A Disaster Identification Method for Adverse Geological Bodies in Tunnels Based on Alteration Geological Evolution Sequence

Abstract

This invention discloses a method for identifying catastrophic changes in unfavorable geological bodies in tunnels based on alteration geological evolution sequences, relating to the field of tunnel disaster prevention and mitigation technology. The method includes: conducting comprehensive advanced geological forecasting on the unexcavated section of an excavated tunnel where unfavorable altered geological bodies have been discovered, until a geophysical anomaly zone is found; setting up logging points along the excavation direction of the tunnel sidewalls of the excavated section, locating the three-dimensional coordinates of the logging points and the tunnel mileage, and recording the logging data; conducting structural surface mapping, rock strength testing, groundwater state measurement, and mineralogical testing at the logging points to obtain in-situ test data; correlating the logging data with the in-situ test data according to the tunnel mileage, extracting catastrophic alteration quantification indicators, and drawing an alteration evolution sequence diagram; constructing an identification criterion for unfavorable alteration bodies; if the identification criterion is met, extrapolating the trend of the catastrophic alteration quantification indicators to construct a catastrophic evaluation system. This invention solves the problem of effectively identifying the engineering properties and catastrophic changes of unfavorable altered geological bodies ahead of the tunnel face.

Description

Technical Field

[0001] This invention relates to the field of tunnel disaster prevention and mitigation technology, and in particular to a method for identifying adverse geological bodies in tunnels based on alteration geological evolution sequences. Background Technology

[0002] Currently, the identification of adversely altered geological bodies during tunnel excavation mainly relies on geophysical exploration methods such as seismic wave reflection and electromagnetic wave reflection. These methods have limitations: they cannot accurately identify key engineering properties of adversely altered geological bodies ahead of the tunnel face, such as rock mass strength, integrity, and water-bearing capacity, and they struggle to determine the likelihood, type, and characteristics of potential disasters. These problems lead to frequent geological disasters such as mudslides, water inrushes, collapses, and large deformations during tunnel construction through adversely altered geological bodies. Patent application CN120762131A, "A Method for Predicting Intrusive Rock Alteration Zone Reservoirs," proposes using spontaneous potential as a characteristic curve to perform waveform indication inversion of intrusive shale and mudstone alteration zones, predicting the distribution and thickness of intrusive rock alteration zones. However, it cannot predict the mechanical properties of altered rock masses or the content of undesirable alteration minerals. Patent application CN119414470A, "Prediction of Rock Mass Mechanical Parameters Based on TSP Advanced Geological Prediction," corrects TSP advanced geological prediction data through simple in-situ testing and combines it with empirical formulas to predict rock mass strength parameters. However, it cannot identify undesirable altered rock masses or predict other parameters, let alone predict catastrophic characteristics.

[0003] In tunnel excavation, as the excavation approaches an adverse altered geological body, the sidewalls of the excavated sections will gradually reveal relatively complete and directly observable alteration geological information. However, current technology lacks a method for identifying hazards in adverse geological bodies within tunnels based on the alteration geological evolution sequence. This method is of significant practical importance for disaster prevention and mitigation and ensuring safety during tunnel construction. Summary of the Invention

[0004] The purpose of this invention is to address the problem that existing technologies cannot effectively identify the engineering properties and catastrophic events of adverse altered geological bodies ahead of the tunnel face, and to propose a catastrophic identification method for adverse geological bodies in tunnels based on the alteration geological evolution sequence, comprising the following steps:

[0005] S1. Conduct comprehensive advanced geological forecasting for the unexcavated sections of excavated tunnels where adverse alteration geological bodies have been found;

[0006] S2. Determine if there is a geophysical anomaly zone. If not, proceed with normal excavation and return to step S1. If there is a geophysical anomaly zone, proceed to step S3.

[0007] S3. Set up recording points along the excavation direction of the tunnel sidewall of the excavated section, locate the three-dimensional coordinates of the recording points and the tunnel mileage, and record the rock mass lithology, structure and alteration zoning information to obtain the recording data.

[0008] S4. Conduct structural surface mapping, rock strength testing, groundwater condition measurement, and mineralogical testing at the recorded test points to obtain in-situ test data;

[0009] S5. Correspond the truncation data with the in-situ test data according to the tunnel mileage, extract the morphological indicators of adverse erosion, and draw an erosion evolution sequence diagram.

[0010] S6. Construct a criterion for identifying adverse erosion variants and determine whether the erosion evolution sequence diagram meets the criterion. If it does not meet the criterion, return to step S1. If it meets the criterion, extrapolate the trend of the morphological indicators of adverse erosion variants and construct a disaster evaluation system.

[0011] Furthermore, comprehensive advanced geological forecasting includes seismic wave reflection and ground-penetrating radar methods.

[0012] Furthermore, the quantification indicators of adverse alteration include: adverse alteration mineral content index CI, alteration intensity index AI, altered rock mass quality index ABQ, and water discharge state index QI.

[0013] Furthermore, the criteria for identifying undesirable alteration types are as follows:

[0014] (1) The AI ​​index declined while the CI index rose in tandem;

[0015] (2) CI > 0.5;

[0016] (3) The ABQ index decreased significantly;

[0017] If any of the above conditions are met, the identification criteria are considered met.

[0018] Furthermore, the calculation methods for the adverse corrosion quantification indicators CI, AI, and ABQ are as follows:

[0019] CI = Content of undesirable altered minerals / Total minerals;

[0020] ;

[0021] ;

[0022] in, This indicates the potassium oxide content of the altered rock mass. This indicates the magnesium oxide content of the altered rock mass. This indicates the sodium oxide content of the altered rock mass. Indicates the calcium oxide content of the altered rock mass. Indicates the uniaxial compressive strength of rock. This represents the rock mass integrity coefficient.

[0023] Furthermore, the formula for extrapolating the trend of the adverse corrosion variable index is as follows:

[0024]

[0025]

[0026]

[0027]

[0028]

[0029] in, This represents the predicted value of the undesirable alteration mineral content index (CI). This represents the average or weighted average of the CI (Compatibility Index) data from multiple logging points closest to the geophysical anomaly zone in the excavated section. This represents the weighted average of the P-wave velocities of the rock mass at multiple logging points closest to the geophysical anomaly zone in the excavated section. This represents the weighted average value of the P-wave velocity in the rock mass within the geophysical anomaly zone. This represents the predicted value of the altered rock mass quality index ABQ. This represents the average or weighted average of the ABQ measured data from multiple logging points closest to the geophysical anomaly zone in the excavated section. This represents the longitudinal wave velocity of the rock mass at the i-th recording point. This represents the mileage between the i-th and (i-1)-th logging points. This represents the predicted value of the effluent quality index (QI), where a and b are regression coefficients. It is the water abundance index. Indicates the longitudinal wave velocity of the rock mass. Indicates the shear wave velocity of the rock mass;

[0030] Collect the WBI values ​​of each excavated section and their corresponding actual observed QI, and perform linear regression fitting to obtain regression coefficients a and b;

[0031] Based on the predicted values ​​of the variable indicators of poor corrosion, the trend of the variable indicators of poor corrosion is extrapolated.

[0032] Furthermore, based on the predicted values ​​of adverse corrosion variable indicators, a disaster assessment system is constructed, as follows:

[0033] according to The value is used to classify the degree of integrity of the altered rock mass, and different scores are assigned according to the degree of integrity of the altered rock mass;

[0034] according to The value is used to classify the water-bearing state of the surrounding rock, and different scores are assigned according to the water-bearing state of the surrounding rock;

[0035] according to The values ​​are used to classify the degree of adverse alteration of the altered rock mass, and different scores are assigned according to the degree of adverse alteration of the altered rock mass;

[0036] Different scores are assigned to different sizes of undesirable altered geological bodies.

[0037] Quantitative indicators for adverse corrosion in abnormal areas , and The scores of the values ​​and the scores of different sizes of adversely altered geological bodies are weighted and summed to obtain the quantitative evaluation results of the disaster.

[0038] The present invention also proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for identifying adverse geological bodies in tunnels based on alteration geological evolution sequences.

[0039] The present invention also proposes an electronic device, including a processor and a memory, wherein the processor and the memory are interconnected, wherein the memory is used to store a computer program, the computer program including computer-readable instructions, and the processor is configured to invoke the computer-readable instructions to execute the above-described method for identifying tunnel adverse geological bodies based on alteration geological evolution sequences.

[0040] The present invention also proposes a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-described method for identifying catastrophic geological bodies in tunnels based on alteration geological evolution sequences.

[0041] The beneficial effects of the technical solution provided by this invention are:

[0042] This invention proposes a disaster identification method for unfavorable geological bodies in tunnels based on alteration geological evolution sequences. It involves comprehensive advanced geological forecasting of the unexcavated sections of excavated tunnels where unfavorable altered geological bodies have been found. After delineating geophysical anomaly zones, detailed alteration geological logging and in-situ testing are conducted on the excavated sections. Quantitative indicators such as the unfavorable alteration mineral content index (CI), alteration intensity index (AI), water release index (QI), and altered rock mass quality index (ABQ) are extracted to construct an alteration evolution sequence. Based on these quantitative indicators, an identification criterion for unfavorable alteration bodies is established. If the criteria are met, the trend of the quantitative indicators in the anomaly zone is extrapolated. A multi-factor disaster evaluation system is used to determine the disaster potential, type, and characteristics. This invention solves the problem that existing technologies cannot effectively identify the engineering attributes and disasters of unfavorable altered geological bodies ahead of the tunnel face. It achieves a leap from qualitative anomaly zone identification to directional and quantitative geological attribute identification, improves the accuracy of geophysical interpretation, provides early warning of disaster risks, and offers reliable technical support for disaster prevention and mitigation in tunnel construction. Attached Figure Description

[0043] Figure 1 This is a flowchart of a method for identifying catastrophic geological features in tunnels based on alteration geological evolution sequences, according to an embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram of geophysical anomaly region (target anomaly region Z) data according to an embodiment of the present invention;

[0045] Figure 3 This is a detailed alteration geological logging according to an embodiment of the present invention;

[0046] Figure 4 This is a variation curve of the adverse corrosion in an embodiment of the present invention;

[0047] Figure 5 This is an alteration evolution sequence diagram according to an embodiment of the present invention;

[0048] Figure 6 This is an alteration evolution sequence diagram containing extrapolated data from an embodiment of the present invention;

[0049] Figure 7 This is a block diagram of an electronic device according to an exemplary embodiment of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0051] The flowchart of the catastrophic identification method for tunnel adverse geological bodies based on alteration geological evolution sequence in this invention is as follows: Figure 1 Specifically, it includes the following steps:

[0052] S1. Conduct comprehensive advanced geological forecasting for the unexcavated sections of excavated tunnels where adverse alteration geological bodies have been found.

[0053] After the tunnel is blasted and excavated and the muck is removed, a geological survey is immediately conducted on the excavated face. If undesirable alteration minerals such as altered sericite, altered chlorite, altered kaolinite, altered montmorillonite, and altered illite are found, it indicates that undesirable altered geological bodies may be developing ahead of the tunnel face. A comprehensive advanced geological forecasting process is then carried out for the unexcavated section ahead of the tunnel face. Conventional geophysical exploration methods such as seismic wave reflection and ground-penetrating radar are used to explore the unexcavated section ahead of the tunnel face.

[0054] S2. Based on the geophysical exploration results, determine whether there is a geophysical anomaly zone ahead of the tunnel face. If not, no further operations are required, and excavation proceeds normally, returning to step S1. If abnormal phenomena such as low wave velocity and low resistivity are observed, delineate this as a physical anomaly zone (designated as target anomaly zone Z), and proceed to step S3. A schematic diagram of the geophysical anomaly zone in this embodiment is provided for reference. Figure 2 . Figure 2 By integrating the tunnel seismic prediction (TSP) data and ground-penetrating radar (GPR) data corresponding to the tunnel mileage ahead of the tunnel face, the geophysical data of the anomaly zone Z is comprehensively displayed.

[0055] S3. Set up recording points along the excavation direction of the tunnel sidewall of the excavated section, locate the three-dimensional coordinates of the recording points and the tunnel mileage, and record the rock mass lithology, structure and alteration zoning information to obtain the recording data.

[0056] The spacing between the logging points is 3-7 meters, and the spacing between the logging points in key sections is reduced to 1-2 meters. A total station is used to accurately locate the logging points and record their three-dimensional coordinates and tunnel mileage, which serve as the spatial reference for all logging data.

[0057] Rock mass lithology: Based on the color, structure, texture and main mineral types of the sidewall surrounding rocks, intrusive rocks (such as granite) or pre-existing strata (such as limestone, sandstone, etc.) are identified; based on the color, residual structure, mineral assemblage, texture and alteration of the altered rocks, the type of altered rocks (such as skarn, marble, etc.) is determined.

[0058] Structure and texture: Describe in detail the rock structure (such as relict texture, metamorphic texture, lepidic metamorphic texture) and texture (such as massive texture, vein texture, disseminated texture, brecciated texture) of intrusive rocks or pre-existing strata and altered rocks.

[0059] Alteration zoning: Based on the recorded lithology and structure of the rock mass, different alteration lithology zones (such as skarn zone, cyanitic zone, mudstone zone, silicified zone, etc.) are accurately divided and marked, and their spatial relationship with the tunnel axis (such as occurrence, thickness, and combination sequence) is determined.

[0060] S4. Conduct structural surface mapping, rock strength testing, groundwater condition measurement, and mineralogical testing at the recorded test points to obtain in-situ test data.

[0061] Structural surface mapping: Using steel tape and geological compasses, the quantity, spacing, opening, location, and width of structural surfaces such as joints, fissures, and weak interlayers, as well as their corresponding dip and angle of orientation, are measured and recorded. As the tunnel is excavated, on-site structural surface mapping is performed whenever new logging points are exposed. This is achieved by measuring the number of joints in the rock mass. Rock mass integrity indices were obtained through statistical analysis. The correspondence between the two is shown in Table 1.

[0062] Table 1 Joint Number of Surrounding Rock in Tunnel Completeness indicators Correspondence table

[0063]

[0064] Indicator meaning:

[0065] Number of rock mass joints ( Unit volume (pieces / m³) 3 The number of joints within a rock mass reflects the density of joints in the rock mass.

[0066] Rock mass integrity index ( ): A quantitative indicator of rock mass integrity; the larger the value, the more intact the rock mass.

[0067] Rock strength testing: The rock strength of the recorded rock samples was tested on-site using a point load tester, and the failure load of the rock samples was recorded. At least five rock samples were tested at each recording point, and the average value was taken as the rock strength result. As the tunnel was excavated, samples were taken for testing whenever new recording points were exposed. The rock compressive strength value calculated through the point load strength test is given by the following formula: , The uniaxial compressive strength of the rock (MPa); The point load strength index (MPa) is the equivalent rock point load strength index for a core diameter of 50 mm.

[0068] Groundwater condition measurement: The excavation face is regularly inspected by manual visual inspection to record the seepage pattern, such as dry, wet, seepage beads, linear flow (gushing water), and stream flow (gushing water); a water measuring weir is set up, and the total drainage flow is measured and recorded regularly; typical water outlets in the tunnel (such as stream flow and linear flow) are observed and sampled on site to describe their turbidity, color, and whether they carry silt or other particulate matter.

[0069] According to the railway tunnel specification (TB 10003-2016), the classification of tunnel water discharge status is based on the water volume QI (L / min·10m) per 10m tunnel length. At that time, the water output was "damp or dripping"; At that time, the water flow was described as "rain-like or linear". At that time, it was described as "a gushing out of water".

[0070] Mineralogical testing: Representative rock fragments or powder samples were collected at logging points on the tunnel sidewalls. A handheld X-ray fluorescence spectrometer was used for rapid scanning on-site to obtain and record the contents of major components such as potassium oxide, magnesium oxide, sodium oxide, and calcium oxide. Simultaneously, a portable near-infrared spectroscopy analyzer was used to test for undesirable alteration minerals such as altered sericite, altered chlorite, altered kaolinite, altered montmorillonite, and altered illite, obtaining and recording the contents of these alteration minerals. As the tunnel was excavated, sampling and testing were conducted whenever new logging points were exposed.

[0071] S5. Match the recorded data with the in-situ test data according to the tunnel mileage, extract the morphological indicators of adverse erosion, and draw an erosion evolution sequence diagram.

[0072] Adverse alteration mineral content index (CI) sequence: Adverse alteration minerals refer to sericite, chlorite, kaolinite, montmorillonite, illite, etc. The adverse alteration mineral content index (CI) is defined as the adverse alteration mineral content / total minerals. The corresponding values ​​are derived from the near-infrared spectral test data of various in-situ logging points. This index can effectively reflect the degree of development of adverse alteration minerals. At the same time, the variation curve of the typical adverse alteration mineral content index (CI) with tunnel mileage is plotted to obtain the corresponding alteration evolution sequence diagram.

[0073] Alteration Intensity Index (AI) Sequence: The alteration intensity index (AI) is defined as... This index effectively reflects the alteration intensity of the surrounding rock. The relevant data comes from X-ray fluorescence analysis results at various in-situ logging points. Simultaneously, a curve showing the variation of the alteration intensity index (AI) with tunnel mileage was plotted, yielding a corresponding alteration evolution sequence diagram. Among these, This indicates the potassium oxide content of the altered rock mass. This indicates the magnesium oxide content of the altered rock mass. This indicates the sodium oxide content of the altered rock mass. This indicates the calcium oxide content of the altered rock mass.

[0074] Altered Rock Mass Quality Index (ABQ) Sequence: To simplify the engineering properties of complex altered geological bodies at logging points into a relatively unified and objective characterization method, this invention establishes the Altered Rock Mass Quality Index (ABQ). Its core is to use the rock compressive strength obtained from the aforementioned point load tests... (Unit: MPa) and rock mass integrity coefficient obtained from structural surface mapping The integration and fusion of these two crucial parameters provides field engineers with a unified "benchmark" for representing the engineering properties of complex altered geological bodies. The specific calculation method is as follows:

[0075] ;

[0076] in, This represents the uniaxial compressive strength of rock (unit: MPa). This represents the rock mass integrity coefficient.

[0077] Simultaneously, the curves of altered rock mass quality index (ABQ) with tunnel mileage were plotted. Finally, the curves of alteration intensity index (AI), adverse alteration mineral content index (CI), altered rock mass quality index (ABQ), and tunnel water discharge status index (QI) with tunnel mileage were combined with advanced geological prediction data and tunnel sidewall lithology logging according to tunnel mileage to obtain the corresponding alteration evolution sequence diagram.

[0078] S6. Construct a criterion for identifying adverse erosion variants and determine whether the erosion evolution sequence diagram meets the criterion. If it does not meet the criterion, return to step S1. If it meets the criterion, extrapolate the trend of the morphological indicators of adverse erosion variants and construct a disaster evaluation system.

[0079] The criteria for identifying undesirable alteration types are:

[0080] (1) The AI ​​index decreased and the CI index increased synchronously. After reaching a high point, the AI ​​index showed a downward trend, indicating that the alteration environment was shifting towards a state conducive to the formation of undesirable alteration minerals. At the same time, the CI index increased synchronously, which means that the curve of undesirable alteration mineral content index changed from a stable state to the starting point of a continuous increase.

[0081] (2) CI>0.5. When the index of undesirable alteration mineral content CI>0.5, it indicates that the geological body has entered a stage of significant development of undesirable alteration.

[0082] (3) The ABQ index decreased significantly, indicating that the engineering properties of the tunnel surrounding rock deteriorated significantly.

[0083] If any of the above conditions are met, the identification criteria are considered met.

[0084] The established criteria for identifying adversely altered geological bodies are compared with the alteration evolution sequence. If any of the criteria are met, the next cycle of excavation continues until the criteria are met.

[0085] If the identification criteria are met, trend extrapolation is performed on the adverse alteration indicators to construct a catastrophic assessment system. This step is the core decision-making step connecting the "alteration evolution sequence" and "geophysical interpretation." Its purpose is to extrapolate known geological markers to the unknown anomaly area ahead of the tunnel face and determine the potential catastrophic types and risks. The specific implementation process is as follows:

[0086] On the alteration geology-tunnel spatial projection map, the range of the target anomaly zone Z is plotted, and the trend extrapolation of key quantitative indicators is performed on the unexcavated section where the target anomaly zone Z is located.

[0087] Quantitative index trend extrapolation: Based on the linear relationship between the CI index, AI index, ABQ index, and other quantitative data sequences of the excavated section and the advanced geological prediction data, trend extrapolation is performed to the unexcavated section ahead of the tunnel face. The average or weighted average of the measured data of adverse alteration quantitative indicators from multiple logging points closest to the geophysical anomaly zone in the excavated section, along with the weighted average of the P-wave velocity of the rock mass, are selected. Combined with the weighted average of the P-wave velocity of the rock mass in the geophysical anomaly zone, the predicted values ​​of the adverse alteration quantitative indicators are obtained, thus achieving trend extrapolation of the adverse alteration quantitative indicators. The weights of the weighted average of the P-wave velocity of the rock mass in the geophysical anomaly zone correspond to the mileage between logging points. Predicted values ​​of key quantitative indicators within anomaly zone Z are generated. , ).

[0088] The calculation formula is as follows:

[0089]

[0090]

[0091]

[0092] in, This represents the predicted value of the undesirable alteration mineral content index (CI). This represents the average or weighted average of the CI (Compatibility Index) data from multiple logging points closest to the geophysical anomaly zone in the excavated section. This represents the weighted average of the P-wave velocities of the rock mass at multiple logging points closest to the geophysical anomaly zone in the excavated section. This represents the weighted average value of the P-wave velocity in the rock mass within the geophysical anomaly zone. This represents the predicted value of the altered rock mass quality index ABQ. This represents the average or weighted average of the ABQ measured data from multiple logging points closest to the geophysical anomaly zone in the excavated section. This represents the longitudinal wave velocity of the rock mass at the i-th recording point. This represents the mileage between the i-th and (i-1)-th logging points.

[0093] Outflow status indicators Quantitative index extrapolation: Based on the TSP and GPR geophysical exploration results, the water discharge status indicators of the unexcavated section were extrapolated. Make predictions.

[0094] The calculation formula is as follows:

[0095]

[0096]

[0097] in, This represents the predicted value of the effluent quality index (QI), where a and b are regression coefficients. It is the water abundance index. Indicates the longitudinal wave velocity of the rock mass. This indicates the transverse wave velocity of the rock mass.

[0098] Collect the WBI values ​​of each excavated section and their corresponding actual observed QI, and perform linear regression fitting to obtain regression coefficients a and b.

[0099] Based on the predicted values ​​of the variable indicators of poor corrosion, the trend of the variable indicators of poor corrosion is extrapolated.

[0100] A multi-factor catastrophic assessment system was constructed: a quantitative catastrophic assessment system for adverse altered geological bodies in the unexcavated section ahead of the tunnel face was established. This system includes multiple evaluation indicators such as the integrity of the altered rock mass, water-bearing status, and the degree and scale of adverse alteration. The specific classification standards for each evaluation indicator are shown in Table 2-5.

[0101] Table 2 Classification of Integrity Degree of Altered Rock Mass

[0102]

[0103] Table 3 Classification of Water-Bearing State of Surrounding Rock

[0104]

[0105] Table 4 Classification of Unfavorable Alteration Degrees in Altered Rock Masses

[0106]

[0107] Table 5. Classification of the Size of Adverse Altered Geological Bodies

[0108]

[0109] Weights and scoring criteria are assigned to each level of each evaluation indicator, and the specific values ​​and calculation methods are shown in Table 6.

[0110] Table 6 Quantitative Assessment Model for Disasters

[0111]

[0112] The calculated quantitative assessment result S of the catastrophic event determines the catastrophic potential of the anomalous area ahead of the tunnel face. Based on the quantitative assessment result S, the catastrophic potential is classified into "extremely high," "high," "relatively high," "medium," and "relatively low" according to S≥4.0, 4.0>S≥3.0, 3.0>S≥2.0, 2.0>S≥1.0, and 1.0>S, respectively. Furthermore, considering that the water abundance, mudification degree, rock mass integrity, and scale of the anomalous area ahead of the tunnel face, whether individually or in combination, determine the phenomena, scale, and duration of the catastrophic event, catastrophic identification is output separately for sudden surge disasters and deformation disasters, as detailed below:

[0113] Results of sudden gas surge disaster identification: First, the potential level of the sudden gas surge disaster is determined and output based on the calculated quantitative evaluation result S. Then, the characteristics of the sudden gas surge disaster are determined and output based on the water abundance, mudification degree, rock mass integrity, and scale level indicators. The possible output results of sudden gas surge disasters in the abnormal area ahead of the tunnel face are shown in Table 7.

[0114] Table 7. List of possible output results for sudden surge disaster identification

[0115]

[0116] First, the potential level of deformation anomaly disaster is determined and output based on the calculated quantitative evaluation result S. Then, the characteristics of deformation anomaly disaster are determined and output based on the water abundance, mudification degree, rock mass integrity, and scale level indicators. The possible output results of deformation anomaly disaster in the anomaly zone in front of the tunnel face are shown in Table 8.

[0117] Table 8. List of possible output results for deformation anomaly disaster identification

[0118]

[0119] To verify the effectiveness of the method of the present invention, tunnel disaster identification was carried out in the study area. During the excavation of the tunnel in the study area, undesirable alteration minerals such as altered sericite and altered chlorite were found in the sidewall rock mass (numbered S1), indicating that there may be undesirable altered geological bodies ahead of the tunnel face.

[0120] Advanced geological prediction work was carried out on the rock mass in front of the tunnel face. The TSP and ground-penetrating radar methods were used to detect the area in front of the tunnel face. No obvious anomalies were found in the S2 section, and normal excavation was carried out. In the S3 section, a low wave velocity and low resistivity anomaly area was delineated and identified as the target anomaly area Z. After recording its mileage range, detailed geological logging of the sidewall alteration of the excavated section was carried out.

[0121] Along the excavation direction, a recording point is set every 5 meters on the sidewall of the excavated tunnel. For key sections with obvious erosion, the spacing between the recording points is increased to 1-2 meters, and the tunnel mileage is recorded.

[0122] Detailed investigations and records were conducted at each logging point: the lithology of the area with unfavorable alteration minerals was found to be vault granite, with a width of 121m. The vault granite is intrusively in contact with the tuff (host rock) at a steep dip. It is light pink, with a medium-grained granitic texture, vault-massive structure, relatively well-developed joints and fissures, poor rock mass integrity, but high rock mass strength.

[0123] The albite-altered granite is adjacent to the vugite and is not fully exposed. The rock mass has a massive structure, but with increasing alteration, it gradually transitions from light red to light gray, and from a medium-grained granitic texture to a metamorphic texture. Simultaneously, with intensifying alteration, joints and fissures gradually increase and become more developed; the integrity of the rock mass gradually deteriorates, becoming more fragmented; and the strength of the rock mass gradually decreases.

[0124] Detailed Alteration Geological Logging Reference of Embodiments of the Invention Figure 3 , Figure 3 It shows the lithological evolution sequence of the excavated tunnel mileage, including rock mass structure, alteration characteristics, alteration boundaries, and spatial relationship with the tunnel axis.

[0125] Systematic in-situ testing was conducted at the established logging points: Structural plane mapping was performed using steel rulers and geological compasses, measuring the number, spacing, opening, and occurrence of joints, fissures, and weak interlayers. It was found that from the vugite to the albite-altered granite section, the joints and fissures gradually became denser, and the rock mass integrity continuously deteriorated (measured volumetric joint count of the rock mass). By referring to the correspondence table of rock mass integrity indices, the rock mass integrity indices of the vug granite and the albite-altered granite were obtained. The values ​​are 0.65 and 0.48, respectively.

[0126] Rock strength testing was conducted using point load strength tests. Rock samples from both the vault granite and albite-altered granite sections were tested separately. The failure load and dimensions of the samples from each rock mass section were recorded, and the point load strength index was calculated. The results showed that the point load strength of the vault granite and albite-altered granite... The pressures are 9.0 MPa and 5.5 MPa, respectively; according to empirical formulas... The uniaxial compressive strength values ​​of the vug granite and the albite-altered granite were calculated to be 118.7 MPa and 82.2 MPa, respectively, through point load strength tests. Similarly, the uniaxial compressive strength values ​​of the five measuring points in front of the anomaly zone Z were 118.7 MPa, 82.2 MPa, 98.7 MPa, 85.2 MPa, and 81.8 MPa.

[0127] Groundwater condition measurements were conducted using a combination of manual visual inspection and weir monitoring. Seepage patterns and total drainage flow were recorded. No seepage was found in the crystal-clear granite section, but significant seepage was observed in the albite granite section. Weir monitoring was performed. Water volume per 10m tunnel length (L / min·10m). The water flow is in the form of rain or linear flow, and the water outlet is relatively turbid and carries mud and sand.

[0128] Representative rock cuttings or rock powder samples were collected at logging points on the tunnel sidewalls and rapidly scanned on-site using a handheld X-ray fluorescence spectrometer (pXRF) to obtain... , , , The content of major components was determined; and a portable near-infrared spectrometer was used to quantitatively analyze undesirable altered minerals such as altered sericite, altered chlorite, altered kaolinite, altered montmorillonite, and altered illite.

[0129] The above-mentioned cataloged data and in-situ test data were precisely matched according to tunnel mileage. Alteration variation indicators were extracted and an alteration evolution sequence model was constructed: the adverse alteration mineral content index (CI) and the alteration intensity index (AI) were calculated.

[0130] Undesirable alteration minerals refer to sericite, chlorite, kaolinite, montmorillonite, illite, etc. The undesirable alteration mineral content index (CI) is defined as the undesirable alteration mineral content / total minerals, and the alteration intensity index (AI) is calculated using the formula... Calculations are performed to obtain specific data and plot the corresponding change curves for tunnel mileage. The adverse erosion variation curve reference of this embodiment of the invention is as follows. Figure 4 , Figure 4 The changes in the measured values ​​of AI and CI for the tunnel's excavated mileage are shown.

[0131] The basic alteration quality index (ABQ) of the altered rock mass was calculated. The ABQ value of the vug granite was greater than 600, and the ABQ value of the albite-altered granite was 457. The ABQ value was plotted as a function of distance to form a complete alteration evolution sequence diagram. The alteration evolution sequence diagram of this invention is for reference. Figure 5 , Figure 5 The lithological evolution sequence of the tunnel excavation mileage in the embodiment is shown, including the rock mass structure, alteration characteristics, alteration boundaries, and spatial relationship with the tunnel axis.

[0132] Based on quantitative indicators and evolutionary sequences, the patent identification criteria are verified as follows: After the AI ​​index reaches its peak in the albite granite section, it plateaus and gradually declines, while the CI index continues to rise synchronously, which meets the identification characteristics of "AI index plateau / decline + CI index rise"; the BQ value decreases significantly from the vugite granite to the albite granite section, which meets the identification requirement of "significant decrease in BQ index". Based on this, it is determined that the quantitative identification of geophysical anomaly areas needs to be initiated; if any of the above conditions are not met, the next cycle of excavation continues and the logging and testing process is repeated.

[0133] Trend extrapolation of key quantitative indicators for the Z section of the target anomaly area: Based on the linear relationship between CI, QI, ABQ indices of the excavated section and advanced geological prediction data, the quantitative indicators of the Z section of the anomaly area are predicted.

[0134] The uniaxial compressive strength values ​​of the rock mass at five measuring points in front of the anomalous zone, as determined by point load tests, were 118.7 MPa, 82.2 MPa, 98.7 MPa, 85.2 MPa, and 81.8 MPa, respectively. Based on statistical analysis of the rock mass structural surfaces, the rock mass integrity indices were calculated to be 0.65, 0.60, 0.55, 0.40, and 0.40, respectively. The calculated ABQ values ​​for each segment were 528, 497, 476, 398, and 398, respectively. The weighted average of the longitudinal wave velocity and ABQ value of the sampled rock mass was then calculated. , The weighted average P-wave velocity of the Z rock mass in the anomaly zone is 4650 m / s and 475 m / s. It is 3100 m / s, according to get The value is 317, which is classified as Class IV surrounding rock, indicating it is fractured.

[0135] The average value of the measured CI values ​​of the surrounding rock in the tunnel section ahead of the anomaly zone is calculated by averaging the measured data from five sampling points ahead. Calculate the weighted average value of the P-wave velocity of the rock mass in the corresponding sampling segment. =4650 m / s and the weighted average of the P-wave velocity of the Z rock mass in the anomaly zone. =3100 m / s, then according to That is, to obtain The calculation formula is =0.72.

[0136] Based on the water discharge status of five measuring points ahead of the Z-zone of the excavated section anomaly, combined with TSP wave velocity data, a linear regression method was used to determine the groundwater occurrence ahead of the tunnel face. Calculate; establish the target linear equation as: QI = 52.63 × WBI + 21.05; combine the TSP data of the anomaly region Z with... Substituting into the fitting equation, we finally obtain the anomaly region Z. The value is approximately 127 (L / min) 10m), complete the alteration evolution sequence diagram as follows Figure 6 , Figure 6 This is a sequence diagram of alteration evolution including extrapolated data from an embodiment of the present invention. Figure 6 The lithological evolution sequence of the tunnel excavation mileage in the embodiment is shown, including the rock mass structure, alteration characteristics, alteration boundaries and spatial relationship with the tunnel axis, as well as the predicted values ​​of CI, ABQ and QI.

[0137] Substituting the various judgment indicators of anomaly zone Z into the disaster quantitative evaluation model, the comprehensive score of anomaly zone Z, S, is ≥ 4.0. The attribute output and disaster potential judgment show that anomaly zone Z is an "extremely high" risk adverse alteration geological body, and the potential disaster is the sudden inrush of mud-water mixture. According to the geophysical exploration, the range of the anomaly zone, L, is about 15m. The comprehensive judgment is that it is a large-scale, extremely high risk mud-water mixture sudden inrush risk, and it is recommended to take advanced pre-grouting measures.

[0138] In one exemplary embodiment, a computer-readable storage medium is included, which stores a computer program that, when executed by a processor, implements the above-described method for identifying tunnel adverse geological bodies based on alteration geological evolution sequences.

[0139] Please see Figure 7 In one exemplary embodiment, the device further includes an electronic device including at least one processor, at least one memory, and at least one communication bus.

[0140] The memory stores a computer program, which includes computer-readable instructions. The processor calls the computer-readable instructions stored in the memory through the communication bus to execute the above-mentioned method for identifying tunnel adverse geological bodies based on the alteration geological evolution sequence.

[0141] In one exemplary embodiment, a computer program product is proposed, including a computer program / instruction that, when executed by a processor, implements the steps of the above-described method for identifying catastrophic geological features in tunnels based on alteration geological evolution sequences.

[0142] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A tunnel unfavorable geological body disaster identification method based on an alteration geological evolution sequence, characterized in that, The method comprises the following steps: S1, comprehensive advanced geological prediction is carried out on the unexcavated section of the excavated tunnel where the adverse alteration geological body is found; S2, it is judged whether there is a geophysical anomaly area, if not, it is excavated normally and returns to step S1; if there is a geophysical anomaly area, step S3 is carried out; S3, logging measurement points are arranged along the driving direction of the side wall of the excavated section of the tunnel, the three-dimensional coordinates of the measurement points and the tunnel mileage are positioned, and the rock mass lithology, structure and alteration zoning information are recorded to obtain logging data; S4, structure surface mapping, rock strength testing, groundwater state measurement and mineralogy testing are carried out at the logging measurement points to obtain in-situ test data; S5, the logging data and the in-situ test data are corresponded according to the tunnel mileage, adverse alteration quantitative indexes are extracted, and an alteration evolution sequence diagram is drawn; The adverse alteration quantitative indexes include: adverse alteration mineral content index CI, alteration intensity index AI, altered rock mass quality index ABQ and water discharge state index QI; the calculation methods of the adverse alteration quantitative indexes CI, AI and ABQ are as follows: CI = adverse alteration mineral content / total mineral; ； ； wherein, represents the oxidized potassium content of the altered rock mass, represents the oxidized magnesium content of the altered rock mass, represents the oxidized sodium content of the altered rock mass, represents the oxidized calcium content of the altered rock mass, represents the uniaxial compressive strength of the rock, represents the rock mass integrity factor; S6, adverse alteration body identification criteria are constructed, it is judged whether the alteration evolution sequence diagram meets the identification criteria, if not, it returns to step S1; if it meets the identification criteria, trend extrapolation is carried out on the adverse alteration quantitative indexes, and a disaster evaluation system is constructed; The adverse alteration body identification criteria are: (1) AI index decreases and CI index increases synchronously; (2) CI > 0.5; (3) ABQ index decreases; Any of the above is considered to meet the identification criteria.

2. The tunnel unfavorable geological body disaster recognition method based on alteration geological evolution sequence according to claim 1, characterized in that, The comprehensive advanced geological prediction includes seismic wave reflection method and geological radar method. 3.The tunnel unfavorable geological body disaster identification method based on alteration geological evolution sequence according to claim 1, characterized in that, The formula for trend extrapolation of the adverse alteration quantitative indexes is as follows: wherein, represents the predicted value of the content index CI of the undesirable alteration minerals, represents the average or weighted average of the measured data of CI of the multiple logging points closest to the geophysical anomaly area of the excavated section, represents the weighted average of the rock mass P-wave velocity of the multiple logging points closest to the geophysical anomaly area of the excavated section, represents the weighted average of the rock mass P-wave velocity of the geophysical anomaly area, represents the predicted value of the quality index ABQ of the altered rock mass, represents the average or weighted average of the measured data of ABQ of the multiple logging points closest to the geophysical anomaly area of the excavated section, represents the rock mass P-wave velocity of the i-th logging point, represents the mileage length between the i-th logging point and the i-1-th logging point, represents the predicted value of the outflow state index QI, and a and b are regression coefficients, is the water enrichment index, represents the rock mass P-wave velocity, represents the rock mass S-wave velocity; The WBI values of each excavated section and the corresponding actual observed QI are collected, and linear regression fitting is carried out to obtain regression coefficients a and b; According to the predicted value of the adverse alteration quantitative index, trend extrapolation of the adverse alteration quantitative index is realized.

4. The tunnel unfavorable geological body disaster identification method based on the alteration geological evolution sequence according to claim 3, characterized in that, According to the predicted value of the adverse alteration quantitative index, a disaster evaluation system is constructed, which is as follows: According to the value of the degree of completeness of the altered rock mass, and different scores are given according to the degree of completeness of the altered rock mass; According to the value of the surrounding rock water enrichment state is divided, and different scores are given according to the surrounding rock water enrichment state; According to the values of the altered rock body, the degree of poor alteration of the altered rock body is divided, and different scores are given according to the degree of poor alteration of the altered rock body; Different scores are given to different scales of adverse alteration geological bodies; Quantitative indicators for adverse corrosion in abnormal areas , and The scores of the values ​​and the scores of different sizes of adversely altered geological bodies are weighted and summed to obtain the quantitative evaluation results of the disaster.

5. A computer readable storage medium storing a computer program, characterized in that: The computer program is executed by the processor to realize the method of any one of claims 1-4.

6. An electronic device, comprising: The computer program is executed by the processor to realize the method of any one of claims 1-4.

7. A computer program product comprising computer programs / instructions, characterized in that, The computer program / instructions are executed by the processor to realize the steps of the method of any one of claims 1-4.

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