"Injecting CO₂ into saline aquifers is currently the most viable approach to mitigate global greenhouse gas effect. Various monitoring techniques are required to achieve 99% accuracy in determining the location of the injected CO₂ plume. Sensor locations are critical to the monitoring quality necessary to meet this requirement but have scarcely been discussed. The pressure profile needs to be modeled accurately at the initial stage of CO₂ injection to guide sensor locations. The objective of this thesis was to develop an analytical solution for CO₂ sequestration based on time and distance. This will guide the locations of downhole pressure sensors and optimize the sensor density.
This work establishes a comprehensive pressure model, in which three flow regimes were fitted on sequences of time domain in each boundary condition, assuming a radial and homogenous saline aquifer. The model includes transient and pseudo steady- state flows to solve early time pressure. The flow front equation divides the aquifer into two flow regions. The analytical solution that applied to two field cases was compared and confirmed with the results from reservoir simulations. Sensitive analyses were performed on major aquifer parameters.
The application of this work was to determine downhole pressure sensor locations. Distributed pressure sensors have the potential to be implemented in CO₂ sequestration operations with a moderate cost. Sensor ranking was optimized by an error weighting matrix based on a covariance matrix and experimental measurement distribution in this work. Sensor placement was guided through regression analysis performed on two flow regions. With the input of sensor physical errors, various ranges of monitoring accuracy can be achieved with different sensor placement densities."--Abstract, page iii.