Integrated Framework for Constrained Optimization of Horizontal/Deviated Well Placement and Control for Geological CO2 Storage

Abstract

Summary A general framework for optimizing the locations and time-varying injection rates of a set of monobore wells for geological carbon storage is presented and applied. Two objective functions, minimization of mobile CO2 fraction at the end of the operation and maximization of storage efficiency, are considered separately in single-objective optimizations and in combination for biobjective optimization. Appropriate linear and nonlinear constraints, involving the geometry of the well configuration, injection rates, and injected mass (for pressure management), are specified. Two derivative-free algorithms, particle swarm optimization (PSO) and differential evolution (DE), are applied and assessed. The various constraints are treated using a preprocessing repair procedure, penalty functions, and a filter method. The framework uses multifidelity (MF) optimization, in which increasing levels of grid resolution are applied during the course of the optimization run. For single-objective optimizations, the MF approach is compared with high-resolution optimization. This treatment is shown to outperform high-resolution PSO and DE optimization in terms of both solution quality and computational requirements. The MF DE optimization case provides the best (feasible) solution, with a 0.090 mobile CO2 fraction at 200 years, which represents a 68% improvement over a heuristic base-case. For the second objective function, MF PSO provides a design that results in a storage efficiency of 0.074, which is about double the base-case value. The well configurations are much different for the two objective functions, with wells more closely spaced, resulting in a single merged plume, for the storage efficiency maximization case. For the mobile CO2 minimization case, by contrast, wells are separated and pulsed, which facilitates dissolution and residual trapping. Biobjective optimization is then performed, again using the MF approach, with a model based on an actual storage operation now under development. The resulting well configurations and CO2 plumes for selected Pareto-optimal solutions are presented.