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We provide a methodological and operational workflow integrating Ensemble Model Calibration and Data Space Inversion to quantify uncertainty and assess data worth in Carbon Capture and Storage (CCS) projects. Assessing storage site integrity and monitoring plume migration is crucial for CO2 storage. Evaluating model quality involves quantifying uncertainties in geological and subsurface parameters affecting CO2 behavior. Data Worth analysis appraises the value of various data types in managing uncertainty, helping prioritize data acquisition to improve model outputs and storage site reliability. While many data can be directly employed in a forward modelling approach, pressure measurements and other dynamic reservoir data are typically considered in an inverse modeling framework, usually performed in a stochastic context. Our field application at the Smeaheia storage complex suggests that the quantity of safely injectable CO2 is the most relevant uncertainty metric, and static pressure data plays a significant role in Data Worth analysis.