A multibranch, multitarget neural network for rapid point-source inversion in a microseismic environment: examples from the Hengill Geothermal Field, Iceland

• Main Authors: Nooshiri, Nima, Bean, Christopher J., Dahm, Torsten, Grigoli, Francesco, id_orcid:0 000-0002-2858-9756, Kristjánsdóttir, Sigríður, Obermann, Anne, id_orcid:0 000-0001-6933-6301, Wiemer, Stefan, id_orcid:0 000-0002-4919-3283
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press 2022
• Subjects: Neural networks; fuzzy logic; Computational seismology; Induced seismicity; Earthquake source observations; Hengill; Rapid Point; Iceland
• Online Access: https://hdl.handle.net/20.500.11850/539199; https://doi.org/10.3929/ethz-b-000539199

Despite advanced seismological techniques, automatic source characterization for microseismic earthquakes remains difficult and challenging since current inversion and modelling of high-frequency signals are complex and time consuming. For real-time applications such as induced seismicity monitoring...