Solution of Benchmark Problems for CO 2 Storage

1. Solution of Benchmark Problems for CO2 Storage Min Jin, Gillian Pickup and Eric Mackay Heriot-Watt University Institute of Petroleum Engineering

2. Outline • Introduction • Problem 1 • Leakage through an abandoned well • Problem 2 • Enhanced methane recovery • Problem 3 • Storage capacity in a geological formation • Conclusions

3. 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

4. Reliability • Depends on • Input data • geological structure • rock permeability/porosity measurements • laboratory measurements • Also depends • Adequate computer models • flow equations • representation of physical processes

5. Reservoir Simulation • Codes are complex • Various different versions available for • gridding model • calculating fluid properties • solving equations • May get slightly different answers

6. 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

7. 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 participating web site: http://www.iws.uni-stuttgart.de/co2-workshop/

8. Heriot-Watt Entry • Solutions to all 3 problems • Eclipse 300 • Reservoir simulation software package • Compositional simulation • Schlumberger

9. Outline • Introduction • Problem 1 • Leakage through an abandoned well • Problem 2 • Enhanced methane recovery • Problem 3 • Storage capacity in a geological formation • Conclusions

10. Problem 1 • CO2 plume evolution and leakage through an abandoned well leaky well k = 200 mD, f = 0.15 aquifer k = 0 mD, f = 0.0 aquitard k = 200 mD, f = 0.15 aquifer 1000 m

11. Problem 1 • CO2 plume evolution and leakage through an abandoned well leaky well CO2 injector aquifer aquitard aquifer

12. Problem 1 • CO2 plume evolution and leakage through an abandoned well leaky well ? CO2 injector aquifer aquitard aquifer

13. 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

14. 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

15. 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

16. x y Challenges • Gridding • Coarse over most of model • Fine near wells

17. Close-up of Grid Centre leaky well injector

18. Challenges • Modelling of abandoned well • Model as high perm column • Model as closed well • output potential production high perm cells closed well

19. 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

20. Challenges • Fluid properties in Problem 1.2 • User-defined • Specified as functions of pressure and temperature • We used constant T = 34 oC • Tuned equations • density and pressure similar to specified values

21. CO2 Distribution after 100 Days, Problem 1.2 Injector Leaky well Gas Sat 0.0 0.2 0.4 0.6 0.8

22. Gas Sat 0.0 0.2 0.4 0.6 0.8 CO2 Distribution after 2000 Days, Problem 1.2 Inj leaky well

23. Results • Leakage rate for Problem 1.2 leaky well modelled as high perm cells

24. 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

25. Outline • Introduction • Problem 1 • Leakage through an abandoned well • Problem 2 • Enhanced methane recovery • Problem 3 • Storage capacity in a geological formation • Conclusions

26. CO2 injector 45 m kh = 50 mD kv = 5mD f = 0.23 producer 200 m 200 m Problem 2 • Enhanced recovery of CH4 combined with CO2 storage

27. Model Details • Two versions • homogeneous • layered • Temperature = 66.7 oC • Depleted reservoir pressure = 35.5 bar • Molecular diffusion = 6 x 10-7 m2/s

28. x P I z Perm (mD) 0 10 20 30 40 50 60 70 80 90 100 Model for Problem 2.2

29. 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

30. 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

31. Result for Problem 2-1

32. Results – Homogeneous Model • Mass Flux of CH4 and CO2

33. Results – Layered Model • Mass Flux of CH4 and CO2

34. Results and Summary • Assume well is shut down when CO2 production reaches 20% by mass • Relatively easy problem

35. Outline • Introduction • Problem 1 • Leakage through an abandoned well • Problem 2 • Enhanced methane recovery • Problem 3 • Storage capacity in a geological formation • Conclusions

36. y Inj x porosity z 0.17 0.19 0.21 0.23 0.25 Problem 3 • Storage capacity in a geological model

37. 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

38. 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

39. CO2 displacing brine Plume of rising CO2 brine displacing CO2 Challenges • Trapping of CO2 by hysteresis after Doughty, 2007

40. CO2 Distribution after 25 Years X with hysteresis fault Y Gas Sat 0.0 0.2 0.5 0.8

41. CO2 Distribution after 50 Years X with hysteresis fault Y Gas Sat 0.0 0.2 0.5 0.8

42. Results • Mass of CO2 in formation over time (kg)

43. Results • Leakage of CO2 across the boundaries no hysteresis with hysteresis

44. 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

45. Outline • Introduction • Problem 1 • Leakage through an abandoned well • Problem 2 • Enhanced methane recovery • Problem 3 • Storage capacity in a geological formation • Conclusions

46. 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

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

48. Solution of Benchmark Problems for CO2 Storage Min Jin, Gillian Pickup and Eric Mackay Heriot-Watt University Institute of Petroleum Engineering