristic. This invention employs a dynamic prediction model driven by measured data to replace traditional theoretical correction terms, as detailed below:

[0081] During the construction and drainage of existing tunnels, the actual water inflow was monitored daily. and corresponding time To construct a standardized and continuous inflow-time measurement sequence (i.e., inflow monitoring sequence). Based on time... The measured inflow rate during the decay period after the existing tunnel reaches its maximum inflow rate is the independent variable. Using the variable as the dependent variable, an exponential function is fitted using a nonlinear regression method to obtain the first decaying inflow function that best suits the actual engineering situation. Its expression is as follows:

[0082] ;

[0083] In the formula, , These are the fitting coefficients. This represents the maximum inflow rate of the existing tunnel. This represents the attenuation coefficient of the existing tunnel.

[0084] S3 constructs a second attenuation inflow function for the pilot tunnel based on the first attenuation inflow function and the second maximum inflow function, specifically including:

[0085] Extract the attenuation coefficient of the first attenuation inflow function;

[0086] Using the second maximum inflow rate as the initial amplitude parameter, and utilizing the attenuation coefficient and the initial amplitude parameter, a second attenuated inflow rate function in the form of a natural exponential function is constructed.

[0087] For the tunnel to be predicted, in the absence of its own measured attenuation data, an attenuation coefficient analogy method is used to construct its attenuation inflow function. The basic assumption is that within the same hydrogeological unit, the attenuation coefficient of the inflow of different tunnels is... Determined by the seepage characteristics of the regional rock mass and the water storage and release mechanism, it can be used as a constant to be transferred within the unit.

[0088] Therefore, the second attenuation inflow function of the preliminary tunnel The expression is as follows:

[0089] ;

[0090] in, This is the second largest inflow volume in the preceding tunnel; The attenuation coefficient of the existing tunnel; This refers to the cumulative decay time of the tunnel from the start of its decay period after breakthrough to the predicted time.

[0091] This model directly extrapolates the measured attenuation law of the same hydrogeological unit, avoiding the bias of blindly using theoretical formulas when there is no measured data, and significantly improving the engineering reliability and applicability of attenuated inflow prediction.

[0092] S4. Based on the first attenuation inflow function, the second attenuation inflow function, and the first maximum inflow, determine the predicted value of the total inflow of the tunnel to be predicted at the prediction time.

[0093] Specifically, it includes:

[0094] Based on the first attenuation inflow function, calculate the predicted value of the first attenuation inflow of the existing tunnel at the predicted time, and based on the second attenuation inflow function, calculate the predicted value of the second attenuation inflow of the preceding tunnel at the predicted time.

[0095] Calculate the sum of the first attenuated inflow prediction value, the second attenuated inflow prediction value, and the first maximum inflow value, and use the sum as the total inflow prediction value of the tunnel to be predicted at the prediction time.

[0096] Considering the hydrological synergistic effects of tunnel group construction: the excavation of tunnels in advance will pre-drain the surrounding rock mass, reduce the potential energy field of regional groundwater, and change the water inflow recharge conditions of adjacent tunnels that are constructed later. In conjunction with the overall project schedule, the excavation sequence and breakthrough nodes of each tunnel are analyzed, and the water inflow attenuation effect caused by the construction sequence is quantified to achieve coupled prediction.

[0097] Taking the coordinated construction of three tunnels as an example, Tunnel A (the existing tunnel) is completed (stable attenuation), Tunnel B (the preceding tunnel) has just been completed (continuous attenuation period), and Tunnel C (the tunnel to be predicted) has just been excavated (initial water inflow is at its maximum). At this time, the predicted total water inflow of Tunnel C is... It can be represented as:

[0098] ;

[0099] in, This represents the maximum inflow rate of Tunnel C (i.e., the first maximum inflow rate). The attenuated inflow rate of tunnel B (determined by the second attenuated inflow rate function). The attenuated inflow rate of tunnel A is determined by the first attenuated inflow rate function.

[0100] In this invention, completed small pilot tunnels and branch tunnels within the engineering area can be selected as verification tunnels. The method described herein is used to retrospectively predict their water inflow, and the predicted values ​​are compared and verified with on-site measurement records. If the prediction error is >20%, the boundary generalization conditions, permeability parameters, attenuation coefficients, etc., in the reverse optimization calculation are adjusted iteratively to make the model parameters fit the actual hydrogeological conditions of the project, ensuring that the prediction results of water inflow for large-scale tunnel groups are accurate and reliable.

[0101] The present invention also provides a specific embodiment, as shown below:

[0102] A pumped-storage power station is located in a complex geological formation. During the feasibility study phase, one exploration tunnel and several boreholes have been excavated. The exploration tunnel construction period is from January to September 2024. It is 1800m long, with a cross-sectional radius of 2.5m, a bottom elevation of 1517m, and a burial depth of 580m. Nearby boreholes revealed a groundwater level at a depth of approximately 350m. Groundwater begins to develop at a depth of 440m in the tunnel, and thereafter, groundwater develops throughout the entire tunnel, mainly in the form of dripping and linear flow, emerging along wide tension fissures and fault zones, with localized pressurized jetting.

[0103] The ventilation and safety tunnel, tailrace tunnel, and exploration adit belong to the same hydrogeological unit, are closely connected hydraulically, and are all within the hydrological influence range of each other. The designed excavation period for the ventilation and safety tunnel is from October 2025 to January 2027, with a bottom elevation of 1485m and a cross-sectional radius of 8m; the designed excavation period for the tailrace tunnel is from May 2026 to December 2027, with a bottom elevation of 1430m and a cross-sectional radius of 7.4m.

[0104] The method for predicting the coordinated inflow of water from a tunnel group, as described in this invention, is used to predict the total inflow of water in the project area when the tailrace tunnel is completed in December 2027, under the condition of parallel operation of the exploration tunnel (i.e., the existing tunnel), the ventilation and safety tunnel (i.e., the pilot tunnel), and the tailrace tunnel (i.e., the tunnel to be predicted). The specific implementation steps are as follows:

[0105] 1. Collection of seepage field characteristics and measurement of flow rate.

[0106] Standardized treatment and seepage field mapping were carried out on the exploration tunnel, and a triangular water measuring weir was set up at the tunnel entrance to monitor the total inflow in real time.

[0107] After the exploration tunnel was excavated and completed in September 2024, continuous steady-state hydrological monitoring was immediately carried out. Once the monitoring results showed that the fluctuation range of the tunnel's water inflow within 24 hours was less than 5%, it was determined that a stable seepage state had been reached, and the stable water inflow of the tunnel was measured. .

[0108] 2. Equivalent permeability coefficient of rock mass inverted based on stable water inflow.

[0109] According to the "Code for Hydrogeological Investigation of Hydropower Projects" (NB / T 10236-2019), the empirical formula of the Oshima Hiroshi method is adopted to determine the stable inflow rate. Distance from groundwater level to the bottom of the tunnel Cross-sectional radius Substituting the parameters into the calculation, the equivalent permeability coefficient of the rock mass within the controlled area of ​​the geological exploration tunnel is obtained by inversion. .

[0110] 3. Maximum water inflow after tunnel excavation predict.

[0111] In this project area, no recharge is considered, and the water inflow is mainly controlled by the drainage and release effect of the surrounding rock.

[0112] 3.1 Prediction of the maximum water inflow in the ventilation and safety tunnel.

[0113] The ventilation and safety tunnel floor elevation is 1485m, corresponding to a burial depth of 612m, and a cross-sectional radius of... The depth is 8m. Drainage in the exploration tunnel began in January 2024 and continued for 22 months until the ventilation and safety tunnel was excavated in October 2025. Monitoring showed that the groundwater level dropped at a uniform rate of 2m / month, with a cumulative drawdown of 44m. The groundwater level depth decreased from the natural 350m to 394m. Therefore, the distance from the groundwater level to the bottom of the tunnel under the drainage effect is... It is 248m. The inversion obtained... , and By inputting the empirical formula of Hiroshi Oshima for forward calculation, the predicted maximum inflow of water into the ventilation and safety tunnel is 5215.38 m³ / (d·km).

[0114] After the ventilation and safety tunnel was excavated, the measured maximum initial water inflow was 5880.5 m³ / (d·km). The deviation between the predicted and measured values ​​was only 11.3%, which is far better than the traditional prediction method (the deviation is usually greater than 20%). This fully verifies the accuracy and engineering applicability of the method of this invention.

[0115] 3.2 Prediction of the maximum inflow of tailrace tunnel.

[0116] The tailrace tunnel has an elevation of 1430m, a corresponding burial depth of 667m, and a cross-sectional radius of... The depth is 8m. By May 2026, when the tailrace tunnel was excavated, the exploration tunnel had been drained for 28 months, with a drawdown depth of 56m; the ventilation and safety tunnel had been drained for 7 months, with a drawdown depth of 14m; the combined drawdown depth of the two tunnels was 70m. Therefore, the groundwater level depth decreased from 350m to 420m due to the drainage effect. The distance from the groundwater level to the bottom of the tunnel is 8m. It is 247m. The inversion obtained... , and By inputting the empirical formula of Hiroshi Oshima's method and conducting forward calculations, the predicted maximum inflow of the tailrace tunnel was found to be 5746.78 m³ / (d·km).

[0117] 4. Reduced water inflow after excavation predict.

[0118] 4.1 Calculation of water inflow attenuation in the exploration tunnel.

[0119] Based on daily monitoring data of the water measuring weir at the entrance of the exploration tunnel, using time The measured inflow rate is the independent variable. Using the monitoring data as the dependent variable, an exponential function was fitted to obtain the water inflow decay function of the geological exploration tunnel. ,refer to Figure 2 As shown, its expression is as follows:

[0120] .

[0121] The exploration tunnel was completed in September 2024 and entered its decay period, which will last until the tailrace tunnel is completed in December 2027. Substituting the values ​​into the attenuation function, we obtain the attenuated inflow rate at that moment. .

[0122] 4.2 Calculation of water inflow attenuation in ventilation and safety tunnel.

[0123] The ventilation and safety tunnel uses the same measured attenuation coefficient as the exploration tunnel. Based on its predicted maximum inflow rate of 5215.38 m³ / (d·km), an inflow rate decay function is constructed:

[0124] .

[0125] The water inflow into the ventilation and safety tunnel will begin to decrease after the tunnel is completed in January 2027, and will continue to decrease until the tailrace tunnel is completed in December 2027. The corresponding attenuation of the inflow was calculated. .

[0126] 5. Coupled prediction of total water inflow during multi-tunnel collaborative construction.

[0127] The excavation period for the geological exploration tunnel is from January 2024 to September 2024; the designed excavation period for the ventilation and safety tunnel is from October 2025 to January 2027; and the designed excavation period for the tailrace tunnel is from May 2026 to December 2027. The excavation of the exploration tunnel, ventilation and safety tunnel, and tailrace tunnel overlaps in timing and involves coordinated dewatering. When the tailrace tunnel excavation is completed in December 2027, the total water inflow in the project area will be the sum of the water inflows from the three tunnels, calculated using the following formula:

[0128] ;

[0129] in, This is the predicted maximum inflow rate for the tailrace tunnel in December 2027. The predicted attenuation of water inflow in the ventilation and safety tunnel as of December 31, 2027. The predicted value of the reduced inflow volume of the exploration tunnel on December 31, 2027.

[0130] This embodiment is obtained through in-situ monitoring and inversion of an exploration tunnel. It can quickly predict the maximum water inflow of any tunnel within the same hydrogeological unit; combined with a unified attenuation coefficient This system can construct attenuation functions for the water inflow of each tunnel, enabling dynamic prediction of the total water inflow of a tunnel group at any time and under any combination of working conditions, and accurately identifying the peak water inflow nodes during multi-chamber construction. Simultaneously, by combining the designed excavation periods of various underground tunnels, multiple peak water inflow points can be estimated. The prediction results can be directly used for optimizing the engineering drainage system, preventing and controlling construction water inrush risks, and scientifically arranging construction procedures, providing quantitative, accurate, and dynamic hydrogeological data for the safe and efficient construction of pumped storage tunnel groups under complex geological conditions.

[0131] This invention innovatively achieves a technological leap from "static prediction of a single tunnel" to "dynamic prediction of tunnel groups," constructing an integrated, high-precision, and highly adaptable water inflow prediction system with the following significant innovative advantages:

[0132] 1. Reusing existing exploration tunnels as test platforms, the equivalent permeability coefficient of the rock mass is inverted through stable water inflow. This parameter is directly derived from the seepage response at the tunnel diameter scale, which significantly improves the representativeness compared to traditional borehole test scales, and eliminates the need for additional excavation of auxiliary tunnels, greatly reducing engineering testing costs.

[0133] 2. Innovative "segmented isolation monitoring method". This invention sets up monitoring sections in different geological sections within the exploration tunnel, independently measures the water inflow of each section, and inverts the equivalent permeability coefficient of the rock mass in the corresponding geological section. This achieves precise zonal assignment of key parameters, solves the problem of "using points to represent the whole", and realizes precise zonal matching and assignment of permeability parameters with geological conditions, effectively improving the spatial accuracy of water inflow prediction in heterogeneous rock masses.

[0134] 3. Constructing a dynamic attenuation model driven by measured data and based on attenuation coefficient analogy. This invention abandons idealized theoretical attenuation formulas and relies on measured data of existing tunnels within the same hydrogeological unit to fit an exponential attenuation function and construct an attenuation model for the tunnel to be predicted by analogy. Based on real field patterns, it extrapolates and predicts, significantly improving the engineering adaptability and reliability of attenuated water inflow prediction.

[0135] 4. Establish a "Dynamic Groundwater Level Correction Model". This invention introduces the concept of dynamic drainage water level, quantifies the cumulative drainage depth of the initial drainage tunnel, determines the actual water head conditions of the subsequent construction tunnel, breaks through the limitations of natural constant water head calculation, and achieves accurate prediction of the initial maximum inflow.

[0136] 5. Construct a "multi-tunnel collaborative construction coupling prediction model". This invention fully considers the hydrological superposition effect caused by the construction sequence, realizes the dynamic conversion calculation of water inflow from a single tunnel to the total water inflow of the tunnel group, and provides accurate data support for the design of the overall drainage system of the tunnel group and the optimization of construction organization.

[0137] 6. This method has a standardized process, clear steps, and convenient parameter acquisition. It strictly follows industry standards and is applicable to different working conditions such as single tunnel and multi-tunnel collaborative construction in hydropower projects. It can also be extended to underground engineering fields such as highways and mines, and has extremely high engineering application value.

[0138] Another embodiment of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the inflow coupling prediction method based on existing tunnel inversion as described above.

[0139] The above descriptions are merely a few embodiments of the present invention and are 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 modifications or alterations made by those skilled in the art without departing from the scope of the technical solution of the present invention using the disclosed technical content are equivalent to equivalent implementation cases and fall within the scope of the technical solution.

Claims

1. A coupled prediction method for water inflow based on inversion of existing tunnels, characterized in that, The method includes: S1. Determine all associated tunnels of the tunnel to be predicted, and select one tunnel with a stable decrease in water inflow from the associated tunnels as the existing tunnel, and the remaining tunnels as the preliminary tunnels. S2. Based on the geometric parameters and stable inflow of the existing tunnel, determine the equivalent permeability coefficient of the rock mass of the existing tunnel, and based on the equivalent permeability coefficient of the rock mass, determine the first maximum inflow of the tunnel to be predicted and the second maximum inflow of the tunnel in advance. S3. Using time as the independent variable and the measured water inflow as the dependent variable, fit the water inflow monitoring sequence of the existing tunnel with a natural exponential function to obtain the first attenuated water inflow function of the existing tunnel, and extract the attenuation coefficient of the first attenuated water inflow function; using the second maximum water inflow as the initial amplitude parameter, and using the attenuation coefficient and the initial amplitude parameter, construct the second attenuated water inflow function in the form of a natural exponential function. Wherein, the first attenuation inflow function The expression is as follows: ； In the formula, , These are the fitting coefficients. This represents the maximum inflow rate of the existing tunnel. The attenuation coefficient of the existing tunnel; The second decaying inflow function The expression is as follows: ； in, This is the second largest inflow volume in the preceding tunnel; The attenuation coefficient of the existing tunnel; This refers to the cumulative decay time of the tunnel from the start of its decay period after breakthrough to the predicted time. S4. Based on the first attenuated inflow function, the second attenuated inflow function, and the first maximum inflow, determine the predicted total inflow value of the tunnel to be predicted at the prediction time.

2. The method according to claim 1, characterized in that, The step S2, determining the equivalent permeability coefficient of the rock mass of the existing tunnel based on its geometric parameters and stable inflow rate, specifically includes: Continuous hydrological monitoring is performed on the existing tunnel, and the total inflow volume when the fluctuation range of the total inflow volume of the existing tunnel is less than a preset threshold within a preset time period is taken as the stable inflow volume. Substituting the geometric parameters of the existing tunnel and the stable inflow rate into the empirical formula of the Oshima Hiroshi method, the equivalent permeability coefficient of the rock mass of the existing tunnel is obtained by inversion.

3. The method according to claim 1, characterized in that, The determination of the first maximum inflow rate of the tunnel to be predicted and the second maximum inflow rate of the tunnel under construction, based on the equivalent permeability coefficient of the rock mass in step S2, specifically includes: The first distance between the groundwater level and the bottom of the tunnel to be predicted and the second distance between the groundwater level and the bottom of the tunnel under the drainage and dewatering effect are determined respectively. Substituting the first distance, the equivalent permeability coefficient of the rock mass, and the cross-sectional radius of the tunnel to be predicted into the empirical formula of the Oshima Hiroshi method, the first maximum inflow of the tunnel to be predicted is obtained. Substituting the second distance, the equivalent permeability coefficient of the rock mass, and the cross-sectional radius of the preliminary tunnel into the empirical formula of the Oshima Hiroshi method, the second maximum inflow of the preliminary tunnel is obtained.

4. The method according to claim 3, characterized in that, Determine the first distance between the groundwater level and the bottom of the tunnel to be predicted, and the second distance between the groundwater level and the bottom of the tunnel under drainage and dewatering conditions, specifically including: The first cumulative drawdown depth of the tunnel to be predicted and the second cumulative drawdown depth of the tunnel under the drainage and dewatering action are determined respectively. The first distance between the groundwater level and the bottom of the tunnel to be predicted is determined based on the first cumulative drawdown, and the second distance between the groundwater level and the bottom of the tunnel to be constructed is determined based on the second cumulative drawdown.

5. The method according to claim 1, characterized in that, S4 specifically includes: Based on the first attenuation inflow function, calculate the first attenuation inflow prediction value of the existing tunnel at the predicted time, and based on the second attenuation inflow function, calculate the second attenuation inflow prediction value of the preceding tunnel at the predicted time. Calculate the sum of the first attenuated inflow prediction value, the second attenuated inflow prediction value, and the first maximum inflow, and use the sum as the total inflow prediction value of the tunnel to be predicted at the prediction time.

6. The method according to claim 1, characterized in that, The step S2, determining the equivalent permeability coefficient of the rock mass of the existing tunnel based on its geometric parameters and stable inflow rate, specifically includes: The existing tunnel is divided into multiple first geological sections according to geological conditions, and the stable water inflow of each first geological section is determined. Based on each stable inflow rate and the geometric parameters of the existing tunnel, the equivalent permeability coefficient of the rock mass corresponding to the first geological section is determined.

7. The method according to claim 6, characterized in that, The determination of the first maximum inflow rate of the tunnel to be predicted and the second maximum inflow rate of the tunnel under construction, based on the equivalent permeability coefficient of the rock mass in step S2, specifically includes: The tunnel to be predicted is divided into multiple second geological sections according to geological conditions, and the tunnel in advance is divided into multiple third geological sections according to geological conditions. The first geological section, the second geological section and the third geological section correspond one-to-one. Based on the equivalent permeability coefficient of the rock mass in each first geological section, the water inflow of the first section corresponding to the second geological section and the water inflow of the second section corresponding to the third geological section are determined respectively. The sum of the water inflow of the first section of all second geological sections is taken as the first maximum water inflow of the tunnel to be predicted, and the sum of the water inflow of the second section of all third geological sections is taken as the second maximum water inflow of the tunnel to be constructed.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the inflow volume coupling prediction method based on existing tunnel inversion as described in any one of claims 1 to 7.

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