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Estimation of characteristic relations for unsaturated flow through rock fractures Jerker Jarsjö Department of Physical Geography and Quaternary Geology,

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Presentation on theme: "Estimation of characteristic relations for unsaturated flow through rock fractures Jerker Jarsjö Department of Physical Geography and Quaternary Geology,"— Presentation transcript:

1 Estimation of characteristic relations for unsaturated flow through rock fractures Jerker Jarsjö Department of Physical Geography and Quaternary Geology, Stockholm University, Stockholm, Sweden.

2 Areas of fundamental research (1)Characteristics of multiphase flow in fractured rock under different ambient conditions (2)Dependence on quantifiable fracture characteristics (aperture distribution, connectivities) (3)Multiphase flow in soil and fractured rock: Similarities and differences. - Are parameter translations of characteristic curves possible? Relevance?

3 Useful for prediction of… Conductivity of gas 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 Movement of accidental oil spills in fractured media (Granite, karst, glaciers)

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

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

6 Empirical vG relation for h<0 K(h)=K s for h  0 where, p c =capillary pressure , n, m = fitting parameters

7 Empirical vG relation for h<0 K(h)=K s for h  0 where, p c =capillary pressure , n, m = fitting parameters Related to bubble pressure Related to width of soil psd m=0.5 usually assumed

8 The cubic law for water flow in a fracture Single fractures: relation between aperture ( a ) and fracture transmissivity T: a a Direction of flow ”Cubic law” (  =density, och µ =viscosity, and g=graviational constant) Cubic law: exact relation Cubic law: approximately true

9 Fracture aperture relation 1 h 5 h48 h Darker areas=wider aperture; gas=white (SKB TR & ) 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 Water occupies the tighter parts, and air the wider parts. Similar to the porous medium case water air (gas)  cut-off aperture (a c ) assumption a c =2  w / p c

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

12 Fitting procedure

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

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16 Conclusions Simple patterns emerge from the matching of seemingly complex curves Fracture roughness related to the n-value of the van Genuchten-formulation: the rougher the fracture, the lower the matching n-value Implies that characteristic curves derived from measurable aperture statistics can be described with soil-based van Genuchten parameters (standard description in most computer codes)

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

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

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

24 Salt precipitation – injectivity effects Permeability reduction factor k/k 0 [-]

25 Summary of plume behaviour

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27 Conclusions  Stratigraphic uncertainty leads to large differences in predicted CO 2 storage in target formation  Parameter uncertainty (permeability) has small impact on CO 2 storage predictions but affects injectivity  Salt precipitation at the border of the target formation affects CO 2 injectivity  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., Scenario simulations of CO 2 injection feasibility, plume migration and storage in a saline aquifer, Scania, Sweden. International Journal of Greenhouse Gas Control, 5(5),

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

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30 m m

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32 PROCESSES DETERMINING THE FATE OF THE HYDROCARBON POLLUTION

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

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