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Deep Quake Dynamics: A Multimodal Fault‐Aware Approach to Earthquake Magnitude and Occurrence Time Forecasting

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, Murat Sahin, Furkan Mangir, Alp Baris Beydemir, Cenk Yaltirak, Sule Gunduz Oguducu   +5 more
wiley   +1 more source

A deterministic algorithm for experimental design applied to tomographic and microseismic monitoring surveys [PDF]

, 2004
SUMMARY Most general experimental design algorithms are either: (i) stochastic and hence give different designs each time they are run with finite computing power, or (ii) deterministic but converge to results that depend on an initial or reference ...
Alberto Michelini, Andrew Curtis, Anthony Lomax, Atkinson, Curtis, Curtis, Curtis, Curtis, Curtis, Curtis, David Leslie, Kijko, Maurer, Maurer, Menke, Mitchell, Rabinowitz, Sabatier, Silvey, Smith, Steinberg, Tarantola, Tarantola, van den Berg   +23 more
core   +1 more source

Landslide Activity in the European Alps ‐ Part 1: A Machine Learning Based Instrumental Catalog From the Analysis of Seismological Data

Journal of Geophysical Research: Earth Surface, Volume 131, Issue 4, April 2026.
Abstract Landslides in the European Alps are a growing concern in the context of climate change. However, landslide catalogs for the European Alps remain incomplete, often lacking precise timing and containing few, if any, entries for remote areas.
Charlotte Groult, Clément Hibert, Jean‐Philippe Malet, Anthony Lomax, Floriane Provost   +4 more
wiley   +1 more source

Holocene Normal Faulting in the Southern Rocky Mountain Trench; Orogenic Collapse Modulated by Glacial Unloading?

Journal of Geophysical Research: Solid Earth, Volume 131, Issue 4, April 2026.
Abstract The Southern Rocky Mountain Trench (SRMT) is a conspicuous valley in the eastern Canadian Cordillera. It lies above a sharp change in lithospheric strength and thickness and is occupied by a normal fault thought to have last been active in the Eocene.
T. Finley, E. Nissen, L. J. Leonard, J. F. Cassidy, V. Prush, B. Miller   +5 more
wiley   +1 more source

Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment

IEEE Access, 2018
Microseismic monitoring is widely applied in dams, mines, and various fields of underground engineering. The number of sensors in microseismic monitoring systems is usually very large, which will result in a huge amount of data being produced if the ...
Ran Zhang, Qingsong Hu, Gang Wang, Bin Ye   +3 more
doaj   +1 more source

Evaluating Seismic Ambient Noise Techniques for Imaging Lava Tubes on the Moon

Journal of Geophysical Research: Planets, Volume 131, Issue 4, April 2026.
Abstract Detecting and characterizing lava tubes is a key objective of upcoming lunar missions. While evidence for their presence exists, their precise dimensions and depths remain uncertain. This study evaluates the potential of seismic ambient noise methods, such as seismic interferometry, H/V spectral ratios, distributed acoustic sensing (DAS), and ...
Sabrina Keil, Rok Sesko, Martin Schimmel, Heiner Igel, Philipp Reiss   +4 more
wiley   +1 more source

Space Correlation Constrained Physics Informed Neural Network for Seismic Tomography

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Physics‐informed neural networks (PINNs) integrate physical constraints with neural architectures and leverage their nonlinear fitting capabilities to solve complex inverse problems. Tomography serves as a classic example, aiming to reconstruct subsurface velocity models to improve seismic exploration.
Yonghao Wang, Zhuo Jia, Bowu Jiang, Wenkai Lu   +3 more
wiley   +1 more source

Downhole microseismic monitoring for low signal-to-noise ratio events [PDF]

Journal of Geophysics and Engineering, 2016
Microseismic monitoring plays an important role in the process of hydraulic fracturing for shale gas/oil production. The accuracy of event location is an essential issue in microseismic monitoring. The data obtained from downhole monitoring system usually show a higher signal-to-noise ratio (SNR) than the recorded data from the surface.
Hang Zhou, Wei Zhang, Jie Zhang
openaire   +1 more source

An Effective Physics‐Informed Neural Operator Framework for Predicting Wavefields

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Solving the wave equation is fundamental for many geophysical applications. However, numerical solutions of the Helmholtz equation face significant computational and memory challenges. Therefore, we introduce a physics‐informed convolutional neural operator (CNO) (PICNO) to solve the Helmholtz equation efficiently.
X. Ma, T. Alkhalifah
wiley   +1 more source

Identification of Microseismic Signals in Coal Mine Rockbursts Based on Hybrid Feature Selection and a Transformer

Applied Sciences
Deep learning algorithms are pivotal in the identification and classification of microseismic signals in mines subjected to impact pressure. However, conventional machine learning techniques often struggle to balance interpretability, computational ...
Jizhi Zhang, Hongwei Wang, Tianwei Shi
doaj   +1 more source