Daniel Awofodu

PhD thesis titled "Improving Reservoir Characterization using the Adjoint Method in History Matching"

* MEPO-SenEx-tNavigator linkage for efficient history matching using batch scripting * Providing reservoir modelling and simulation solutions to clients * Uncertainty quantification * Fractured reservoir model history matching * Field development optimization * Underground gas storage simulations (e.g CCS, CCUS, N2 and H2) * Providing SenEx support to users all around the world

Assisted in a research work focused on applying a combination of derivative-free (Evolution Strategy) and derivative-based (Adjoint Method) optimization algorithms in history matching of a reservoir simulation model with polymer EOR flooding

Applied a novel optimization approach called the "Sequential Schedule Optimizer" based on the Covariance Matrix Adaptation - Evolution Strategy (CMA-ES) to field development problems (e.g. water allocation problems for NPV maximization and plateau production attainment challenges) with many control variables and long simulation times. My master thesis research aimed to devise an intelligent method for produced water management in oilfields

• Trained to write programs using Python and to use python scripts as external postprocessors in MEPO. • Performed history-matching, well location screening and optimisation on existing brownfield reservoirs as well as sensitivity & risk analysis on both greenfield and brownfield reservoirs with the aid of the leading reservoir optimisation software, MEPO. • Worked with a team of software developers and computer scientists in testing yet-to-be-released versions of MEPO and other software.