A decade of progress in the modeling and simulation of geologic carbon storage

Over the past decade, geological carbon storage (GCS) has developed into a deployable technology, with modeling and simulation playing a central role in site permitting, operations, and risk assessment. This paper synthesizes a decade of progress in CO2 storage modeling, with a focus on field-scale modeling and incorporation into decision support and regulatory workflows. We summarize advances across the modeling spectrum, from reduced-order screening tools to compositional flow simulation and coupled-multi-physics models, and discuss how uncertainty quantification, data assimilation, and emerging machine-learning methods are being integrated to support decision-making and regulatory filings. Particular attention is given to boundary condition implementation, upscaling from core to field scale, dynamic fault modeling and reactivation assessment, trapping mechanisms, and CO2 storage in depleted hydrocarbon reservoirs. Case studies from major GCS projects illustrate how simulation tools are applied and refined through monitoring data. Despite significant progress, remaining challenges relate to how they are applied, particularly overconfidence, insufficient sensitivity analyses, limited probabilistic uncertainty quantification, and inconsistencies in regulatory expectations. We conclude by identifying key research gaps and priorities needed to support the safe, reliable, and scalable deployment of GCS.