Results 21 to 30 of about 37,745 (280)

Applying deep learning to teleseismic phase detection and picking: PcP and PKiKP cases

Artificial Intelligence in Geosciences
The availability of a tremendous amount of seismic data demands seismological researchers to analyze seismic phases efficiently. Recently, deep learning algorithms exhibit a powerful capability of detecting and picking on P- and S-wave phases.
Congcong Yuan, Jie Zhang
doaj   +2 more sources

Robust Phase Association and Simultaneous Arrival Picking for Downhole Microseismic Data Using Constrained Dynamic Time Warping [PDF]

Sensors
Accurate phase association and arrival time picking are pivotal for reliable microseismic event location and source characterization. However, the complexity of downhole microseismic wavefields, arising from heterogeneous subsurface structures, variable ...
Tuo Wang, Limin Li, Shanshi Wen, Yiran Lv, Zhichao Yu, Chuan He   +5 more
doaj   +2 more sources

Improved methods for hydro-frac event detection and phase picking [PDF]

Global Meeting Abstracts, 2009
The ability to detect small microseismic events and identify their P and S phase arrivals is a key issue in hydraulic fracture monitoring because of the low signal-to-noise ratios. We propose a cross-correlation approach to detect small magnitude events with similar mechanisms and locations as a nearby master event.
Fuxian Song, Sadi H. Kuleli, Nafi M. Toksoz, Haijiang Zhang, Bruce Cornish, John Quirein, Donghong Pei, Steve Zannoni   +7 more
openaire   +2 more sources

Deep Learning Phase Picking of Large-N experiments [PDF]

, 2019
The popularisation of the use of large-N arrays of seismometers has resulted in a significant increase of the size of the datasets recorded during these experiments. Therefore, new challenges have arisen on how to process all these data efficiently, and in an automated fashion.
Fernandez-Prieto, Luis, Villaseñor, Antonio   +1 more
openaire   +4 more sources

A Lightweight Network for Seismic Phase Picking on Embedded Systems

IEEE Access
Phase picking is a critical task in seismic data processing, where deep learning methods have been applied to enhance its accuracy. While lightweight deep learning networks have been optimized for edge computing devices, there is a lack of networks ...
Yadongyang Zhu, Shuguang Zhao, Wei Wei, Fudong Zhang, Fa Zhao   +4 more
doaj   +2 more sources

KVP: a multiscale kurtosis approach for seismic phase picking

Geophysical Journal International
SUMMARY Automatic event detection and phase picking are critical for processing the large volumes of data produced by modern seismological instrumentation. Accurate picking is especially challenging in Distributed Acoustic Sensing (DAS) recordings, where data quality can significantly vary along segments of the fibre due to localized ...
Hugo Latorre, Sergi Ventosa, Arantza Ugalde, Antonio Villaseñor, Rafael Bartolomé, César R Ranero   +5 more
openaire   +3 more sources

Reducing the Parameter Dependency of Phase-Picking Neural Networks with Dice Loss

The Seismic Record
Training a neural network for picking seismic phase arrivals has been commonly posed as a segmentation problem. It is a highly imbalanced segmentation problem in the sense that the background vastly dominates the foreground because we are trying to pick ...
Yongsoo Park, Gregory C. Beroza
doaj   +2 more sources

Development of a Premium Tea-Picking Robot Incorporating Deep Learning and Computer Vision for Leaf Detection [PDF]

Applied Sciences
Premium tea holds a significant place in Chinese tea culture, enjoying immense popularity among domestic consumers and an esteemed reputation in the international market, thereby significantly impacting the Chinese economy.
Luofa Wu, Helai Liu, Chun Ye, Yanqi Wu
doaj   +2 more sources

USTC-Pickers: a Unified Set of seismic phase pickers Transfer learned for ChinaKey points

Earthquake Science, 2023
Current popular deep learning seismic phase pickers like PhaseNet and EQTransformer suffer from performance drop in China. To mitigate this problem, we build a unified set of customized seismic phase pickers for different levels of use in China. We first
Jun Zhu, Zefeng Li, Lihua Fang
doaj   +1 more source

A Date with Telomerase: Pick You Up at S Phase [PDF]

Molecular Cell, 2011
Using the MS2 system for labeling mRNA, in this issue, Gallardo et al. (2011) find that telomere lengthening depends on a stable accumulation of multiple telomerase complexes in late S phase and that this process is temporally regulated by Rif1/2 proteins.
Hocine, S., Singer, R.H.
openaire   +2 more sources