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Distributed Acoustic Sensing, Seismic Interferometry and a Rock Laboratory in the Swiss Alps

October 24, 2018 @ 2:00 pm - 3:00 pm


Ambient noise interferometry is an established tool for investigating the subsurface on multiple scales across the Earth. With increasing popularity of recent technical advances in seismic and seismological instrumentation (such as distributed acoustic sensing (DAS) and rotational ground-motion measurements), the adaption of existing ambient noise interferometry frameworks to new observational quantities becomes necessary.

We extended the theory of seismic interferometry to a variety of observational quantities with the main focus on strain and strain rate – such as obtained from DAS systems.
With numerical, 3D spectral element simulations using the high-performance software suite SALVUS, we test the new theoretical framework and investigate the impact of source, receiver and measurement effects on seismic interferometry.

From our theoretical and numerical investigations it becomes eminent that the common assumption of Greens function retrieval by correlation does generally not hold, underlining the importance of a consistent theoretical and numerical framework that accounts for structure, source and observational effects.


To investigate the potential of DAS further, we conduct some experiments in a tunnel in the Grimsel Rock Laboratory in Southern Switzerland. Benefits of the site are existing fibers in a range of cemented boreholes with collocated strain-meters, borehole seismometers, a co-located permanent seismometer from the Swiss Seismological Service (SED), relatively low noise levels and the availability of multiple active sources. With an additional array of geophones and seismometers in addition to the already mentioned instrumentation, a large variety of comparisons to DAS data quality can be made. The variety of experiments and the range of seismic and seismological receivers has the potential to yield great insight in the potentials and limitations of DAS.

We present intermediate results of the mentioned experiments and give a site-specific evaluation of the potentials of DAS.


About the Speaker: Patrick Paitz

Patrick currently is a PhD student in the Seismology and Wave Physics group at ETH Zürich. He is mainly working on the integration of distributed acoustic sensing and other alternative measurement techniques into a theoretical and numerical framework for active and passive seismology, including noise interferometry and full-waveform inversion. Recently he started acquiring some real DAS data in the Swiss Alps for a wide range of applications.

Patrick obtained his Bachelors degree in Applied Geosciences at the Karlsruhe Institute of Technology (KIT) in Germany in 2014 and his Master in the joint program of Applied Geophysics from Delft University of Technology, RWTH Aachen University and the Swiss Federal Institute of Technology in Zürich (ETHZ) in 2016. After working on publishing his Master Thesis together with Prof. Andreas Fichtner and Alexey Gokhberg about machine learning applications in passive seismology, he started his ongoing research as a PhD student in 2016. He is interested in a wide range of seismological applications, newly emerging measurement techniques for active and passive seismology and other fields such as machine learning and data science.


Host: Nate Lindsey


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