Design of a Surfactant/Polymer Process in a Hard Brine Context: A Case Study Applied to Bramberge Reservoir
Rene Tabary (IFP Energies nouvelles) | Frederic Douarche (IFP Energies nouvelles) | Brigitte Bazin (IFP Energies nouvelles) | Pierre Maxime Lemouzy (Beicip-Franlab) | Patrick Moreau (Rhodia) | Mikel Morvan (Rhodia)
Bramberge reservoir is a low temperature (40°C), high permeability (~1 Darcy) sandstone reservoir located in Germany. Waterflooded during several decades, oil production has been declining for the past few years. These conditions make this reservoir a good candidate for surfactant-polymer flooding.
Despite favourable attributes, the use of production brine, which exhibits very high hardness, as a re-injection fluid makes this project challenging and unique.
In this paper, we illustrate how this specific hurdle can be managed using a new strategy specifically developed for hard brines.
We show that surfactant/polymer formulations can be optimized in Bramberge re-injection brine despite its hardness with adequate properties for SP flooding (ultra-low interfacial tension and good solubility). The high level of divalent ions, and especially calcium ions, makes alkalis irrelevant for this project. We demonstrate using coreflood experiments that conventional injection strategies, successfully applied in soft brines (salinity gradient, etc…), and brine management options fail in these specific conditions because of the high chemicals adsorption. This high adsorption is showed to be strongly related to divalent ions.
We finally propose a successful alternative based on a careful selection of adsorption inhibitors. Using these additives, high oil recovery (94 %OOIP) was obtained together with low anionic surfactant and polymer adsorption. The overall technical performance is in line with conventional alkali-surfactant-polymer strategy in soft brine making this project very attractive and promising.
The process is currently in an optimization phase for pilot and field scale simulations allowing technical and economical optimization.
View Full Document