Preliminary engineering application of microseismic monitoring technique to rockburst prediction in tunneling of Jinping Ⅱ project

Monitoring and prediction of rockburst remain to be worldwide challenges in geotechnical engineering.In hydropower,transportation and other engineering fields in China,more deep,long and large tunnels have been under construction in recent years and underground caverns are more evidently featured by ＂long,large,deep and in group＂,which bring in many problems associated with rock mechanics problems at great depth,especially rockburst.Rockbursts lead to damages to not only underground structures and equipments but also personnel safety.It has been a major technical bottleneck in future deep underground engineering in China.In this paper,compared with earthquake prediction,the feasibility in principle of monitoring and prediction of rockbursts is discussed,considering the source zones,development cycle and scale.The authors think the feasibility of rockburst prediction can be understood in three aspects：（1） the heterogeneity of rock is the main reason for the existence of rockburst precursors;（2） deformation localization is the intrinsic cause of rockburst;and（3） the interaction between target rock mass and its surrounding rock mass is the external cause of rockburst.As an engineering practice,the application of microseismic monitoring techniques during tunnel construction of Jinping II Hydropower Station was reported.It is found that precursory microcracking exists prior to most rockbursts,which could be captured by the microseismic monitoring system.The stress concentration is evident near structural discontinuities（such as faults or joints）,which shall be the focus of rockburst monitoring.It is concluded that,by integrating the microseismic monitoring and the rock failure process simulation,the feasibility of rockburst prediction is expected to be enhanced.

Microseismic monitoring and numerical simulation on the stability of high-steep rock slopes in hydropower engineering

For high-steep slopes in hydropower engineering, damage can be induced or accumulated due to a seriesof human or natural activities, including excavation, dam construction, earthquake, rainstorm, rapid riseor drop of water level in the service lifetime of slopes. According to the concept that the progressivedamage （microseismicity） of rock slope is the essence of the precursor of slope instability, a microseismicmonitoring system for high-steep rock slopes is established. Positioning accuracy of the monitoringsystem is tested by fixed-position blasting method. Based on waveform and cluster analyses of microseismicevents recorded during test, the tempo-spatial distribution of microseismic events is analyzed.The deformation zone in the deep rock masses induced by the microseismic events is preliminarilydelimited. Based on the physical information measured by in situ microseismic monitoring, an evaluationmethod for the dynamic stability of rock slopes is proposed and preliminarily implemented bycombining microseismic monitoring and numerical modeling. Based on the rock mass damage modelobtained by back analysis of microseismic information, the rock mass elements within the microseismicdamage zone are automatically searched by finite element program. Then the stiffness and strengthreductions are performed on these damaged elements accordingly. Attempts are made to establish thecorrelation between microseismic event, strength deterioration and slope dynamic instability, so as toquantitatively evaluate the dynamic stability of slope. The case studies about two practical slopes indicatethat the proposed method can reflect the factor of safety of rock slope more objectively. Numericalanalysis can help to understand the characteristics and modes of the monitored microseismic events inrock slopes. Microseismic monitoring data and simulation results can be used to mutually modify thesensitive rock parameters and calibrate the model. Combination of microseismic monitoring and numericalsimulation provides a more objective basis for the numerical model and parameters and a solidmechanical foundation for the microseismic monitoring.

Application of a microseismic monitoring system in deep mining

A microseismic monitoring system was used in the Donggua Shan underground copper mine, and its application was introduced. The spacial distribution of the seismic event was monitored effectively during mining with this system. The distribution of the seismic intensity in different time periods and in the different mining districts was obtained via the clustering analysis of the monitored results, and the different intensity concentration districts of seismicity were compartmentalized. The various characteristics and waveforms of different vibrations in the underground mine were revealed with the help of the micro-seismic monitoring system. It was proved that the construction and application of the micro-seismic monitoring system in the mine not only realized the continuous monitoring of seismicity in the deep mine, but also settled an this system.

Developments and prospects of microseismic monitoring technology in underground metal mines in China

Microseismic monitoring technology has become an important technique to assess stability of rock mass in metal mines.Due to the special characteristics of underground metal mines in China,including the high tectonic stress,irregular shape and existence of ore body,and complex mining methods,the application of microseismic technology is more diverse in China compared to other countries,and is more challenging than in other underground structures such as tunnels,hydropower stations and coal mines.Apart from assessing rock mass stability and ground pressure hazards induced by mining process,blasting,water inrush and large scale goaf,microseismic technology is also used to monitor illegal mining,and track personnel location during rescue work.Moreover,microseismic data have been used to optimize mining parameters in some metal mines.The technology is increasingly used to investigate cracking mechanism in the design of rock mass supports.In this paper,the application,research development and related achievements of microseismic technology in underground metal mines in China are summarized.By considering underground mines from the perspective of informatization,automation and intelligentization,future studies should focus on intelligent microseismic data processing method,e.g.,signal identification of microseismic and precise location algorithm,and on the research and development of microseismic equipment.In addition,integrated monitoring and collaborative analysis for rock mass response caused by mining disturbance will have good prospects for future development.

Formation mechanism of rockburst in deep tunnel adjacent to faults:Implication from numerical simulation and microseismic monitoring

Rockbursts were frequently encountered in the construction of deeply buried tunnels at the Jinping-II hydropower station, Southwest China. In those cases, the existence of large structural planes, such as faults, was usually observed near the excavation boundaries. The formation mechanism of the “11·28” rockburst, which was a typical rockburst and occurred in a drainage tunnel under a deep burial depth, high in-situ stress state and complex geological conditions, has been difficult to explain. Realistic failure process analysis(RFPA3D) software was adopted to numerically simulate the whole failure process of the surrounding rock mass around the tunnel subjected to excavation. The spatial distribution of acoustic emission derived from numerical simulation contributed to explaining the mechanical responses of the process. Analyses of the stress, safety reserve coefficient and damage degree were performed to reveal the effect of faults on the formation of rockbursts in the deep tunnel. The existence of faults results in the formation of stress anomaly areas between the tunnel and the fault. The surrounding rock mass failure propagates toward the fault from the initial failure, to different degrees. The relative positions and angles of faults play significant roles in the extent and development of surrounding rock mass failure, respectively. The increase in the lateral stress coefficient leads to the aggravation of the surrounding rock mass damage, especially in the roof and floor of the tunnel. Moreover, as the rock strength-stress ratio increases, the failure mode of the near-fault tunnel gradually changes from the stress-controlled type to the compound-controlled type. These findings were consistent with the microseismic monitoring results and field observations, which was helpful to understand the mechanical behavior of tunnel excavation affected by faults. The achievements of this study can provide some references for analysis of the failure mechanisms of similar deep tunnels.

Activation characteristics analysis on concealed fault in the excavating coal roadway based on microseismic monitoring technique

In order to effectively monitor the concealed fault activation process in excavation activities, based on the actual condition of a working face containing faults with high outburst danger in Xin Zhuangzi mine in Huainan, China, we carried out all-side tracking and monitoring on the fault activation process and development trend in excavation activities by establishing a microseismic monitoring system. The results show that excavation activities have a rather great influence on the fault activation. With the working face approaching the fault, the fault activation builds up and the outburst danger increases; when the excavation activities finishes, the fault activation tends to be stable. The number of microseismic events are corresponding to the intensity of fault activation, and the distribution rules of microseismic events can effectively determine the fault occurrence in the mine. Microseismic monitoring technique is accurate in terms of detecting geologic tectonic activities, such as fault activations lying ahead during excavation activities. By utilizing this technique, we can determine outburst danger in excavation activities in time and accordingly take effective countermeasures to prevent and reduce the occurrence of outburst accidents.

Stability evaluation for steep bank slope with microseismic monitoring in Three Gorges Reservoir area

Rock slide is one of the common geohazard in the Three Gorges Reservoir area, and it affects the shipping of the Yangtze River and the safety of people living on the banks. In order to investigate the internal fracturing mechanism of rock mass, distributed microseismic monitoring network was arranged with 15 three component geophones(3C geophones), deployed at borehole and out of the sliding mass in the unstable Dulong slope. Stein Unbiased Risk Estimation(SURE) method was used to noise suppression for the microseismic record, and decomposition parameters of the Continuous Wavelet Transform(CWT) were determined with maximum energy of correlation coefficient(MECC) method. The signal-to-noise ratio was tripled after the process, and source parameters are obtained with full waveform inversion. The rupture volume model was counted by the irregular grid statistics with the events’ density. It shows that the rock slide is of a small scale and composed of a single block. Moreover, the relationship among microseismicity, displacement and rainfall were discussed in the paper. The deformation rate was dramatically changed in the period of intensive events. There is a good consistency especially in the rainfall period. Although there is a time delay, continuous rainfall is more likely to cause the increase of microseismic events. The results show that the Dulong slope is a shallow rock slide in the state of creep deformation, and the rupture mechanism of the rock mass is left-lateral normal fault with shear failure. The research provides more key information for the early warning and prevention of rock slides and helps to reduce the risk of geohazards.

Effect analysis of borehole microseismic monitoring technology on shale gas fracturing in western Hubei

Hydraulic fracturing technology is an important means of shale gas development,and microseismic monitoring is the key technology of fracturing effect evaluation.In this study,hydraulic fracturing and microseismic monitoring were simultaneously conducted in the Eyangye 2HF well(hereinafter referred to as EYY2HF well).The target stratum of this well is the second member of the Doushantuo Formation of the Sinian System,which is the oldest stratum of horizontal shale gas wells in the world.A total of 4341 microseismic fracturing events were identified,and 23 fracturing stages of the well were defined.The fluctuation of the number of events showed a repeating“high-low”pattern,and the average energy of these events showed minimal differences.These findings indicate that the water pressure required for the reconstruction of the EYY2HF well is appropriate.The main body of the fracture network extended from northwest to southeast,consistent with the interpretation of regional geological and seismic data.The stimulated rock volumes showed a linear increase with the increase of the fracturing stage.Some technological measures,such as quick lift displacement,quick lift sand ratio,and pump stop for secondary sand addition,were adopted during fracturing to increase the complexity of the fracture network.Microseismic fracture monitoring of the well achieved expected eff ects and guided real-time fracturing operations and fracturing eff ect evaluation.

Fractal characterization for the mining crack evolution process of overlying strata based on microseismic monitoring technology

In order to study the evolution laws during the development process of the coal face overburden rock mining-induced fissure,we studied the process of evolution of overburden rock mining-induced fissures and dynamically quantitatively described its fractal laws,based on the high-precision microseismic monitoring method and the nonlinear Fractal Geometry Theory.The results show that:the overburden rock mining-induced fissure fractal dimension experiences two periodic change processes with the coal face advance,namely a Small→ Big→ Small process,which tends to be stable;the functional relationship between the extraction step distance and the overburden rock mining-induced fissure fractal dimension is a cubic curve.The results suggest that the fractal dimension reflects the evolution characteristics of the overburden rock mining-induced fissure,which can be used as an evaluation index of the stability of the overburden rock strata,and it provides theoretical guidance for stability analysis of the overburden rock strata,goaf roof control and the support movements in the mining face.

Microseismic Monitoring Data Fusion Algorithm and Coal and Gas Outbursts Prediction

The prediction study on coal and gas outbursts is carried out by monitoring some indices which are sensitive to the initiation of coal and gas outbursts. The values and changing roles of the indices are the foundations of coal and gas outbursts prediction. But now, only the data of ere key monitoring station is used in the coal and gas outbursts prediction practice, and the other data are ignored. In order to overcome the human factor and make full use of the monitoring information, the technique of multi-sensor target tracking is proposed to deal with the microseismic informatiion. With the results of microseismic events, the activities of geological structure, fracure-depth of roof and floor, and the location of gas channel are obtained. These studies indicate that it is considerably possible to predict the coal and gas outbursts using microseismic monitoring with its inherent ability to remotely monitor the progressive failure caused by mining.

Distribution characteristics and the evolution law of excavation damage zone in the large-span transition section of high-speed railway tunnel based on microseismic monitoring

Purpose–The microseismic monitoring technique has great advantages on identifying the location,extent and the mechanism of damage process occurring in rock mass.This study aims to analyze distribution characteristics and the evolution law of excavation damage zone of surrounding rock based on microseismic monitoring data.Design/methodology/approach–In situ test using microseismic monitoring technique is carried out in the large-span transition tunnel of Badaling Great Wall Station of Beijing-Zhangjiakou high-speed railway.An intelligent microseismic monitoring system is built with symmetry monitoring point layout both on the mountain surface and inside the tunnel to achieve three-dimensional and all-round monitoring results.Findings–Microseismic events can be divided into high density area,medium density area and low density area according to the density distribution of microseismic events.The positions where the cumulative distribution frequencies of microseismic events are 60 and 80%are identified as the boundaries between high and medium density areas and between medium and low density areas,respectively.The high density area of microseismic events is regarded as the high excavation damage zone of surrounding rock,which is affected by the grade of surrounding rock and the span of tunnel.The prediction formulas for the depth of high excavation damage zone of surrounding rock at different tunnel positions are given considering these two parameters.The scale of the average moment magnitude parameters of microseismic events is adopted to describe the damage degree of surrounding rock.The strong positive correlation and multistage characteristics between the depth of excavation damage zone and deformation of surrounding rock are revealed.Based on the depth of high excavation damage zone of surrounding rock,the prestressed anchor cable(rod)is designed,and the safety of anchor cable(rod)design parameters is verified by the deformation results of surrounding rock.Originality/value–The research provides a new method to predict the surrounding rock damage zone of large-span tunnel and also provides a reference basis for design parameters of prestressed anchor cable(rod).

Analysis of rockburst mechanism and warning based on microseismic moment tensors and dynamic Bayesian networks

One of the major factors inhibiting the construction of deep underground projects is the risk posed by rockbursts.A study was conducted on the access tunnel of the Shuangjiangkou hydropower station to determine the evolutionary mechanism of microfractures within the surrounding rock mass during rockburst development and develop a rockburst warning model.The study area was chosen through the combination of field studies with an analysis of the spatial and temporal distribution of microseismic(MS)events.The moment tensor inversion method was adopted to study rockburst mechanism,and a dynamic Bayesian network(DBN)was applied to investigating the sensitivity of MS source parameters for rockburst warnings.A MS multivariable rockburst warning model was proposed and validated using two case studies.The results indicate that fractures in the surrounding rock mass during the development of strain-structure rockbursts initially show shear failure and are then followed by tensile failure.The effectiveness of the DBN-based rockburst warning model was demonstrated using self-validation and K-fold cross-validation.Moment magnitude and source radius are the most sensitive factors based on an investigation of the influence on the parent and child nodes in the model,which can serve as important standards for rockburst warnings.The proposed rockburst warning model was found to be effective when applied to two actual projects.

A 3D microseismic data-driven damage model for jointed rock mass under hydro-mechanical coupling conditions and its application

Rock mass is a fractured porous medium usually subjected to complex geostress and fluid pressure simultaneously.Moreover,the properties of rock mass change in time and space due to mining-induced fractures.Therefore,it is always challenging to accurately measure rock mass properties.In this study,a three-dimensional(3D)microseismic(MS)data-driven damage model for jointed rock mass under hydro-mechanical coupling conditions is proposed.It is a 3D finite element model that takes seepage,damage and stress field effects into account jointly.Multiple factors(i.e.joints,water and microseismicity)are used to optimize the rock mass mechanical parameters at different scales.The model is applied in Shirengou iron mine to study the damage evolution of rock mass and assess the crown pillar stability during the transition from open-pit to underground mining.It is found that the damage pattern is mostly controlled by the structure,water and rock mass parameters.The damage pattern is evidently different from the two-dimensional result and is more consistent with the field observations.This difference is caused by the MS-derived damage acting on the rock mass.MS data are responsible for gradually correcting the damage zone,changing the direction in which it expands,and promoting it to evolve close to reality.For the crown pillar,the proposed model yields a more trustworthy safety factor.In order to guarantee the stability of the pillar,it is suggested to take waterproof and reinforcement measures in areas with a high degree of damage.

Fault detection based on microseismic events

In unconventional reservoirs, small faults allow the flow ofoil and gas as well as act as obstacles to exploration; for, （1） fracturing facilitates fluid migration, （2） reservoir flooding, and （3） triggering of small earthquakes. These small faults are not generally detected because of the low seismic resolution. However, such small faults are very active and release sufficient energy to initiate a large number of microseismic events （MEs） during hydraulic fracturing. In this study, we identified microfractures （MF） from hydraulic fracturing and natural small faults based on microseismicity characteristics, such as the time-space distribution, source mechanism, magnitude, amplitude, and frequency. First, I identified the mechanism of small faults and MF by reservoir stress analysis and calibrated the ME based on the microseismic magnitude. The dynamic characteristics （frequency and amplitude） of MEs triggered by natural faults and MF were analyzed; moreover, the geometry and activity types of natural fault and MF were grouped according to the source mechanism. Finally, the differences among time-space distribution, magnitude, source mechanism, amplitude, and frequency were used to differentiate natural faults and manmade fractures.

Weighted-elastic-wave interferometric imaging of microseismic source location

Knowledge of the locations of seismic sources is critical for microseismic monitoring. Time-window-based elastic wave interferometric imaging and weighted- elastic-wave （WEW） interferometric imaging are proposed and used to locate modeled microseismic sources. The proposed method improves the precision and eliminates artifacts in location profiles. Numerical experiments based on a horizontally layered isotropic medium have shown that the method offers the following advantages： It can deal with Iow-SNR microseismic data with velocity perturbations as well as relatively sparse receivers and still maintain relatively high precision despite the errors in the velocity model. Furthermore, it is more efficient than conventional traveltime inversion methods because interferometric imaging does not require traveltime picking. Numerical results using a 2D fault model have also suggested that the weighted-elastic-wave interferometric imaging can locate multiple sources with higher location precision than the time-reverse imaging method.

Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices

Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.

Discrimination of mining microseismic events and blasts using convolutional neural networks and original waveform

Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic events for providing accurate information of rockmass.The accurate identification of microseismic events and blasts determines the timeliness and accuracy of early warning of microseismic monitoring technology.An image identification model based on Convolutional Neural Network(CNN)is established in this paper for the seismic waveforms of microseismic events and blasts.Firstly,the training set,test set,and validation set are collected,which are composed of 5250,1500,and 750 seismic waveforms of microseismic events and blasts,respectively.The classified data sets are preprocessed and input into the constructed CNN in CPU mode for training.Results show that the accuracies of microseismic events and blasts are 99.46%and 99.33%in the test set,respectively.The accuracies of microseismic events and blasts are 100%and 98.13%in the validation set,respectively.The proposed method gives superior performance when compared with existed methods.The accuracies of models using logistic regression and artificial neural network(ANN)based on the same data set are 54.43%and 67.9%in the test set,respectively.Then,the ROC curves of the three models are obtained and compared,which show that the CNN gives an absolute advantage in this classification model when the original seismic waveform are used in training the model.It not only decreases the influence of individual differences in experience,but also removes the errors induced by source and waveform parameters.It is proved that the established discriminant method improves the efficiency and accuracy of microseismic data processing for monitoring rock instability and seismicity.

Propagation patterns of microseismic waves in rock strata during mining:an experimental study

Microseismic monitoring has been widely used in mines for monitoring and predicting dynamic disasters such as rockbursts and waterbursts. However, to develop high-precision microseismic monitoring systems, the propagation patterns of microseismic waves under complex geological conditions must be elucidated. To achieve this aim, a simulation model of a typical coalmine was designed using similar materials according to the similarity theory to simulate the mining process. Geophones were embedded into the model to detect the propagation of elastic waves from microseisms. The results show that in an unmined solid rock mass, the wave velocity in shallow rock strata is mainly affected by geologically weak planes, whereas in deep strata it is affected mainly by the density of the rock mass. During propagation, the amplitude first decreases and then increases rapidly with increasing propagation distance from the coal layer. After mining, our results indicate that the goaf causes significant attenuation of the wave velocity. After the goaf was backfilled, the velocity attenuation is reduced to some extent but not eliminated. The results of this study can be used as guidelines for designing and applying microseismic monitoring systems in mines.

Identification methods for anomalous stress region in coal roadways based on microseismic information and numerical simulation

It is believed that the microseismicity induced by mining effect and gas gradient disturbance stress is a precursor to the essential characteristics of roadway unstability. In order to effectively identify and evaluate the stability of coal roadways in the process of mine development and extraction, a microseismic monitoring system was deployed for the study of the stress evolution process, damage degree and distribution characteristics in the tailgate and headgate. The mine under study is the 62113 outburst working face of Xin Zhuangzi coalmine in Huainan mining area. The whole process of microfractures initiation,extension, interaction and coalescence mechanisms during the progressive failure processes of the coal rock within the delineated and typical event clusters were investigated by means of a two dimensional realistic failure process analysis code(RFPA2D-Flow). The results show that the microseismic events gradually create different-sized event clusters. The microseismicity of the tailgate is significantly higher than that of the headgate. The study indicates that the greater anomalous stress region matches the area where microfractures continuously develop and finally connect to each other and form a fissure zone.Due to the mine layout and stress concentration, the ruptured area is mainly located on the left shoulder of the tailgate roof. The potential anomalous stress region of the coal roadway obtained by numerical simulation is relatively in good agreement with the trend of spatial macro evolution of coal rock microfractures captured by the microseismic monitoring system. The research results can provide important basis for understanding instability failure mechanism of deep roadway and microseismic activity law in complex geologic conditions, and it ultimately can be used to guide the selection and optimization of reinforcement and protection scheme.

Characteristics of microseismic b-value associated with rock mass large deformation in underground powerhouse caverns at different stress levels

Rock mass large deformation in underground powerhouse caverns has been a severe hazard in hydropower engineering in Southwest China.During the development of rock mass large deformation,a sequence of fractures was generated that can be monitored using microseismic(MS)monitoring techniques.Two MS monitoring systems were established in two typical underground powerhouse caverns featuring distinct geostress levels.The MS b-values associated with rock mass large deformation and their temporal variation are analysed.The results showed that the MS bvalue in course of rock mass deformation was less than 1.0 in the underground powerhouse caverns at a high stress level while larger than 1.5 at a low stress level.Prior to the rock mass deformation,the MS b-values derived from both the high-stress and low-stress underground powerhouse caverns show an incremental decrease over 10%within 10 d.The results contribute to understanding the fracturing characteristics of MS sources associated with rock mass large deformation and provide a reference for early warning of rock mass large deformation in underground powerhouse caverns.