Microseismic Monitoring System Research Articles

Integrating Microseismic Monitoring for Predicting Water Inrush Hazards in Coal Mines

The essence of roof water inrush in coal mines fundamentally stems from the development of water-bearing fracture zones, facilitating the intrusion of overlying aquifers and thereby leading to water hazard incidents. Monitoring rock-fracturing conditions through the analysis of microseismic data can, to a certain extent, facilitate the prediction and early warning of water hazards. The water inflow volume stands as the most characteristic type of data in mine water inrush accidents. Hence, we investigated the feasibility of predicting water inrush events through anomalies in microseismic data from the perspective of water inflow volume variations. The data collected from the microseismic monitoring system at the 208 working face were utilized to compute localization information and source parameters. Based on the hydrogeological conditions of the working face, the energy screening range and its calculation grid characteristics were determined, followed by the generation of kernel density cloud maps at different depths. By observing these microseismic kernel density cloud maps, probabilities of roof water-conducting channel formation and potential locations were inferred. Subsequently, based on the positions of these roof water-conducting channels on the planar domain, the extension depth and expansion direction of the water-conducting channels were determined. Utilizing microseismic monitoring data, a quantitative assessment of water inrush risk was conducted, thereby establishing a linkage between microseismic data and water (inrush) data, which are two indirectly related datasets. The height of microseismic events was directly proportional to the trend of water inflow in the working face. In contrast, the occurrence of water inflow events and microseismic events exhibited a specific lag effect, with microseismic events occurring prior to water inrush events. Abnormalities in microseismic monitoring data partially reflect changes in water-conducting channel patterns. When connected with coal seam damage zones, water inrush hazards may occur. Therefore, abnormalities in microseismic monitoring data can be regarded as one of the precursor signals indicating potential floor water inrushes in coal seams.

Rockburst early warning based on microseism and critical point theory

During the tunnel construction, rockbursts occurred, posing a risk to safety. To mitigate this risk, a microseismic monitoring system was installed in the tunnel to provide early warning of rockbursts. After conducting research on the evolution of microseismic events in terms of number, moment magnitude, and energy within a specific time frame, an approach for rockbursts risk assessment based on microseismic moment magnitude was proposed. The critical point theory was utilized to quantitatively analyze the energy release process of the surrounding rock before intense rockbursts. This analysis revealed that the energy release of the surrounding rock before rockbursts can be divided into three stages: stable energy release stage, transitional energy release stage and accelerated energy release stage. The obtained process, derived from the critical point theory, was compared and analyzed alongside the evolution process of value of b, cumulative apparent volume, and energy index.

Application and Research of Microseismic Monitoring System and Hydraulic Fracturing Technology in Coal Mines

In order to improve the effectiveness of coal mine gas control and enhance the level of coal mine safety production, the application of a microseismic monitoring system and hydraulic fracturing technology in coal mines was studied. Applying hydraulic fracturing technology to coal mine gas treatment, firstly, the geological structure and gas concentration in the mining area are detected using the radio tunnel perspective method and infrared differential absorption method. Then, the relevant parameters of hydraulic fracturing are determined, and finally, hydraulic fracturing technology is implemented. Microseismic monitoring technology is used to monitor the cracks formed during hydraulic fracturing construction and evaluate the fracturing effect. The instantaneous energy envelope is obtained from the microseismic data of each detection channel after stacking and Hilbert transform static correction. A microseismic in-phase inversion positioning objective function based on travel time residuals is constructed, and under the constraints of polarization analysis, the optimal solution is obtained through search iteration to complete microseismic in-phase inversion positioning. Experimental results have shown that after applying this method to coal mine gas control, the gas concentration decreases below the execution standard, achieving good control effects. Under microseismic monitoring in coal mines, the hydraulic fracturing effect can be effectively and reasonably evaluated, and the safety production level of coal mines can be improved.

Study on stress distribution law of surrounding rock of roadway under the goaf and mechanism of pressure relief and impact reduction

To safely extract residual coal from a mine affected by rock bursts, the concept of “roadways under goafs” has been proposed as an effective layout. The pressure relief and shock reduction mechanism of roadways under goafs is elucidated through theoretical analysis, numerical simulation, and engineering verification. The stress model for goafs is established based on elastoplastic mechanics, followed by the construction of a force model for coal beneath the goafs. The stress composition of roof, floor and two sides of roadway under a goaf are analyzed. Using the FLAC-PFC coupling simulation method, the excavation process from top coal mining to bottom coal mining roadways of a No. 17 coal mine in Heilongjiang Province was simulated. The simulation results validate the spatiotemporal evolution of the stress and displacement in the surrounding rock mass of the roadway situated beneath goafs and determine the precise location of the roadway and length of its bottom coal face. A large diameter borehole of the roadway and presplitting blasting of the coal face roof are used to solve the local high stress danger area. Moreover, the roadway support mode of the “steel shed + spray arch support + monomer + π steel beam” is proposed. Finally, through the data of the field micro-seismic and stress monitoring system, the effectiveness of the pressure relief and shock reduction of roadways under goafs, the high efficiency of local danger relief of the roadways and working faces, and the practicability of the “steel shed + spray arch support + monomer + π steel beam” support of the roadways broken by surrounding rock are verified. A good basis for choosing a reasonable location for roadways and surrounding rock control methods for residual bottom coal mining and rock burst mining can be found in the research results.

Automatic P-Phase-Onset-Time-Picking Method of Microseismic Monitoring Signal of Underground Mine Based on Noise Reduction and Multiple Detection Indexes.

The underground pressure disaster caused by the exploitation of deep mineral resources has become a major hidden danger restricting the safe production of mines. Microseismic monitoring technology is a universally recognized means of underground pressure monitoring and early warning. In this paper, the wavelet coefficient threshold denoising method in the time-frequency domain, STA/LTA method, AIC method, and skew and kurtosis method are studied, and the automatic P-phase-onset-time-picking model based on noise reduction and multiple detection indexes is established. Through the effect analysis of microseismic signals collected by microseismic monitoring system of coral Tungsten Mine in Guangxi, automatic P-phase onset time picking is realized, the reliability of the P-phase-onset-time-picking method proposed in this paper based on noise reduction and multiple detection indexes is verified. The picking accuracy can still be guaranteed under the severe signal interference of background noise, power frequency interference and manual activity in the underground mine, which is of great significance to the data processing and analysis of microseismic monitoring.

Experimental Study on Calibration of Amplitude-Frequency Measurement Deviation for Microseismic Sensors in Coal Mines.

Microseismic monitoring systems (MMS) have become increasingly crucial in detecting tremors in coal mining. Microseismic sensors (MS), integral components of MMS, profoundly influence positioning accuracy and energy calculations. Hence, calibrating these sensors holds immense importance. To bridge the research gap in MS calibration, this study conducted a systematic investigation. The main conclusions are as follows: based on calibration tests on 102 old MS using the CS18VLF vibration table, it became evident that certain long-used MS in coal mines exhibited significant deviations in frequency and amplitude measurements, indicating sensor failure. Three important calibration indexes, frequency deviation, amplitude deviation, and amplitude linearity are proposed to assess the performance of MS. By comparing the index of old and new MS, critical threshold values were established to evaluate sensor effectiveness. A well-functioning MS exhibits an absolute frequency deviation below 5%, an absolute amplitude deviation within 55%, and amplitude linearity surpassing 0.95. In normal operations, the frequency deviation of MS is significantly smaller than the amplitude deviation. Simplified waveform analysis has unveiled a linear connection between amplitude deviation and localization results. An analysis of the Gutenberg-Richter microseismic energy calculation formula found that the microseismic energy calculation is influenced by both the localization result and amplitude deviation, making it challenging to pinpoint the exact impact of amplitude deviation on microseismic energy. Reliable MS, as well as a robust MS, serve as the fundamental cornerstone for acquiring dependable microseismic data and are essential prerequisites for subsequent microseismic data mining. The insights and findings presented here provide valuable guidance for future MS calibration endeavors and ultimately can guarantee the dependability of microseismic data.

Microseismic event waveform classification using CNN-based transfer learning models

The efficient processing of large amounts of data collected by the microseismic monitoring system (MMS), especially the rapid identification of microseismic events in explosions and noise, is essential for mine disaster prevention. Currently, this work is primarily performed by skilled technicians, which results in severe workloads and inefficiency. In this paper, CNN-based transfer learning combined with computer vision technology was used to achieve automatic recognition and classification of multi-channel microseismic signal waveforms. First, data collected by MMS was generated into 6-channel original waveforms based on events. After that, sample data sets of microseismic events, blasts, drillings, and noises were established through manual identification. These datasets were split into training sets and test sets according to a certain proportion, and transfer learning was performed on AlexNet, GoogLeNet, and ResNet50 pre-training network models, respectively. After training and tuning, optimal models were retained and compared with support vector machine classification. Results show that transfer learning models perform well on different test sets. Overall, GoogLeNet performed best, with a recognition accuracy of 99.8%. Finally, the possible effects of the number of training sets and the imbalance of different types of sample data on the accuracy and effectiveness of classification models were discussed.

The construction of mine water recycling performance evaluation index system under the Internet of Things environment

The utilization rate of water resources of mines in China is still relatively low. The evaluation of mine water recycling has practical guiding significance for the planning, positioning, development, and construction of groundwater in today’s society. This article constructs an evaluation system for mine water recycling based on the key performance index (KPI) via the Internet of Things and big data platforms. This system evaluates the recycling status of mine water. First, the micro-seismic monitoring system and the hydrological dynamic detection system are deployed in work. The installation and debugging methods are compared to meet the monitoring requirements. Second, the filtered clear water is used for equipment cooling and firefighting dust removal at the mining face through the constant pressure supply pump. The excess clear water is discharged to the surface. Finally, 16 indicators are screened from four dimensions to construct a key KPI mine water evaluation system for evaluation and optimization. The results demonstrate that the first mine water monitoring system runs well and is fully functional, achieving the expected goal. The utilization rate evaluation score has increased yearly, from 3.05 points in 2016 to 3.39 points in 2020. However, the per capita utilization rate score still needs improvement. It is essential to improve the rationality of development and utilization.

Characterizing Rockbursts and Analysis on Hilbert-Huang Transform Spectrum of Microseismic Events, Shuangjiangkou Hydropower Station, Based on Microseismic Monitoring

The Shuangjiangkou hydropower station in China has complex geological conditions with high in situ stress. During the tunnel excavation, rockbursts occurred frequently, which seriously affected construction progress. Microseismic (MS) monitoring technology was used to explore rock MS activities to predict rockbursts. The MS monitoring system can capture a large number of MS signals. Based on Hilbert–Huang transform (HHT) instantaneous frequency analysis technology, using MATLAB software (R2022a) to write a program to convert the MS waveform, the frequency and energy characteristics of MS signals at a certain time can be obtained. By analyzing the frequency and energy characteristics of every event, the microseism active areas can be determined, and then rockbursts can be predicted scientifically. This paper selected two different construction sites, which were the main powerhouse and the access tunnel in the main powerhouse, as the research background. Introducing HHT instantaneous time–frequency analysis technology conducted MS event dynamic analysis and predicted rockbursts. The HHT spectrum scientifically and comprehensively displayed MS signal frequency characteristics at a certain time and reflected the change laws of signal instantaneous energy and local abrupt change information. The results indicated that some parameter anomalies in the event spectrum can predict rockbursts. For complex tunnel construction conditions, the HHT time–frequency analysis technology can realize a new idea of using a single-channel signal to predict rockbursts, which was very meaningful.

CNN-Transformer for Microseismic Signal Classification

The microseismic signals of coal and rock fractures collected by underground sensors contain masses of blasting vibration signals generated by coal mine blasting, and the waveforms of the two signals are highly similar. In order to identify the true microseismic signals with a microseismic monitoring system quickly and accurately, this paper proposes a lightweight network model that combines a convolutional neural network (CNN) and transformer, named CCViT. Of these, the CNN is used to extract shallow features locally, and the transformer is used to extract deep features globally. Moreover, a modified channel attention module provides important channel information for the model and suppresses useless information. The experimental results on the dataset used in this paper show that the proposed CCViT model has significant advantages for floating point operations (FLOPs), parameter quantity, and accuracy compared to many advanced network models.

Investigation on Mining-Induced Floor Water Inrush from Column and Its Control Based on Microseismic Monitoring

Water inrush is the biggest threat for safe mining in the Ruifeng coalmine, located in North China. In the study mining area, the floor water inrush is mainly caused by mining activities and collapse column. In this article, the mechanical criteria of floor water inrush are obtained based on cusp catastrophe theory, which is used to assess floor water inrush risk in the Ruifeng coalmine. Theoretical analysis shows that floor water inrush is very likely to occur during coal mining without the influence of geological structures. Additionally, FLAC3D was used to simulate the damage of floor strata during the mining face advances. Numerical results show that the water inrush channel occurs in front of the mining face due to the influence of stress concentration. Therefore, a microseismic monitoring system was applied to monitor the formation of water inrush pathway. Field monitoring results show that two water inrush pathways were accurately predicted and positioned. Based on the microseismic monitoring results, target grouting was adopted to prevent water inrush. This study provides significant guidance for the prevention of floor water inrush.

Distribution Law of Mine Ground Pressure via a Microseismic Sensor System

The particularity of the occurrence conditions of the ore body in Xianglushan Tungsten Mine determines the mining form of the ore body and the particularity of the ground pressure distribution after mining. A large number of mined-out areas, supporting pillars, and natural and human factors have formed a comprehensive disaster environment. This can lead to frequent disasters, great harm, serious economic losses, and the necessity of severe environmental protection operations in the mine. This study aims to establish a microseismic monitoring system according to the actual needs of the site and to reveal the law of ground pressure manifestation by analyzing the distribution characteristics of microseismic events; to analyze the occurrence stability of the goaf; further verify it laterally; and finally, demonstrate the feasibility and effectiveness of the microseismic monitoring sensor system. In view of the current ground pressure problem in Xiangxuoshan tungsten mine, the stress change characteristics during dynamic mining and filling were obtained through comparative analysis of different perspectives such as surface change, energy release, and mining loudness, and key areas were identified to improve the reliability of underground ground pressure monitoring. The results show that the process of deposit destabilization caused by ore body mining can be further analyzed by microseismic monitoring, and the combination of surface settlement, mining intensity, and energy release can verify the accuracy of stress distribution and ground pressure transfer. In turn, the general reliability of underground ground pressure hazard warning is empirically improved.

Analysis of Coal Floor Fault Activation Inducing Water Inrush Using Microseismic Monitoring—A Case Study in Zhaogu No. 1 Coal Mine of Henan Province, China

Previously conducted studies have established that mining activities can activate faults, which will cause floor water inrush disasters and cause loss of personnel and property. In order to reduce the possibility of water inrush disasters in mining, it is particularly important to study the dynamic characteristics and rules of floor fault activation under the influence of mining. In this work, firstly, a microseismic monitoring system was established in the working face to analyze the changes of microseismic indexes before and after grouting. It was found that grouting can enhance the strength of a rock mass and play a role in sealing the water channel. Secondly, the quadratic kernel function of microseismic event energy was established. It was found that the accumulation degree of microseismic events and the region of high energy kernel density increased with the decrease of the distance between the working face and the left boundary of the “analysis region”. Combined with a microseismic event index and water inflow, the activation process of the floor fault was divided into five stages. Finally, the plastic failure region of surrounding rock under different excavation steps was analyzed by numerical simulation, and the characteristics of fault activation were further explained. A method of taking measures to prevent water inrush in the “sign stage of fault activation” was proposed.

Study on Microseismic Activity Characteristics of Composite Coal Pillar in 21201 Coal Face of Hulusu Mine

Hulusu coal mine adopts “121 method” for back mining, and the coal pillar between adjacent workings is 30m. 21102 working have been mined for more than 3 years, leaving the auxiliary return airway has not been repaired for a long time which results in the serious deformation. If employs the adjacent 21201 workings to mine, the cost of reusing the 21102 auxiliary return airway is high. Therefore, the mine dug a new return airway 10m away from the mine, and forming a 45m composite coal column with double coal pillars and double return airways. Based on the ARAMIS M\E microseismic monitoring system, the spatial distribution characteristics of microseismic accidents near the composite coal pillar of 21201 coal face are studied, and explore the quantitative relationship among the retrieval rate of 21201 coal face, the frequency, and energy of microseismic accidents, which provided a theoretical basis and technical support for determining the scientific and reasonable retrieval rate of 21201 coal face.

Investigation of the Microseismic Response Characteristics of a Bottom Structure’s Ground Pressure Activity under the Influence of Faults

To further understand the changing pattern of the bottom structure’s ground pressure activity under the influence of faults, predicting the potential occurrence of geological hazards and rock blast problems to reduce the loss of resources is important. A new microseismic monitoring system was established based on the original Pulang copper mine microseismic monitoring system. This paper analyzed the change law of the microseismic events on the fault in the first mining area of the Pulang copper mine, calculated the cumulative apparent volume and energy index changes of the microseismic events near the fault base, and quantitatively analyzed the microseismic event anomalies under the influence of the fault. The results show that rupture of the rock makes the cumulative apparent volume and energy index change significantly, while the timeliness of both makes the cumulative apparent volume predictive of the occurrence of rock fracture and rockburst, and the number of microseismic events corresponds to the intensity of the fault activation, which plays a predictive and guiding role in the subsequent study of fault activation, stability monitoring, and safe production in the mine area of Pulang copper mine.

A Study on Classification Method of Mine Vibration Based on Microseismic Monitoring Cloud Service Platform

With the gradual deepening of mining depth, sudden ground pressure disasters such as rock burst and collapse caused by deep high stress and high rock pressure are major hidden dangers affecting mine safety production. Microseismic monitoring technology has been widely applied in the field of mine ground pressure disaster warning. The existing microseismic monitoring system has some problems, such as inaccurate automatic recognition and classification of waveform signals, low quality and low efficiency of manual processing. In this paper, the automatic classification of vibration signals in the process of mining is studied, and the automatic classification results are uploaded to the cloud service platform in real time, which solves the technical bottleneck of the existing microseismic monitoring system. Meanwhile, the real-time monitoring of mine ground pressure safety is guaranteed based on the cloud service platform of microseismic monitoring.

Multi-Index Geophysical Monitoring and Early Warning for Rockburst in Coalmine: A Case Study.

Rockburst is a major disaster in deep mining, restricting the safety and the production efficiency of the Laohutai Coal Mine in Fushun, Liaoning Province. To predict and prevent coalmine rockbursts, a comprehensive method based on multi-instrument monitoring is proposed by using a YDD16 acoustic-electromagnetic monitor and microseismic monitoring system, including microseismic (MS) monitoring, electromagnetic radiation (EMR) monitoring, and acoustic emission (AE) monitoring. Field investigation shows that MS, AE, and EMR signals have abnormal precursors before rockbursts in a new working face. Based on the fluctuation theory and D-S evidence theory, the multi-index geophysical monitoring and early warning technology for rockburst disasters in the Laohutai Coal Mine are established. The method has been applied to the prediction of rockbursts in the Laohutai Coal Mine. The application shows that the acoustic-electromagnetic synchronous monitoring and early warning technology can accurately identify the potential rockburst risk and trigger an early warning, which is more reliable than a single method. The case study of the Laohutai rockburst shows that the joint early warning method of multi-instrument comprehensive monitoring can predict the possibility of rockbursts.

Study of the Evolution Characteristics of Microseismic Events during the Excavation of Underground Caverns under High Geostress

A microseismic (MS) monitoring system was established, and numerical modeling was performed using Fast Lagrangian Analysis of Continua in 3 Dimensions (FLAC3D) to examine the evolution characteristics of MS events during the excavation of underground caverns under high geostress. Specifically, the spatial and temporal damage characteristics of the rock mass, the dynamic relationship between the evolution of MS events, the site construction conditions, and the geological structures under high geostress were also analyzed. In addition, a three-dimensional numerical model of underground caverns was built to demonstrate the deformation characteristics of the rock mass. As a result, the characteristics of a large number of MS events, multiple concentration zones of MS events, and long periods of stress adjustment were discovered in underground caverns under high geostress. It was found that the primary cause of MS events was site blasting construction. In particular, the distribution of the MS events was strongly correlated with the location of the site blasting construction, and the frequency of the MS events was positively correlated with it. The structural plane is a discontinuous plane with very low or no tensile strength, and its presence also increased the number of MS events and raised the possibility of the surrounding rock becoming unstable. Moreover, the MS monitoring data agreed with the numerical modeling results, which can be useful in estimating damage to underground caverns under high geostress and predicting disasters.

Microseismic Dynamic Response and Multi-Source Warning during Rockburst Monitoring Based on Weight Decision Analysis

To prevent rockburst disasters and improve the accuracy of warnings for rockburst, based on the microseismic data of the 1366 working face of Hengda Coal Mine collected by the microseismic monitoring system, Fourier transform, wavelet packet transform, and Hilbert-Huang transform analysis methods are used for time-frequency domain joint analysis. The time-frequency differences of the main frequency, amplitude, frequency band percentage, and instantaneous energy of the high-energy microseismic event and the events before high-energy microseismic event are obtained. The analysis shows that the high-energy event has obvious low frequency characteristics, and when the high-energy event occurs, the instantaneous energy shows an obvious "inverted V" trend. At the same time, it is found that the acoustoelectric indexes show a trend of "rising" or "inverted V" when the high-energy event occurs. On this basis, the unascertained measure comprehensive evaluation model of rock burst hazard is established by analytic hierarchy process (AHP). Based on the analysis of microseismic data and the acoustoelectric index of the 1366 working face in Hengda coal mine, it is of great significance to determine the warning indicators for rockburst, improve the accuracy of uncertainty quantitative analysis for rockburst, and improve the discrimination accuracy of rockburst risk.

Microseismic Precursors of Coal Mine Water Inrush Characterized by Different Waveforms Manifest as Dry to Wet Fracturing.

Microseismic monitoring systems have been widely installed to monitor potential water hazards in limestone of the coal floor. The temporal and spatial distribution of rock fracture-induced microseismic events can be used as early warning indicators of potential water inrush from the coal floor. We established a microseismic monitoring system in the working face of Wangjialing coal mine. Besides traditional fluid-independent rock fracture-induced microseismic waveforms, fluid-dependent hybrid-frequency microseismic waveforms also play important roles in determining the microseismic precursors of water inrush. Hybrid-frequency microseismic waveforms have a sharp P wave and no obvious S wave phase. We infer that the first high-frequency signal is caused by the brittleness of the rock in the floor under the influence of the water pressure. The second low-frequency signal is caused by the water oscillations in the fractures. These hybrid-frequency waveforms represent the development of fracturing. In addition, the lifting height of the complete aquiclude above the confined water is very limited, and the water inrush from the floor is often closely related to these hidden faults. Therefore, the activation signal of hidden faults in the working face of coal mining can be monitored to effectively warn about the water inrush from the coal seam floor caused by faults. By analyzing different microseismic events, the monitoring and early warning of water disaster in the coal mine floor can be improved. This will help in taking measures in advance within the mine to ensure personnel safety and to reduce property losses.