Results 11 to 20 of about 24,569,148 (220)
A Nonparametric Method for Automatic Denoising of Microseismic Data [PDF]
Shock and Vibration, 2018 Noise suppression or signal-to-noise ratio (SNR) enhancement is often desired for better processing results from a microseismic dataset. In this paper, we proposed a nonparametric automatic denoising algorithm for microseismic data.
Pingan Peng, Liguan Wang
doaj +3 more sources
Decision Tree Model for Rockburst Prediction Based on Microseismic Monitoring
Advances in Civil Engineering, 2021 Rockburst is an extremely complex dynamic instability phenomenon for rock underground excavation. It is difficult to predict and evaluate the rank level of rockburst in practice.
Hongbo Zhao, Bingrui Chen, Changxing Zhu
doaj +2 more sources
Sensors, 2021 Due to the complexity of the various waveforms of microseismic data, there are high requirements on the automatic multi-classification of such data; an accurate classification is conducive for further signal processing and stability analysis of ...
Hang Zhang +5 more
doaj +2 more sources
Energies, 2023 Microseismic monitoring has become a well-known technique for predicting the mechanisms of rock failure in deeply buried energy exploration, in which noise has a great influence on microseismic monitoring results.
Shibin Tang +4 more
doaj +2 more sources
Resonance in downhole microseismic data and its removal [PDF]
International Meeting for Applied Geoscience & Energy, 2016 We identified resonance due to poor geophone-borehole coupling in downhole microseismic data and proposed to use spiking deconvolution and relative spectrum analysis to remove its effect. The resonance may hinder the arrival time picking and contaminate microseismic waveform spectrum.
Zhang, Z, Rector, JW, Nava, MJ
openaire +5 more sources
Applied Sciences (Switzerland), 2023 Based on the relationship between rockburst and microseismic event indicators, this study proposes that the risk of rockburst in mine working faces, roadways, and even the entire mine should be studied through the “double high” risk evaluation of ...
Xuelong Li, Deyou Chen, Shumin Liu
exaly +3 more sources
Deep Neural Networks for Detection and Location of Microseismic Events and Velocity Model Inversion From Microseismic Data Acquired by Distributed Acoustic Sensing Array [PDF]
Sensors, 2021 Roman Pevzner +2 more
exaly +2 more sources
Research on computational propagation and identification of mine microseismic signals based on deep learning. [PDF]
PLoS ONEIn the mining field, hydraulic fracturing of coal - seam boreholes generates a large number of weak microseismic signals. The accurate identification of these signals is crucial for subsequent positioning and inversion.
Dongmei Liu +7 more
doaj +2 more sources
Historic microseismic data and their relation to the wave-climate in the North Atlantic
Meteorologische Zeitschrift, 2005 Microseismic data from observatories in Europe, which have been continuously recorded since about 100 years, contain information on the wave-climate in the North Atlantic. They can potentially be used as additional constraints in high-resolution temporal
Torsten Dahm +3 more
doaj +2 more sources
工程科学学报, 2021 With the gradual transition of coal mining to deep mining, the number and intensity of rock burst events in the deep mining process are gradually increasing.
Yan-yu PEI +5 more
doaj +1 more source