Precipitation Reaction Fronts in Subsurface Environments: Insights from Experiments and Challenges for Modeling and Engineering

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1 Precipitation Reaction Fronts in Subsurface Environments: Insights from Experiments and Challenges for Modeling and Engineering INL Subsurface Biogeochemical Research (SBR) Scientific Focus Area George Redden (Technical Lead) Yoshiko Fujita Hai Huang Timothy Johnson* Roelof Versteeg** Mike McIlwain Luanjing Guo Zhijie Xu* Don Fox *Now at PNNL, **Now at Sky Research James Henriksen Robert Smith - University of Idaho Tsigabu Gebrehiwet - University of Idaho Lee Slater, Chi Zhang - Rutgers University Alexandre Tartakovsky - PNNL Andre Revil - Colorado School of Mines

2 Reaction front A region where reactants are mixing at the molecular scale to create conditions where reactions occur. Strong local chemical gradients Potentially far from equilibrium Challenging for scaling and volume averaging A A B B? A B B A A + B = C System described by A x,y,z, B x,y,z and C x,y,z System described by A, B and C

3 Engineering mineral precipitation often involves injecting at least one component of a multi-component reaction.

4 Why focus on induced mineral precipitation? Consequences Permeability reduction Fracture sealing Flow path modification for applications Environmental remediation Geologic carbon sequestration Subsurface resource extraction Geothermal (high T, P, sc-co 2 ) Enhanced oil recovery In situ mining Waste isolation repositories Subsurface energy storage and recovery Fuels, heat, pressure Geotechnical engineering of soils

5 The INL SFA: Basic and applied science aspects of amendment-driven precipitation reaction fronts Emphasize experiments at intermediate scales where system level behavior can be observed Behavior of Complex Systems AND Complex Behavior of Systems Consider conditions that could be relevant in engineered systems Physical and chemical gradients Kinetically controlled processes Strong physical-chemical process coupling Context: Modifying the mobility of 90 Sr Ca 2+ Ca 2+ HCO 3 - HCO 3 - Sr 2+ Sr 2+ Sr 2+ Coprecipitation Encapsulation Flow diversion

6 Examples of mixing-precipitation reaction fronts: INL SFA experimental campaigns I. Mixing and precipitation by double diffusion Ca 2+ CO 3 2- II. Parallel flow Ca 2+ CO 3 2- III. Sequential mixing Ca 2+ CO 3 2- IV. Urease facilitated precipitation of CaCO 3 urea CO 2-3 Ca 2+ CaCO 3

7 I. Double-Diffusion Mixing and Precipitation

8 Predecessor to gel experiments: Diffusion and precipitation in a sand matrix SO 4 2- Ca 2+

9 Predecessor to gel experiments: Diffusion and precipitation in a sand matrix SO 4 2- Ca 2+ Concentration nucleation K sp SO 2- Saturation 4 Ca 2+ state Saturation

10 Precipitation expected in 6 hours. No visible change after 6 days. Blue dye added. Migrating barrier. Chemical asymmetry? Density driven?

11 Double diffusion in gel columns CaCl 2 gel NaHCO 3 or NaH 2 PO 4 Diffusion-driven mixing zone/precipitation Hypotheses concern chemical asymmetry, reaction front focusing and migration Implications: Utility of predictions based on volume averages Sensing and data interpretation challenges

12 Carbonate vs. phosphate systems CO 3 2- Ca 2+.1M.1M PO 4 3- Ca 2+

13 Carbonate vs. phosphate systems Ca 2+ :PO 4 3- Ca 2+ :CO 3 2-

14 Carbonate system: model simulations HCO 3 - CaCO 3(s)

15 Phosphate system banding: Model simulations CaHPO 4 2H 2 O Ca 10 (PO 4 ) 6 OH 2

16 Ion ratios vary within mixing zones A B Traditional precipitation rate models consider only the saturation state, not the ratio of the component ions: Rate = k ( 1 Ω) n B A where Ω = { Ca }{ CO K so } However, precipitation rates and precipitate phase/morphology depend on ion ratio = Implications for pore filling, and solid solution chemistry

17 CaCO 3 precipitation kinetics at constant saturation (Ω~12) but variable ion ratio Max precipitation rate observed where log(r) = (CO 3 2- )/(Ca 2+ ) ~ - 0.6

18 II. Parallel Flow

19 2-D Flow Cell Ca 2+ CO 3 2-

20 Tracer test showing fluid-fluid interface and mixing 60 cm 60 cm Blue dye Red dye 50mM Na 2 CO 3 50mM CaCl 2 Darcy Flow ~ 1cm/min

21 Propagation of calcium carbonate 60 cm 50mM Na 2 CO 3 50mM CaCl 2

22 SEM images Sample Position: 45cm 2 μm 5 μm 20 μm 20 μm Sample Position: 2.5cm 5 μm 10 μm

23 III. Sequential Injection

24 Sequential injection in a 2-D fracture cell Nikon D2x camera with 55mm lens ~ 1 meter Image acquisition Flow Manifold Aperture Smooth Glass Plate Pressure Chamber Confinement Pressure Inlets Plate-Glass Window Plate-Glass Window Diffuse r LED Light Source (Fan Cooled) Fracture field with a mean 2.4E-02 cm wall separation length Composite image depicting evolution of the displacement front s leading edge (flux = 7312 cm/hr)

25 Precipitation zone narrow compared to mixing Early time: mixing zone formed; precipitation not observed. Later time and stop flow: More extensive mixing; limited precipitation. Flow Ca 2+ Ca 2+ 1 cm Area of mixing zone, segmented image CO 3 2- Mixed Volume (when injection stopped) Ca 2+ CO 3 2- Mixed Volume (after 3 days of diffusive mixing) Position of Mineral Formation (clear water flush after 3 days)

26 Sequential Injection: Early stage, Transient Precipitation Transmitted light images, 0.24 mm mean aperture, 0.36 cm/min 280 mm After 2 minutes (Precipitates dissolved after 5 minutes) Blue 100 mm CaCl 2 (Saturated WRT CaCO 3(s) ) Clear 100 mm Na 2 CO 3 (Saturated WRT CaCO 3(s) )

27 50 minutes Sequential Injection: Late stage, NO PRECIPITATION (Transmitted light images) 1mm 52 minutes 280 mm 54 minutes Blue 100 mm CaCl 2 (Saturated WRT CaCO 3(s) ) 59 minutes Clear 100 mm Na 2 CO 3 (Saturated WRT CaCO 3(s) )

28 Sequential Injection: 3 zones with preserved structure? Clear 100 mm Na 2 CO 3 (Saturated WRT CaCO 3(s) ) Saturated WRT CaCO 3(s) Blue 100 mm CaCl 2 (Saturated WRT CaCO 3(s) )

29 IV. In situ reactant generation: Urease facilitated CaCO 3 precipitation

30 urea, Ca 2+, Sr 2+ Immobilized urease NH 4+, HCO 3 - H + k ppt. Ca 2+ Sr 2+ urea k hydrol urease OH - Ka2 (Ca,Sr)CO 3 K sorption Na +, Cl -, H +, NH 4+, OH - +

31 Experimental Setup CO 2 sorbent Schematic of urease column experiment Marriott Bottle σ ph Sample Collector ~60cm Camera Multi channel resistance data system Immobilized enzyme zone Samples from individual ports σ ph

32 Urease catalyzed CaCO 3 precipitation urease urea H 2 NCONH 2 + 3H 2 O 2NH 4+ + HCO 3- + OH -

33 Urease catalyzed CaCO 3 precipitation urease urea + Ca 2+ H 2 NCONH 2 + 2H 2 O + Ca 2+ 2NH 4+ + CaCO 3 (s)

34 Urease catalyzed CaCO 3 precipitation ph Urea Ammonium ph Enzyme Zone Column Port mm Enzyme Zone Column Port mm Enzyme Zone Column Port

35 Urease catalyzed CaCO 3 precipitation Calcium Strontium Enzyme Zone Enzyme Zone mm mm Column Port Column Port Note: Solution in contact with CaCO 3(s)s and downstream appears to be significantly supersaturated.

36 a b c Pore-scale precipitation (a, b, c) CaCO 3 (vaterite?) concentrated at grain-grain contacts, (d) particle cementation in low flow rate experiment, (e) Calcite(?) is produced in higher flow rate experiment (e). d e

37 Urease catalyzed CaCO 3 precipitation: Mineralized Ca 2+ and Sr 2+ Low flow High flow Calcium/Silica Gel (moles/g) 4.5E E E E E E E E E E+00 Enzyme Zone Column Port Ca+ + Sr E E E E E E E E E E+00 Strontium/Silica Gel (moles/g) 4.5E E E E E E E E E E+00 Enzyme Zone Column Port Ca2+ Sr2+ 3.5E E E E E E E E+00 Strontium/Silica Gel (moles/g)

38 More Predictable: Precipitates form Less predictable: Supersaturated solutions in presence of solid Pore-scale distribution of solid phases Co-location of multiple precipitation products Changes in geotechnical properties of media Changes in flow paths at multiple scales Profile of solid phase saturation states Local or Volume averaged reaction rate Transient events Precipitation boundaries with irreducible permeability

39 Modeling

40 Chemical model (the short list) urea Immobilized urease Ca 2+, Sr 2+ NH 4+, HCO 3 - Urea Hydrolysis H 2 NCONH 2 + 3H 2 O --> 2NH 4+ + HCO 3- + OH - Calcium Carbonate Precipitation Ca 2+ + CO 3 2- CaCO 3 (s) Sum of the Two Above Reactions H 2 NCONH 2 + 2H 2 O + Ca 2+ 2NH 4+ + CaCO 3 (s) Kinetic Factors: > Nucleation > Precipitation (mass transfer control and intrinsic rates) > Enzyme kinetics (Fidaleo and Lavecchia (2003))

41 Chemical model (the longer list) R urea [ E] = 0 E 1 1 a R T T ref kref e CUrea total C ph + 10 KES,2 M + urea 1+ 1 ph K + + P KES,1 10 NH4 ( K C ) Solid-solution interface reactions... Nucleation...

42 Simulator Development (RAT from MOOSE) RAT is developed from MOOSE: Multi-physics Object Oriented Simulation Environment (multi-scale & multidimensional). Motivation SFA studies engineered tightly-coupled reactive transport systems mixed kinetic and equilibrium reactions coupled with flow and transport Built upon existing INL capabilities, can be readily modified to accommodate new ideas. Petsc SNES Physics Thermal Solid Contact MOOSE Framework Mesh I/O Element Library Solver Interface Trilinos NOX Reaction Diffusion 42

43 Simulations by RAT (1) Ureolytic-driven calcite precipitation urea, Ca 2+, Immobilized Sr 2+ urease NH 4+, HCO - 3

44 Simulations by RAT (1) Fluid displacement in variable aperture fracture cell Composite image depicting evolution of the displacement front s leading edge (flux = 7312 cm/hr)

45 Sensing: Complex Resistivity

46 Complex resistivity (CR, a.k.a. induced polarization) Interfacial polarization Electrolytic conduction Interfacial polarization NH 4,Na, H +, OH - Adsorption (Ca, Sr) CO Na, H + - Desorption Distribution of charge Source Current V+ V- E = 0 E = 0 V + V - Potential Phase Shift Time Amplitude

47 Urea Hydrolysis Mediated Calcite Precipitation Experiment: CR response Urea hydrolysis Polarization (σ ) Bulk conductivity (S/m) Urea stage 1 hydrolysis Conduction (σ ) stage 2 Urea hydrolysis and CaCO 3 ppt Z1 real (S/m) Z2 real (S/m) Z3 real (S/m) Z4 real (S/m) Z5 real (S/m) Z6 real (S/m) Z7 real (S/m) Z8 real (S/m) Time (minutes) Conduction and polarization mechanisms are sensitive to urea hydrolysis and precipitation processes. Processes driving the increases in phase delay during stage 1 (urea hydrolysis only) are likely responsible for the increases in bulk conductivity in hydrolyzing zones. Interfacial polarization (IP) methods offer potential for tracking reaction fronts

48 Understanding and Controlling Precipitation Reaction Fronts in Subsurface Environments Dynamics of reactant transport, mixing and mineral precipitation. Behavior of Complex Systems and Complex Behavior of Systems Many others: LBNL PNNL LANL Oregon State University Please visit posters INL SFA Overview Experiments Modeling Geophysics and Input and Suggestions