Methods

I create and work intensely with big-data seismic events catalogs and investigate the seismic waveform to determine subsurface structures and earthquake source characteristics. My work builds on top of the scientific open-source software eco-system, predominantly in the Python programming language. I am a strong believer in reproducible research and both employ and share open data and open code.

Earthquake Characterization

I characterize earthquakes in terms of their location, origin time, magnitude and focal mechanism. The resulting earthquake catalogs form the basis for the identification of seismically active structures in the area in question and their interpretation in a tectonic context. The catalogs can be evaluated with statistical or machine learning methods to recognize spatial and temporal patterns of earthquake occurrence and re-occurrence. From the focal mechanisms, I compute the tectonic stress tensor.

Receiver Funcitons

I compute receiver functions form global earthquake seismograms observed at single seismic stations. They hold information about subsurface interfaces and the elastic properties of the units in between. I develop forward and inverse computational methods to retrieve this information using Bayesian statistics.

Seismic Tomography

I compute 3-dimensional images of the subsurface elastic wave speed structure from the arrival times of seismic waves at dense seismic networks. These images can be interpreted in terms of subsurface structure and properties. Combined with the earthquake distribution, they facilitate complex interpretations of tectonic processes.

Petrophysical Modelling

I interpret the elastic properties derived from the receiver functions and seismic tomography in terms of rock types using petrophysical models. These models are based on published laboratory measurements of natural and synthetic rock samples and honor effects of elastic anisotropy, fluid-filled pore-space and changes of elastic properties with pressure and temperature.