Optimization of Alkaline-Surfactant-Polymer (ASP) flooding minimizing risk of scale deposition

Alkaline-Surfactant-Polymer (ASP) flooding, which is classified as chemical EOR (Enhanced Oil Recovery) technique, has a great potential to recover an additional 10-25% of the oil in place, as demonstrated during various field pilot tests. A typical ASP flooding comprises of three stages: main ASP slug, polymer post slug and finally a water slug. The surfactant reduces the interfacial-tension between the displacing fluid and oil, the alkaline reduces the surfactant adsorption and creates in-situ natural surfactant, and the polymer decreases the water to oil mobility ratio. However, the deposition of inorganic scales directly attributed to geochemical processes during ASP flooding can significantly impact the viability of ASP floods. ASP flooding has economic limitations due to the large volumes of chemicals injected. Therefore, technical and economical feasibility of ASP flooding depends on the effective use of the injected chemicals and slug formulation. The main purpose of this paper is to describe the automatic optimisation of ASP flooding designs using an optimization algorithm, in particular, PSO (Particle Swarm Optimization). The algorithm identifies the most efficient optimum ASP design for a given set of criteria, specifically minimizing the total chemical expense and the scaling risk, and maximizing the oil revenue and NPV (Net Present Value).