A multi-tier framework for CO2 storage capacity estimation: Aligning methods with data availability

Accurate estimation of geological CO 2 storage capacity is critical to the successful deployment of carbon capture and storage (CCS) projects. However, the diversity of existing methods, each with distinct data requirements and assumptions, creates challenges in selecting appropriate approaches, especially during early project stages when data are sparse. This study presents a structured, six-tier framework that guides users in selecting and applying suitable estimation techniques based on the maturity of geological and operational data. The framework integrates static, analytical, and numerical methods into a progressive, adaptive structure. It enables meaningful, constraint-aware estimates at any stage of development, even when only limited inputs are available, and supports refinement as more detailed data emerge. Each tier builds upon the last by introducing increasingly advanced methods, beginning with basic volumetric estimates and advancing through pressure-constrained calculations, injectivity modeling, and full-physics dynamic simulations. At every level, the framework provides recommended parameter ranges, fallback values, and structured uncertainty bracketing to ensure transparency and methodological rigor. Initial estimates are retained and iteratively refined, yielding progressively narrower and more defensible capacity ranges. The novelty of the framework lies in its ability to generate credible CO 2 storage estimates under any data condition and to guide practitioners through a clear, step-by-step method selection process. It offers a unified, scalable, and uncertainty-aware workflow that supports screening and field-scale design, bridging the gap between theoretical methods and applied project needs. The framework was validated on the Nisku Formation in Alberta, with site-wide and single-well capacity results aligning closely with published benchmarks, thereby confirming its predictive reliability. The analysis was further extended to evaluate the performance of multi-well configurations and enhancement strategies.