Lab-on-a-chip insights: advancing subsurface flow applications in carbon management and hydrogen storage

Area of Science:

• Energy Science and Engineering
• Geosciences
• Chemical Engineering

Background:

• Sustainable energy transition necessitates advanced solutions for climate change mitigation.
• Hydrogen and carbon storage and utilization technologies are pivotal for this transition.
• Microfluidic technologies offer unique pore-scale insights into subsurface fluid dynamics.

Purpose of the Study:

• To review the role of microfluidic technologies in advancing subsurface fluid dynamics for CCUS, EOR, and UHS.
• To highlight how microfluidic platforms visualize pore-scale interactions crucial for process optimization.
• To discuss the integration of advanced techniques like machine learning with microfluidics for predictive capabilities.

Main Methods:

• Development of lab-on-a-chip devices mimicking subsurface conditions.
• Detailed studies of phenomena like viscous fingering, capillary trapping, and phase behavior.
• Integration of advanced imaging, spectroscopy, and machine learning (ML) with microfluidic experiments.

Main Results:

• Microfluidics provide clear visualization of fluid-fluid and fluid-solid interactions at the pore scale.
• Lab-on-a-chip devices enable detailed studies of CCUS, EOR, and UHS processes, including hysteresis in hydrogen storage.
• Integration with ML enhances understanding and predictive capabilities for subsurface applications.

Conclusions:

• Microfluidic technologies are integral to advancing CCUS, EOR, and UHS.
• Continued research, especially ML integration, is critical for optimizing microfluidic experiments and storage strategies.
• Further exploration of microbial activities and foam behavior in UHS can refine storage and contribute to a sustainable energy future.