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Three-dimensional reactive transport simulation of the CCS demonstration project in Tomakomai, Hokkaido, Japan

Kohei Akaku1, Fumiaki Okumura1, Susumu Okubo1, Yusuke Wasaki1, Junji Yamamoto1, Hajime Yamamoto2, Yusuke Hiratsuka2, Takayasu Honda3 and Takahiro Nakajima4

1Japan Petroleum Exploration Co., Ltd. (JAPEX)

2Taisei Corporation 3Japan CCS Co., Ltd. (JCCS)

4Research Institute of Innovative Technology for the Earth (RITE)

INTRODUCTION

The Ministry of Economy, Trade and Industry of Japan has started a large-scale CCS

demonstration project in the Tomakomai area, Hokkaido. A geochemical reaction model was built

from the water analysis and mineralogical data gathered in the wells. The reaction model was

coupled with a field-scale reservoir model, and three-dimensional simulation studies were

conducted to predict the long-term behavior of CO2 including mineral trapping. We used

multiphase reactive geochemical transport code TOUGHREACT version 2.0 (Xu et al., 2011),

which was revised to enable parallel computing and consideration of hysteresis of relative

permeability for residual CO2 trapping. Thermoddem (http://thermoddem.brgm.fr), a

thermodynamic database which focuses on low temperature water/rock interaction including

zeolites and clay minerals was applied for the calculation.

GEOCHEMICAL MODEL

A target reservoir of the Tomakomai project is sandstone layers of the Moebetsu Formation at a

depth of approximately 1,100 m under the seabed. The sandstone contains quartz, plagioclase,

glauconite and biotite abundantly with K-feldspar, serpentinite, pyroxene and amphibole as primary

detrital minerals, whereas smectite (saponite), kaolinite, clinoptilolite, calcite and pyrite are

observed as diagenetic minerals. The formation water was sampled from the observation well OB-2

(Table 1). Based on the water analysis, we made a thermodynamic reconstruction of the water

composition by assuming equilibria with the diagenetic minerals, in addition to siderite, magnesite

and amorphous silica at formation temperature, 44°C, after the methods in Palandri and Reed

(2001). It was confirmed that the reconstructed formation water is markedly under-saturated with

respect to most of the detrital minerals and over-saturated with quartz, K-feldspar and chlorite to

some extent (Table 2).

The reactive surface areas of the minerals in the subsurface conditions are generally unknown.

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Furthermore, the batch reaction simulations between the reconstructed formation water and

sandstone without CO2 injection showed that the geometric-based reactive surface areas equivalent

to the grain size of sandstone (e.g. Xu et al., 2011) were unrealistic because the calculated water

composition was unstable with time. Therefore, we reduced the reactive surface areas for the

under-saturated detrital minerals by 3-5 orders of magnitude; in addition, the precipitation of the

over-saturated minerals was suppressed to obtain nearly stable water composition through 10,000

years (Table 2). The sensitivity of the reactive surface area of glauconite was separately tested in

the following reactive transport simulations with CO2 injection because its correction was rather

insensitive to the long-term stability of the water composition in the batch simulations. As the

model with these corrections matched the field observation of diagenesis, we believe this model is

appropriate for predicting the long-term behavior of CO2 in the Moebetsu Formation.

Table 1

Analysis of the water in the Moebetsu formation and its thermodynamic reconstruction

Analyzed composition of waterfrom Tomakomai well OB-2

sampled on 19 Feb. 2013

Thermodynamically reconstructedwater composition

Formation Temperature （°C） 44pH 8.34 7.11mg/kg

Cl- 1942 1907

SO42- 9.16 9.20

HCO3- 731 608

HS- not analyzed 0.000111SiO2(aq) 74.4 165

Al3+ not detected 0.0000401

Ca2+ 78.5 39.1

Mg2+ 13.7 6.43

Fe2+ 0.30 0.85

K+ 26.6 26.7

Na+ 1365 1371

NH4+ 2.7 2.71

RemarksThe pH measured atatmospheric pressure and roomtemperature.

Equilibrium with pyrite, amorphoussilica, Na-clinoptilorite, kaolinite,siderite, magnesite, calcite, Fe-Na-saponite.

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Table 2

Mineral saturation indices (log Q/K) of the reconstructed Moebetsu formation water and kinetic parameters used in the model inj-MN1.

# From Palandri and Kharaka (2004), except for pyrite, clinoptilolite and siderite. & Geometric-based reactive surface areas for sandstone grain are from Xu (2011) and those for

plagioclase, serpentinite, biotite, pyroxene and amphibole reduced by 3-5 orders of magnitude. * Minerals set to dissolution only due to slow precipitation at the formation

temperature.

Minerals Compositions Mineralcomposition

Saturationindex in water

Kinetic rateconstants#

ActivationEnergy#

Reactivesurface area&

vol% logQ/Klog(k) 25°C(mol/m2/s)

Ea(kJ/mol) cm2/g

Rock forming mineralsquartz* SiO2 36.11 0.96 -13.40 90.9 9.1plagioclase (albite/anorthite) Na0.5Ca0.5Al1.5Si2.5O8 25.84 -2.37 -10.91 45.2 9.1.E-04K-feldspar* KAlSi3O8 2.36 1.62 -12.41 38.0 9.1calcite CaCO3 0.10 eq. -5.81 23.5 9.1saponite(FeNa) Na0.34Mg2FeAl0.34Si3.66O10(OH)2 0.09 eq. -14.41 48.0 108.7kaolinite Al2(Si2O5)(OH)4 6.34 eq. -13.18 22.2 108.7chlorite (clinochlore/daphnite)* Mg2.5Fe2.5Al2Si3O10(OH)8 0.95 2.15 -12.52 88.0 9.1glauconite (K0.75Mg0.25Fe1.5Al0.25)(Al0.25Si3.75)O10(OH)2 12.42 -1.44 -9.10 85.0 9.1serpentinite Mg3Si2O5(OH)4 2.24 -5.17 -12.00 73.5 108.7E-3biotite (siderophyllite/eastonite) KFeMgAl3Si2O10(OH)2 9.51 -5.18 -12.55 22.0 108.7E-3clinoptilolite(Na) Na1.1(Si4.9Al1.1)O12:3.5H2O 2.74 eq. -12.63 58.0 9.1pyrite FeS2 0.27 eq. -10.40 62.7 12.9pyroxene (diopside/hedenbergite) CaMg0.8Fe0.2Si2O6 0.33 -3.87 -11.11 40.6 9.1.E-04amphibole (tremolite/actinolite) Ca2(Mg3Fe2)Si8O22(OH)2 0.69 -5.93 -10.60 94.4 9.1.E-05Secondary mineralsamorphous silica SiO2 0.00 -9.42 49.8 9.1siderite FeCO3 0.00 -8.90 62.8 9.1magnesite MgCO3 0.00 -9.34 23.5 9.1dawsonite NaAlCO3(OH)2 -2.08 -7.00 62.8 9.1dolomite (ordered) CaMg(CO3)2 -0.26 -8.60 95.3 9.1

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ONE-DIMENSIONAL REACTIVE TRANSPORT SIMULATIONS

One-dimensional simulations of CO2 injection at a rate of 200,000 tons/year for 3 years coupled

with the geochemical models confirmed the dissolution of glauconite and precipitation of siderite

and magnesite, as prominent mineral leaching and trapping mechanisms of CO2. In the case where

the reactive surface area of glauconite was set to the geometric-based value, mineral trapping starts

in 10 years and reaches 85% of the injected CO2 at 1,000 years from start of CO2 injection

(inj-MN1 in Fig. 1). In contrast, the simulation where the reactive surface area was reduced by 4

orders of magnitude shows only 20% mineral trapping of the injected CO2 at 10,000 years

(inj-MN3 in Fig. 1).

Fig. 1. Results of one-dimensional simulations of CO2 injection for the Moebetsu formation. Figures

on the left hand side show the results of the model inj-MN1, whereas those on the right hand side are

the results of the model inj-MN3 where the reactive surface area of glauconite was reduced by 4

orders of magnitude. The upper figures show changes of CO2 distribution between phases

(“super-critical state”, so-called gas, “aqueous”, solubility trapped in water and “mineral”, trapped as

carbonate minerals) with time. The lower figures show changes in mineral abundance with time.

THREE-DIMENSIONAL SIMULATIONS

The geochemical models were coupled with a three-dimensional field-scale reservoir model and

simulation studies were conducted. The upward movement of CO2 driven by buoyancy forces is

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 10 100 1000 10000

CO

2tra

pped

(%)

-2.0E+9

-1.5E+9

-1.0E+9

-5.0E+8

0.0E+0

5.0E+8

1.0E+9

1.5E+9

2.0E+9

1 10 100 1000 10000

Cha

nges

in m

iner

al a

bund

ance

(mol

)

Time since injection starts (years)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 10 100 1000 10000

CO

2tra

pped

(%)

-2.0E+9

-1.5E+9

-1.0E+9

-5.0E+8

0.0E+0

5.0E+8

1.0E+9

1.5E+9

2.0E+9

1 10 100 1000 10000

Cha

nges

in m

iner

al a

bund

ance

(mol

)

Time since injection starts (years)

glauconite

amorph silicasiderite

calcite

kaolinite

magnesite

Moebetsu, inj-MN1(1D)

pyrite

aqueous

super-critical mineral

aqueous

super-critical

mineral

glauconite

amorph silica

siderite

calcitekaolinitemagnesite

precipitation

dissolution

precipitation

dissolution

chloritechlorite

Moebetsu, inj-MN3(1D)

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limited because much is trapped as residual CO2 in the model. The 3D simulation using the

inj-MN1 model gives results similar to the 1D simulation. However, the 3D simulation using the

model where the reactive surface area of glauconite was reduced by 4 orders of magnitude shows a

significant difference from the 1D result over 1,000 years, and the mineral trapping reaches 60 %

of the injected CO2 at 10,000 years (Fig. 2). We believe this is caused by the downward movement

of water saturated with CO2, which is slightly denser than the original formation water, and that the

gravity flow of the CO2 saturated water promotes mineral leaching and trapping (Fig. 3 and 4). The

mineralogical study showed that glauconite is abundant in the matrix of the sandstone, and

suggests that the latter case (inj-MN3-3D) with slow glauconite dissolution is the most reasonable

prediction.

Fig. 2. Results of three-dimensional simulations of CO2 injection for the model inj-MN1 and

inj-MN3 where the reactive surface area of glauconite was reduced by 4 orders of magnitude. The

super-critical CO2 includes residual trapped due to hysteresis of relative permeability. The others are

the same as the caption in Fig. 1.

CONCLUSIONS

We developed a geochemical model that successfully explains observed diagenesis of the

formation rocks as well as water analysis data by employing an appropriate thermodynamic

database. The reactive surface areas of minerals, generally unknown in the subsurface, were

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 10 100 1000 10000

CO

2tra

pped

(%)

-1.0E+10

-5.0E+9

0.0E+0

5.0E+9

1.0E+10

1.5E+10

2.0E+10

1 10 100 1000 10000

Cha

nges

in m

iner

al a

bund

ance

(mol

)

Time since injection starts (years)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 10 100 1000 10000

CO

2tra

pped

(%)

-1.0E+10

-5.0E+9

0.0E+0

5.0E+9

1.0E+10

1.5E+10

2.0E+10

1 10 100 1000 10000

Cha

nges

in m

iner

al a

bund

ance

(mol

)

Time since injection starts (years)

glauconite

amorph silica

siderite

calcite

kaolinitemagnesite

Moebetsu, inj-MN1(3D)

pyrite

aqueous

super-critical mineral

Moebetsu, inj-MN3(3D)

aqueous

super-critical

mineral

glauconite

amorph silica siderite

calcitekaolinite

magnesite

precipitation

dissolution

precipitation

dissolution

residual trapped

chlorite

residual trapped

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estimated based on the long-term stability of water composition. However, large uncertainties, in

the orders of magnitude, still remain in the long-term prediction of the mineral trapping associated

with the CO2 injection. More information on reactive surface areas at in situ reservoir conditions is

needed. We also recognized that the reactive transport simulation fully coupled with a

three-dimensional hydrodynamic model including residual trapping is important for the long-term

assessment of the CO2 behavior.

ACKOWLEDGEMENTS

This study was supported by the Ministry of Economy, Trade and Industry of Japan (METI),

Japan CCS Co., Ltd. (JCCS) and Research Institute of Innovative Technology for the Earth (RITE).

The authors would like to thank to all staff involved in the project.

REFERENCES

Palandri J. L. and Reed M. H. (2001) Reconstruction of in situ composition of sedimentary

formation waters. Geochim. Cosmochim. Acta 65, 1741–1767.

Palandri, J. and Kharaka, Y. (2004) A Compilation of Rate Parameters of Water–Mineral

Interaction Kinetics for Application to Geochemical Modeling. Report 2004-1068.

Xu, T., Spycher, N., Sonnenthal, E., Zhang, G., Zheng, L. and Pruess, K. (2011) TOUGHREACT

Version 2.0: A simulator for subsurface reactive transport under non-isothermal multiphase

flow conditions. Computers & Geosciences 37, 763-774.

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Fig. 3. Results of three-dimensional simulations of CO2 injection for the Moebetsu formation (inj MN3 model). Molality of CO2 in aqueous phase

(mol/kg.H2O) on the plan view of layer K=41, around the bottom of the model (a) and the cross section of layer I=10 (b). Aqueous pH on the plan view of

layer K=41 (c) and the cross section of layer I=10 (d). The distributions in 3, 13, 103, 1,000, 5,000 and 10,000 years after CO2 injection starts respectively.

K=41

I=10

K=41

I=10

(a)

(b)

(c)

(d)

North North

North North

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Fig. 4. Results of three-dimensional simulations of CO2 injection for the Moebetsu formation (inj MN3). Changes in abundance of glauconite (mol

m3.medium) on the plan view of layer K=41 (e) and the cross section of layer I=10 (f). Those for siderite on (g) and (h). The others are the same as the

caption in Fig. 3.

K=41

I=10

K=41

I=10

(e)

(f)

(g)

(h)

North North

North North