Gigatonne scale geological storage of carbon dioxide and energy (such as hydrogen) will be central aspects of a sustainable energy future, both for mitigating CO₂ emissions and providing seasonal-based green energy provisions. In this Review, we evaluate the feasibility and challenges of expanding subsurface carbon dioxide storage into a global-scale business, and explore how this experience can be exploited to accelerate the development of underground hydrogen storage. Carbon storage is technically and commercially successful at the megatonne scale, with current projects mitigating approximately 30 Mt of CO₂ per year. However, limiting anthropogenic warming to 1.5°C could require gigatonnes of storage per year by 2050, and a scaleup from 2025 approaching rates of deployment that would be historic for energy technology. Scale-up is not limited by geology or engineering. Advances in understanding storage complex geology, subsurface fluid dynamics, and seismic risk underpin new engineering strategies including the development of multi-site, basin scale, storage resource management. Instead economic and societal contraints pose barriers to project development. Underground hydrogen storage, still in development, will face similar issues. Overcoming these barriers with strengthened financial incentives, and programs to address concerns inhibiting public acceptance, will enable the storage of CO₂ at climate relevant scales.

Multiphase flows in porous media are important in many natural and industrial processes. Pore-scale models for multiphase flows have seen rapid development in recent years and are becoming increasingly useful as predictive tools in both academic and industrial applications. However, quantitative comparisons between different pore-scale models, and between these models and experimental data, are lacking. Here, we perform an objective comparison of a variety of state-of-the-art pore-scale models, including lattice Boltzmann, stochastic rotation dynamics, volume-of-fluid, level-set, phase-field, and pore-network models. As the basis for this comparison, we use a dataset from recent microfluidic experiments with precisely controlled pore geometry and wettability conditions, which offers an unprecedented benchmarking opportunity. We compare the results of the 14 participating teams both qualitatively and quantitatively using several standard metrics, such as fractal dimension, finger width, and displacement efficiency. We find that no single method excels across all conditions and that thin films and corner flow present substantial modeling and computational challenges.