Optimization of in-depth divergence strategies

Abstract

This study discusses the potential of the in-depth water diversion (IDD) process to enhance oil recovery from subsurface reservoirs and investigates IDD strategies through an ensemble optimization approach. Pilot studies in the North Sea performed in recent years have shown that Sodium Silicate can be applied as blocking agent, diverting water to unswept zones of the reservoir. On the other hand, numerical simulation studies have tried to simulate the IDD behaviour with methods based on weak coupling of a reservoir flow simulator and an external chemical module. This study presents a fully implicit coupled chemical-compositional-flow implementation to simulate the permeability reduction through silicate gels, since IDD is essentially a coupled flow-chemical process. In addition, this study discusses the impact of resolution in space and time on the simulation performance for 2D subsurface petroleum reservoir models. Sensitivity of the oil recovery, and IDD characteristics such as moles of silicate, to design parameters of the IDD process is discussed as well. Since adjoint gradients are not typically available for the parameters describing in-depth divergence and the uncertainties are expected to be large, the optimization study uses an ensemble-based methodology to find optimal IDD reservoir management strategies. In addition to discussing IDD strategies in a deterministic setting, the design of optimal IDD strategies under geological uncertainty is investigated. This study will demonstrate that the in-depth divergence process can be used to extend the reservoir field production life time when timing, size of the Sodium Silicate batch and concentration is optimized. Finally this study discusses the issue of computational costs associated with modeling high resolution required for accurate simulation of this coupled process.