Download presentation

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 Inlet plugging at the transition time Permeability decline 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 & 1997, SPE 38181 Khatib, Z., 1995, SPE 28488 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 α_β correlation is a missing equation

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
**Contents: Conclusions Introduction:**

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

12
**Darcy’s law accounting for permeability damage**

13
**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

14
**1d DBF: System of three equations for three unknowns**

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

15
**Skin factor 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= pvi, pressure drop increases 5 times. Calculate the pressure drop increase for T= pvi.

16
**Profiles and histories as obtained from analytical solution**

17
**Particle capture kinetics**

Inlet plugging at the transition time Permeability decline 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

18
**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 M=1 M=3 M=25 M=1 M=3 M=25 The increase happens during (1-5)10-5 p.v.i. :

19
**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

20
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 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

21
Well AA016 Offshore A Brazil

22
Well AA013 Offshore A Brazil

23
Well AA002 Offshore A Brazil

24
**Injectivity damage characterization for history of 28-6- wells**

25
**Probabilistic distributions for injectivity impairment parameters**

Well data Coreflood data

26
**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

27
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

28
**Injector A7 data were treated. Prediction**

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

Similar presentations

Presentation is loading. Please wait....

OK

Modelling Rate Effects in Imbibition

Modelling Rate Effects in Imbibition

© 2018 SlidePlayer.com Inc.

All rights reserved.

To make this website work, we log user data and share it with processors. To use this website, you must agree to our Privacy Policy, including cookie policy.

Ads by Google

Ppt on special educational needs Ppt on structure of chromosomes during prophase Ppt on water the essence of life Ppt on model view controller diagram Ppt on email etiquettes and conventions Ppt on second law of thermodynamics and entropy Download ppt on oxidation and reduction agents Ppt on power system stability course Ppt on zener diode voltage Ppt on company act 2013