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A stochastic inversion workflow for monitoring the distribution of CO₂ injected into deep saline aquifers.

Perozzi, Lorenzo; Gloaguen, Erwan; Giroux, Bernard; Holliger, Klaus (2016). A stochastic inversion workflow for monitoring the distribution of CO₂ injected into deep saline aquifers. Computational Geosciences , vol. 20 , nº 6. p. 1287-1300. DOI: 10.1007/s10596-016-9590-3.

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Résumé

We present a two-step stochastic inversion approach for monitoring the distribution of CO₂ injected into deep saline aquifers for the typical scenario of one single injection well and a database comprising a common suite of well logs as well as time-lapse vertical seismic profiling (VSP) data. In the first step, we compute several sets of stochastic models of the elastic properties using conventional sequential Gaussian co-simulations (SGCS) representing the considered reservoir before CO₂ injection. All realizations within a set of models are then iteratively combined using a modified gradual deformation algorithm aiming at reducing the mismatch between the observed and simulated VSP data. In the second step, these optimal static models then serve as input for a history matching approach using the same modified gradual deformation algorithm for minimizing the mismatch between the observed and simulated VSP data following the injection of CO₂. At each gradual deformation step, the injection and migration of CO₂ is simulated and the corresponding seismic traces are computed and compared with the observed ones. The proposed stochastic inversion approach has been tested for a realistic, and arguably particularly challenging, synthetic case study mimicking the geological environment of a potential CO₂ injection site in the Cambrian-Ordivician sedimentary sequence of the St. Lawrence platform in Southern Québec. The results demonstrate that the proposed two-step reservoir characterization approach is capable of adequately resolving and monitoring the distribution of the injected CO₂. This finds its expression in optimized models of P- and S-wave velocities, density, and porosity, which, compared to conventional stochastic reservoir models, exhibit a significantly improved structural similarity with regard to the corresponding reference models. The proposed approach is therefore expected to allow for an optimal injection forecast by using a quantitative assimilation of all available data from the appraisal stage of a CO₂ injection site.

Type de document: Article
Mots-clés libres: CO₂ sequestration; stochastic inversion; gradual deformation; VSP
Centre: Centre Eau Terre Environnement
Date de dépôt: 07 mai 2018 17:53
Dernière modification: 07 mai 2018 17:53
URI: http://espace.inrs.ca/id/eprint/5715

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