Excavation-induced microseismicity and rockburst occurrence in deep underground projects provide invaluable information that can be used to warn rockburst occurrence,facilitate rockburst mitigation procedures,and anal...Excavation-induced microseismicity and rockburst occurrence in deep underground projects provide invaluable information that can be used to warn rockburst occurrence,facilitate rockburst mitigation procedures,and analyze the mechanisms responsible for their occurrence.Based on the deep parallel tunnels with the maximum depth of 1890 m created as part of the Neelum–Jhelum hydropower project in Pakistan,similarities and differences on excavation-induced microseismicity and rockburst occurrence between parallel tunnels with soft and hard alternant strata are studied.Results show that a large number of microseismic(MS)events occurred in each of the parallel tunnels during excavation.Rockbursts occurred most frequently in certain local sections of the two tunnels.Significant differences are found in the excavation-induced microseismicity(spatial distribution and number of MS events,distribution of MS energy,and pattern of microseismicity variation)and rockbursts characteristics(the number and the spatial distribution)between the parallel tunnels.Attempting to predict the microseismicity and rockburst intensities likely to be encountered in subsequent tunnel based on the activity encountered when the parallel tunnel was previously excavated will not be an easy or accurate procedure in deep tunnel projects involving complex lithological conditions.展开更多
This paper selects some representative regions to obtain their G-R relation curves according to their seismicity characteristics,by using ML≥2.0 microseismicity data(1970~1993)in North China.The annual occurrence rat...This paper selects some representative regions to obtain their G-R relation curves according to their seismicity characteristics,by using ML≥2.0 microseismicity data(1970~1993)in North China.The annual occurrence rate of events of each magnitude can be inferred from the G-R relation.At the same tune,the actual annual occurrence rate of earthquakes of higher magnitudes can be calculated from historical earthquakes(1300-1993)recorded in the same region.It seems that both results are almost the same.Therefore,the rate of events of higher magnitudes can be obtained by using microseismicity data when the proper region is selected.However,two points should be noticed:(1)The method can only give the annual occurrence rate in a seismicity system and estimate the whole situation of the system.(2)When there is a very large earthquake in and near the period in which the microseismicity data are applied,the actual occurrence rate of the system,including this larger earthquake,cannot be obtained by this method.展开更多
Hydraulic fracturing （HF） technique has been extensively used for the exploitation of unconventional oiland gas reservoirs. HF enhances the connectivity of less permeable oil and gas-bearing rock formationsby fluid ...Hydraulic fracturing （HF） technique has been extensively used for the exploitation of unconventional oiland gas reservoirs. HF enhances the connectivity of less permeable oil and gas-bearing rock formationsby fluid injection, which creates an interconnected fracture network and increases the hydrocarbonproduction. Meanwhile, microseismic （MS） monitoring is one of the most effective approaches to evaluatesuch stimulation process. In this paper, the combined finite-discrete element method （FDEM） isadopted to numerically simulate HF and associated MS. Several post-processing tools, includingfrequency-magnitude distribution （b-value）, fractal dimension （D-value）, and seismic events clustering,are utilized to interpret numerical results. A non-parametric clustering algorithm designed specificallyfor FDEM is used to reduce the mesh dependency and extract more realistic seismic information.Simulation results indicated that at the local scale, the HF process tends to propagate following the rockmass discontinuities; while at the reservoir scale, it tends to develop in the direction parallel to themaximum in-situ stress. 2014 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting byElsevier B.V. All rights reserved.展开更多
Petroleum reservoir operations such as oil and gas production, hydraulic fracturing, and water injection induce considerable stress changes that at some point result in rock failure and emanation of seismic energy. Su...Petroleum reservoir operations such as oil and gas production, hydraulic fracturing, and water injection induce considerable stress changes that at some point result in rock failure and emanation of seismic energy. Such seismic energy could be large enough to be felt in the neighborhood of the oil fields, therefore many issues are recently raised regarding its environmental impact. In this research we analyze the magnitudes of microseismicity induced by stimulation of unconventional reservoirs at various basins in the United States and Canada that monitored the microseismicity induced by hydraulic fracturing operations. In addition, the relationship between microseismic magnitude and both depth and injection parameters is examined to delineate the possible framework that controls the system. Generally, microseismicity of typical hydraulic fracturing and injection operations is relatively similar in the majority of basins under investigation and the overall associating seismic energy is not strong enough to be the important factor to jeopardize near surface groundwater resources. Furthermore, these events are less energetic compared to the moderately active tectonic zones through the world and usually do not extend over a long period at considerably deep parts. However, the huge volume of the treatment fluids and improper casing cementing operation seem to be primary sources for contaminating near surface water resources.展开更多
The volume of influence of excavation at the right bank slope of Dagangshan Hydropower Station, southwest China, is essentially determined from microseismic monitoring, numerical modeling and conventional measurements...The volume of influence of excavation at the right bank slope of Dagangshan Hydropower Station, southwest China, is essentially determined from microseismic monitoring, numerical modeling and conventional measurements as well as in situ observations. Microseismic monitoring is a new application technique for investigating microcrackings in rock slopes. A micro- seismic monitoring network has been systematically used to monitor rock masses unloading relaxation due to continuous exca- vation of rock slope and stress redistribution caused by dam impoundment later on, and to identify and delineate the potential slippage regions since May, 2010. An important database of seismic source locations is available. The analysis of microseismic events showed a particular tempo-spatial distribution. Seismic events predominantly occurred around the upstream slope of 1180 m elevation, especially focusing on the hanging wall of fault XL316-1. Such phenomenon was interpreted by numerical modeling using RFPA-SRM code （realistic failure process analysis-strength reduction method）. By comparing microseismic activity and results of numerical simulation with in site observation and conventional measurements results, a strong correlation can he obtained between seismic source locations and excavation-induced stress distribution in the working areas. The volume of influence of the rock slope is thus determined. Engineering practices show microseismic monitoring can accurately diagnose magnitude, intensity and associated tempo-spatial characteristics of tectonic activities such as faults and unloading zones. The integrated technique combining seismic monitoring with numerical modeling, as well as in site observation and conventional surveying, leads to a better understanding of the internal effect and relationship between microseismic activity and stress field in the right bank slope from different perspectives.展开更多
Rockbursts have become a significant hazard in underground mining,underscoring the need for a robust early warning model to ensure safety management.This study presents a novel approach for rockburst prediction,integr...Rockbursts have become a significant hazard in underground mining,underscoring the need for a robust early warning model to ensure safety management.This study presents a novel approach for rockburst prediction,integrating the Mann-Kendall trend test(MKT)and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards.The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts.The MKT is then applied to analyze the real-time trend of each index,with adherence to rockburst characterization laws serving as the warning criterion.By employing a confusion matrix,the warning effectiveness of each index is assessed,enabling index preference determination.Ultimately,the integrated rockburst hazard index Q is derived through data fusion.The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q,surpassing the performance of any individual index.Moreover,the model’s adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data,making it suitable for complex underground working environments.By providing an efficient and accurate basis for decision-making,the proposed model holds great potential for the prevention and control of rockbursts.It offers a valuable tool for enhancing safety measures in underground mining operations.展开更多
Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current...Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current arrival picking methods.Thus,a real-time arrival picking method of MS signals is constructed based on a convolutional-recurrent neural network(CRNN).This method fully utilizes the advantages of convolutional layers and gated recurrent units(GRU)in extracting short-and long-term features,in order to create a precise and lightweight arrival picking structure.Then,the synthetic signals with field noises are used to evaluate the hyperparameters of the CRNN model and obtain an optimal CRNN model.The actual operation on various devices indicates that compared with the U-Net method,the CRNN method achieves faster arrival picking with less performance consumption.An application of large underground caverns in the Yebatan hydropower station(YBT)project shows that compared with the short-term average/long-term average(STA/LTA),Akaike information criterion(AIC)and U-Net methods,the CRNN method has the highest accuracy within four sampling points,which is 87.44%for P-wave and 91.29%for S-wave,respectively.The sum of mean absolute errors(MAESUM)of the CRNN method is 4.22 sampling points,which is lower than that of the other methods.Among the four methods,the MS sources location calculated based on the CRNN method shows the best consistency with the actual failure,which occurs at the junction of the shaft and the second gallery.Thus,the proposed method can pick up P-and S-arrival accurately and rapidly,providing a reference for rock failure analysis and evaluation in engineering applications.展开更多
Microseismic source location is crucial for the early warning of rockburst risks.However,the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy.Intelligent techni...Microseismic source location is crucial for the early warning of rockburst risks.However,the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy.Intelligent techniques,such as the full convolutional neural network(FCNN),can capture spatial information but struggle with complex microseismic sequence.Combining the FCNN with the long shortterm memory(LSTM)network enables better time-series signal classification by integrating multiscale information and is therefore suitable for waveform location.The LSTM-FCNN model does not require extensive data preprocessing and it simplifies the microseismic source location through feature extraction.In this study,we utilized the LSTM-FCNN as a regression learning model to locate the seismic focus.Initially,the method of short-time-average/long-time-average(STA/LTA)arrival time picking was employed to augment spatiotemporal information.Subsequently,oversampling the on-site data was performed to address the issue of data imbalance,and finally,the performance of LSTM-FCNN was tested.Meanwhile,we compared the LSTM-FCNN model with previous deep-learning models.Our results demonstrated remarkable location capabilities with a mean absolute error(MAE)of only 7.16 m.The model can realize swift training and high accuracy,thereby significantly improving risk warning of rockbursts.展开更多
Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust l...Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust localization method that integrates kernel density estimation(KDE)with damping linear correction to enhance the precision of microseismic/acoustic emission(MS/AE)source positioning.Our approach systematically addresses abnormal arrival times through a three-step process:initial location by 4-arrival combinations,elimination of outliers based on three-dimensional KDE,and refinement using a linear correction with an adaptive damping factor.We validate our method through lead-breaking experiments,demonstrating over a 23%improvement in positioning accuracy with a maximum error of 9.12 mm(relative error of 15.80%)—outperforming 4 existing methods.Simulations under various system errors,outlier scales,and ratios substantiate our method’s superior performance.Field blasting experiments also confirm the practical applicability,with an average positioning error of 11.71 m(relative error of 7.59%),compared to 23.56,66.09,16.95,and 28.52 m for other methods.This research is significant as it enhances the robustness of MS/AE source localization when confronted with data anomalies.It also provides a practical solution for real-world engineering and safety monitoring applications.展开更多
Rock fracture mechanisms can be inferred from moment tensors(MT)inverted from microseismic events.However,MT can only be inverted for events whose waveforms are acquired across a network of sensors.This is limiting fo...Rock fracture mechanisms can be inferred from moment tensors(MT)inverted from microseismic events.However,MT can only be inverted for events whose waveforms are acquired across a network of sensors.This is limiting for underground mines where the microseismic stations often lack azimuthal coverage.Thus,there is a need for a method to invert fracture mechanisms using waveforms acquired by a sparse microseismic network.Here,we present a novel,multi-scale framework to classify whether a rock crack contracts or dilates based on a single waveform.The framework consists of a deep learning model that is initially trained on 2400000+manually labelled field-scale seismic and microseismic waveforms acquired across 692 stations.Transfer learning is then applied to fine-tune the model on 300000+MT-labelled labscale acoustic emission waveforms from 39 individual experiments instrumented with different sensor layouts,loading,and rock types in training.The optimal model achieves over 86%F-score on unseen waveforms at both the lab-and field-scale.This model outperforms existing empirical methods in classification of rock fracture mechanisms monitored by a sparse microseismic network.This facilitates rapid assessment of,and early warning against,various rock engineering hazard such as induced earthquakes and rock bursts.展开更多
Microseism,acoustic emission and electromagnetic radiation(M-A-E)data are usually used for predicting rockburst hazards.However,it is a great challenge to realize the prediction of M-A-E data.In this study,with the ai...Microseism,acoustic emission and electromagnetic radiation(M-A-E)data are usually used for predicting rockburst hazards.However,it is a great challenge to realize the prediction of M-A-E data.In this study,with the aid of a deep learning algorithm,a new method for the prediction of M-A-E data is proposed.In this method,an M-A-E data prediction model is built based on a variety of neural networks after analyzing numerous M-A-E data,and then the M-A-E data can be predicted.The predicted results are highly correlated with the real data collected in the field.Through field verification,the deep learning-based prediction method of M-A-E data provides quantitative prediction data for rockburst monitoring.展开更多
The Ms 6.4 earthquake occurred on May 21,2021 in Yangbi County,Dali Prefecture,Yunnan Province,which was the largest earthquake after the 2014 Jinggu Ms 6.6 earthquake,in western Yunnan.After the earthquake,the rapid ...The Ms 6.4 earthquake occurred on May 21,2021 in Yangbi County,Dali Prefecture,Yunnan Province,which was the largest earthquake after the 2014 Jinggu Ms 6.6 earthquake,in western Yunnan.After the earthquake,the rapid field investigation and earthquake relocation reveal that there was no obvious surface rupture and the earthquake did not occur on pre-existing active fault,but on a buried fault on the west side of Weixi–Qiaohou–Weishan fault zone in the eastern boundary of Baoshan sub-block.Significant foreshocks appeared three days before the earthquake.These phenomena aroused scholars'intensive attention.What the physical process and seismogenic mechanism of the Yangbi Ms 6.4 earthquake are revealed by the foreshocks and aftershocks?These scientific questions need to be solved urgently.展开更多
The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized ...The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized VariationalMode Decomposition(VMD)jointWavelet Threshold Denoising(WTD)algorithm(BVW)is proposed.The BVW algorithm integrates VMD and WTD,both of which are optimized by BWOA.Specifically,this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited IntrinsicMode Functions(BLIMFs).Subsequently,these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold are selected as the effective mode functions,and the effective mode functions are denoised using WTD to filter out the residual low-and intermediate-frequency noise.Finally,the denoised microseismic signal is obtained through reconstruction.The ideal values of VMD parameters and WTD parameters are acquired by searching with BWOA to achieve the best VMD decomposition performance and solve the problem of relying on experience and requiring a large workload in the application of the WTD algorithm.The outcomes of simulated experiments indicate that this algorithm is capable of achieving good denoising performance under noise of different intensities,and the denoising performance is significantly better than the commonly used VMD and Empirical Mode Decomposition(EMD)algorithms.The BVW algorithm is more efficient in filtering noise,the waveform after denoising is smoother,the amplitude of the waveform is the closest to the original signal,and the signal-to-noise ratio(SNR)and the root mean square error after denoising are more satisfying.The case based on Fankou Lead-Zinc Mine shows that for microseismic signals with different intensities of noise monitored on-site,compared with VMD and EMD,the BVW algorithm ismore efficient in filtering noise,and the SNR after denoising is higher.展开更多
Kazakhstan is currently drafting new construction regulations that comply with the major provisions of the Eurocodes.Such regulations are created on the basis of seismic zoning maps of various degrees of detail,develo...Kazakhstan is currently drafting new construction regulations that comply with the major provisions of the Eurocodes.Such regulations are created on the basis of seismic zoning maps of various degrees of detail,developed by our Institute of Seismology using a new methodological approach for Kazakhstan.The article is about creating the first normative map of the Detailed Seismic Zoning on a probabilistic foundation for the Republic of Kazakhstan’s East Kazakhstan region.We carried out the probabilistic assessment of seismic hazard using a methodology consistent with the main provisions of Eurocode 8and updated compared with that used in developing maps of Kazakhstan’s General Seismic Zoning and seismic microzoning of Almaty.The most thorough and current data accessible for the area under consideration were combined with contemporary analytical techniques.Updates have been done to not only the databases being used but also the way seismic sources were shown,including active faults now.On a scale of 1:1000000,precise seismic zoning maps of the East Kazakhstan region were created for two probabilities of exceedance:10%and 2%in 50 years in terms of peak ground accelerations and macroseismic intensities.The obtained seismic hazard distribution is generally consistent with the General Seismic Zoning of Kazakhstan’s previous findings.However,because active faults were included and a thoroughly revised catalog was used,there are more pronounced zones of increased danger along the fault in the western part of the region.In the west of the territory,acceleration values also increased due to a more accurate consideration of seismotectonic conditions.Zoning maps are the basis for developing new state building regulations of the Republic of Kazakhstan.展开更多
Due to the depletion of conventional energy reserves,there has been a global shift towards non-conventional energy sources.Shale oil and gas have emerged as key alternatives.These resources have dense and heterogeneou...Due to the depletion of conventional energy reserves,there has been a global shift towards non-conventional energy sources.Shale oil and gas have emerged as key alternatives.These resources have dense and heterogeneous reservoirs,which require hydraulic fracturing to extract.This process depends on identifying optimal fracturing layers,also known as‘sweet spots’.However,there is currently no uniform standard for locating these sweet spots.This paper presents a new model for evaluating fracturability that aims to address the current gap in the field.The model utilizes a hierarchical analysis approach and a mutation model,and is distinct in its use of original logging data to generate a fracturability evaluation map.Using this paper’s shale fracturing sweet spot evaluation method based on a two-step mutation model,four wells in different blocks of Fuling and Nanchuan Districts in China were validated,and the results showed that the proportion of high-yielding wells on the sweet spot line could reach 97.6%,while the proportion of low-producing wells was only 78.67%.Meanwhile,the evaluation results of the model were compared with the microseismic data,and the matching results were consistent.展开更多
In order to clarify the danger of water breakout in the bottom plate of extra-thick coal seam mining, 2202 working face of a mine in the west is taken as the research object, and it is proposed to use the on-site moni...In order to clarify the danger of water breakout in the bottom plate of extra-thick coal seam mining, 2202 working face of a mine in the west is taken as the research object, and it is proposed to use the on-site monitoring means combining borehole peeping and microseismic monitoring, combined with the theoretical analysis to analyze the danger of water breakout in the bottom plate. The results show that: 1) the theoretically calculated maximum damage depth of the bottom plate is 27.5 m, and its layer is located above the Austrian ash aquifer, which has the danger of water breakout;2) the drill hole peeping at the bottom plate of the working face shows that the depth of the bottom plate fissure development reaches 26 m, and the integrity of the water barrier layer has been damaged, so there is the risk of water breakout;3) for the microseismic monitoring of the anomalous area, the bottom plate of the return air downstream channel occurs in the field with a one-week lag, which shows that microseismic monitoring events may reflect the water breakout of the underground. This shows that the microseismic monitoring events can reflect the changes of the underground flow field, which can provide a reference basis for the early warning of water breakout. The research results can provide reference for the prediction of sudden water hazard.展开更多
Microseismic event location is one of the core parameters in microseismic monitoring,and the accuracy of localization will directly affect the effectiveness of engineering applications.However,limited by spatial facto...Microseismic event location is one of the core parameters in microseismic monitoring,and the accuracy of localization will directly affect the effectiveness of engineering applications.However,limited by spatial factors,the geometry of the sensor installation will be close to linear,which makes the localization equation suffer from the pathological problem,and the localization accuracy is greatly reduced.To address this problem,the reasons for the pathological problem are analyzed from the perspective of the objective function residuals and coefficient matrix.The pathological problem is caused by the combined effect of the poorer sensor array and data errors,and its residual isosurface shows a conical distribution,and as the residual value decreases,the apex of the isosurface gradually extends to the far side,and the localization results do not converge.For this reason,an improved regularized Newton downhill localization algorithm is proposed.In this method,firstly,the Newtonian downhill method is improved so that the magnitudes of the seismic source parameters are the same,and the condition number of the coefficient matrix is reduced;then,the L-curve method is used to calculate the regularization factor for the pathological equations,and the coefficient matrix is improved;finally,the pathological equations are regularized,and the seismic source coordinates are obtained by the improved Newtonian downhill method.The results of engineering applications show that compared with the traditional algorithm based on automatic of P-arrival picking,the number of effective microseismic events calculated by the proposed localization algorithm is increased by 194.7%,and the localization accuracy is substantially improved.The proposed algorithm reduces the problem of low accuracy of S-arrival picking and allows localization using only P-wave arrival.The method reduces the quality requirements of the data and significantly improves the utilization of microseismic events and positioning accuracy.展开更多
To find discriminating features in seismograms for the classification of mine seismic events,signal databases of blasts and microseismic events were established based on manual identification.Criteria including the re...To find discriminating features in seismograms for the classification of mine seismic events,signal databases of blasts and microseismic events were established based on manual identification.Criteria including the repetition of waveforms,tail decreasing,dominant frequency and occurrence time of day were considered in the establishment of the databases.Signals from databases of different types were drawn into a unified coordinate system.It is noticed that the starting-up angles of the two types tend to be concentrated into two different intervals.However,it is difficult to calculate the starting-up angle directly due to the inaccuracy of the P-wave arrival＇s picking.The slope value of the starting-up trend line,which was obtained by linear regression,was proposed to substitute the angle.Two slope values associated with the coordinates of the first peak and the maximum peak were extracted as the characteristic parameters.A statistical model with correct discrimination rate of greater than 97.1% was established by applying the Fisher discriminant analysis.展开更多
The development of unconventional resources, such as shale gas and tight sane gas, requires the integration of multi-disciplinary knowledge to resolve many engineering problems in order to achieve economic production ...The development of unconventional resources, such as shale gas and tight sane gas, requires the integration of multi-disciplinary knowledge to resolve many engineering problems in order to achieve economic production levels. The reservoir heterogeneit3 revealed by different data sets, such as 3D seismic and microseismic data, can more full3 reflect the reservoir properties and is helpful to optimize the drilling and completioT programs. First, we predict the local stress direction and open or close status of the natura fractures in tight sand reservoirs based on seismic curvature, an attribute that reveals reservoi heterogeneity and geomechanical properties. Meanwhile, the reservoir fracture network is predicted using an ant-tracking cube and the potential fracture barriers which can affec hydraulic fracture propagation are predicted by integrating the seismic curvature attribute anc ant-tracking cube. Second, we use this information, derived from 3D seismic data, to assis in designing the fracture program and adjusting stimulation parameters. Finally, we interpre the reason why sand plugs will occur during the stimulation process by the integration of 3E seismic interpretation and microseismic imaging results, which further explain the hydraulic fracure propagation controlling factors and open or closed state of natural fractures in tigh sand reservoirs.展开更多
We propose a new method for inverting source function of microseismic event induced in mining. The observed data from microseismic monitoring during mining are represented by a wave equation in a spherical coordinate ...We propose a new method for inverting source function of microseismic event induced in mining. The observed data from microseismic monitoring during mining are represented by a wave equation in a spherical coordinate system and then the data are transformed from the time-space domain to the time-slowness domain based on tomographic principle, from whichwe can obtain the signals related to the source in the time-slowness domain. Through analyzing the relationship between the signal located at the maximum energy and the source function, we derive the tomographic equations to compute the source function from the signals and to calculate the effective radiated energy based on the source function. Moreover, we fit the real amplitude spectrum of the source function computed from the observed data into the co-2 model based on the least squares principle and determine the zero-frequency level spectrum and the corner frequency, finally, the source rupture radius of the event is calculated and The synthetic and field examples demonstrate that the proposed tomographic inversion methods are reliable and efficient展开更多
基金Projects(41972295,U1965205)supported by the National Natural Science Foundation of ChinaProject(2019ZDK034)supported by the Guangxi Key Laboratory of Disaster Prevention and Engineering Safety,China。
文摘Excavation-induced microseismicity and rockburst occurrence in deep underground projects provide invaluable information that can be used to warn rockburst occurrence,facilitate rockburst mitigation procedures,and analyze the mechanisms responsible for their occurrence.Based on the deep parallel tunnels with the maximum depth of 1890 m created as part of the Neelum–Jhelum hydropower project in Pakistan,similarities and differences on excavation-induced microseismicity and rockburst occurrence between parallel tunnels with soft and hard alternant strata are studied.Results show that a large number of microseismic(MS)events occurred in each of the parallel tunnels during excavation.Rockbursts occurred most frequently in certain local sections of the two tunnels.Significant differences are found in the excavation-induced microseismicity(spatial distribution and number of MS events,distribution of MS energy,and pattern of microseismicity variation)and rockbursts characteristics(the number and the spatial distribution)between the parallel tunnels.Attempting to predict the microseismicity and rockburst intensities likely to be encountered in subsequent tunnel based on the activity encountered when the parallel tunnel was previously excavated will not be an easy or accurate procedure in deep tunnel projects involving complex lithological conditions.
基金This project was sponsored by the National Natural Science Foundation of China under the contract of No. 49574207
文摘This paper selects some representative regions to obtain their G-R relation curves according to their seismicity characteristics,by using ML≥2.0 microseismicity data(1970~1993)in North China.The annual occurrence rate of events of each magnitude can be inferred from the G-R relation.At the same tune,the actual annual occurrence rate of earthquakes of higher magnitudes can be calculated from historical earthquakes(1300-1993)recorded in the same region.It seems that both results are almost the same.Therefore,the rate of events of higher magnitudes can be obtained by using microseismicity data when the proper region is selected.However,two points should be noticed:(1)The method can only give the annual occurrence rate in a seismicity system and estimate the whole situation of the system.(2)When there is a very large earthquake in and near the period in which the microseismicity data are applied,the actual occurrence rate of the system,including this larger earthquake,cannot be obtained by this method.
基金supported by the Natural Sciences and Engineering Research Council of Canada through Discovery Grant 341275 (G. Grasselli) and Engage EGP 461019-13
文摘Hydraulic fracturing （HF） technique has been extensively used for the exploitation of unconventional oiland gas reservoirs. HF enhances the connectivity of less permeable oil and gas-bearing rock formationsby fluid injection, which creates an interconnected fracture network and increases the hydrocarbonproduction. Meanwhile, microseismic （MS） monitoring is one of the most effective approaches to evaluatesuch stimulation process. In this paper, the combined finite-discrete element method （FDEM） isadopted to numerically simulate HF and associated MS. Several post-processing tools, includingfrequency-magnitude distribution （b-value）, fractal dimension （D-value）, and seismic events clustering,are utilized to interpret numerical results. A non-parametric clustering algorithm designed specificallyfor FDEM is used to reduce the mesh dependency and extract more realistic seismic information.Simulation results indicated that at the local scale, the HF process tends to propagate following the rockmass discontinuities; while at the reservoir scale, it tends to develop in the direction parallel to themaximum in-situ stress. 2014 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting byElsevier B.V. All rights reserved.
文摘Petroleum reservoir operations such as oil and gas production, hydraulic fracturing, and water injection induce considerable stress changes that at some point result in rock failure and emanation of seismic energy. Such seismic energy could be large enough to be felt in the neighborhood of the oil fields, therefore many issues are recently raised regarding its environmental impact. In this research we analyze the magnitudes of microseismicity induced by stimulation of unconventional reservoirs at various basins in the United States and Canada that monitored the microseismicity induced by hydraulic fracturing operations. In addition, the relationship between microseismic magnitude and both depth and injection parameters is examined to delineate the possible framework that controls the system. Generally, microseismicity of typical hydraulic fracturing and injection operations is relatively similar in the majority of basins under investigation and the overall associating seismic energy is not strong enough to be the important factor to jeopardize near surface groundwater resources. Furthermore, these events are less energetic compared to the moderately active tectonic zones through the world and usually do not extend over a long period at considerably deep parts. However, the huge volume of the treatment fluids and improper casing cementing operation seem to be primary sources for contaminating near surface water resources.
基金supported by the National Natural Science Foundation of China (Nos. 50820125405, 50909013 and 50804006)the National Basic Research Program (973) of China (No. 2007CB209404)
文摘The volume of influence of excavation at the right bank slope of Dagangshan Hydropower Station, southwest China, is essentially determined from microseismic monitoring, numerical modeling and conventional measurements as well as in situ observations. Microseismic monitoring is a new application technique for investigating microcrackings in rock slopes. A micro- seismic monitoring network has been systematically used to monitor rock masses unloading relaxation due to continuous exca- vation of rock slope and stress redistribution caused by dam impoundment later on, and to identify and delineate the potential slippage regions since May, 2010. An important database of seismic source locations is available. The analysis of microseismic events showed a particular tempo-spatial distribution. Seismic events predominantly occurred around the upstream slope of 1180 m elevation, especially focusing on the hanging wall of fault XL316-1. Such phenomenon was interpreted by numerical modeling using RFPA-SRM code （realistic failure process analysis-strength reduction method）. By comparing microseismic activity and results of numerical simulation with in site observation and conventional measurements results, a strong correlation can he obtained between seismic source locations and excavation-induced stress distribution in the working areas. The volume of influence of the rock slope is thus determined. Engineering practices show microseismic monitoring can accurately diagnose magnitude, intensity and associated tempo-spatial characteristics of tectonic activities such as faults and unloading zones. The integrated technique combining seismic monitoring with numerical modeling, as well as in site observation and conventional surveying, leads to a better understanding of the internal effect and relationship between microseismic activity and stress field in the right bank slope from different perspectives.
基金The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China(Grant Nos.52011530037 and 51904019)the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange&Growth Program(Grant No.QNXM20210004).We also greatly appreciate the assistance provided by Kuangou coal mine,China Energy Group Xinjiang Energy Co.,Ltd.
文摘Rockbursts have become a significant hazard in underground mining,underscoring the need for a robust early warning model to ensure safety management.This study presents a novel approach for rockburst prediction,integrating the Mann-Kendall trend test(MKT)and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards.The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts.The MKT is then applied to analyze the real-time trend of each index,with adherence to rockburst characterization laws serving as the warning criterion.By employing a confusion matrix,the warning effectiveness of each index is assessed,enabling index preference determination.Ultimately,the integrated rockburst hazard index Q is derived through data fusion.The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q,surpassing the performance of any individual index.Moreover,the model’s adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data,making it suitable for complex underground working environments.By providing an efficient and accurate basis for decision-making,the proposed model holds great potential for the prevention and control of rockbursts.It offers a valuable tool for enhancing safety measures in underground mining operations.
基金We acknowledge the funding support from National Natural Science Foundation of China(Grant No.42077263).
文摘Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current arrival picking methods.Thus,a real-time arrival picking method of MS signals is constructed based on a convolutional-recurrent neural network(CRNN).This method fully utilizes the advantages of convolutional layers and gated recurrent units(GRU)in extracting short-and long-term features,in order to create a precise and lightweight arrival picking structure.Then,the synthetic signals with field noises are used to evaluate the hyperparameters of the CRNN model and obtain an optimal CRNN model.The actual operation on various devices indicates that compared with the U-Net method,the CRNN method achieves faster arrival picking with less performance consumption.An application of large underground caverns in the Yebatan hydropower station(YBT)project shows that compared with the short-term average/long-term average(STA/LTA),Akaike information criterion(AIC)and U-Net methods,the CRNN method has the highest accuracy within four sampling points,which is 87.44%for P-wave and 91.29%for S-wave,respectively.The sum of mean absolute errors(MAESUM)of the CRNN method is 4.22 sampling points,which is lower than that of the other methods.Among the four methods,the MS sources location calculated based on the CRNN method shows the best consistency with the actual failure,which occurs at the junction of the shaft and the second gallery.Thus,the proposed method can pick up P-and S-arrival accurately and rapidly,providing a reference for rock failure analysis and evaluation in engineering applications.
基金financial support of the Fundamental Research Funds for the Central Universities(Grant No.2022XSCX35)the National Natural Science Foundation of China(Grant Nos.51934007 and 52104230).
文摘Microseismic source location is crucial for the early warning of rockburst risks.However,the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy.Intelligent techniques,such as the full convolutional neural network(FCNN),can capture spatial information but struggle with complex microseismic sequence.Combining the FCNN with the long shortterm memory(LSTM)network enables better time-series signal classification by integrating multiscale information and is therefore suitable for waveform location.The LSTM-FCNN model does not require extensive data preprocessing and it simplifies the microseismic source location through feature extraction.In this study,we utilized the LSTM-FCNN as a regression learning model to locate the seismic focus.Initially,the method of short-time-average/long-time-average(STA/LTA)arrival time picking was employed to augment spatiotemporal information.Subsequently,oversampling the on-site data was performed to address the issue of data imbalance,and finally,the performance of LSTM-FCNN was tested.Meanwhile,we compared the LSTM-FCNN model with previous deep-learning models.Our results demonstrated remarkable location capabilities with a mean absolute error(MAE)of only 7.16 m.The model can realize swift training and high accuracy,thereby significantly improving risk warning of rockbursts.
基金the financial support provided by the National Key Research and Development Program for Young Scientists(No.2021YFC2900400)Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(CPSF)(No.GZB20230914)+2 种基金National Natural Science Foundation of China(No.52304123)China Postdoctoral Science Foundation(No.2023M730412)Chongqing Outstanding Youth Science Foundation Program(No.CSTB2023NSCQ-JQX0027).
文摘Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust localization method that integrates kernel density estimation(KDE)with damping linear correction to enhance the precision of microseismic/acoustic emission(MS/AE)source positioning.Our approach systematically addresses abnormal arrival times through a three-step process:initial location by 4-arrival combinations,elimination of outliers based on three-dimensional KDE,and refinement using a linear correction with an adaptive damping factor.We validate our method through lead-breaking experiments,demonstrating over a 23%improvement in positioning accuracy with a maximum error of 9.12 mm(relative error of 15.80%)—outperforming 4 existing methods.Simulations under various system errors,outlier scales,and ratios substantiate our method’s superior performance.Field blasting experiments also confirm the practical applicability,with an average positioning error of 11.71 m(relative error of 7.59%),compared to 23.56,66.09,16.95,and 28.52 m for other methods.This research is significant as it enhances the robustness of MS/AE source localization when confronted with data anomalies.It also provides a practical solution for real-world engineering and safety monitoring applications.
基金supported by Western Research Interdisciplinary Initiative R6259A03.
文摘Rock fracture mechanisms can be inferred from moment tensors(MT)inverted from microseismic events.However,MT can only be inverted for events whose waveforms are acquired across a network of sensors.This is limiting for underground mines where the microseismic stations often lack azimuthal coverage.Thus,there is a need for a method to invert fracture mechanisms using waveforms acquired by a sparse microseismic network.Here,we present a novel,multi-scale framework to classify whether a rock crack contracts or dilates based on a single waveform.The framework consists of a deep learning model that is initially trained on 2400000+manually labelled field-scale seismic and microseismic waveforms acquired across 692 stations.Transfer learning is then applied to fine-tune the model on 300000+MT-labelled labscale acoustic emission waveforms from 39 individual experiments instrumented with different sensor layouts,loading,and rock types in training.The optimal model achieves over 86%F-score on unseen waveforms at both the lab-and field-scale.This model outperforms existing empirical methods in classification of rock fracture mechanisms monitored by a sparse microseismic network.This facilitates rapid assessment of,and early warning against,various rock engineering hazard such as induced earthquakes and rock bursts.
基金supported by the National Natural Science Foundation of China(Grant No.51934007)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20220691).
文摘Microseism,acoustic emission and electromagnetic radiation(M-A-E)data are usually used for predicting rockburst hazards.However,it is a great challenge to realize the prediction of M-A-E data.In this study,with the aid of a deep learning algorithm,a new method for the prediction of M-A-E data is proposed.In this method,an M-A-E data prediction model is built based on a variety of neural networks after analyzing numerous M-A-E data,and then the M-A-E data can be predicted.The predicted results are highly correlated with the real data collected in the field.Through field verification,the deep learning-based prediction method of M-A-E data provides quantitative prediction data for rockburst monitoring.
文摘The Ms 6.4 earthquake occurred on May 21,2021 in Yangbi County,Dali Prefecture,Yunnan Province,which was the largest earthquake after the 2014 Jinggu Ms 6.6 earthquake,in western Yunnan.After the earthquake,the rapid field investigation and earthquake relocation reveal that there was no obvious surface rupture and the earthquake did not occur on pre-existing active fault,but on a buried fault on the west side of Weixi–Qiaohou–Weishan fault zone in the eastern boundary of Baoshan sub-block.Significant foreshocks appeared three days before the earthquake.These phenomena aroused scholars'intensive attention.What the physical process and seismogenic mechanism of the Yangbi Ms 6.4 earthquake are revealed by the foreshocks and aftershocks?These scientific questions need to be solved urgently.
基金funded by the National Natural Science Foundation of China(Grant No.51874350)the National Natural Science Foundation of China(Grant No.52304127)+2 种基金the Fundamental Research Funds for the Central Universities of Central South University(Grant No.2020zzts200)the Science Foundation of the Fuzhou University(Grant No.511229)Fuzhou University Testing Fund of Precious Apparatus(Grant No.2024T040).
文摘The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized VariationalMode Decomposition(VMD)jointWavelet Threshold Denoising(WTD)algorithm(BVW)is proposed.The BVW algorithm integrates VMD and WTD,both of which are optimized by BWOA.Specifically,this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited IntrinsicMode Functions(BLIMFs).Subsequently,these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold are selected as the effective mode functions,and the effective mode functions are denoised using WTD to filter out the residual low-and intermediate-frequency noise.Finally,the denoised microseismic signal is obtained through reconstruction.The ideal values of VMD parameters and WTD parameters are acquired by searching with BWOA to achieve the best VMD decomposition performance and solve the problem of relying on experience and requiring a large workload in the application of the WTD algorithm.The outcomes of simulated experiments indicate that this algorithm is capable of achieving good denoising performance under noise of different intensities,and the denoising performance is significantly better than the commonly used VMD and Empirical Mode Decomposition(EMD)algorithms.The BVW algorithm is more efficient in filtering noise,the waveform after denoising is smoother,the amplitude of the waveform is the closest to the original signal,and the signal-to-noise ratio(SNR)and the root mean square error after denoising are more satisfying.The case based on Fankou Lead-Zinc Mine shows that for microseismic signals with different intensities of noise monitored on-site,compared with VMD and EMD,the BVW algorithm ismore efficient in filtering noise,and the SNR after denoising is higher.
基金the“Seismic hazard assessment of the territories of regions and cities of Kazakhstan on a modern scientific and methodological basis”,program code F.0980,IRN OR11465449The funding source is the Ministry of Education and Science of the Republic of Kazakhstan。
文摘Kazakhstan is currently drafting new construction regulations that comply with the major provisions of the Eurocodes.Such regulations are created on the basis of seismic zoning maps of various degrees of detail,developed by our Institute of Seismology using a new methodological approach for Kazakhstan.The article is about creating the first normative map of the Detailed Seismic Zoning on a probabilistic foundation for the Republic of Kazakhstan’s East Kazakhstan region.We carried out the probabilistic assessment of seismic hazard using a methodology consistent with the main provisions of Eurocode 8and updated compared with that used in developing maps of Kazakhstan’s General Seismic Zoning and seismic microzoning of Almaty.The most thorough and current data accessible for the area under consideration were combined with contemporary analytical techniques.Updates have been done to not only the databases being used but also the way seismic sources were shown,including active faults now.On a scale of 1:1000000,precise seismic zoning maps of the East Kazakhstan region were created for two probabilities of exceedance:10%and 2%in 50 years in terms of peak ground accelerations and macroseismic intensities.The obtained seismic hazard distribution is generally consistent with the General Seismic Zoning of Kazakhstan’s previous findings.However,because active faults were included and a thoroughly revised catalog was used,there are more pronounced zones of increased danger along the fault in the western part of the region.In the west of the territory,acceleration values also increased due to a more accurate consideration of seismotectonic conditions.Zoning maps are the basis for developing new state building regulations of the Republic of Kazakhstan.
基金This work was supported by the National Science and Technology Major Project during the 13th Five-Year Plan under Grant Number 2016ZX05060004.
文摘Due to the depletion of conventional energy reserves,there has been a global shift towards non-conventional energy sources.Shale oil and gas have emerged as key alternatives.These resources have dense and heterogeneous reservoirs,which require hydraulic fracturing to extract.This process depends on identifying optimal fracturing layers,also known as‘sweet spots’.However,there is currently no uniform standard for locating these sweet spots.This paper presents a new model for evaluating fracturability that aims to address the current gap in the field.The model utilizes a hierarchical analysis approach and a mutation model,and is distinct in its use of original logging data to generate a fracturability evaluation map.Using this paper’s shale fracturing sweet spot evaluation method based on a two-step mutation model,four wells in different blocks of Fuling and Nanchuan Districts in China were validated,and the results showed that the proportion of high-yielding wells on the sweet spot line could reach 97.6%,while the proportion of low-producing wells was only 78.67%.Meanwhile,the evaluation results of the model were compared with the microseismic data,and the matching results were consistent.
文摘In order to clarify the danger of water breakout in the bottom plate of extra-thick coal seam mining, 2202 working face of a mine in the west is taken as the research object, and it is proposed to use the on-site monitoring means combining borehole peeping and microseismic monitoring, combined with the theoretical analysis to analyze the danger of water breakout in the bottom plate. The results show that: 1) the theoretically calculated maximum damage depth of the bottom plate is 27.5 m, and its layer is located above the Austrian ash aquifer, which has the danger of water breakout;2) the drill hole peeping at the bottom plate of the working face shows that the depth of the bottom plate fissure development reaches 26 m, and the integrity of the water barrier layer has been damaged, so there is the risk of water breakout;3) for the microseismic monitoring of the anomalous area, the bottom plate of the return air downstream channel occurs in the field with a one-week lag, which shows that microseismic monitoring events may reflect the water breakout of the underground. This shows that the microseismic monitoring events can reflect the changes of the underground flow field, which can provide a reference basis for the early warning of water breakout. The research results can provide reference for the prediction of sudden water hazard.
基金the financial support from the National Natural Science Foundation of China(Grant no.42077263).
文摘Microseismic event location is one of the core parameters in microseismic monitoring,and the accuracy of localization will directly affect the effectiveness of engineering applications.However,limited by spatial factors,the geometry of the sensor installation will be close to linear,which makes the localization equation suffer from the pathological problem,and the localization accuracy is greatly reduced.To address this problem,the reasons for the pathological problem are analyzed from the perspective of the objective function residuals and coefficient matrix.The pathological problem is caused by the combined effect of the poorer sensor array and data errors,and its residual isosurface shows a conical distribution,and as the residual value decreases,the apex of the isosurface gradually extends to the far side,and the localization results do not converge.For this reason,an improved regularized Newton downhill localization algorithm is proposed.In this method,firstly,the Newtonian downhill method is improved so that the magnitudes of the seismic source parameters are the same,and the condition number of the coefficient matrix is reduced;then,the L-curve method is used to calculate the regularization factor for the pathological equations,and the coefficient matrix is improved;finally,the pathological equations are regularized,and the seismic source coordinates are obtained by the improved Newtonian downhill method.The results of engineering applications show that compared with the traditional algorithm based on automatic of P-arrival picking,the number of effective microseismic events calculated by the proposed localization algorithm is increased by 194.7%,and the localization accuracy is substantially improved.The proposed algorithm reduces the problem of low accuracy of S-arrival picking and allows localization using only P-wave arrival.The method reduces the quality requirements of the data and significantly improves the utilization of microseismic events and positioning accuracy.
基金Projects(51374244,11447241)supported by the National Natural Science Foundation of China
文摘To find discriminating features in seismograms for the classification of mine seismic events,signal databases of blasts and microseismic events were established based on manual identification.Criteria including the repetition of waveforms,tail decreasing,dominant frequency and occurrence time of day were considered in the establishment of the databases.Signals from databases of different types were drawn into a unified coordinate system.It is noticed that the starting-up angles of the two types tend to be concentrated into two different intervals.However,it is difficult to calculate the starting-up angle directly due to the inaccuracy of the P-wave arrival＇s picking.The slope value of the starting-up trend line,which was obtained by linear regression,was proposed to substitute the angle.Two slope values associated with the coordinates of the first peak and the maximum peak were extracted as the characteristic parameters.A statistical model with correct discrimination rate of greater than 97.1% was established by applying the Fisher discriminant analysis.
文摘The development of unconventional resources, such as shale gas and tight sane gas, requires the integration of multi-disciplinary knowledge to resolve many engineering problems in order to achieve economic production levels. The reservoir heterogeneit3 revealed by different data sets, such as 3D seismic and microseismic data, can more full3 reflect the reservoir properties and is helpful to optimize the drilling and completioT programs. First, we predict the local stress direction and open or close status of the natura fractures in tight sand reservoirs based on seismic curvature, an attribute that reveals reservoi heterogeneity and geomechanical properties. Meanwhile, the reservoir fracture network is predicted using an ant-tracking cube and the potential fracture barriers which can affec hydraulic fracture propagation are predicted by integrating the seismic curvature attribute anc ant-tracking cube. Second, we use this information, derived from 3D seismic data, to assis in designing the fracture program and adjusting stimulation parameters. Finally, we interpre the reason why sand plugs will occur during the stimulation process by the integration of 3E seismic interpretation and microseismic imaging results, which further explain the hydraulic fracure propagation controlling factors and open or closed state of natural fractures in tigh sand reservoirs.
基金supported jointly by projects of the National Natural Science Fund Project(No.51174016)the National Key Basic Research and Development Plan 973(No.2010CB226803)
文摘We propose a new method for inverting source function of microseismic event induced in mining. The observed data from microseismic monitoring during mining are represented by a wave equation in a spherical coordinate system and then the data are transformed from the time-space domain to the time-slowness domain based on tomographic principle, from whichwe can obtain the signals related to the source in the time-slowness domain. Through analyzing the relationship between the signal located at the maximum energy and the source function, we derive the tomographic equations to compute the source function from the signals and to calculate the effective radiated energy based on the source function. Moreover, we fit the real amplitude spectrum of the source function computed from the observed data into the co-2 model based on the least squares principle and determine the zero-frequency level spectrum and the corner frequency, finally, the source rupture radius of the event is calculated and The synthetic and field examples demonstrate that the proposed tomographic inversion methods are reliable and efficient
