Student buy-in as a key mechanism for student engagement and performance in an active-learning context is explored. This paper provides the first operational definition of student buy-in to in-class activities, in this case characterizing the complex nature of students’ responses in an active-learning classroom.

Sleipner is a commercial CO2 storage site in the North Sea with good constraints from monitoring data, but also with some significant uncertainties regarding temperature, pressure and gas/brine behavior. At Sleipner, we have used high-quality repeated seismic and gravimetric surveys for monitoring and calibrating the reservoir uncertainties. To model the CO2 behavior we have used two main approaches: a) traditional reservoir simulations, using black oil and compositional fluid descriptions; and b) invasion percolation simulations, using threshold pressure and fluid density descriptions that assume the dominance of capillary and gravity forces. The key findings from the study are: The invasion percolation simulation gave the best initial match to observed data, leading us to reassess the input assumptions for the black oil and compositional simulations. By taking into account gravity segregation and modifying the reservoir simulation input data, we were able to get a much better match for the black oil and compositional simulations. There is still scope for further optimization and history matching, however, this study has reduced the range of domain variables leading to an improved understanding of the flow processes involved in geological storage of CO2 in saline formations. The study has led us to conclude that we can make realistic and predictive CO2 storage models provided that the site-specific conditions are honored, including reservoir and fluid property characterization. The necessary tight constraints on input parameters are achieved by calibration against monitoring data. Our study illustrates both a rather novel approach to modeling CO2 storage and the need for improved input to conventional simulators. Application of our approach to other CO2 storage sites will help in achieving more realistic understanding of CO2 storage, thereby contributing to the maturation of CO2 storage technology worldwide.

Predictors of student commitment and engagement in an undergraduate science course featuring active learning are explored. The study identified student trust in the instructor as an important predictor of student commitment and engagement in an active-learning context.

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