14-17 May 2018
New Orleans
US/Central timezone

Analysis of CO2 residual trapping over the range of scales, from field to core to pore scales - Heletz, Israel, pilot injection site

14 May 2018, 15:37
2m
New Orleans

New Orleans

Poster + 3 Minute Pitch MS 3.11: fundamental aspects of geological storage of CO2 Parallel 2-A

Speaker

Auli Niemi (Uppsala University)

Description

Residual trapping is one of the key trapping mechanisms for CO2 geological storage, yet difficult to determine in-situ. The present study addressed determination of residual trapping over the entire range of scales from pore to core to field scale, based on data from Heletz, Israel [1] pilot CO2 injection site. During 2016-2017 two dedicated push-pull experiments have been carried out at the site for the specific purpose of quantifying the residual trapping in-situ, in a well-characterized reservoir layer at 1.6 km depth. The field experiments use a combination of hydraulic, thermal and/or tracer tests before and after creating the residually trapped zone of CO2 and the difference in the responses of these tests is used to estimate the residual trapping of CO2 in-situ. The first experiment is based on hydraulic withdrawal tests before and after the creation of the residually trapped zone. In this experiment, the residually trapped zone was also created by fluid withdrawal, by first injecting CO2, then withdrawing fluids until CO2 was at residual saturation. In the second test, the main characterization method is injection/withdrawal of water and partitioning tracers, whose recovery with and without residually trapped CO2 in the formation is compared. In the second experiment the residually trapped zone is created by first injecting CO2 and then injecting water saturated with CO2 in order to push away the mobile CO2. The experimental field results have been modelled both with simplified analytical models for guidance and with ‘full-physics’ TOUGH2 [2] simulators, to match the observations and to obtain values for in-situ residual trapping. The resulting estimates are discussed as well as compared to results from laboratory measurements on rock cores, including their modeling with pore network models. The pore network modeling has been based on laboratory data on rock samples from the site. In the first set of pore network modeling, data such as throat size distribution, permeability and characteristic two-phase flow functions [3] were used to calibrate the model, while the second analysis was based on actual scanned pore space data [4] along with measured hydraulic values.

References

References

[1] Niemi, Auli, et al. (2016) "Heletz experimental site overview, characterization and data analysis for CO 2 injection and geological storage." International Journal of Greenhouse Gas Control 48 (2016): 3-23.

[2] Pruess, Karsten, Curt Oldenburg and George Moridis (1999) TOUGH2 USER’S GUIDE, VERSION 2. Lawrence Berkeley National Laboratory Report. LBNL-43134.

[3] Hingerl, F., Yang, F., Pini, R., Xao, X., Toney, M.F., Liu, Y. and Besnon , S.M. (2016) Characterization of heterogeneity in Heletz sandstone from core to pore scale and quantification of its impact on multiphase flow. International Journal of Greenhouse Gas Control 48 (2016): 69-83.

[4] Tatomir, A., Matthias Halisch, Duschl, F., Peche, A., Wiegand, B., Schaffer, M., Licha, T., Niemi, A., Bensabat, J., Sauter, M. (2016) An integrated core-based analysis for characterization of flow, transport and mineralogical parameters of the Heletz pilot CO2 storage reservoir. International Journal of Greenhouse Gas Control 48 (2016): 24-43.

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Primary authors

Auli Niemi (Uppsala University) Dr Jacob Bensabat (EWRE) Saba Joodaki (Uppsala Univeristy ) Rasmusson Kristina (Uppsala Unviersity ) Farzad Basirat (Department of Earth Sciences, Uppsala University) Maryeh Hedayati (Uppsala University ) Prof. Zhibing Yang (Wuhan University) Lilyanne Perez (EWRE) Stanislav Levchenko (EWRE ) Alon Shklarnik (EWRE) Alexandru Tatomir (University of Göttingen ) Martin Sauter (University of Göttingen ) Fritjof Fagerlund (Uppsala University) Ferdinand F. Hingerl (Streamsim Technologies ) Prof. Sally Benson (Stanford University) Chin-Fu Tsang (Uppsala University and Lawrence Berkeley Nartional Laboratory )

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