Details

Autor(en) / Beteiligte

• Askar, Ahmad H.
• Illangasekare, Tissa H.
• Ilie, Ana Maria Carmen

Titel

Monitoring Brine Leakage From Deep Geologic Formations Storing Carbon Dioxide: Design Framework Validation Using Intermediate‐Scale Experiment

Ist Teil von

• Water resources research, 2021-12, Vol.57 (12), p.n/a

Ort / Verlag

Washington: Blackwell Publishing Ltd

Erscheinungsjahr

2021

Link zum Volltext

Quelle

Wiley-Blackwell Full Collection

Beschreibungen/Notizen

• Monitoring brine leakage from CO2 geological storages (CGS) is necessary to protect shallow aquifers against contamination. A framework for designing CGS monitoring systems that optimally use both easily available shallow zone data and hard‐to‐obtain deep zone observations is developed and validated. This framework is based on calibrating a transport model using monitoring data to determine leakage source conditions and then predict the subsequent brine plume that potentially contaminates shallow aquifers. As cost considerations are expected to limit monitoring deep formations, the framework is developed to minimize the number of deep observation points (e.g., deep sensors). The best monitoring locations that yield the most worthful data for reducing predictive uncertainty is selected by integrating linear uncertainty analysis with Genetic Algorithm under this framework. Due to practical challenges, testing such a framework in the field is not feasible. Thus, the framework was tested in an intermediate‐scale soil tank, where monitoring data on brine leakage plume development from the storage zone to the shallow aquifer were collected. Predictions made by a transport model calibrated on these data were then compared with experimental measurements to evaluate data informativity and thus validate the framework's applicability. The results demonstrate the framework ability to select the optimum monitoring locations for leakage detection and model calibration. It was also found that not only deep observations, but also shallow zone data are worthful to determine source conditions. Moreover, the results showed the possibility of identifying the likely areas to be impacted in the shallow aquifer using early stage monitoring data. Plain Language Summary Potential exists for formation brine to leak through caprock discontinuities when CO2 is injected into deep geologic formations to reduce greenhouse gas loading to the atmosphere. Strategies are needed to evaluate storage permanence and protect shallow groundwater from contamination using monitoring systems. As installing the necessary sensors in deep zones is expensive, cost reduction should be a goal in designing such monitoring systems. This research validated an optimal design framework that integrates observations from shallow wells with a limited number of deep sensors based on the value of collected data in meeting monitoring goals. As field validation of such a framework is not technically feasible, data from a simulated leakage event in a large laboratory test tank was used. In this validation, data collected from the monitoring locations selected by the framework was used to calibrate a transport model. The validation results showed how model predictions of leakage rate and location, lateral flow in the storage zone, and plume development in the shallow aquifer were improved by calibrating the model with the collected monitoring data. Key Points Linear uncertainty analysis combined with Genetic Algorithm is used to design monitoring systems for brine leakage from CO2 storages Experimental data generated in an intermediate‐scale test system simulating brine leakage was used to validate the developed framework The results show that the prediction accuracy of the brine plume varies largely with the worth of data used in model calibration