Novel Workflows
TRANSFORM2 is exploiting Machine L earning techniques (ML) and Distributed Acoustic Sensing (DAS) to create novel real-time workflows, incorporating these advanced techniques, aimed at the
enhancement of detectability and characterization of earthquakes, across Near Fault Observatories.
We move beyond
the demonstration of improved algorithms by creating integrated and reliable operational software that can be
exploited by all NFOs. We develop software, where relevant, that is applicable to network geometries
that reflect our actual NFOs, spanning scales from meters from faults to regional monitoring over distances of
hundreds of kilometers.
The state of the art ML and DAS techniques as applied to seismologyby TRANSFORM² will enable:
- The creation of deeper, more consistent earthquake catalogues by improving phase picking, noise reduction, and event association using traditional seismic data.
- The automation of real-time workflows for earthquake source characterization, including ML-based focal mechanism determination using both P- and S-wave data, addressing challenges like shear-wave splitting.
- Improved event detection
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