I am a PhD candidate in energy resources engineering at Stanford School of Earth, Energy and Environmental Sciences, and a 2019 Knight-Hennessy scholar. I graduated from the Colorado School of Mines with a bachelor’s degree in petroleum engineering and a minor in public affairs, and a master’s degree in petroleum engineering. I am passionate about tackling the dual challenge of meeting global demand for energy while lowering greenhouse gas emissions.
My interest in Carbon Capture, Storage, and Utilization (CCUS) has led me to study the intricate surface chemistry and physics of rocks and their interactions with reservoir fluids and injected CO2. My research employs experimental, machine learning and modelling techniques to understand and optimize carbon storage and utilization processes. Experimental procedure using x-ray computed tomography (CT) imaging can capture continuously the dynamics of reactive fluid imbibition. However, field of view during dynamic experiments, especially using clinical CT, is typically insufficient to characterize accurately shale fabric features on the order of micrometers, or less. The lack of resolution is also a common problem while acquiring seismic images during injection at field scale. I aspire to reduce the uncertainties during CO2 injection and monitoring through the means of enhanced visualization achieved using super resolution convolutional neural networks. The enhanced experimental observations allow me to create elaborate reactive transport models.