Results 31 to 40 of about 5,383,519 (211)
Recognition of Microseismic and Blasting Signals in Mines Based on Convolutional Neural Network and Stockwell Transform [PDF]
IEEE Access, 2020 The microseismic monitoring signals which need to be determined in mines include those caused by both rock bursts and by blasting. The blasting signals must be separated from the microseismic signals in order to extract the information needed for the ...
Jiulong Cheng +5 more
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Sustainability, 2023 The purpose of denoising microseismic mine signals (MMS) is to extract relevant signals from background interference, enabling their utilization in wave classification, identification, time analysis, location calculations, and detailed mining feature ...
Quanjie Zhu +5 more
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The Optimum Wavelet Base of Wavelet Analysis in Coal Rock Microseismic Signals
Advances in Mechanical Engineering, 2014 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
Xinmin He, Shoufeng Tang, Minming Tong
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Automated Platform for Microseismic Signal Analysis: Denoising, Detection, and Classification in Slope Stability Studies [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2021 Microseismic monitoring has been increasingly used in the past two decades to illuminate (sub)surface processes such as landslides, due to its ability to record small seismic waves generated by soil movement and/or brittle behaviour of rock ...
Jiangfeng Li +2 more
exaly +1 more source
Detection and location of microseismic events with low signal-to-noise ratios
International Petroleum Technology Conference, 2014 Microseismic monitoring of hydraulic fractures is the process of monitoring the small earthquakes induced by fluid injection during hydraulic fracture stimulation. The primary goal of microseismic monitoring is to map the source positions of microseismic
Jing Yu +9 more
core +2 more sources
Downhole microseismic signal denoising via empirical wavelet transform and adaptive thresholding
Journal of Geophysics and Engineering, 2018 Downhole microseismic data have the characteristics of low signal-to-noise ratio and high frequency, which pose a major challenge to noise attenuation.
Yue Li, Zhihong Qian, Qian Zhihong
exaly +2 more sources
IEEE Access, 2019 Aiming at the situation that complementary ensemble empirical mode decomposition (CEEMD) noise suppression method may produce redundant noise and wavelet transform easily loses high-frequency detail information, considering wavelet packet transform can ...
Ling-Qun Zuo +4 more
semanticscholar +3 more sources
First-Arrival Picking for Microseismic Monitoring Based on Deep Learning
International Journal of Geophysics, 2021 In microseismic monitoring, achieving an accurate and efficient first-arrival picking is crucial for improving the accuracy and efficiency of microseismic time-difference source location.
Xiaolong Guo
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Geophysics, 2016 Detection and arrival picking of microseismic events with low signal-to-noise ratios (S/N) are problematic because these events are usually obscured by ambient noise.
Yuyang Tan
exaly +2 more sources
Dynamic model of microseismic signal transformation
Mining Journal of Kryvyi Rih National UniversityA.V. Bakai, B.I. Rybalko
openaire +2 more sources