Results 61 to 70 of about 6,541 (225)
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
Shoufeng Tang, Minming Tong, Xinmin He
doaj +1 more source
Energy Science &Engineering, EarlyView.Mining disturbance tends to trigger fault stick‐slip instability and induce disasters. This paper establishes a mechanical model to propose a critical criterion, which is verified to be reliable via FLAC3D, providing a theoretical basis for early warning of fault slip disasters.
Bowen Wu, Yanhui Li
wiley +1 more source
Key Criteria for a Successful Microseismic Project [PDF]
, 2010 As microseismic monitoring expands, a wide variety of monitoring configurations have evolved including vertical, horizontal and deviated observation wells as well as surface and near-surface monitoring.
L.. Bennett +4 more
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Transfer Learning and Benchmarking for Induced Seismic Event Detection: Insights From Oklahoma
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.Abstract Machine learning models for microseismicity detection are often limited by the scarcity of large and high‐quality labeled data sets in many regions. To address this need, we introduce the Oklahoma Labeled AI Dataset (OKLAD), a manually curated data set compiled by the Oklahoma Geological Survey (OGS).
Hongyu Xiao +7 more
wiley +1 more source
Classification of Microseismic Signals Using Machine Learning [PDF]
The classification of microseismic signals represents a fundamental preprocessing step in microseismic monitoring and early warning. A microseismic signal source rock classification method based on a convolutional neural network is proposed.
Yi Cui +6 more
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Are microseismic ground displacements a significant geomorphic agent? [PDF]
, 2014 This paper considers the role that microseismic ground displacements may play in fracturing rock via cyclic loading and subcritical crack growth. Using a coastal rock cliff as a case study, we firstly undertake a literature review to define the spatial ...
Rosser, Nicholas J. +3 more
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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
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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
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Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.Abstract We develop a sensitivity‐guided, surrogate‐assisted Bayesian framework to infer fracture network parameters from elastic waves. Synthetic fracture networks characterized by power‐law length exponent a $a$, fracture density d $d$, and percolation parameter p $p$ are constructed.
Le Zhang +4 more
wiley +1 more source
The Application and Prospect of Microseismic Technique in Coalmine [PDF]
, 2012 Microseismic monitoring technique has been developed for more than 50 years, and has successfully found it application in underground construction, tunnel, reservoir dam, oil production and so on.
Zhu, Shujie, Cheng, Jianyuan, Qin, Si
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