Proceedings of IAHS
Proceedings of IAHS
PIAHS
Articles | Volume 382
Articles | Volume 382
https://doi.org/10.5194/piahs-382-449-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/piahs-382-449-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 382
Pre-conference publication
 | 
22 Apr 2020
Pre-conference publication |  | 22 Apr 2020

Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques

Matteo Frigo, Massimiliano Ferronato, Laura Gazzola, Pietro Teatini, Claudia Zoccarato, Massimo Antonelli, Anna Antonia Irene Corradi, Maria Carolina Dacome, Michela De Simoni, and Stefano Mantica

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Short summary
The numerical prediction of land subsidence above producing reservoirs can be affected by a number of uncertainties due to several factors. In this work, we use a Bayesian approach to reduce the initial uncertainties about the mechanical parameters in order to improve the reliability of land subsidence predictions. The numerical results obtained in an experiment on a real-world gas field confirms that is a valuable and effective approach.
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