Estimation of characteristic relations for unsaturated flow through rock fractures

1. Estimation of characteristic relations for unsaturated flow through rock fractures Jerker Jarsjö Department of Physical Geography and Quaternary Geology, Stockholm University, 106 91 Stockholm, Sweden.jerker.jarsjo@natgeo.su.se

2. Areas of fundamental research • Characteristics of multiphase flow in fractured rock under different ambient conditions • Dependence on quantifiablefracturecharacteristics (aperture distribution, connectivities) • Multiphaseflow in soil and fractured rock: Similarities and differences. -Are parameter translationsofcharacteristiccurvespossible? Relevance?

3. Useful for prediction of… • Conductivityofgas or non-aqueous phase liquids (NAPLS) in fractured media • Immobilization and trapping of NAPLS in fractured media Application examples: • Storage of waste /oil in bedrock • Storage of carbon dioxide storage in deep saline aquifers and potential return flows • Movementofaccidentaloil spills in fractured media (Granite, karst, glaciers)

4. Experimental determination of pressure – saturation (- conductivity) – relationsin soil Step A-E: succesively increased underpressure (-) A B C =0: atmospheric pressure D Water saturation, S* E * S = Vw/Vtot (Vw=vol. water, Vtot=total vol.)

5. Experimental determination of pressure – saturation (- conductivity) – relationsin soil Step A-E: succesively increased underpressure (-) A B C =0: atmospheric pressure D Water saturation, S* E A B S =n C D The water saturation is a function of the underpressure, i.e. S= S(). Straightforward to determine experimentally E 0 underpressure (-, m.water column)

6. Empirical vG relation for h<0 K(h)=Ks for h0 where , pc=capillary pressure d, n, m = fitting parameters

7. Empirical vG relation Related to bubble pressure for h<0 K(h)=Ks for h0 where , pc=capillary pressure d, n, m = fitting parameters Related to width of soil psd m=0.5 usually assumed

8. The cubic law for water flow in a fracture • Singlefractures: relation betweenaperture (a) and fracturetransmissivity T: (r =density, och µ =viscosity, and g=graviational constant) ”Cubic law” Direction offlow Direction offlow a a Cubic law: exact relation Cubic law: approximately true

9. Fracture aperture relation 1 h 5 h 48 h Darker areas=wider aperture; gas=white (SKB TR-98-17 & 01-13 ) The fracture aperture distribution (and the mean aperture) can be measured in situ or in the lab

10. Distribution of water and air in a fracture • cut-off aperture (ac) assumption water ac=2w/ pc air (gas) Water occupies the tighter parts, and air the wider parts. Similar to the porous medium case

11. Fracture aperture relation For unsaturated fracture flow Predict relative fracture transmissivity through consideration of the cubic law (TR-98-17) Tus (w) us=unsaturated s=saturated w=water  Ts

12. Fitting procedure

13. Considered T-data Estimation of corresponding hydraulic apertureand mean aperture T-values estimated from hydraulic testing(R-07-48)

14. (b)

15. (b)

16. Conclusions • Simple patterns emerge from the matching of seemingly complex curves • Fractureroughnessrelatedto the n-valueof the van Genuchten-formulation: the rougher the fracture, the lower the matching n-value • Impliesthatcharacteristiccurvesderived from measurableaperture statistics can be describedwithsoil-based van Genuchten parameters (standard description in most computer codes)

17. Geological storage in deep saline aquifers Cap rock: confining unit –low permeability Storage formation: high permeability high porosity Feasable if return flows are sufficiently small (min 95% retained after 100 years)

18. Storage potential in Sweden and investigation site

19. Target: sandstone aquifer at 1670 m depth

20. Representation in the TOUGH2 code Stratigraphic uncertainty

21. Parameter value uncertainty …confidence interval for k

22. Uncertainties addressed through scenario analyses Considered scenarios: A) Base case B) No upper barrier (thin claystone layer not continuous) C) High permeability (95% confidence limit) D) Combination B+C + simulations for different injection pressures

23. Resulting plume migration (1000 days) Volumetric gas saturation [-]

24. Permeability reduction factor k/k0 [-] Salt precipitation – injectivity effects

25. Summary of plume behaviour

26. Summary of plume behaviour

27. Conclusions • Stratigraphic uncertainty leads to large differences in predicted CO2 storage in target formation • Parameter uncertainty (permeability) has small impact on CO2 storage predictions but affects injectivity • Salt precipitation at the border of the target formation affects CO2injectivity • At low injection rates, salt precipitates within the target formation, decreasing its storage ability Journal reference: Chasset, C., Jarsjö, J., Erlström, M., Cvetkovic, V. and Destouni, G., 2011. Scenario simulations of CO2 injection feasibility, plume migration and storage in a saline aquifer, Scania, Sweden. International Journal of Greenhouse Gas Control, 5(5), 1303-1318.

28. March 15, 2012 Airplane crash and kerosene spill on top of Kebnekaise mountain (Rabots glacier) Sweden

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30. 2096.3 m 2101.3 m

32. PROCESSES DETERMINING THE FATE OF THE HYDROCARBON POLLUTION

36. Sampling of water 1/week + passive 13-14 July 160 mm precipitation (TRS) 15, 18 July traced og naftalen & PAH in Rabot jokk