SPIE Photonics West 2021
Conference paper

Advanced optical on-chip analysis of fluid flow for applications in carbon dioxide trapping

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Carbon dioxide capture and storage into underground geological formations is a promising route to reduce emissions into the atmosphere and limit global warming. Geo-sequestration involves the injection of carbon laden solutions directly into the pore space in sedimentary rocks, saline formations, or abandoned oil fields. More scientific research is still needed to understand how the pore structure and material properties of the rock matrix influence the extent to which pressurized fluids can be injected and permeate the pore network. Our research focuses on studying the fundamental mechanics of pore infiltration at micro-and nanoscopic scales to develop a comprehensive model of carbon dioxide sequestration within geological pore networks. We are using single and two-phase flow simulations of fluid injection into the rock pore space, modeled as a network of capillaries representing the geometry extracted from high-resolution X-ray microtomography of suitable rocks [1]. To experimentally validate the simulation results, we have developed a Si/SiO2lab-on-chip platform for testing porosity models on well-defined geometries at the microscale. The single and multiphase flow measurements performed on the microfluidic chip are monitored with optical microscopy in real time. In this contribution, we will report the progress in our research and development of optical imaging techniques applied to the microfluidic chip. Specifically, we demonstrate how advanced image analysis can be used to extract information about the position and flow properties of fluids and theirinterfaces. The image analysis results are critical for calibrating high-accuracy flow simulation models for pore scale injection and mineralization of carbon dioxide. [1] Neumann, R.F., Barsi-Andreeta, M., Lucas-Oliveira, E. et al. High accuracy capillary network representation in digital rock reveals permeability scaling functions. Sci Rep 11, 11370 (2021).