GNGTS 2018 - 37° Convegno Nazionale

528 GNGTS 2018 S essione 2.3 development. This platform provides a collection of data sets of time-correlated geophysical, technological and other relevant geo-data organised in so-called Episodes , which relate anthropogenic seismicity to its industrial cause. For details regarding the IS-EPOS platform see the quick start guide ( IS-EPOS, 2018). Acknowledgements. The work presented in this abstract is based on the paper by Garcia-Aristizabal et al (2018). This research has been performed in the framework of the EU H2020 SHEER (Shale gas exploration and exploitation induced Risks) Project, Grant No. 640896. The implementation of the MERGER system in the IS-EPOS platform is performed in the framework of the EU H2020 EPOS-IP (European Plate Observing System) Project, Grant No. 676564. The research activities of AMRAwere co-financed by the Italian Ministry of Economic Development (MISE- DGRME) in the framework of the cooperation agreement No. 23671. References Bedford T, Cooke R (2001) Probabilistic risk analisys: foundations and methods. Cambridge University Press, Cambridge Garcia-Aristizabal A, Capuano P, Russo R, Gasparini P (2017) Multi-hazard risk pathway scenarios associated with unconventional gas development: Identification and challenges for their assessment. Energy Procedia 125:116– 125, 10.1016/j.egypro.2017.08.087, european Geosciences Union General Assembly 2017, EGU Division Energy, Resources & Environment (ERE) Garcia-Aristizabal A, Kocot J, Russo R, Gasparini P (2018) A probabilistic tool for multi-hazard risk analysis using a bow-tie approach: application to environmental risk assessments for geo-resource development projects. Acta Geophysica (article in press):–, 10.1007/s11600-018-0201-7 Gasparini P, Garcia-Aristizabal A (2014) Seismic Risk Assessment, Cascading Effects. In: Beer M, Kougioumtzoglou IA, Patelli E, Au ISK (eds) Encyclopedia of Earthquake Engineering, Springer Berlin Heidelberg, Berlin, Heidelberg, pp 1–20, 10.1007/978-3-642-36197-5\s\do5(2)60-1, URL https://doi.org/10.1007/978-3-642-36197- 5\s\do5(2)60-1 Iannacchione AT (2008) The Application of major hazard risk assessment MHRA to eliminate multiple fatality occurrences in the U.S. minerals industry. Tech. rep., National Institute for Occupational Safety and Health, Spokane Research Laboratory, URL https://lccn.loc.gov/2009285807 IS-EPOS (2018) IS-EPOS Platform User Guide. Tech. rep., (last accessed: May 2018), URL https://tcs.ah-epos.eu/ eprints/1737 Khakzad N, Khan F, Amyotte P (2013) Quantitative risk analysis of offshore drilling operations: ABayesian approach. Safety Science 57:108–117 Khakzad N, Khakzad S, Khan F (2014) Probabilistic risk assessment of major accidents: application to offshore blowouts in the Gulf of Mexico. Natural Hazards 74(3):1759–1771 Liu Z, Nadim F, Garcia-Aristizabal A, Mignan A, Fleming K, Luna BQ (2015) A three-level framework for multi-risk assessment. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards 9(2):59–74 Marzocchi W, Garcia-Aristizabal A, Gasparini P, Mastellone ML, Di Ruocco A (2012) Basic principles of multi-risk assessment: a case study in Italy. Natural Hazards 62(2):551–573, 10.1007/s11069-012-0092-x, URL https://doi. org/10.1007/s11069-012-0092-x Rausand M, Høyland A (2004) System Reliability Theory: Models, Statistical Methods and Applications. Wiley- Interscience, Hoboken, NJ Yang M, Khan FI, Lye L (2013) Precursor-based hierarchical Bayesian approach for rare event frequency estimation: A case of oil spill accidents. Process Safety and Environmental Protection 91(5):333–342, 10.1016/j. psep.2012.07.006, URL http://www.sciencedirect.com/science/article/pii/S0957582012000894