The use of Data Assimilation (DA) techniques is receiving an increasing interest in geomechanical applications, with the aim to assess and reduce uncertainties associated to numerical outcomes by model constrain with available measurements. In geomechanical simulations, ensemble-based DA approaches are usually preferred. Among such techniques, Ensemble Smoother with Multiple Data Assimilation (MDA-ES) is usually recognized to improve the outcomes in nonlinear problems, but its use and parameter definition is still object of research. In this paper, MDA-ES has been tested in a synthetic case study dealing with the prediction of land subsidence above a producing hydrocarbon reservoir. Its effectiveness has been investigated varying both the DA parametrization and the geomechanical properties.

Integration of Data Assimilation Techniques in Geomechanical Modelling: Ensemble Smoother with Multiple Data Assimilation Analysis

Gazzola, Laura
;
Ferronato, Massimiliano;Frigo, Matteo;Teatini, Pietro;Zoccarato, Claudia
2021

Abstract

The use of Data Assimilation (DA) techniques is receiving an increasing interest in geomechanical applications, with the aim to assess and reduce uncertainties associated to numerical outcomes by model constrain with available measurements. In geomechanical simulations, ensemble-based DA approaches are usually preferred. Among such techniques, Ensemble Smoother with Multiple Data Assimilation (MDA-ES) is usually recognized to improve the outcomes in nonlinear problems, but its use and parameter definition is still object of research. In this paper, MDA-ES has been tested in a synthetic case study dealing with the prediction of land subsidence above a producing hydrocarbon reservoir. Its effectiveness has been investigated varying both the DA parametrization and the geomechanical properties.
2021
Challenges and Innovations in Geomechanics
978-3-030-64513-7
978-3-030-64514-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3383729
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