A method for excavating and supporting a tunnel near a moving fault

Abstract

The application discloses a kind of near parallel active fault tunnel excavation support method, belong to tunnel construction technical field, can solve the problem that existing technology is difficult to effectively protect buried fault, the method comprises: S1, according to the geological data of the crossing region of target tunnel determines the first predicted distribution of buried fault in crossing region;S2, according to the first predicted distribution determines the predicted distribution region of buried fault in crossing region, according to the exploration data of predicted distribution region, correct the first predicted distribution, obtain current predicted distribution;S3, according to current predicted distribution determines the distance between each to be constructed section of target tunnel and buried fault, and the to be constructed section with distance less than preset threshold is determined as high-risk construction section;S4, according to current predicted distribution determines the support measure of high-risk construction section, according to support measure, carries out excavation construction to high-risk construction section, and according to construction effect, the support structure of high-risk construction section is modified.The application is used for tunnel construction.

Description

Technical Field

[0001] This invention relates to a method for excavation and support of a near-parallel active fault tunnel, belonging to the field of tunnel construction technology. Background Technology

[0002] Near-parallel active fault tunnels refer to tunnel projects that are approximately parallel to the strike of known active faults. These tunnels traverse areas deep underground where hidden faults often exist due to stress transmission and uneven stress distribution. Hidden faults are fracture structures that do not directly expose at the surface but lie beneath underground rock strata or Quaternary sediments. Hidden faults are highly concealed and pose a potential threat to tunnel construction, especially when they are in an unstable state, potentially triggering earthquakes or engineering disasters.

[0003] However, due to the unclear distribution pattern of concealed faults, existing technologies are unable to accurately locate and detect them, thus making it impossible to effectively protect against concealed faults during tunnel construction, which poses a serious threat to the construction safety of tunnel projects. Summary of the Invention

[0004] This invention provides a method for excavation and support of tunnels with near-parallel active faults, which can solve the problem that existing technologies are difficult to effectively protect against hidden faults during construction.

[0005] This invention provides a method for excavation and support of tunnels along near-parallel active faults, the method comprising:

[0006] S1. Determine the first predicted distribution of the concealed fault in the area traversed by the target tunnel based on the geological data of the area traversed; the extension direction of the target tunnel matches the strike of the active fault in the area traversed.

[0007] S2. Determine the predicted distribution area of ​​the concealed fault in the crossing area based on the first predicted distribution area, and correct the first predicted distribution area based on the exploration data of the predicted distribution area to obtain the current predicted distribution area.

[0008] S3. Determine the distance between each section of the target tunnel to be constructed and the hidden fault based on the current predicted distribution, and identify the sections to be constructed with a distance less than a preset threshold as high-risk construction sections.

[0009] S4. Determine the support measures for the high-risk construction section based on the current predicted layout, carry out excavation construction on the high-risk construction section according to the support measures, and adjust the support structure of the high-risk construction section according to the construction effect.

[0010] Optionally, S1 specifically includes:

[0011] S11. Construct a three-dimensional geological model of the traversed area based on the geological data of the traversed area;

[0012] S12. Determine the first predicted distribution of the concealed fault based on the three-dimensional geological model.

[0013] Optionally, the geological data includes geomorphological data and geophysical data; S11 specifically includes:

[0014] Based on the geomorphological data of the traversed area, the first distribution area of ​​the concealed fault in the traversed area is determined, and the first distribution area is explored to obtain the exploration data of the concealed fault.

[0015] A three-dimensional geological model of the traversed area is constructed based on the geomorphological data, the exploration data of the concealed fault, and the geophysical data.

[0016] Optionally, the exploration data includes shallow exploration data and deep exploration data; exploration of the first distribution area to obtain exploration data of the concealed fault specifically includes:

[0017] Trenching is conducted in the first distribution area to obtain shallow exploration data of the concealed fault;

[0018] Drilling is conducted in the first distribution area to obtain deep exploration data of the concealed fault.

[0019] Optionally, in S2, the first predicted distribution is corrected based on the exploration data of the predicted distribution area to obtain the current predicted distribution, specifically including:

[0020] Before the excavation of the target tunnel, the first predicted distribution is corrected based on the exploration data of the predicted distribution area to obtain the corrected predicted distribution.

[0021] During the excavation of the target tunnel, the predicted distribution is corrected based on the current geological information of the working face of the target tunnel to obtain the current predicted distribution.

[0022] Optionally, in S4, the support measures for the high-risk construction section are determined based on the current predicted distribution, specifically including:

[0023] S41. Based on the current predicted layout, determine the advanced support measures for the working face before excavation of the high-risk construction section;

[0024] S42. Based on the current predicted distribution, determine the initial support measures for the surrounding rock during the excavation of the high-risk construction section;

[0025] S43. Based on the current predicted distribution and the deformation monitoring data of the surrounding rock after the implementation of the initial support measures, determine the reinforcement support measures for the tunnel wall of the high-risk construction section.

[0026] Optionally, the advanced support measures include advanced pipe roof support and advanced grouting; S41 specifically includes:

[0027] Based on the current predicted distribution, the first construction parameters for advanced pipe roof support and advanced grouting are determined, and the advanced support measures are determined based on the first construction parameters.

[0028] Optionally, the initial support measures include anchor bolt support and steel arch support; S42 specifically includes:

[0029] Based on the current predicted distribution, second construction parameters for anchor bolt support and steel arch support are determined, and the initial support measures are determined based on the second construction parameters.

[0030] Optionally, the reinforced support measures include setting a secondary lining layer and arranging expansion joints in the secondary lining layer; S43 specifically includes:

[0031] The third construction parameters of the secondary lining layer are determined based on the deformation monitoring data, and the layout parameters of the expansion joints are determined based on the current predicted distribution.

[0032] The reinforced support measures are determined based on the third construction parameters and the layout parameters.

[0033] Optionally, the third construction parameter includes the reinforcement area and reinforcement ratio of the secondary lining layer.

[0034] The beneficial effects that this invention can produce include:

[0035] (1) Based on the geological data of the area through which the target tunnel passes, the present invention determines the first predicted distribution of the hidden fault in the area through which the tunnel passes, thereby preliminarily exploring the distribution pattern of the hidden fault. Then, local exploration is carried out in the predicted distribution area of ​​the hidden fault, and the first predicted distribution is corrected based on the exploration data, so as to achieve accurate positioning of the hidden fault. This solves the problem that the existing technology is difficult to accurately locate and detect the hidden fault, and can provide a reliable basis for the safe construction of the target tunnel.

[0036] (2) This invention obtains a modified predicted distribution by modifying the first predicted distribution, and further iteratively modifies the modified predicted distribution based on the current geological information of the working face during the excavation of the target tunnel, thereby obtaining the current predicted distribution. In this way, the current predicted distribution can be continuously adjusted based on the actual exposure information of the concealed fault, so that the current predicted distribution continuously approaches the actual distribution law of the concealed fault, thereby improving the accuracy of locating the concealed fault.

[0037] (3) Based on the current predicted distribution, the present invention identifies the construction section that is close to the hidden fault as the high-risk construction section, and determines the support measures for the high-risk construction section in a targeted manner according to the current predicted distribution, so that the support measures are compatible with the distribution pattern of the hidden fault, thereby effectively protecting the hidden fault and improving the construction safety of the target tunnel.

[0038] (4) In response to the potential threat of concealed faults, this invention adopts phased support measures at different construction stages in high-risk construction sections. Specifically, advanced support measures are taken for the working face before excavation, initial support measures are taken for the surrounding rock during excavation, and reinforced support measures are taken for the tunnel wall after the initial support measures are implemented. This ensures that the support measures cover the entire construction process of the high-risk construction section and are gradually superimposed as the construction progresses, thus guaranteeing effective protection. At the same time, the support measures at each stage are arranged and implemented based on the current predicted distribution and can be adjusted accordingly based on the tunnel monitoring data, improving the effectiveness, flexibility, and pertinence of the support measures layout.

[0039] (5) This invention obtains geomorphic data of the crossing area through remote sensing images, topographic mapping and other methods, obtains shallow exploration data of the concealed fault through trenching, obtains deep exploration data of the concealed fault through drilling, and obtains various physical parameters of the crossing area through geophysical exploration, thereby obtaining geological data of the crossing area. This allows the geological data to reflect the geological conditions of the crossing area more comprehensively. Then, the construction of a three-dimensional geological model of the crossing area based on the geological data can improve the accuracy of the model construction, thereby improving the positioning accuracy of the concealed fault. Attached Figure Description

[0040] Figure 1 A flowchart of the excavation and support method for a near-parallel active fault tunnel provided in an embodiment of the present invention. Detailed Implementation

[0041] The present invention will now be described in detail with reference to the embodiments, but the present invention is not limited to these embodiments.

[0042] This invention provides a method for excavation and support of tunnels along near-parallel active faults, such as... Figure 1 As shown, the method includes:

[0043] S1. Determine the first predicted distribution of the concealed faults in the area traversed by the target tunnel based on the geological data of the area traversed; the extension direction of the target tunnel matches the strike of the active faults in the area traversed.

[0044] Specifically, the extension direction of the target tunnel matching the orientation of the active fault in the area it traverses means that the extension direction of the target tunnel is approximately parallel to the orientation of the identified active fault in the area it traverses, i.e., the target tunnel is a near-parallel active fault tunnel.

[0045] Because the target tunnel extends approximately parallel to the strike of the known active faults, the potential threat posed by the active faults to the tunnel is relatively small. However, deep underground in the area traversed by the target tunnel, there are often hidden faults that are not exposed on the surface due to stress transmission and uneven stress distribution. Hidden faults are highly concealed and their distribution patterns are unclear. Compared to known active faults, hidden faults pose a greater potential threat to tunnel construction. Therefore, to ensure the construction safety of the target tunnel and avoid engineering disasters, it is necessary to accurately predict the distribution patterns of hidden faults so that corresponding measures can be taken during the construction process to reduce their threat.

[0046] S1 specifically includes:

[0047] S11. Construct a three-dimensional geological model of the area traversed by the target tunnel based on the geological data of the traversed area, specifically including:

[0048] (1) Obtaining geological data

[0049] In this embodiment, the geological data of the traversed area includes geological and geomorphological data, geophysical data, and exploration data of concealed faults in the traversed area.

[0050] Among them, geomorphological data can be obtained through remote sensing images, topographic mapping and other methods. Based on the geomorphological data, macro-geomorphological analysis of the traversed area can be carried out to initially identify signs of hidden faults, such as linear landforms and abrupt topographic changes, thereby initially determining the first distribution area of ​​hidden faults.

[0051] Geophysical data can be obtained using geophysical methods such as magnetotellurics and micro-animal probing. Magnetotellurics can effectively detect the electrical differences between different underground media, while micro-animal probing can capture minute vibration signals generated by the activity of concealed faults. By analyzing changes in the magnetotelluric field and minute vibration signals, the location, strike, and activity characteristics of concealed faults can be preliminarily detected using geophysical inversion methods.

[0052] The exploration data of concealed faults includes shallow exploration data and deep exploration data. In this embodiment, the first distribution area of ​​the concealed fault in the traversed area is determined based on the geomorphological data of the traversed area. Then, in the first distribution area of ​​the concealed fault, trenching is carried out by excavating shallow pits or trenches to directly observe the stratigraphic structure, lithological changes, and the presence of concealed fault fracture zones, which can clarify the shallow characteristics of the concealed fault and obtain shallow exploration data of the concealed fault. At the same time, core analysis is carried out on the deep strata in the first distribution area by drilling to analyze the material composition and structural characteristics of the deep fault, which can clarify the deep fault attitude of the concealed fault and its differences from the shallow characteristics, thus obtaining deep exploration data of the concealed fault.

[0053] Specifically, the trenching depth can be 1m to 3m, and the drilling depth can be 10m to 500m.

[0054] (2) Constructing a three-dimensional geological model

[0055] First, this embodiment performs data preprocessing on multi-source data, including geomorphological data, geophysical data, shallow exploration data of concealed faults, and deep exploration data. Specifically, the multi-source data is converted into a unified data format and corrected to the same coordinate system. At the same time, outliers and duplicate values ​​caused by measurement errors, instrument malfunctions, and other factors are removed from the multi-source data to improve data quality.

[0056] Then, in this embodiment, feature extraction is performed on the preprocessed multi-source data. Based on the extracted data features, spatial overlay analysis is used to spatially overlay various features. At the same time, pre-trained machine learning algorithms are used to classify and cluster the multi-source data to mine potential correlations between data in order to identify the characteristics and attributes of concealed faults, thereby constructing a three-dimensional geological model containing concealed faults.

[0057] Specifically, this embodiment can spatially overlay various features based on a Geographic Information System (GIS).

[0058] S12. Determine the first predicted distribution of concealed faults in the traversing area based on the three-dimensional geological model.

[0059] Because the three-dimensional geological model contains the characteristics and properties of concealed faults, it can reflect the distribution information such as the location, strike, and activity characteristics of concealed faults. Since this distribution information is essentially a predicted distribution information obtained based on the geological data of the traversed area, this embodiment defines the distribution information of concealed faults obtained from the three-dimensional geological model as the first predicted distribution.

[0060] S2. Determine the predicted distribution area of ​​the concealed fault in the crossing area based on the first predicted distribution area, and correct the first predicted distribution area based on the exploration data of the predicted distribution area to obtain the current predicted distribution area.

[0061] Since the first predicted distribution is based on geological data of the traversed area, it differs somewhat from the actual distribution of the concealed fault. To achieve accurate location of the concealed fault, the first predicted distribution needs to be corrected based on the actual exposure information of the concealed fault.

[0062] In this embodiment, the predicted distribution area of ​​the concealed fault in the traversing area can be determined based on the first predicted distribution area. Local exploration of the predicted distribution area can obtain local accurate information about the concealed fault. Simultaneously, information about the concealed fault exposed on the working face of the target tunnel can also be obtained. Based on the deviation between the local accurate information and the first predicted distribution, the first predicted distribution can be corrected, thereby improving the accuracy of concealed fault location.

[0063] Specifically, in this embodiment, the predicted distribution area is explored before the target tunnel is excavated, and the first predicted distribution is corrected based on the exploration data of the predicted distribution area to obtain a corrected predicted distribution. Then, during the excavation of the target tunnel, the corrected predicted distribution is further corrected based on the current geological information of the working face of the target tunnel to obtain the current predicted distribution. Simultaneously, during the excavation of the target tunnel, the working face of the target tunnel will continuously advance in the extension direction of the target tunnel, and the current geological information of the working face will continuously change with the construction progress. Therefore, the current predicted distribution can be iteratively corrected and dynamically updated based on the current geological information of the working face, thereby continuously improving the accuracy of the current predicted distribution and providing a reliable basis for the construction of subsequent sections.

[0064] The specific steps for correcting the first predicted distribution in this embodiment include:

[0065] (1) Collect exploration data of the predicted distribution area.

[0066] Intensive drilling or trenching is conducted in the predicted distribution area to directly obtain underground strata cores and concealed fault materials. This allows for the determination of the material composition and structural plane orientation (strike, dip, and angle) of the concealed faults. For example, core samples can be used to observe striations, steps, and mineral cementation levels to determine the activity history of the concealed faults. Trenching can reveal the shallow features of the concealed faults, verifying whether the initial predicted distribution matches these shallow features.

[0067] Meanwhile, the core samples obtained from drilling can be subjected to laboratory testing and analysis (such as rock mechanics tests, isotope dating, electron microscopy, etc.) to determine the physical and mechanical parameters (such as strength, permeability, etc.) and activity age of the concealed fault material, thereby supplementing the missing details in the three-dimensional geological model.

[0068] (2) Deviation comparison.

[0069] Spatial location comparison: The actual location of the concealed faults obtained through exploration in the predicted distribution area (such as the depth and coordinates of the fracture zone determined by drilling) will be compared with the predicted location calculated by the three-dimensional geological model to determine the spatial location deviation.

[0070] Comparison of attitude parameters: The dip angle, strike and other attitude parameters of the concealed faults obtained by exploration in the predicted distribution area will be compared with the attitude parameters calculated by the three-dimensional geological model to determine the deviation of the attitude parameters (e.g., the predicted dip angle calculated by the three-dimensional geological model is 60°, while the actual dip angle is 55°).

[0071] Attribute feature comparison: The thickness, material composition and other attribute features of the concealed fault fracture zone obtained by exploration in the predicted distribution area will be compared with the attribute features calculated by the three-dimensional geological model to determine the attribute feature deviation.

[0072] (3) Correct the three-dimensional geological model.

[0073] Using the actual location of the concealed faults obtained from exploration as control points, the spatial coordinates of the concealed fault interfaces in the three-dimensional geological model are adjusted to correct the extension trajectory of the concealed faults. Combined with the occurrence parameters and attribute characteristics obtained from exploration, the occurrence parameters and attribute characteristics of the three-dimensional geological model are updated to make the three-dimensional geological model more closely resemble the real geological structure of the traversed area.

[0074] Furthermore, this embodiment also optimizes the machine learning algorithm for the three-dimensional geological model based on exploration data. For example, if a systematic deviation is found between the geophysical data and the exploration data for the predicted distribution area, the geophysical inversion parameters are recalibrated (e.g., adjusting the resistivity threshold), or the feature weights of the machine learning algorithm are optimized (e.g., increasing the priority of drilling data in the training of the machine learning algorithm).

[0075] After correction, this implementation marks the error range of the corrected three-dimensional geological model (such as the positioning error of the concealed fault ±5m) in order to quantify the uncertainty and provide more reliable geological parameters for subsequent construction and support.

[0076] If, after correction, the 3D geological model still has significant deviations (such as deviations exceeding the allowable range for engineering), then exploration points should be added in the predicted distribution area, and the above process of "collecting exploration data - deviation comparison - model correction" should be repeated until the accuracy of the 3D geological model meets the construction requirements (such as the location error of the concealed fault ≤ 10m).

[0077] (4) Cyclic verification and dynamic update.

[0078] During the excavation of the target tunnel, the 3D geological model is verified in real time based on the current geological information revealed at the working face (such as the actual exposure location of concealed fault fracture zones). The prediction parameters of the 3D geological model for concealed faults in the remaining excavation section are dynamically updated, continuously improving the prediction accuracy of the 3D geological model. Through iterative correction of the 3D geological model, the current predicted distribution reflected by the 3D geological model is also dynamically updated, thereby continuously improving the positioning accuracy of concealed faults.

[0079] This embodiment corrects the three-dimensional geological model by conducting exploration in the predicted distribution area, and has the following specific functions:

[0080] (1) Solving the multiple solutions for locating deep faults.

[0081] The inversion results of geophysical data may be subject to multiple interpretations due to factors such as differences in the electrical properties of the subsurface medium and noise interference. In contrast, data obtained directly through exploration methods such as drilling, trenching, and direct observation are first-hand, authentic geological data that have not been inferred by algorithms. This can eliminate the ambiguity of geophysical data and ensure the accuracy of the location and occurrence of concealed faults.

[0082] (2) Connecting the differences in features between shallow and deep parts.

[0083] Concealed faults often exhibit characteristics of "simple shallow outcrops and complex deep structures" (e.g., steep shallow dip angles and gentler deep dip angles). Borehole exploration can identify these vertical differences, avoiding the distortion of deep models caused by relying solely on shallow exploration.

[0084] (3) Reduce construction risks.

[0085] If the 3D geological model is not corrected, it may result in insufficient or excessive support measures (e.g., the support measures do not cover the affected area of ​​the concealed fault due to the offset of the concealed fault location) or excessive support measures (e.g., misjudging the size of the concealed fault leads to unnecessary costs). By correcting the model through exploration, it can be ensured that the support measures are accurately applied to the affected area of ​​the concealed fault.

[0086] By obtaining real geological data through field exploration and verifying and correcting the three-dimensional geological model, the essence is to eliminate uncertainties in geological exploration by comparing the "theoretical model" with "actual observation". This reflects the closed-loop control concept of "from data to model, and then from model to field verification", which can ensure that the positioning accuracy of hidden faults meets the engineering requirements, thereby providing a reliable basis for the subsequent construction of the target tunnel.

[0087] S3. Determine the distance between each section of the target tunnel to be constructed and the hidden fault based on the current predicted distribution, and identify the sections to be constructed with a distance less than the preset threshold as high-risk construction sections.

[0088] Simultaneously, this embodiment monitors the surrounding rock deformation, support structure stress, and hidden fault activity in real time during construction. Surrounding rock deformation includes crown settlement, perimeter convergence, and surface subsidence; support structure stress includes anchor bolt stress and steel arch frame stress; and hidden fault activity includes displacement and minor vibrations. The monitoring frequency is flexibly adjusted according to the construction progress and the activity of the hidden fault to acquire and analyze data promptly. By analyzing the monitoring data in real time and setting early warning thresholds, an automatic warning signal is issued when the monitoring data reaches or exceeds the threshold, prompting engineering technicians to take appropriate measures. For example, when the surrounding rock deformation is excessive, construction on the corresponding part should be stopped immediately, and temporary reinforcement measures should be taken for the deformed area; when the lining structure is damaged, temporary support should be provided for the damaged part to prevent the accident from escalating; in the event of water or mud inrush, personnel and equipment should be organized promptly for drainage, and the water or mud inrush points should be sealed.

[0089] S4. Determine the support measures for high-risk construction sections based on the current predicted distribution, carry out excavation construction on the high-risk construction sections according to the support measures, and modify the support structure of the high-risk construction sections based on the construction effect, specifically including:

[0090] S41. Based on the current predicted layout, determine the advanced support measures for the working face before excavation of high-risk construction sections.

[0091] In this embodiment, the advanced support measures include advanced pipe roof support and advanced grouting. Based on the current predicted distribution, this embodiment determines the first construction parameters for advanced pipe roof support and advanced grouting, and then determines the advanced support measures based on these first construction parameters.

[0092] The first construction parameters include the pipe roof diameter and spacing of the advanced pipe roof support, as well as the grout type and grouting speed of the advanced grouting.

[0093] Advanced pipe roof support: Before excavation of high-risk construction sections, advanced support is carried out along the outer side of the tunnel excavation outline using large-diameter, long-distance pipe roofs. The spacing between pipe roofs is determined based on the width of the concealed fault fracture zone and the stability of the rock and soil. For example, the spacing between pipe roofs can be 50cm, forming a load-bearing arch through the pipe roofs.

[0094] Pre-grouting: Grouting is carried out using pre-grouted small pipes. The grout is determined according to the properties of the soil and rock mass of the concealed fault, and can be cement grout, cement mortar or chemical grout. Pre-grouting can effectively reinforce the soil and rock mass of the fracture zone of the concealed fault.

[0095] S42. Based on the current predicted layout, determine the initial support measures for the surrounding rock during the excavation of high-risk construction sections.

[0096] In this embodiment, the initial support measures include anchor bolt support and steel arch support. Based on the current predicted distribution, this embodiment determines the second construction parameters for anchor bolt support and steel arch support, and then determines the initial support measures based on these second construction parameters.

[0097] The second construction phase includes the diameter, length, and spacing of the anchor bolts for anchor bolt support, as well as the spacing of the steel arch frames for steel arch frame support.

[0098] For example, early-strength, high-performance concrete can be sprayed onto the surrounding rock immediately after excavation. The thickness can be 25cm, and the concrete strength grade can be C25. Steel fibers or synthetic fibers are added to the sprayed concrete to quickly seal the surrounding rock surface.

[0099] When using anchor bolts for support, high-strength, fully bonded anchor bolts are employed, with diameters ranging from 20mm to 28mm and lengths from 3m to 5m. The spacing between bolts can be 0.8m to 1.2m. These anchor bolts anchor the concealed fault fracture zone and surrounding rock to stable strata. The steel arch frame spacing can be 0.5m to 0.8m. By installing large-sized steel arch frames, a combined support system is formed with the anchor bolts and shotcrete, effectively reinforcing the surrounding rock.

[0100] Simultaneously, this embodiment conducts microseismic monitoring on high-risk construction sections during excavation and employs sectional excavation methods (such as bench excavation, CD method, and CRD method) to excavate these sections under microseismic monitoring. During excavation, the excavation advance and method can be adjusted promptly based on changes in the intensity and frequency of the microseismic signal. If the microseismic signal abnormally increases, it indicates that the surrounding rock may be in an unstable state, and the advance should be reduced or excavation should be suspended, while strengthening the support. If blasting excavation is used, controlled blasting techniques can be employed in areas near concealed faults, such as smooth blasting or pre-splitting blasting, to complete the excavation.

[0101] S43. Based on the current predicted distribution and the deformation monitoring data of the surrounding rock after the implementation of the initial support measures, determine the reinforcement support measures for the tunnel walls in high-risk construction sections.

[0102] In this embodiment, the reinforcement measures include setting up a secondary lining layer and laying expansion joints in the secondary lining layer. This embodiment determines the third construction parameters of the secondary lining layer based on deformation monitoring data, and determines the layout parameters of the expansion joints based on the current predicted distribution; then, the reinforcement measures are determined based on the third construction parameters and the layout parameters.

[0103] The third construction parameters include the thickness of the secondary lining layer, the amount of steel reinforcement, the area of ​​reinforcement, the number of steel reinforcement layers, the diameter of steel reinforcement and the reinforcement ratio, etc. The layout parameters include the width of the expansion joint and the filling material, etc.

[0104] In this embodiment, based on the deformation monitoring data of the surrounding rock, a secondary lining layer is constructed promptly after the initial support has stabilized. The secondary lining layer adopts a reinforced concrete structure. Based on the geological conditions, surrounding rock grade, cross-sectional dimensions, and stress conditions of the target tunnel, the required bearing capacity of the lining structure is calculated using methods such as structural mechanics calculations and finite element analysis, thereby determining the third construction parameters. Simultaneously, in this embodiment, expansion joints are appropriately set in the secondary lining layer near the concealed fault area. For example, the joint width can be 2cm, and the expansion joints can be filled with water-stopping materials and elastic sealing materials.

[0105] This embodiment utilizes advanced pipe roof support to form a load-bearing arch, resisting the surrounding rock pressure caused by the activity of the concealed fault. Advanced grouting reinforces the soil and rock mass within the fractured zone of the concealed fault, improving its strength and self-stabilizing capacity, and reducing the risk of collapse during excavation. During sectional excavation, the excavation progress and methods are adjusted promptly based on changes in the intensity and frequency of microseismic signals to maintain relative stability of the surrounding rock. A secondary lining layer provides greater support resistance to the target tunnel, effectively resisting the deformation and pressure of the surrounding rock caused by the activity of the concealed fault. Expansion joints are incorporated into the secondary lining layer, allowing it to adapt to certain deformations during the activity of the concealed fault, preventing cracking and damage to the lining structure, and ensuring effective support for the target tunnel.

[0106] S44. Excavation of the high-risk construction section is carried out according to the above support measures, and the support structure of the high-risk construction section is modified according to the construction effect.

[0107] This embodiment uses a total station and a level to measure the geometric data (such as crown elevation, sidewall width, clearance dimensions, axis coordinates, etc.) and deformation data (such as displacement and settlement of the tunnel crown, sidewalls, etc.) of the target tunnel, and inspects the lining surface quality. By comparing the measurement and inspection data with the design parameters of the high-risk construction section, the construction effect of the high-risk construction section can be determined, and corrections should be made to the parts and support structures where the construction effect does not meet the preset requirements.

[0108] For example, when there are geometric deviations and the local lining thickness is insufficient, shotcrete or cast concrete can be used to thicken the lining. For irregular parts caused by over-excavation or under-excavation of the tunnel outline, the over-excavated part can be backfilled with concrete of the same grade as the lining; the under-excavated part needs to be locally excavated and repaired. When there is abnormal deformation, it can be improved by strengthening the support and reinforcing the surrounding rock. When there are surface quality problems, cracks can be treated by surface sealing or pressure grouting, honeycomb pitting can be repaired and cured, and water leakage can be treated by a combination of water blocking and drainage.

[0109] This embodiment determines the first predicted distribution of hidden faults in the area traversed by the target tunnel based on geological data, thereby preliminarily revealing the distribution pattern of hidden faults. Then, local exploration is carried out in the predicted distribution area of ​​hidden faults, and the first predicted distribution is corrected based on the exploration data, so as to achieve accurate positioning of hidden faults. This solves the problem that existing technologies are difficult to accurately locate and detect hidden faults, and can provide a reliable basis for the safe construction of the target tunnel.

[0110] This embodiment obtains a revised predicted distribution by modifying the first predicted distribution, and further iteratively modifies the revised predicted distribution based on the current geological information of the working face during the excavation of the target tunnel, thereby obtaining the current predicted distribution. This allows for continuous adjustment of the current predicted distribution based on the actual exposure information of the concealed fault, making the current predicted distribution increasingly closer to the actual distribution pattern of the concealed fault, thus improving the accuracy of locating the concealed fault.

[0111] Based on the current predicted distribution, this embodiment identifies the construction section that is close to the hidden fault as a high-risk construction section. According to the current predicted distribution, targeted support measures are determined for the high-risk construction section so that the support measures are adapted to the distribution pattern of the hidden fault, thereby effectively protecting the hidden fault and improving the construction safety of the target tunnel.

[0112] This embodiment addresses the potential threat of concealed faults by implementing phased support measures at different stages of construction in high-risk sections. Specifically, pre-excavation support is applied to the working face before excavation; initial support is implemented on the surrounding rock during excavation; and reinforced support is applied to the tunnel walls after the initial support is in place. This ensures that support measures cover the entire construction process of the high-risk section and are gradually layered as construction progresses, guaranteeing effective protection. Furthermore, the support measures at each stage are arranged and implemented based on the current predicted distribution and can be adjusted according to tunnel monitoring data, improving the effectiveness, flexibility, and specificity of the support measures.

[0113] This embodiment acquires geomorphic data of the traversed area through remote sensing imagery and topographic mapping, obtains shallow exploration data of the concealed fault through trenching, obtains deep exploration data of the concealed fault through drilling, and obtains various physical parameters of the traversed area through geophysical exploration, thereby obtaining geological data of the traversed area. This geological data can comprehensively reflect the geological conditions of the traversed area. Then, constructing a three-dimensional geological model of the traversed area based on the geological data can improve the accuracy of the model construction, thereby improving the positioning accuracy of the concealed fault.

[0114] The above description is merely a few embodiments of this application and is not intended to limit this application in any way. Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any changes or modifications made by those skilled in the art without departing from the scope of the technical solution of this application using the disclosed technical content are equivalent to equivalent implementation cases and fall within the scope of the technical solution.

Claims

1. A method for excavation and support of a near-parallel active fault tunnel, characterized in that, The method includes: S1. Determine the first predicted distribution of the concealed fault in the area traversed by the target tunnel based on the geological data of the area traversed; the extension direction of the target tunnel matches the strike of the active fault in the area traversed. S2. Determine the predicted distribution area of ​​the concealed fault in the crossing area based on the first predicted distribution area, and correct the first predicted distribution area based on the exploration data of the predicted distribution area to obtain the current predicted distribution area. S3. Determine the distance between each section of the target tunnel to be constructed and the hidden fault based on the current predicted distribution, and identify the sections to be constructed with a distance less than a preset threshold as high-risk construction sections. S4. Determine the support measures for the high-risk construction section based on the current predicted layout, carry out excavation construction on the high-risk construction section according to the support measures, and adjust the support structure of the high-risk construction section according to the construction effect.

2. The method according to claim 1, characterized in that, S1 specifically includes: S11. Construct a three-dimensional geological model of the traversed area based on the geological data of the traversed area; S12. Determine the first predicted distribution of the concealed fault based on the three-dimensional geological model.

3. The method according to claim 2, characterized in that, The geological data includes geomorphological data and geophysical data; S11 specifically includes: Based on the geomorphological data of the traversed area, the first distribution area of ​​the concealed fault in the traversed area is determined, and the first distribution area is explored to obtain the exploration data of the concealed fault. A three-dimensional geological model of the traversed area is constructed based on the geomorphological data, the exploration data of the concealed fault, and the geophysical data.

4. The method according to claim 3, characterized in that, The exploration data includes shallow exploration data and deep exploration data; exploration is conducted in the first distribution area to obtain exploration data of the concealed fault, specifically including: Trenching is conducted in the first distribution area to obtain shallow exploration data of the concealed fault; Drilling is conducted in the first distribution area to obtain deep exploration data of the concealed fault.

5. The method according to claim 1, characterized in that, S2 corrects the first predicted distribution based on the exploration data of the predicted distribution area to obtain the current predicted distribution, specifically including: Before the excavation of the target tunnel, the first predicted distribution is corrected based on the exploration data of the predicted distribution area to obtain the corrected predicted distribution. During the excavation of the target tunnel, the predicted distribution is corrected based on the current geological information of the working face of the target tunnel to obtain the current predicted distribution.

6. The method according to claim 2, characterized in that, S4 determines the support measures for the high-risk construction section based on the current predicted distribution, specifically including: S41. Based on the current predicted layout, determine the advanced support measures for the working face before excavation of the high-risk construction section; S42. Based on the current predicted distribution, determine the initial support measures for the surrounding rock during the excavation of the high-risk construction section; S43. Based on the current predicted distribution and the deformation monitoring data of the surrounding rock after the implementation of the initial support measures, determine the reinforcement support measures for the tunnel wall of the high-risk construction section.

7. The method according to claim 6, characterized in that, The aforementioned advanced support measures include advanced pipe roof support and advanced grouting; S41 specifically includes: Based on the current predicted distribution, the first construction parameters for advanced pipe roof support and advanced grouting are determined, and the advanced support measures are determined based on the first construction parameters.

8. The method according to claim 6, characterized in that, The initial support measures include anchor bolt support and steel arch support; S42 specifically includes: Based on the current predicted distribution, second construction parameters for anchor bolt support and steel arch support are determined, and the initial support measures are determined based on the second construction parameters.

9. The method according to claim 6, characterized in that, The reinforced support measures include setting a secondary lining layer and arranging expansion joints in the secondary lining layer; S43 specifically includes: The third construction parameters of the secondary lining layer are determined based on the deformation monitoring data, and the layout parameters of the expansion joints are determined based on the current predicted distribution. The reinforced support measures are determined based on the third construction parameters and the layout parameters.

10. The method according to claim 9, characterized in that, The third construction parameter includes the reinforcement area and reinforcement ratio of the secondary lining layer.

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