Antonio P. Rinaldi

Periodic behavior of soil CO2 emissions in diffuse degassing areas of the Azores archipelago: Application to seismovolcanic monitoring

Time series of soil CO2 efflux recorded in the Azores archipelago volcanic-hydrothermal areas feature daily and seasonal variations. The recorded CO2 efflux values were lower during summer than in the winter season. The diurnal CO2 efflux values were higher at dawn and lower in the early afternoon, contrary to that observed in biogenic environments. CO2 efflux cycles correlated well with the environmental variables, such as air temperature, wind speed, and barometric pressure, which also showed low- and high-frequency periodicities. Several simulations were performed here using the Transport of Unsaturated Groundwater and Heat 2 (TOUGH2) geothermal simulator to complement the study of Rinaldi et al. (2012). The effects of the water table depth, air temperature perturbation amplitude, and soil thermal gradient contributed to an explanation of the contrasts observed in the diurnal (S1) and semidiurnal (S2) soil CO2 efflux peaks for the different monitoring sites and seasons. Filtering techniques (multivariate regression analysis and fast Fourier transform filters) were also applied to the recorded time series to remove effects of external variables on the soil CO2 efflux. The resulting time series (the residuals) correspond to the best approach to the deep-seated (volcanic/hydrothermal) CO2 emissions and thus should be used in seismovolcanic monitoring programs. Even if no evident correlation can be established yet between the soil CO2 residuals and seismicity over the monitored time, a seismic swarm that occurred around the end of 2008 might have triggered some deviations from the observed daily cycles.

Inverse modeling of ground surface uplift and pressure with iTOUGH-PEST and TOUGH-FLAC: The case of CO 2 injection at In Salah, Algeria

Ground deformation, commonly observed in storage projects, carries useful information about processes occurring in the injection formation. The Krechba gas field at In Salah (Algeria) is one of the best-known sites for studying ground surface deformation during geological carbon storage. At this first industrial-scale on-shore CO2 demonstration project, satellite-based ground-deformation monitoring data of high quality are available and used to study the large-scale hydrological and geomechanical response of the system to injection. In this work, we carry out coupled fluid flow and geomechanical simulations to understand the uplift at three different CO2 injection wells (KB-501, KB-502, KB-503). Previous numerical studies focused on the KB-502 injection well, where a double-lobe uplift pattern has been observed in the ground-deformation data. The observed uplift patterns at KB-501 and KB-503 have single-lobe patterns, but they can also indicate a deep fracture zone mechanical response to the injection.The current study improves the previous modeling approach by introducing an injection reservoir and a fracture zone, both responding to a Mohr-Coulomb failure criterion. In addition, we model a stress-dependent permeability and bulk modulus, according to a dual continuum model. Mechanical and hydraulic properties are determined through inverse modeling by matching the simulated spatial and temporal evolution of uplift to InSAR observations as well as by matching simulated and measured pressures. The numerical simulations are in agreement with both spatial and temporal observations. The estimated values for the parameterized mechanical and hydraulic properties are in good agreement with previous numerical results. In addition, the formal joint inversion of hydrogeological and geomechanical data provides measures of the estimation uncertainty. Modeling of deep fracture opening and stress-dependent permeability at the In Salah CO2 storage project.Hydromechanical parameters estimation with inverse modeling of coupled fluid flow and geomechanics.Sensitivity analysis highlights strong coupling between hydromechanical parameters and observations.Exploring the uncertainty range in estimated parameters.