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Density driven flow in porous media: How accurate are our models? Wolfgang Kinzelbach Institute for Hydromechanics and Water Resources Engineering Swiss.

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Presentation on theme: "Density driven flow in porous media: How accurate are our models? Wolfgang Kinzelbach Institute for Hydromechanics and Water Resources Engineering Swiss."— Presentation transcript:

1 Density driven flow in porous media: How accurate are our models? Wolfgang Kinzelbach Institute for Hydromechanics and Water Resources Engineering Swiss Federal Institute of Technology, Zurich, Switzerland

2 Contents Examples of density driven flow in aquifers Equations –Formulation –Special features of density driven flows Benchmarks –Analytical and exact solutions –Experimental benchmark: Grid convergence –Experimental benchmark: Fingering problem Upscaling issues Conclusions

3 Density driven flows in groundwater resources management Sea water intrusion Salt water upconing under freshwater lenses (both on islands and inland) Salt water fingering under playa lakes and saltpans Flow around salt domes (nuclear waste repositories) Brine injection Leachate from waste deposits Even the ordinary tracer experiment...

4 Saltwater Intrusion Salt water Fresh water

5 Formation of toe Fresh water Salt water

6 Saltwater Upconing Salt water Fresh water

7 Example: Salt Water Upconing on Wei Zhou Island Thesis Li Guomin

8 Upconing Freshwater Lens

9 Alternative Extraction Strategies

10 Salinity backflow from Chotts in Tunisia Oasis

11 200 km Salt fingers on islands in the Okavango Delta

12 Islands and salt crusts in Delta

13 Schematic cross section of an island Transpiration Evaporation Increasing salinity of GW Trona saltcrust Increasing salinity of GW gravity vs. upward flow

14 Instability on the Islands Critical Wooding Number: k f = m/s, u ET =10 -8 m/s instable stable

15 Simulation of fingering t=900 d c max =11 mg/lt=2900 d c max =30 mg/lt=6000 d c max =54 mg/lt=8500 d c max =75 mg/l t=12400 d c max =110 mg/l t=16800 d c max =235 mg/l t=25000 d c max =350 mg/l t=32500 d c max =350 mg/l t=46500 d c max =350 mg/l t=66000 d c max =350 mg/l

16 Flow in the vicinity of a salt dome Recharge Discharge Top of salt dome Salt water - fresh water interface No density difference With density difference

17 Mass balance total mass Mass balance salt Darcy law Dispersion tensor Constitutive relationships Boundary conditions (many combinations) Basic Equations expressed in mass fraction c and pressure p e.g. Possible simplification: Boussinesq approximation

18 Features of density driven flow -Non-linearity -Consistency problem of boundary conditions -Rotational flow with closed streamlines -Plus all difficulties known from advective- dispersive transport

19 Flow in porous media and rotation Darcy-flow in heterogeneous porous media is rotational Example: But we still have: In density flow, rotation is non-trivial: closed streamlines Rotational when not parallel to For constant k/ kfkf

20 Numerical solution and testing of codes Analytical solutions Exact solutions Inter-code comparison Experimental benchmarks Grid convergence All computations are made with d 3 f, a density flow model using unstructured grids, finite volume discretization, multigrid solver, error estimator, automatic local refinement/coarsening, parallel computing

21 Idea of exact solution (steady state) Pressure equation Salt mass fraction equation Assume any differentiable functions p(x,z), c(x,z) Assume any domain Assign function values as first kind boundary conditions on boundary of that domain

22 Plug functions into flow equations Pressure Salt mass fraction Right-hand sides are not zero: They are interpreted as source-sink terms So analytical expressions are exact solution for problem with - these source-sink terms and - first kind boundary conditions with given function values Only good if source-sink terms are small and do not dominate the problem

23 Analytical expressions for exact solution (steady state) Pressure Salt mass fraction Values in example tuned to make sources/sinks small: =20, =12, h=.14, =1, 0 =1, =1, x =0.1, z =0.02, x s =1, z s =-0.1 In PDE: n=1, g=1, k=10, =1, D m =1, / c=0.1, (c)= 0 + / c c=1+0.1c

24 Analytical Salt mass fraction Pressure Values between 0 and 1.13 p units Values between 0 and 1 c units Plugged into equations for c and p

25 Source-sink distributions Total mass Salt mass Red: max. input Turquoise: 0 input Red: max. input Light blue: 0 input Blue: output

26 Computed (with 4 grid levels) Salt mass fraction Pressure Values between 0 and 1.13 p units Values between 0 and 1 c units

27 Error Pressure Salt mass fraction Red : computed value too large by % Blue: computed value too small by % Red : computed value too large by % Blue: computed value too small by %

28 Experimental benchmark 3D transient experiment in box with simple boundary and initial conditions Measurement of concentration distribution in 3D with Nuclear Magnetic Resonance Imaging Measurement of breakthrough curves Drawback: Test of both model equations and mathematics Way out: Construction of a grid convergent solution inspired by the physical experiments

29 Experimental setup Cube filled with glass beads of diameter 0.7 mm Size of model 20*20*20 cm 3 Injection of dense fluid on bottom center hole Application of base flow via top corner holes In unstable case: Injection from below and rotation All parameters measured except transverse dispersivity, diffusion coefficient

30 Experimental setup continued 20 cm Salt water stable situation unstable situation

31 Stable situation: Low concentration contrast

32 NMR images of diagonal section: stable situation at low concentration contrast Injection End Flushing Equilibration

33 NMR images of diagonal section: stabel situation at high concentration contrast Injection Equilibration Entraining End

34 Two modes No density contrast Large density contrast

35 Experimental breakthrough curves Low contrast High contrast

36 Comparison of computed and measured breakthrough curves Low contrast High contrast Choice of parameters within intervals given through measurements of those

37 Comparison of concentrations along diagonal section Low contrast case, end of experiment

38 Comparison of concentrations along diagonal section High contrast case, end of experiment

39 Level # grid points , , , ,146,689 Grid convergence: Low contrast case unit x at level 7: 1.56 mm

40 Grid convergence: Low contrast case

41 Level# grid points , , , ,146, ,974,593 Grid convergence: High contrast case unit x at level 8: 0.78 mm

42 Grid convergence: High contrast case

43 Error of grid-convergent solutions Low contrast High contrast

44 Unstable case: NMRI data

45 NMRI of vertical and horizontal section: fingering experiment Vertical section Horizontal section

46 Fingering: Experiment vs. Computation

47 Finger velocity: comparison of experiment and computation

48 Causes for poor perfomance Numerical dispersion smoothes out fingers and eliminates driving force Initial perturbance not known well enough Start of fingers on microlevel, not represented by continuum equations

49 Influence of heterogeneity on density flow Homogeneous Henry problem Heterogeneous Henry problem

50 Definition of Henry problem: Homogeneous aquifer Hydraulic conductivity 1E-2 m/s, effective diffusion coefficient 1.886E-05 m 2 /s Boundary conditions: Left fresh water flux given at 6.6E-05 m/s Right hydrostatic salt water, salt mass fraction kg/kg

51 Solution of Henry problem: Homogeneous aquifer Relative concentration contours between 0 (left) and 1 (right) in steps of 0.1

52 Heterogeneous Henry problem: Permeability distribution Lognormal distribution, exponential autocorrelation Arithmetic mean 1.68E-9 m 2, Geometric mean 1.02E-9 m 2 Variance of log(k) = 1 Corr. lengths: horizontal 0.05 m, vertical 0.05 m Red: 3.5E-08 m 2, Blue: 2.6E-11 m 2

53 Heterogeneous Henry Problem: Concentration distribution Relative concentration contours between 0 (left) and 1 (right) in steps of 0.1 Eff. diffusion coefficient as in homogeneous case Question: Are there equivalent effective parameters to mimick main effect of heterogeneity in a homogeneous model?

54 Heterogeneous Henry Problem Comparison (zero local dispersion) Heterogeneous case Only diffusion Homogeneous case: Permeability equal arithmetic mean of heterogeneous case Only diffusion Homogeneous case: Permeability equal geometric mean of heterogeneous case Only diffusion

55 Heterogeneous Henry Problem Comparison (zero local dispersion) Heterogeneous case only diffusion Homogeneous case: Permeability equal geometric mean of heterogeneous case only diffusion, zero dispersion Homogeneous case: Permeability equal geometric mean of heterogeneous case, diffusion plus macrodispersion after Gelhar&Axness

56 Heterogeneous Henry Problem Comparison (with local dispersion) Heterogeneous case Diffusion + local dispersion Homogeneous case: Permeability geometric mean Diffusion + local dispersion Homogeneous case: Permeability geometric mean Diffusion + macrodispersion after Gelhar&Axness

57 Effective dispersion parameters - Stable situation with flow against direction of density gradient effective longitudinal dispersivity given by Gelhar & Welty, A 11 (with density gradient) < A 11 (without density gradient) - Unstable situation with flow in direction of density gradient at sufficiently large Wooding/Raleigh number, dispersivities grow to infinity due to fingers forming - Horizontal flow towards a fixed concentration leads to boundary layer. Dispersion at upper right boundary and at stagnation point is upstream diffusion: c/c 0 = 1 – exp (-x/ L ) Upstream diffusion

58 Conclusions Density flow of increasing importance in groundwater field Tests for reliability of codes are available Density flow especially with high contrast numerically demanding: Grid convergence may require millions of nodes Numerical simulation of fingering instabilities still inadequate Heterogeneities can be handled by effective media approach in situation without fingering New numerical methods are in the pipeline


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