1 / 22

Modified nested-gridding for upscaling-downscaling of reservoir simulation

International Conference on Flows and Mechanics in Natural Porous Media  from Pore to Field Scale - Pore2Field  16 - 18 November 2011. Modified nested-gridding for upscaling-downscaling of reservoir simulation. Masoud Babaei Prof. Peter R. King. Outline. What is Upscaling?

oriel
Download Presentation

Modified nested-gridding for upscaling-downscaling of reservoir simulation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. International Conference onFlows and Mechanics in Natural Porous Media from Pore to Field Scale - Pore2Field  16 - 18 November 2011 Modified nested-gridding for upscaling-downscaling of reservoir simulation Masoud Babaei Prof. Peter R. King

  2. Outline • What is Upscaling? • Assign “effective” properties to coarse scale gridblocksfrom properties of fine scale geocellular grid. • Capture the flow features of fine scale model. • Why Upscale? • Make simulation practical • ─ geological models: ~10 ‑100 million cells • Reduce CPU time for uncertainty analysis and risk assessment • Importance of upscaling • Errors associated with upscaling for EOR performance simulation • Adaptive Local-Global (ALG) upscalingand Nested-Gridding (NG) downscaling • Modifications • Water and polymer flood simulation and comparison of production curves and saturation profiles • Remarks

  3. Upscaling of Absolute Permeability • 6×6×5 • 60×60×50 • Pressure Solver Method (PSM) • Warren, J.E. & Price, H.S. (1961)

  4. Water flooding Pressure equation Saturation equation • Finite difference for pressure eqn. • Implicit (Newton-Raphson) iteration loop for saturation eqn. • Tracer flow • Multiphase flow

  5. 1 1 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 0 0.5 1 1.5 0 0.2 0.4 0.6 0.8 1 1 0.8 0.6 0.4 0.2 0 0 0 0.2 0.4 0.6 0.8 1 0 0.5 1 1.5 Comparison with fine scale (Errors of Upscaling) Water cut vs. PV injected Smooth layer (1) Reference―, GM―,PSM ― Injector Producer Injector 1 0.8 0.6 0.4 0.2 Channelized layer (37) Producer Upscaled from 60×220 to 6×22 10th SPE CSP Model, Christie, M.A. & Blunt, M.J. (2001)

  6. Adaptive Iterative Upscaling-Downscaling Scheme Adaptive local global iterative upscaling: Chen, Y. & Durlofsky, L.J. (2006). Kippe, V., Aarnes,J. & Knut-Andreas (2008) Calculate the coarse transmissibility from assumed boundary conditions Criterion for detecting the dynamic regions: Use new coarse pressures as boundaries of local problems Solve coarse problem by coarse properties

  7. Adaptive Iterative Upscaling-Downscaling Scheme (continued) Nested-Gridding downscaling Gautier, Y., Blunt, M.J. & Christie, M.A. (1999)

  8. Modifications in downscaling ALG-MNG ALG-MNG– or ALG-MNG+

  9. Switching the scales Fine scale permeability Coarse scale representation Fine scale saturation Reconstructed fine scale velocity Coarse scale velocity Reference fine scale simulation Upscaling/Downscaling simulation

  10. Water cut- Layer 10 Water cut- Layer 37 Water cut- Layer 47 1 1 1 0.8 0.8 0.8 0.6 0.6 0.6 0.4 PSM 0.4 0.4 PSM PSM PSM-NG PSM-NG PSM-NG ALG ALG ALG 0.2 0.2 0.2 ALG-MNG ALG-MNG ALG-MNG Fine Fine Fine 0 0 0 0 0.5 1 1.5 0 0 0.5 0.5 1 1 1.5 1.5 PVI PVI PVI Linear flow case f(S)=const. 0.004 to 20,000mD Upscaled from 60×220 to 6×22

  11. Layer 47 Layer 37 Layer 10 0.2 1 0.8 PSM-NG PSM-NG PSM-NG ALG-NG ALG-NG ALG-NG PSM-MNG PSM-MNG PSM-MNG ALG-MNG 0.8 ALG-MNG 0.16 0.6 ALG-MNG 0.6 0.12 0.4 0.08 0.4 0.2 0.2 0 0 0 0.5 0.5 0.5 1 1 1 1.5 1.5 1.5 PVI PVI PVI Error in saturation profiles Application of MNG

  12. Fine Model 0.8 0.6 0.4 0.2 0 ALG-NG Model ALG-MNG– Model 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 PSM-NG Model 0.8 0.6 0.4 0.2 0 Saturation profiles

  13. Water cut- Layer 37- M=0.1 Water cut- Layer 10- M=0.1 1 1 PSM PSM-NG 0.8 0.8 ALG ALG-MNG+ ALG-MNG– 0.6 0.6 Fine PSM 0.4 0.4 PSM-NG ALG ALG-MNG+ 0.2 0.2 ALG-MNG– Fine 0 0 0 0.5 1 0 0.5 1 1.5 1.5 PVI PVI Multiphase flow, M=0.1

  14. Water cut- Layer 10- M=10 Water cut- Layer 37- M=10 1 1 0.8 0.8 0.6 0.6 PSM PSM 0.4 0.4 PSM-NG PSM-NG ALG ALG ALG-MNG+ ALG-MNG+ 0.2 0.2 ALG-MNG– ALG-MNG– Fine Fine 0 0 0 0.5 1 1.5 0 0.5 1 1.5 PVI PVI Multiphase flow, M=10

  15. Layer 47 Layer 37 Layer 10 0.19 0.55 1 PSM-NG PSM-NG ALG-NG ALG-NG 0.45 0.8 PSM-MNG PSM-MNG PSM-NG 0.14 ALG-MNG+ ALG-MNG+ ALG-NG ALG-MNG– ALG-MNG– PSM-MNG 0.35 0.6 ALG-MNG+ ALG-MNG– 0.09 0.25 0.4 0.15 0.04 0.2 0 0 0 0.5 0.5 0.5 1 1 1 1.5 1.5 1.5 PVI PVI PVI Error in saturation profiles

  16. Layer 37 (m3/atm.day) 7 Fine PSM-NG 6 ALG-NG ALG-MNG+ 5 ALG-MNG– 4 Layer 47 (m3/atm.day) 8 3 Fine 7 PSM-NG 2 ALG-NG 6 ALG-MNG+ 1 ALG-MNG– 5 0 4 0 10 20 30 40 50 60 3 2 1 0 0 10 20 30 40 50 60 Directional flow with constant-pressure production 60×220 to 6×22

  17. 6 0.5 0.5 0.5 0.4 0.4 0.4 4 0.3 0.3 0.3 2 0.2 0.2 0.2 0.1 0.1 0.1 0 0 0 0 Synthetic channelized system Chen et al. 2004, This permeability model is characterized by high variations from 0.02 to 6.5×107mD, a mean of 7×104mD and isotropic normalized correlation lengths varying from 0.05 to 0.5.

  18. Application on polymer flooding

  19. Recovery Factor 0.35 0.3 0.25 0.2 0.15 Fine PSM 0.1 PSM-NG ALG 0.05 ALG-MNG– 0 0 0.5 1 1.5 Upscaling-downscaling for polymer flood

  20. Next step We can compartmentalize the solution of saturation equation (transport equation) in the same fashion.

  21. Remarks • We implemented an upscaling-downscaling scheme for incompressible waterflooding simulation with satisfyingly accurate result compared to direct gemodel (fine scale ) simulation. • We introduced a simple modification with good improvements in downscaling part. • Use of basis functions in downscaling part can lead to time saving in large scale reservoirs without loss of precision of original skill courtesy of incompressibility.

  22. Thank you for your attention Questions?

More Related