Deep lEarning foRecasting of Induced Seismicity for risK management operations

Información del proyecto

DERISK

Identificador del acuerdo de subvención: 101105516

DOI

10.3030/101105516

Proyecto cerrado

Fecha de la firma de la CE 6 Abril 2023

Fecha de inicio 3 Julio 2023

Fecha de finalización 2 Julio 2025

Financiado con arreglo a

• Marie Skłodowska-Curie Actions (MSCA)

Coste total

Sin datos

Aportación de la UE

€ 172 750,08

Coordinado por

UNIVERSITA DI PISA
Italy

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Documents, reports (1)

Communication, Dissemination & Exploitation Plan

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens.

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected processed or generated by the action It is a document describing what data will be collected processed or generated and following what methodology and standards whether and how this data will be shared andor made open and how it will be curated and preserved

Publicaciones

Peer reviewed articles (2)

Effects on a Deep-Learning, Seismic Arrival-Time Picker of Domain-Knowledge Based Preprocessing of Input Seismograms

Autores: Anthony Lomax; Matteo Bagagli; Sonja Gaviano; Spina Cianetti; Dario Jozinović; Alberto Michelini; Christopher Zerafa; Carlo Giunchi
Publicado en: Seismica, 2024, ISSN 2816-9387
Editor: McGill University Library
DOI: 10.26443/SEISMICA.V3I1.1164

Local earthquake tomography of the Alpine region from 24 years of data

Autores: M Bagagli; I Molinari; T Diehl; E Kissling
Publicado en: Geophysical Journal International, 2025, ISSN 1365-246X
Editor: Oxford University Press (OUP)
DOI: 10.1093/GJI/GGAF028

Conference proceedings (3)

A Waveform-Based Graph Neural Network Approach for Microseismic Monitoring

Autores: Matteo Bagagli, Francesco Grigoli, Davide Bacciu
Publicado en: 2025
Editor: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-13238

HEIMDALL: a grapH-based sEIsMic Detector And Locator for microseismicity

Autores: Matteo Bagagli, Francesco Grigoli, Davide Bacciu
Publicado en: 2024
Editor: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU24-6552

Leveraging Deep-Learning Methods for Operational Analysis at Enhanced Geothermal Systems

Autores: Matteo Bagagli, Francesco Grigoli, Davide Bacciu
Publicado en: 2025
Editor: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-17747