Imperial College London

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Transcript Imperial College London

Impact of capillary trapping on geological CO

2

storage

Martin Blunt, Branko Bijeljic, Tara C LaForce, Stefan Iglauer, Ran Qi, Saleh Al Mansoori, Chris Pentland and Erica Thompson

Outline

Field scale: Streamline Simulation Core scale: Column Experiment Pore scale: CT scan

Background

Long term fate, how can you be sure that the CO 2 stays underground?

Field scale - The streamline method

Permeability field Pressure solve Saturation along SL Initial saturation SL tracing Saturation for the next time step

Streamline method for CO

2

transport

Phases (3) Hydrocarbon Aqueous Solid CO 2

+ + +

Components (4) Oil

+ + +

Water

+

Salt

+ +

Hydrocarbon phase Todd&Longstaff Fingering model for CO 2 in oil Aqueous phase

Streamline method for CO

2

transport

Trapping model

Pore-scale model matches experimental data.

• Kr is from Berea sandstone, which matches Oak (1990)’s experiments.

• CO 2 /water system is weakly water-wet (Chiquet

et al.

, 2007) contact angle ( θ) = 65º.

New trapping model (Juanes

et al.

, 2006)

S gt

 

S

max

g

 

S

max

g

2

S gf

 1 2        1  (  4 

S

  1 )

g

2  

S gt

  (

S g

S gt

)(

S g

S

max

g

)     

Design of carbon dioxide storage

10 Mobility ratio between carbon dioxide/brine mixture and formation brine 1 Mobility ratio = 1.0

0.1

Mobility ratio between chase brine and carbon dioxide/brine mixture during chase brine injection 0.01

0 0.1

0.2

0.3

0.4

0.5

f f gi ci

0.6

0.7

0.8

0.9

1

The ratio of the mobility of injected brine and CO 2 to the formation brine as a function of the injected CO 2 -phase volume fraction,

f gi

.

Design of carbon dioxide storage

1D analysis: Numerical simulation vs. analytical solution

0.2

0.18

0.16

0.14

0.12

0.1

0.08

0.06

0.04

0.02

0 0

Dissolution front

Trapped CO 2 200 400

Chase brine front

Mobile CO 2

Advancing CO 2 front

Simulation Analytical solution 600 800 Distance (m) 1000 1200 1400

f gi

= 0.5

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0 0

Dissolution front

Trapped CO 2 200

Chase brine front

Mobile CO 2

Advancing CO 2 front

Simulation Analytical solution 400 600 800 1000 Distance (m) 1200 1400

f gi

= 0.85

Design of carbon dioxide storage

Producer Injector

SPE 10 reservoir model, 1,200,000 grid cells (60X220X85), 7.8 Mt CO 2 injected.

Z Z 3200m X Y 2280m Trapped CO 2 saturation 3200m X Y 2280m Mobile CO 2 saturation

Two years after chase water injection for

f gi

=0.85.

Design of carbon dioxide storage

3D simulation: Storage efficiency vs. trapping efficiency

Trapping efficiency

= the fraction of the injected mass of CO 2 that is either trapped or dissolved

Storage efficiency

= the fraction of the reservoir pore volume filled with CO 2

The storage efficiency is highest for f

gi

= 0.85, which also requires minimum mass of chase brine to trap 95% of CO 2 .

Design Criterion

• Inject CO 2 +brine where mobility ratio = 1.0 (

f gi

=0.85 in this example).

• Inject chase brine that is 25% of the initially injected CO 2 mass.

• 90-95% of the CO 2 is trapped.

Issues arising from field scale simulation

• Streamline-based simulator has been extended to model CO 2 storage in aquifers and oil reservoir by incorporating a Todd-Longstaff model, equilibrium transfer between phases (dissolution) and rate-limited reaction; • Trapping is an important mechanism to store CO 2 phase. Our study showed that WAG CO 2 as an immobile injection into aquifer can trap more than 90% of the CO 2 injected; • We have proposed a design strategy for CO 2 storage in aquifers, in which CO 2 and formation brine are injected simultaneously followed by chase brine. • Streamline-based simulation combined with pore-scale network modeling can capture both the large-scale heterogeneity of the reservoir and the pore-scale effects of trapping.

Future work

Injection strategy design

• Require better experimental data, since the trapping model used has a significant impact on the results.

• Design of an injection strategy to maximize CO 2 and oil recovery.

storage

CT Scanning

 A homogeneous sandpack was compressed and the porosity was determined via mass balance (Φ = 38,93).

 n-Heptane was injected; when no more brine was produced, another CT scan was performed at the irreducible water saturation, S wi .

 CO 2 was injected again. Gas injection was stopped when no more liquid production was observed. Another CT scan was taken.

 30 pore volumes (PV) of brine were injected and a final CT scan was taken at the residual gas saturation S gr .

 resolution 9 µm

Sandpack at irreducible water saturation

Brine – blue Sand – red Oil - orange • • • Oil penetrates on average mainly into the larger pores as expected by capillary pressure considerations. Thin water layer is visible on the rock surface as expected for quartz.

Oil has penetrated into the middle of some pores.

Sandpack at residual gas saturation

Brine –blue Sand – red CO 2 - yellow • • • The largest CO 2 ganglia is continuously spread over the largest available pore.

Though overall gas accumulates in the larger pores, a random distribution between large and medium size pores is observable.

Several tiny gas bubbles are randomly distributed in the pore volume. Though they might originate from the segmentation process, it is thought that they are real.

Vertical column experiments – Sor vs. Soi

•Sand-packed columns were oriented vertically.

•5 pore volumes of de-aired brine were injected to reach full saturation.

•Decane reservoir connected to top of columns and brine allowed to drain under gravity from the base. Decane enters the top of the column. No pumping.

•Equilibrium reached where both columns have a (theoretically) identical oil saturation profile versus height.

•One column removed for slicing and sampling – Soi .

•Second column has brine injected from the base, Brine sweeps oil leaving an Sor . Coulmn sliced and sampled.

COLUMN A - Soi COLUMN B - Sor

Vertical column experiments – Sor vs. Soi - results

0.30

0.25

0.20

0.15

0.10

0.05

0.00

0.0

0.2

Land - Experiment 2 Experimental Data - Exp. 2 Core Flood Results Land - Core Flood 0.4

Soi

0.6

0.8

1.0