Seismic inversion in the presence of noise

Bjorn Engquist (U of Texas, Austin)

May 17. 2022, 14:00 — 14:45

Seismic inversion is the process of using measurements of seismic waves on the surface of the earth to determine geophysical properties of the subsurface. This process is marginally ill-posed and naturally noise play an important role. We will analyze this role in the context of uncertainty quantification, Bayesian and frequency-based analysis. The particular setting we will consider is the recently popular, so-called Full Waveform Inversion, which in mathematical terms is PDE-constrained optimization. The objective or loss function in the optimization measures the mismatch between data and a forward wave equation. We will consider Sobolev norms and the Wasserstein metric from optimal transport to measure this mismatch.

Further Information
ESI Boltzmann Lecture Hall
Associated Event:
Computational Uncertainty Quantification: Mathematical Foundations, Methodology & Data (Thematic Programme)
Clemens Heitzinger (TU Vienna)
Fabio Nobile (EPFL, Lausanne)
Robert Scheichl (U Heidelberg)
Christoph Schwab (ETH Zurich)
Sara van de Geer (ETH Zurich)
Karen Willcox (U of Texas, Austin)