CN108226998B - Geological advance prediction method based on TSP system and 3D network of rock mass random discontinuities - Google Patents

Abstract

The invention discloses a geological advance prediction method based on a TSP system and a three-dimensional network of a random discontinuous surface of a rock mass. The TSP system collects data on site, and judges the validity of the data; processes and checks the data, and obtains the surrounding rock in front 3D network model data to obtain previous exploration data; divide the statistical homogeneous area of rock mass structure and the number of dominant groups of discontinuous surfaces in the statistical homogeneous area; generate 3D discontinuous surface space based on the data corresponding to each group of discontinuous surfaces Network numerical model; combined with exploration data, TSP analysis results and discontinuous surface space three-dimensional network numerical model to comprehensively predict the stability of the rock mass ahead. The invention uses the TSP detection results as the original data, integrates the three-dimensional network of the random discontinuous surface of the rock mass to accurately predict and warn the stability of the rock mass ahead of the underground project, improves the accuracy of the forecast, effectively guides the on-site construction of the underground project, and guarantees Construction safety on the front line of the project.

Description

Geological advance prediction based on TSP system and 3D network of rock mass random discontinuities method

technical field

The invention relates to a geological advance prediction method based on a TSP system and a three-dimensional network of random discontinuous surfaces of rock masses.

Background technique

With the continuous improvement of my country's scientific and technological level and comprehensive national strength, transportation projects such as highways, railways and urban subways have achieved world-renowned achievements. At the same time, it has also driven the construction of underground projects into a leapfrog development track. A number of long tunnels with complicated geological conditions and difficult construction techniques have been built one after another. At present, China is the country with the most tunnels and underground projects, the fastest development speed, and the most complicated geological and structural forms in the world. There are countless underground projects such as mountain tunnels, subway tunnels, underwater tunnels, and hydroelectric pressure tunnels under construction or to be built. number. In the excavation of underground engineering, because the rock mass is cut into various rock blocks of different sizes and shapes by the structural surface, with the continuous excavation of the underground engineering, the original static equilibrium state of the surrounding rock is broken, and a certain Some unstable blocks exposed on the air surface will slide along the weak structural surface and cause local block loss, and even cause a chain reaction in serious cases, causing local collapse and instability of surrounding rock within a certain range of underground engineering, seriously affecting Project progress, safety of personnel and equipment. Therefore, in order to ensure the safety of underground engineering construction and improve the efficiency of engineering construction, advanced geological detection in underground engineering is more important.

At present, the TSP advanced geological prediction system adopts the principle of seismic wave reflection, which is easy to operate and can predict the geological conditions in front of the underground engineering face for a long distance. The signal is transmitted by micro blasting in the borehole within a certain distance behind the excavation face. The seismic wave caused by the blasting propagates in the rock mass in the form of a spherical surface, and part of it propagates to the front of the underground project. When the seismic wave encounters the rock wave When the impedance difference interface (such as faults, broken zones, lithological changes, caves and groundwater, etc.), part of the seismic signal is reflected back, the reflected signal is converted into an electrical signal by the receiving sensor and amplified, and the corresponding calculation of the reflected signal can determine the fault. Geological related parameters.

The stability of a rock mass is controlled by discontinuities in the rock mass. Before the stability analysis of the rock mass, the primary problem is to find out the geological conditions of the rock mass, especially the distribution characteristics of the discontinuities in the rock mass. Because the discontinuous surface reflects the discontinuous and uneven nature of the rock mass. However, the distribution of discontinuities in the rock mass does not have the characteristics that can be followed. They are randomly distributed in the rock mass, and their geometric shapes are unpredictable. Therefore, statistical inference and probability methods are used for research. . The 3D network simulation is just based on probability theory and statistics, and its research object is the geometric characteristics of discontinuous surface space. Simplify the geometric form of the assumed discontinuity surface, correct the on-site sampling deviation through the method of probability statistics and spatial analytic geometry, solve the correct geometric parameters such as trace length, size, space density, and occurrence distribution, and construct the discontinuous surface through the Monte-Carlo method. The combination of continuous surfaces in three-dimensional space forms a three-dimensional network model.

Advanced geological forecasting of traditional underground engineering processes the TSP data collected on site through corresponding post-processing software to obtain time profiles, depth migration profiles, extracted reflection layers, rock physical and mechanical parameters, and reflection profiles of P, SH, and SV waves. Interpretation of the obtained results can predict the weak zone, broken zone, fault, water content, etc. ahead. Although the TSP system is widely used in the advanced prediction of underground engineering, it does not combine the three-dimensional network of random discontinuities of the rock mass to predict the stability of the rock mass ahead of the underground engineering. How to predict the stability of rock mass in advance based on the TSP system and the 3D network of rock mass random discontinuities in underground engineering is a technical problem that needs to be solved urgently.

Contents of the invention

In order to solve the above-mentioned problems, the present invention proposes a geological advance prediction method based on the TSP system and the three-dimensional network of the random discontinuity surface of the rock mass. The present invention is based on the TSP system, with the occurrence information ( Such as inclination, inclination, etc.) as the original data, combined with the three-dimensional network of random discontinuity of the rock mass to predict and warn the stability of the rock mass ahead of the underground project, accurately and efficiently determine the stability of the surrounding rock ahead, and reduce the risk caused by unstable blocks. It can effectively guide the on-site construction of underground projects and ensure the construction safety of the front line of the project.

In order to achieve the above object, the present invention adopts the following technical solutions:

A geological advance prediction method based on a TSP system and a three-dimensional network of random discontinuities in rock mass, comprising the following steps:

(1) The TSP system collects data on site and judges the validity of the data;

(2) Process and review the data, obtain the 3D network model data of the surrounding rock in front, and obtain the previous exploration data;

(3) divide the statistical homogeneous area of rock mass structure and the number of discontinuous surface dominant groups in the statistical homogeneous area;

(4) According to the corresponding data simulation of each group of discontinuous surfaces, a three-dimensional network numerical model of discontinuous surfaces is generated;

(5) Combining the exploration data, TSP analysis results and the numerical model of the three-dimensional network of the discontinuity surface, the stability of the rock mass in front is comprehensively predicted in advance.

Further, in the step (1), judging the validity of the data refers to selecting a signal whose interference with the data is less than a threshold during the on-site test.

Further, in the step (2), the TSP system data information includes depth migration map, three-dimensional display map, occurrence information and rock mass 2D physical property map.

Further, in the step (2), analyze the surrounding rock conditions in front of the excavation face in combination with the previous exploration data and the depth migration map generated after processing by the TSP system, and make a preliminary prediction.

In the described step (3), the rock mass structure is statistically divided into homogeneous regions, and different rock mass structures have different rock mass mechanical characteristics and rock mass hydraulic properties, and the probability correlation table Schmidt diagram comparison method is adopted, combined with the actual According to the geological characteristics of the rock mass structure, the statistical homogeneity area is divided.

In the step (4), the three-dimensional network numerical model of the discontinuous surface, the process includes: the deviation correction of the discontinuous surface trace length and the simulation of the trace length size, the simulation of the discontinuous surface spacing and density, and the discontinuous surface occurrence measurement deviation Calibration or/and Monte Carlo simulation and model checking.

In the step (4), an endpoint estimator method based on probability and statistics is used to correct the discontinuous track length, simulate the diameter of the disk, fit the distribution density function and correct the deviation of the distance measurement.

In described step (4), the simulation process of discontinuous surface distance, density is to simulate the distance of discontinuous surface, adopt X ² and KS test method to carry out the best fitting of probability density function, obtain the probability distribution density of distance Functions and their corresponding parameters; the tensor method proposed by Oda is used to calculate the space density of discontinuous surfaces.

In the step (4), according to the average diameter of each group of discontinuous surfaces in space, combined with the weight distribution formula, each discontinuous surface is assigned a different weight, and then the discontinuous surface occurrence measurement deviation correction is performed .

In described step (4), the process of Monte Carlo simulation and model inspection comprises:

(4-1) Determine the scale of the generated network model;

(4-2) Determine the number of discontinuous surfaces in the scale form of the generated network model;

(4-3) Determine the spatial position of each discontinuous surface, adopt the method of Monte Carlo simulation, randomly generate the center point coordinates of each discontinuous surface;

(4-4) Determine the size of each discontinuous surface diameter: use the Monte Carlo method to simulate and generate the discontinuous surface diameter and make it obey the known best probability distribution;

(4-5) Determine the occurrence of the discontinuous surface;

(4-6) Combine the results of all simulations to form a complete model and test it.

Compared with prior art, the beneficial effect of the present invention is:

The invention is a rock mass stability advance prediction method based on the TSP system and the rock mass random discontinuous surface three-dimensional network. This method uses the detection results of TSP as the original data, and integrates the 3D network of random discontinuities of the rock mass to accurately predict and warn the stability of the rock mass ahead of the underground project, which improves the accuracy of the forecast and effectively guides the on-site construction of the underground project. , to ensure the construction safety of the front line of the project.

Description of drawings

The accompanying drawings constituting a part of the present application are used to provide further understanding of the present application, and the schematic embodiments and descriptions of the present application are used to explain the present application, and do not constitute improper limitations to the present application.

Fig. 1 is the flow chart of the realization of the method of the present invention.

Detailed ways:

The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and/or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and/or combinations thereof.

In the present invention, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom" etc. indicate The orientation or positional relationship is based on the orientation or positional relationship shown in the accompanying drawings, and is only a relative term determined for the convenience of describing the structural relationship of the various components or elements of the present invention, and does not specifically refer to any component or element in the present invention, and cannot be understood as a reference to the present invention. Invention Limitations.

In the present invention, terms such as "fixed", "connected" and "connected" should be understood in a broad sense, which means that they can be fixedly connected, integrally connected or detachably connected; they can be directly connected or can be connected through the middle The medium is indirectly connected. For relevant researchers or technical personnel in the field, the specific meanings of the above terms in the present invention can be determined according to specific situations, and should not be construed as limitations on the present invention.

As shown in Figure 1, a geological advance prediction method based on the TSP system and the three-dimensional network of random discontinuities in the rock mass includes the following steps:

Step 1: The TSP system collects data on site and judges the validity of the data;

Step 2: Process and review the data, and obtain the 3D network model data of the surrounding rock in front;

After the data processing of the TSP system, the depth migration map, three-dimensional display map, occurrence information and 2D physical property map of the rock mass in front of the excavation face can be obtained.

Combining the previous exploration data and the depth migration map generated after processing by the TSP system, the surrounding rock conditions (faults, broken zones, water content, etc.) in front of the excavation face were analyzed and a preliminary prediction was made.

The corresponding three-dimensional network numerical model data is extracted by combining the analysis conclusions with the obtained occurrence information.

Step 3: dividing the statistically homogeneous area of the rock mass structure and the number of discontinuous surface dominant groups in the statistically homogeneous area;

Different rock mass structures have different rock mass mechanical characteristics and rock mass hydraulic properties. The statistical homogeneity area of rock mass structure is divided by using the Schmidt diagram comparison method of probability correlation table and combining with the actual geological characteristics.

The number of dominant groups is divided for the discontinuous surfaces in each statistically homogeneous area.

Step 4: Simulate the data corresponding to each group of discontinuous surfaces to generate a three-dimensional network numerical model of the discontinuous surface space;

Correction of discontinuous track length, simulation of disc diameter, fitting of distribution density function, and deviation correction of spacing measurement. The method of correcting the deviation mainly adopts the endpoint estimator method based on probability and statistics.

Simulation of discontinuous face spacing, density. Firstly, simulate the spacing of the discontinuous surface, and use the X2 and K-S test methods to perform the best fitting of the probability density function, and obtain the probability distribution density function of the spacing and its corresponding parameters; use the tensor method proposed by Oda to carry out the discontinuous surface space Calculation of density.

Discontinuity surface occurrence measurement deviation correction. According to the average diameter of each group of discontinuous surfaces in space, combined with the weight distribution formula, different weights are assigned to each discontinuous surface, and then correction is performed.

Monte Carlo simulation and model checking. Generating a 3-D network model needs to determine the scale of the generated network model, and its shape is a rectangular box. The process is as follows: ① determine the scale of the box; ② determine the number of discontinuous surfaces in the box; ③ determine the spatial position of each discontinuous surface, and use the method of Monte Carlo simulation to randomly generate the center of each discontinuous surface Point coordinates; ④Determine the size of each discontinuous surface diameter: use Monte Carlo method to simulate and generate the discontinuous surface diameter and make it obey the known best probability distribution; ⑤Determine the occurrence of the discontinuous surface; ⑥Model combination: Combine the simulation results of the above steps to form a complete model and test it.

Step five: comprehensive interpretation. Combined with the exploration data, TSP analysis results and the numerical model of the three-dimensional network of the discontinuity surface, the stability of the front rock mass is comprehensively predicted in advance.

The above descriptions are only preferred embodiments of the present application, and are not intended to limit the present application. For those skilled in the art, there may be various modifications and changes in the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included within the protection scope of this application.

Although the specific implementation of the present invention has been described above in conjunction with the accompanying drawings, it does not limit the protection scope of the present invention. Those skilled in the art should understand that on the basis of the technical solution of the present invention, those skilled in the art do not need to pay creative work Various modifications or variations that can be made are still within the protection scope of the present invention.

Claims (8)

1. A geological advance prediction method based on TSP system and rock mass random discontinuity surface three-dimensional network, it is characterized in that: comprise the following steps: (1) The TSP system collects data on site and judges the validity of the data; (2) Process and review the data, obtain the 3D network model data of the surrounding rock in front, and obtain the previous exploration data; (3) divide the statistical homogeneous area of rock mass structure and the number of discontinuous surface dominant groups in the statistical homogeneous area; (4) According to the corresponding data simulation of each group of discontinuous surfaces, a three-dimensional network numerical model of discontinuous surfaces is generated; (5) Combined with the exploration data, using the TSP detection results as the original data, combined with the numerical model of the three-dimensional network of the discontinuity surface, the stability of the rock mass in front is comprehensively predicted in advance; In the step (2), the TSP system data information includes a depth migration map, a three-dimensional display map, occurrence information and a rock mass 2D physical property map; In the step (2), the surrounding rock conditions in front of the excavation face are analyzed and a preliminary prediction is made in combination with the previous exploration data and the depth migration map generated after processing by the TSP system. 2. A kind of geological advance prediction method based on TSP system and rock mass random discontinuity surface three-dimensional network as claimed in claim 1, it is characterized in that: in the described step (1), the data validity is discriminated, means In the field test process, the signal whose interference to the data is less than the threshold is selected. 3. a kind of geological advance prediction method based on TSP system and rock mass random discontinuity surface three-dimensional network as claimed in claim 1, it is characterized in that: in described step (3), to rock mass structure statistical homogeneous area division , different rock mass structures have different rock mass mechanical characteristics and rock mass hydraulic properties, using the probability correlation table Schmidt diagram comparison method, combined with the actual geological characteristics to divide the statistical homogeneity area of rock mass structure. 4. a kind of geological advance prediction method based on TSP system and rock mass random discontinuity surface three-dimensional network as claimed in claim 1, is characterized in that: in described step (4), discontinuity surface space three-dimensional network numerical model, The process includes: deviation correction of discontinuous surface trace length and simulation of trace length size, simulation of discontinuous surface spacing and density, correction of discontinuous surface occurrence measurement deviation or/and Monte Carlo simulation and model verification. 5. a kind of geological advance prediction method based on TSP system and rock mass random discontinuity surface three-dimensional network as claimed in claim 1, it is characterized in that: in described step (4), adopt the endpoint based on probability statistics The estimator method performs discontinuity track length correction, disk diameter simulation, distribution density function fitting, and spacing measurement bias correction. 6. A kind of geological advance prediction method based on TSP system and rock mass random discontinuity surface three-dimensional network as claimed in claim 1, it is characterized in that: in the described step (4), the simulation process of discontinuity surface spacing, density In order to simulate the spacing of the discontinuous surface, the X ² and KS test methods are used to carry out the best fitting of the probability density function, and the probability distribution density function of the spacing and its corresponding parameters are obtained; Calculation of density. 7. A kind of geological advance prediction method based on TSP system and rock mass random discontinuity surface three-dimensional network as claimed in claim 1, it is characterized in that: in the described step (4), according to having obtained each group of discontinuity surface The average diameter in space, combined with the weight distribution formula, assigns different weights to each discontinuous surface, and then corrects the deviation of the discontinuous surface occurrence measurement. 8. A kind of geological advance prediction method based on TSP system and rock mass random discontinuity three-dimensional network as claimed in claim 1, it is characterized in that: in the described step (4), the process of Monte Carlo simulation and model inspection include: (4-1) Determine the scale of the generated network model; (4-2) Determine the number of discontinuous surfaces in the scale form of the generated network model; (4-3) Determine the spatial position of each discontinuous surface, adopt the method of Monte Carlo simulation, randomly generate the center point coordinates of each discontinuous surface; (4-4) Determine the size of each discontinuous surface diameter: use the Monte Carlo method to simulate and generate the discontinuous surface diameter and make it obey the known best probability distribution; (4-5) Determine the occurrence of the discontinuous surface; (4-6) Combine the results of all simulations to form a complete model and test it.