fast simulation of highly heterogeneous and fractured porous media
TRANSCRIPT
Fast Simulation of Highly Heterogeneous andFractured Porous Media
Knut–Andreas Lie
SINTEF ICT, Dept. Applied Mathematics
Bergen, May 2006
Applied Mathematics May 2006 1/20
The GeoScale Project Portifolio
Vision:
Direct simulation of fluid flow on high-resolution geomodels ofhighly heterogeneous and fractured porous media in 3D.
Research keywords:
multiscale methods, upscaling/downscaling
robust discretisations of pressure equations
fast simulation of fluid transport
Contact:
http://www.math.sintef.no/geoscale/
+47 22 06 77 10 / +47 930 58 721
Applied Mathematics May 2006 2/20
GeoScale Portifolio – A Collaborative Effort
Partners:
SINTEF
Universities of Bergen, Oslo, and Trondheim
Schlumberger, Shell, Statoil
Education:
4-5 PhD grants (RCN, UoB, NTNU, Shell)
4 postdoc grants (RCN, EU, Schlumberger)
2 master students
Collaboration:
Stanford, Texas A&M, Ume̊a
Schlumberger Moscow Research, Statoil Research Centre
Applied Mathematics May 2006 3/20
Simulation on Geological Models
For various reasons, there is a need fordirect simulation on high-resolutiongeomodels. This is difficult:
K spans many length scales andhas multiscale structure
maxK/ minK ∼ 103–1010
Details on all scales impact flow
Gap between simulation models and geomodels:
High-resolution geomodels may have 107 − 109 cells
Conventional simulators are capable of about 105 − 106 cells
Applied Mathematics May 2006 4/20
Motivation
Applications for fast (and lightweight) simulators for :
direct simulation of large geomodels
multiple realisations
history-matching
. . .
Long-term collaboration with Schlumberger:
Petrel workflow tools
FrontSim streamline simulator
Applied Mathematics May 2006 5/20
Developing More Robust Discretisations
Accurate simulation on industry-standard grid models ischallenging!
Skew and deformed gridblocks:
Non-matching cells:
Our approach: finite elements and/or mimetic methods
Applied Mathematics May 2006 6/20
Developing an Alternative to Upscaling
We seek a methodology that:
gives a detailed image of the flow pattern on the fine scale,without having to solve the full fine-scale system
is robust and flexible with respect to the coarse grid
is robust and flexible with respect to the fine grid and thefine-grid solver
is accurate and conservative
is fast and easy to parallelise
Applied Mathematics May 2006 7/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓
⇑
Coarse grid blocks:⇓
⇑
Flow problems:
Multiscale method:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Applied Mathematics May 2006 8/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Multiscale method:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Applied Mathematics May 2006 8/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Multiscale method:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Applied Mathematics May 2006 8/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓ ⇑Coarse grid blocks:
⇓ ⇑Flow problems:
Multiscale method:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Applied Mathematics May 2006 8/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓ ⇑Coarse grid blocks:
⇓ ⇑Flow problems:
Multiscale method:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Applied Mathematics May 2006 8/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓ ⇑Coarse grid blocks:
⇓ ⇑Flow problems:
Multiscale method:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Applied Mathematics May 2006 8/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓ ⇑Coarse grid blocks:
⇓ ⇑Flow problems:
Multiscale method:
⇓
⇑
Coarse grid blocks:
⇓
⇑
Flow problems:
Applied Mathematics May 2006 8/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓ ⇑Coarse grid blocks:
⇓ ⇑Flow problems:
Multiscale method:
⇓
⇑
Coarse grid blocks:
⇓ ⇑Flow problems:
Applied Mathematics May 2006 8/20
From Upscaling to Multiscale Methods
Standard upscaling:
⇓ ⇑Coarse grid blocks:
⇓ ⇑Flow problems:
Multiscale method:
⇓ ⇑Coarse grid blocks:
⇓ ⇑Flow problems:
Applied Mathematics May 2006 8/20
Advantage: Accuracy10th SPE Comparative Solution Project
Producer A
Producer B
Producer C
Producer D
Injector
Tarbert
UpperNess
Geomodel: 60× 220× 85 ≈ 1, 1 million grid cells
Simulation: 2000 days of production
Applied Mathematics May 2006 9/20
Advantage: AccuracySPE10 Benchmark (5× 11× 17 Coarse Grid)
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ReferenceMsMFEM Nested Gridding
ReferenceMsMFEM Nested Gridding
ReferenceMsMFEM Nested Gridding
ReferenceMsMFEM Nested Gridding
Nested gridding: upscaling + downscaling
Applied Mathematics May 2006 10/20
Computational Complexity
Direct solution may be more efficient, so why bother with multiscale?
Full simulation: O(102) timesteps.
Basis functions need not berecomputed
Also:
Possible to solve very largeproblems
Easy parallelization8x8x8 16x16x16 32x32x32 64x64x64
0
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8x 107
Computation of basis functionsSolution of global system
Fine scale solution
Applied Mathematics May 2006 12/20
Flexibility
Multiscale mixed formulation:
coarse grid = union of cells in fine grid
Given a numerical method thatworks on the fine grid, theimplementation is straightforward.
One avoids resampling when goingfrom fine to coarse grid, and viceversa
Other formulations:
Finite-volume methods: based upon dual grid −→ special casesthat complicate the implementation in the presence of faults, localrefinements, etc.
Applied Mathematics May 2006 13/20
Flexibility wrt. GridsFracture Networks
1
1Grid model courtesy of M. Karimi-Fard, Stanford
Applied Mathematics May 2006 17/20
Fast Simulation of Fluid Transport
discontinuous Galerkin
reordering
large time-steps
multiphase transport
tracer flow
delineation of volumes
Applied Mathematics May 2006 18/20
Future Work
Multiscale methods
Well models (adaptive gridding, multilaterals)
More general grids (block-structured, PEBI, ..)
Compressibility, multiphase and multicomponent
Adaptivity
Fractures and faults
Applications:
Multiscale history matching
Carbonate reservoirs..?
CO2..?
Applied Mathematics May 2006 20/20