Validating Plume Predictions with Insights from A Decade of MMV from an Active CO2 Injection Site

Abstract Dynamic model calibration is key to addressing geological complexities, ultimately providing valuable insights for optimizing storage efficiency in CCS projects. This paper aims to validate CO2 plume predictions through a decade of monitoring, measurement, and verification (MMV) at an active CO2 injection site in Canada. It examines the integration of geological and flow models with seismic data from the Aquistore project to refine plume predictive accuracy and enhance long-term monitoring strategies. We used geological modeling, flow simulations, and seismic monitoring to validate CO2 plume predictions at Aquistore. The geological model was constructed using seismic, log, and core data, incorporating key storage and sealing formations. Flow simulations were calibrated using ten years of injection data, capturing geological uncertainties. Multiple seismic surveys provided plume migration insights, with noise filtering and amplitude analysis refining detection accuracy. Dynamic model calibration incorporated reservoir heterogeneity, ensuring accurate plume representation. These findings reinforce the effectiveness of selected MMV strategies in optimizing CCS operations and establishing a benchmark for future CO2 storage projects. The process of analyzing seismic acquisition data for CO2 plume detection was complex, requiring background noise exclusion and applying a defined threshold to amplitude difference maps. This method enabled the delineation of the main plume outline. This study confirms that geological heterogeneity, structural flexure, and variable reservoir properties influence CO2 plume migration at Aquistore. Time-lapse seismic monitoring revealed that plume expansion was non-uniform across perforated intervals, reflecting differences in saturation and thickness. Refining the geological and flow models with seismic inversion data improved predictive accuracy, transitioning from a simple layer-cake assumption to one that incorporated geological complexities, such as structural flexure and reservoir heterogeneity. Observations confirm that selected MMV strategies effectively track plume behavior, demonstrating the value of 4D seismic in model validation. Calibrated model iterations strengthen confidence in CO2 storage safety and efficacy. Ultimately, field observations and modeling results underscore the importance of integrating continuous monitoring with adaptive modeling approaches to optimize injection strategies, minimize uncertainties, and ensure long-term CO2 containment in saline aquifers. This paper offers novel insights by integrating long-term CO2 plume monitoring with advanced seismic techniques, enhancing predictive accuracy in geological storage. It advances the existing MMV methodologies through demonstrating real-time calibration of flow models. These findings play a crucial role in optimizing storage strategies, mitigating uncertainties, and improving monitoring frameworks for future CCS projects, ensuring safe and efficient long-term CO2 sequestration.

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