Mining-induced Seismicity Research Articles

Determination of the Advanced Mining Influence Range in Coal Mines Based on the Statistical Analysis of Mining-Induced Seismicity

Determining the advanced mining influence range of an underground working face is crucial for preventing dynamic disasters, such as coal bursts and gas outbursts. In this study, the occurrence of advanced seismicity before the working face as well as its correlation with the acoustic emission (AE) activity of coal and rocks under axial loading was analyzed. Based on the results, a novel statistical method to determine the advanced mining influence range based on advanced seismicity data was proposed and then validated with a case study. The results show that advanced seismicity is caused by the combined effects of static and dynamic stresses at the working face. This seismicity can be used to assess the mining influence degree of the working face on the advanced coal and rock mass, and determine the advanced mining influence range. Using the novel statistical method, the normalized curves for the total number and total energy of the advanced mining-induced seismicity can be plotted. Then, the advanced mining influence range can be determined using thresholds. The thresholds can be established based on the AE activities observed in coal and rock samples under axial static loading. In the case study in this research, the thresholds for the total seismic number and total seismic energy are 0.076 and 0.052, respectively. The corresponding advanced mining influence ranges are 275 m and 245 m, respectively. Field monitoring confirms an advanced mining influence range of 255 m, which validates the results obtained using the novel statistical method.

The role of mining-induced seismicity amplitude and frequency in gob-side roadway rib spalling

The role of mining-induced seismicity amplitude and frequency in gob-side roadway rib spalling

Geomechanical Analysis of the Main Roof Deformation in Room-and-Pillar Ore Mining Systems in Relation to Real Induced Seismicity

Rockbursts represent one of the most serious and severe natural hazards emerging in underground copper mines within the Legnica–Glogow Copper District (LGCD) in Poland. The contributing factor determining the scale of this event is mining-induced seismicity of the rock strata. Extensive expertise of the copper mining practitioners clearly indicates that high-energy tremors are the consequence of tectonic disturbances or can be attributed to stress/strain behaviour within the burst-prone roof strata. Apparently, seismic activity is a triggering factor; hence, attempts are made by mine operators to mitigate and control that risk. Underlying the effective rockburst control strategy is a reliable seismicity forecast, taking into account the causes of the registered phenomena. The paper summarises the geomechanics analyses aimed to verify the actual seismic and rockburst hazard levels in one of the panels within the copper mine Rudna (LGCD). Two traverses were designated at the face range and comparative analyses were conducted to establish correlations between the locations of epicentres of registered tremors and anomaly zones obtained via analytical modelling of changes in stress/strain behaviours within the rock strata. The main objective of this study was to evaluate the likelihood of activating carbonate/anhydrite layers within the main roof over the excavation being mined, with an aim to verify the potential causes and conditions which might have triggered the registered high-energy events. Special attention is given to two seismic events giving rise to rockbursts in mine workings. Results seem to confirm the adequacy and effectiveness of solutions provided by mechanics of deformable bodies in the context of forecasting the scale and risk of dynamic phenomena and selecting the appropriate mitigation and control measures in copper mines employing the room-and-pillar mining system.

Estimation of the resonance frequency of rotational and translational signals evoked by mining-induced seismicity

Estimation of the resonance frequency of rotational and translational signals evoked by mining-induced seismicity

Influence of Water Saturation of the Medium on the Productivity of Mining-Induced Seismicity: A Case Study of the Khibiny Massif

Influence of Water Saturation of the Medium on the Productivity of Mining-Induced Seismicity: A Case Study of the Khibiny Massif

Identification of the mining accidents by a two-step clustering method for the mining-induced seismicity

Clustering methods aim to categorize data or samples into distinct groups based on their similarity. When applying clustering methods to earthquake events, it is crucial to establish a metric for quantifying the similarity between these events. Directly applying this clustering method to a catalog of mining-induced seismicity may lead to clustering earthquake events induced by different mining activities or accidents into the same group. To address this issue, a two-step clustering method has been proposed and applied for analyzing a catalog of mining-induced seismicity. The first step involves spatial distance-based clustering of seismic events, while the second step focuses on moment tensor analysis-based clustering of these events. The results obtained from the MT-based clustering method are visualized using Hudson Graphs, and box plots serve as an evaluation tool for assessing the quality of MT clustering. Most box plots demonstrate desirable quality in terms of MT cluster results, indicating successful outcomes. By the proposed two-step clustering method combined with actual mining activities, the potential accident locations and categories can be hypothesized while valuable recommendations provided for mining operations.

Structural performance of buildings affected by mining activities: a review

Subsidence and earthquakes induced by mining activities often cause significant damage to nearby surface structures. These damages may pose risks to occupant’s safety and deteriorate structural performance under serviceability and ultimate limit states, potentially endangering lives. As many structures may lack design considerations to withstand the additional loads and displacements imposed by mining activities, accurate prediction of their structural performance is imperative. This paper aims to present a comprehensive review of analytical methods and standard guidelines for assessing the performance of buildings near mining areas, particularly in response to subsidence and mining-induced seismicity. The paper presents the essential framework required for accurately assessing the performance of this building group. Based on the results, a brief methodology is presented to aid engineers in assessing the performance of structures near mines.

Impact of mining-induced seismicity on land subsidence occurrence

Mining-induced seismicity can damage buildings and surface infrastructure and cause fatalities. It is a growing concern, owing to the sudden occurrence of seismic events, lack of effective prediction capabilities, and associated consequences. In this study, we analyzed 13 high-energy mining-induced earthquakes from 2016 to 2020 in Poland's Legnica-Glogow Copper District (LGCD), based on data recorded by the Induced Seismicity-European Plate Observing System (IS-EPOS). We used European Space Agency (ESA) Sentinel-1 Copernicus satellite radar images, to study the co-seismic subsidence in the region. Additionally, we employed volumetric point source approximation and a Bayesian inverse modeling scheme to estimate the location and strength of subsurface collapses from the land subsidence data. Finally, we correlated the geological constraints with the land subsidence and earthquake source parameters. The interferometric synthetic aperture radar (InSAR) displacement maps portrayed maximum line-of-sight (LOS) displacements of −144 mm and − 124 mm in ascending and descending images, respectively, with maximum land subsidence reaching −142 mm. Notably, only a few earthquakes with large magnitudes caused land subsidence. There was a significant correlation between earthquake magnitude and land subsidence; the greater the thickness of the loose Quaternary strata, the smaller the land subsidence. According to the inversion results, the focal depths of the collapses associated with the earthquakes were 437–669 m. However, the estimated collapse depths were situated above the mining exploitation fields, within the rigid Triassic rock layers. The associated collapse energy was 1.62 times greater than the seismic energy, indicating aseismic deformation in the field. Additionally, we observed spatial discrepancy between the location of the earthquake epicenters and the maximum land subsidence. Thus, our study can improve the current understanding of the impact of mining-induced seismicity, the occurrence of associated land subsidence, and seismic mechanisms in mining areas.

Study on deep learning methods for coal burst risk prediction based on mining-induced seismicity quantification

The assessment of Coal burst risk (CBR) is the premise of bump disaster prevention and control. It is the implementation criterion to guide various rock burst prevention and control measures. The existing static prediction and evaluation methods for CBR cannot be effectively combined with the results of underground dynamic monitoring. This study proposed a mining-induced seismicity information quantification method based on the fractal theory. Deep learning methods were used to construct a deep learning framework of coal burst risk (DLFR) based on the fractal dimension of microseismic information. Gray correlation analysis (GRA), information gain ratio (IGR), and Pearson correlation coefficient are used to screen and compare factors. Statistical evaluation indicators such as macro-F1, accuracy rate, and fitness curve were used to evaluate model performance. Taking the Gaojiapu coal mine as a case study, the performance of deep learning models such as BP Neural Network (BP), Support Vector Machine (SVM) and its optimized model based on particle swarm optimization (PSO) algorithm under this framework is discussed. The research results' reliability and validity are verified by comparing the predicted results with the actual results. The research results show that the prediction results of CBR in DLFR are consistent with the actual results, and the model is reliable and effective. The mining-induced seismicity quantification can solve the problem of insufficient training samples for the CBR. With this, different pressure relief measures can be formulated based on the results of the CBR predictions to achieve "graded" precise prevention and control.

Physically motivated moment-tensor decomposition for mining-induced seismicity

SUMMARY Compared to existing schemes, the decomposition of moment tensors for mining-induced seismic events into closing-crack and double-couple components has the advantage that each can be interpreted in terms of a physical source process (excavation convergence and slip/shear, respectively). Obviously, not every moment tensor permits such a decomposition, and we translate existing bounds on those that do to the Hudson source-type plot. For moment tensors falling within these bounds, it has previously been noted that there will be a infinite set of possible decompositions in general. We derive an implicit equation defining this set and suggest physically motivated criteria that can be used to select a single decomposition from it. Furthermore, for moment tensors falling outside the source-type bounds, we present a simple geometric scheme for determining the closest moment tensor within them (which can then be decomposed). To demonstrate the methods developed in this paper, we apply them to two catalogues of mining-induced seismicity.

Prediction of mining-induced seismicity and damage assessment of induced surface buildings in thick and hard key stratum working face: a case study of Liuhuanggou coal mine in China

Thick and hard key stratum working faces are characterized by frequent mine tremors and significant ground tremors during mining which seriously threaten the safety production of the mine. With working face (4-5) 06 of Xinjiang Liuhuanggou Coal Mine as the engineering background, using field investigation, microseismic monitoring, and theoretical analysis, a mining-induced seismicity prediction method and damage assessment of surface buildings for thick and hard key stratum working faces is proposed, which is based on the evolution characteristics of overlying strata spatial structure and the motion state of the key stratum. The results of the study are as follows: 1) The movement law of overlying strata is the basis of mining-induced seismicity prediction for working faces. The magnitude of the risk of mining-induced seismicity occurrence is mainly related to the boundary conditions of the working face, the thickness of the key stratum, the distance from the coal seam to the key stratum, the height of the overlying strata spatial structure, and the fracture step of the key stratum. 2) The mining-induced seismicity energy contains the original accumulation elastic energy of the key stratum, the transfer elastic energy of low rock strata, and the accumulation elastic energy of gravity work. Based on this, a mechanical model of surface building damage induced by the release of mining-induced seismicity energy was established. A ground vibration damage boundary and vibration induction boundary under the action of strong mining-induced seismicity were proposed, and the service life of buildings when they reach the critical damage value under the action of frequent mining-induced seismicity was obtained. 3) The temporal and spatial distribution law of mining-induced seismicity activities in thick and hard key stratum working faces was revealed. According to the results of micro-seismic monitoring, the “zonality” characteristics of the time series and the “transition” law of spatial distribution of mining-induced seismicity verified the reliability of the mining-induced seismicity prediction method. The research results provide a theoretical basis for predicting mining-induced seismicity and assessing the risk of induced disasters during the mining process of thick and hard key stratum working faces, and can provide technical support for mining-induced seismicity prevention and control and safety production in mines with similar conditions.

Geomechanical and tectonophysical conditions of mining-induced seismicity in the Upper Silesian Coal Basin in Poland: a case study

Geomechanical and tectonophysical conditions of mining-induced seismicity in the Upper Silesian Coal Basin in Poland: a case study

Moment Tensor Inversion and Coseismic Stress Characteristics of Mining-Induced Seismicity in Coal Pillar Area

Moment Tensor Inversion and Coseismic Stress Characteristics of Mining-Induced Seismicity in Coal Pillar Area

Mechanism of the coal bursts in the working face during mining of steeply inclined and extra thick coal seam

Coal bursts caused by mining-induced seismicity occur in the working face in steeply inclined and extra thick coal seams (SIETCSs). This article presents a case study in SIETCS through discrete element simulation as well as field investigation. The evolution of the coal burst was studied from the perspective of stress distribution, crack propagation and coal fragment ejection. The results showed that dynamic failure mainly occurred in the coal near the roof. The deep bottom coal and the top coal near the roof are under high static stress due to the clamping effect of the roof and floor and the rotation of the deep roof. The coal burst in the working face was triggered by mining-induced seismicity. The coal burst occurred when the sum of the static stress and the dynamic stress caused by the mining-induced seismicity exceeds the sum of the ultimate strength of the coal and the support strength, which was called the ‘clamping-rotation-dynamic loads’ mechanism. During the coal burst, the cracks developed rapidly into the deep bottom coal and the top coal on the roof side. The results can serve as an important reference for the coal burst failure mechanism in the working face in SIETCSs.

Failure mechanism and control of the coal bursts triggered by mining-induced seismicity: a case study

Failure mechanism and control of the coal bursts triggered by mining-induced seismicity: a case study

Comprehensive use of the Gutenberg–Richter law and geotomography for improving seismic hazard evaluation in hard coal mines

Mining-induced seismicity occurs in numerous underground mines worldwide where extraction is conducted at great depths or in areas characterised by complex tectonic structure. It is accompanied by rock bursts, which result in the loss of working functionality and the possibility of accidents among personnel. The issue of a constant and reliable seismic hazard evaluation is of key significance for both the safety of miners and the stability of production. Research on its improvement is directed at developing new interpretive solutions and methods. The nature of the presented solution is the complex interpretation of seismological data that characterise rock mass seismicity and of underground measurement results in the form of a map presenting the longitudinal wave propagation velocity distribution in the rock surrounding the mined coal seam. The solution was tested in hard coal mines located in the Upper Silesian Coal Basin. The mines are equipped with a modern seismological system enabling the constant monitoring of seismicity together with hazard level evaluation as well as with seismic apparatus for conducting periodic measurements of the seismic wave propagation velocity before the mining face. Comprehensive seismic hazard evaluation criteria were determined based on the obtained results, involving the anomaly of the Gutenberg–Richter law “b” value and the maximum longitudinal seismic wave propagation velocity in the roof rock. The obtained experience and the result validation of this new comprehensive hazard evaluation method confirm its practical usefulness and indicate the directions of improvement for the solution in question.

In-situ stress field inversion and its impact on mining-induced seismicity

The magnitude and direction of the in-situ stress field significantly influence the Geodynamic disaster. Taking the Gaojiapu Coal Mine in the northwest Binchang mining area as the study area, the distribution law of the in-situ stress field and its relationship with microseismic events were analyzed and discussed through field geological investigation, in-situ measurement, and numerical simulation. The results show that: (1) The Maximum horizontal principal stress (MaxHPS) is mainly concentrated in the turning end of the fold, the axis of the syncline, the undulation end of the anticline, the footwall of the fault, and the two ends of the fault. (2) The MaxHPS in the footwall area of the fault is greater than that in the hanging wall area. (3) The MaxHPS at the axial part of the syncline is greater than that at the wing part, and the MaxHPS at the wing part is greater than that at the anticline. (4) In areas with high MaxHPS and Lateral pressure coefficient (LPC), the frequency of high-energy microseismic events is high. (5) The 105J high-energy microseismic events more easily occur in areas with MaxHPS greater than 38 MPa and LPC greater than 1.50.

Effect of mining and geology on mining-induced seismicity – A case study

Mining-induced seismicity is a commonly occurring phenomenon in underground mines. This poses a greater challenge to the safety of the mining operation. This paper presents a case study of the Young-Davidson mine in northern Ontario, Canada, where seismic events of magnitude Mn 2.0+ have been observed at mining depths of 600 to 800 m below the surface. The occurrence of large seismic events at such shallow depths is the key issue of this study. A comprehensive study of the microseismic database has been conducted to discern the root causes for the unusually strong seismic activities recorded at shallow depths. The effects of mining activities in the vicinity of two dykes intersecting the orebody on the seismic response are investigated. Variation of the b-value derived from the magnitude-frequency distribution is examined, and moment tensor inversion for three large seismic events is carried out to determine the source mechanisms. It is shown from this investigation that the influence of the sill pillar is more critical, leading to high mining-induced stress and the occurrence of large events. While the findings from this research are specific to this case study, they could be used to shed light on the causes of induced seismicity at other mines with similar conditions.

Quantitative assessment of the spatio-temporal correlations of seismic events induced by longwall coal mining

Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal (ST) correlation of mining-induced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mining-induced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function (ACF), semivariogram and Moran's I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.

Underground Rock Mass Behavior Prior to the Occurrence of Mining Induced Seismic Events

The variations of seismic velocity prior to the occurrence of major seismic events are an indicator of the rock mass performance subjected to mining-induced stress. There have been no prior field-scale studies to examine stress change within the rockmass volume immediately prior to potentially damaging mining-induced seismicity. Monitoring stress change is critical for mine stability and operation safety and eventually improves production by optimizing mine designs and mining practices. In this study, five major seismic events that occurred in a narrow-vein mine were used as case studies in order to investigate any significant changes in P-wave velocity distribution, on a daily basis, within a week of seismic events with Mw > 1; if observed, such changes could provide a warning to mine engineers and workers. It was observed there was no consistent significant velocity change of more than 1% within 200 m of the hypocenters within 6 days prior to the events. Additionally, the influence of blasting in the week of the occurrence of events was investigated however no recognizable trend was observed between blasting and changes in the seismic velocity distribution within the rock mass on the day of a blast or the following day.