1. Prediction of wettability variation and its impact on flow using pore- to reservoir-scale simulations Matthew Jackson, Per Valvatne and Martin Blunt Centre for Petroleum Studies Department of Earth Science and Engineering Imperial College of Science, Technology and Medicine London U.K.

2. Impact of wettability variations Aim of this study is to investigate and predict the effect of wettability variations on flow at the pore- and reservoir-scales Use a pore-scale network model in conjunction with conventional reservoir-scale simulations Predict experimental relative permeability and waterflood recoveries for water-wet and mixed-wet Berea sandstone assuming wettability variations result from variations in S wi Predict the impact on recovery of wettability variations associated with a transition zone above the oil-water contact (variations in S wi )

3. The network model: detailed geometry 9mm 3 cube containing 12349 pores and 26146 throats Reconstructed directly from a sample of Berea sandstone —more likely to be truly predictive

4. The network model: detailed physics Two-phase flow in layers and corners Snap-off, piston-type displacement and co-operative pore body filling Allow wettability alteration after drainage by changing advancing contact angle allocated to each oil-filled pore and throat Drainage Waterflooding

5. Prediction of relative permeability: Water-wet Berea data (Oak, 1990) Drainage  r = 0°)

6. Imbibition  a = 50-80°) Uniform distribution Prediction of relative permeability: Water-wet Berea data (Oak, 1990)

7. Prediction of waterflood recovery: Mixed-wet Berea data (Jadhunandan and Morrow, 1990)

9. Wettability variations above OWC z SwSw More oil wet Water wet Different initial water saturations

10. Hysteresis: Killough model

11. Network model: Water-wet  a = 50-80°

12. Network model: Oil-wet  a = 110-180°

13. Oil-wet: Killough vs. network Killough model Network model

14. Effect of varying initial water saturation S wi = 0.00 S w = 0.40 S wi = 0.05 S w = 0.40 Pores contacted by oil remain water-wet

15. Effect of varying initial water saturation Pores contacted by oil become oil-wet S wi = 0.00 S w = 0.40 S wi = 0.05 S w = 0.40

16. Hysteresis: Effect at reservoir-scale Use conventional simulation to investigate effect of wettability variations on reservoir-scale flow within transition zone Simulate four cases: — assume reservoir is uniformly water-wet — assume reservoir is uniformly oil-wet — recognise wettability variation — use Killough hysteresis model with oil-wet bounding curve (measured at top of reservoir) — use relative permeability curves derived from network model

17. Maureen Field Simulation Model

18. Simulation results

19. Conclusions Predicted experimental relative permeability and waterflood data for water-wet and mixed-wet Berea sandstone Emperical hysteresis models do not capture variations in relative permeability if wettability varies with height due to variations in S wi associated with capillary rise Relative permeabilities predicted by network model reflect pore-scale displacement mechanisms which yield low water relative permeabilities for moderate S wi Wettability variation has a significant effect on predicted recovery at the reservoir-scale Demonstrate that network models of real rocks may be used as a tool to predict wettability variations and their impact on flow at the reservoir- scale

20. Acknowledgements BHP Enterprise Oil Department of Trade and Industry Gaz de France Japan National Oil Corporation PDVSA-Intevep Schlumberger Shell Statoil