Production strategy optimization through model-based decision analysis to manage a heavy oil reservoir: polymer flooding and intelligent wells

Abstract

It is hard to produce heavy oil from reservoirs, which leads to lower oil recovery, highinvestments, and eventually lower economic returns. Consequently, polymer flooding is arecommended enhanced oil recovery (EOR) method to that type of oil reservoir. Polymer floodingincreases water viscosity of the injected brine by adding polymers, causing a decrease in the watermobility. This allows a sweep efficiency improvement translated into a gain in oil recovery.Additionally, intelligent wells provide the capability to manage a production strategy bycontrolling multiple production zones, reducing costs of well interventions, accelerating the oilproduction, and decreasing the injection and production of water.Choosing an appropriate oil production strategy with polymer flooding is not an easy taskdue to geological, rock-fluid properties, technical, operational, and economic uncertainties.Physical phenomena in polymer properties like salinity, retention, viscosity, degradation, amongothers, bring additional uncertainties that make the selection of a production strategy even morecomplex. Also, reported problems with injectivity can impact negatively the economic returns. Inaddition, intelligent wells can be an alternative to those drawbacks since production optimizationis achieved by maximizing the sweep efficiency and controlling the production/injection schemes.Last, this doctoral proposal intends to face these challenges since EQUINOR is interestedin applying a risk-return decision analysis to a Brazilian offshore heavy oil field. Thus, theuncertainties study on this project is manly addressed to evaluate management strategies from aneconomic and operational perspective using numerical simulation studies throughout a modelbased decision analysis. This work will probably count with the cooperation of Professor Arne Skauge from University of Bergen. (AU)