Results 71 to 80 of about 5,315,268 (243)

Fracture evolution of a thick soft protection layer and the water inrush mechanism in overburden under longwall mining

Deep Underground Science and Engineering, EarlyView.
Through shear–tensile creep tests and viscoelastic modeling, the fracture evolution of thick soft protective layers is clarified. Results show thickness‐dependent rheological failure modes that govern four types of roof water inrush, providing a mechanism‐based framework for hazard prediction and control. Abstract In the Jurassic coal‐bearing strata of
Mengnan Liu, Wei Qiao, Xianggang Cheng, Xiangsheng Meng, Peichao Feng   +4 more
wiley   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

Full-waveform Based Microseismic Event Detection and Signal Enhancement: The Subspace Approach [PDF]

, 2013
Microseismic monitoring has proven to be an invaluable tool for optimizing hydraulic fracturing stimulations and monitoring reservoir changes. The signal to noise ratio (SNR) of the recorded microseismic data varies enormously from one dataset to another,
Kuleli, Huseyin Sadi, Song, Fuxian, Toksoz, M. Nafi, Warpinski, Norm R.   +3 more
core  

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Denoising Method for Microseismic Signals with Convolutional Neural Network Based on Transfer Learning

International Journal of Computational Intelligence Systems, 2023
Microseismic signals contain various information for oil and gas developing. Increasing the signal-to-noise ratio of microseismic signals can successfully improve the effectiveness of oil and gas resource exploration.
Xuegui Li, Shuo Feng, Yuantao Guo, Hanyang Li, Yingjie Zhou   +4 more
doaj   +1 more source

Monitoring rock freezing and thawing by novel geoelectrical and acoustic techniques [PDF]

, 2016
Automated monitoring of freeze-thaw cycles and fracture propagation in mountain rockwalls is 23 needed to provide early warning about rockfall hazards. Conventional geoelectrical methods 24 such as electrical resistivity tomography (ERT) are limited by ...
Cane, Tim, Krautblatter, Michael, Kuras, Oliver, Murton, Julian B, Schober, Sandra, Tschofen, Dominique, Uhlemann, Sebastian, Watson, Phil   +7 more
core   +1 more source

Integrated processing method for microseismic signal based on deep neural network

Geophysical Journal International, 2020
Denoising and onset time picking of signals are essential before extracting source information from collected seismic/microseismic data. We proposed an advanced deep dual-tasking network (DDTN) that integrates these two procedures sequentially to ...
Hang Zhang, Chun-chi Ma, Yupeng Jiang, Tianbin Li, V. Pazzi, N. Casagli   +5 more
semanticscholar   +1 more source

Data-Driven Signal–Noise Classification for Microseismic Data Using Machine Learning

Energies, 2021
It is necessary to monitor, acquire, preprocess, and classify microseismic data to understand active faults or other causes of earthquakes, thereby facilitating the preparation of early-warning earthquake systems.
Sungil Kim, Byungjoo Yoon, Jungtek Lim, Myungsun Kim   +3 more
semanticscholar   +1 more source

Research on the Laws of Destructive Patterns and Control Measures of Overlying Rock in High‐Efficiency Large‐Scale Mining Faces

Energy Science &Engineering, EarlyView.
With the advancement of coal mining technology driving the development of working faces toward increased mining heights and extended lengths, the enlargement of face dimensions has led to expanded overlying strata failure zones and intensified ground pressure manifestations. Consequently, traditional methods for determining hydraulic support resistance
Chen Gong, Peilin Gong, Kang Yi, Kaijie Duan, Lizhu Liu, Peng Li   +5 more
wiley   +1 more source

Time difference of arrival estimation of microseismic signals based on alpha-stable distribution [PDF]

Nonlinear Processes in Geophysics, 2018
Microseismic signals are generally considered to follow the Gauss distribution. A comparison of the dynamic characteristics of sample variance and the symmetry of microseismic signals with the signals which follow α-stable distribution reveals that ...
R.-S. Jia, R.-S. Jia, Y. Gong, Y. Gong, Y.-J. Peng, Y.-J. Peng, H.-M. Sun, H.-M. Sun, X.-L. Zhang, X.-L. Zhang, X.-M. Lu, X.-M. Lu   +11 more
doaj   +1 more source