Chemical Enhanced Oil Recovery (EOR) techniques have recently seen a new revival owing to high oil consumption and favorable conditions that drove the oil price in a range where use of chemical is becoming economically viable. Advancements in technologies and understanding of past failures also contribute to this revival. However it appears that there is a lack of a comprehensive tool which allows exploration and assessment of combined chemical EORs at the field scale, and which can be driven dynamically to simulate realistic field applications.

In this paper we propose a set of integrated models for polymer-brine, surfactant, alkaline and foam including ions exchange for calculating effective salinities. These models can be driving by a set of flexible field management functionalities which allow a dynamic optimization of the use of the chemicals to maximize oil contact and ultimately its recovery.

A work flow to assess the balance of viscous, capillary and gravity forces involved in the EOR process is proposed to pre-screen the type of chemicals needed to modify the force balance. This approach will precede and guide the dynamic optmization.


Exploration for hydrocarbons is reaching global frontiers, and the short- and long-term challenges will be to maximize recovery from existing fields. As an important subset of the enhanced oil recovery (EOR) offering, chemical EOR techniques have developed as an economical and viable alternative for increasing oil recovery. Their success though relies heavily on a thorough understanding and ne-tuning of the chemical interactions between the injected chemicals, the fluids in place, and the rock. These interactions eventually determine optimal injection and production scenarios and ultimately the total increment in oil recovery.

Modeling of processes such as alkaline-surfactant-polymer (ASP) flooding, low salinity water flooding, solvent flooding, and foam injection for gas mobility control require a detailed description of the EOR agent interaction with the rock and reservoir fluids. This includes flexible modeling of solution viscosities, non-Newtonian behavior,

permeability reductions due to adsorption (e.g. in polymer flooding), capillary de-saturation effect due to decreasing oil-water interfacial tension, chemical losses to the formation due to adsorption, change of wettability characteristics, and chemicals degradation, to mention just a few.

However, the success and cost-effective design of EOR projects relies on the ability to model complex combinations of these processes in realistic reservoir settings while taking into account limitations in surface equipment, project economics, and consistency in the numerical solution. Being able to monitor the chemicals within the reservoir and being able to adapt the injection and production schedule automatically become key elements in optimizing chemical EOR processes.

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