EGU2020-9402, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-9402
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Electrical Resistivity Tomography Concept for CO2 Injection Monitoring at the Svelvik CO2 Field Lab

Tobias Raab, Wolfgang Weinzierl, Dennis Rippe, Bernd Wiese, and Cornelia Schmidt-Hattenberger
Tobias Raab et al.
  • GFZ German Research Centre for Geosciences, 4.8 Geoenergy, Potsdam, Germany (traab@gfz-potsdam.de)

Carbon Capture and Storage technology is considered to be able to contribute to a carbon neutral society and is again receiving increased attention in the efforts to reduce CO2 emissions. To ensure safe operation of such CO2 storage projects, reliable monitoring technologies are required. Due to the generally high electrical resistivity contrast between CO2 and formation water, Electrical Resistivity Tomography (ERT) can be considered one of the most effective geophysical techniques in the monitoring of CO2 migration in the subsurface.

Within the ERA-NET co-funded ACT project Pre-ACT (Pressure control and conformance management for safe and efficient CO2 storage - Accelerating CCS Technologies) a CO2 injection and monitoring experiment was planned at the Svelvik CO2 Field Lab, located on the Svelvik ridge at the outlet of the Drammensfjord in Norway. The Svelvik field lab consists of four 100 m deep monitoring wells, drilled in July 2019, surrounding an existing well used for brine and CO2 injection. Each monitoring well is equipped with modern sensing systems including five types of fiber-optic cables, conventional and capillary pressure monitoring systems, as well as 16 ERT electrodes with a spacing of five meters.

With 64 installed electrodes, a large number of measurement configurations is possible. We combine the free and open-source geophysical modeling library pyGIMLI with ECLIPSE reservoir modeling to simulate the expected behavior of all cross-well electrode configurations during a CO2 injection experiment. Simulated CO2 saturations are converted to changes in apparent resistivity using Archie's law. Different considerations have to be made to select a suitable set of electrode configurations, i.e. not too large geometric factors, maximum response to the predicted change, as well as sensitivity in the target area. We select sets of configurations based on different criteria, i.e. the ratio between the measured change in resistivity in relation to the geometric factor, the maximum change in apparent resistivity, and maximum sensitivity in the target area. The individually selected measurement schedules are tested by inverting them with different assumed data errors. The numerical results show adequate resolution of the CO2 plume.

The CO2 injection took place between 27th October 2019 and 5th November 2019. Approximately two metric tonnes of CO2 were injected in 65 m depth. Preliminary field results indicate a considerably lower response than predicted by our model. These discrepancies can potentially be explained by oversimplified simulations as well as operational uncertainties. Results from baseline and repeat surveys can therefore support an integrated approach towards a revised static and dynamic model for the test site.

Acknowledgements:

This work was produced within the SINTEF-coordinated Pre-ACT project (Project No. 271497) funded by RCN (Norway), Gassnova (Norway), BEIS (UK), RVO (Netherlands), and BMWi (Germany) and co-funded by the European Commission under the Horizon 2020 programme, ACT Grant Agreement No 691712. We also acknowledge industry partners Total, Equinor, Shell, TAQA.

Finally, we thank the SINTEF-owned Svelvik CO2 Field Lab (funded by ECCSEL through RCN, with additional support from Pre-ACT and SINTEF) for assistance during installations and for financial support.

How to cite: Raab, T., Weinzierl, W., Rippe, D., Wiese, B., and Schmidt-Hattenberger, C.: Electrical Resistivity Tomography Concept for CO2 Injection Monitoring at the Svelvik CO2 Field Lab, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9402, https://doi.org/10.5194/egusphere-egu2020-9402, 2020

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