Tunnel water gushing risk assessment method and system based on big data and transient electromagnetic method

Abstract

The application discloses a tunnel water gushing risk assessment method and system based on big data and transient electromagnetic method, and the method comprises the following steps: determining a tunnel water-bearing structure in a digital base map according to different stratum permeability characteristics classification and the resistivity spatial distribution in front of the tunnel; dividing the tunnel water-bearing structure into a saturated area and a non-saturated area according to a saturation degree interpretation threshold of different stratum core resistivity; calculating a tunnel unit time water gushing amount; dividing a tunnel water gushing risk grade according to the tunnel unit time water gushing amount and the soft and hard degree of different strata core; outputting corresponding measures according to the tunnel water gushing risk grade; constructing a database comprising the interpretation threshold, the permeability coefficient, the soft and hard degree of different strata core, the saturated partition of the tunnel water-bearing structure, the tunnel unit time water gushing amount calculation and the tunnel water gushing risk grade division; learning based on the database, continuously accumulating to form regional experience values, and realizing efficient assessment and prevention and control of the tunnel water gushing risk according to the regional experience values.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of tunnel gushing water prevention and control, and more particularly relates to a tunnel gushing water risk assessment method and system based on big data and transient electromagnetic method. BACKGROUND

[0002] Tunnels are typical underground projects and are located in complex underground environments, and will face safety threats caused by water during construction. With the increase of the buried depth and length, the safety risks of tunnel construction and operation caused by groundwater are greater, the safety threat of tunnel engineering caused by tunnel gushing water is serious, the disaster consequences are serious, and the engineering losses are great.

[0003] The prior art generally carries out hydrogeological specialities in the survey and design stage of the tunnel, evaluates the potential gushing water of the tunnel, estimates the safety risk of the tunnel gushing water, designs certain pressure relief measures and engineering reinforcement measures, and prevents and controls the safety threat of the tunnel gushing water. There are also long-distance and short-distance combined advanced geological prediction during the tunnel construction period, combined with advanced drilling and construction records, to evaluate the gushing water safety risk caused by the water-bearing structure to the tunnel construction, take certain drainage and engineering plugging measures, and prevent and control the safety threat of the tunnel gushing water. However, these methods do not closely combine the geophysical prospecting methods and the physical properties of the rock-soil body, and are more qualitative than quantitative. The front end is disconnected from the corresponding characteristics of the rock-soil body impedance and the physical properties, so that the influence mechanism of water on the resistance characteristics of the rock-soil body is not well studied. The middle end of the transient electromagnetic method is disconnected from the engineering geological section, so that the detection and prediction results are too rough and not specific. The rear end of the transient electromagnetic method is disconnected from the tunnel water-bearing structure detection and prediction, the tunnel gushing water volume evaluation, and the gushing water risk evaluation. In other words, the front end is not covered enough, the middle end is not comprehensive enough, and the rear end is not extended enough. There is a problem of low efficiency of tunnel gushing water detection and prediction and risk assessment.

[0004] Therefore, there is an urgent need for a tunnel gushing water risk assessment method based on high-precision transient electromagnetic method detection, which has high tunnel water-bearing structure detection precision, high tunnel gushing water risk evaluation efficiency, and good tunnel gushing water risk assessment effect, and the three are coordinated and unified. SUMMARY

[0005] In order to solve the above defects or improvement requirements of the prior art, the present application provides a tunnel water gushing risk assessment method and system based on big data and transient electromagnetic method, which utilizes a tunnel axis direction engineering geological profile digital base map, different stratum coring resistivity test data, different stratum permeability characteristic test data, different stratum and tunnel water-bearing structure space coupling law data, water-bearing structure fine partition data, tunnel and saturated partition space relationship data, tunnel water gushing quantitative evaluation data, and gushing risk grading data to form a physical property database, combines the physical property database with the transient electromagnetic method tunnel water gushing risk evaluation, learns based on the database, continuously accumulates to form regional experience values, realizes efficient evaluation and prevention and control of the tunnel water gushing risk according to the regional experience values, gradually improves the detection accuracy of the transient electromagnetic method detection equipment, improves the tunnel water gushing evaluation efficiency, and improves the tunnel water gushing risk evaluation effect, and can provide a method and technical support for water gushing risk evaluation of tunnels under construction and in operation.

[0006] In order to achieve the above-mentioned purpose, one aspect of the present application provides a tunnel water gushing risk assessment method based on big data and transient electromagnetic method, comprising the following steps:

[0007] S1: constructing a tunnel axis direction engineering geological profile digital base map in a transient electromagnetic method detection software, obtaining saturation interpretation threshold values of different stratum core resistivities in the digital base map, measuring saturated permeability coefficients of different strata in the digital base map, and determining different stratum core hardness degrees;

[0008] S2: detecting and obtaining the resistivity spatial distribution in front of the tunnel by using the transient electromagnetic method, determining the tunnel water-bearing structure in the digital base map according to different stratum permeability characteristic grades and the resistivity spatial distribution in front of the tunnel;

[0009] S3: dividing the tunnel water-bearing structure into saturated zones and non-saturated zones in the digital base map according to the saturation interpretation threshold values of the different stratum core resistivities;

[0010] S4: calculating the tunnel unit time water gushing amount according to the contact area of the tunnel and each water-bearing structure saturated zone and the saturated permeability coefficients of different strata, dividing the tunnel water gushing risk grade according to the tunnel unit time water gushing amount and different stratum core hardness degrees, and outputting corresponding measures according to the tunnel water gushing risk grade;

[0011] S5: constructing a database containing the saturation interpretation threshold values of different stratum core resistivities, the saturated permeability coefficients of different strata, the different stratum core hardness degrees, the tunnel water-bearing structure saturated partition, the tunnel unit time water gushing amount calculation, and the tunnel water gushing risk grade division in the transient electromagnetic method detection software, learning based on the database, continuously accumulating to form regional experience values, and realizing efficient evaluation and prevention and control of the tunnel water gushing risk according to the regional experience values by repeating step S4.

[0012] Further, the step S1 of obtaining the saturation interpretation threshold of the core resistivity of different strata in the digitized base map comprises the following steps:

[0013] S11: Obtain the core of different strata in the digitized base map of the engineering geological profile of the tunnel axis direction by tunnel exploration hole, face tracking sampling or advanced drilling, and conduct indoor test to determine the resistivity evolution curve of the core of different strata under different water contents;

[0014] S12: Take the linear intersection point at both ends of one of the curves as an inflection point; the resistivity value corresponding to the inflection point is the upper limit value R s1 of the core resistivity of the corresponding stratum, and the resistivity value corresponding to the end point of the curve is the lower limit R s2 of the core resistivity of the corresponding stratum; take the range value R s1 ~ R s1 between the resistivity value R s2 corresponding to the inflection point and the resistivity value corresponding to the end point of the curve as the saturation interpretation threshold of the core resistivity of the corresponding stratum;

[0015] S13: Repeat step S12 to obtain the saturation interpretation threshold of the core resistivity of different strata.

[0016] Further, the step S2 of detecting and obtaining the resistivity spatial distribution in front of the tunnel by using the transient electromagnetic method and determining the tunnel water-bearing structure in the digitized base map according to the permeability classification of different strata and the resistivity spatial distribution in front of the tunnel comprises:

[0017] S21: Detect the resistivity spatial distribution rule in front of the tunnel within a certain range by using the transient electromagnetic method, and obtain the suspected area of the tunnel water-bearing structure determined based on the traditional electromagnetic signal characteristics of the transient electromagnetic method; that is, the suspected water-bearing structure represented by low resistance is circled by using the difference and difference characteristics of the change of resistivity;

[0018] S22: Match the suspected areas of the tunnel water-bearing structure determined in different batches with the face stake number on the digitized engineering geological profile base map of the tunnel axis strata, and superimpose and display on the digitized engineering geological profile to form the resistivity and strata spatial coupling rule of the suspected area of the tunnel water-bearing structure;

[0019] S23: comprehensively judge according to the permeability classification of each stratum and the resistivity and strata spatial coupling rule of the suspected area of the tunnel water-bearing structure, and circulate the tunnel water-bearing structure.

[0020] Further, the step S23 of comprehensively judging according to the permeability classification of each stratum and the resistivity and strata spatial coupling rule of the suspected area of the tunnel water-bearing structure, and circulating the tunnel water-bearing structure comprises:

[0021] The formation permeability k < 6 x 10 -6 m / min in the suspected water-bearing structure is determined as a non-water-bearing structure.

[0022] The formation permeability k ≥ 6 x 10 -6 m / min in the suspected water-bearing structure is determined as a water-bearing structure.

[0023] Further, the division of the tunnel water-bearing structure in step S3 into a saturated zone when the tunnel water-bearing structure has a resistivity within the saturated interpretation threshold range of the different formation core resistivities, and into a non-saturated zone otherwise, achieves fine zoning of each tunnel water-bearing structure.

[0024] Further, the tunnel water inflow in step S4 is calculated by formula (1):

[0025]

[0026] In the formula, Q is the water inflow per unit time, t is the unit time (usually per minute, min), n is the number of saturated zones, S i is the contact area of the i-th formation, k i is the saturated permeability coefficient of the i-th formation.

[0027] Further, in step S4, the tunnel water inflow risk level is determined according to the tunnel water inflow per unit time and the hardness of the different formation cores, including:

[0028] Regardless of the hardness of the different formation cores, when the tunnel water inflow per unit time Q ≤ 1 m 3 / min, the tunnel water inflow risk is determined as low risk.

[0029] When the uniaxial compressive strength of the different formation cores is > 20 MPa, and the tunnel water inflow per unit time Q > 1 m 3 / min, the tunnel water inflow risk is determined as medium risk.

[0030] When the uniaxial compressive strength of the different formation cores is ≤ 20 MPa, and the tunnel water inflow per unit time Q > 1 m 3 / min, the tunnel water inflow risk is determined as high risk.

[0031] Further, in step S1, the tunnel axis direction engineering geological profile digital base map is obtained, including forming a tunnel axis direction engineering geological profile digital base map by logging a tunnel axis direction engineering geological profile through tunnel advanced horizontal drilling holes, core sampling, and borehole photography.

[0032] Further, the measuring the saturated permeability coefficient of different strata in the digitalized base map in step S1 comprises: measuring the saturated permeability coefficient of different strata in the digitalized base map by water injection or water pumping test on the tunnel exploration hole, or measuring the saturated permeability coefficient of different strata by indoor permeability test on the rock core obtained from the tunnel face or the advanced drill hole; in the case of not having the above conditions, the saturated permeability coefficient of different strata can also be determined by engineering analogy.

[0033] The determining the soft and hard degree of the rock core of different strata in step S1 comprises: comprehensively determining the soft and hard degree of the rock core of different strata by indoor uniaxial compressive strength test or field rebound test on the rock core obtained from the tunnel exploration hole, the tunnel face sampling or the advanced drill hole.

[0034] The second aspect of the present application provides a tunnel water gushing risk assessment system based on big data and transient electromagnetic method, which is used to realize the tunnel water gushing risk assessment method based on big data and transient electromagnetic method, and comprises a first main module, a second main module, a third main module, a fourth main module and a fifth main module.

[0035] The first main module is used to construct a tunnel axis direction engineering geological profile digitalized base map in the transient electromagnetic method detection software, obtain the saturation degree interpretation threshold of the rock core resistivity of different strata in the digitalized base map, measure the saturated permeability coefficient of different strata in the digitalized base map, and determine the soft and hard degree of the rock core of different strata.

[0036] The second main module is used to detect and obtain the resistivity spatial distribution in front of the tunnel by the transient electromagnetic method, determine the tunnel water-bearing structure in the digitalized base map according to the different strata permeability characteristics classification and the resistivity spatial distribution in front of the tunnel.

[0037] The third main module is used to divide the tunnel water-bearing structure into saturated area and unsaturated area in the digitalized base map according to the saturation degree interpretation threshold of the rock core resistivity of different strata.

[0038] The fourth main module is used to calculate the tunnel unit time water gushing amount according to the contact area of the tunnel and each water-bearing structure saturated area and the saturated permeability coefficient of different strata, divide the tunnel water gushing risk grade according to the tunnel unit time water gushing amount and the soft and hard degree of the rock core of different strata, and output the corresponding measures according to the tunnel water gushing risk grade.

[0039] The fifth main module is used for constructing a database containing saturation interpretation thresholds of core resistivity of different strata, saturated permeability coefficients of different strata, core softness and hardness of different strata, saturated partition of tunnel water-bearing structure, tunnel unit time water inflow calculation and tunnel water inflow risk grade division in transient electromagnetic method detection software, learning based on the database, continuously accumulating to form regional experience values, and realizing efficient evaluation of tunnel water inflow risk according to the regional experience values.

[0040] Overall, compared with the prior art, the above technical solutions conceived by the present application can achieve the following beneficial effects:

[0041] (1) The tunnel water inflow risk assessment method and system based on big data and transient electromagnetic method can realize efficient prediction of tunnel water inflow risk by recording tunnel axis direction engineering geological profile to form a tunnel axis direction engineering geological profile digital base map in transient electromagnetic method detection software through tunnel advanced horizontal drilling, core sampling and borehole photography, conducting indoor tests on cores of different strata in the tunnel axis direction engineering geological profile digital base map to obtain saturation interpretation thresholds of core resistivity of different strata, measuring saturated permeability coefficients of different strata in the digital base map and determining core softness and hardness of different strata, determining tunnel water-bearing structure in the digital base map according to different stratum permeability classification and resistivity spatial distribution in front of the tunnel, combining the digital engineering geological profile with transient electromagnetic method detection of water-bearing structure to realize combination of geotechnical impedance corresponding characteristics and physical properties, carrying out saturation partition of tunnel water-bearing structure according to the saturation interpretation thresholds of core resistivity of different strata, evaluating connectivity of each tunnel water-bearing structure saturation zone and judging spatial relationship between the tunnel and each tunnel water-bearing structure saturation zone, so that the detection and prediction results of the transient electromagnetic method are closely related to the engineering geological profile, calculating tunnel unit time water inflow according to the contact area between the tunnel and each water-bearing structure saturation zone and the saturated permeability coefficients of different strata, dividing tunnel water inflow risk grade according to the tunnel unit time water inflow and the core softness and hardness of different strata, outputting corresponding measures according to the tunnel water inflow risk grade, combining transient electromagnetic method tunnel water-bearing structure detection and prediction with tunnel water inflow assessment and water inflow risk assessment, and realizing efficient prediction of tunnel water inflow risk.

[0042] (2) The tunnel water gushing risk assessment method and system based on big data and transient electromagnetic method of the present application combines digital engineering geological profile with transient electromagnetic method water-bearing structure prediction, predicts water gushing risk through more detailed and rich tunnel transient electromagnetic method detection, and couples all results on the digital stratum profile for display, facilitating comparison and analysis with other advanced geological prediction results, and compared with the prior art, the prediction result is more intuitive, and the tunnel water gushing comprehensive risk prediction efficiency and effect can be greatly improved.

[0043] (3) The tunnel water gushing risk assessment method and system based on big data and transient electromagnetic method of the present application constructs a database containing saturation interpretation threshold of different stratum core resistivity, different stratum saturation permeability coefficient, different stratum core softness degree, tunnel water-bearing structure saturation partition, tunnel unit time water gushing amount calculation and tunnel water gushing risk grade division in the transient electromagnetic method detection software, combines the physical property database with the transient electromagnetic method tunnel water gushing risk evaluation, learns based on the database, and continuously accumulates to form regional experience value, realizes efficient evaluation and prevention and control of tunnel water gushing risk according to the regional experience value; the present application uses physical property feature influence precision, and conversely inverts physical property feature, both of which are fed back to form a big data system including forward data and inversion data, improves the detection precision and evaluation efficiency of the model through big data training model; and further realizes the improvement of the detection precision of the transient electromagnetic method detection equipment, the improvement of the tunnel water gushing amount evaluation efficiency and the improvement of the tunnel water gushing risk evaluation effect; can provide method and technical support for water gushing risk evaluation of tunnels under construction and in operation; the present application has wide application prospect and great popularization value. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 It is a flowchart of the tunnel water gushing risk assessment method based on big data and transient electromagnetic method of the present application;

[0045] Figure 2 It is a core saturation and resistivity evolution curve diagram in the tunnel water gushing risk assessment method based on big data and transient electromagnetic method of the present application;

[0046] Figure 3 It is a structure diagram of tunnel water-bearing structure fine partition in the tunnel water gushing risk assessment method based on big data and transient electromagnetic method of the present application;

[0047] Figure 4 It is a diagram of no intersection between the tunnel and the water-bearing structure in the tunnel water gushing risk assessment method based on big data and transient electromagnetic method of the present application;

[0048] Figure 5 It is a diagram of partial intersection between the tunnel and the water-bearing structure in the tunnel water gushing risk assessment method based on big data and transient electromagnetic method of the present application;

[0049] Figure 6 It is a schematic view of complete intersection of a tunnel and a water-bearing structure in an embodiment of the tunnel water gushing risk assessment method based on big data and transient electromagnetic method;

[0050] Figure 7 It is a structural schematic view of an embodiment of the tunnel water gushing risk assessment system based on big data and transient electromagnetic method;

[0051] Figure 8 It is a structural schematic view of an electronic device. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application. In addition, the technical features involved in each embodiment of the present application described below can be combined with each other as long as they do not conflict with each other.

[0053] The geophysical method used by the prior art in preventing and controlling the safety threat of tunnel water gushing and the physical properties of rock-soil body are not closely combined, qualitative is greater than quantitative, the influence mechanism of front water on rock-soil body resistance characteristics is insufficient, the detection and prediction results of middle-end transient electromagnetic method are disconnected with engineering geological section, the detection and prediction of rear-end transient electromagnetic method tunnel water-bearing structure are disconnected with tunnel water gushing volume evaluation and water gushing risk evaluation, that is, the front end is not enough, the middle end is not comprehensive enough, and the rear end is not extended enough, the detection and prediction efficiency is low; based on the above reasons, as shown in the Figure 1 An aspect of the present application provides a tunnel water gushing risk assessment method based on big data and transient electromagnetic method, comprising the following steps:

[0054] S1: constructing a tunnel axis direction engineering geological section digital base map in a transient electromagnetic method detection software, obtaining a saturation degree interpretation threshold of different stratum core resistivity in the digital base map, measuring the saturation permeability coefficient of different strata in the digital base map, and determining the soft and hard degree of different stratum cores;

[0055] S2: detecting and obtaining the resistivity spatial distribution in front of the tunnel by using the transient electromagnetic method, determining the tunnel water-bearing structure in the digital base map according to the different stratum permeability characteristics classification and the resistivity spatial distribution in front of the tunnel;

[0056] S3: dividing the tunnel water-bearing structure into a saturated area and a non-saturated area in the digital base map according to the saturation degree interpretation threshold of the different stratum core resistivity;

[0057] S4: calculating tunnel unit time water inflow according to the contact area of the tunnel with each water-bearing structure saturated zone and the saturated permeability coefficient of the different strata; dividing the tunnel water inflow risk level according to the tunnel unit time water inflow and the soft and hard degree of the different strata core; outputting the corresponding measures according to the tunnel water inflow risk level;

[0058] S5: constructing a database containing the saturation interpretation threshold of the different strata core resistivity, the saturated permeability coefficient of the different strata, the soft and hard degree of the different strata core, the tunnel water-bearing structure saturated partition, the tunnel unit time water inflow calculation and the tunnel water inflow risk level division in the transient electromagnetic method detection software, learning based on the database, continuously accumulating to form regional experience value, and realizing efficient evaluation of tunnel water inflow risk according to the regional experience value.

[0059] Further, the step S1 of obtaining the tunnel axis direction engineering geological profile digital base map includes: forming the tunnel axis direction engineering geological profile digital base map by recording the tunnel axis direction engineering geological profile through tunnel advanced horizontal drilling, core sampling and drilling camera shooting; and using the same as the base map for comparison of subsequent transient electromagnetic detection results, which can solve the separation of existing technology geophysical prospecting and engineering exploration.

[0060] Further, the step S1 of obtaining the saturation interpretation threshold of the different strata core resistivity in the digital base map includes the following steps:

[0061] S11: obtaining the core of the different strata in the tunnel axis direction engineering geological profile digital base map through tunnel exploration hole, tunnel face tracking sampling or advanced drilling, and performing indoor test to determine the resistivity evolution curve of the core of the different strata under different water content (saturation), as shown in Figure 2 ;

[0062] S12: taking the linear intersection point of both ends of the curve as an inflection point; the resistivity value corresponding to the inflection point is the upper limit value R s1 of the resistivity of the corresponding strata core, and the resistivity value corresponding to the end point of the curve is the lower limit R s2 of the resistivity of the corresponding strata core; the range value R s1 ~R s2 between the resistivity value R s1 corresponding to the inflection point and the resistivity value corresponding to the end point of the curve is taken as the saturation interpretation threshold of the resistivity of the corresponding strata core;

[0063] S13: repeating step S12 to obtain the saturation interpretation threshold of the resistivity of the different strata core;

[0064] The saturation interpretation threshold of the resistivity of different strata in the digitalized base map provides interpretation threshold support for further refined saturation partition based on the preliminary exploration results of the spatial coupling of the tunnel water-bearing structure and strata by subsequent transient electromagnetic method exploration, and is simultaneously used as database accumulation learning data.

[0065] Further, the measurement of the saturated permeability coefficient of different strata in the digitalized base map in step S1 includes:

[0066] The saturated permeability coefficient of different strata is measured by water injection or water pumping test on the tunnel exploration hole, or is determined by indoor permeability test on the core obtained from the tunnel face or the advanced drill hole; in the case where the above conditions are not available, the saturated permeability coefficient of different strata can also be determined by engineering analogy; the saturated permeability coefficient of different strata is used as parameter support for subsequent water inflow estimation, and is simultaneously used as database accumulation learning data.

[0067] Further, the determination of the softness and hardness of the core of different strata in step S1 includes the comprehensive determination of the softness and hardness of the core of different strata by indoor uniaxial compressive strength test or field rebound test on the core obtained from the tunnel exploration hole, the tunnel face sampling or the advanced drill hole, and the softness and hardness of the core of different strata are used as parameter support for subsequent water inflow risk comprehensive evaluation, and are simultaneously used as database accumulation learning data.

[0068] Further, the spatial distribution of the resistivity in front of the tunnel is detected and obtained by the transient electromagnetic method in step S2, and the tunnel water-bearing structure is determined in the digitalized base map according to the permeability grading of different strata and the spatial distribution of the resistivity in front of the tunnel; including:

[0069] S21: the spatial distribution law of the resistivity in front of the tunnel is obtained by the transient electromagnetic method, and the suspected area of the tunnel water-bearing structure determined based on the traditional electromagnetic signal characteristics of the transient electromagnetic method is obtained; that is, the suspected water-bearing structure represented by low resistance is circled out by using the difference and difference characteristics of the change of the resistivity;

[0070] S22: the suspected areas of the tunnel water-bearing structure determined in different batches are matched with the tunnel axis strata digitalized engineering geological profile base map, and are superimposed and displayed on the digitalized engineering geological profile to form the spatial coupling law of the resistivity of the suspected area of the tunnel water-bearing structure and the strata;

[0071] S23: the suspected area of the tunnel water-bearing structure is circled out according to the comprehensive judgment of the permeability grading of different strata and the spatial coupling law of the resistivity of the suspected area of the tunnel water-bearing structure and the strata.

[0072] Further, as shown in Table 1, the suspected area of the tunnel water-bearing structure is circled out according to the comprehensive judgment of the permeability grading of different strata and the spatial coupling law of the resistivity of the suspected area of the tunnel water-bearing structure and the strata in step S23, including:

[0073] The formation permeability in the suspected water-bearing structure is low permeability (k < 6 x 10 -6 m / min), and is determined as a non-water-bearing structure;

[0074] The formation permeability in the suspected water-bearing structure is medium or above (k≥6 x 10 -6 m / min), and is determined as a water-bearing structure;

[0075] Table 1 Comprehensive delineation criteria for tunnel water-bearing structure range

[0076]

[0077] Further, in step S3, the tunnel water-bearing structure is divided into saturated and unsaturated areas in the digital base map according to the saturation interpretation threshold of the different formation core resistivity; including dividing the tunnel water-bearing structure into saturated area if the resistivity is within the saturation interpretation threshold of the different formation core resistivity, otherwise into unsaturated area, thus achieving fine zoning of each tunnel water-bearing structure.

[0078] Further, step S3 also includes connectivity evaluation of each tunnel water-bearing structure saturated area, to determine whether each saturated area is spatially connected; if connected, all connected saturated areas are taken as one large area for spatial relationship evaluation with the tunnel. If not connected, each saturated area is taken as a separate area for spatial relationship evaluation with the tunnel; step S3 also includes judging the spatial relationship between the tunnel and each tunnel water-bearing structure saturated area, including no intersection and intersection; the intersection is further divided into partial intersection and complete intersection; as shown in Figures 4-6 Fig. S is the contact area between the tunnel and the saturated area; if the tunnel intersects with each tunnel water-bearing structure saturated area, the contact area between the tunnel and each water-bearing structure saturated area is estimated.

[0079] Further, in step S4, the tunnel water inflow is calculated by formula (1) :

[0080]

[0081] In the formula, Q is the water inflow per unit time, t is the unit time (usually per minute, min), n is the number of saturated areas passing through the formation, S i is the contact area of the i-th formation, k i is the saturated permeability coefficient of the i-th formation.

[0082] Further, Table 2 is the tunnel water inflow risk determination criteria; in step S4, the tunnel water inflow risk level is determined according to the tunnel water inflow per unit time and the soft and hard degree of different formation cores, including:

[0083] Regardless of the soft and hard degree of different stratum cores, if the tunnel unit time water inflow Q≤1m 3 / min, the tunnel water inflow risk is determined as low risk;

[0084] Regardless of the soft and hard degree of different stratum cores, if the tunnel unit time water inflow Q≤1m 3 / min, the tunnel water inflow risk is determined as low risk;

[0085] Regardless of the soft and hard degree of different stratum cores, if the tunnel unit time water inflow Q≤1m 3 / min, the tunnel water inflow risk is determined as low risk;

[0086] Table 2 Tunnel water inflow risk determination standard

[0087]

[0088] Further, the step S4 outputs the countermeasures corresponding to each risk level according to the tunnel water inflow risk level, including:

[0089] When the tunnel water inflow risk is low risk, no special measures are needed;

[0090] When the tunnel water inflow risk is medium risk, measures such as open drainage are needed to strengthen dewatering and drainage, and avoid the adverse effects of long-term soaking and softening of the construction area between the working face and the secondary lining;

[0091] When the tunnel water inflow risk is high risk, active measures need to be taken to strengthen protection, or active pressure relief, or a combination of both engineering measures can be taken to control the safety risk of tunnel water inflow.

[0092] Further, the step S5 includes constructing a database in the software system database, which contains the saturation interpretation threshold of different stratum core resistivity, the saturation permeability coefficient of different strata, the soft and hard degree of different stratum cores, the tunnel water-bearing structure saturation partition, the tunnel unit time water inflow calculation, and the tunnel water inflow risk level division. The regional experience value is constantly accumulated to repeat the step S4 to realize efficient evaluation and prevention and control of tunnel water inflow risk. With the increase of regional experience value, the detection accuracy of transient electromagnetic method detection equipment is gradually improved, the tunnel water inflow evaluation efficiency is improved, and the tunnel water inflow risk evaluation effect is improved.

[0093] The application provides a tunnel water gushing risk assessment method based on big data and transient electromagnetic method, which quantitatively evaluates the tunnel unit time water gushing amount by using the tunnel axis direction engineering geological profile digitization, the core resistivity and permeability test, the stratum and water-bearing structure space coupling rule, the water-bearing structure fine saturation zoning and the tunnel and saturation zoning space relationship, grades the tunnel water gushing risk according to the tunnel unit time water gushing amount and the core softness and hardness of different strata, and combines the physical property database and the transient electromagnetic method tunnel water gushing risk evaluation, so that method and technical support can be provided for the water gushing risk evaluation of the tunnel under construction and in operation.

[0094] As shown in Figure 7 The second aspect of the application provides a tunnel water gushing risk assessment system based on big data and transient electromagnetic method, which is used for realizing the above-mentioned risk assessment method and comprises a first main module, a second main module, a third main module, a fourth main module and a fifth main module.

[0095] The first main module is used for constructing a tunnel axis direction engineering geological profile digitization base map in the transient electromagnetic method detection software, obtaining the saturation degree interpretation threshold of the core resistivity of different strata in the digitization base map, measuring the saturated permeability coefficients of different strata in the digitization base map and determining the core softness and hardness of different strata.

[0096] The second main module is used for detecting and obtaining the resistivity space distribution in front of the tunnel by using the transient electromagnetic method, determining the water-bearing structure of the tunnel in the digitization base map according to the different stratum permeability characteristics classification and the resistivity space distribution in front of the tunnel.

[0097] The third main module is used for dividing the water-bearing structure of the tunnel into saturated zones and unsaturated zones in the digitization base map according to the saturation degree interpretation threshold of the core resistivity of different strata.

[0098] The fourth main module is used for calculating the tunnel unit time water gushing amount according to the contact area of the tunnel and each water-bearing structure saturated zone and the saturated permeability coefficients of different strata, dividing the tunnel water gushing risk grade according to the tunnel unit time water gushing amount and the core softness and hardness of different strata, and outputting the corresponding measures according to the tunnel water gushing risk grade.

[0099] The fifth main module is used for constructing a database comprising the saturation degree interpretation threshold of the core resistivity of different strata, the saturated permeability coefficients of different strata, the core softness and hardness of different strata, the tunnel water-bearing structure saturated zoning, the tunnel unit time water gushing amount calculation and the tunnel water gushing risk grade division in the transient electromagnetic method detection software, learning based on the database, continuously accumulating to form regional experience values, and realizing the efficient evaluation of the tunnel water gushing risk according to the regional experience values.

[0100] It should be noted that the tunnel water gushing risk assessment system based on big data and transient electromagnetic method provided in the embodiment can be a computer program (including program code) running in a computer device, for example, the tunnel water gushing risk assessment system based on big data and transient electromagnetic method is an application software; the tunnel water gushing risk assessment system based on big data and transient electromagnetic method can be used to execute the corresponding steps in the above method provided in the embodiment of the present application.

[0101] In some possible implementation manners, the tunnel water gushing risk assessment system based on big data and transient electromagnetic method provided in the embodiment can be implemented in a combination of software and hardware, for example, the tunnel water gushing risk assessment system based on big data and transient electromagnetic method provided in the embodiment of the present application can be a processor in the form of a hardware decoding processor, which is programmed to execute the tunnel water gushing risk assessment method based on big data and transient electromagnetic method provided in the embodiment of the present application, for example, the processor in the form of a hardware decoding processor can adopt one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), or other electronic elements.

[0102] In some possible implementation manners, the tunnel water gushing risk assessment system based on big data and transient electromagnetic method provided in the embodiment can be implemented in a software manner, which can be software in the form of programs and plug-ins, and includes a series of modules to implement the tunnel water gushing risk assessment method based on big data and transient electromagnetic method provided in the embodiment of the present application.

[0103] The tunnel water inrush risk assessment system based on big data and transient electromagnetic method provided by the embodiment is characterized in that: a tunnel axis direction engineering geological profile digital base map is constructed in a transient electromagnetic method detection software, a saturation interpretation threshold of a different stratum core resistivity in the digital base map is obtained, a saturated permeability coefficient of different strata in the digital base map is measured, and the soft and hard degrees of different stratum cores are determined; the transient electromagnetic method is used to detect and obtain the resistivity spatial distribution in front of the tunnel, the tunnel water-bearing structure is determined in the digital base map according to the different stratum permeability characteristics classification and the resistivity spatial distribution in front of the tunnel, the tunnel water-bearing structure is divided into a saturated area and a non-saturated area in the digital base map according to the saturation interpretation threshold of the different stratum core resistivity, the connectivity of each tunnel water-bearing structure saturated area is evaluated, and the spatial relationship between the tunnel and each tunnel water-bearing structure saturated area is judged, if there is intersection, the contact area between the tunnel and each water-bearing structure saturated area is estimated, the tunnel unit time water inrush amount is calculated according to the contact area between the tunnel and each water-bearing structure saturated area and the saturated permeability coefficient of different strata, the tunnel water inrush risk grade is divided according to the tunnel unit time water inrush amount and the soft and hard degrees of different stratum cores, the corresponding measures are output according to the tunnel water inrush risk grade, a database containing the saturation interpretation threshold of different stratum core resistivity, the saturated permeability coefficient of different strata, the soft and hard degrees of different stratum cores, the tunnel water-bearing structure saturated partition, the tunnel unit time water inrush amount calculation and the tunnel water inrush risk grade division is constructed in the transient electromagnetic method detection software, the physical property database is combined with the transient electromagnetic method tunnel water inrush risk assessment, learning is based on the database, regional experience values are accumulated and formed, the efficient assessment and prevention and control of the tunnel water inrush risk are realized according to the regional experience values, the detection accuracy of the transient electromagnetic method detection equipment is gradually improved, the tunnel water inrush amount assessment efficiency is improved, and the tunnel water inrush risk assessment effect is improved, and the method and technical support can be provided for the water inrush risk assessment of the tunnel under construction and in operation.

[0104] The third aspect of the application also provides an electronic device, Figure 8 is a structural schematic diagram of the electronic device of the embodiment, as Figure 8As shown, the electronic device 1000 in this embodiment may include: a processor 1001, a network interface 1004, and a memory 1005. Furthermore, the electronic device 1000 may also include: a user interface 1003, and at least one communication bus 1002. The communication bus 1002 is used to implement communication between these components. The user interface 1003 may include a display screen and a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1004 may be a high-speed RAM or non-volatile memory, such as at least one disk storage device. The memory 1005 may optionally be at least one storage device located remotely from the processor 1001. Figure 8 As shown, the memory 1005, which is a computer-readable storage medium, may include an operating system, a network communication module, a user interface module, and a device control application.

[0105] like Figure 8 In the illustrated electronic device 1000, the network interface 1004 provides network communication functionality; the user interface 1003 is primarily used to provide an input interface for the user; and the processor 1001 can be used to call the device control application stored in the memory 1005 to achieve:

[0106] In the transient electromagnetic method detection software, a digital base map of the engineering geological profile along the tunnel axis is constructed. The saturation interpretation threshold of the resistivity of the rock cores of different strata in the digital base map is obtained. The saturation permeability coefficient of different strata in the digital base map is measured and the hardness of the rock cores of different strata is determined.

[0107] The resistivity spatial distribution in front of the tunnel was detected and obtained using the transient electromagnetic method. Based on the permeability characteristics of different strata and the resistivity spatial distribution in front of the tunnel, the water-bearing structure of the tunnel was determined on the digital base map.

[0108] Based on the saturation interpretation threshold of the resistivity of the rock cores of different strata, the water-bearing structure of the tunnel is divided into saturated and unsaturated zones in the digital base map;

[0109] The tunnel's water inflow per unit time is calculated based on the contact area between the tunnel and the saturated zones of various water-bearing structures and the saturated permeability coefficients of the different strata; the tunnel's water inflow risk level is classified based on the tunnel's water inflow per unit time and the hardness of the rock cores of different strata; and corresponding countermeasures are output based on the tunnel's water inflow risk level.

[0110] The database is constructed in the transient electromagnetic method detection software, and contains saturation interpretation thresholds of core resistivity of different strata, saturated permeability coefficients of different strata, soft and hard degrees of core of different strata, saturated partition of water-bearing structures of the tunnel, tunnel unit time water inflow calculation, and tunnel water inflow risk grade division; based on database learning, regional experience values are accumulated, and efficient evaluation and prevention and control of tunnel water inflow risk are realized according to the regional experience values.

[0111] It should be appreciated that in some possible implementations, the processor 1001 can be a central processing unit (CPU), and can also be other general-purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or can also be any conventional processor. The memory can include a read-only memory and a random access memory, and provide instructions and data for the processor. A part of the memory can also include a nonvolatile random access memory. For example, the memory can also store device type information.

[0112] In specific implementations, the electronic device 1000 can execute the implementation manners provided by each step in the above Figure 1 by using various functional modules built therein. For details, refer to the implementation manners provided by each step above, which will not be described herein again.

[0113] The electronic device provided in this embodiment constructs a digital base map of the engineering geological profile along the tunnel axis in the transient electromagnetic method detection software. It obtains the saturation interpretation threshold of the resistivity of different strata cores in the digital base map, measures the saturation permeability coefficient of different strata in the digital base map, and determines the hardness of the cores in different strata. It uses transient electromagnetic method to detect and obtain the spatial distribution of resistivity in front of the tunnel. Based on the classification of different strata permeability characteristics and the spatial distribution of resistivity in front of the tunnel, it determines the water-bearing structure of the tunnel in the digital base map. Based on the saturation interpretation threshold of the resistivity of the cores in different strata, it divides the water-bearing structure of the tunnel into saturated and unsaturated zones in the digital base map. It evaluates the connectivity of each saturated zone of the tunnel water-bearing structure and determines the spatial relationship between the tunnel and each saturated zone of the tunnel water-bearing structure. If there is an intersection, it estimates the contact area between the tunnel and each saturated zone of the water-bearing structure. Based on the contact area between the tunnel and each saturated zone of the water-bearing structure and the different strata... The system calculates the tunnel's water inflow per unit time using the saturated permeability coefficient. Based on this, it classifies tunnel water inflow risk levels according to the water inflow per unit time and the hardness of different strata core samples. Corresponding countermeasures are then output for each risk level. A database is constructed within the transient electromagnetic method (TEM) detection software, containing saturation interpretation thresholds for resistivity of different strata core samples, saturated permeability coefficients for different strata, hardness of different strata core samples, saturation zones of the tunnel's water-bearing structure, calculation of tunnel water inflow per unit time, and classification of tunnel water inflow risk levels. This physical property database is combined with the TEM tunnel water inflow risk assessment. Based on database learning, regional experience values ​​are continuously accumulated, enabling efficient assessment and prevention of tunnel water inflow risk. This gradually improves the detection accuracy of the TEM detection equipment, increases the efficiency of tunnel water inflow assessment, and enhances the effectiveness of tunnel water inflow risk assessment. It provides methodological and technical support for water inflow risk assessment of tunnels under construction and in operation.

[0114] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement... Figure 1 The methods provided in each step are detailed in the implementation methods provided in the above steps, and will not be repeated here.

[0115] The computer readable storage medium provided by the embodiment constructs a digital base map of a tunnel axis direction engineering geological profile in transient electromagnetic method detection software, obtains a saturation interpretation threshold of core resistivity of different strata in the digital base map, measures the saturated permeability coefficients of different strata in the digital base map, and determines the soft and hard degrees of the core of different strata; the resistivity spatial distribution in front of the tunnel is detected and obtained by using the transient electromagnetic method, the tunnel water-bearing structure is determined in the digital base map according to the permeation characteristics grading of different strata and the resistivity spatial distribution in front of the tunnel; the tunnel water-bearing structure is divided into saturated zones and unsaturated zones in the digital base map according to the saturation interpretation threshold of the core resistivity of different strata; the connectivity of each tunnel water-bearing structure saturated zone is evaluated, and the spatial relationship between the tunnel and each tunnel water-bearing structure saturated zone is judged, if there is intersection, the contact area between the tunnel and each water-bearing structure saturated zone is estimated; the tunnel unit time water inflow is calculated according to the contact area between the tunnel and each water-bearing structure saturated zone and the saturated permeability coefficients of different strata; the tunnel water inflow risk level is divided according to the tunnel unit time water inflow and the soft and hard degrees of the core of different strata, and the corresponding measures are output according to the tunnel water inflow risk level; a database containing the saturation interpretation threshold of core resistivity of different strata, the saturated permeability coefficients of different strata, the soft and hard degrees of the core of different strata, the tunnel water-bearing structure saturated zoning, the tunnel unit time water inflow calculation and the tunnel water inflow risk level division is constructed in the transient electromagnetic method detection software; the physical property database is combined with the transient electromagnetic method tunnel water inflow risk evaluation, and based on database learning, regional experience values are accumulated to realize efficient evaluation and prevention and control of tunnel water inflow risk according to the regional experience values; the detection accuracy of the transient electromagnetic method detection equipment is gradually improved, the tunnel water inflow evaluation efficiency is improved, and the tunnel water inflow risk evaluation effect is improved; the method and technical support can be provided for the water inflow risk evaluation of the tunnel under construction and in operation.

[0116] Any reference to storage, memory, database or other medium herein includes non-volatile and / or volatile storage. Non-volatile storage can include read-only memory (ROM), programmable ROM (PROM), electronically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile storage can include random-access memory (RAM), or external cache memory. By way of illustration, and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus direct memory access (RDMA), and Rambus in-memory direct computer bus RAM (RDRAM), etc.

[0117] Those skilled in the art will readily understand that the above description is only the preferred embodiment of the present application and is not intended to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A tunnel water inrush risk assessment method based on big data and transient electromagnetic method, characterized in that: The method comprises the following steps: S1: constructing a tunnel axis direction engineering geological profile digital base map in transient electromagnetic method detection software, obtaining saturation interpretation threshold values of different stratum core resistivities in the digital base map, measuring the saturated permeability coefficients of different strata in the digital base map, and determining the soft and hard degrees of different stratum cores; S2: detecting and obtaining the resistivity spatial distribution in front of the tunnel by using the transient electromagnetic method, determining the tunnel water-bearing structure in the digital base map according to the stratum permeability grading and the resistivity spatial distribution in front of the tunnel; S3: dividing the tunnel water-bearing structure into saturated and unsaturated zones in the digital base map according to the saturation interpretation threshold values of the different stratum core resistivities; S4: calculating the tunnel unit time water inflow according to the contact area of the tunnel and each water-bearing structure saturated zone and the saturated permeability coefficients of different strata, dividing the tunnel water inflow risk grade according to the tunnel unit time water inflow and the soft and hard degrees of different stratum cores, and outputting the corresponding measures for each risk grade according to the tunnel water inflow risk grade; S5: constructing a database containing the saturation interpretation threshold values of different stratum core resistivities, the saturated permeability coefficients of different strata, the soft and hard degrees of different stratum cores, the tunnel water-bearing structure saturated partition, the tunnel unit time water inflow calculation and the tunnel water inflow risk grade division in the transient electromagnetic method detection software, learning based on the database, continuously accumulating to form regional experience values, and realizing efficient evaluation and prevention and control of the tunnel water inflow risk according to the regional experience values.

2. The tunnel water inrush risk assessment method based on big data and transient electromagnetic method according to claim 1, characterized in that: In step S1, the saturation interpretation threshold values of different stratum core resistivities in the digital base map are obtained, comprising the following steps: S11: obtaining the cores of different strata in the tunnel axis direction engineering geological profile digital base map through tunnel exploration holes, face tracking sampling or advanced drilling, and performing indoor tests to determine the resistivity evolution curves of the cores of different strata under different water contents; S12: The point where the two ends of one of the curves intersect linearly is taken as the inflection point; the resistivity value corresponding to the inflection point is the upper limit R of the resistivity of the corresponding stratum core. s1 The resistivity value corresponding to the end point of the curve is the lower limit R of the resistivity of the corresponding stratum core. s2 The resistivity value R corresponding to the inflection point s1 The range R between the resistivity value corresponding to the end point of the curve and the value of the curve. s2 ~ R s1 As the saturation interpretation threshold of the corresponding stratum core resistivity; S13: repeating step S12 to obtain the saturation interpretation threshold values of different stratum core resistivities.

3. The tunnel water inrush risk assessment method based on big data and transient electromagnetic method according to claim 1, characterized in that: In step S2, the tunnel water-bearing structure is determined in the digital base map according to the stratum permeability grading and the resistivity spatial distribution in front of the tunnel by using the transient electromagnetic method to detect and obtain the resistivity spatial distribution in front of the tunnel; comprising: S21: obtaining the tunnel water-bearing structure suspected area determined based on the traditional electromagnetic signal characteristics of the transient electromagnetic method by using the transient electromagnetic method to detect the resistivity spatial distribution law in front of the tunnel; that is, using the difference and change amount difference characteristics of the resistivity change to circle out the suspected water-bearing structure represented by low resistance; S22: matching the tunnel water-bearing structure suspected areas determined in different batches with the face stake numbers on the tunnel axis direction digital engineering geological profile base map, and superimposing and displaying them on the digital engineering geological profile to form the resistivity and stratum space coupling law of the tunnel water-bearing structure suspected area; S23: comprehensively judging according to the stratum permeability grading and the resistivity and stratum space coupling law of the tunnel water-bearing structure suspected area, and delineating the tunnel water-bearing structure.

4. The tunnel water inrush risk assessment method based on big data and transient electromagnetic method according to claim 3, characterized in that: In step S23, the tunnel water-bearing structure is determined according to the classification of the permeability characteristics of each stratum and the coupling law of the resistivity of the suspected area of the tunnel water-bearing structure and the stratum space, and the tunnel water-bearing structure is circled, including: Formation permeability k < 6 x 10 -6 m / min in the suspected water-bearing structure is determined to be a non-water-bearing structure. The formation permeability k ≥ 6 x 10 -6 m / min in the suspected water-bearing structure is determined to be a water-bearing structure.

5. The tunnel water inrush risk assessment method based on big data and transient electromagnetic method according to any one of claims 1-4, characterized in that: In step S3, the tunnel water-bearing structure is divided into a saturated area or a non-saturated area according to whether the resistivity of the tunnel water-bearing structure is within the saturation interpretation threshold range of the resistivity of the different stratum cores, so as to realize the fine zoning of each tunnel water-bearing structure.

6. The tunnel water inrush risk assessment method based on big data and transient electromagnetic method according to any one of claims 1-4, characterized in that: In step S4, the tunnel water inflow is calculated by formula (1): （1） wherein is the water influx per unit time, t is the time, is the number of zones crossed in the saturated zone, is the number of zones crossed in the saturated zone, is the contact area of the formation, is the number of zones crossed in the saturated zone, is the saturated permeability coefficient of the formation.

7. The tunnel water inrush risk assessment method based on big data and transient electromagnetic method according to any one of claims 1-4, characterized in that: In step S4, the tunnel water inflow risk level is determined according to the tunnel water inflow per unit time and the hardness of the different stratum cores, including: No matter how the hardness of different strata core, the tunnel unit time water inflow Q≤1 m 3 / min, the tunnel water inflow risk is low risk; The uniaxial compressive strength of different strata cores is greater than 20 MPa, and the tunnel unit time water inflow Q is greater than 1 m 3 / min, and it is determined that the tunnel water inflow risk is medium risk. The uniaxial compressive strength of different strata cores is less than or equal to 20 MPa, and the tunnel unit time water inflow Q is greater than 1 m 3 / min, and it is determined that the tunnel water inflow risk is high.

8. The tunnel water inrush risk assessment method based on big data and transient electromagnetic method according to any one of claims 1-4, characterized in that: In step S1, the tunnel axis direction engineering geological profile digital base map is constructed in the transient electromagnetic method detection software, including: the tunnel axis direction engineering geological profile digital base map is formed by recording the tunnel axis direction engineering geological profile in the transient electromagnetic method detection software through the tunnel advanced horizontal drilling hole, core sampling and drilling camera.

9. The tunnel water inrush risk assessment method based on big data and transient electromagnetic method according to any one of claims 1-4, characterized in that: In step S1, the saturation permeability coefficient of the different strata in the digital base map is measured, including: the saturation permeability coefficient of the different strata in the digital base map is measured by water injection or water pumping test on the tunnel exploration hole, or the saturation permeability coefficient of the different strata is determined by indoor permeability test on the cores obtained from the tunnel face or advanced drilling hole; in the case where the above conditions are not available, the saturation permeability coefficient of the different strata can also be determined by engineering analogy; In step S1, the hardness of the different stratum cores is determined, including: the hardness of the different stratum cores is determined by indoor uniaxial compressive strength test or field rebound test on the cores obtained from the tunnel exploration hole, tunnel face sampling or advanced drilling hole. 10.A tunnel water gushing risk assessment system based on big data and transient electromagnetic method, characterized in that, The tunnel water inflow risk assessment method based on big data and transient electromagnetic method according to any one of claims 1-9 is implemented, including: a first main module, a second main module, a third main module, a fourth main module and a fifth main module; wherein, The first main module is used to construct a tunnel axis direction engineering geological profile digital base map in the transient electromagnetic method detection software, to obtain the saturation degree interpretation threshold of the resistivity of the different stratum cores in the digital base map, to measure the saturation permeability coefficient of the different strata in the digital base map, and to determine the hardness of the different stratum cores; The second main module is used to detect and obtain the resistivity spatial distribution in front of the tunnel by using the transient electromagnetic method, to determine the tunnel water-bearing structure in the digital base map according to the classification of the permeability characteristics of the different strata and the resistivity spatial distribution in front of the tunnel; The third main module is used to divide the tunnel water-bearing structure into a saturated area and a non-saturated area in the digital base map according to the saturation degree interpretation threshold of the resistivity of the different stratum cores; The fourth main module is used to calculate the tunnel water inflow per unit time according to the contact area of the tunnel and each water-bearing structure saturated area and the saturation permeability coefficient of the different strata, to divide the tunnel water inflow risk level according to the tunnel water inflow per unit time and the hardness of the different stratum cores, and to output the corresponding measures according to the tunnel water inflow risk level. The fifth main module is used for constructing a database containing saturation interpretation threshold values of different stratum core resistivities, saturated permeability coefficients of different strata, soft and hard degrees of different stratum cores, saturated partition of water-bearing structures of a tunnel, tunnel unit time water inflow calculation, and tunnel water inflow risk grade division in transient electromagnetic method detection software, learning based on the database, continuously accumulating to form regional experience values, and realizing efficient evaluation of tunnel water inflow risk according to the regional experience values.

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