Reduced order models, networks and applications to modeling and imaging with waves (Vladimir Druskin, Cambridge)

02.03.2018 10:30

Geophysical seismic exploration, as well as radar&sonar imaging deals with large scale wave propagation problems. Conventional imaging approaches are often computationally extensive and unreliable. In this talk I will show how the model order reduction can address these issues. In the model order reduction, one approximates response (transfer function) of a largescale dynamic system using a smaller system, known as reduced order model (ROM), that retains certain features of the larger problem. We consider ROMs that can be realized via sparse networks, e.g., mass-spring strings. In particular, I will discuss recent application of such ROMs to multiscale modeling and direct imaging in strongly heterogeneous models with multiple echoes.


salle 17, Séminaire d'analyse numérique

Organisé par

Section de mathématiques


Vladimir Druskin, Schlumberger-Doll Research Center,Cambridge

entrée libre


Catégorie: Séminaire

Mots clés: analyse numérique