Solution of Benchmark Problems for CO 2 Storage

Solution of Benchmark

Problems for CO2 Storage

Min Jin, Gillian Pickup and Eric MackayHeriot-Watt University

Institute of Petroleum Engineering

Outline

• Introduction

• Problem 1– Leakage through an abandoned well

• Problem 2– Enhanced methane recovery

• Problem 3– Storage capacity in a geological formation

• Conclusions

Numerical Simulation

• Simulation is a very important tool for CO2 storage

• Can give estimates of– migration of CO2 gas

– dissolution in brine– build-up of pressure around injection

well– etc

Reliability

• Depends on– Input data

• geological structure• rock permeability/porosity measurements• laboratory measurements

• Also depends– Adequate computer models

• flow equations• representation of physical processes

Reservoir Simulation

• Codes are complex• Various different versions available

for– gridding model– calculating fluid properties– solving equations

• May get slightly different answers

Benchmark Problems

• Compare solutions using different codes

• If results are the same– gives confidence in simulation results

• If they are different– indicates where more work is needed

Stuttgart Workshop, April 2008

• Aim– Discuss current capabilities of

mathematical and numerical models for CO2 storage

• Compare results of 3 benchmark problems

• Focus model development on open questions and challenges

• 12 groups participatingweb site: http://www.iws.uni-stuttgart.de/co2-workshop/

Heriot-Watt Entry

• Solutions to all 3 problems

• Eclipse 300– Reservoir simulation software package– Compositional simulation– Schlumberger

Outline

• Introduction

• Problem 1– Leakage through an abandoned well

• Problem 2– Enhanced methane recovery

• Problem 3– Storage capacity in a geological formation

• Conclusions

Problem 1

• CO2 plume evolution and leakage through an abandoned well

aquifer

aquifer

aquitard

leaky well

1000 m

k = 0 mD,= 0.0

k = 200 mD,= 0.15

k = 200 mD,= 0.15

Problem 1

• CO2 plume evolution and leakage through an abandoned well

aquifer

aquifer

CO2 injector

aquitard

leaky well

Problem 1

• CO2 plume evolution and leakage through an abandoned well

aquifer

aquifer

CO2 injector

aquitard

?leaky well

Model Details

• Lateral extent of model: 1000 m x 1000 m

• Separation of wells: 100 m• Aquifer thickness: 30 m

– perm: 200 mD, poro = 0.15

• Aquitard thickness: 100 m– impermeable

• Abandoned well– model as thin column of 1000 mD, poro =

0.15

Details of Fluid Properties

• Problem 1.1– Reservoir is very deep, ~3000 m– Simplified fluid properties

• constant with P and T

• Problem 1.2– Shallower reservoir, <800 m

– CO2 can change state when rising

– More complex fluid properties

Other Inputs to Simulation

• Constant injection rate– 8.87 kg/s

• Pressure should stay constant at the edges of the model

• No-flow boundaries top and bottom

Challenges

• Gridding– Coarse over most of model– Fine near wells

x

y

Close-up of Grid Centre

leaky wellinjector

Challenges

• Modelling of abandoned wella) Model as high perm columnb) Model as closed well

• output potential production

high perm cells closed well

Challenges

• Maintaining pressure constant at boundaries

• Eclipse designed for oil reservoirs– assumes sealed boundaries

• leads to build up of pressure

• We added aquifers to sides of the model

– fluids could move into the aquifer– prevented build up of pressure

Challenges

• Fluid properties in Problem 1.2a) User-definedb) Specified as functions of pressure and

temperature

• We used constant T = 34 oC– Tuned equations

• density and pressure similar to specified values

CO2 Distribution after 100 Days, Problem 1.2

InjectorLeaky well

Gas Sat

0.0 0.2 0.4 0.6 0.8

CO2 Distribution after 2000 Days, Problem 1.2

Gas Sat

0.0 0.2 0.4 0.6 0.8

Inj leaky well

Results

• Leakage rate for Problem 1.2

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0 500 1000 1500 2000 2500

time (day)

leak

age

volu

me/

inje

ctio

n v

olu

me

(%)

leaky well modelled as high perm cells

Summary of Problem 1

• Successfully predicted well rate– Using high perm cells for leaky well

• well model overestimated leakage

– Our results similar to others

• Leakage rate ~ 0.1% injected volume

Outline

• Introduction

• Problem 1– Leakage through an abandoned well

• Problem 2– Enhanced methane recovery

• Problem 3– Storage capacity in a geological formation

• Conclusions

Problem 2

• Enhanced recovery of CH4 combined with CO2 storage

kh = 50 mDkv = 5mD = 0.23

CO2 injector

producer

200 m

45 m

200 m

Model Details

• Two versions1. homogeneous2. layered

• Temperature = 66.7 oC• Depleted reservoir pressure = 35.5

bar• Molecular diffusion = 6 x 10-7 m2/s

Model for Problem 2.2

P

x

z

I

0 10 20 30 40 50 60 70 80 90 100

Perm (mD)

Other Inputs to Simulation

• Constant injection rate for CO2

– 0.1 kg/s– inject into lower layer– produce from upper layer

• Constant pressure at production well– P = 35.5 bar

• No-flow across model boundaries

Challenges

• Mixing of gases

• Changes in physical properties of gas mixture with composition– can be modelled in Eclipse 300

• Numerical diffusion– will artificially increase the molecular

diffusion

Result for Problem 2-1

Results – Homogeneous Model

0.00

500.00

1000.00

1500.00

2000.00

2500.00

3000.00

0 200 400 600 800 1000 1200 1400 1600 1800 2000

time (day)

mas

s f

lux

(kg

/d)

CH4 CO2

• Mass Flux of CH4 and CO2

Results – Layered Model

0

500

1000

1500

2000

2500

3000

0 200 400 600 800 1000 1200 1400 1600 1800 2000

time (day)

mas

s fl

ux

(kg

/d)

CH4 CO2

• Mass Flux of CH4 and CO2

Results and Summary

• Assume well is shut down when CO2 production reaches 20% by mass

• Relatively easy problem

Problem Model Shut-in time (days)

Recovery Efficiency (%)

2.1 homogeneous 1727 59

2.2 layered 1843 64

Outline

• Introduction

• Problem 1– Leakage through an abandoned well

• Problem 2– Enhanced methane recovery

• Problem 3– Storage capacity in a geological formation

• Conclusions

Problem 3

• Storage capacity in a geological model

Inj

x

y

z0.17 0.19 0.21 0.23 0.25

porosity

Model Details

• Lateral dimensions– 9600 m x 8900 m

• Formation thickness– between 90 and 140 m

• Variable porosity and permeability

• Depth ~ 3000 m

• Temperature = 100 oC

Challenges

• Simulation of system after injection has ceased– CO2 continues to rise due to buoyancy

– Brine moves into regions previously occupied by CO2

– Brine can occupy small pores, trapping CO2 in larger pores

• additional trapping mechanism• hysteresis

Challenges

• Trapping of CO2 by hysteresis

after Doughty, 2007

Plume of rising CO2

CO2 displacing brine

brine displacing CO2

CO2 Distribution after 25 Years

Gas Sat

0.0 0.2 0.5 0.8

Y

X

withhysteresisfault

CO2 Distribution after 50 Years

Gas Sat

0.0 0.2 0.5 0.8

Y

X

withhysteresisfault

Results

• Mass of CO2 in formation over time

0.0E+00

2.0E+09

4.0E+09

6.0E+09

8.0E+09

1.0E+10

1.2E+10

1.4E+10

0 5000 10000 15000 20000

Time (days)

Mas

s o

f C

O2

totalfreedissolved

(kg)

Results• Leakage of CO2 across the boundaries

CO2 inter-region mass flow rate for Problem 3

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Time (day)

Mas

s F

low

rat

e (k

g/s)

P3-1

P3-2no hysteresis

with hysteresis

Summary of Problem 3

• CO2 did not move towards the fault– moved up-dip– leaked across model boundary

• Hysteresis did make difference, but not much difference in this example

• About 0.2 of the injected CO2 dissolved after 50 years

Outline

• Introduction

• Problem 1– Leakage through an abandoned well

• Problem 2– Enhanced methane recovery

• Problem 3– Storage capacity in a geological formation

• Conclusions

Conclusions

• Benchmark solutions highlight difficulties– Adaptation of simulator for oil/gas

reservoirs to CO2 storage

– Difficulties are surmountable

– Schlumberger created new module for CO2 storage

• Participation in the workshop– Giving us confidence in simulations

Acknowledgements

• We thank Schlumberger for letting us use the Eclipse simulation software

Solution of Benchmark

Problems for CO2 Storage

Min Jin, Gillian Pickup and Eric MackayHeriot-Watt University

Institute of Petroleum Engineering