Seismology

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Overview

Seismology studies how seismic waves reveal Earth’s interior and how earthquakes and ground motion develop, supporting hazard assessment, exploration, and monitoring. Work combines physical methods such as phase picking, tomography, moment-tensor inversion, and wave-equation simulation with neural networks, transformers, self-supervised learning, and generative models for detection, denoising, prediction, and subsurface imaging. Evaluation spans earthquake catalogs and regional or teleseismic records, synthetic wavefields and velocity models, field surveys, and sparse sensor arrays, with probabilistic inference used to quantify uncertainty. A central challenge is making data-driven systems reliable across regions, instruments, geology, and noise while preserving physical consistency and signal fidelity, especially when labeled field data are scarce.

Latest papers

CardsList

43 papers5 papers in the last four weeks, up 25% on the four weeks before. 0.0% of all new papers.

  1. HypoNet Nankai PS: rapid hypocenter determination for the Nankai Trough using physics-informed neural networks with three-dimensional P- and S-wave velocity models

    Oct 20, 2026Ryoichiro Agata, Ayako Nakanishi, Dan Bassett +3SeismologyPhysics-Informed ML

    Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Japan · Earth Sciences New Zealand, New Zealand · Faculty of Sciences, Kyushu University, Japan

  2. Event-Centric Earthquake Monitoring with a Multi-Station Transformer

    Oct 12, 2026Haoyu Wang, Weiqiang ZhuSeismology

    Department of Earth & Planetary Science, University of California, Berkeley · Berkeley Seismology Laboratory, University of California, Berkeley

  3. An AI-assisted conditioning and geological interpretation workflow for usage in implicit geological modeling

    Oct 7, 2026Stefan Carpentier, Jan Diederik van Wees, Eva de Boever +5Seismology

    TNO Netherlands Organisation for Applied Scientific Research · Fraunhofer IEG, Fraunhofer Institution for Energy Infrastructures and Geotechnologies, IEG, Aureliusstr. 2, 52062 Aachen, Germany

  4. Real-world application of deep learning in large-scale seismic interference attenuation: A case study in the Camie field of Angola

    Oct 7, 2026Jing Sun, Song HouSeismology

    Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, Van Mourik Broekmanweg 6, Delft 2628 XE, The Netherlands. · VIRIDIEN (UK) Ltd, Crompton Way, Manor Royal Estate, Crawley, West Sussex RH10 9QN, UK.

  5. Physical Cross-Modal Masked Autoencoding for Seismic-to-Well Representation Learning

    Sep 28, 2026Meher Gajula, Keyla Gonzalez, Ben Lasscock +1Cross-Modal Representation LearningRepresentation Learning

  6. Seismic Site Response Prediction from Sparse Observations Using Finite-Element-Pretrained Latent Dynamics

    Sep 17, 2026Yi Zhu, Su Chen, Xiaojun LiNeural Surrogate ModelingLatent Dynamics Modeling

    State Key Laboratory of Bridge Safety and Resilience, Beijing University of Technology Beijing 100124, China

  7. Should All Noises Be Treated Equally: Impact of Input Noise Variability on Neural Network Robustness

    Sep 13, 2026Salma Alsinan, Maksim Makarenko, Sixiu Liu +2Noise RobustnessOOD Generalization

    King Abdullah University of Science and Technology, Saudi Arabia · Aramco Upstream Research Center at KAUST, Saudi Arabia · EXPEC Advanced Research Center, Aramco, Saudi Arabia

  8. Solving the Elastic Wave Equation with Physics-Informed Neural Networks: A Robust and Critical Assessment

    Sep 7, 2026Davide Staub, Ben MoseleyNeural PDE SolversPhysics-Informed ML

    Department of Mathematics, ETH Zürich

  9. SeisBench DAS: A machine learning framework for Distributed Acoustic Sensing

    Sep 7, 2026Jannes Münchmeyer, Han Xiao, Frederik TilmannDistributed Acoustic SensingScientific ML

    GFZ Helmholtz Centre for Geosciences · Institute for Geological Sciences, Freie Universität Berlin, Berlin, Germany

  10. SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning

    Aug 25, 2026Quenton Yeo, Zhaoge Bi, Linghan Huang +3SeismologyMamba

    The University of Sydney Sydney, Australia · Accenture Sydney, Australia · The University of New South Wales Sydney, Australia

  11. SeisEvo: Evolution of Seismic Data Reconstruction Algorithms by Agents

    Aug 18, 2026Yingjie Xu, Siwei Yu, Jianwei MaAutomated Algorithm DiscoverySeismology

    School of Mathematics and Center of Geophysics, Harbin Institute of Technology, Harbin, Heilongjiang, China · Department of Mathematics, National University of Singapore, Singapore · School of Earth and Space Sciences, Peking University, Beijing, China

  12. Voxel-based 3D Facies Segmentation from Seismic Data: A Comparative Study

    Aug 14, 2026Duc-Thanh Pham, Minh-Tan Pham, Anh Nguyen +13D Semantic SegmentationSeismology

    FPT Software AI Center, Hanoi, Vietnam · Institut de Recherche en Informatique et Syst`emes Al´eatoires (IRISA), UMR 6074, Universit´e Bretagne Sud, 56000 Vannes, France · Department of Computer Science, University of Liverpool, Liverpool, United Kingdom

  13. Consensus-gated Multi-Agent Neural Architecture Search for Seismic Fault Segmentation

    Aug 14, 2026Shehram Baig, Ahmad MustafaNeural Architecture SearchLarge Language Model-Guided NAS

    Information Technology University (ITU), Lahore, Pakistan · King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

  14. Automatic Knowledge Graph Construction and Query for Earthquake Catalogs

    Jul 27, 2026Yuxin Zhou, Huai Zhang, S. Mostafa MousaviKG ConstructionGraph Retrieval-Augmented Generation

    State Key Laboratory of Earth System Numerical Modeling and Application, College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China · Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA 02138, USA

  15. Juxtaposition of Shallow Reservoir-Triggered Seismicity and Deep Tectonic Locking in the Qiaojia-Dongchuan Seismic Gap

    Jul 21, 2026Yuxin Zhou, Huai Zhang, S. Mostafa Mousavi +5Seismology

    State Key Laboratory of Earth System Numerical Modeling and Application, College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China 100049. · Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA 02128, USA

  16. Joint Velocity Slope Diffusion Prior for Structurally Constrained Velocity Model Building

    Jul 6, 2026Francesco Brandolin, Tariq AlkhalifahSeismologyDiffusion Posterior Sampling

    King Abdullah University of Science and Technology (KAUST) Thuwal, Kingdom of Saudi Arabia

  17. Generative wave propagator

    Jul 5, 2026Shijun Cheng, Tariq AlkhalifahPDE Surrogate ModelingOne-Step Generative Modeling

    Division of Physical Science and Engineering King Abdullah University of Science and Technology Thuwal 23955-6900, Saudi Arabia

  18. Probabilistic Inversion with Flow Matching

    Jun 30, 2026Baldur Paulwitz, Stefan BuskeFlow MatchingBayesian Inverse Problems

    Institute of Geophysics and Geoinformatics, TU Bergakademie Freiberg

  19. Bayesian three-dimensional seismic travel-time tomography for active- and passive-source seismic data using physics-informed neural network

    Jun 19, 2026Ryoichiro Agata, Kazuya Shiraishi, Gou Fujie +1Uncertainty QuantificationBayesian Inverse Problems

    Japan Agency for Marine-Earth Science and Technology · Earth Science New Zealand

  20. Contrastive Learning for Seismic Horizon Tracking with Domain-Specific Priors

    Jun 15, 2026Alexandre Thouvenot, Lionel Boillot, Vincent GriponContrastive Learning3D Representation Learning

    IMT Atlantique, LAB-STICC, UMR CNRS 6285, F-29238 Brest, France · TotalEnergies, OneTech, 64000 Pau, France

  21. Learning Earthquake Wave Arrival Time Picking from Labels with Inaccuracies

    Jun 13, 2026Sen Li, Xu Yang, S. Mostafa Mousavi +5Contrastive LearningSeismology

    Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA. · School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu, China · School of Mines, China University of Mining and Technology, Xuzhou, Jiangsu, China +1

  22. When Do Autoregressive Sequence Models Forecast Physical Wavefields? A Controlled Study on Synthetic Seismograms

    Jun 9, 2026Waleed Esmail, Stuart Russell, Jana Klinge +2Multi-Token PredictionSeismology

    Institut für Kernphysik, Universität Münster Wilhelm-Klemm-Straße 9, 48149 Münster, Germany · Institut für Geophysik, Universität Münster Corrensstraße 24, 48149 Münster, Germany · James Cook University, 1 James Cook Drive, Douglas, QLD 4814, Australia +1

  23. Using Seismic Statistical Features and VQ-VAE to Improve Spatiotemporal Seismicity Predictability

    Jun 8, 2026Wei Quan, Denise GorseVector-Quantized Variational AutoencoderSeismology

    Department of Computer Science University College London

  24. Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures

    Jun 1, 2026Waleed Esmail, Stuart Russell, Jana Klinge +2Multivariate Time Series ForecastingTime Series Forecasting

    Institut für Kernphysik, Universität Münster, Wilhelm-Klemm-Straße 9, 48149, Münster · Institut für Geophysik, Universität Münster, Corrensstraße 24, 48149, Münster · James Cook University, 1 James Cook Drive, Douglas, Queensland, 4814, Australia +1

  25. SubsurfaceGen: Procedural Generation of Field-Scale Earth Models and Seismic Data

    May 28, 2026Joseph Stitt, Pratik Rathore, Madeleine Udell +1Synthetic Data GenerationPDE Surrogate Modeling

    Stanford University

  26. MULTISEISMO: A Multimodal Seismic Dataset and Model for Cross-Modal Seismic Understanding

    May 25, 2026Sai Munikoti, Ian Stewart, Chengping Chai +4Multimodal ReasoningSeismology

    Pacific Northwest National Laboratory (PNNL), Richland, WA 99354 USA · Oak Ridge National Laboratory (ORNL), Oak Ridge, TN 37830 USA · Sandia National Laboratory (SNL), Albuquerque, NM 87123 USA +1

  27. Evaluating Neural Probabilistic Forecasts of Sparse Earthquake Counts: What Survives a Careful Evaluation

    May 20, 2026Alim IgilikProbabilistic ForecastingSeismology

    [physics.geo-ph]

  28. OpenSeisML: Open Large-Scale Real Seismic and well-log Dataset for Generative AI

    May 19, 2026Ipsita Bhar, Huseyin Tuna Erdinc, Thales Souza +2Synthetic Data GenerationTraining Data Curation

    Georgia Institute of Technology, Atlanta, USA · Osokey Ltd, Henley-on-Thames, UK

  29. Deploying Self-Supervised Learning for Real Seismic Data Denoising

    May 11, 2026Giovanny A. M. Arboleda, Claudio D. T. de Souza, Carlos E. M. dos Anjos +6Self-Supervised Image DenoisingSelf-Supervised Learning

    COPPE Federal University of Rio de Janeiro Rio de Janeiro, Brazil · CENPES, Petrobras Rio de Janeiro, Brazil

  30. Total Generalized Variation regularization closes the gap between neural-eld and classical methods in seismic travel-time tomography

    May 11, 2026Isao KurosawaSeismologyPDE Inverse Problems

    IVXA, Japan.