Optimize a WAG Field Development Plan, Use Case of Carbonate Ultra-Deep Water Reservoir
Authors: Torrado R. Rodriguez , Paola G. De , Perez A. Fernandez , Fuenmayor A. A. , De Azevedo M. Silva , Embid S. 
Published: March 2015

Abstract
The low recovery factor associated with carbonate reservoir and the availability of affordable gas has drawn new attention to a Water Alternative Gas (WAG) strategy to enhance hydrocarbon recovery for reservoir at early stage of production. The use of WAG allows to improve sweep efficiency limiting fingering and hydrocarbon trapping at macroscopic (Water injection - WI) and microscopic (pore) (Gas Injection - GI) level.
The purpose of this work is twofold: present a new field development plan optimization formulation generalized for continuous and/or WAG injection and its suggested application to a real reservoir test case. Optimum field development plans for different strategies are presented and the advantages of a WAG strategy as opposite to a continuous water injection are further discussed. The proposed optimization problem covers well placement, control, schedule and gas lift under uncertainty. This problem is formulated as Mixed Integer Nonlinear Programing (MINLP) with non-linear constrains in order to take into account operational restrictions.
A carbonate deep water reservoir at the early stages of its exploitation has been used to evaluate this new workflow. An in-house Particle Swarm Optimization (PSO) algorithm has been used to solve this nonlinear optimization problem. The use of a real field as test bench poses additional strength on the robustness of the formulation in presence of a large number of decision variables and constrains. Special care has been taken in the field development plan selection, taking into account the optimal solution as well as additional objectives and sentiments added by the decision makers which increase the realism of the final solution.
The optima selected were compared to a WAG base case adjusted using standard commercial tools according to best practice. The results obtained for the current reservoir highlight key performances of the optimization algorithm applied to the WAG strategy. WAG increases the recovery factor and enhance an early production (paramount to improve the NPV according to the economic model) with respect to a continuous WI. The optimization of WAG cycles allows to find the best hydrocarbon production under the constrain imposed by the facilities and the gas availability. The optimum inter-well-distance and schedule results from the compromise between a strong sweep yet avoiding an early water breakthrough and reducing interference among producers. The well layout is therefore an output of the NPV optimization, the carbonate geological characterization and the operation risk. The optimal field development plan has shown a 35% of increment in NPV compared to the base case.
This workflow presented and discussed presents an innovative and general formulation for the optimization of a WAG and/or continuous injection for real reservoir under uncertainty. The optimization algorithm allows fast convergence and accurate results. The extension to multiple objective functions and the inclusion of the human decision in the optimization process is also considered.