Uncertainty propagation and risk assessment for geological carbon storage
The project’s aims are to conduct research on geological carbon storage from the perspective of dynamic analysis and process systems engineering, looking in particular at the dynamics between the wellhead and the CO2 storage reservoir. The main objective is to achieve closed loop operation and management of the reservoir with respect to CO2 sequestration and storage, along with enhanced oil recovery in cases where the reservoir is not fully depleted.
Another important aspect of the research is risk assessment and uncertainty propagation. This includes making predictions on overall CO2 injectivity and storage capacity, risk of reservoir fracture and CO2 leakage. This is being investigated using Monte Carlo simulation and more efficient methods such as polynomial chaos expansions.
The student’s role in the project will be to develop methods for uncertainty propagation and risk assessment in geological carbon storage. Accurate risk assessment is crucial in geological carbon storage, especially with respect to the possibility of CO2 leakage, and in the estimation of overall CO2 storage capacity of the reservoir. The student will investigate more efficient methods of uncertainty propagation, including polynomial chaos expansion. These methods use orthogonal polynomials as a basis, and offer compact approximate descriptions of stochastic variables. The coefficients of the polynomials are evaluated by comparison with data from the full-scale reservoir model. This project will involve the development and modification of MATLAB code for uncertainty propagation and risk assessment. This will involve running reservoir simulations, constructing polynomial chaos expansion based models for uncertainty propagation, and using these models for risk assessment. There is expertise in the group related to the construction of stochastic reduced order models.