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Acoustic Emission and Seismic moment tensor catalogs associated with triaxial stick-slip experiments performed on Westerly Granite samples

The dataset contains source parameters of acoustic emission (AE) events recorded during triaxial friction (stick-slip) experiments performed on the Westerly Granite sample WgN05. In addition we provide raw waveform data of AE events recorded in triggered mode with a network of 16 AE sensors. Basic seismic catalog associated with the stick-slip experiment contains origin time, hypocentral location in local Cartesian coordinate system of the sample (with associated uncertainties), and AE-derived magnitude. In addition, for a subset of AEs we provide full moment tensors. This catalog include information on fault parameters (strike, dip and rake of the two nodal planes), percentage of isotropic, compensated linear vector dipole and double-couple components of the full moment tensor, P, T, B axes orientations in the coordinate system of the sample, uncertainty assessment, as well as the six independent moment tensor components. Finally, we provide a time series of axial stress values as presented in the Kwiatek et al. (2023) as well as the coordinates of the AE sensors. The catalog and parametric data is supplemented with the raw waveform recordings stored in HDF5 format from 16 acoustic emission sensors placed on the surface of the sample.

An Open-Source Site Database of Strong-Motion Stations in Japan: K-NET and KiK-net

This is an open-source site database for a total number of 1742 earthquake recording sites in the K-NET (Kyoshin network) and KiK-net (Kiban Kyoshin network) networks in Japan. This database contains site characterization parameters directly derived from available velocity profiles, including average wave velocities, bedrock depths, and velocity contrast. Meanwhile, it also consists of parameters obtained from earthquake horizontal-to-vertical spectral ratio (HVSR), e.g., peak frequency, amplitude, width and prominence. In addition, the site database also comprises topographic and geological proxies inferred from regional models or maps. Each parameter is derived in a consistent manner for all sites. This site database can benefit the application of machine learning techniques in studies on site amplifications. Besides, it can facilitate, for instances, the search of the optimal site parameter(s) in depicting site amplification, the development and testing of new or existing prediction models or methodologies. This zip file contains earthquake HVSR data, including metadata and plots of automatically identified peaks (frequency, amplitude, prominence and width) at 1700+ K-NET and KiK-net strong-motion recordings stations. This MATLAB code is for automatically picking peaks (frequency, amplitude, prominence and width) from HVSR curves.

Supplementary material to "Machine Learning can predict the timing and size of analog earthquakes"

This data set includes the results of digital image correlation of one experiment on subduction megathrust earthquakes with interacting asperities performed at the Laboratory of Experimental Tectonics (LET) Univ. Roma Tre in the framework of AspSync, the Marie Curie project (grant agreement 658034) lead by F. Corbi in 2016-2017. Detailed descriptions of the experiments and monitoring techniques can be found in Corbi et al. (2017 and 2019) to which this data set is supplementary material.We here provide Digital Image Correlation (DIC) data relative to a 7 min long interval during which the experiment 
produces 40 seismic cycles with average duration of about 10.5 s (see Figure S1 in Corbi et al., 2019). The DIC analysis yields quantitative about the velocity field characterizing two consecutive frames, measured in this case at the model surface. For a detailed description of the experimental procedure, set-up and materials used, please refer to the article of Corbi et al. (2017) paragraph 2. This data set has been used for: a) studying the correlation between apparent slip-deficit maps and earthquake slip pattern (see Corbi et al., 2019; paragraph 4); and b) as input for the Machine Learning investigation (see Corbi et al., 2019; paragraph 5).Further technical information about the methods, data products and matlab scripts is proviced in the data description file. The list of files explains the file and folder structure of the data set.

Seismic moment and injection efficiency evolution during Enhanced Geothermal System (EGS) projects

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Enhanced earthquake catalog (2017–February 5, 2023) for the epicentral region of the 2023 Mw 7.8 Kahramanmaraş earthquake, Türkiye

This earthquake catalog was constructed using a combination of artificial intelligence and traditional methods for phase picking, phase association, and earthquake relocation. It covers the period from January 1, 2017, to February 5, 2023—one day prior to the Mw 7.8 earthquake that struck Türkiye. The dataset includes three subsets: 1) Raw Catalog: Comprises 14,128 events obtained from the full association and relocation process, without filtering based on event type or location quality. 2) Earthquake Catalog: Comprises 5,721 tectonic events with well-constrained hypocenters (68% confidence ellipsoid semi-major axis < 8 km and depth < 15 km). 3) Anthropogenic Catalog: Comprises 1,695 human-induced events, primarily quarry blasts, also with well-constrained hypocenters (68% confidence ellipsoid semi-major axis < 8 km and depth < 15 km).

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