This study investigates how a polymer flood design can be optimized while considering geological uncertainty in the reservoir models. Polymer flooding can increase oil recovery, reduce water cut, and improve sweep efficiency by diverting flow to low permeable zones. We applied two different history matching approaches (manual and gradient-based) to match data from a prolonged waterflood in the Watt field, a synthetic but realistic clastic reservoir that is based on real data and captures a wide range of geological heterogeneities and uncertainties through a range of different model scenarios and model realizations. The subsequent polymer flood is then optimized using history-matched models (constrained optimization) and the original, non-history-matched models (unconstrained optimizations). The aim is to study how geological uncertainties innate in clastic reservoir affect polymer flooding, and how different history matching approaches impact the predicted reservoir performance and optimal polymer flood design. A key observation is that shale cut-offs were a major uncertainty when optimizing the polymer flood for this field. In addition, the constrained optimization gave a much narrower forecast for incremental oil recovery during polymer flooding, possibly underestimating both risk and economic opportunities.


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  1. Arnold, D.
    et al.. (2013) ‘Hierarchical benchmark case study for history matching, uncertainty quantification and reservoir characterisation’, Computers and Geosciences, 50, pp. 4–15.
    [Google Scholar]
  2. Cannella, W. J., Huh, C. and Seright, R. S.
    (1988) ‘Prediction of Xanthan Rheology in Porous Media’, Proceedings of SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, (2), pp. 353–368. doi: 10.2523/18089‑MS.
    https://doi.org/10.2523/18089-MS [Google Scholar]
  3. Manrique, E.
    et al.. (2010) ‘EOR: current status and opportunities’, SPE Paper 130113. Society of Petroleum Engineers, 2008, pp. 1–21. doi: 10.2118/130113‑MS.
    https://doi.org/10.2118/130113-MS [Google Scholar]
  4. Sandrea, I. and Sandrea, R.
    (2007) ‘Global Oil Reserves — Recovery Factors Leave Vast Target for EOR Technologies.’, Oil & Gas Journal, 105(45), pp. 1–8.
    [Google Scholar]
  5. Sorbie, K. S.
    (1991) Polymer-Improved Oil Recovery, Glasgow and London: Blackie and Son Ltd.
    [Google Scholar]

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