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.
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.
the Creative Commons Attribution 4.0 License.
Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques
Matteo Frigo
CORRESPONDING AUTHOR
Department of Civil, Environmental and Architectural Engineering, Padova, Italy
Massimiliano Ferronato
Department of Civil, Environmental and Architectural Engineering, Padova, Italy
Laura Gazzola
Department of Civil, Environmental and Architectural Engineering, Padova, Italy
Pietro Teatini
Department of Civil, Environmental and Architectural Engineering, Padova, Italy
Claudia Zoccarato
Department of Civil, Environmental and Architectural Engineering, Padova, Italy
Massimo Antonelli
Eni S.p.A., Milan, Italy
Anna Antonia Irene Corradi
Eni S.p.A., Milan, Italy
Maria Carolina Dacome
Eni S.p.A., Milan, Italy
Michela De Simoni
Eni S.p.A., Milan, Italy
Stefano Mantica
Eni S.p.A., Milan, Italy
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The potential of the integrated use of A-DInSAR data and 3D groundwater flow and geomechanical models to capture and assess aquifer dynamics is performed. The approach has been applied to investigate the response during and after pumping of a portion of the Madrid aquifer. The short time delay (about one month) between the groundwater pumping and the system response (land displacements) are likely due to a minor role played by the clayey layers.
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The Venice coastland forms the major low-lying area in Italy and encompasses a variety of environments, such as farmlands, estuaries, deltas, lagoons and urbanized areas. Since most of the territory lies at a ground elevation below or slightly above the mean sea-level, also a few mm/yr of land subsidence can seriously impacts on the coastal system. In this study, we present an analysis of the vulnerability to relative sea-level rise (RSLR) considering an uneven land subsidence distribution.
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ENI monitoring plan to measure and monitor the subsidence process, during field production and also after the field closure, is intended to support a sustainable field development and an acceptable exploitation programme in which the actual risk connected with the field production is evaluated in advance, shared and agreed among all the involved subjects: oil company, stakeholders and local community (with interests in the affected area) .
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S. Ye, Y. Wang, J. Wu, P. Teatini, J. Yu, X. Gong, and G. Wang
Proc. IAHS, 372, 249–253, https://doi.org/10.5194/piahs-372-249-2015, https://doi.org/10.5194/piahs-372-249-2015, 2015
S. Ye, Y. Luo, J. Wu, P. Teatini, H. Wang, and X. Jiao
Proc. IAHS, 372, 443–448, https://doi.org/10.5194/piahs-372-443-2015, https://doi.org/10.5194/piahs-372-443-2015, 2015
G. Isotton, M. Ferronato, G. Gambolati, and P. Teatini
Proc. IAHS, 372, 519–523, https://doi.org/10.5194/piahs-372-519-2015, https://doi.org/10.5194/piahs-372-519-2015, 2015
L. Tosi, E. E. Kruse, F. Braga, E. S. Carol, S. C. Carretero, J. L. Pousa, F. Rizzetto, and P. Teatini
Nat. Hazards Earth Syst. Sci., 13, 523–534, https://doi.org/10.5194/nhess-13-523-2013, https://doi.org/10.5194/nhess-13-523-2013, 2013
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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.
The numerical prediction of land subsidence above producing reservoirs can be affected by a...