BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Marc Boxberg (RWTH Aachen University) DTSTART:20250825T111500Z DTEND:20250825T120000Z DTSTAMP:20260417T003352Z UID:cam/73 DESCRIPTION:Title: Dat a-Driven Inversion for Ultrasonic Wave Propagation: From Full-Waveform Inv ersion to Gaussian Process Emulation\nby Marc Boxberg (RWTH Aachen Uni versity) as part of CAM seminar\n\nLecture held in MV:L14.\n\nAbstract\nFu ll-waveform inversion (FWI) is a powerful technique for reconstructing sub surface properties from wavefield data\, typically employing adjoint-state methods to compute sensitivity kernels and optimize model parameters. How ever\, in highly attenuative media\, strong energy dissipation complicates backpropagation\, posing challenges for gradient-based optimization metho ds.\nIn this talk\, I will discuss two alternative approaches to wavefield -based inversion\, using ultrasonic laboratory measurements as an example application. First\, I will outline a standard FWI approach utilizing conj ugate-gradient optimization to iteratively refine P-wave velocity and S-wa ve velocity. Second\, I will present a data-driven alternative: a Gaussian process emulator that approximates the misfit function over the parameter space\, enabling efficient inversion without the need for explicit backpr opagation. This approach offers advantages in scenarios where traditional FWI struggles due to high attenuation or limited data coverage. However\, so far\, it has only been tested for determining P- and S-wave velocities as well as attenuation parameters in homogeneous rock samples. I will disc uss potential extensions and applications beyond ultrasonic experiments\, highlighting broader implications for geophysical inversion problems.\n LOCATION:https://researchseminars.org/talk/cam/73/ END:VEVENT END:VCALENDAR