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The sensitivity of CO2 storage simulations to
pressure artifacts: indications from the
Sleipner Benchmark model
Geophysical Modelling for CO2 Storage, Monitoring and
Appraisal, University of Leeds, November, 2015
Andrew Cavanagh
Principal Researcher
Statoil RDI
 acava@statoil.com
 +47 9027 9715
Workflow...
2
Decide the model purpose
Establish conceptual geological models
Build rock models
Build property models
Assign flow properties and functions
Upscale flow properties and functions
Make forecasts
Assess and handle uncertainties
Re-iterate as necessary:
1. Maintain subsurface
database;
2. Preserve model build
decision track;
3. Discard or archive the
model results;
4. Address the next
question…
Compare simulations to
observations
2.0
0.0
Totalmass,CO2(Mt)
Simulated time: 100 yrs
0.25
0.00
DissolvedCO2(Fraction)
VE x10
The Sleipner plume
• Seismic monitoring has allowed for significant
improvements in understanding CO2 flow dynamics
• An improved basis for predicting the future plume
distribution and estimation of dissolved CO2
 High-resolution model
(Layer 9 circa 2008)
 Good match to observed
distribution (red line)
Permedia BOS
3 Classsification: Draft 2014-04-22 (Cavanagh, Energy Procedia 2013)
Sleipner Benchmark (IEAGHG)
0.25
0.00
Dissolution estimate
4
DissolvedCO2(Fraction)
2.0
0.0
Totalmass,CO2(Mt)
Simulated time: 100 yrs
(2010)
10%
20%
VE x10
Permedia CO2 BOS
(Cavanagh, EP, 2013)
Implementation after
Hassanzadeh et al.
(IJGGC, 2008)
Plume calibration
• Darcy flow approach:
− Viscous forces, reservoir simulation
− Vertical equilibrium assumption (VE)
− Poor match, strong pressure artifact
• Percolating flow approach:
− Capillary forces, basin modeling
− Gravity assumption for migration (MGN)
− Equally poor match, but is buoyancy closer?
• We then allow the pressure to dissipate in the VE reservoir simulation,
and the plume redistributes to its buoyant equilibrium position. A much
better match to the footprint of the seismic observation is achieved.
Flow modeling based on seismic
5 Classsification: Draft 2014-04-22
Reservoir simulation
2-phase black oil model (CO2 BOS)
6 Classsification: Draft 2014-04-22
• Calibrating for 2008 seismic footprint
based on pressure equilibrium
• Simulation time in years:
• Pressure field at the end of injection:
~ 460 to 710 kPa (65-100 psi) overpressure
~ 250 kPa (36 psi) drop over 3 km
1015203040506070809010010
710
460
X
Conclusion
7
1999 2001 2002 2004 2006 2008
Dynamic equilibrium
The simulation results clearly indicate that the plume beneath
the caprock is gravity-dominated, and close to equilibrium at
every observation point (Cavanagh, Energy Procedia, 2013)
Reservoir simulations for CO2 storage may be susceptible to
significant pressure artifacts that distort the model outcome.
Implication
8
Pressure
Spatial distribution
Timing
Without calibration and correction, reservoir simulations are
highly likely to be misleading with respect to CO2 storage.



9
• Area of Interest: 3x6 km
• Cell resolution: 50x50x0.5 m
• Geocellular mesh: 550,000 cells
Sleipner Benchmark II
 Cap Rock
 Sand Wedge
 Thick Shale
 Utsira Sand
 Thin Barrier
 Base Utsira
(Cavanagh & Haszeldine, IJGGC, 2014)
10
NORWAY
A big thank you to...
Philip Ringrose (Statoil)
Varunendra Singh
Hilde Hansen
Bamshad Nazarien
Martin Iding
NeilWildgust (IEAGHG… PTRC… GCCSI!!!)
Chris Leskiw (Permedia)
JasonWudkevich
The sensitivity of CO2 storage simulations
to pressure artifacts: Indications from the
Sleipner Benchmark model
Andrew Cavanagh
Principal Researcher
acava@statoil.com
Tel: +47 2097 2715
www.statoil.com

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20 Years and 20Mt, Statoil Storage Experience, Andrew Cavanagh - Geophysical Modelling for CO2 Storage, Leeds, 3 November 2015

  • 1. The sensitivity of CO2 storage simulations to pressure artifacts: indications from the Sleipner Benchmark model Geophysical Modelling for CO2 Storage, Monitoring and Appraisal, University of Leeds, November, 2015 Andrew Cavanagh Principal Researcher Statoil RDI  acava@statoil.com  +47 9027 9715
  • 2. Workflow... 2 Decide the model purpose Establish conceptual geological models Build rock models Build property models Assign flow properties and functions Upscale flow properties and functions Make forecasts Assess and handle uncertainties Re-iterate as necessary: 1. Maintain subsurface database; 2. Preserve model build decision track; 3. Discard or archive the model results; 4. Address the next question… Compare simulations to observations
  • 3. 2.0 0.0 Totalmass,CO2(Mt) Simulated time: 100 yrs 0.25 0.00 DissolvedCO2(Fraction) VE x10 The Sleipner plume • Seismic monitoring has allowed for significant improvements in understanding CO2 flow dynamics • An improved basis for predicting the future plume distribution and estimation of dissolved CO2  High-resolution model (Layer 9 circa 2008)  Good match to observed distribution (red line) Permedia BOS 3 Classsification: Draft 2014-04-22 (Cavanagh, Energy Procedia 2013) Sleipner Benchmark (IEAGHG)
  • 4. 0.25 0.00 Dissolution estimate 4 DissolvedCO2(Fraction) 2.0 0.0 Totalmass,CO2(Mt) Simulated time: 100 yrs (2010) 10% 20% VE x10 Permedia CO2 BOS (Cavanagh, EP, 2013) Implementation after Hassanzadeh et al. (IJGGC, 2008)
  • 5. Plume calibration • Darcy flow approach: − Viscous forces, reservoir simulation − Vertical equilibrium assumption (VE) − Poor match, strong pressure artifact • Percolating flow approach: − Capillary forces, basin modeling − Gravity assumption for migration (MGN) − Equally poor match, but is buoyancy closer? • We then allow the pressure to dissipate in the VE reservoir simulation, and the plume redistributes to its buoyant equilibrium position. A much better match to the footprint of the seismic observation is achieved. Flow modeling based on seismic 5 Classsification: Draft 2014-04-22
  • 6. Reservoir simulation 2-phase black oil model (CO2 BOS) 6 Classsification: Draft 2014-04-22 • Calibrating for 2008 seismic footprint based on pressure equilibrium • Simulation time in years: • Pressure field at the end of injection: ~ 460 to 710 kPa (65-100 psi) overpressure ~ 250 kPa (36 psi) drop over 3 km 1015203040506070809010010 710 460 X
  • 7. Conclusion 7 1999 2001 2002 2004 2006 2008 Dynamic equilibrium The simulation results clearly indicate that the plume beneath the caprock is gravity-dominated, and close to equilibrium at every observation point (Cavanagh, Energy Procedia, 2013) Reservoir simulations for CO2 storage may be susceptible to significant pressure artifacts that distort the model outcome.
  • 8. Implication 8 Pressure Spatial distribution Timing Without calibration and correction, reservoir simulations are highly likely to be misleading with respect to CO2 storage.   
  • 9. 9 • Area of Interest: 3x6 km • Cell resolution: 50x50x0.5 m • Geocellular mesh: 550,000 cells Sleipner Benchmark II  Cap Rock  Sand Wedge  Thick Shale  Utsira Sand  Thin Barrier  Base Utsira (Cavanagh & Haszeldine, IJGGC, 2014)
  • 10. 10 NORWAY A big thank you to... Philip Ringrose (Statoil) Varunendra Singh Hilde Hansen Bamshad Nazarien Martin Iding NeilWildgust (IEAGHG… PTRC… GCCSI!!!) Chris Leskiw (Permedia) JasonWudkevich The sensitivity of CO2 storage simulations to pressure artifacts: Indications from the Sleipner Benchmark model Andrew Cavanagh Principal Researcher acava@statoil.com Tel: +47 2097 2715 www.statoil.com