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Three-dimensional reactive transport simulation of the CCS demonstration project

in Tomakomai, Hokkaido, Japan

GastechMakuhari, Chiba

4 April 2017

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 Corporation3Japan CCS Co., Ltd. (JCCS)4Research Institute of Innovative Technology for the Earth (RITE)

2

• CO2 trapping mechanism• Geochemical reaction model for Tomakomai project• One-dimensional reactive transport simulation• Three-dimentional reactive transport simulation• Conclusions

TOUGHREACT version 2.0 (LBNL) revised in RITEThermoddem database (BRGM)

3

Outline

Reservoirs and cap rocks of the Tomakomai CCS demonstration Project 4

Reservoir

Cap rock

※Aspect Ratio=1:1

Injection Well for

Moebetsu Fm.

Injection Well for

Takinoue Fm.

(projected)

Cap rock

Reservoir

Landward(North) Seaward(South)

T1 Member of Takinoue Fm. (Volcanic Rocks)

Fureoi Fm. (Mudstone）

Quaternary sediments

Moebetsu Fm. (Mudstone)

Takinoue Fm. (Mudstone)

Nina Fm. (Mudstone)

Moebetsu Fm. (Sandstone)

Mukawa Fm. (Sandstone, Mudstone, etc.)

Biratori-Karumai Fm. (Mudstone)

Depth

in

mete

rs (

bM

SL)

(TD 5,800m)

(TD 3,650m)

Observation Well

for Moebetsu Fm.

Copyright 2017 Japan CCS Co., Ltd.

CO2 storage mechanisms in geological formations

http://www.co2captureproject.org/co2_trapping.html

IPCC (2005)

• The effectiveness of geological storage depends on a combination of physical and geochemical trapping mechanisms.

Structural and stratigraphic trapping is primarily important.

Residual trapping due to capillary forces and solubility trapping in water are highly important, too.

The forth mechanism, mineral trapping, is believed to be slow, potentially taking a thousand years or longer.

• What is going on in the Moebetsu Formation?

5

Analysis of water and its thermodynamic reconstruction

• Why do we need thermodynamic reconstruction? Ideally, formation water should be in

equilibrium with diagenetic minerals. But… Concentrations of minor components (Al3+,

HS-) are not usually obtained through the water analysis.

Degassing and mineral precipitation before water sampling.

• On the other hand… Thermodynamic database for solubility of

minerals and aqueous ion properties is not always perfect.

Native minerals are too complex structures and compositions.

The reconstruction is a validation step of the following reactive transport simulation.

• A good result with Thermoddem (BRGM, 2014).

6

Analyzed composition

Tomakomai well OB-2

Thermodynamically

reconstructed water

Temperature （°C） 44

pH 8.34 7.11

mg/kg

Cl- 1942 1907

SO42- 9.16 9.20

HCO3- 731 608

HS- not analyzed 0.000111

SiO2(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

Remarks

The pH measured at

atmospheric pressure

and room temperature.

Equilibrium with pyrite,

amorphous silica, Na-

clinoptilorite, kaolinite,

siderite, magnesite, calcite,

Fe-Na-saponite.

Mineral saturation indices (log Q/K) of the reconstructed water

• Reconstructed water is under-saturated with the detrital minerals (plagioclase, glauconite, biotite, serpentinite, pyroxene and amphibole).

• The formation water does not possibly react well with these minerals.

• Over-saturated with quartz, K-feldspar and chlorite is probably due to kinetic barrier at low temperature.

7

Minerals Compositions

Saturation

index

in water

logQ/K

Rock forming minerals

quartz SiO2 0.96

plagioclase (albite/anorthite) Na0.5Ca0.5Al1.5Si2.5O8 -2.37

K-feldspar KAlSi3O8 1.62

calcite CaCO3 0.00

saponite(FeNa) Na0.34Mg2FeAl0.34Si3.66O10(OH)2 0.00

kaolinite Al2(Si2O5)(OH)4 0.00

chlorite (clinochlore/daphnite) Mg2.5Fe2.5Al2Si3O10(OH)8 2.15

glauconite (K0.75Mg0.25Fe1.5Al0.25)(Al0.25Si3.75)O10(OH)2 -1.44

serpentinite Mg3Si2O5(OH)4 -5.17

biotite (siderophyllite/eastonite) KFeMgAl3Si2O10(OH)2 -5.18

clinoptilolite(Na) Na1.1(Si4.9Al1.1)O12:3.5H2O 0.00

pyrite FeS2 0.00

pyroxene (diopside/hedenbergite) CaMg0.8Fe0.2Si2O6 -3.87

amphibole (tremolite/actinolite) Ca2(Mg3Fe2)Si8O22(OH)2 -5.93

Secondary minerals

amorphous silica SiO2 0.00

siderite FeCO3 0.00

magnesite MgCO3 0.00

dawsonite NaAlCO3(OH)2 -2.08

dolomite (ordered) CaMg(CO3)2 -0.26

Kinetic parameters

• Kinetic rate constants and activation energies for dissolution of minerals are from literature (e.g. Palandri and Kharaka, 2004).

• Reactive surface area of minerals is the most uncertain parameter. The standard values for sandstone grain size are quoted from Xu et al. (2011).

• Based on the batch reaction simulation without CO2 injection, we decided…

Reduce the reactive surface areas for the under-saturated detrital minerals by 3-5 orders of magnitude, except for glauconite

Precipitation of the over-saturated minerals was suppressed

• Nearly stable water composition through 10,000 years. Reasonable model!

K

QkAr

m

mmmm 1

15.29811

exp25

TRE

kka

m

8

MineralsMineral

composition

Kinetic rate

constants

Activation

Energy

Reactive

surface area

vol%log(k) 25°C

(mol/m2/s)

Ea

(kJ/mol)

A

(cm2/g)

Rock forming minerals

quartz 36.11 -13.40 90.9 9.1

plagioclase (albite/anorthite) 25.84 -10.91 45.2 9.1.E-04

K-feldspar 2.36 -12.41 38.0 9.1

calcite 0.10 -5.81 23.5 9.1

saponite(FeNa) 0.09 -14.41 48.0 108.7

kaolinite 6.34 -13.18 22.2 108.7

chlorite (clinochlore/daphnite) 0.95 -12.52 88.0 9.1

glauconite 12.42 -9.10 85.0 9.1

serpentinite 2.24 -12.00 73.5 108.7E-3

biotite (siderophyllite/eastonite) 9.51 -12.55 22.0 108.7E-3

clinoptilolite(Na) 2.74 -12.63 58.0 9.1

pyrite 0.27 -10.40 62.7 12.9

pyroxene (diopside/hedenbergite) 0.33 -11.11 40.6 9.1.E-04

amphibole (tremolite/actinolite) 0.69 -10.60 94.4 9.1.E-05

Secondary minerals

amorphous silica -9.42 49.8 9.1

siderite -8.90 62.8 9.1

magnesite -9.34 23.5 9.1

dawsonite -7.00 62.8 9.1

dolomite (ordered) -8.60 95.3 9.1

Results of one-dimensional (1D) simulations

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 10 100 1000 10000

CO

2tr

app

ed

(%)

Time since injection starts (years)

溶存CO2

鉱物CO2

超臨界CO2

-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

Changes in m

inera

l abundance

(mo

l)


石英

非晶質シリカ

斜長石

カリ長石

方解石

シデライト

マグネサイト

ドーソナイト

ドロマイト

ＦｅＣａ－サポ

ナイトカオリナイト

緑泥石

海緑石

蛇紋石

黒雲母

黄鉄鉱

Ｎａ－斜プチロ

ル沸石

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 10 100 1000 10000

CO

2tr

app

ed

(%)


溶存CO2

鉱物CO2

超臨界CO2

-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

Changes in m

inera

l abundance

(mol)


石英

非晶質シリカ

斜長石

カリ長石

方解石

シデライト

マグネサイト

ドーソナイト

ドロマイト

ＦｅＣａ－サ

ポナイトカオリナイト

緑泥石

海緑石

蛇紋石

黒雲母

黄鉄鉱

Ｎａ－斜プチ

ロル沸石

glauconite

amorph silicasiderite

calcite

kaolinite

magnesite

Moebetsu, inj-MN1(1D)

pyrite

aqueous

super-critical mineral

aqueous

super-critical

mineral

glauconite

amorph silica

siderite

calcite

kaolinite

magnesite

precipitation

dissolution

precipitation

dissolution

chloritechlorite


Reactive surface area of glauconite was reduced by 4 orders of magnitude for “inj-MN3”.

• 45 m thickness• 44°C• Φ=28.1%• k=233 mD• 50,000 tons/year for 3 years• TOUGHREACT

• Prominent reactions Dissolution of glauconite Precipitation of amorphous

silica and kaolinite CO2 trapped by precipitation

of siderite and magnesite

• Mineral trapping of CO2 depends on the reactive surface area of glauconite. 85% mineral trapped in “inj-

MN1” model at 1,000 years 20% in “inj-MN3” model at

10,000 years

9

Results of three-dimensional (3D) simulations

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 10 100 1000 10000

CO

2tr

app

ed

(%)


超臨界ＣＯ２

残留ＣＯ２

溶存ＣＯ２

鉱物ＣＯ２

-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

ng

es in m

ine

ral a

bu

nd

an

ce

(mo

l)


石英

非晶質シリカ

斜長石

カリ長石

方解石

シデライト

マグネサイト

ドーソナイト

ドロマイト

ＦｅＮａ－サポナ

イトカオリナイト

緑泥石

海緑石

蛇紋石

黒雲母

黄鉄鉱

Ｎａ－斜プチロル

沸石

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 10 100 1000 10000

CO

2tr

app

ed

(%)


超臨界ＣＯ

２残留ＣＯ２

溶存ＣＯ２

鉱物ＣＯ２

-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

ng

es in m

inera

l a

bu

nd

an

ce

(mo

l)


石英

非晶質シリカ

斜長石

カリ長石

方解石

シデライト

マグネサイト

ドーソナイト

ドロマイト

ＦｅＮａ－サポナ

イトカオリナイト

緑泥石

海緑石

蛇紋石

黒雲母

黄鉄鉱

Ｎａ－斜プチロル

沸石

glauconite

amorph silica

siderite

calcite

kaolinite

magnesite


pyrite

aqueous

super-critical mineral


aqueous

super-critical

mineral

glauconite

amorph silica siderite

calcite

kaolinite

magnesite

precipitation

dissolution

precipitation

dissolution

residual trapped

chlorite

residual trapped

Reactive surface area of glauconite was reduced by 4 orders of magnitude for “inj-MN3”.

• Prominent reactions are same as 1D.• Mineral trapping of CO2 is similar

to 1D if dissolution of glauconite is fast.

• However, “inj-MN3” model with slow dissolution of glauconite is different from 1D over 1,000 years.

60% mineral trapped in “inj-MN3” model at 10,000 years

• Geochemical models were coupled with 3D field-scale reservoir model

• 3.6km×4km×800m• 43,119 active grids• 200,000 tons/year for 3 years• TOUGHREACT

10

3D field-scale simulations (molality & pH of inj-MN3 model)

K=41

I=10

K=41

I=10

(a)

(b)

(c)

(d)

North North

North North

Dissolved CO2 in water (molality) water pH

• Upward movement of CO2 driven by buoyancy forces is limited because much is trapped as residual CO2 .• Over 1,000 years, downward movement of water saturated with CO2, which is slightly denser than the original formation water, is predicted.

11

K=41

I=10

K=41

I=10

(e)

(f)

(g)

(h)

North North

North North

3D field-scale simulations (glauconite & siderite of inj-MN3 model)

Changes of glauconite (mol/m3) Changes of siderite (mol/m3)

• Gravity flow of the CO2 saturated water promotes mineral leaching and trapping over 1,000 years.

12

Conclusions

• We developed a geochemical model that successfully explains observed diagenesis and water composition.

• The reactive surface areas of minerals, generally unknown in the subsurface, were estimated based on the long-term stability of water composition.

• However, large uncertainties, in the orders of magnitude, still remain. We believe slow glauconite dissolution case is the most reasonable prediction as glauconite is abundant in the matrix of the sandstone.

• More information on reactive surface areas at in situ reservoir conditions is needed. • We also recognized that the geochemical simulation fully coupled with a three-

dimensional hydrodynamic model including residual trapping is important for the long-term assessment of the CO2 behavior.

13

Acknowledgements

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.

14

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Japan Petroleum Exploration Co., Ltd.

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