A methodological approach is proposed in order to define and evaluate the rock volume surrounding an underground gas storage (UGS) reservoir that is potentially subjected to a stress perturbation due to the storage activities. The analysis is based on a coupled computational modeling approach combining flow dynamics with geomechanics in the reservoir. Long-term records of injected and produced gas volume and pore pressure are used to calibrate a 3-D fluid-dynamic reservoir model, which is enlarged to the active surrounding aquifer to evaluate the extent of the propagation of the pressure variation. A multi-year detection of the land motion above the reservoir can lead to the development of a reliable geomechanical model of the UGS site, similarly to the procedure developed by Teatini et al. [2011] and Janna et al. [2012], including the prediction of the mechanics of the faults possibly intercepting the investigated rock volume. The mechanics of faults is simulated by a fully implicit algorithm by means of recent computational strategies based on Lagrange multipliers [Franceschini et al., 2020, 2022a,b]. The combined action of the fluid-dynamic and geomechanical models can predict the propagation of the stress disturbance generated in the reservoir and its surroundings during the cyclic injection-extraction process. The analysis of the propagation of the stress disturbance during UGS activities allows to define the rock volume surrounding the reservoir that is potentially affected by the mining operations. The definition of this volume has a twofold motivation: (i) to identify the region where the monitoring program should be focused during the execution of the UGS activities; (ii) to exclude those occurrences, such as micro-seismic events located outside the identified volume, that cannot be related with the UGS activities. Copyright 2024, Society of Petroleum Engineers.

Predicting the Volume of Influence of an Underground Gas Storage Reservoir: Application to a Real-World Case in Italy

Teatini, P.;Ferronato, M.;Franceschini, A.;
2024

Abstract

A methodological approach is proposed in order to define and evaluate the rock volume surrounding an underground gas storage (UGS) reservoir that is potentially subjected to a stress perturbation due to the storage activities. The analysis is based on a coupled computational modeling approach combining flow dynamics with geomechanics in the reservoir. Long-term records of injected and produced gas volume and pore pressure are used to calibrate a 3-D fluid-dynamic reservoir model, which is enlarged to the active surrounding aquifer to evaluate the extent of the propagation of the pressure variation. A multi-year detection of the land motion above the reservoir can lead to the development of a reliable geomechanical model of the UGS site, similarly to the procedure developed by Teatini et al. [2011] and Janna et al. [2012], including the prediction of the mechanics of the faults possibly intercepting the investigated rock volume. The mechanics of faults is simulated by a fully implicit algorithm by means of recent computational strategies based on Lagrange multipliers [Franceschini et al., 2020, 2022a,b]. The combined action of the fluid-dynamic and geomechanical models can predict the propagation of the stress disturbance generated in the reservoir and its surroundings during the cyclic injection-extraction process. The analysis of the propagation of the stress disturbance during UGS activities allows to define the rock volume surrounding the reservoir that is potentially affected by the mining operations. The definition of this volume has a twofold motivation: (i) to identify the region where the monitoring program should be focused during the execution of the UGS activities; (ii) to exclude those occurrences, such as micro-seismic events located outside the identified volume, that cannot be related with the UGS activities. Copyright 2024, Society of Petroleum Engineers.
2024
Proceedings of the SPE Europe Energy Conference & Exhibition 2024
SPE Europe Energy Conference & Exhibition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3539732
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