# Solution of Benchmark Problems as long as CO2 Storage Solution of Benchmark Problems as long as CO2 Storage

## Solution of Benchmark Problems as long as CO2 Storage Solution of Benchmark Problems as long as CO2 Storage

McDonald, Beth, Host has reference to this Academic Journal, PHwiki organized this Journal Solution of Benchmark Problems as long as CO2 Storage Min Jin, Gillian Pickup in addition to Eric Mackay Heriot-Watt University Institute of Petroleum Engineering Outline Introduction Problem 1 Leakage through an ab in addition to oned well Problem 2 Enhanced methane recovery Problem 3 Storage capacity in a geological as long as mation Conclusions Numerical Simulation Simulation is a very important tool as long as CO2 storage Can give estimates of migration of CO2 gas dissolution in brine build-up of pressure around injection well etc

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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 as long as 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 in addition to numerical models as long as CO2 storage Compare results of 3 benchmark problems Focus model development on open questions in addition to challenges 12 groups participating web 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 ab in addition to oned well Problem 2 Enhanced methane recovery Problem 3 Storage capacity in a geological as long as mation Conclusions

Problem 1 CO2 plume evolution in addition to leakage through an ab in addition to oned well aquifer aquifer aquitard leaky well 1000 m k = 0 mD, f = 0.0 k = 200 mD, f = 0.15 k = 200 mD, f = 0.15 Problem 1 CO2 plume evolution in addition to leakage through an ab in addition to oned well aquifer aquifer CO2 injector aquitard leaky well Problem 1 CO2 plume evolution in addition to leakage through an ab in addition to oned 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 Ab in addition to oned 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 in addition to 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 in addition to bottom Challenges Gridding Coarse over most of model Fine near wells Close-up of Grid Centre leaky well injector Challenges Modelling of ab in addition to oned well Model as high perm column Model as closed well output potential production high perm cells closed well Challenges Maintaining pressure constant at boundaries Eclipse designed as long as 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 1.2 User-defined Specified as functions of pressure in addition to temperature We used constant T = 34 oC Tuned equations density in addition to pressure similar to specified values CO2 Distribution after 100 Days, Problem 1.2 Injector Leaky well Gas Sat 0.0 0.2 0.4 0.6 0.8 CO2 Distribution after 2000 Days, Problem 1.2 Inj leaky well Results Leakage rate as long as Problem 1.2 leaky well modelled as high perm cells Summary of Problem 1 Successfully predicted well rate Using high perm cells as long as leaky well well model overestimated leakage Our results similar to others Leakage rate ~ 0.1% injected volume

Outline Introduction Problem 1 Leakage through an ab in addition to oned well Problem 2 Enhanced methane recovery Problem 3 Storage capacity in a geological as long as mation Conclusions Problem 2 Enhanced recovery of CH4 combined with CO2 storage Model Details Two versions homogeneous layered Temperature = 66.7 oC Depleted reservoir pressure = 35.5 bar Molecular diffusion = 6 x 10-7 m2/s

Model as long as Problem 2.2 Other Inputs to Simulation Constant injection rate as long as 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

Conclusions Benchmark solutions highlight difficulties Adaptation of simulator as long as oil/gas reservoirs to CO2 storage Difficulties are surmountable Schlumberger created new module as long as CO2 storage Participation in the workshop Giving us confidence in simulations Acknowledgements We thank Schlumberger as long as letting us use the Eclipse simulation software Solution of Benchmark Problems as long as CO2 Storage Min Jin, Gillian Pickup in addition to Eric Mackay Heriot-Watt University Institute of Petroleum Engineering

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