D-SET: Probing the evolution of fault properties during the seismic cycle with Deep Learning
Contributors
Project leader:
Supervisors:
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1.
Sapienza University of Rome
Description
This dataset has been developed to analyze fault zone properties affected by the Norcia mainshock on October 30, 2016. It comprises waveform data from nine seismic stations surrounding the rupture site of the Vettore fault segment. Waveforms were selectively gathered from within a 3 km band perpendicular to the fault, exclusively including seismic events deeper than 2 km to minimize anthropogenic sources and surface-based seismic noise. The dataset is balanced to diminish the influence of Amatrice aftershocks, extending asymmetrically 15 km northeast and 4 km southwest of the Norcia epicenter, and only includes events with magnitudes greater than Mw 0.5 to ensure data quality.
Technical info (English)
The .hdf5 files features waveforms retrieved from three-component seismometers, which include one vertical and two horizontal sensors in an orthogonal arrangement, recording detailed ground motions in the east (E), north (N), and vertical (Z) directions. Each waveform is presented in a 25-second window, structured to include 5 seconds pre- and 20 seconds post-theoretical P-wave arrival, calculated using a global velocity model. Waveform data is sampled at either 100 Hz or 125 Hz. To facilitate uniform analysis, waveforms initially recorded at 125 Hz have been resampled to 100 Hz to standardize the dataset.
The accompanying .csv file contains detailed metadata, organized into two distinct categories: seismic events (source_) and recording stations (receiver_). For seismic events, the metadata includes identifiers such as source IDs, alongside spatial and temporal data such as event magnitudes, depths, coordinates, and origin times. For the recording stations, the metadata provides station names, types, network codes, and exact locations, including elevation, latitude, and longitude.
Files
dataset.zip
Files
(5.1 GB)
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