Sizing a geodetic network for risk-oriented monitoring of surface deformations induced by CO2 injection: Experience feedback with InSAR data collected at In-Salah, Algeria
Résumé
CO2 capture and storage (CCS) is recognized as a promising solution to tackle greenhouse gas emissions. Key issues associated with CCS relate to the integrity of the reservoir and the containment effectiveness. Some risk events (e.g. regional over-pressurization, leakage through a fault or an abandoned well) identified in the risk analysis may be linked with surface deformations anomalies, which can be detected and followed using surface deformation measurements.
At In-Salah (Algeria), Interferometric Synthetic Aperture Radar (InSAR) data are available for all points due to ideal surface conditions. If a similar injection occurred in constrained conditions (large cover of vegetated areas for instance), a geodetic network (set of corner reflectors that constitute artificial measurements points) could be used to compensate the scarcity of existing persistent scatterers. The present study aims at exploring the feasibility of using such a geodetic network as part of the monitoring plan in constrained conditions. The sizing of such a network is discussed regarding three monitoring objectives: regional-scale surveillance, local anomaly with known and unknown spatial locations. In the context of In-Salah, a very limited number of measurement points (∼20) enables capturing the regional deformation pattern. The addition of a series of less than 5 supplementary points brings useful information to detect local anomalies of small-to-moderate (e.g. subsidence, with 1 km radius and 2 mm/y maximal amplitude) size for a known position. For detecting an unpredicted anomaly, the measurements network density needs to be largely increased, making the method more expensive. Though the results are not directly transposable in other settings, this experience feedback brings useful orders of magnitude and an original risk-oriented approach.