Workflow of the prediction of reservoir models based on data assimilation of previous reservoir models and Bayesian inversion of rock physics models. (FE0031544– Penn State)
Plume Detection and Storage Efficiency focuses on technologies to determine:
Changes in reservoir pressure due to carbon dioxide (CO2) injection.
Where the CO2 plume is located.
How the CO2 plume moves through the reservoir.
Research under this area can include:
Modeling to predict the movement of the plume.
Monitoring technologies that measure where the plume is and where it is going.
Modeling that incorporates all the hydrologic and geochemical processes to predict how the CO2 is distributed in the pore space and ultimately trapped in the reservoir.
Geophysical tools and field measurements focused on tracking the plume and determining its spatial distribution in the reservoir.
Intelligent monitoring systems (IMSs) and machine learning, which integrate and analyze multiple data types from multiple sources over multiple time frames for decision making and performance assessment.
Tracers that can provide information on the distribution of the CO2 and where it is moving in the reservoir.
