Optimization of Steamflooding Heavy Oil Reservoirs

Abstract

Abstract Conformance improvement is the key to success in most enhanced oil recovery (EOR) processes including CO2 flooding and steamflooding. In spite of technical and economic limitations, foam has been used as dispersions of microgas bubbles in the reservoir to enhance mobility. Steam-foam has numerous applications in the industry, including heavy oil reservoirs, which are a significant part of the future energy supply. Steam-foam applications have been used to prevent steam channeling and steam override, thus improving overall sweep efficiency, in both continuous steam and cyclic steam injection processes. The objective of this study is to investigate the key components of this complex process, where relatively high temperatures are recorded, in order to have a robust understanding of chemistry and the thermal stability of surfactants. The efficiency and therefore economics of the steam-foam process are strongly reliant on surfactant adsorption and retention. This requires a good understanding of the process for effective sizing of the foam injected. In this study, a commercial reservoir simulator is used where surfactant transport is modeled with surfactant availability and is determined by a combination of surfactant adsorption, surfactant thermal decomposition, and oil partitioning due to temperature. The degree of mobility decrease is interpolated as a result of factors that contain aqueous surfactant kind and concentration, the presence of an oil phase, and the capillary number. An empirical foam modeling method is employed with foam mobility decrease treated by means of modified gas relative permeability curves. The simulation results outline the sensitivity of these parameters and controlling agents, providing a better understanding of the influence of surfactant adsorption and thus, a number of chemicals to be used in an efficient manner. Optimum values for decision parameters that we have control on have been determined by coupling a commercial optimization software with the reservoir simulator. Uncertainty parameters such as surfactant adsorption have been analyzed in terms of significance on the recovery process. Even though steamflooding is thoroughly studied in the literature, there is no recent in-depth study that not only investigates the decision parameters but also uncertainty variables via a robust coupling of a reservoir simulator and an optimization/uncertainty software that model use of foam in steamflooding. This study aims to fill this gap by outlining the optimization workflow, the comparison of parameters with tornado charts and providing useful information for the industry.