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1
Davydov, Vadim A. "Shallow seismic sounding based on ellipticity analysis of microtremor." Georesursy 21, no. 1 (March 30, 2019): 78–85. http://dx.doi.org/10.18599/grs.2019.1.78-85.
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A brief review is carried out of the previous study about the spectral ratios of horizontal and vertical components of microseismic oscillations displacement. The basic principles of resonant boundaries allocation and the construction of deep sections based on the H/V relations (ellipticity) are considered. A description of the equipment used, the method of recording and processing microseismic noise are presented. The main goal of the research work is to clarify the nature of the connection between the ellipticity of microseisms with geological features and the correctness of constructing deep sections based on them. The initial data are the amplitude spectra of the components of microseismic signal, obtained using the fast Fourier transformation. In the course of experimental work it was found that the spectral relations retain their characteristic features regardless of the azimuth of observations. A number of practical examples compare microseismic sections with results from other geophysical methods and drilling information. The results obtained indicate the complex nature of the ellipticity of microseismic noise under different conditions, however, they make it possible to determine the main interfaces between the upper part of the geological section. Resonant boundaries emitted by microtremor are often located near refractive seismic boundaries. This is consistent with the theory that resonance effects occur at the interface between two media with a high contrast of acoustic impedance.
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Tang, Shoufeng, Minming Tong, and Xinmin He. "The Optimum Wavelet Base of Wavelet Analysis in Coal Rock Microseismic Signals." Advances in Mechanical Engineering 6 (January 1, 2014): 537415. http://dx.doi.org/10.1155/2014/537415.
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Coal rock rupture microseismic signal is characterized by time-varying, nonstationary, unpredictability, and transient property. Wavelet transform is an important method in microseismic signals processing. However, different wavelet bases yield different results when analyzing the same signal. To study the comparability of different wavelet bases in analyzing microseismic signals, the current paper uses the microseismic signals released from coal rock bursting as the research subject. Through the analysis of the properties of commonly used wavelet basis functions and the characteristics of coal rock microseismic signals, the current study found that Coiflet and Symlet wavelets are suitable for analyzing coal rock microseismic signals. Sym 8 and Coif 2 wavelets were found to be suitable for analyzing and denoising coal rock microseismic signals. After Sym 8 wavelet denoising, signal-to-noise ratio (SNR) and the root mean square error were 30.4184 and 1.3109 E–07, respectively. After Coif 2 wavelet denoising, the SNR and the root mean square error values were 35.2176 and 1.0312 E–07, respectively. The results will aid in the analysis and extraction of coal rock microseismic signals.
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Warpinski, N. R. R., M. J. J. Mayerhofer, K. Agarwal, and J. Du. "Hydraulic-Fracture Geomechanics and Microseismic-Source Mechanisms." SPE Journal 18, no. 04 (May 6, 2013): 766–80. http://dx.doi.org/10.2118/158935-pa.
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Summary Interpretation of microseismic results and attempts to link microseismic-source mechanisms to fracture behavior require an understanding of the geomechanics of the fracturing process. Stress calculations around fractures show that the area normal to the fracture surface is stabilized by a pressurized fracture as a result of increased total stress and decreased shear stress. In this area, microseisms can occur only if leakoff pressurizes natural fractures, bedding planes, or other weakness features, and source mechanisms are thus likely to show a volumetric component that has either opening or closing movement in addition to shear slippage. Conversely, the tip tensile region is destabilized by a reduction in total stress and an increase in shear stress, with the likelihood that microseisms would be generated in this region because of these changes. Such microseisms would not yet be invaded by the fracturing fluid, and events that are mostly shear would be expected. Systems with multiple fractures, such as those that are potentially created in multiperforation-cluster stages, are much more complex, but similar elements can be outlined for those as well. Source mechanisms can help delineate these different types of microseismic behaviors, but the evaluation of such mechanisms reveals that they provide no significant information about the hydraulic fracture. Whereas it would be valuable if source mechanisms could provide information about the mechanics of the hydraulic fracture (e.g., opening, closing, and proppant), calculations show that both the energy and volume associated with microseismicity are an insignificant fraction of the total energy and volume input into the stimulation. Thus, hydraulic fractures are almost entirely aseismic. The analysis of source mechanisms should concentrate on what those data reveal about the reservoir (e.g., natural fractures and faults). Integrated diagnostic studies provide more value in understanding both the microseismicity and interpretation of the microseismic results.
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Aleksandrov, Vadim, Marsel Kadyrov, Andrey Ponomarev, Denis Drugov, and Irina Bulgakova. "Microseismic Multistage Formation Hydraulic Fracturing (MFHF) Monitoring Analysis Results." Key Engineering Materials 785 (October 2018): 107–17. http://dx.doi.org/10.4028/www.scientific.net/kem.785.107.
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Microseismic monitoring of hydrocarbon fields is one of the promising areas of modern seismology. In recent years, the methodology of microseismic monitoring for seismic emission has been actively developing in the oil and gas industry in order to study the impact of various technogenic processes on the hydrocarbon (HC) fields being developed. The technology does not require powerful sources of sounding signals, but uses constantly existing weak seismic fields of artificial or natural origin. During the development of the field, periodic monitoring of the intensity and spatial position of the zones of microseismic activity allows controling the behavior of HC deposits in order to optimize their development. Distinctive features of this technology are high mobility, fast deployment time, high resolution, and low cost of receiving, transferring and processing of microseismic data. The purpose was to analyze the results and evaluate the effectiveness of MFHF using microseismic monitoring of seismic emission processes. The results were obtained with the help of quantitative microseismic monitoring of seismic foci occurring successively near the well ports at different times during MFHF.
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Verbytskyi, Serhii, Bohdan Kuplovskyi, Vasyl Prokopyshyn, Oleksandr Stetskiv, Iryna Nishchimenko, Taras Brych, and Oleh Kruk. "GEODYNAMICS." GEODYNAMICS 1(30)2021, no. 1(30) (June 29, 2021): 58–64. http://dx.doi.org/10.23939/jgd2021.01.058.
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Objective. To refine seismic hazard parameters by registering high-frequency microseisms within the site under reconstruction in connection with the land plot enlargement of a plant intended for electronic components manufacturing. To quantify the estimated intensity of seismic shakings (in MSK-64 scale scores) accounting for the effects associated with local engineering and geological conditions at the study site. Methods. Seismic microzonation practical works at construction sites implies the application of short-period microseism registration method, which is considered to be one of the most efficient and unbiased instrumental SMZ methods when the field seismological studies are to be performed in a short period of time. The method relies on comparing parameters of soil micro-vibrations generated by natural and anthropogenic sources at the studied and the reference sites. At that, the soil is regarded as a filter capable of modifying the amplitude and phase oscillation spectra of seismic waves hitting the sedimentary cover basement. The seismic intensity gains were determined by comparing the amplitudes of soil oscillations at registration points over several sections of the site and at a reference point. Microseisms were recorded by using two identical three-channel digital seismic stations DAS-05 being the newest ones out of the model series of automatic seismic stations developed at S. I. Subbotin Institute of Geophysics of the NAS of Ukraine. VEGIK seismometers were used as seismometers. Results. Microseismic oscillation recording analysis has revealed that the main contribution to the formation of a wave field is due to the urban background disturbances falling within the frequency range of f = 8.0 - 18.0 Hz, as well as low-frequency natural oceanic effects amounting to f = 0.4 - 8.0 Hz while high-frequency vibrations are caused by anthropogenic factors amounting to f = 18.0 - 27.0 Hz (Fig. 3). Data of synchronous 24-hour microseism registering have indicated a sufficiently high stability of the amplitude level and frequency composition of microseismic oscillations, which suggests that the microseismic processes approximate stationary ones, provided that non-stationary events are removed from records. Plots of seismic intensity gain values at different frequencies caused by soil conditions at the studied site, determined according to the relation of averaged microseismic amplitude spectra both at the studied and reference site, are shown in Fig. 4. The average estimates of seismic intensity gains in the frequency range of 0.1 - 20.0 Hz for the construction site soil conditions, calculated with respect to microseismic spectral densities per all three vibration components, are presented in Table 1. The seismic intensity gain in relation to the initial (background) one for the engineering and geological conditions of the site equals to ΔIr = -0.21. Scientific novelty. Given the amplitude ratio and amplitude spectra of microseisms recorded at different sites and at the reference point, refined parameters of seismic hazards for the developable site have been obtained with consideration of the local soil conditions effects. Evaluation ratings of seismic shaking calculated intensity (in MSK-64 scale scores) based on effects associated with the local engineering and geological conditions of the study site have been provided. Practical significance. Construction site SMZ yields updated values of seismic forces relative to the general seismic zonation of the country, which allows taking into account possible gain in seismic severity at the design stage of earthquake-proof construction. Consideration of SMZ results at construction of engineering structures prevents human casualties and reduces economic losses in case of seismic manifestations.
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Zorn, Erich, Abhash Kumar, William Harbert, and Richard Hammack. "Geomechanical analysis of microseismicity in an organic shale: A West Virginia Marcellus Shale example." Interpretation 7, no. 1 (February 1, 2019): T231—T239. http://dx.doi.org/10.1190/int-2018-0072.1.
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Using an innovative workflow incorporating microseismic attributes and geomechanical well logs, we have defined major geomechanical drivers of microseismic expression to understand reservoir stimulation response in an engineering/geologic context. We sampled microseismic data from two hydraulically fractured Marcellus wells in the Appalachian Basin, West Virginia, vertically through the event cloud, crossing shale, limestone, sandstone, and chert. We focused our analysis on the Devonian organic shale and created pseudologs of moment magnitude Mw, b-value, and event count. The vertical moving-average sampling of microseismic data was completed such that the sample interval matched that of the geophysical well log. This technique creates robust, high-resolution microseismic logs that indicate subtle changes in microseismic properties and allow direct crossplotting of microseismic versus geophysical logs. We chose five geomechanical properties to form the framework against which to interrogate the microseismic data: Young’s modulus (YM), Poisson’s ratio (PR), brittleness, lambda-rho, and mu-rho. In addition, we included gamma as a useful measure of organic content. Having defined this microseismic-geomechanical crossplot space, we derived insights into the response of these units during hydraulic fracturing. Observations include (1) larger magnitude microseismicity occurs in high PR, high YM rocks; high event counts are found in low PR rocks, (2) low b-value (high in situ stress) is consistent with the occurrence of larger magnitude events and low event counts, and (3) YM and PR act as bounding conditions, creating “sweet spots” for high and low Mw, event count, and stress. In our crossplot space, there is a meaningful link between microseismicity and the elastic properties of the host rock. In light of this dependence of stimulation potential on elastic properties, the calculation of microseismic pseudologs at stimulation sites and application of our crossplot framework for microseismic-geomechanical analysis in unconventional shale will inform operators in planning and forecasting stimulation and production, respectively.
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Rafiq, Aamir, David W. Eaton, Adrienne McDougall, and Per Kent Pedersen. "Reservoir characterization using microseismic facies analysis integrated with surface seismic attributes." Interpretation 4, no. 2 (May 1, 2016): T167—T181. http://dx.doi.org/10.1190/int-2015-0109.1.
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We have developed the concept of microseismic facies analysis, a method that facilitates partitioning of an unconventional reservoir into distinct facies units on the basis of their microseismic response along with integrated interpretation of microseismic observations with 3D seismic data. It is based upon proposed links between magnitude-frequency distributions and scaling properties of reservoirs, including the effects of mechanical bed thickness and stress heterogeneity. We evaluated the method using data from hydraulic fracture monitoring of a Late Cretaceous tight sand reservoir in central Alberta, in which microseismic facies can be correlated with surface seismic attributes (primarily principal curvature, coherence, and shape index) from a coincident 3D seismic survey. Facies zones are evident on the basis of attribute crossplots, such as maximum moment release rate versus cluster azimuth. The microseismically defined facies correlate well with principal curvature anomalies from 3D seismic data. By combining microseismic facies analysis with regional trends derived from log and core data, we delineate reservoir partitions that appear to reflect structural and depositional trends.
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Dong, Linlu, Ying Yang, Bo Qian, Yaosheng Tan, Hailong Sun, and Nuwen Xu. "Deformation Analysis of Large-Scale Rock Slopes Considering the Effect of Microseismic Events." Applied Sciences 9, no. 16 (August 19, 2019): 3409. http://dx.doi.org/10.3390/app9163409.
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To research the macroscopic deformation of rock microseismic damage, a high-precision microseismic monitoring system was established on the left bank slope of the Baihetan hydropower station in Southwestern China. Based on the microseismic monitoring and field deformation data, the seismic source radius was applied to characterize the rock fracture scale. Numerical simulations introduced the rock micro-fracture information into the three-dimensional numerical model of the left bank slope and established the damage constitutive model. The unloading deformation process of the left bank abutment rock mass is described by numerical calculations. The feedback analysis method considering the effect of microseismic damage is preliminary exploratory research, which provides a new idea for the stability analysis of similar high rock slopes.
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Święch, Eryk. "Uncertainties in microseismic event location analysis." Geology, Geophysics & Environment 41, no. 1 (2015): 143. http://dx.doi.org/10.7494/geol.2015.41.1.143.
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Duan, Dong, Chun An Tang, and Xiao Jing Feng. "Microseismic Monitoring System Establishment and its Application to Xinzhangzi Coal Mine." Advanced Materials Research 396-398 (November 2011): 99–102. http://dx.doi.org/10.4028/www.scientific.net/amr.396-398.99.
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Microseismic monitoring technology is the important method for safety monitoring of coal mine. The Xinzhuangzi coal mine is high gas and outburst mine, in order to ensure safety in process of mining and tunneling, the microseismic monitoring system is built. Waveform analysis database of microseismic information and interference signal is built, the results of microseismic monitoring is preliminary analyzed. The results showed that microseismic monitoring system is stable and reliable, and the results are accurate. Microseismic monitoring technology provides a new monitoring tool and method for coal mining.
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Jia, Jing, Xianjie Hao, Guanghui Zhao, Yubao Li, Xiaoyu Chuai, Lei Huang, Guangyao Pan, et al. "Evolution Analysis of Microseismic Events before and after Mining through Large-Scale Weak Zone with High Confined Water." Advances in Civil Engineering 2021 (August 3, 2021): 1–12. http://dx.doi.org/10.1155/2021/6915221.
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The existence of large-scale weak zone will have a great adverse impact on coal mining in high confined aquifer. Taking the Wutongzhuang Coal Mine which is threatened by high-pressure water as an example, this paper studies the difference between the microseismic events before and after mining and analyzes the influence of the large size weak zone on the coal mining on the confined aquifer. The research results show that the microseismic characteristics of the large soft weak belt are small number of events, the spatial distribution of events is concentrated, and the energy level is large. The amplitude of microseismic events is higher, and the proportion of large events in microseismic events is larger than that of small events; the characteristics of microseismic events caused by mining face mining are that the number of events is more, the distribution of events is loose, the distribution of roof and floor is more, the energy level is less, the amplitude is smaller, and the proportion of small and medium events in microseismic events is larger than that of large events. Due to the joint influence of large-scale weak zone of floor and mining, the floor in the middle area of working face is affected by mining, the number of microseismic events in each aquifer increases suddenly, the karst fissures between the aquifers are further developed, and there is a trend of transfixion. Therefore, measures such as floor grouting should be taken to reinforce the large-scale weak zone before mining.
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Feng, Guang Liang, Xia Ting Feng, Zhou Neng Zhao, Guo Feng Liu, and Ya Xun Xiao. "Analysis of a Collapse in Deep Tunnel Based on Microseismic Monitoring." Applied Mechanics and Materials 256-259 (December 2012): 1181–86. http://dx.doi.org/10.4028/www.scientific.net/amm.256-259.1181.
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Tunnel collapse causes serious casualties and economic losses. One typical case analysis of a collapse in deep-buried tunnel based on microseismic monitoring is presented. The results show that the number of microseismic event keeps increasing and the distribution of microseismic events becomes concentrated in space domain gradually during collapse nucleation process. And average distance squared decreases gradually during the imminent period time just before the collapse. The failure evolution mechanism of the collapse is analyzed by moment tensor method. It is noted that the failure mechanism between this kind of collapse and immediate strain-structure rockburst is similar. However, the proportion of shear and mixed fracture for collapse is higher than immediate strain-structure rockburst. It due to the rich structure planes in collapse zone.
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Mao, Haoyu, Min Zhang, Biao Li, and Nuwen Xu. "Stability Analysis of the Left Bank Slope of Baihetan Hydropower Station Based on the MF-DFA Method." Advances in Civil Engineering 2020 (July 31, 2020): 1–19. http://dx.doi.org/10.1155/2020/8898318.
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Based on the left bank slope of Baihetan hydropower station in Southwestern China, a high-precision microseismic monitoring system was established. An early warning model of surrounding rock mass deformation and failure based on MF-DFA was proposed. The results showed that the multifractal characteristics of the microseismic and blasting waveform time series in the left bank slope were obvious, and the multifractal spectrum width of the blasting waveform is much larger than that of microseismic waveform. Before the slope cracks increased, the multifractal time-varying response characteristics of microseismic waveform showed strong regularity, which could be regarded as a precursor of surrounding rock mass deformation. Before the deformation and failure of surrounding rock mass, the multifractal spectrum width Δα showed an increasing trend while the multifractal spectrum of microseismic waveforms Δf(α) presented a decreasing trend, which can be regarded as a precursor of surrounding rock mass deformation; when deformation and failure occurred, Δα showed a decreasing trend and Δf(α) showed an increasing trend, which can be regarded as a deformation failure period; after the occurrence of deformation and failure, both Δα and Δf(α) showed a steady trend, and Δf(α) would approach to the zero line, which can be regarded as a stable period.
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Chen, Feng, Tianhui Ma, Chun’an Tang, Yanhong Du, Zhichao Li, and Fei Liu. "Research on the Law of Large-Scale Deformation and Failure of Soft Rock Based on Microseismic Monitoring." Advances in Civil Engineering 2018 (July 17, 2018): 1–8. http://dx.doi.org/10.1155/2018/9286758.
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Based on the existing Canadian ESG microseismic monitoring system, a mobile microseismic monitoring system for a soft rock tunnel has been successfully constructed through continuous exploration and improvement to study the large-scale nucleation and development of microfractures in the soft rock of the Yangshan Tunnel. All-weather, continuous real-time monitoring is conducted while the tunnel is excavated through drilling and blasting, and the waveform characteristics of microseismic events are analysed. Through the recorded microseismic monitoring data, the variation characteristics of various parameters (e.g., the temporal, spatial, and magnitude distributions of the microseismic events, the frequency of microseismic events, and the microseismic event density and energy) are separately studied during the process of large-scale deformation instability and failure of the soft rock tunnel. The relationship between the deterioration of the rock mass and the microseismic activity during this failure process is consequently discussed. The research results show that a microseismic monitoring system can be used to detect precursors; namely, the microseismic event frequency and energy both will appear “lull” and “active” periods during the whole failure process of soft rock tunnel. Two peaks are observed during the evolution of failure. When the second peak occurs, it is accompanied by the destruction of the surrounding rock. The extent and strength of the damage within the surrounding rock can be delineated by the spatial, temporal, and magnitude distributions of the microseismic events and a microseismic event density nephogram. The results of microseismic analysis confirm that a microseismic monitoring system can be used to monitor the large-scale deformation and failure processes of a soft rock tunnel and provide early warning for on-site construction workers to ensure the smooth development of the project.
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Xiao, Peiwei, Bo Qian, Peng Jiang, Nuwen Xu, and Biao Li. "Deformation Forecasting of Surrounding Rock Mass Based on Correlation between Frequency and Fracture Scale of Microseismicity." Advances in Civil Engineering 2018 (July 10, 2018): 1–13. http://dx.doi.org/10.1155/2018/4037402.
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The macroscopic deformation and failure of engineering rock mass may occur as a result of evolution and breakdown of its internal microfracture. Therefore, the macroscopic state of rock mass can be obtained from fracture scale of microfracture in real time. To assess instability and predict macroscopic deformation and failure of engineering rock mass, a time-frequency analysis technique based on S transform was proposed to investigate microseismic waveform and reveal the correlation between macroscopic deformation failure and microseismic frequency characteristics of engineering rock mass in combination with fracture scale. To minimize the influence of external factors on parameters calculated, a significant amount of microseismic data from three large-scale hydropower projects in southwestern China was collected as the statistical sample. The analysis of correlation between fracture scale and frequency characteristics of microseismic events was carried out based on the statistical sample. Combining with microseismic data and multipoint extensometers in the underground powerhouse of the Houziyan hydropower station, engineering verification was conducted. The result shows that the high-frequency components decrease and microseismic signals display low-frequency characteristic as the fracture scale increases; the microseismic high-frequency components decreased at first and then increased during the deformation process of surrounding rock mass, and the frequency of microseismic events shifts from high band to a lower one before deformation.
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Lyubushin, A. A. "Cluster analysis of low-frequency microseismic noise." Izvestiya, Physics of the Solid Earth 47, no. 6 (June 2011): 488–95. http://dx.doi.org/10.1134/s1069351311040057.
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Van Dok, Richard, Brian Fuller, Les Engelbrecht, and Marc Sterling. "Seismic anisotropy in microseismic event location analysis." Leading Edge 30, no. 7 (July 2011): 766–70. http://dx.doi.org/10.1190/1.3609091.
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Liu, Liting, Liang Kang, Xi Zhang, Yong Tang, and Zilong Li. "Analysis of Noise Characteristics in Microseismic Monitoring." IOP Conference Series: Materials Science and Engineering 729 (February 10, 2020): 012017. http://dx.doi.org/10.1088/1757-899x/729/1/012017.
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Cabarcas, Carlos, and Roger Slatt. "Sequence stratigraphic principles applied to the analysis of borehole microseismic data." Interpretation 2, no. 3 (August 1, 2014): SG15—SG23. http://dx.doi.org/10.1190/int-2013-0151.1.
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Based on a sequence stratigraphic framework developed using gamma ray stacking patterns, we have identified brittle-ductile couplets, which allow us to better interpret the microseismic response recorded during a single-stage hydraulic fracture stimulation treatment monitored from three strategically located observation wells. We have analyzed and compared hydraulic fracturing results inferred by individual processing of microseismic data acquired from horizontal and vertical sensor arrays, as well as the results from simultaneously processing the signals recorded by all three sensors. Ultimately, we have decided in favor of the triple array simultaneous solution as the most useful data set to interpret the stimulation treatment due to the location of the microseismic events coupled with the theoretical expectation from our sequence stratigraphic framework. The final data set has not only allowed us to better interpret the hydraulic fracturing results, but also helped us improve recommendations in support of the field development campaign.
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Cheng, Ai Ping, Yong Tao Gao, Chao Liu, and Jin Fei Chai. "Microseismic Monitoring and Numerical Simulation Research of Floor Failure Depth in Extra-Thick Coal Seam." Advanced Materials Research 881-883 (January 2014): 1799–804. http://dx.doi.org/10.4028/www.scientific.net/amr.881-883.1799.
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Based on the condition of fully mechanized caving face in one mine, two methods of microseismic monitoring and numerical analysis were combined to study the evolution characteristics and development law of floor failure depth in extra-thick coal seam. Microseismic monitoring results show that the number of microseismic events partly reflects the influence of mining disturbance in the roof and floor rock mass. The distribution of microseismic events are intensive near the coal mining face, which show the floor rock mass is seriously damaged during the coal mining. The greatest floor failure depth estimated from mine microseismic monitoring is 31 meters. Numerical analysis indicate that the rock stress around the mine stope is redistributed during the coal mining, due to the effect of mining disturbance. The abutment pressure increases in front of the coal mining face and the stress reduces in the mined areas. The concentration and release of the stress makes contribution to the destroy of the floor rock. The maximum floor failure depth is up to 28 meters calculated from numerical simulation. The consistency of microseismic monitoring results and numerical analysis improve that it is effective and reliable to obtain floor failure depth and considerably possible to predict the water inrush using microseismic monitoring technology with its inherent ability to remotely monitor the progressive failure caused by mining. The research results have great popularization and application values for the similar mine.
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Rindraharisaona, Elisa J., Guilhem Barruol, Emmanuel Cordier, Fabrice R. Fontaine, and Alicia Gonzalez. "Cyclone Signatures in the South-West Indian Ocean from Two Decades of Microseismic Noise." Atmosphere 12, no. 4 (April 13, 2021): 488. http://dx.doi.org/10.3390/atmos12040488.
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Tropical Cyclones (TC) represent the most destructive natural disaster affecting the islands in the South-West Indian Ocean (SWIO) each year. Monitoring ocean activity is therefore of primary importance to secure lands, infrastructures and peoples, but the little number of oceanographic instruments makes it challenging, particularly in real time. Long-term seismological records provide a way to decipher and quantify the past cyclonic activity by analyzing microseisms, seismic waves generated by the ocean activity and propagating through the solid Earth. In the present study, we analyze this microseismic noise generated by cyclones that develop in the SWIO basin between 1999 and 2020, using broadband seismic stations in La Réunion. The power spectral density (PSD), together with the root mean square (RMS) analyses of continuous seismic data recorded by the permanent Geoscope RER seismic station, indicate the intensification of the microseismic noise amplitude in proportion to the cyclone intensity. Thus, we establish a relationship between the cyclone intensity and the PSD of the Secondary Microseisms (SM) in frequency band ∼0.14 to 0.25 Hz (4 to 7 s period). The Pearson coefficient between the observed and estimated TC intensity are >0.8 in the presence of a cyclone with mean wind speeds >75 km/h and with a seismic station distance-to-storm center D < 3000 km. A polarization analysis in the time and frequency domains allows the retrieval of the backazimuth of the SM sources during isolated cyclone events and well-polarized signal, i.e., CpH > 0.6. We also analyzed the RMS of the Primary Microseisms (PM frequency between ∼0.05 and 0.1 Hz, i.e., for 10 to 20 s period) for cyclones passing nearby La Réunion (D < 500 km), using the available temporary and permanent broadband seismic stations. We also found high correlation coefficients (>0.8) between the PM amplitude and the local wave height issued from the global hindcast model demonstrating that the PM amplitude can be used as a robust proxy to perform a real-time wave-height monitoring in the neighboring ocean. Transfer functions are calculated for several cyclones to infer wave height from the seismic noise amplitude recorded on land. From the analysis of two decades of data, our results suggest that it is possible to quantify the past ocean activity for as long as continuous seismic archives are available, emphasizing microseismic noise as a key observable for quantifying and understanding the climate change.
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Forghani-Arani, Farnoush, Mark Willis, Seth S. Haines, Mike Batzle, Jyoti Behura, and Michael Davidson. "An effective noise-suppression technique for surface microseismic data." GEOPHYSICS 78, no. 6 (November 1, 2013): KS85—KS95. http://dx.doi.org/10.1190/geo2012-0502.1.
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The presence of strong surface-wave noise in surface microseismic data may decrease the utility of these data. We implement a technique, based on the distinct characteristics that microseismic signal and noise show in the [Formula: see text] domain, to suppress surface-wave noise in microseismic data. Because most microseismic source mechanisms are deviatoric, preprocessing is necessary to correct for the nonuniform radiation pattern prior to transforming the data to the [Formula: see text] domain. We employ a scanning approach, similar to semblance analysis, to test all possible double-couple orientations to determine an estimated orientation that best accounts for the polarity pattern of any microseismic events. We then correct the polarity of the data traces according to this pattern, prior to conducting signal-noise separation in the [Formula: see text] domain. We apply our noise-suppression technique to two surface passive-seismic data sets from different acquisition surveys. The first data set includes a synthetic microseismic event added to field passive noise recorded by an areal receiver array distributed over a Barnett Formation reservoir undergoing hydraulic fracturing. The second data set is field microseismic data recorded by receivers arranged in a star-shaped array, over a Bakken Shale reservoir during a hydraulic-fracturing process. Our technique significantly improves the signal-to-noise ratios of the microseismic events and preserves the waveforms at the individual traces. We illustrate that the enhancement in signal-to-noise ratio also results in improved imaging of the microseismic hypocenter.
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Zhu, Xiao Jing, Yi Shan Pan, and Zhi Tang. "Technology Principle and Application of Microseismic Monitoring Rockburst." Advanced Materials Research 1010-1012 (August 2014): 1487–93. http://dx.doi.org/10.4028/www.scientific.net/amr.1010-1012.1487.
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In order to monitor and forecast rockburst, and analyze the source and magnitude,a set of microseismic monitoring rockburst technology was developed,combining with the actual situation in Dongtan coal mine.The technique used SOS microseismic monitoring system to determine failure points,record rockburst moments,the size of epicenter,the epicenter pressure drop and vibration mechanism,infer coal and rock stress state and destruction,and evaluate and monitor rockburst danger degree in accordance with changes of microseismic activities,focal position and activities tendency. The optimization microseismic monitoring network was layoutted in monitoring areas.The seismic geophone picked up microseismic signals and recorded in the rockburst figure,and the rockburst occurrence regularity and development trend were studied based on statistical analysis results of microseismic datas.Then by using VB6.0,the rockburst monitoring results were compounded in the mining drawing with concentration analysis.The rockburst events were statistical processed partitionedly to obtained vibration frequency,maximum vibration energy and total shock energy.The rockburst can be monitored and predicted through the rockburst events reflected by the datas.
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Li, Juan, Yuan Li, Shou Ji, Yue Li, and Zhihong Qian. "Signal-to-noise ratio enhancement for downhole microseismic data based on 3D shearlet transform." GEOPHYSICS 84, no. 3 (May 1, 2019): V207—V218. http://dx.doi.org/10.1190/geo2018-0262.1.
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Downhole microseismic data are characterized for their high frequency and small amplitude, which bring great difficulty for noise suppression. We present a random noise attenuation method for downhole microseismic data based on the 3D shearlet transform (3DST). In contrast to the 2D shearlet, 3DST takes into account the correlation among three components of downhole microseismic. With the help of correlation among the data, downhole microseismic data are reassembled into a new 3D matrix and then transformed to the shearlet domain. After the analysis of the coefficients’ energy and the high-order cumulant on each scale, an efficient threshold function is proposed. We apply a small threshold to the coefficients associated with the signal’s scales, and a large threshold is chosen for the scales of the noise. Experimental results indicate that the algorithm significantly improves the signal-to-noise ratio of the microseismic data and effectively preserves a valid signal.
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Li, Dewei, Ruizhao Yang, Lingbin Meng, and Wang Li. "Application of brittleness index to interpret microseismic event distribution in a hydraulically fractured shale formation." Interpretation 9, no. 1 (January 4, 2021): T1—T7. http://dx.doi.org/10.1190/int-2019-0292.1.
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Many factors can impact the location data of microseismic events, including natural fractures, rock lithology, in situ stress, and hydraulic-fracturing parameters. The distribution of microseismic events generally tends toward highly brittle areas or areas with brittle minerals. Moreover, location data of microseismic events lack effective evaluation methods. Therefore, we have developed a method to use lithologic information and prestack seismic data to explain the distribution of well Tian Xing microseismic events. We have analyzed the brittleness of the target formation through the well logs and core. We inverted the Young’s modulus and Poisson’s ratio based on simultaneous amplitude variation with offset inversion by the prestack seismic data. We then computed the 3D brittleness index (BI) property volume by Grieser and Rickman’s method. In addition, the microseismic event distribution and BI map were then combined to show the internal relationship between the two results. We found that the well logs and core analysis demonstrated that the target formation has high brittleness. Generally, areas with more natural fractures have a higher probability of inducing hydraulic fractures. However, the analysis results show that the BI has an impact on the distribution of hydraulic fractures. Therefore, BI explains the reason for the distribution of almost all events in the northeast of the perforation. These observations also supported the concept that microseismic events preferentially grow toward more brittle areas.
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Nagano, Koji. "Time–quefrency analysis of overlapping similar microseismic events." Exploration Geophysics 47, no. 2 (June 2016): 133–44. http://dx.doi.org/10.1071/eg15033.
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Fagan, Deborah, Kasper van Wijk, and James Rutledge. "Clustering revisited: A spectral analysis of microseismic events." GEOPHYSICS 78, no. 2 (March 1, 2013): KS41—KS49. http://dx.doi.org/10.1190/geo2012-0323.1.
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Identifying individual subsurface faults in a larger fault system is important to characterize and understand the relationship between microseismicity and subsurface processes. This information can potentially help drive reservoir management and mitigate the risks of natural or induced seismicity. We have evaluated a method of statistically clustering power spectra from microseismic events associated with an enhanced oil recovery operation in southeast Utah. Specifically, we were able to provide a clear distinction within a set of events originally designated in the time domain as a single cluster and to identify evidence of en echelon faulting. Subtle time-domain differences between events were accentuated in the frequency domain. Power spectra based on the Fourier transform of the time-domain autocorrelation function were used, as this formulation results in statistically independent intensities and is supported by a full body of statistical theory upon which decision frameworks can be developed.
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Smith, Valerie, and Paul Jaques. "Illinois Basin – Decatur Project pre-injection microseismic analysis." International Journal of Greenhouse Gas Control 54 (November 2016): 362–77. http://dx.doi.org/10.1016/j.ijggc.2015.12.004.
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Sherman, Christopher S., Joseph P. Morris, Pengcheng Fu, and Randolph R. Settgast. "Recovering the microseismic response from a geomechanical simulation." GEOPHYSICS 84, no. 4 (July 1, 2019): KS133—KS142. http://dx.doi.org/10.1190/geo2018-0184.1.
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The analysis of microseismic events is one of a few tools available for characterizing processes that occur within the subsurface. We have developed a method for modeling microseismic activity in the subsurface that allows us to model microseismic events at the reservoir scale. By embedding this method in a fully coupled hydromechanical numerical code, we simulate the development of hydraulic fractures in an unconventional reservoir with an explicitly represented discrete fracture network for a relatively simple synthetic model and a more complicated model based upon field observations. The results demonstrate that the model can be effectively calibrated against measured microseismic activity, and it can be used to make predictions regarding the timing, location, and amplitude of events in the subsurface.
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Wang, Kaikai, Chun’an Tang, Ke Ma, Xintang Wang, and Qiang Li. "An Automatic Recognition Method of Microseismic Signals Based on S Transformation and Improved Gaussian Mixture Model." Advances in Civil Engineering 2020 (August 7, 2020): 1–24. http://dx.doi.org/10.1155/2020/8825990.
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The microseismic signals in the coal minefield are very complex because of its special environment with a large number of blast vibration signals, and how to effectively identify the microseismic signals is still a big problem. S transform (ST) and Manifold Learning (ML) methods are introduced to extract the characteristics of the microseismic signals, and Gaussian Mixture Model based on the improved Bee Colony optimization algorithm (IBC-GMM) is established to identify the microseismic signals accurately. Firstly, the time-frequency characteristics of microseismic signals in coal mine are extracted by ST analysis. It is found that there are obvious time-frequency differences between rock-fracturing signals and blast vibration signals. Blast vibration signals have short duration, high frequency, and complex frequency spectrum, and their dominant frequencies are mainly over 100 Hz. However, rock-fracturing signals are relatively slow, with low frequency and stable spectrum change, and their dominant frequencies are generally below 100 Hz. Then, combining with the microseismic data of Xiashinjie coal mine in Tongchuan, China, the feature dimension reduction is carried out by Manifold Learning (ML) method, and the processed feature vectors are automatically recognized by IBC-GMM. Field test results show that the method summarizes the characteristics of the microseismic wave which are difficult to emerge as the learning vector, and the features reflect the key features of microseismic signals well. The identification accuracy is as high as 94%, and its recognition effect is superior to other recognition models (such as traditional Gaussian Mixture Model based on Expectation-Maximum (EM-GMM), Backpropagation (BP) neural network, Random Forests (RF), Bayes (Bayes) methods, and Logistic Regression (LR) method). Therefore, IBC-GMM could be used to mine engineering microseismic monitoring waveform recognition to provide the reference.
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De Lauro, E., S. De Martino, M. Falanga, and M. Palo. "Statistical analysis of Stromboli VLP tremor in the band [0.1–0.5] Hz: some consequences for vibrating structures." Nonlinear Processes in Geophysics 13, no. 4 (August 10, 2006): 393–400. http://dx.doi.org/10.5194/npg-13-393-2006.
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Abstract. We analyze time series of Strombolian volcanic tremor, focusing our attention on the frequency band [0.1–0.5] Hz (very long period (VLP) tremor). Although this frequency band is largely affected by noise, we evidence two significant components by using Independent Component Analysis with the frequencies, respectively, of ~0.2 and ~0.4 Hz. We show that these components display wavefield features similar to those of the high frequency Strombolian signals (>0.5 Hz). In fact, they are radially polarised and located within the crater area. This characterization is lost when an enhancement of energy appears. In this case, the presence of microseismic noise becomes relevant. Investigating the entire large data set available, we determine how microseismic noise influences the signals. We ascribe the microseismic noise source to Scirocco wind. Moreover, our analysis allows one to evidence that the Strombolian conduit vibrates like the asymmetric cavity associated with musical instruments generating self-sustained tones.
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Maity, Debotyam, and Fred Aminzadeh. "Novel fracture zone identifier attribute using geophysical and well log data for unconventional reservoirs." Interpretation 3, no. 3 (August 1, 2015): T155—T167. http://dx.doi.org/10.1190/int-2015-0003.1.
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We have characterized a promising geothermal prospect using an integrated approach involving microseismic monitoring data, well logs, and 3D surface seismic data. We have used seismic as well as microseismic data along with well logs to better predict the reservoir properties to try and analyze the reservoir for improved mapping of natural and induced fractures. We used microseismic-derived velocity models for geomechanical modeling and combined these geomechanical attributes with seismic and log-derived attributes for improved fracture characterization of an unconventional reservoir. We have developed a workflow to integrate these data to generate rock property estimates and identification of fracture zones within the reservoir. Specifically, we introduce a new “meta-attribute” that we call the hybrid-fracture zone-identifier attribute (FZI). The FZI makes use of elastic properties derived from microseismic as well as log-derived properties within an artificial neural network framework. Temporal analysis of microseismic data can help us understand the changes in the elastic properties with reservoir development. We demonstrate the value of using passive seismic data as a fracture zone identification tool despite issues with data quality.
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Meyer, Matthias, Samuel Weber, Jan Beutel, and Lothar Thiele. "Systematic identification of external influences in multi-year microseismic recordings using convolutional neural networks." Earth Surface Dynamics 7, no. 1 (February 4, 2019): 171–90. http://dx.doi.org/10.5194/esurf-7-171-2019.
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Abstract. Passive monitoring of ground motion can be used for geophysical process analysis and natural hazard assessment. Detecting events in microseismic signals can provide responsive insights into active geophysical processes. However, in the raw signals, microseismic events are superimposed by external influences, for example, anthropogenic or natural noise sources that distort analysis results. In order to be able to perform event-based geophysical analysis with such microseismic data records, it is imperative that negative influence factors can be systematically and efficiently identified, quantified and taken into account. Current identification methods (manual and automatic) are subject to variable quality, inconsistencies or human errors. Moreover, manual methods suffer from their inability to scale to increasing data volumes, an important property when dealing with very large data volumes as in the case of long-term monitoring. In this work, we present a systematic strategy to identify a multitude of external influence sources, characterize and quantify their impact and develop methods for automated identification in microseismic signals. We apply the strategy developed to a real-world, multi-sensor, multi-year microseismic monitoring experiment performed at the Matterhorn Hörnligrat (Switzerland). We develop and present an approach based on convolutional neural networks for microseismic data to detect external influences originating in mountaineers, a major unwanted influence, with an error rate of less than 1 %, 3 times lower than comparable algorithms. Moreover, we present an ensemble classifier for the same task, obtaining an error rate of 0.79 % and an F1 score of 0.9383 by jointly using time-lapse image and microseismic data on an annotated subset of the monitoring data. Applying these classifiers to the whole experimental dataset reveals that approximately one-fourth of events detected by an event detector without such a preprocessing step are not due to seismic activity but due to anthropogenic influences and that time periods with mountaineer activity have a 9 times higher event rate. Due to these findings, we argue that a systematic identification of external influences using a semi-automated approach and machine learning techniques as presented in this paper is a prerequisite for the qualitative and quantitative analysis of long-term monitoring experiments.
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Ma, Ke, Su-jian Wang, Fu-zhen Yuan, Yi-lin Peng, Shi-min Jia, and Fengqiang Gong. "Study on Mechanism of Influence of Mining Speed on Roof Movement Based on Microseismic Monitoring." Advances in Civil Engineering 2020 (September 29, 2020): 1–9. http://dx.doi.org/10.1155/2020/8819824.
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Based on the study of the movement rule of the rock strata under the influence of the mining speed in the typical working face of Dongjiahe coal mine, the distribution of microseismic events and the variation characteristics of microseismic parameters in the slow and fast advancing stage are compared and analyzed, and the mechanism of the rock strata activity under the influence of the mining advancing speed is revealed from the perspective of the microfracture. The results show that the movement of the roof strata and the stress adjustment of surrounding rock have certain timeliness. The maximum advanced distance of microseismic events in the slow and fast stages is 185 m and 130 m, respectively, and the maximum lag distance of microseismic events in the goaf is 120 m and 180 m, respectively. The time of stress adjustment of surrounding rock is short, and the load transfer of the roof is insufficient. The advanced distance of microseismic events is increased, and the lag distance decreases. The percentage of microseismic events in the total number of events is 47% and 38%, respectively, in the slow and fast stages of advancing. With the increase of mining speed, the intensity of roof strata activity in the goaf is weakened. The rock failure decreases and the volume of broken block increases, and roof collapse and rotary subsidence are insufficient. During the nonpressure period, the maximum development elevation of microseismic events is +350 m and +300 m, respectively, in the slow and fast stages, while with the development elevation of microseismic events in the roof pressure near +390 m, increasing the mining speed cannot change the final failure height of the overburden. During the analysis period of roof pressure, the concentrated release of microseismic energy in the faster stage is 183% of that in the slower stage. The increase of large moment magnitude event frequency leads to the decrease of b value. The risk of roof instability and strata behavior increases.
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Yu, Qun, Chun-An Tang, Liancong Li, GuanWen Cheng, and Lie-Xian Tang. "Study on Rockburst Nucleation Process of Deep-Buried Tunnels Based on Microseismic Monitoring." Shock and Vibration 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/685437.
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The objective of this study was to investigate the rockburst nucleation process and provide a theoretical basis for its prediction. A microseismic monitoring system was established in deep tunnels at Jinping II Hydropower Station. Using a digital multichannel microseismic monitoring system and monitoring technique, twenty-four-hour continuous real-time monitoring of macroscopic was realized in diversion tunnel #3. Substantial microseismic monitoring data were acquired to study the macroeconomic instability failure mechanisms in the rockburst nucleation process in terms of dynamic crack propagation, including microcrack initiation, development, propagation, shear zone formation, and coalescence. The intrinsic relationship between the spatiotemporal evolution patterns of the microseismicity and the rockbursts was preliminarily explored. The monitoring and analysis results indicated that the driving source of certain rockbursts could be expressed as the combined results of the local rockburst energy and the transfer energy; that is,Edrive=Elocal+Etransfer. Strong rockbursts can induce the recurrence of rockbursts in nearby locations. In addition, a comparative analysis of the formation and failure mode of molds in underground caverns was performed using the finite element analysis program RFPA. Based on this engineering study, we verified the feasibility of applying microseismic monitoring to rockbursts in deep rock tunnels.
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Ge, Maochen, and P. K. Kaiser. "Interpretation of physical status of arrival picks for microseismic source location." Bulletin of the Seismological Society of America 80, no. 6A (December 1, 1990): 1643–60. http://dx.doi.org/10.1785/bssa08006a1643.
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Abstract The automatic recognition of a microseismic event usually relies on two criteria: threshold voltage level and event recognition time window. Current microseismic source location techniques are severaly limited because the physical status of an arrival pick is not known. This paper presents a theory for the identification of the physical status of an arrival pick. It consists of an arrival time difference analysis and a residual analysis. The theory can be used to discriminate various types of arrival picks critical for microseismic source location. An event-based velocity model can then be established and used to determine the source location more accurately. The theory provides a unique approach that may be utilized in various automatic acoustic/seismic processing systems.
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Cui, Feng, Yanbin Yang, Xingping Lai, Chong Jia, and Pengfei Shan. "Experimental Study on the Effect of Advancing Speed and Stoping Time on the Energy Release of Overburden in an Upward Mining Coal Working Face with a Hard Roof." Sustainability 12, no. 1 (December 19, 2019): 37. http://dx.doi.org/10.3390/su12010037.
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In order to study the influence of advancing speed and stoping time of a coal face on the scale and frequency of rock burst, the energy release characteristics of an overburden fracture under six advancing speeds and four stoping times are studied by theoretical analysis and similar simulation experiments. The distribution characteristics of microseismic events before and after stoppage are compared, and the load/unload response ratio is introduced to analyze the relationship between the synergistic effect of advancing speed and stoping time and the characteristics of microseismic events in coal and rock mass. The mechanism of rock burst induced by the advancing speed and stoping time effect in the working face is studied, and the coordinated regulation and mitigation of advancing speed and stoping time are analyzed and completed. The results show that the effect of advancement speed and stoping time is very important to the energy release of overburden. The energy released by microseismic events during stoping is exponentially related to the advancing speed. The change of advancing speed causes the change of microseismic event characteristics, reflecting the evolution process of overburden structure and its energy. During stoping, the secondary microseismic events disturbed by mining occur frequently, leading to the significant difference of energy released by microseismic events during stoping. After stoping, the microseismic energy is more than four times higher than that during the stop period, and the risk of coal seam impact is high during the stope period. The synergetic change of advancement speed and stoping time changes the cycle of energy accumulation and release. The response ratio of loading and unloading considering the effect of advancement speed and stoping time is established by using the corresponding ratio of loading and unloading, and the impact risk of the coal seam is quantitatively analyzed. Based on the monitoring and analysis of microseismic events, the safety mining index of coordinated control with the energy of a single microseismic event of 180 J is established, and the best advancing speed of the working face is determined to be 4 m/d. According to the corresponding ratio of loading and unloading, the reasonable stoping time of different advancing speeds and the corresponding advancing speed of different stoping times after the resumption of mining are determined, so as to provide a reference for the safe and efficient mining of similar rock burst mines.
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Sović, Ivica, Kristina Šariri, and Mladen Živčić. "High frequency microseismic noise as possible earthquake precursor." Research in Geophysics 3, no. 1 (August 7, 2013): 2. http://dx.doi.org/10.4081/rg.2013.e2.
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Before an earthquake occurs, microseismic noise in high frequency (HF) range, <em>i.e.</em> 2-25 Hz, is being generated during preparation process. These signals change the microseismic noise and, consequently, the spectrum of microseismic noise. Time variation of spectra recorded at the same seismological station could imply the change of the state of noise source. We propose the image moment analysis approach to objectively compare microseismic noise spectra. The result could be used for earthquake precursor identification. Expected spectra change is in HF range, so the analysis has been limited to the shallow tectonic earthquakes with epicenters close, up to 15 km, the seismological stations. The method has been tested post festum using four earthquakes in Dinarides which satisfied condition for epicentral distance. The spectra were calculated for noise recorded in time intervals of 10 days before and 6 to 10 days after the earthquakes. Affine moment invariants were calculated for noise spectra which were treated as the input objects. Spectra of the first five days in the series were referent spectra. The classification parameters were Euclidean distances between referent spectra and the spectra for all days in the series, including referent ones. The results have shown that the spectra of the microseismic noise become noticeably different than the other spectra in time intervals one or two days before an earthquake.
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Wei, Like, Qingxin Qi, Hongyan Li, Bin Zhang, Yongren Wang, and Linghai Kong. "A Case Study of Damage Energy Analysis and an Early Warning by Microseismic Monitoring for Large Area Roof Caving in Shallow Depth Seams." Shock and Vibration 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/709459.
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Shallow depth coal seams are widely spread in Shendong mining area, which is located in the Northwestern region of China. When working face is advanced out of concentrated coal pillar in upper room and pillar goaf, strong strata behaviors often cause support crushing accidents, and potentially induce large area residual pillars instability and even wind blast disaster. In order to predict the precise time when the accident happens, guaranteeing life-safety of miner, microseismic monitoring system was for the first time applied in shallow coal seam. Based on damage mechanics correlation theory, the damage energy model is established to describe relationship between damage level and cumulative energy of microseismic events. According to microseismic monitoring data of two support crushing accidents, the damage energy model is verified and an effective early warning method of these accidents is proposed. The field application showed that the early warning method had avoided miners suffering from all support crushing accidents in Shigetai coal mine.
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Capon, Jack. "Analysis of Microseismic Noise at LASA, NORSAR and ALPA†." Geophysical Journal of the Royal Astronomical Society 35, no. 1-3 (September 15, 2009): 39–54. http://dx.doi.org/10.1111/j.1365-246x.1973.tb02413.x.
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Yousef, Baban M., and Doug A. Angus. "Analysis of fracture induced scattering of microseismic shear-waves." Studia Geophysica et Geodaetica 61, no. 4 (May 29, 2017): 728–53. http://dx.doi.org/10.1007/s11200-016-0384-9.
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Williams, Michael John, Joel Herve Le Calvez, Sandy Conners, and Wenyue Xu. "Integrated microseismic and geomechanical study in the Barnett Shale Formation." GEOPHYSICS 81, no. 3 (May 2016): KS135—KS147. http://dx.doi.org/10.1190/geo2015-0077.1.
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We have developed a careful chronological review of multistage stimulation treatments, in which microseismic interpretation was supported by fracture simulation and finite-element geomechanical simulation. The interpretation of a zipper frac stimulation treatment conducted in the Barnett Shale Formation in 2011 progressed from microseismic interpretation, from well-site observation, to a self-consistent understanding across multiple stages and multiple wells. Through this process, we have developed a tutorial on practical interpretation of microseismic data in the context of the hydraulic fracture treatment information (pump data) and regional structural information from interpretation of 3D seismic sections. Analysis of microseismic data included summarizing groups of events in the form of [Formula: see text]-value, [Formula: see text]-value, and extracted planar geometries. We advocate the development of a chronological interpretation, the consistency of which is tested using forward modeling. The process is iterative and relies on the forward modeling of complex fracturing and finite-element geomechanical models to inform iterations of the interpretation. Although extended case studies of this type are unsuitable for well-site analysis, we recommend their use for planning stimulation treatments for future nearby wells and to inform strategies for refracturing later in the well’s life.
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Blias, Emil, and Vladimir Grechka. "Analytic solutions to the joint estimation of microseismic event locations and effective velocity model." GEOPHYSICS 78, no. 3 (May 1, 2013): KS51—KS61. http://dx.doi.org/10.1190/geo2012-0517.1.
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Obtaining hypocenters of microseismic events, a primary task in mining, geothermal, and hydraulic-fracturing applications of induced seismicity, requires a velocity model for computing those hypocenters. In our paper, relying on a notion that information provided by microseismic events themselves enables one to construct a velocity model and calculate the event hypocenters in that model, we derive exact analytic solutions to the joint velocity-estimation/event-location problem for downhole microseismic data acquired in homogeneous isotropic media. We show that traveltimes and polarization vectors of the direct P- and S-waves excited by a microseismic event and recorded by a string of receivers placed in one or two vertical wells not only uniquely constrain the event location and the medium velocities but also entail a straightforward analysis of the uncertainties of those estimates caused by the presence of noise in the data. Although the P- and S-wave velocities calculated analytically under the assumption of the medium homogeneity cannot fully absorb the complexity of heterogeneous subsurface models, they become the proper effective velocities for a given microseismic event, and the corresponding event location—which is no longer exact even for noise-free data—might serve as a useful initial guess for more sophisticated event-location techniques that account for the velocity heterogeneity.
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Akram, Jubran, and David W. Eaton. "A review and appraisal of arrival-time picking methods for downhole microseismic data." GEOPHYSICS 81, no. 2 (March 1, 2016): KS71—KS91. http://dx.doi.org/10.1190/geo2014-0500.1.
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We have evaluated arrival-time picking algorithms for downhole microseismic data. The picking algorithms that we considered may be classified as window-based single-level methods (e.g., energy-ratio [ER] methods), nonwindow-based single-level methods (e.g., Akaike information criterion), multilevel- or array-based methods (e.g., crosscorrelation approaches), and hybrid methods that combine a number of single-level methods (e.g., Akazawa’s method). We have determined the key parameters for each algorithm and developed recommendations for optimal parameter selection based on our analysis and experience. We evaluated the performance of these algorithms with the use of field examples from a downhole microseismic data set recorded in western Canada as well as with pseudo-synthetic microseismic data generated by adding 100 realizations of Gaussian noise to high signal-to-noise ratio microseismic waveforms. ER-based algorithms were found to be more efficient in terms of computational speed and were therefore recommended for real-time microseismic data processing. Based on the performance on pseudo-synthetic and field data sets, we found statistical, hybrid, and multilevel crosscorrelation methods to be more efficient in terms of accuracy and precision. Pick errors for S-waves are reduced significantly when data are preconditioned by applying a transformation into ray-centered coordinates.
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Ding, Ke, Lianguo Wang, Mei Yu, Wenmiao Wang, and Bo Ren. "Study on Microseismic Monitoring, Early Warning, and Comprehensive Prevention of a Rock Burst under Complex Conditions." Shock and Vibration 2020 (September 19, 2020): 1–12. http://dx.doi.org/10.1155/2020/8863771.
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Rock bursts in coal mines are usually unpredictable. In view of this problem, the energy–frequency relationship and spatial distribution characteristics of microseismic events during the mining of 5305 working face in Xinhe Coal Mine under complex geological conditions were analyzed in this study. Besides, the law and precursors of rock burst occurrence in this working face were discussed. The following research results were obtained. Before the rock burst occurred in 5305 working face, the energy and frequency of microseismic events vary in the following order: “peak-drop-rise-rock burst.” The analysis on spatial characteristics of microseismic events suggests that microseismic events were mainly concentrated at the boundary between the roof and the coal seam or at the hard roof near the coal seam within 0–160 m in front of the working face, and most of the events lay on the goaf side. Moreover, the energy and frequency of microseismic events both decrease in the above region before the rock burst occurred. This “microseismic event absence” phenomenon can be regarded as one of the precursors of rock burst occurrence. In addition, a multilevel antiburst scheme was proposed for the complex conditions: (1) to adopt large-diameter boreholes pressure relief technology and key layer high-level pressure relief technology for adjusting the stress distribution in the surrounding rock of crossheading in front of the working face and dissipating elastic strain energy; (2) to determine the advance speed to be 1.5 m/d for reducing the mining disturbance; (3) to adopt full-section reinforced support of the roadway for enhancing the antiburst capacity of surrounding rock. After the implementation of this scheme, the energy and frequency of microseismic events monitored on-site changed gently, and 5305 working face was safely recovered to the stop line position. The scheme boasts a remarkable rock burst prevention and control effect.
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Xu, Nu Wen, Chu Nan Tang, Si Hao Wu, Gui Lin Li, and Ju Ying Yang. "Optimal Design of Microseismic Monitoring Networking and Error Analysis of Seismic Source Location for Rock Slope." Advanced Materials Research 163-167 (December 2010): 2991–99. http://dx.doi.org/10.4028/www.scientific.net/amr.163-167.2991.
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For the purpose of getting a better understanding of failure mechanisms of rock fracturing due to construction perturbation inside the right rock slope of Dagangshan Hydropower Staion, a high precision microseimic monitoring system was installed and preliminary source location data have been investigated. The optimal design of microseimic monitoring network, especially the sensor array was investigated based on P method and Powell algorithm. The positioning accuracy of the system has been adjusted according to artificial fixed blasting tests. The testing results show that microseismic source location error is less than 10 m in the scope of the sensor array, which demonstrates the monitoring system deployed at the right slope has a high positioning accuracy. Signals from 112 microseismic events with moment magnitude ranging from -1.8 to -0.4 were recorded during its 2-month monitoring period. The cluster distribution of microseismic events can reflect directly the construction progresses such as the concentration of microseismicity inside the drainage tunnel at 1081 m level. The present study have significantly improved the understanding of the characteristics of the failure associated with excavation inside the rock slope, and will greatly benefit the potential sliding areas prediction and support of hazards in the phase of construction in future.
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Zhang, Zhishuai, Jing Du, and Fuchun Gao. "Simultaneous inversion for microseismic event location and velocity model in Vaca Muerta Formation." GEOPHYSICS 83, no. 3 (May 1, 2018): KS23—KS34. http://dx.doi.org/10.1190/geo2017-0010.1.
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Velocity models play a key role in locating microseismic events; however, it is usually challenging to construct them reliably. Traditional model-building strategies depend on the availability of well logs or perforation shots. We simultaneously invert for microseismic event locations and a velocity model under the Bayesian inference framework, and we apply it in a field data set acquired in the Vaca Muerta Formation at Neuquén, Argentina. This methodology enables uncertainty and posterior covariance analysis. By matching the moveouts of the P- and S-wave arrival times, we were able to estimate a 1D velocity model to achieve improved event locations. Various analyses indicate the superiority of this model over a model built with the traditional strategy. With this algorithm, we can perform microseismic monitoring to fracturing treatments in which no perforation data are available. In addition, we can also apply it for long-term passive seismicity reservoir monitoring in which changes of reservoir properties are expected.
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Wilson, Thomas H., Ariel K. Hart, and Pete Sullivan. "Interrelationships of Marcellus Shale gas production to frac-induced microseismicity, interpreted minor faults and fractures zones, and stimulated reservoir volume, Greene County, Pennsylvania." Interpretation 4, no. 1 (February 1, 2016): T15—T30. http://dx.doi.org/10.1190/int-2015-0045.1.
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The data we analyzed are from a Marcellus Shale gas field in Greene County, southwestern Pennsylvania. We first investigated the relationship between microseismic event trends and discontinuities extracted from 3D seismic data and their relationship to [Formula: see text]. This analysis was followed by an examination of the relationship of cumulative gas production to radiated energy, stimulated reservoir volume (SRV), and energy density (ED). We have determined that microseismic event trends observed in multiwell hydraulic fracture treatments were similar to the trends of interpreted small faults and fracture zones extracted from 3D seismic coverage of the area. Hydraulic fracture treatments conducted in six laterals produced clusters of microseismic events with an average trend of N51°E and, to a more limited extent, N56°W. The N51°E microseismic event trend coincided closely with the average N52°E trend of interpreted minor faults and fracture zones extracted from the 3D seismic data. That relationship suggested that microseismic events form through reactivation of old faults and fracture zones in response to an easterly trending [Formula: see text]. We also found that variations in gas production correlated with variations in radiated microseismic energy ([Formula: see text] of 0.985), SRV ([Formula: see text] of 0.974), and ED ([Formula: see text] of 0.989). SRV is a measure of the volume of space occupied by induced microseismicity, whereas energy release per unit volume (ED) can be directly related to rupture area created through hydraulic fracture stimulation. We suggest that ED serves as a better estimator of production potential in unconventional shale reservoirs.
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Pengfei, Lyu, Bao Xinyang, Lyu Gang, and Chen Xuehua. "Research on Fault Activation Law in Deep Mining Face and Mechanism of Rockburst Induced by Fault Activation." Advances in Civil Engineering 2020 (November 30, 2020): 1–13. http://dx.doi.org/10.1155/2020/8854467.
Full textAbstract:
To effectively monitor and control the severe mining-induced rockburst in deep fault area, the fault activation law and the mechanical essence of rockburst induced by crossing fault mining were studied through theoretical analysis, microseismic monitoring, field investigation, and other methods; numerical simulation was employed to verify the obtained fault activation law and the mechanical nature. First, the distribution of microseismic sources at different mining locations and the fault activation degree were analyzed. According to the microseismic frequency and the characteristics of the energy stage, the fault activation degree was divided into three stages: fault stress transfer, fault pillar stress behavior, and fault structure activation. It was determined that the impact disaster risk was the strongest in the stage of the fault pillar stress behavior. Based on the periodic appearance law of microseisms in fault area, three types of conceptual models of fault-type rockburst were proposed, and the rockburst carrier system model of “roof-coal seam-floor” in the fault area was established. The mechanical essence of fault-type rockburst was obtained as follows: under the action of fault structure, the static load of the fault coal pillar was increased and superimposed with the active dynamic load of the fault, leading to high-strength impact disaster. Finally, the prevention and treatment concepts of fault-type rockburst were proposed. The monitoring and prevention measures of fault-type rockburst were taken from two aspects: the monitoring and characterization of fault rockburst and weakening control of the high static load of the fault coal pillar and dynamic load of fault activation. The proposed concepts and technical measures have been verified in the working face 14310 of Dongtan Coal Mine with sound results. The research results have a guiding significance for the prevention and control of rockburst in a similar mining face under crossing fault mining.
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Zhang, Mingwei, Qingbin Meng, Shengdong Liu, and Hideki Shimada. "A Synthetic Solution for Identification and Extraction of the Effective Microseismic Wave Component Using Decomposition on Time, Frequency, and Wavelet Coefficient Domains." Shock and Vibration 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/3875170.
Full textAbstract:
To reduce noise components from original microseismic waves, a comprehensive fine signal processing approach using the integrated decomposition analysis of the wave duration, frequency spectrum, and wavelet coefficient domain was developed and implemented. Distribution regularities of the wave component and redundant noise on the frequency spectrum and the wavelet coefficient domain were first expounded. The frequency threshold and wavelet coefficient threshold were determined for the identification and extraction of the effective wave component. The frequency components between the reconstructed microseismic wave and the original measuring signal were compared. The noise elimination effect via the scale-changed domain decomposition was evaluated. Interaction between the frequency threshold and the wavelet coefficient threshold in the time domain was discussed. The findings reveal that tri-domain decomposition analysis achieves the precise identification and extraction of the effective microseismic wave component and improves the reliability of waves by eliminating the redundant noise. The frequency threshold and the wavelet coefficient threshold on a specific time window are two critical parameters that determine the degree of precision for the identification of the extracted wave component. This research involves development of the proposed integrated domain decomposition method and provides a diverse view on the fine processing of the microseismic signal.