Results 61 to 70 of about 15,161 (215)
Seismic phase picking, which aims to determine the arrival time of P- and S-waves according to seismic waveforms, is fundamental to earthquake monitoring. Generally, manual phase picking is trustworthy, but with the increasing number of worldwide stations and seismic monitors, it becomes more challenging for human to complete the task comprehensively ...
Wang, Yuchen, Wang, Ruihuan
openaire +2 more sources
Geoscience Data Journal, Volume 13, Issue 2, April 2026.EQMT integrates earthquake catalog data, fault‐network geometry, engineered features, and graph embeddings in a unified framework for forecasting earthquake magnitude and occurrence time. The framework is designed to reflect inter‐fault spatial dependencies together with temporal seismic patterns, addressing limitations of approaches based only on ...
Kiymet Kaya +5 more
wiley +1 more source
Annals of Geophysics, 2004 We performed an analysis of refraction data recorded in Italy since 1968 in the frame of the numerous deep seismic sounding and wide-angle reflection/refraction projects.
R. Tondi +4 more
doaj +1 more source
Velocity estimation via registration-guided least-squares inversion [PDF]
, 2013 This paper introduces an iterative scheme for acoustic model inversion where the notion of proximity of two traces is not the usual least-squares distance, but instead involves registration as in image processing.
Baek, Hyoungsu +2 more
core +3 more sources
Near Surface Geophysics, Volume 24, Issue 2, Page 170-186, April 2026.Abstract This study presents a methodological framework for estimating electromagnetic wave velocities in ground‐penetrating radar (GPR) data based exclusively on the analysis of diffractions. The approach integrates diffraction separation using the plane wave destruction algorithm and subsequent velocity refinement through the residual diffraction ...
Ian E. Vogado +3 more
wiley +1 more source
地震科学进展Based on 778 earthquakes (2009—2022) and their observation reports recorded by the Hunan Seismic Network, through the analysis of the cross-correlation of the waveforms, 149 repeated earthquake pairs were identified which were recorded at least 3 ...
Qiyun Yan +6 more
doaj +1 more source
Reservoir management optimization: case study of an oil rim located in the Gulf of Guinea comparing dynamic simulation of low cost smart wells with conventional wells [PDF]
, 2011 Imperial Users ...
Toure - Vuillemet, Mariama +1 more
core
Recognition and reconstruction of coherent energy with application to deep seismic reflection data [PDF]
, 2000 Reflections in deep seismic reflection data tend to be visible on only a limited number of traces in a common midpoint gather. To prevent stack degeneration, any noncoherent reflection energy has to be removed.
Paul, A., Van der Baan, M.
core +1 more source
Seismic $P$ Phase Picking Using a Kurtosis-Based Criterion in the Stationary Wavelet Domain [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2008 The seismic P phase first arrival identification is a fundamental problem in seismology. The accurate identification of the P-wave first arrival is not a trivial process, particularly when the seismograms present a very low signal-to-noise ratio (SNR) or are contaminated with artificial transients that could produce false alarms.
Galiana-Merino JJ +2 more
openaire +5 more sources
FocoNet: Transformer‐Based Focal‐Mechanism Determination
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.Abstract Traditional focal‐mechanism determination primarily relies on fitting the first‐motion polarities with grid‐search algorithms. We developed a machine‐learning model, FocoNet, to include more seismic information into focal mechanism determination.
Xiaohan Song +3 more
wiley +1 more source