Results 161 to 170 of about 3,083 (240)

Understanding the Robustness of Reparameterized Full‐Waveform Inversion Through Loss Landscape Perspective: Application to VSP Data

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Full waveform inversion (FWI) reconstructs subsurface models by minimizing the mismatch between observed and simulated seismic data. However, the strong nonlinearity of the inversion problem makes gradient‐based optimization highly sensitive to inaccurate initial models and incomplete observational data.
Ning Wang, Ying Shi, Bingchuan Geng, Xuan Ke   +3 more
wiley   +1 more source

Multi-scale dual-path attention network for seismic background noise attenuation. [PDF]

Sci Rep
Han L, Wang D, Li F.
europepmc   +1 more source

Synthetic Seismic Data Generation for Deep Learning Segmentation of Clinoforms: Integrating Process‐Based Forward Stratigraphic Modelling and Ray‐Based Seismic Modelling

Basin Research, Volume 38, Issue 4, July–August 2026.
This study aims to develop a deep learning model for automated clinoform segmentation. The trained model achieved high segmentation performance on a synthetic testing dataset and successfully generalised to real seismic profiles. The proposed approach demonstrates the effectiveness of using forward stratigraphic modelling and point spread function for ...
Waleed AlGharbi, Rebecca E. Bell, Cédric John   +2 more
wiley   +1 more source

Directional adaptive mode total variation for seismic data denoising. [PDF]

Sci Rep
Banjade TP, Zhou C, Yang Y, Li H, Deng J.   +4 more
europepmc   +1 more source

Seismic Risk of Critical Transport Systems: Sensitivity Analysis of the Campania Railway Network to Bradyseism's Features

Risk Analysis, Volume 46, Issue 8, August 2026.
ABSTRACT This study examines the impact of epistemic uncertainties on the seismic risk of a critical transport system, the Campania railway network, during the ongoing bradyseismic unrest at Campi Flegrei, south of Italy. Seismic risk is quantified as the length of the railway requiring post‐event inspection, an operational proxy for service disruption.
Raffaele De Risi, Francesco Pugliese, Jitendra Agarwal, Francisco Pinto   +3 more
wiley   +1 more source

Long period quakes linked to Mefite D'Ansanto (Italy) mantellic CO₂ emissions. [PDF]

Sci Rep
Cusano P, Morabito S, Petrosino S, Nardone L.   +3 more
europepmc   +1 more source

Insights Into Magmatic Degassing, Hydrothermal Dynamics, and Eruption Precursors From Long Term SO2 Emission Monitoring at Whakaari/White Island, New Zealand

Geophysical Research Letters, Volume 53, Issue 14, 28 July 2026.
Abstract Long‐term SO2 emission rate time series are critical for deciphering the subsurface processes regulating open‐vent volcanoes, yet extracting cyclical drivers from continuous degassing records remains challenging. We analyze a 14‐year (2006–2020) SO2 emission rate data set from Whakaari/White Island, New Zealand, identifying five chronological ...
A. Mazot, C. Miller, K. Britten, B. Scott, G. Kilgour, Cynthia Werner   +5 more
wiley   +1 more source

Anomalous dynamic response and micro-zonation of saline sabkha soils of eastern Saudi Arabia using 3D seismic behavior modelling. [PDF]

Sci Rep
Fayyaz M, Al-Shayea NA, Waheed MA, Abduljauwad SN, Ahmed HU.   +4 more
europepmc   +1 more source

Tsunami Traveling Ionospheric Disturbances Triggered by the 29 July 2025 Mw 8.8 Kamchatka Earthquake Observed in Japan and Taiwan

Geophysical Research Letters, Volume 53, Issue 14, 28 July 2026.
Abstract The 29 July 2025 Mw 8.8 Kamchatka earthquake generated notable seismic and tsunami waves. The total electron content (TEC) derived by more than 1,400 ground‐based global navigation satellite system (GNSS) receiving stations in Japan and Taiwan is employed to examine the spatiotemporal evolution of seismic‐ and tsunami‐traveling ionospheric ...
Chun‐Yen Huang, Jann‐Yenq Liu, Chi‐Yen Lin, Tatsuhiro Yokoyama, Kenji Satake, Tien‐Chi Liu, Tung‐Yuan Hsiao, Charles Chien‐Hung Lin, Chia‐Hung Chen   +8 more
wiley   +1 more source

Tsunamigenic fault structures revealed in the 2024 Noto earthquake (M7.6) rupture area. [PDF]

Sci Rep
Park JO, Mohammadigheymasi H, Yamaguchi A, Okino K, Fujie G, Jamali Hondori E, Arikawa T, Kurihara T, Imai K.   +8 more
europepmc   +1 more source