Research And Application Of Using Mine Tremor Velocity Tomography To Forecast Rockburst Danger In Coal Mine

The rockburst phenomena become progressively more severe as the mining depth and extent increase, so it is urgent to get the stress information to realize the prediction of rockburst. Focusing the experimental relationship between stress and tremor velocity derived from laboratory investigation, this thesis built the mine tremor velocity tomography model to calculate the velocity using mine tremor information. The influencing factors of the model,such as the optimal configuration of seismological observation network and the improvement of input data precision, were analyzed by theoretical analysis, field testing, numerical simulation and numerical emulation so as to obtain accurate result, thereby revealing the correlation between rockburst and velocity, which is used to guide the prevention measures and calculate three prediction indexs. At last, the method was applied to the engineering practice and applications.Through the laboratorial research, the experimental models between stress and tremor velocity were created under different loading and unloading ways. Also the parameters of the derived model were analyzed. Studies indicate that the velocity gradient is usually highest at elastic stage and then begins to level out at plastic stage. Velocity can be used to infer stress distribution because the relationship can be expressed as power functions. The measured sonic velocity showed that the experimental models have the better fitness than theoretical formula.The damping least square solution model is proposed based on the mine tremor velocity tomography theory, wich use SIRT algorithm and various seismic raytracing methods to calculate the velocity. In order to evaluate the stability of inversion result, the evaluation model of expected velocity deviation was created based on the statistical methods. Studies show that the solution algorithm is rather time-cousuming, but can ensure the program to be convergent steadily, and also the good corresponding relationship exists between the expected velocity deviation model and raypath sampling density.In this paper, according to practical conditions and requirements of coal mines, especially the accuracy of picking seismic wave arrivals at stations and building velocity model, the main influencing factors and bad conditions which influence the accuracy of source location were analyzed using the theory of D-optimal design and localization. A view of using the comprehensive index method to determine the high microseismic activity zones and the occurrence probability of mining-induced tremors was also proposed. In addition, since the location capacity of network can't be reflected accurately using the source standard error calculated by the traditional theoretical analysis, the model of expected epicenter and hypocenter error was created by numerical emulation experiment, and then the optimal design and assessment system of network was built up finally. The results from experiment and field practice show that, the optimal design and assessment system can be used to solve the optimal plan of network quickly and evaluate the location ability of network exactly.In order to improve the input data precision, the P-wave was selected and filted by wavelet analysis to improve the accuracy of picking first arrival time which is used in the two kinds of source location algorithm in forward calculation by the created algorithm GE-POWELL to identify the best channel number and the initial velocity value. The application of these methods in field tests can effectively improve the location accuracy of mine tremor.Based on strength theory, energy theory and dynamic load equation, three prediction indexs including velocity anomaly, velocity gradient VG anomaly and stress concentration factor calculated by experimental relationship between stress and tremor velocity were created to predict rockburst danger. The prediction results are used to guide the prevention measures. The compared analysis between CT experiment and numerical simulation was conducted in LW16302C Jisan Coal Mine. The application results show that they have the common points and differences, but velocity has the stronger applicability.The on-site prediction and prevention practice was conducted by using the recorded mine tremor signals form LW10302 in Baodian Coal Mine and LW8929 in Xin Zhouyao Coal Mine with SOS microseismic monitoring system. The three prediction indexs calculated from inversion velocity distribution were used to predict the rockburst danger zone and level for the next period and the future monitoring results showed that most of the rockburst events and strong mine tremors truly occurred in the predicted danger zones and well correlated with the stress concentration zones in coal pillar etc. The successful application indicated that the mine tremor velocity tomography can exactly predicit the rockburst danger and point out the direction for prevention.