1 / 56

Flow and transport in highly heterogeneous and fractured media

Flow and transport in highly heterogeneous and fractured media. HDR J.-R. de Dreuzy Géosciences Rennes-CNRS. Risk assessment for High Level Radioactive Waste storage. OBJECTIVES: Characterization and consequences of heterogeneity. Predictions for a complex system Mean behavior

zahina
Télécharger la présentation

Flow and transport in highly heterogeneous and fractured media

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Flow and transport in highly heterogeneous and fractured media HDR J.-R. de Dreuzy Géosciences Rennes-CNRS

  2. Risk assessment for High Level Radioactive Waste storage PhD. Etienne Bresciani (2008-2010)

  3. OBJECTIVES: Characterization and consequences of heterogeneity • Predictions for a complex system • Mean behavior • Uncertainty • Relevant knowledge from a lack of data • Determinism of large-scale structures • Stochastic modeling of smaller-scale structures • Relation between geological structures and hydraulic complexity • What are the key hydro-geological structures? • How to identify them (directly & inversely)? J.-R. de Dreuzy, HDR

  4. Outline (fractured media) • Framework • Field observations • What is the relevant flow structure? (1996-) • From fracture characteristics to hydraulic properties • Operative modeling approach (2006-) • Discrete double-porosity models • Inverse problem (2005-) • Channel identifications • Optimal use of a data network • Numerical simulations (1996-) • Transport (2000-) • Mid- to long-term projects (2009-) J.-R. de Dreuzy, HDR

  5. Outline • Framework • Field observations • What is the relevant flow structure? (1996-) • From fracture characteristics to hydraulic properties • Operative modeling approach (2006-) • Discrete double-porosity models • Inverse problem (2005-) • Channel identifications • Optimal use of a data network • Numerical simulations (1996-) • Transport (2000-) • Mid- to long-term projects J.-R. de Dreuzy, HDR

  6. Evidences of fracture flow • 3 site-scale examples • Livingstone • Yucca Mountain • Mirror Lake • Blueprint of fracture flow • Channeling • Permeability scaling • Fracture geological characteristics

  7. Livingstone hazardous waste landfill Mixed built-in and natural wastes confinement [Hanor,1994] Artificial large-scale permeameter What is really permeability? J.-R. de Dreuzy, HDR

  8. Livingstone hazardous waste landfill Consequence of data scarcity Fractures in the confiningclay layer have not been observed but are dominant J.-R. de Dreuzy, HDR

  9. a Influence of fractures on the permeability of the clay layer

  10. Yucca mountain Permeability increases with scale High flow channeling 36Cl J.-R. de Dreuzy, HDR

  11. Mirror Lake Permeabilityscaling Flow structure Permeability decreases with scale High flow channeling

  12. 1st Fracture geologicalcharacteristic: Fracture length distribution Odling, N. E. (1997), Scaling and connectivity of joint systems in sandstones from western Norway, Journal of Structural Geology, 19(10), 1257-1271. Bour, O., et al. (2002), A statistical scaling model for fracture network geometry, with validation on a multiscale mapping of a joint network (Hornelen Basin, Norway), Journal of Geophysical Research, 107(B6). Hornelen, Norway a=2.75 O. Bour, Ph. Davy

  13. Organization of fractures Correlation between fracture positions PhD C. Darcel (1999-2002) Mechanical interactions between fractures Ph. Davy D2D=1.7 Joint set in Simpevarp (Sweden) Ph. Davy, C. Darcel, O. Bour, R. Le Goc

  14. Outline • Framework • Field observations • What is the relevant flow structure? (1996-) • From fracture characteristics to hydraulic properties • Operative modeling approach (2006-) • Discrete double-porosity models • Inverse problem (2005-) • Channel identifications • Optimal use of a data network • Numerical simulations (1996-) • Transport (2000-) • Mid- to long-term projects (2009-) J.-R. de Dreuzy, HDR

  15. Reduce complexity from geology to hydraulicsFracture network simulation Complex medium structure Simple flow equation + Simple flow equation Complex parameters Identified flow structures Complex flow equation Simple parameters Flow structure? K~exp[w(p,a).s2(log K)/2] J.-R. de Dreuzy, HDR

  16. Reduce complexity from geology to hydraulicsFracture network simulation Complex medium structure Simple flow equation + Simple flow equation Complex parameters Identified flow structures Complex flow equation Simple parameters Flow structure? K~exp[w(p,a).s2(log K)/2] J.-R. de Dreuzy, HDR

  17. de Dreuzy, J. R., P. Davy, and O. Bour (2001), Hydraulic properties of two-dimensional random fracture networks following a power law length distribution: 1-Effective connectivity, Water Resources Research, 37(8). a modeling paradigm J.-R. de Dreuzy, HDR

  18. Influence of fracture organization At threshold Far above threshold Non correlated fractures D=d a=2.75 Correlated fractures D=1.75 a=2.75 Close Permeability Different flow structure Same permeability Same flow structure de Dreuzy, J.-R., et al. (2004), Influence of spatial correlation of fracture centers on the permeability of two-dimensional fracture networks following a power law length distribution, Water Resources Research, 40(1).

  19. Reduce complexity from geology to hydraulicsFracture network simulation Complex medium structure Simple flow equation + Simple flow equation Complex parameters Identified flow structures Complex flow equation Simple parameters Flow structure? K~exp[w(p,a).s2(log K)/2] J.-R. de Dreuzy, HDR

  20. Well test interpretation models D=2 10 h Transport dans les fractals 100 h 1<D<2 D : dimension fractale dw : dimension de transport anormal D=1

  21. Well test in Ploemeur Fractional flow dimension n=1.6 Fractional flow dimension n=1.6 contact zone normal fault zone Anomalous diffusion exponent dw= 2.8 Meaning of n and dw? Le Borgne , T., O. Bour, J.-R. de Dreuzy, P. Davy, and F. Touchard, Equivalent mean flow models for fracturedaquifers: Insights from a pumping tests scalinginterpretation, Water ResourcesResearch, 2004.

  22. Inverse problem on (n,dw) Ploemeur Integrated information on flow structure de Dreuzy, J.-R., et al. (2004), Anomalous diffusion exponents in continuous 2D multifractal media, PhysicalReview E, 70. de Dreuzy, J.-R., and P. Davy (2007), Relation between fractional flow and fractal or long-range permeability field in 2D, Water Resources Research, 43.

  23. Conclusion on the influence of fracture characteristics on hydraulic properties • Blueprint of structures on data • Sensitivity of well tests on structure organization • Classical upscaled hydraulic approaches • Strong homogenization • Strong localization • Intermediary flow structures • Deterministic versus statistical structures depending on available data and objectives J.-R. de Dreuzy, HDR

  24. Outline • Framework • Field observations • What is the relevant flow structure? (1996-) • From fracture characteristics to hydraulic properties • Operative modeling approach (2006-) • Discrete double-porosity models • Inverse problem (2005-) • Channel identifications • Optimal use of a data network • Numerical simulations (1996-) • Transport (2000-) • Mid- to long-term projects (2009-) J.-R. de Dreuzy, HDR

  25. From classical DFN and continuous approaches to an alternative hybrid approach PhD DelphineRoubinet 2008-2010 PhD Romain Le Goc 2007-2009 J.-R. de Dreuzy, HDR

  26. Classical modeling approaches Geological data Fracture characteristics Hydraulic data geochemical data DATA Calibration Parameterization inverse direct MODEL Homogenized permeabilities Continuous models-deterministic Geometrical structures DFN-stochastic Mean behavior PREDICTIONS Uncertainty Equilibrium between data, model and predictions (objectives) J.-R. de Dreuzy, HDR

  27. Alternative: identifiable hybridmodelingapproach Geological data Fracture characteristics Hydraulic data geochemical data DATA Inverse Inverse direct Inverse 0 MODEL Discrete dual-porosity model Stochastic smaller fractures Deterministic larger fractures Mean behavior PREDICTIONS Uncertainty Equilibrium between data, model and predictions (objectives) J.-R. de Dreuzy, HDR

  28. Discrete Dual-Porosity modelsPhD DelphineRoubinet 2008-2010 PhD DelphineRoubinet (2008-2010) J.-R. de Dreuzy, HDR

  29. Equivalent hydraulic matrix (EHM) permeability Tensor EHM PhD D. Roubinet (2008-2010)

  30. Increasing the relevance of fracture-matrix exchanges (experiments )Y. Méheust, J. de Brémondd’ArsPhD of L. Michel (2005-2008) and J. Bouquain (2008-2010) Rough fracture experiments PhD. Laure Michel LB pore-scale simulation of advection, diffusion and gravity With L. Talon, H. Auradou (FAST) Advection dominant Gravity dominant Importance of gravity

  31. Outline • Framework • Field observations • What is the relevant flow structure? (1996-) • From fracture characteristics to hydraulic properties • Operative modeling approach (2006-) • Discrete double-porosity models • Inverse problem (2005-) • Channel identifications • Optimal use of a data network • Numerical simulations (1996-) • Transport (2000-) • Mid- to long-term projects (2009-) J.-R. de Dreuzy, HDR

  32. Identification of major flow channels from head data (PhD Romain Le Goc 2007-2009) Minimization of an objective function = mismatch between data and model Non convex objective functions Gradient algorithms Monté-Carlo inverse algorithms like simulated annealing, genetic algorithms, taboo search,… PhD. Romain Le Goc (2007-2009)

  33. Inversion algorithmIterative parameterization of the channels First step Objective Function (classical least-square formulation): Solving direct problem Parameter estimation in optimizing Fobj using simulated annealing PhD. Romain Le Goc (2007-2009)

  34. Second step Inversion algorithm Objective Function with regularization term Regularization term: values from previous step as a priori values PhD. Romain Le Goc (2007-2009)

  35. Inversion algorithm i-th step Objective Function with regularization term Regularization term is build at each iteration The refinement level is controlled by the information included in the data (accounting for under- and over-parameterization)‏ PhD. Romain Le Goc (2007-2009)

  36. Knowledge content of dataData sensitivity to heterogeneity FLOW Flow structure in a 2D synthetic fracture network PhD. Romain Le Goc (2007-2009)

  37. Outline • Framework • Field observations • What is the relevant flow structure? (1996-) • From fracture characteristics to hydraulic properties • Operative modeling approach (2006-) • Discrete double-porosity models • Inverse problem (2005-) • Channel identifications • Optimal use of a data network • Numerical simulations (1996-) • Transport (2000-) • Mid- to long-term projects (2009-) J.-R. de Dreuzy, HDR

  38. Field perspective on the inverse problemLimestone aquifer example (SEH)J. Bodin, G. Porel, F. Delay, Univ. of Poitiers, MACH-1 M2 AlexandreBoisson 2007 J. Bodin, G. Porel, F. Delay, University of Poitiers

  39. Niveau piézométrique 105 m 14 m 34 m 17 m 3 m FRACTURES KARST J. Bodin, G. Porel, F. Delay

  40. LARGE NUMBER OF WELLS Modeling exercise: Prediction of doublet test from all other available information J.-R. de Dreuzy, CARI 2008 J. Bodin, G. Porel, F. Delay

  41. Sensitivity depends on stimulation configuration Collaboration with J. Erhel (INRIA) & A. Ben Abda (Tunis)

  42. Inverse problem on a broader range of hydraulic data • Point-wise head and flow data (PhD. Romain Le Goc) • Monopole and dipole tests (with J. Erhel & A. Ben Abda) • Dipole nets • Tripoles do not bring additional facilities • Flow-metry (with T. Le Borgne & O. Bour) • Identification of 3D flow structures • Use of travel-time and geochemical data (with L. Aquilina) • In situ fracture-matrix interactions on 222Rn and 4He data on Ploemeur site (M2 N. Le Gall) • Long-term chronicle of nitrates and sulfates on Ploemeur (C. Darcel & Ph. Davy) J.-R. de Dreuzy, HDR

  43. Outline • Framework • Field observations • What is the relevant flow structure? (1996-) • From fracture characteristics to hydraulic properties • Operative modeling approach (2006-) • Discrete double-porosity models • Inverse problem (2005-) • Channel identifications • Optimal use of a data network • Numerical simulations (1996-) • Transport (2000-) • Mid- to long-term projects (2009-) J.-R. de Dreuzy, HDR

  44. Intensive development and use of numerical methods10-years collaboration with J. Erhel (INRIA) • Balance between precision and efficiency • 3D fracture flow simulations • B. Poirriez (PhD INRIA 2008-2010) • G. Pichot (Post-Doc Géosciences Rennes 2008-2009) • Transient-state simulations • Large-scale intensive transport simulation • A. Beaudoin (Univ. of Le Havre) • Parallelization • Sub domain methods • D. Tromeur-Dervout (Univ. of Lyon) • Platform development • E. Bresciani (INRIA, 2007) • N. Soualem (INRIA, 2008-2010) J.-R. de Dreuzy, CARI 2008

  45. 3D flow and transport simulation in fractured media Broad power-law length distribution n(l)~l-a with lmin<l<L Large number of fractures: ~103 to 105 a=3.4 L=50 lmin ~15 103fractures Post-Doc GéraldinePichot (2008-2009) PhD BaptistePoirriez (2008-2010)

  46. Relaxing mesh generation difficulties by using Mortar-like methods Non-Matching Fracture meshes Matching Fracture meshes Head distribution in a simple fracture network Post-Doc G. Pichot (2008-2009)

  47. Outline • Framework • Field observations • What is the relevant flow structure? (1996-) • From fracture characteristics to hydraulic properties • Operative modeling approach (2006-) • Discrete double-porosity models • Inverse problem (2005-) • Channel identifications • Optimal use of a data network • Numerical simulations (1996-) • Transport (2000-) • Mid- to long-term projects (2009-) J.-R. de Dreuzy, HDR

  48. Transport • Transport in fractured media • The example of percolation theory (2001) • Pre-asymptotic to asymptotic regimes • Collaboration with A. Beaudoin & J. Erhel (2006-) • Velocity field structure • Collaboration with T. Le Borgne & J. Carrera • Reactive transport • Simulation means • Fluid-Solid and Fluid-Fluid reactivity J.-R. de Dreuzy, HDR

  49. Pre-asymptotic and asymptotic laws for inert transport Advection-diffusion in highly heterogeneous media (s2=9) J.-R. de Dreuzy, HDR

  50. Reactive transport a=1, n=0.9, D=0, gKa=1, s2=1.5 Particles Concentration Influence of heterogeneity on: - Sorption reactivity (PhD. K. Besnard 2001-2003) - Dynamic of mixing (T. Le Borgne, M. Dentz, J. Carrera)

More Related