Results 101 to 110 of about 4,586 (215)
Investigation of microseismic signal denoising using an improved wavelet adaptive thresholding method. [PDF]
Sci Rep, 2022 Zhang Z, Ye Y, Luo B, Chen G, Wu M.
europepmc +1 more source
Detection and monitoring of high stress concentration zones induced by coal mining using numerical and microseismic method [PDF]
, 2001 Zones of high stress concentration induced by coal mining at a depth of 1250 meters in the Lorraine Collieries are detected and monitored using a combination of numerical and microseismic methods.
Al Heib, Marwan +3 more
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Shock and Vibration, 2019 An experiment designed to simulate coal during excavation was conducted. Microseismic signals of coal under vibration conditions during excavation and subsequent waiting time of the coal roadway at different excavation speeds were collected and analyzed.
Qifei Wang +5 more
doaj +1 more source
Efforts were made to determine the seismicity of Mars as well as define its internal structure by detecting vibrations generated by marsquakes and meteoroid impacts.
Anderson, D. L. +9 more
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Semi-automatic detection and localization of microseismicity induced by a "salt dissolution provoked" cavity collapse [PDF]
, 2013 Natural underground cavities, active or abandoned mine workings, particularly when they are shallow, can provoke large scale land subsidence and collapses attended by catastrophic social-economic impacts.
Bernard, Pascal +5 more
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Multi-channel microseismic signals classification with convolutional neural networks
IAES International Journal of Artificial Intelligence (IJ-AI)Identifying and classifying microseismic signals is essential to warn of mines’ dangers. Deep learning has replaced traditional methods, but labor-intensive manual identification and varying deep learning outcomes pose challenges. This paper proposes a transfer learning-based convolutional neural network (CNN) method called microseismic signals ...
Hongmei Shu +4 more
openaire +1 more source
IEEE Access, 2018 Reliable detection and recovery of a microseismic event in large volume of passive monitoring data is usually a challenging task due to the low signal-to-noise ratio environment.
Naveed Iqbal +5 more
doaj +1 more source
Shock and Vibration, 2017 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 ...
Mingwei Zhang +3 more
doaj +1 more source
Siamese Unsupervised Clustering For Removing Uncertainty In Microseismic Signal Labelling
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing SymposiumThe labelling of large seismic datasets is a challenging problem. Currently the methods most favoured by geoscientists are based on well known geophysical properties with STA/LTA ratio pickers remaining highly trusted to generate results which can be quickly attributed due to their ability to pick relatively high Signal to Noise Ratio (SNR) events with
Murray, David +2 more
openaire +2 more sources
Seismic imaging of hydraullically-stimulated fractures: A numerical study of the effect of the source mechanism [PDF]
, 2012 We present a numerical study of seismic imaging of hydraulically stimulated fractures using a single source from an adjacent fracturing-process. The source is either a point force generated from the perforation of the casing of the well or a double ...
Bakku, Sudhish Kumar +3 more
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