A surrounding rock grade discrimination method based on elastic wave advanced geological prediction

Abstract

The application belongs to the field of advanced geological prediction, and discloses a surrounding rock grade discrimination method based on elastic wave advanced geological prediction, which comprises the following steps: collecting elastic wave advanced geological prediction data of a certain working face and performing working face geological sketching; processing the elastic wave advanced geological prediction data; discretizing the prediction parameter characteristics; establishing the corresponding relationship between the prediction parameters and the geological characteristics; determining the surrounding rock grade of each mileage point; predicting the mileage segmentation; and comprehensively analyzing and outputting the surrounding rock grade of the first prediction mileage segment. Thus, the relationship between the elastic wave advanced geological prediction parameters and the surrounding rock geological conditions is established by using the characteristics of the elastic wave advanced geological prediction parameters; the surrounding rock geological conditions represented by the prediction mileage segment are quantified by using the threshold values of the elastic wave parameters and the working face parameters; and the result of the relative working face surrounding rock grade of the prediction mileage segment is calculated by using the surrounding rock characteristics represented by the elastic wave parameters, so that the surrounding rock grade of the prediction mileage segment is quickly determined.

Description

Technical Field

[0001] This invention relates to the field of geological advanced prediction technology, and in particular to a method for determining the surrounding rock grade based on elastic wave advanced geological prediction. Background Technology

[0002] During tunnel excavation, the surrounding rock grade is an important reference indicator for guiding the construction and excavation progress. However, the technical specifications for geophysical advanced geological prediction do not explicitly stipulate that advanced geological prediction methods can be used to determine the surrounding rock grade. In actual construction, predictions are mostly based on subjective experience, and the accuracy of the determination results needs to be improved. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for determining the surrounding rock grade based on elastic wave advanced geological prediction. The method establishes the relationship between prediction parameters and geological characteristics, determines the correction method of single parameters and comprehensive parameters for the surrounding rock grade, and forms an efficient and rapid method for identifying the surrounding rock grade, which can effectively guide tunnel excavation and construction.

[0004] The objective of this invention is achieved through the following technical solution:

[0005] A method for determining the surrounding rock grade based on elastic wave advanced geological prediction, characterized in that it includes:

[0006] Advanced geological prediction data of elastic waves were collected at the tunnel face. A geological sketch of the tunnel face was created. Based on the surrounding rock grade of the tunnel face and the geological sketch, the initial model parameters required for elastic wave inversion were constrained, thereby obtaining the initial model selection for water-bearing probability, P-wave velocity, S-wave velocity, and Poisson's ratio parameters. The predicted mileage segment K was discretized into K0. i The distance between mileage points, K for each mileage point i The parameter characteristics within are used by the mileage point K. i The parameters of the observation center point are replaced by comprehensive characteristic values; a threshold for judging stress gradient value and surrounding rock integrity is established to determine the surrounding rock integrity of the rock mass based on the stress gradient value, and the structural characteristics and hardness of the rock mass and the relative relationship with the tunnel face are predicted based on the P-wave velocity ratio, S-wave velocity ratio, P-wave velocity change rate, and Poisson's ratio, thereby determining the surrounding rock grade at each mileage point; the surrounding rock grade change characteristics and duration of the predicted tunnel are determined based on lithological characteristics, and the segment mileage location is determined based on lithological change characteristics and spatial distribution characteristics of each parameter; the surrounding rock grade of each segment mileage is analyzed segment by segment until the surrounding rock grade of the entire predicted tunnel segment mileage is determined, and the surrounding rock grade of the entire segment mileage is output and predicted.

[0007] Further, the step of constraining initial model parameters required for elastic wave inversion according to the surrounding rock grade of the bedding plane and based on the geological sketch includes: setting initial X, Y, Z three-dimensional space P-wave velocity values within the P-wave velocity range specified by the surrounding rock grade specification, and constructing an initial P-wave velocity model as a starting point for elastic wave inversion calculation; constructing an initial water-bearing probability model and an initial Poisson's ratio model according to the obtained water-bearing condition, and calculating a S-wave velocity model according to the initial Poisson's ratio model and the P-wave velocity model:

[0008]

[0009] wherein, is the initial Poisson's ratio model, is the initial P-wave velocity model, is the S-wave velocity model; and the inversion obtains stress gradient, water-bearing probability, P-wave velocity, S-wave velocity, and Poisson's ratio parameters.

[0010] Further, the step of discretizing the predicted mileage section K into K i interval mileages, and replacing the parameter characteristics of each mileage point K i with the parameter comprehensive characteristic value of the observation center point of the mileage point K i , wherein the characteristic parameters include:

[0011] a series of stress gradient values of each mileage point in the segmented mileage:

[0012]

[0013] a series of water-bearing probabilities of each mileage point in the segmented mileage:

[0014]

[0015] a series of P-wave velocities of each mileage point in the segmented mileage:

[0016]

[0017] a series of S-wave velocities of each mileage point in the segmented mileage:

[0018]

[0019] a series of Poisson's ratios of each mileage point in the segmented mileage:

[0020] .

[0021] Further, the step of calculating the P-wave velocity ratio K vp in the P-wave velocity ratio, S-wave velocity ratio, P-wave velocity change rate, and Poisson's ratio value includes:

[0022]

[0023] wherein is the longitudinal wave velocity of the first 3m, is an intermediate variable, i∈(1,100); the transverse wave velocity ratio K is calculated as: vs

[0024]

[0025] wherein is the transverse wave velocity of the first 3m, is an intermediate variable, i∈(1,100); the longitudinal wave velocity variation rate is calculated as:

[0026]

[0027] wherein j is the interval between each mile point, i is an intermediate variable, i∈(1,100).

[0028] Further, the value predicts the relative relationship between the structural characteristics and hardness of the rock mass and the tunnel face, which comprises: determining the structural characteristics and hardness by using the wave velocity characteristics, forming the upper and lower threshold values K1' and K1 of the longitudinal wave velocity ratio, the upper and lower threshold values K2' and K2 of the transverse wave velocity ratio, and the threshold value K3 of the longitudinal wave velocity variation rate; the determination results include: case 1: when K1' > K1, K2' > K2, or K3 ≥ K3, <0.35, the hardness of the surrounding rock is one level higher than that of the tunnel face, and the joint fissure development degree of the structural surface is consistent with that of the tunnel face; case 2: when K1' > K1, K2' > K2, and K3 < K3, <0.35, the hardness of the surrounding rock is one level higher than that of the tunnel face, and the joint fissure development degree of the structural surface is weaker than that of the tunnel face; case 3: when K1' > K1, K2' < K2, K2 ≤ K2, and K3 < K3, <0.35, the hardness of the surrounding rock is consistent with that of the tunnel face, and the joint fissure development degree of the structural surface is weaker than that of the tunnel face; case 4: when K1' ≤ K1, K2' < K2, K2 ≤ K2, or K3 ≥ K3, ≥0.35, the hardness of the surrounding rock is consistent with that of the tunnel face, and the joint fissure development degree of the structural surface is stronger than that of the tunnel face; case 5: when K1' ≤ K1,​ ≤ K2', or ≥ K3, ≥ 0.35, the hardness of the surrounding rock and the hardness of the surrounding rock of the working face are reduced by one level, and the joint fissure development degree of the structural surface is stronger than that of the working face; case 6: when ≤ K1', ≤ K2', and < K3, ≥ 0.35, the hardness of the surrounding rock and the hardness of the surrounding rock of the working face are reduced by one level, and the joint fissure development degree of the structural surface is consistent with that of the working face; otherwise, it is determined that the strength of the surrounding rock and the joint fissure development degree of the working face are consistent.

[0029] Further, the water content probability value is connected with the groundwater development situation, and the water content probability spatial distribution characteristics and the threshold The water enrichment situation of the surrounding rock is divided into dry or humid, seepage water, linear flow water, and gushing water.

[0030] Further, the determination of the surrounding rock grade of each mileage point includes comprehensive determination of the hardness, integrity, structural characteristics, and water enrichment situation of the surrounding rock to determine the surrounding rock grade of each point; wherein, the comparison result of the surrounding rock integrity obtained based on the stress gradient and the working face, and the change of the structural characteristics and hardness of the surrounding rock relative to the working face based on the longitudinal and transverse wave velocity ratio, the longitudinal wave velocity change rate, and the Poisson ratio are used to comprehensively determine the change of the surrounding rock grade of the mileage point relative to the surrounding rock grade of the working face.

[0031] Further, the comprehensive determination of the change of the surrounding rock grade of the mileage point relative to the surrounding rock grade of the working face includes: the conditions for increasing the grade by one level are that the surrounding rock integrity degree obtained based on the stress gradient is consistent with the working face, and the wave velocity parameter determination result belongs to case 2; or the surrounding rock integrity degree obtained based on the stress gradient is better than the working face, and the corresponding wave velocity parameter determination result belongs to case 1 or case 2 or case 3. The conditions for reducing the grade by one level are that the surrounding rock integrity degree obtained based on the stress gradient is consistent with the working face, and the wave velocity parameter determination result belongs to case 5. Or the surrounding rock integrity degree obtained based on the stress gradient is worse than the working face, and the corresponding wave velocity parameter determination result belongs to case 4 or case 5 or case 6; the condition for no change is that if the determination of a certain mileage point does not satisfy any of the above conditions, it is determined that the surrounding rock grade at this point is consistent with the surrounding rock grade of the working face, and no adjustment is required; after determining the surrounding rock grade corresponding to each mileage point, the surrounding rock grade is corrected according to the water enrichment situation: if the water enrichment situation is linear flow water or gushing water, the surrounding rock grade is reduced by one level, and if the surrounding rock grade is the worst surrounding rock grade, the surrounding rock grade does not change; if the water enrichment situation is dry or humid, or seepage water, the surrounding rock grade does not change.

[0032] Further, the tunnel lithology characteristics are determined to determine whether the surrounding rock grade of the predicted tunnel changes frequently, the surrounding rock grade change characteristics and duration of the predicted tunnel are determined according to the lithology characteristics, and the segmented mileage position is determined based on the lithology change characteristics and through the spatial distribution characteristics of the parameters, including: the total length of the one-time prediction is divided into a plurality of predicted segmented mileages ; wherein the segmented mileage position does not separate the continuous surrounding rock stress characteristics, the segmented mileage position does not separate the distribution characteristics of a certain continuous water body, and the segmented mileage position does not separate the high-speed trap zone or the low-speed trap zone.

[0033] Further, the surrounding rock grade of each segmented mileage is analyzed segment by segment until the surrounding rock grade determination of the entire segmented mileage is completed, and the predicted surrounding rock grade of the entire mileage segment is output, including: the surrounding rock grade of the segmented mileage Y i is determined, the segmented mileage Y i length N is counted, the proportion of various surrounding rock grades in the segmented mileage is calculated, the maximum surrounding rock grade proportion value is taken as the surrounding rock grade of the segmented mileage, and if the surrounding rock grades at the rear proportion are continuously distributed and the continuous data exceeds 6, the surrounding rock grades including the maximum proportion and the continuous surrounding rock grades are output in the predicted mileage. The surrounding rock grade is analyzed segment by segment until the surrounding rock grade determination of the entire segmented mileage is completed, and the predicted surrounding rock grade of the entire segmented mileage is output.

[0034] The beneficial effects of the present application are:

[0035] The method of the present application overcomes the short board of requiring a large amount of field test data and manual experience in surrounding rock grade identification, and only relies on elastic wave advanced geological prediction parameters to realize efficient, rapid and intelligent surrounding rock grade identification, saves construction cost, and improves construction efficiency. The present application uses the characteristics of elastic wave advanced geological prediction parameters to establish the relationship between the elastic wave advanced geological prediction parameters and the surrounding rock geological conditions; through the threshold values of the elastic wave parameters and the working face parameters, the surrounding rock geological conditions represented by the segmented mileage are quantified; the surrounding rock characteristics represented by the elastic wave parameters are used to calculate the surrounding rock grade of the segmented mileage relative to the working face, and the determination of the surrounding rock grade of the segmented mileage is quickly realized. The prediction effect is more efficient and rapid. A high-efficiency and convenient method is provided for rapid identification of the surrounding rock grade, and the speed and efficiency of the surrounding rock grade identification are improved.

[0036] In other words, the application uses the geological sketch results of the working face and the elastic wave data inversion parameter characteristics in the elastic wave advanced geological prediction, forms a threshold determination condition flow process of surrounding rock grade determination through multiple excavation verifications, and overcomes the technical problems that the elastic wave geological prediction data mainly depends on the personal experience of the technical personnel, the surrounding rock grade determination is highly subjective, and the experience requirement is high. Therefore, the method obtains the prediction data based on the elastic wave advanced geological prediction, reveals the surrounding rock geological conditions, further obtains the changes of the surrounding rock geological structure characteristics, forms the threshold model of each tunnel, and finally determines the surrounding rock grade, realizes the rapid and intelligent determination of the surrounding rock grade, and improves the determination accuracy and efficiency of the surrounding rock grade. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 FIG. 1 is a flowchart of a surrounding rock grade determination method based on elastic wave advanced geological prediction according to an embodiment of the application. DETAILED DESCRIPTION

[0038] The technical solutions of the application will be described clearly and completely below with reference to the embodiments. Obviously, the described embodiments are only some of the embodiments of the application, but not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the application.

[0039] Reference Figure 1 For better understanding, the application provides a surrounding rock grade determination method based on elastic wave advanced geological prediction. The stress gradient, water content probability, P-wave and S-wave velocity, Poisson's ratio and other parameters obtained by elastic wave data inversion are used to determine the relative good and bad of the geological conditions of the prediction point and the geological conditions of the working face, determine the surrounding rock grade of each mileage point, and determine the mileage segmentation of the first prediction result through the parameter space distribution characteristics, comprehensively analyze and determine the surrounding rock grade of the segmented mileage. The method specifically includes the following steps:

[0040] S1, use an instrument (such as a seismograph) to collect elastic wave advanced geological prediction data at the working face, and make a geological sketch of the working face. The geological sketch content includes lithology, weathering degree, joint development condition (such as joint number and spacing), water content and other geological information.

[0041] In some examples, the elastic wave advanced geological prediction system can be based on the observation mode to collect the elastic wave advanced geological prediction data with good signal-to-noise ratio, and make a detailed geological sketch of the working face including lithology, weathering degree, joint development condition, joint number, water content and other geological conditions.

[0042] S2, elastic wave advanced geological prediction data processing is performed, initial model parameters (for example, P-wave velocity) required for elastic wave inversion are constrained according to the surrounding rock grade of the working face and based on the geological sketch, and initial model selection of parameters such as water-bearing probability, P-wave velocity, S-wave velocity, and Poisson's ratio is obtained, and initial model values that are more consistent with geological conditions are obtained.

[0043] Specifically, an initial surrounding rock grade of the working face is inferred according to the geological sketch of the working face (such as the number of joints, spacing, lithology, and water-bearing condition as described above). The inferred surrounding rock grade is used to constrain the initial model parameters (mainly P-wave velocity) required for elastic wave inversion. The constraint process is as follows:

[0044] Based on the inferred surrounding rock grade of the geological sketch, initial P-wave velocity values in X, Y, and Z three-dimensional space are set within the P-wave velocity range given in the corresponding surrounding rock grade specification, and a three-dimensional initial P-wave velocity model is constructed. This model will serve as the starting point for elastic wave inversion calculation.

[0045] Based on the water-bearing condition obtained in S1, an initial water-bearing probability model and an initial Poisson's ratio model are constructed. For example, when the water-bearing condition of the working face is dry or moist, the initial water-bearing probability value is 30%, and the Poisson's ratio value is 0.27-0.28; when the water-bearing condition of the working face is dripping water or seepage water, the initial water-bearing probability value is 50%, and the Poisson's ratio value is 0.29-0.30.

[0046] Then, according to the initial Poisson's ratio model and the initial P-wave velocity model , the initial S-wave velocity model is obtained according to the calculation formula .

[0047] Based on the foregoing, the P-wave velocity, S-wave velocity, water-bearing probability, Poisson's ratio, and initial velocity model are input into the elastic wave geological prediction data processing module, and stress gradient, water-bearing probability, wave velocity, and Poisson's ratio parameters are obtained by inversion. For example, the elastic wave geological prediction data processing module can use professional elastic wave advanced geological prediction data processing software to obtain stress gradient, water-bearing probability, P-wave velocity, and S-wave velocity parameters.

[0048] S3, the predicted mileage section K is discretized into K i mileage intervals, and the parameter characteristics in each mileage point K i are replaced by the parameter comprehensive characteristic value of the observation center point of the mileage point K i ; wherein the parameter characteristics include stress gradient value, water-bearing probability, P-wave velocity, S-wave velocity, and Poisson's ratio.

[0049] Specifically, the 100m section of the forecast is discretized into 1m interval mile, and the parameter characteristics of each mile are replaced by the parameter comprehensive characteristic value of the observation center point; the parameter value of the observation center point is calculated, and the observation center point position of each mile is taken as the center to take the three-dimensional space, and the stress gradient values of all points in the space are weighted and averaged to obtain a stress gradient value stress center1 The stress gradient values of the mile points in the segmented mile are calculated in turn 100 in total, and in the same way, the following method is used to obtain in turn:

[0050] A series of water content probabilities of the mile points in the segmented mile:

[0051]

[0052] A series of P-wave velocities of the mile points in the segmented mile:

[0053]

[0054] A series of S-wave velocities of the mile points in the segmented mile:

[0055]

[0056] A series of Poisson's ratios of the mile points in the segmented mile:

[0057] .

[0058] S4, build a qualitative semi-quantitative relationship between commonly used parameters and surrounding rock geological characteristics, including establishing the corresponding relationship between stress gradient value and surrounding rock integrity, specifically, establishing the stress gradient value and the determination threshold of surrounding rock integrity (stress gradient is an important parameter indicating the degree of surrounding rock integrity), according to the stress gradient value, the rock mass can be divided into complete, relatively complete, poor integrity, relatively broken, broken; And according to the P-wave velocity ratio, S-wave velocity ratio and P-wave velocity change rate, Poisson's ratio to predict the relative relationship between the structure characteristics and hardness of the rock mass and the working face.

[0059] In detail, the P-wave velocity ratio, S-wave velocity ratio and P-wave velocity change rate, Poisson's ratio are used to predict the relative relationship between the structure characteristics and hardness of the rock mass and the working face, including:

[0060] Calculate the P-wave velocity ratio K vp :

[0061] Further, considering that the lithological characteristics of a general rock mass within 3m range hardly change, the P-wave velocity of the first 3m is taken instead of the P-wave velocity characteristics of the surrounding rock working face:

[0062] .

[0063] Calculate the shear wave velocity ratio K vs : Similarly The shear wave velocity of the first 3m is K .

[0064] Calculate the longitudinal wave velocity variation rate. For example, the longitudinal wave velocity variation rate with a distance of 1m at the mile point is:

[0065]

[0066] In other examples, the longitudinal wave velocity variation rate with a distance of 2m is:

[0067] .

[0068] Then, the wave velocity characteristics are used to determine the structure characteristics and hardness, and the upper and lower threshold values K1' and K1 of the longitudinal wave velocity ratio of the predicted tunnel, the upper and lower threshold values K2' and K2 of the shear wave velocity ratio, and the threshold value K3 of the longitudinal wave velocity variation rate are formed. Specifically, it includes:

[0069] Case 1: when >K1, >K2, Or ≥K3, <0.35, the hardness of the surrounding rock is one higher than that of the working face, and the joint fissure development degree of the structure surface is consistent with that of the working face;

[0070] Case 2: when >K1, >K2, And <K3, <0.35, the hardness of the surrounding rock is one higher than that of the working face, and the joint fissure development degree of the structure surface is weaker than that of the working face;

[0071] Case 3: when >K1, K2' < K2, ≤K2, And <K3, <0.35, the hardness of the surrounding rock is consistent with that of the working face, and the joint fissure development degree of the structure surface is weaker than that of the working face;

[0072] Case 4: when ≤K1', K2' < K2, ≤K2, Or ≥K3, ≥0.35, the hardness of the surrounding rock is consistent with that of the working face, and the joint fissure development degree of the structure surface is stronger than that of the working face;

[0073] Case 5: When ≤ K1’, ≤ K2’, or ≥ K3, ≥ 0.35, the hardness of the surrounding rock is reduced by one level compared to the hardness of the surrounding rock at the working face, and the joint fissure development degree of the structural plane is stronger than that at the working face;

[0074] Case 6: When ≤ K1’, ≤ K2’, and < K3, ≥ 0.35, the hardness of the surrounding rock is reduced by one level compared to the hardness of the surrounding rock at the working face, and the joint fissure development degree of the structural plane is consistent with that at the working face;

[0075] In other cases, it is determined that the strength of the surrounding rock is consistent with the joint fissure development degree at the working face.

[0076] The water-bearing probability value is related to the groundwater development situation. The water-bearing probability mainly reflects the water-rich situation of the surrounding rock. According to the spatial distribution characteristics and threshold values of the water-bearing probability The water-rich situation of the surrounding rock can be divided into dry or humid, seepage water, linear flow water, and gushing water.

[0077] In the above determination process, the threshold values of the parameters reflecting the characteristics of the surrounding rock are corrected through multiple actual excavation results.

[0078] S5, determine the surrounding rock grade at each mileage point, including determining the hardness, integrity, structural characteristics, and water-rich situation of the surrounding rock to determine the surrounding rock grade at each point.

[0079] Specifically, the comparison results of the surrounding rock integrity obtained based on the stress gradient and the change of the structural characteristics and hardness of the surrounding rock relative to the working face based on the longitudinal and transverse wave velocity ratio, longitudinal wave velocity change rate, and Poisson's ratio are used to comprehensively determine the change of the surrounding rock grade at the mileage point relative to the surrounding rock grade at the working face, including:

[0080] The condition for increasing the grade by one level, i.e., the surrounding rock becomes better, includes:

[0081] The degree of integrity of the surrounding rock obtained based on the stress gradient is consistent with that at the working face, and the wave speed parameter determination result in step 4 belongs to case 2; or the degree of integrity of the surrounding rock obtained based on the stress gradient is better than that at the working face, and the corresponding wave speed parameter determination result in step 4 belongs to case 1 or case 2 or case 3.

[0082] The condition for reducing the grade by one level, i.e., the surrounding rock becomes worse, includes:

[0083] The degree of integrity of the surrounding rock obtained based on the stress gradient is consistent with the face, and the wave velocity parameter determination result in step 4 belongs to case 5. Or the degree of integrity of the surrounding rock obtained based on the stress gradient is worse than the face, and the wave velocity parameter determination result in step 4 belongs to case 4 or case 5 or case 6.

[0084] The conditions for the grade not to change include:

[0085] If the determination of a certain mileage point does not satisfy any of the above conditions, it is determined that the surrounding rock grade at this point is consistent with the surrounding rock grade of the face, and no adjustment is needed.

[0086] After determining the surrounding rock grade corresponding to each mileage point, the surrounding rock grade is corrected according to the water enrichment condition obtained in S4: if the water enrichment condition is linear flow water, the surrounding rock grade is one grade worse, and the surrounding rock grade is already the worst, then the surrounding rock grade does not change; if the water enrichment condition is dry or humid, or dripping water, the surrounding rock grade does not change.

[0087] S6, determine whether the surrounding rock grade of the predicted tunnel changes frequently according to the lithological characteristics of the tunnel, to determine the surrounding rock grade change characteristics and duration of the predicted tunnel according to the lithological characteristics; for example, hard rock tunnels such as granitic rocks, the surrounding rock grade lasts for a longer distance; for example, sedimentary rock tunnels such as argillaceous siltstone and carbonaceous shale, the surrounding rock grade lasts for a shorter distance.

[0088] Based on the aforementioned lithological change characteristics, the segment mileage position is determined through the spatial distribution characteristics of each parameter, for example, the total length of a prediction is divided into multiple segment mileages The segment mileage position cannot separate the continuous surrounding rock stress characteristics, the segment mileage position cannot separate the distribution characteristics of a certain continuous water body, and the segment mileage position cannot separate a certain high-speed or low-speed trap zone.

[0089] S7, determine the surrounding rock grade for the segment mileage Y i , calculate the proportion of each surrounding rock grade in the segment mileage Y i , take the maximum surrounding rock grade proportion value as the surrounding rock grade of the segment mileage; if the surrounding rock grade with a late proportion is continuous and the continuous data exceeds 6, output the surrounding rock grade including the surrounding rock with the maximum proportion and the continuous surrounding rock grade; similarly, if there are multiple surrounding rocks with continuous data exceeding 6, output multiple surrounding rock grades.

[0090] Then, analyze the surrounding rock grade segment by segment according to the segment mileage , until the surrounding rock grade determination of the entire segment mileage is completed, and output the surrounding rock grade of the entire mileage segment of the prediction.​

[0091] The foregoing is considered as illustrative only of the principles of the application. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the application to the exact construction and operation described. Accordingly, all such variations are intended to be included within the scope of the present application as defined in the claims below and their equivalents.

Claims

1. A surrounding rock grade discrimination method based on elastic wave advanced geological prediction, characterized by, The method comprises the following steps: The geological sketch of the tunnel face is obtained by collecting the elastic wave data of the tunnel face, and the initial tunnel face surrounding rock grade is obtained according to the geological sketch of the tunnel face; the initial model parameters required for elastic wave inversion are constrained according to the surrounding rock grade of the tunnel face and based on the geological sketch, so that the initial model of the water-bearing probability, the longitudinal wave velocity, the transverse wave velocity and the Poisson's ratio parameters is obtained; The longitudinal wave velocity, the transverse wave velocity, the water-bearing probability and the Poisson's ratio parameters are input into the elastic wave geological prediction data processing module to obtain the stress gradient, the water-bearing probability, the longitudinal wave velocity, the transverse wave velocity and the Poisson's ratio parameters by inversion; The predicted range section K is discretized into K i ranges, each range point K i The parameter characteristics within the range point K i are replaced by the parameter synthetic characteristic value of the observation center point The stress gradient value and the determination threshold of the surrounding rock integrity are established to determine the surrounding rock integrity of the rock mass according to the stress gradient value, and the relative relationship between the structure characteristics and hardness of the rock mass and the tunnel face is predicted according to the longitudinal wave velocity ratio, the transverse wave velocity ratio, the longitudinal wave velocity change rate and the Poisson's ratio value, and the surrounding rock grade of each mileage point is determined; The surrounding rock grade variation characteristics and the duration of the predicted tunnel are determined according to the lithological characteristics, and the segmented mileage position is determined based on the lithological variation characteristics and the spatial distribution characteristics of the parameters; The surrounding rock grades of the segmented mileages are analyzed segment by segment until the surrounding rock grade determination of the entire predicted tunnel is completed, and the surrounding rock grades of the entire segmented mileages are output and predicted.

2. The method according to claim 1, wherein, The constraint of the initial model parameters required for elastic wave inversion according to the surrounding rock grade of the tunnel face and based on the geological sketch comprises: Based on the surrounding rock grade inferred from the geological sketch, the initial X, Y and Z three-dimensional spatial longitudinal wave velocity values are set within the longitudinal wave velocity range given in the surrounding rock grade specification, and a three-dimensional initial longitudinal wave velocity model is constructed as the starting point of the elastic wave inversion calculation; According to the obtained water-bearing condition, an initial water-bearing probability model and an initial Poisson's ratio model are constructed, and the initial transverse wave velocity model is calculated according to the initial Poisson's ratio model and the initial longitudinal wave velocity model: wherein, is an initial Poisson's ratio model, is an initial P-wave velocity model, is an initial S-wave velocity model.

3. The method according to claim 2, characterized in that: The predicted mileage section K is discretized into K i mileage points K i The parameter characteristics within the interval of the distance between the mileage points K i The parameter characteristics of the observation center point are replaced by the parameter comprehensive characteristic value of the mileage point K, and the parameter characteristics include: A series of stress gradient values of each mileage point in the segmented mileage: A series of water-bearing probabilities of each mileage point in the segmented mileage: A series of longitudinal wave velocities of each mileage point in the segmented mileage: A series of transverse wave velocities of each mileage point in the segmented mileage: A series of Poisson's ratios of each mileage point in the segmented mileage: 。 4. The method according to claim 3, wherein, establishing the longitudinal wave velocity ratio, the transverse wave velocity ratio, and the longitudinal wave velocity change rate, Poisson's ratio value, wherein the longitudinal wave velocity ratio K is calculated as vp K = Vp / Vs wherein is the longitudinal wave velocity for the first 3 m, i is an intermediate variable, i e (1, 100); The ratio of shear wave velocities K is calculated vs is: wherein is the shear wave velocity for the first 3 m, i is an intermediate variable, i e (1, 100); The longitudinal wave velocity change rate is calculated as: Where j is the distance between each mileage point, and i is an intermediate variable, i∈(1,100).

5. The method according to claim 4, wherein the method is characterized by, The prediction of the structure characteristics and hardness of the rock mass and the relative relationship with the tunnel face according to the longitudinal wave velocity ratio, the transverse wave velocity ratio, the longitudinal wave velocity change rate and the Poisson's ratio value comprises: The structure characteristics and hardness are determined by using the wave velocity characteristics, and the upper and lower threshold values K1' of the longitudinal wave velocity ratio, K1, the upper and lower threshold values K2' of the transverse wave velocity ratio, K2, and the longitudinal wave velocity change rate threshold value K3 are formed; the judgment result includes: Case 1: when > K1, > K2, or ≥ K3, When the surrounding rock hardness is higher than the face rock hardness by one level and the joint fissure development degree of the structural plane is consistent with the face, when the surrounding rock hardness is higher than the face rock hardness by 0.35, the surrounding rock hardness is higher than the face rock hardness by one level, and the joint fissure development degree of the structural plane is consistent with the face. Case 2: When > K1, > K2, and < K3, When the hardness ratio of surrounding rock to the face is greater than 0.35, the development degree of joint fissure of the structural plane is weaker than that of the face. Case 3: When >K1, K2' K2, and K3, When the hardness of surrounding rock is less than 0.35, the hardness of surrounding rock is consistent with the hardness of working face, and the development degree of structural plane joint fissure is weaker than that of working face. Case 4: When ≤ K1', K2' < K3 ≤ K2, or ≥ K3, ≥ 0.35, the hardness of surrounding rock is consistent with that of the working face, and the development degree of structural plane joint fissure is stronger than that of the working face; Case 5: When ≤ K1', ≤ K2', or ≥ K3, ≥ 0.35, the hardness of surrounding rock decreases by one level compared to the hardness of the working face, and the joint fissure development degree of the structural plane is stronger than that of the working face. Case 6: When ≤ K1', ≤ K2', and < K3, ≥ 0.35, the hardness of the surrounding rock decreases by one level compared to the hardness of the face surrounding rock, and the development degree of the joint fissures of the structural plane is consistent with that of the face. In other cases, it is determined that the surrounding rock strength is consistent with the joint fissure development degree of the tunnel face.

6. The method according to claim 5, wherein the method is characterized by: The water-bearing probability value is connected with the groundwater development condition, and the water-bearing probability spatial distribution characteristics and threshold value are used to determine the water-bearing probability value The water-rich conditions of surrounding rock are divided into dry or humid, seepage water, linear flow water and gushing water.

7. The method according to claim 6, wherein the method is characterized by, The determination of the surrounding rock grade of each mileage point comprises the comprehensive determination of the surrounding rock grade of each point by judging the hardness, integrity, structure characteristics and water enrichment condition of the surrounding rock; The stress gradient is used to obtain the integrity of the surrounding rock and the contrast result of the tunnel face, and the structure characteristics and hardness of the surrounding rock are determined based on the ratio of the P-wave velocity to the S-wave velocity, the P-wave velocity variation rate, and the Poisson's ratio, so as to comprehensively determine the change of the surrounding rock grade of the mileage point relative to the surrounding rock grade of the tunnel face.

8. The method according to claim 7, wherein the method is characterized by, The comprehensive determination of the change of the surrounding rock grade of the mileage point relative to the surrounding rock grade of the tunnel face comprises: The condition for increasing the grade by one level is that the integrity of the surrounding rock obtained based on the stress gradient is consistent with the tunnel face, and the wave velocity parameter determination result belongs to case 2; or the integrity of the surrounding rock obtained based on the stress gradient is better than that of the tunnel face, and the corresponding wave velocity parameter determination result belongs to case 1 or case 2 or case 3; The condition for decreasing the grade by one level is that the integrity of the surrounding rock obtained based on the stress gradient is consistent with the tunnel face, and the wave velocity parameter determination result belongs to case 5; or the integrity of the surrounding rock obtained based on the stress gradient is worse than that of the tunnel face, and the corresponding wave velocity parameter determination result belongs to case 4 or case 5 or case 6; The condition for keeping the grade unchanged is that if the determination of a certain mileage point does not satisfy any of the above conditions, it is determined that the surrounding rock grade of the mileage point is consistent with the surrounding rock grade of the tunnel face; After determining the surrounding rock grade corresponding to each mileage point, the surrounding rock grade is corrected according to the water enrichment condition: if the water enrichment condition is linear flow water or gushing water, the surrounding rock grade is reduced by one level, and if the surrounding rock grade is the worst, the surrounding rock grade does not change; if the water enrichment condition is dry or humid, or dripping water, the surrounding rock grade does not change.

9. The method according to claim 1, wherein the method is characterized by, According to the rock property characteristics of the tunnel, it is determined whether the surrounding rock grade of the predicted tunnel changes frequently, and the surrounding rock grade change characteristics and duration of the predicted tunnel are determined according to the rock property characteristics, and the segmented mileage positions are determined based on the rock property change characteristics and the spatial distribution characteristics of the parameters, comprising: dividing the total length of the first prediction into a plurality of predicted segmental distances ; The segmented mileage positions do not separate the continuous surrounding rock stress characteristics, the segmented mileage positions do not separate the distribution characteristics of a certain continuous water body, and the segmented mileage positions do not separate the high-speed or low-speed trap zones.

10. The method according to claim 9, wherein the method is characterized by, The surrounding rock grade of each segmented mileage is analyzed segment by segment until the surrounding rock grade determination of the entire segmented mileage is completed, and the predicted surrounding rock grade of the entire mileage segment is output, comprising: Segment mileage Y i Determine the surrounding rock grade, and count the segment mileage Y i Length N, calculate the proportion of various surrounding rock grades in the segment mileage, and take the maximum surrounding rock grade proportion value as the surrounding rock grade of the segment mileage; If the surrounding rock grade distribution at the rear end is continuous, and the continuous data exceeds 6, the surrounding rock with the largest proportion and the continuous surrounding rock grade are output at the predicted mileage. According to the segment mileage , the surrounding rock grade is analyzed segment by segment until the surrounding rock grade determination of the entire segment mileage is completed, and the surrounding rock grade of the entire segment mileage is output once.

Images