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

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Presentation transcript:

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

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?

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)

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

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

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

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

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

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

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

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

Fitting procedure

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

(b)

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)

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

Storage potential in Sweden and investigation site

Target: sandstone aquifer at 1670 m depth

Representation in the TOUGH2 code Stratigraphic uncertainty

Parameter value uncertainty …confidence interval for k

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

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

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

Summary of plume behaviour

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),

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

/

m m

PROCESSES DETERMINING THE FATE OF THE HYDROCARBON POLLUTION

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