CN-121994345-A - Grouting monitoring method and system based on distributed optical fibers

CN121994345ACN 121994345 ACN121994345 ACN 121994345ACN-121994345-A

Abstract

The application discloses a grouting monitoring method and a grouting monitoring system based on distributed optical fibers, wherein the optical fibers are distributed and paved in a grouting area, the method comprises the steps of determining microseismic events and microseismic data corresponding to the microseismic events according to optical fiber sensing data, fusing the microseismic data, grouting parameters and geological information to obtain microseismic fusion characteristics aiming at any microseismic event, inputting the microseismic fusion characteristics into a trained microseismic characteristic analysis model for analysis to obtain stress change coefficients and fracture mechanism probability, constructing a geomechanical simulation model according to the geological information, carrying out dynamic inversion, generating a grouting process evolution diagram, and further determining grouting effect information and/or grouting state information as grouting monitoring results of the grouting area. The method can realize real-time dynamic inversion of the grouting process, generate a visual map for intuitively displaying the grouting process, and acquire accurate and reliable grouting monitoring results.

Inventors

GAO RUGAO
GAO ZHENYI
CHEN XINGHU
WANG WEIJUN
WU QIUHONG
LIN HANG
TANG WENYU
ZHANG XUELI
JIANG RUIHAN
LIU JINGYI

Assignees

湖南科技大学

Dates

Publication Date: 20260508
Application Date: 20260109

Claims (10)

1. A grouting monitoring method based on distributed optical fibers, wherein the optical fibers are distributed and laid in a grouting area, the method comprising: Acquiring grouting parameters and geological information of the grouting area and optical fiber sensing data acquired by the optical fiber; Determining a microseismic event and microseismic data corresponding to the microseismic event according to the optical fiber sensing data; aiming at any microseismic event, carrying out space-time alignment and feature fusion on the microseismic data, the grouting parameters and the geological information to obtain microseismic fusion features corresponding to the microseismic event; Inputting the microseismic fusion characteristics into a trained microseismic characteristic analysis model for analysis, and obtaining a stress change coefficient and a fracture mechanism probability corresponding to the microseismic event output by the microseismic characteristic analysis model; Constructing a geomechanical simulation model according to the geological information, and carrying out dynamic inversion on the geomechanical simulation model according to the stress change coefficient, the fracture mechanism probability, the microseismic data, the grouting parameters and the geological information to generate a grouting process evolution diagram; and determining grouting effect information according to the stress change coefficient and the fracture mechanism probability, determining grouting state information according to the grouting process evolution diagram, and taking the grouting effect information and/or the grouting state information as grouting monitoring results of the grouting area.
2. The method of claim 1, wherein the fiber sensing data comprises brillouin shift data, and wherein determining microseismic events and microseismic data corresponding to the microseismic events from the fiber sensing data comprises: Determining optical fiber strain information of the grouting area according to the Brillouin frequency shift data and a preset first corresponding relation, wherein the first corresponding relation is the corresponding relation between the Brillouin frequency shift data and the optical fiber strain information; Detecting and separating a transient strain signal which accords with the preset microseism signal characteristics from the optical fiber strain information, and taking an event corresponding to the transient strain signal as the microseism event; and extracting time domain features, frequency domain features and spatial position features corresponding to the transient strain signals as the microseismic data.
3. The method of claim 1, wherein the microseismic feature analytical model is a deep belief network model built by superposition of multi-layer limited boltzmann machines, and the trained microseismic feature analytical model is trained by: acquiring sample data of a plurality of historical grouting projects, wherein the sample data comprises sample fusion characteristics, sample stress change coefficients corresponding to the sample fusion characteristics and sample fracture mechanism probability; Training a plurality of the limited boltzmann machines forming the deep confidence network model layer by adopting the sample fusion characteristics in an unsupervised learning mode to obtain a pre-trained microseismic characteristic analysis model; Taking the sample stress change coefficient and the sample fracture mechanism probability as supervision targets, performing supervision fine adjustment on the pre-trained microseismic feature analysis model, and obtaining the trained microseismic feature analysis model under the condition that the pre-trained microseismic feature analysis model meets the preset training stop condition.
4. The method of claim 1, wherein the steps of constructing a geomechanical simulation model from the geologic information and dynamically inverting the geomechanical simulation model based on the stress variation coefficient, the fracture mechanism probability, the microseismic data, the grouting parameters, and the geologic information to generate a grouting process evolution map comprise: constructing a geomechanical simulation model of the grouting area according to the geological information; Constructing a correlation three-dimensional graph according to the microseismic data and the grouting parameters, wherein the correlation three-dimensional graph is used for representing the corresponding relation between any microseismic event and grouting working condition parameters; Constructing an associated thermodynamic matrix according to the microseismic data, the grouting parameters and the geological information, wherein the associated thermodynamic matrix is used for representing the corresponding relation between any microseismic event and grouting response information; Constructing stress distribution information and fracture network information of the grouting area according to the stress change coefficient and the fracture mechanism probability; Aiming at any microseismic event, searching grouting working condition parameters corresponding to the microseismic event from the associated three-dimensional graph as target working condition parameters; searching grouting response information corresponding to the microseismic event from the associated thermodynamic matrix to serve as target response information; in a simulation environment, setting the stress distribution information and the fracture network information as initial conditions of the geomechanical simulation model, inputting the target working condition parameters as boundary conditions, taking the target response information as simulation constraint conditions, and driving the geomechanical simulation model to perform finite element simulation according to the stress change coefficient and the fracture mechanism probability to generate a slurry diffusion path evolution diagram and a stratum disturbance range evolution diagram; And taking the slurry diffusion path evolution diagram and/or the stratum disturbance range evolution diagram as the grouting process evolution diagram.
5. The method of claim 4, wherein constructing an associated three-dimensional map from the microseismic data and the grouting parameters comprises: Determining event position coordinates of any microseismic event according to the microseismic data; respectively determining grouting pipe position coordinates of a plurality of grouting pipes according to the grouting parameters; Determining the position coordinates of the grouting pipes with the nearest space distance according to the event position coordinates, and taking the grouting pipe corresponding to the position coordinates of the grouting pipes as an associated grouting pipe; Acquiring grouting pressure information of the associated grouting pipe and grouting interval information between the associated grouting pipe and an adjacent grouting pipe, and taking the grouting pressure information and the grouting interval information as grouting working condition parameters corresponding to the microseismic event; Mapping the microseismic event into one data point in a preset three-dimensional visualization space according to the event position coordinate and the grouting working condition parameter, wherein one coordinate dimension of the three-dimensional visualization space represents the grouting pressure information, one coordinate dimension represents the grouting interval information, and the other coordinate dimension represents the event position coordinate; And calculating the density values of the microseismic events of different areas in the three-dimensional visualization space, and performing color rendering on the corresponding areas according to the density values of the microseismic events to generate the associated three-dimensional graph.
6. The method of claim 4, wherein constructing an associated thermodynamic matrix from the microseismic data, the grouting parameters, and the geological information comprises: determining microseismic features of any microseismic event according to the microseismic data, wherein the microseismic features at least comprise energy features and frequency spectrum features; determining slurry property parameters and grouting process rate parameters corresponding to the microseism event according to the grouting parameters; inquiring stratum inherent attribute parameters corresponding to the microseismic event from the geological information according to the event position coordinates of the microseismic event; Constructing a two-dimensional correlation table based on the microseismic characteristics, the slurry property parameters, the grouting process rate parameters and the stratum inherent attribute parameters which correspond to the microseismic events respectively, wherein the row dimension of the two-dimensional correlation table represents the microseismic characteristics, and the column dimension represents grouting response parameters composed of the slurry property parameters, the grouting process rate parameters and the stratum inherent attribute parameters; Calculating an association strength index between the microseismic characteristic corresponding to each cell in the two-dimensional association table and the grouting response parameter; and filling the colors of each cell according to the associated intensity index to obtain the associated thermodynamic matrix.
7. The method according to claim 4, wherein the step of determining grouting effect information according to the stress variation coefficient and the fracture mechanism probability, determining grouting state information according to the grouting process evolution diagram, and using the grouting effect information and/or the grouting state information as grouting monitoring results of the grouting area comprises the following steps: classifying the microseismic events according to the stress change coefficient and the fracture mechanism probability to obtain a reinforcing event and a fracture event; Determining stratum reinforcement effect indexes according to the proportion of the reinforcement events in the microseism events; identifying a slurry driven event from the microseismic events according to the fracture mechanism probability; determining a slurry diffusion path from a spatial location of the slurry driven event; Taking the microseismic event on the slurry diffusion path as a diffusion event, and classifying the diffusion event according to the stress change coefficient of the diffusion event to obtain a stable diffusion event and an abnormal disturbance event; determining a slurry diffusion path rationality index according to the proportion of the stable diffusion event in the diffusion event; taking the stratum reinforcing effect index and/or the slurry diffusion path rationality index as the grouting effect information; Determining grouting stability indexes according to the slurry diffusion path evolution diagram; determining slurry filling indexes according to the stratum disturbance range evolution diagram; taking the grouting stability index and/or the slurry filling index as the grouting state information; and taking the grouting effect information and/or the grouting state information as grouting monitoring results of the grouting area.
8. A grouting monitoring system based on distributed optical fibers, wherein the optical fibers are distributed and laid in a grouting area, the system comprising: the multi-source data acquisition module is used for acquiring grouting parameters, geological information and optical fiber sensing data acquired by the optical fibers of the grouting area; The microseismic data acquisition module is used for determining microseismic events and microseismic data corresponding to the microseismic events according to the optical fiber sensing data; The fusion characteristic acquisition module is used for carrying out space-time alignment and characteristic fusion on the microseismic data, the grouting parameters and the geological information aiming at any microseismic event to obtain microseismic fusion characteristics corresponding to the microseismic event; The fusion characteristic analysis module is used for inputting the microseism fusion characteristics into a trained microseism characteristic analysis model to analyze, so as to obtain a stress change coefficient and a fracture mechanism probability corresponding to the microseism event output by the microseism characteristic analysis model; The evolution diagram acquisition module is used for constructing a geomechanical simulation model according to the geological information, and carrying out dynamic inversion on the geomechanical simulation model according to the stress change coefficient, the fracture mechanism probability, the microseismic data, the grouting parameters and the geological information to generate a grouting process evolution diagram; And the monitoring result acquisition module is used for determining grouting effect information according to the stress change coefficient and the fracture mechanism probability, determining grouting state information according to the grouting process evolution diagram, and taking the grouting effect information and/or the grouting state information as grouting monitoring results of the grouting area.
9. An electronic device comprising a processor, a memory and a program or instruction stored on the memory and executable on the processor, the program or instruction when executed by the processor implementing the method of any one of claims 1-7.
10. A readable storage medium, characterized in that it stores thereon a program or instructions, which when executed by a processor, implements the method according to any of claims 1-7.

Description

Grouting monitoring method and system based on distributed optical fibers Technical Field The application belongs to the field of grouting monitoring, and particularly relates to a grouting monitoring method and system based on distributed optical fibers. Background The grouting technology is a core technology for guaranteeing engineering safety, and is important for accurate monitoring of grouting process and effect. The current mainstream grouting monitoring technology is to arrange discrete sensors in a monitoring area to collect rock mass vibration signals, and the method has the defects of limited monitoring range, weak anti-interference capability, low signal-to-noise ratio and the like. Therefore, the distributed optical fiber monitoring technology is introduced due to the advantages of global coverage, strong interference resistance, high sensitivity and the like. However, although the distributed optical fiber technology solves the difficult problem of data acquisition and generates massive, multi-scale and nonlinear microseismic strain data, in the prior art, it is difficult to automatically and accurately extract physical characteristics directly related to stratum mechanical behaviors from multi-source complex data, and further, it is difficult to realize real-time dynamic inversion of a grouting process, and a visual map for intuitively displaying the grouting process cannot be generated, so that an accurate and reliable grouting monitoring result cannot be obtained. Disclosure of Invention The invention aims to provide a grouting monitoring method and system based on distributed optical fibers, which aim to at least solve one of the technical problems in the prior art. In a first aspect, an embodiment of the present application provides a grouting monitoring method based on a distributed optical fiber, where the optical fiber is distributed and laid in a grouting area, and the method includes: Acquiring grouting parameters and geological information of the grouting area and optical fiber sensing data acquired by the optical fiber; Determining a microseismic event and microseismic data corresponding to the microseismic event according to the optical fiber sensing data; aiming at any microseismic event, carrying out space-time alignment and feature fusion on the microseismic data, the grouting parameters and the geological information to obtain microseismic fusion features corresponding to the microseismic event; Inputting the microseismic fusion characteristics into a trained microseismic characteristic analysis model for analysis, and obtaining a stress change coefficient and a fracture mechanism probability corresponding to the microseismic event output by the microseismic characteristic analysis model; Constructing a geomechanical simulation model according to the geological information, and carrying out dynamic inversion on the geomechanical simulation model according to the stress change coefficient, the fracture mechanism probability, the microseismic data, the grouting parameters and the geological information to generate a grouting process evolution diagram; and determining grouting effect information according to the stress change coefficient and the fracture mechanism probability, determining grouting state information according to the grouting process evolution diagram, and taking the grouting effect information and/or the grouting state information as grouting monitoring results of the grouting area. In a second aspect, an embodiment of the present application provides a grouting monitoring system based on a distributed optical fiber, where the optical fiber is distributed and laid in a grouting area, and the system includes: the multi-source data acquisition module is used for acquiring grouting parameters, geological information and optical fiber sensing data acquired by the optical fibers of the grouting area; The microseismic data acquisition module is used for determining microseismic events and microseismic data corresponding to the microseismic events according to the optical fiber sensing data; The fusion characteristic acquisition module is used for carrying out space-time alignment and characteristic fusion on the microseismic data, the grouting parameters and the geological information aiming at any microseismic event to obtain microseismic fusion characteristics corresponding to the microseismic event; The fusion characteristic analysis module is used for inputting the microseism fusion characteristics into a trained microseism characteristic analysis model to analyze, so as to obtain a stress change coefficient and a fracture mechanism probability corresponding to the microseism event output by the microseism characteristic analysis model; The evolution diagram acquisition module is used for constructing a geomechanical simulation model according to the geological information, and carrying out dynamic inversion on the geomechanical simulation model according to the stre