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Skin Factor due to Injectivity Decline Injection Well History Analysis and Interpretation

Skin Factor due to Injectivity Decline Injection Well History Analysis and Interpretation . Bedrikovetsky , P., Fonseca, D. R., da Silva, M. J. (North Fluminense State University, Rio de Janeiro ) Furtado, C., Serra de Souza, A.L. & Siqueira, A.G. ( Petrobras, Cenpes ). Injectivity index

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Skin Factor due to Injectivity Decline Injection Well History Analysis and Interpretation

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  1. Skin Factor due to Injectivity Decline Injection Well History Analysis and Interpretation Bedrikovetsky , P., Fonseca, D. R., da Silva, M. J.(North Fluminense State University, Rio de Janeiro ) Furtado, C., Serra de Souza, A.L. & Siqueira, A.G.(Petrobras, Cenpes)

  2. Injectivity index II = q/Dp

  3. Particle capture kinetics Deposition at core inlet Permeability decline Inlet plugging at the transition time 4 deep bed filtration parameters: λ – filtration coefficient β – formation damage coeficient α – critical porosity ratio kc – external cake formation Transition time

  4. Impedance J – reciprocal of II 3 equations: m(λ,β), ttrans(α, λ) and mc(kc, λ,β, α) 1 equations is missing !!! Proposal: critical porosity ratio α=0.5 Mean α=0.1 • M. Sharma, S. Pang, K. Wennberg, 1994, SPE 28489 & 1997, SPE 38181 • Khatib, Z., 1995, SPE 28488 α_β correlation is a missing equation • W.M.G.T. van den Broek, Bruin, J.N., Tran, T.K., 1999, SPE 54769 • Bedrikovetsky, P., Tran, P. , Van den Broek, et.al, 2003, J SPE PF, No 3 • Da Silva, M., Bedrikovetsky, P., Van den Broek, W.M.G., 2004, SPE 89885

  5. Injectivity Index and Impedance

  6. ASSUMPTIONS OF THE INJECTIVITY IMPAIRMENT MODEL • ·Water incompressibility • ·Small particle concentration -> the suspension density is equal to water density • ·No diffusion • ·Linear law for particle capture kinetics • ·Constant filtration coefficient • ·No particle penetrates after the transition time • Incompressible external filter cake

  7. Injectivity decline curve treatment and prediction Impedance curve

  8. Injectivity damage parameters as calculated from well history Sharma, M., Pang, S., Wennberg, K.E., 2000, J SPE P& F Treatment of 27 routine lab test data from SPE by the α(β) correlation Bedrikovetsky, P., Tran, P. , Van den Broek, et.al, 2003, J SPE PF, No 3

  9. Offshore A, Brazil • Contents: • Introduction: • Analytical model for injectivity impairment accounting for varying Oil-Water mobility • Effect of varying O-W mobility • Injection well impairment – prediction results • Conclusions

  10. 1. Deep bed filtration of injected particles Physics meaning of filtration coefficient

  11. Darcy’s law accounting for permeability damage

  12. One Dimensional Deep Bed Filtration: System of three equations for three unknowns Mass balance for suspended and retained particles Particle capture kinetics Darcy’s law with permeability damage

  13. 1d DBF: System of three equations for three unknowns Mass balance for suspended and retained particles Particle capture kinetics Introduce dimensionless radius, time, rate and concentrations Darcy’s law with permeability damage The dimensionless system is: • Iwasaky, T., 1937 • Herzig, J., Leclerc,D. and Goff, P. 1970 • Sharma M., et.al., 1987, 1994, 1997

  14. 1D injection of particle suspension into a “clean” core Impedance versus time T, p.v.i. Skin factor During constant rate injection into an injection well during T=0.0001 pvi, pressure drop increases 5 times. Calculate the pressure drop increase for T=0.0005 pvi.

  15. Profiles and histories as obtained from analytical solution

  16. Particle capture kinetics Permeability decline Inlet plugging at the transition time Deposition at core inlet 4 deep bed filtration parameters: λ – filtration coefficient β – formation damage coeficient α – critical porosity ratio kc – external cake formation Transition time

  17. M=1 M=1 M=3 M=3 M=25 M=25 Injectivity Increase During Damage-Free Waterflooding During the particle-free water injection into a reservoir saturated by oil that is less mobile than water, the total mobility ratio increases M times due to displacement of less mobile fluid by more mobile one The increase happens during (1-5)10-5 p.v.i. :

  18. Mass balance for water (Buckley-Leverett) Darcy’s law for total oil-water flux Total oil-water mobility accounting for particle retention in swept zone Mass balance for suspended and retained particles Kinetics of particle retention Combined Effect of Formation Damage and Mobility Variation on Injectivity Decline

  19. 1 1 4 4 2 5 3 6 2 5 3 6 Impedance curve behaviour for M=1, 3 and 25 for high and low formation damage (curves 1,2,3 and 4,5,6 respectively); a)for time scale 0.01 p.v.i.; b) zoom for time scale 0.00001 p.v.i. The effect is particularly significant for heavy oil reservoirs and for relatively low formation damage If during the short initial waterflooding stage in a heavy oil reservoir the injectivity does not change, the reservoir suffers large formation damage which will cause a significant injectivity decrease

  20. Well AA016 Offshore A Brazil

  21. Well AA013 Offshore A Brazil

  22. Well AA002 Offshore A Brazil

  23. Injectivity damage characterization for history of 28-6- wells

  24. Probabilistic distributions for injectivity impairment parameters Coreflood data Well data

  25. Well-history-based Injectivity Prediction with and without varying O_W mobility effect Shumbera, D. A. et.al, 2003, SPE 84416 Paige, R. W. et al, 1995, SPE 29774

  26. Conclusions • Some injectivity index increase before the injectivity impairment is explained by displacement of more viscous oil by less viscous water from injector vicinity • The analytical model for injectivity impairment accounts for particle deep bed filtration, external cake formation and for varying oil-water mobility during waterflood • The analytical model allows determination of the injectivity impairment coefficients – filtration and formation damage coefficients, critical porosity fraction and cake permeability - from well injectivity decline curve • The injectivity impairment coefficients as obtained from treatment of xxx injectors vary in the same intervals as that obtained from lab coreflood

  27. Injector A7 data were treated. Prediction. Well fracturing was anticipated • Acidification was anticipated in case of well A13. • Reservoir B is similar to reservoir A. Well injectivity was predicted. • Finally, it was recommended to drill 37 wells instead of 26 wells • Horizontal injector N23 data have been treated, and penetration radius 1/ was found to be xxx cm. Acidification was planned based on this radius. It allows to economise xxx cu m of acid • Vertical well N13 data have been treated, and penetration radius 1/ was found to be xxx cm. It allows recommending xxx cm depth of perforation instead of xx cm planned before

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