Thread: EGU 2017 session: Computational Seismology: From forward to inverse modelling across the scales

Started: 2016-12-01 22:13:02
Last activity: 2016-12-01 22:13:02
Topics: EGU Meetings
Dear colleagues,


We would like to draw your attention to the Computational Seismology session at the 2017 European Geosciences Union General Assembly (EGU).

The aim of the session is to bring seismologists, computational and earth scientists together to discuss on the recent theoretical and technical developments in computational seismology from exploration to global scale. Scientific results from high-performance computations are also welcome. Please see the session description below for more details.

The solicited presenters are:

Alice-Agnes Gabriel (Munich University)
Lion Krischer (ETH Zurich)
Stephen Beller (University of Nice)

EGU will be held on April 23-28, 2017 in Vienna. Please note that the deadline of abstract submission is January 11, 2017.

Best regards,

Ebru Bozdag
Andreas Fichtner
Mike Afanasiev
Christian Boehm
Dave May
Yann Capdeville


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SM7.2/GD8.9
Computational Seismology: From forward to inverse modelling across the scales


This session aims to address the current status and future directions in computational seismology, discuss the scientific outcomes of high-performance forward and inverse simulations as well as the new developments in theory, numerical solvers and HPC systems to better harness the computational resources.

We encourage contributions from seismic modelling across the scales parallel to advancements in high-performance computing highlighting, but not limited to,

- seismic codes on emerging CPU/GPU architectures,
- advancements in forward modelling solvers and numerical techniques,
- large-scale workflows on HPC systems and their automatisation,
- big data (seismic & computational) problems,
- optimisation strategies,
- full-waveform inversion from local to global scales,
- seismological results of HPC applications from passive (earthquakes and noise) and active seismic sources,
- uncertainty analysis for large-scale imaging,
- parallel visualisation, etc.



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