MODELING OF THE LABORATORY TESTS OF INTERACTION OF THE NaNO3-NaOH FLUIDS WITH SANDSTONE ROCKS FROM DEEP RADIONUCLIDE REPOSITORY SITE, USING TOUGHREACT

1
MODELING OF THE LABORATORY TESTS OF INTERACTION
OF THE NaNO3-NaOH FLUIDS WITH SANDSTONE ROCKS
FROM DEEP RADIONUCLIDE REPOSITORY SITE, USING
TOUGHREACT A.V. Kiryukhin 1, E.P. Kaymin2, E.V.
Zakharova2, ?.?. Zubkov3 1Institute of
Volcanology and Seismology FEB RAS, Piip-9,
Petropavlovsk-Kamchatsky, Russia, 683006 2-
Institute of Physical Chemistry and
Electrochemistry RAS, Leninsky-31, Moscow,
Russia, 119991 3- Siberia Chemical Plant,
Kurchatova-1, Seversk, Russia
ABSTRACT
MODEL CALIBRATION
Chemical Input Data Initial mineral fractions are
shown in Table 1, parameters of kinetic
water-rock chemical interaction assigned the same
as in (Kiryukhin et al, 2004) paper (Ea- energy
of activation, kJ/kmole), while other parameters
were corrected during model calibration (Table
2). Chemical compositions of the initial solution
(natural pore fluids) and injected fluid are
shown in Tables 3 and 4, correspondingly.
TOUGHREACT modeling was used to reproduce
laboratory tests with sandstone samples collected
from deep radionuclide repository site in Siberia
Chemical Plant. Laboratory test includes
injection of alkaline fluids into sandstone
samples at 70??. Modeling results were compared
with observed test data (mineral phase change,
transient concentration data at the outlet of
sample column). Some minerals were restrain in
the model to precipitate or dissolve according to
laboratory test results. Model and test
convergence in mineral phases (Na-smectite and
kaolinite precipitation in the model, quartz,
microcline, chlorite and biotite dissolution in
the model) were obtained. Nevertheless it was not
found possible to generate sodium carbonates in
the model (while sodium clearly observed in the
test). Transient chemical concentration data at
the outlet of sample column match Na only. Its
concluded that the model should be improved in
the future work to better match observed data.
Calibration Data Two tests with duration of 79
days and 42 days correspondingly were performed
with injection mass flux at average level 2.50
10-5 kg/s m2. During test (at times 9, 16, 23,
30, 32, 58, 79 days) sampling of fluid took
place at column outlet for chemical analysis (Na,
Al, Si, Ca, Mg, K, Sr). Microprobe analysis of
mineral composition of samples after testing was
done. Microprobe analysis performed based on Link
INCA ENERGY200 to electronic scan facility
CamScan MV-2300. A.A. Grafchikov (Institute of
Experimental Mineralogy RAS) took participation
in this analysis.
c
d
a
Figure above Modeling results of mineral
fraction change along injection steamline in the
sandstone column. Figure left Modeling (lines)
and laboratory test (solid circles) match
(transient chemical concentrations of fluids).
INTRODUCTION
CONCLUSIONS
b
(1) TOUGHREACT modeling was used to reproduce
laboratory tests with sandstones samples
collected from deep radionuclide repository site
in Siberia Chemical Plant. Laboratory test
include injection of alkaline fluids into
sandstones samples at 70??. (2) Model and test
convergence in mineral phases (Na-smectite and
kaolinite precipitation in the model, quartz,
microcline, chlorite and biotite dissolution in
the model) were obtained due to restrain for some
minerals to precipitate /dissolve. Nevertheless
it was not found possible to generate sodium
carbonate in the model (while sodium clearly
observed in the test). Transient chemical
concentrations data at the outlet of sample
column match Na only. pH match show the same
trend of model and experiment, while absolute
modeling values 2.6 units greater. Ca and Mg
match model and experiment show the same trend,
while absolute values in the model 2-3 orders
less than experiment. (3) The main reason
model and laboratory test mis-match seems to be
TOUGHREACT not taking into account
mineral/mineral chemical reactions. In laboratory
test was found K release to solutions, and Al
consumed by secondary minerals due to biotite,
K-feldspars, muscovite replacing by clay
minerals, ?????????? ??????????. If such
reactions will be implemented in TOUGHREACT, then
convergence of modeling and laboratory test data
may improve. ACKNOWLEDGEMENTS We express our
gratitude to T. Xu, N.Spycher (Lawrence Berkeley
National Laboratory) for valuable comments and
suggestions, B.N. Ryzhenko and ?.?. Limantseva
(GeoChi RAS), I.B. Slovtsov (IVS FEB RAS) for
additional thermodynamic calculations. This work
was supported by Siberia Chemical Plant, FEB RAS
project 06-I-???-109 and RFBR project
06-05-64688-?.
e
TOUGHREACT is a computer code capable to simulate
thermal-hydrodynamic-chemical (THC) processes
including multiphase nonisothermal transport and
kinetics of the rock - fluid chemical
interaction. The THC processes and secondary
minerals associations observed in some drilled
geothermal fields of the recent volcanic activity
areas have been successfully reproduced by
TOUGHREACT simulations (Xu, T. and Pruess, K.,
2001, A.V. Kiryukhin et al, 2004). Similar
processes took place during waste radionuclide
fluids injection in sandstones aquifers. When
liquid radionuclide waste injected in layer type
reservoirs (Siberia Chemical Plant (SCP),
(Seversk), Mining-Chemical Plant (MCP)
(Zheleznogorsk) chemical interaction with
natural pore fluids and clay minerals of the deep
repository site took place. New secondary
minerals created, while primary minerals
dissolve, temperature increase due to radiogenic
heat release (A.I. Rybalchenko et al, 1994).
Monitoring of the hydrogeological parameters in
the wells, as well as laboratory experiments at
P-T conditions corresponding to physical and
chemical processes in repository sites conducted
to get reliable information on processes there
(?.?. Zubkov et al, 2002, E.P. Kaymin et al,
2004). Reliable numerical model needed to
forecast process of migration of radionuclides
and to guaranty safety condition in repository
sites too. In this study, TOUGHREACT was used to
reproduce laboratory experiment of the process of
technogenic alteration observed in sandstones
(obtained from deep repository site) as a result
of chemical interaction during NaNO3-NaOH fluid
injection in rock samples at temperature 70??.
Modeling results calibrated against observed
secondary minerals, generated during laboratory
experiment and identified based on microprobe
analysis, and against transient chemistry data of
fluids, discharged from the core outlet during
laboratory experiment.
f
g
h
Scan electron images of samples (E.P. Kaymin
data) a- Chlorite (Chl) replacement by
montmoril- lonite (Mont), b- Muscovite (Ms)
replacement by kaolinite (Kaol), c- Biotite (Bt)
replacement by montmorillonite (Mont), d-
K-feldspar (Kfs) replacement by montmorillonite
(Mont) , e- grains of magnetite hosted in clay
minerals,f- magnetite (white) inside of
montmorillonite (grey) replaced biotite grain,
g- sodium or trona (Na) release in form of crust
and regions in montmorillonite (Mont),h- sodium
or trona (Na) release in form of regions in
montmorillonite (Mont). Note black space is
polymeric matrix.
Modeling Results TOUGHREACT modeling of the
laboratory test (run 7) yield the following
results (1) Mineral phase fractions change. By
the end of 79 day alkaline solution injection
quartz - dissolve (from 9.2 10-5 to 9.8 10-5),
microcline dissolve (from 3.1 10-6 to 3.2 10-6),
albite-low - dissolve (to 1.4 10-6), Na-smectite
(montmorillonite) precipitate in the middle and
outlet part of column (up to 1.8 10-3), kaolinite
precipitate in the middle and outlet part of
column (up to 1.1 10-5), chlorite dissolve (3.0
10-9), muscovite dissolve everywhere (from 6.3
10-5 to 7.3 10-5). Secondary mineral phases
(Na-smectite and kaolinite) were formed during
first 9 days only. No sodium carbonate
precipitations was obtained in the model (while
abundant sodium carbonates observed during
laboratory test). (2) Match of observed and
modeling transient chemical concentrations of
fluid sampled from sandstone column outlet (run
7)shows the following. pH match show the same
trend of model and experiment, while absolute
modeling values 2.6 units greater. Na
concentrations from model match those from the
experiment. ? match show model 3 times less
values than experiment. Ca match model and
experiment show the same trend, while absolute
values in the model 2-3 orders less than
experiment. Mg match show the same trend in
model and experiment, while, model absolute
values are 1-2 orders less. Al match show model
yield 4 order greater compare experiment. Si
match show convergence in the first times, while
later model concentrations 3 times greater
experiment. It was also found that change of
rate constants of mineral precipitations (kS) for
Na-smectite and kaolinite (Table 3) has no effect
on ?? and outlet discharge transient chemical
concentrations.

Flow and Solution Input Data According to the
Laboratory test data 700? isothermal conditions
with mass flux 2.50 10-5 kg/s m2 and pressure
3.0MPa were assigned in the model. Sample
porosity assigned 0.2. The length of the model
correspond to the length of test sample 15 cm.
1-D numerical grid generated includes 32
elements B 1 source of injected fluid (element
volume 5.00E20 m3, R 1- R 30 elements represents
sandstone column of 15 cm length, each element
with width of 0.005 m, and D 1 inactive element
with specified pressure 3.0 MPa, which correspond
to discharge from the column outlet.
MODEL SETUP
REFERENCES
A.V. Kiryukhin, ?.Y. Puzankov, I.B. Slovtsov et
al, Thermal-Hydrodynamic-Chemical modeling
processes of secondary mineral precipitation in
production zones of geothermal fields (in print
Vulcanologia and Seismologia, 32 p.).
Rybalchenko A.I., Pimenov M.K., Kostin P.P. et
al. Deep injection of liquid radionuclide waste.
?oscow, IzdAT publ., 1994, 256 p. (in Russian).
Xu, T. and Pruess, K., 2001a, On Fluid Flow and
Mineral Alteration in Fractured Caprock of
Magmatic Hydrothermal Systems, Journal of
Geophysical Research, 106 (B2), 2121-2138.
?.?. Zubkov, ?.V. Makarova, V.V. Danilov, ?.V.
Zakharova, ?.P. Kaymin, ?.?. Menyailo, ?.I.
Rybalchenko, Technogenic geochemical processes
during injection of the liquid radionuclide waste
into sandstones layer type reservoirs,
Geoecology, Engineering Geology, Hydrogeology,
Geocriology, 2002, ?2, p.133-144. ?.P. Kaymin,
?.V. Zakharova, L.I. Konstantinova, ?.?.
Graphchikov, L.Y. ?ranovich, V.?. Shmonov, Study
of the interaction of alkaline radionuclide waste
with sanstone rocks, Geoecology, Engineering
Geology, Hydrogeology, Geocriology, 2004, ?5,
p.427-432. A.V. Kiryukhin, T. Xu, K. Pruess, J.
Apps, I. Slovtsov, Thermal-Hydrodynamic-Chemical
(THC) Modeling Based on Geothermal Field Data,
Geothermics, v.33, No.3, 2004, p. 349-381.
In this study, TOUGHREACT was used to reproduce
laboratory experiment of the process of
technogenic alteration observed in sandstones. In
the model , adjective and diffusive transport of
aqueous chemical species is considered. Mineral
dissolution/precipitation can proceed at
equilibrium and /or under kinetic conditions,
according to the following rate law r kS
(1-Q/K) exp(Ea/(R298.15)-Ea/(RT)), where k
kinetic constant of the chemical
dissolution/precipitation at 250C, mole/sm2 S
specific reactive surface area, m2/m3 Q is
activity product K is equilibrium constant for
mineral-water interaction Ea is the activation
energy, kJ/kmole R is the gas constant,
kJ/kmole K, and T is temperature, K.
Temperature effects are also considered for
geochemical reaction calculations in which
equilibrium and kinetic data are functions of
temperature.