Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques
<p>The numerical prediction of land subsidence above producing reservoirs can be affected by a number of uncertainties, related for instance to the deep rock constitutive behavior, geomechanical properties, boundary and forcing conditions, etc. The quality and the amount of the available obser...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2020-04-01
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| Series: | Proceedings of the International Association of Hydrological Sciences |
| Online Access: | https://www.proc-iahs.net/382/449/2020/piahs-382-449-2020.pdf |
| _version_ | 1818957634075623424 |
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| author | M. Frigo M. Ferronato L. Gazzola P. Teatini C. Zoccarato M. Antonelli A. A. I. Corradi M. C. Dacome M. De Simoni S. Mantica |
| author_facet | M. Frigo M. Ferronato L. Gazzola P. Teatini C. Zoccarato M. Antonelli A. A. I. Corradi M. C. Dacome M. De Simoni S. Mantica |
| author_sort | M. Frigo |
| collection | DOAJ |
| description | <p>The numerical prediction of land subsidence above producing reservoirs can be affected by a number of uncertainties, related for instance to the deep rock constitutive behavior, geomechanical properties, boundary and forcing conditions, etc.
The quality and the amount of the available observations can help reduce such uncertainties by constraining the numerical model outcome and providing more reliable estimates of the unknown governing parameters. In this work, we address the numerical simulation of land subsidence above a producing hydrocarbon field in the Northern Adriatic, Italy, by integrating the available monitoring data in the computational model with the aid of Data Assimilation strategies. A preliminary model diagnostic analysis, i.e. the <span class="inline-formula"><i>χ</i><sup>2</sup></span>-test, allows for identifying the most appropriate forecast ensemble. Then, a Bayesian approach, i.e. the Red Flag technique, and a smoother formulation, i.e. the Ensemble Smoother, provide a significant reduction of the prior uncertainties.
The experiment developed on a real-world gas field confirms that the integration of monitoring observations with classical geomechanical models is a valuable approach to improve the reliability of land subsidence predictions and to exploit in a systematic way the increasing amount of available measurement records.</p> |
| first_indexed | 2024-12-20T11:12:58Z |
| format | Article |
| id | doaj.art-59b030e566b1427db0fa5bc35cb4ce6d |
| institution | Directory Open Access Journal |
| issn | 2199-8981 2199-899X |
| language | English |
| last_indexed | 2024-12-20T11:12:58Z |
| publishDate | 2020-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Proceedings of the International Association of Hydrological Sciences |
| spelling | doaj.art-59b030e566b1427db0fa5bc35cb4ce6d2022-12-21T19:42:42ZengCopernicus PublicationsProceedings of the International Association of Hydrological Sciences2199-89812199-899X2020-04-0138244945510.5194/piahs-382-449-2020Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniquesM. Frigo0M. Ferronato1L. Gazzola2P. Teatini3C. Zoccarato4M. Antonelli5A. A. I. Corradi6M. C. Dacome7M. De Simoni8S. Mantica9Department of Civil, Environmental and Architectural Engineering, Padova, ItalyDepartment of Civil, Environmental and Architectural Engineering, Padova, ItalyDepartment of Civil, Environmental and Architectural Engineering, Padova, ItalyDepartment of Civil, Environmental and Architectural Engineering, Padova, ItalyDepartment of Civil, Environmental and Architectural Engineering, Padova, ItalyEni S.p.A., Milan, ItalyEni S.p.A., Milan, ItalyEni S.p.A., Milan, ItalyEni S.p.A., Milan, ItalyEni S.p.A., Milan, Italy<p>The numerical prediction of land subsidence above producing reservoirs can be affected by a number of uncertainties, related for instance to the deep rock constitutive behavior, geomechanical properties, boundary and forcing conditions, etc. The quality and the amount of the available observations can help reduce such uncertainties by constraining the numerical model outcome and providing more reliable estimates of the unknown governing parameters. In this work, we address the numerical simulation of land subsidence above a producing hydrocarbon field in the Northern Adriatic, Italy, by integrating the available monitoring data in the computational model with the aid of Data Assimilation strategies. A preliminary model diagnostic analysis, i.e. the <span class="inline-formula"><i>χ</i><sup>2</sup></span>-test, allows for identifying the most appropriate forecast ensemble. Then, a Bayesian approach, i.e. the Red Flag technique, and a smoother formulation, i.e. the Ensemble Smoother, provide a significant reduction of the prior uncertainties. The experiment developed on a real-world gas field confirms that the integration of monitoring observations with classical geomechanical models is a valuable approach to improve the reliability of land subsidence predictions and to exploit in a systematic way the increasing amount of available measurement records.</p>https://www.proc-iahs.net/382/449/2020/piahs-382-449-2020.pdf |
| spellingShingle | M. Frigo M. Ferronato L. Gazzola P. Teatini C. Zoccarato M. Antonelli A. A. I. Corradi M. C. Dacome M. De Simoni S. Mantica Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques Proceedings of the International Association of Hydrological Sciences |
| title | Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques |
| title_full | Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques |
| title_fullStr | Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques |
| title_full_unstemmed | Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques |
| title_short | Numerical simulation of land subsidence above an off-shore Adriatic hydrocarbon reservoir, Italy, by Data Assimilation techniques |
| title_sort | numerical simulation of land subsidence above an off shore adriatic hydrocarbon reservoir italy by data assimilation techniques |
| url | https://www.proc-iahs.net/382/449/2020/piahs-382-449-2020.pdf |
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