– Normal mode based tomography
– Seismic imaging of the Earth’s core
– Observation of mantle discontinuities
– Interpretation of seismology in terms of mineral physics and fluid dynamics
– Regional surface wave seismology
– Induced seismicity
– Deep Earth
Coordination NARS network.
– Inverse theory
– Advanced processing of seismic data using machine learning
– (Numerical) wave propagation in complex media
– Full waveform inversion
– Thermo-chemical interpretation of seismic tomography
– Earthquake sources
– Seismic interferometry
– Imaging science, inverse problems, machine learning applications
– Acoustic, elastic and electromagnetic wave propagation
– Wavefield imaging & monitoring @ field and laboratory scales, connections between geophysical and medical imaging
– Complex materials, describing microstructures, imaging & monitoring microscale properties
– Experimental rock physics & ultrasonics
Wavefields induced by earthquakes are highly complicated, both due to refined source characteristics and complex structure. As a consequence, the resulting vibrations, recorded at the Earth’s surface, are hard to fully understand. Yet, it are the complicated arrivals that are key to further unravelling Earth’s structure and its dynamics. I work on array methods to turn complicated seismic measurements into interpretable data. In the past, I focused on methods that use the data for unveiling Earth structure. Currently, I focus on obtaining source characteristics, especially from induced seismicity.
I love to learn about the dynamics and composition of the deep Earth, especially in the lower mantle. Seismology is our most powerful tool for acquiring in-situ observations of the Earth’s interior, but in order to convert from seismic to physical structure, we need to understand the relationship between seismic observables and thermodynamic parameters. This is a non-trivial task, and in my research I collaborate with seismologists, geodynamicists, statisticians and mineral physicists to try to understand and quantify what constraints seismic data allow us to place on the thermal and chemical properties of the deep Earth. In recent years I have worked mainly on the core-mantle boundary region and in future I plan to focus also on the mantle transition zone.
I am a Post-doc on the DeepNL project, a collaborative project between the Unversity of Utrecht and University of Twente funded by NWO. The projection will explore numerical modelling of seismic wave propagation, machine learning and probabilistic techniques to understand changes in the Earths shallow crust in near real time for hazard monitoring.
My particular interests are:
– Bayesian and Trans-dimensional approaches to Inverse Problems.
– Numerical modelling of physical processes within the Earth such as Seismic wave propagation and Attenuation.
phone: +31 (0)30 253 5047
room: VMA 2.44
Sujania Talavera Soza
I study large scale seismic structure in the mantle and the inner core, with a focus on seismic velocity and attenuation using normal modes. My goal is to complement the knowledge acquired from experimental and computational studies about the behavior of mantle and inner core minerals. I am currently working on building a global 3D mantle attenuation model and collaborating with mineral physicists and other seismologists, in order to enhance the interpretations of my observations.
phone: +31 (0)30 253 5109
room: VMA 2.40