Mitigating climate change requires efficient computational frameworks for simulating CO2 capture and storage. In this presentation, I introduce an open simulation environment for pore-scale assessment in digital rock [1] that creates accurate capillary network representations [2] based on microscopic tomography data taken from sandstone and carbonate rock plugs [3]. Single-phase and two-phase flow simulations within a digital rock’s capillary network can be performed assuming realistic reservoir conditions. One research use case of the simulator is the injection of super-critical carbon dioxide into sandstone, for optimizing carbon dioxide saturation as function of temperature and pressure, respectively [4]. For predicting the long-term geologic storage of carbon dioxide, the simulator tracks computationally the modifications caused by carbon mineralization within each capillary of the connected pore space [1]. The process gradually reduces the diameter of capillaries over time and causes the porosity and permeability of the rock to degrade. If flow conditions are not optimized, a rock might not achieve its full geologic storage potential. 
While having the potential for improving the simulation of flow in digital rock, current applications of quantum computing are mainly in the prediction of materials properties at molecular scale [5]. One example is the binding of carbon dioxide in nano-pores designed for application in direct air capture [6]. Hybrid, quantum-classical algorithms on pre-fault tolerant quantum processing units deliver useful predictions and are a promising approach for advancing the discovery of novel materials for carbon dioxide capture.

References
[1] D. A., Lazo Vasquez, et al. “Simulating Carbon Mineralization at Pore Scale in Capillary Networks of Digital Rock”. Transp Porous Med 152, 64 (2025). https://doi.org/10.1007/s11242-025-02193-1
[2] R. F. Neumann, et al. “High accuracy capillary network representation in digital rock reveals permeability scaling functions”. Sci Rep 11, 11370 (2021). https://www.nature.com/articles/s41598-021-90090-0
[3] M. Esteves Ferreira, et al., “Full scale, microscopically resolved tomographies of sandstone and carbonate rocks augmented by experimental porosity and permeability values”. Sci Data 10, 368 (2023). https://doi.org/10.1038/s41597-023-02259-z
[4] J. Tirapu Azpiroz, et al., “Enhanced carbon dioxide drainage observed in digital rock under intermediate wetting conditions”. Sci Rep 14, 15852 (2024). https://www.nature.com/articles/s41598-024-65920-6
[5] Y. Alexeev, et al., “Quantum-centric supercomputing for materials science: A perspective on challenges and future directions”. Future Generation Computer Systems, 160, 666-710 (2024). https://doi.org/10.1016/j.future.2024.04.060
[6] M. Barroca, et al., “Exploring qubit-ADAPT-VQE for materials discovery in direct air capture”. APL Quantum 1, 046103 (2024). https://doi.org/10.1063/5.0219500