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Insights on CO2 Migration Based on a Multi-physical Inverse Reservoir Modeling Framework

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Wagner,  F.
6.3 Geological Storage, 6.0 Geotechnologies, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/wiese

Wiese,  B.
6.3 Geological Storage, 6.0 Geotechnologies, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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Schmidt-Hattenberger,  Cornelia
6.3 Geological Storage, 6.0 Geotechnologies, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Maurer,  H.
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Zitation

Wagner, F., Wiese, B., Schmidt-Hattenberger, C., Maurer, H. (2016): Insights on CO2 Migration Based on a Multi-physical Inverse Reservoir Modeling Framework - Papers, 78th EAGE Conference and Exhibition (Vienna, Austria 2016).
https://doi.org/10.3997/2214-4609.201601659


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_1779903
Zusammenfassung
Permanent geophysical crosshole methods offer opportunities to provide spatiotemporal information on CO2 migration, since the physical properties change in regions affected by fluid substitution. The direct and quantitative integration of geophysical methods in a reservoir modeling context is not straightforward and requires multi-physical process models coupled through petrophysical parameter transformations. Based on an example from the Ketzin CO2 storage site, Germany, we present a hydrogeophysical modeling workflow, in which simulated CO2 distributions are transfered to changes in electrical properties used for geoelectrical forward modeling. Simultaneous inversion of the electrical time-lapse response, reservoir pressure and CO2 arrival times has not been reported before and enables estimation of the permeability distribution. The calibrated model captures the known migration direction of the CO2 and is able to explain the multi-physical calibration dataset. The presented framework allows to integrate various types of observations into a single hydrogeophysical model leading to increased confidence in permeability parameterization and, in perspective, to improved predictive assessments of the storage reservoir.