Imaging what is inaccessible to direct observation, based on elastic waves, is a major issue with a wide range of applications of high societal and economic impact. In this project we aim at drastically improving the resolution of seismic tomography to produce enhanced finely-resolved images in a domain with such high societal and economic interest: regional seismological tomography at unprecedented resolution, in particular for passive seismic acquisition by dense arrays. We go beyond classical passive imaging approaches such as ambient noise tomography or receiver function migration, by performing high-frequency full waveform imaging of the shallow or deep Earth, to help investigate the deep roots of continental orogens or the extended fault sources of large earthquakes. To achieve this goal, we extend our imaging techniques to high frequencies, and derive data-driven simulation schemes and novel techniques for highly unstructured irregular problems in high-performance computing.
One of the ground-breaking steps that we propose is to abandon typical approximations in wave propagation models, and refuse to lose accuracy in images because the cost incurred is considered unaffordable. Another is to include the full contribution of shear waves; in recent preliminary but promising results we have shown that this can sometimes lead to a ten-fold resolution increase locally. To do so we will address two methodological gaps jointly: developing improved hybrid calculation techniques, and using well designed and tuned high-performance data-driven computing approaches for unstructured and/or imbalanced problems. Their combined use is an innovative concept, which opens a new avenue of research in the targeted application.
A few groups worldwide, including ours, have recently targeted the largest supercomputers in the world to perform high-resolution inversions of seismological datasets. For instance, J. Tromp at Princeton (USA), in collaboration with us, uses the second largest machine in the world to perform seismic imaging of the whole Earth, and with E. Casarotti of INGV (Italy) we pursue a PRACE European project to do imaging of the whole country of Italy on the largest European machine. Even if impressive, this is not usable by the whole community on a daily basis because most geophysicists do not have access to such largest machines, and if so they would need to use them for years in a row anyway (and would likely lack the experience and/or time to do so). In this project our approach is thus the opposite: we purposely want to target standard regional or national computing centers of moderate size that are easily accessible (so-called Tier-2 machines, maybe Tier-1 in a transition period) and design flexible and semi-automated inversion workflows with quality-control metrics for them, so that the community can use them in daily research, not only a few groups worldwide. The set of imaging tools that we will develop, analyze and implement will be based on data-driven high-performance computing techniques, in particular the orchestration, marshalling and coordination of the involved huge amounts of data. The project thus bridges the fields of data analytics and high-performance computing, which has been identified as a major challenge for the coming years.
The expected scientific impact is high because we propose a new paradigm in the field of imaging methods. This paradigm will bring these tomographic problems to physical resolutions that have never been accessible before. If successful, the proposal can also be a breakthrough with mid-term consequences on industrial applications because highly-accurate tomographic images are of crucial importance for exploration of energy resources e.g. in the oil industry. The expected societal impact is also high because we will help develop new capabilities to monitor populated areas to assess their safety, and also study the source of large earthquakes.
Monsieur Vadim MONTEILLER (Centre National de recherche Scientifique Délégation Provence et Corse _ Laboratoire de Mécanique et d'Acoustique)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
IANS Institute of Applied Analysis and Numerical Simulation (IANS)
CNRS - GET Centre National de la Recherche Scientifique- Géosciences Environnement Toulouse (GET)
CNRS DR12_LMA Centre National de recherche Scientifique Délégation Provence et Corse _ Laboratoire de Mécanique et d'Acoustique
Help of the ANR 341,622 euros
Beginning and duration of the scientific project: December 2017 - 36 Months