Multi-Scale Reactive Transport Modeling · A: High resolution atom probe tomography (APT) profile...
Transcript of Multi-Scale Reactive Transport Modeling · A: High resolution atom probe tomography (APT) profile...
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Carl Steefel1, Sergi Molins1, Hang Deng1, Christophe Tournassat2, Lauren
Beckingham3, Li Yang1, Jennifer Druhan4, David Trebotich1
1 Energy Geosciences Division, Lawrence Berkeley National Laboratory 2 BGRM, French Geological Survey Orléans, France 3 Auburn University, Alabama 4 University of Illinois, Champaign
Multi-Scale Reactive Transport Modeling
October 25, 2016
Bureau de Recherches Géologiques et Minières
Orleans, France
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Acknowledgments
• This work was supported by the U.S. Department of
Energy, Office of Science, Basic Energy Sciences, Chemical
Sciences, Geosciences, and Biosciences Division.
• This work was also supported as part of the Center for
Nanoscale Control of Geologic CO2, an Energy Frontier
Research Center funded by the U.S. Department of
Energy, Office of Science, Basic Energy Sciences.
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Work to date has covered a range of scales, but
scales have not been coupled
Multiscale Problem
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Coupled processes in reactive transport
Steefel, DePaolo, & Lichtner, 2005
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Pore to Continuum Scale
• Pore scale models
• Solid, gas, and liquid interfaces
resolved
• Gradients in concentration and
reaction rate can develop
• Continuum models
• Solid, liquid, and gas all coexist in
space within REV
• Reactions treated as if taking place
throughout control volume
• Fluid phase is well mixed (no
gradients in concentration or rate)
Li et al, 2008
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Equations: Pore to Continuum Scale
Pore Scale Continuum or Darcy Scale
Flow
𝜕𝒖
𝜕𝑡+ 𝒖 ⋅ 𝛻 𝒖 + 𝛻𝑝 = 𝜈Δ𝒖
𝛻 ⋅ 𝒖 = 0
𝒒 = −𝒌
𝜇𝛻𝑝
𝛻 ⋅ 𝒌𝛻𝑝 = 0
Transport 𝜕𝑐
𝜕𝑡= 𝛻 ⋅ 𝐷𝛻𝑐 − 𝛻 ⋅ 𝒖𝑐
𝜽𝜕𝑐
𝜕𝑡= 𝛻 ⋅ 𝒟𝛻𝑐 − 𝛻 ⋅ 𝒒𝑐
where 𝒟 = 𝜽𝝉𝐷 + 𝜶𝑳 𝒖
Reaction
−𝐷𝛻𝑐 ⋅ 𝒏 = 𝑘 𝑓(𝒄) 𝑟 = 𝑘 𝑨 𝑓(𝒄)
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From Experiment to Characterization to High-
Resolution Simulation
Molins et al, ES&T 2014
Capillary tube experiment on
calcite
Microtomography
at the ALS
Digital image of CaCO3
packed capillary tube for
simulation
Pore-scale reactive transport simulation with 3
billion degrees of freedom
Comparison with
experiment
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Fracture Evolution
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The formation of an altered layer caused
by preferential dissolution of calcite is
also evident in the µCT images.
The µCT images and
aperture maps showed the
formation of a preferential
flow channel in the
fracture, i.e. wormholing or
channeling
Duperow Experimental Results
Ajo-Franklin et al., 2016
Ajo-Franklin et al., 2016
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Movie courtesy Dave Trebotich, Berkeley
Lab
Initial data for simulation from Beamline
8.3.2, Advanced Light Source, Berkeley Lab
Fracture Evolution in Duperow Dolomite
scCO2 saturated brine injected into fracture from left side
High resolution pore scale model showing mineral
dissolution and wormholing
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Subsurface Exascale Computing
Exascale Computing: 1018 floating point operations/sec
High resolution pore scale simulations of topology of a single fracture in dolomite using Chombo-Crunch.
Top: Initial geometry of fracture. Bottom: Modified geometry after 18 hours.
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2.5D Micro-Continuum Model for
Fracture Evolution
• Each grid is represented as a
continuum
o Porosity: 𝜙𝑖,𝑗 = 𝑏𝑖,𝑗/𝐷𝑍
o Permeability: 𝑘𝑖,𝑗 = 𝑏𝑖,𝑗3 /(12𝐷𝑍)
o Aperture (𝑏) changes as a result of
mineral reactions.
• The fracture is discretized in
two dimensions parallel to
the fracture plane
o Aperture map of the initial
fracture geometry derived
from the µCT images
Deng et al, 2016
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The temporal changes cannot be captured, regardless of the parameters used.
A diffusion coefficient on the order of 10-10 m2/s was used for the altered layer.
The simulation results demonstrate that the diffusion limitation caused by the altered layer is the mechanism for decreasing calcite dissolution over time.
2.5D Modeling Results: Effluent Chemistry
Without diffusion limitation With diffusion limitation
Deng et al, 2016
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The model captures the spatial pattern of fracture aperture increase.
Without diffusion
limitation With diffusion
limitation Experiment
Ap
ertu
re c
ha
ng
e [m
m]
2D maps of aperture change
2.5D Modeling Results: Aperture Change
Deng et al, 2016
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Glass Corrosion
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Resolution of Nanoscale Reaction Fronts
A: High resolution atom probe tomography (APT) profile across glass alteration front.
B: Schematic representation of distribution of fronts for 25 year altered glass shown on left.
Gin et al. (2013)
Application to nanoscale reaction fronts resulting from
borosilicate glass corrosion/weathering over 25 years
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mKC Model for Glass Corrosion
Diffusion of water through the pristine glass and its alteration products;
Ion exchange between water and the cations in the glass;
Kinetically controlled hydrolysis reactions resulting in breaking of glass
network bonds (Si, B, Al);
Multicomponent diffusion of ions through the glass corrosion products;
Precipitation reactions for amorphous and/or crystalline phases of variable
composition that are kinetically and thermodynamically controlled;
Kinetically controlled ripening and/or densification reactions that can reduce
the porosity and/or pore connectivity (and thus the diffusivity) of the
corrosion products;
Kinetically and thermodynamically controlled formation of new crystalline
phases (e.g., smectite, zeolite), with possible consequences for the transport
properties of the corrosion layer;
Flow and diffusion in the aqueous phase adjacent to the glass surface.
Steefel et al, 2015
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Simulation of Nanoscale Reaction Front
𝑅𝑐𝑜𝑟𝑟 = 𝑘𝑎𝐻−ℎ𝑦𝑑𝑟𝑎𝑡𝑒𝑑10 1 −
𝑄𝑎𝑚−𝑠𝑖𝑙𝑖𝑐𝑎
𝐾𝑎𝑚−𝑠𝑖𝑙𝑖𝑐𝑎
3
Corrosion rate law used in modeling
Front Position over Time Simulated Elemental Profiles
• Overall corrosion rate is controlled
by diffusion through pristine glass
• Relatively rapid glass corrosion
once glass is hydrated via diffusion-
cation exchange
• Nonlinear dependence on glass
hydration to capture front
separation
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Modeling Coupled Nucleation
and Growth
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Modeling classical and non-classical nucleation
and crystal growth/transformation
ACC ACC r
calcite ACC ACC calcite r
calcite calcite calcite r
R k G
R A k G
R A k G
Approach based on Crystal Size Distributions (Steefel & Van Cappellen, 1990)
Approach based on mineral “pools”, Li, Jun, & Steefel, in prep.
Nucleation of Amorphous Calcium
Carbonate (ACC) followed by
“aging” to more stable calcite
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Coupled Flow-Diffusion Experiments in
Micro-Capillary Tubes
Steefel & Yang, in prep.
Dif
fusi
on
-Con
troll
ed
Dirichlet
boundary condition No flux
boundary condition
Flow
Forsterite
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0.000 0.005 0.010 0.015 0.020 0.025 0.030
0.00E+000
2.00E-009
4.00E-009
6.00E-009
8.00E-009
1.00E-008
1.20E-008
1.40E-008
1.60E-008
1.80E-008
Mag
ne
site m
ass (
mo
le)
dist_x (m)
Mass of magnesite precipitation observed
Maximum amount of magnesite that could have formed from corresponding forsterite dissolution
Secondary Magnesite Precipitation vs
Primary Forsterite Dissolution
~ 56% all Mg2+ released via forsterite dissolution has been precipitated as magnesite
Magnesite mapped by
Raman spectroscopy
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Secondary Magnesite Precipitation
Rprecipitation is the overall precipitation;
Aforsterite, the surface area of forsterite for heterogeneous
nucleation of magnesite;
Amagnesite : surface area of neoformed magnesite
Nucleation Crystal Growth
3 2
0 23 3exp
3 lnprecipitation forsterite magnesite growth magnesite
B
R J A A k fk T
06/29/2016 Goldschmidt2016
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Conceptual Model for Formation of
Secondary Magnesite Pattern
NUCLEATION OF MAGNESITE: Where the pore fluids are supersaturated with respect to
magnesite as a result of forsterite dissolution, the exponential function of the heterogeneous
nucleation rates produces a peak-shaped distribution of initial magnesite nuclei
EPITAXIAL GROWTH OF MAGNESITE: These initial magnesite seeds quickly catalyze
growth of magnesite on magnesite and the peak grows
SUPPRESSION OF SUBSEQUENT NUCLEATION: The growth of the magnesite peaks
reduces supersaturation locally within some diffusion distance of the peak
time
Suppression of
nucleation Suppression of
nucleation
Transition to Crystal Growth Initial Nucleation Zone
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Modeling Coupled Nucleation and
Growth of Magnesite with CrunchTope
σ = 150 mJ/m2
• Forsterite rate constant:
10-9 mol/m2/s
• Magnesite rate constant:
10-8 mol/m2/s
• D = 10-9 m2/s
Modeling with CrunchTope:
Steefel et al, 2015, Reactive transport
codes for subsurface environmental
simulation, Computational Geosciences
19
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Effects of nucleation and
crystal growth on pore structure
Sc1 Sc2 Sc3 Sc4
Sc1 Sc2 Sc3 Sc4
Sc2 Sc3 Sc4
a)
b)
c)
Sc1
Solid 2
Solid 1
C. Noiriel et al, 2015
Flow velocity fields for
various crystal growth
scenarios
Scenarios for precipitation
in porous grain pack
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Modeling Isotopic Fractionation
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Calcite Precipitation with Kinetic Isotope
Fractionation
Solid Fluid
Rf = kf [Ca][CO3]
Rb = kb[CaCO3]
Gebrehiwet et al., 2012 20 mm
2 233( )net f b f f eq CaCO sCa CO
R R R k a a k K a
Based on Principle of Detailed Balancing
Lasaga, 1981; DePaolo, 2011
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Calcite Precipitation with Isotopic
Re-Equilibration
4444 3
44
3
[ ]
[ ]Ca
CaCOa X
CaCO
44RN =44kb
44 X[44Ca][CO3]
Ksp
44 X-1
æ
è ç ç
ö
ø ÷ ÷
40RN =40kb
40X[40Ca][CO3]
Ksp
40X-1
æ
è ç ç
ö
ø ÷ ÷
Druhan et al., 2013; Steefel et al. 2014
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δ44C
a (
‰)
fluid
bulk mineral
days
δ44C
a (
‰)
fluid
bulk mineral
days
δ44C
a (
‰)
fluid
bulk mineral
days
Druhan et al., 2013; Steefel et al. 2014
Isotopic Equilibration of Calcium in Calcite
Isotopically irreversible In equilibrium with bulk In equilibrium with surface
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Kinetic Fractionation as a Function of
Growth Rate
Isotopic ratio at boundary
DePaolo, 2011
Calcite Precipitation at
Low Damköhler Number
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Fractionation at Variable Damköhler Number
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 20 40 60 80 100
Log Q/Keq
Su
pers
atu
rati
on
(L
og
Q/K
eq
)
Distance (cm)
Approach to chemical
equilibrium, so
kinetic fractionation
is reduced
Rayleigh distillation produces is linear log
Concentration d44Ca space
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New Frontiers
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Watershed Concentration-Discharge Relations: Linear or Nonlinear?
Distribution of residence times
in a high elevation watershed,
Colorado (Engdahl and
Maxwell, 2015)
Hypothetical distribution of
residence time and reaction rates
(Damköhler number) in a
mountainous catchment
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• Fukushima Daiichi Nuclear Power
Plant accident occurred in March
2011, spreading airborne
contamination out to sea and to
northwest over a large tract of land
• Need to understand behavior of
individual “compartments” (farmland,
forest soils, water bodies, and
groundwater systems) and their
interactions.
• Predictive modeling based on high
resolution characterization is needed
to evaluate effectiveness of active
and passive remediation options.
Fukushima Nuclear Accident
35
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Exascale Computing Trajectory
Pore-scale soil processes (Molins et al, 2014)
Extreme resolution terrestrial modeling Nested hierarchical scale terrestrial modeling
Watershed-scale water and
geochemical cycling is a
problem that will require
Exascale Computation
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Summary Points
• Multi-scale nature of reactive transport in earth and
environmental systems remains a challenge
• Improved estimates of reactivity are possible when physical
and chemical heterogeneity are taken into account
• Mineral nucleation, mostly neglected in reactive transport
models, may have a dramatic effect on evolution of both
physical (permeability) and geochemical properties
• Rock or sediment texture still poorly captured in reactive
transport models (needs to be focus of next 10 years of
software development)
• Impermeable, clay-rich materials will require treatment of
electrostatic effects on transport and sorption
• Fully coupled corrosion models may provide insight into
waste form durability
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Reactivity in Subsurface
Formations
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Reactivity of Sediments, Nagaoka Japan
Haizume Formation Predominantly sandstone
Thin layers of shales
(siltstone to mudstone)
interbedded within
sandstone layers
Mineralogy (XRD)
Abundant quartz,
plagioclase, K-feldspar,
smectite and pyroxene
Injection depth = 1100
m
T = 48°C
P = 108 bars
40 t CO2/day, total of 10 kt CO2 stored
CO2 injection period: 7/2003 –1/2005
k = 6 mD
Thickness = 60 m
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Characterization Approach for Nagaoka Sediment
Beckingham et al, 2016, Geochimica
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2-D SEM-BSE & QEMSCAN of Nagaoka
Sediment
Beckingham et al, 2016
Sediment dominated by smectite, plagioclase, pyroxene +
volcanic glass
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Beckingham et al, 2016, Geochimica et Cosmochimica Acta
Surface Area Approximations
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1. Disaggregated sediment experiments in
well-stirred reactor
2. Compare with intact coreflood experiments
(pore structure intact)
Nagaoka Experimental Approach
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Cation leaching (Ca+Na+K >
SiO2) in glass phase over first 300
hours
Fit with mineral volume
percentages from QEMSCAM
Mapping—All grains accessible
Disaggregated Sediment Experiment
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With and without glass phase Grain Size Distribution
Including Grain Size Distribution and Glass
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Best Fit with Image Analysis Surface Area
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Simulation of Coreflood Experiment using
Disaggregated Sediment Experiment RSA
Overprediction: EPIC FAIL!
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10x to 20x lower SSA than Disaggregated Sediment experiment values
Second glass with cation leaching required to match results
Core Modeling with Pore-Accessible RSA
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Contaminant Migration
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Multi-Site Cation Exchange Models
• Multi-site formulation may
expand range of chemical
conditions over which
sorption can be described
• For example, the case of Cs+,
an important contaminant at
Hanford
Binary exchange
data from Zachara
et al. (2002)
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Retardation of Radionuclides
1
porosity
bulk density of soil or sediment
distribution coefficient (ml/g)
B d
f
B
d
KR
K
f
C v C
t R x
Advection Equation with Retardation
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Modeling of Cs breakthrough using
column experiment-derived parameters
Using column-derived data,
an improved parameterization is possible
(Steefel et al., 2003)
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Cesium Kd from Ion Exchange Model
Cesium Kd in Hanford
Sediments
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S-SX Tank Farm Leaks at Hanford,
Washington
Investigate 216,000 liter leak which occurred over
1 week in 1965 at the SX-115 tank
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Flow and Heat Transport Modeling of
SX-115 Leak
Steefel, 2004
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3D Reactive Transport Modeling of
SX-115 Leak
Steefel, 2004
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Match of Field Data with Column
Parameters
Steefel, 2004
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Cs Migration below Hanford SX-108 Tank
Steefel et al., 2005
Greatest mobility of 137Cs was below the
Hanford SX-108 tanks
Abject failure of Kd models spawned a major
Science and Technology Program at Hanford
funded by the U.S. Department of Energy