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Page 1: Capturing Effective Permeabilities of Field Compaction bands

Capturing Effective Permeabilities of Field Compaction bands 

with Level Set and Hybrid Lattice Boltzmann/Finite Element Simulations

WaiChing Sun, Northwestern UniversityProf. Jose E. Andrade, California Institute of Technology

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Motivation2

Aztec Sandstone, Holcomb et al 2007

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Significant porosity and permeability reductions are 

observed in compaction bands 

Are compaction bands efficient flow barriers?

If so,  What are the geometrical features that lead to permeability reductions?

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Effective Permeability Measurement via Lattice Boltzmann method

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( )ij ij

k v xh

13 211 8.6 10

0.21f

k m

13 211 1.8 10

0.13f

k m

intrinsic permeability tensor of REV is computed by finding volume average velocity of Lattice Boltzmann cube with prescribed hydraulic gradient on a 150x150x150 voxels

Reynold’s number must be less than 1 to ensure the validity of Darcy’s law

Flow outside CB Flow inside CBFlow in transition zone13 2

11 2.4 10

0.15f

k m

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Question:

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1. How does the micro‐structural change cause permeability reduction? 

2. How about scale effect?

3. How can we verify our results?

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Outline1. Background2. Tools used to study 

characteristics of compaction band

i. Medial Axis (use level set)ii. Tortuosity (use weight 

graph)iii. Isolated Pore Space (use 

graph)iv. Effective permeability (use 

FEM/LBM)3. Results on Aztec 

sandstone4. Conclusion

Raw Tomography Images

Binary Images

Medial Axis

Shortest Flow Path

Isolated Pore Space

Effective Permeability

5

Image Segmentation

SPS Algorithm

FEM/LBM

Level Set Method

Recursive Function

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Image Segmentation

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Raw Tomography Images

Binary Images

Medial Axis

Shortest Flow Path

Isolated Pore Space

Effective Permeability

Image Segmentation

Dijkstra’s Algorithm

FEM/LBM

Level Set Method

Recursive Function

Page 7: Capturing Effective Permeabilities of Field Compaction bands

Aztec Sandstone Specimen 3D tomographic images are taken from Aztec sandstone collected at Valley of Fire 

State Park,  Nevada. 

A threshold is defined to distinguish pore space and 

skeleton.

A binary 3D images are crated from the original 3D 

images.

Connected and isolated pore space are not distinguished.

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Aztec Sandstone Image, Leonir, et al 2010

Work conducted by Dr. Leonir

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Level Set Method

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Raw Tomography Images

Binary Images

Medial Axis

Shortest Flow Path

Isolated Pore Space

Effective Permeability

Image Segmentation

Dijkstra’s Algorithm

FEM/LBM

Level Set Method

Recursive Function

Page 9: Capturing Effective Permeabilities of Field Compaction bands

Medial Axis of Flow Paths

• Medial axis is the spine of a volume filling object• Media axis  is a union of curves that represent the topology and geometry of the volume 

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Sirjani and Cross, 1991L

Le

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Relation between Level Set Function and Medial Axis 

• Local minimum of the signed distance function  are located at medial axis. 

• Use level set scheme to obtain signed distance function

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Locating Medial Axis of Flow Path via Level Set

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Convert binary image into level set via semi‐implicit scheme

Extract Local minimum of level set function

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Formulation of Variational Level Set Method

• Action functional (Li et al 2005)

• Governing  equation

• Semi‐Implicit Finite Difference Scheme

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Penalize  the deviation of from a signed distance function 

Drive  = 0 at the object boundaries

The discrete Laplacianterm is treated 

implicitly 

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Shortest Path Searching Algorithm

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Raw Tomography Images

Binary Images

Medial Axis

Shortest Flow Path

Isolated Pore Space

Effective Permeability

Image Segmentation

SPS Algorithm (Dijkstra, 1953)

FEM/LBM

Level Set Method

Recursive Function

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Graph Theory

Extract topology 

info

Each fluid voxel as nodes

Connectednodes with 

edges

Assignweight to edges

Form weighted graph

Apply SPS algorithm

Determine shortest Flow Path

Determine Geometrical tortuosity

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Weighted Graph

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Distance = 

Weight  

Fluid voxel = node

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[74]

Shortest Path Searching Algorithm

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1

24

3

7 86

5

9

12

15

10

1311

14

1816

19

[19][19+14=33] [19+6=25]

[35] [37]

[46]

[69]

[45] [45]

[51]

[59] [55]

[66]

[70][75]17

20[78]

[56]

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Shortest Flow Path Inside and Outside Compaction Bands

0.10.2

0.30.4

0.5

0.10.2

0.30.4

0.5

0.1

0.2

0.3

0.4

0.5

x, mmy, mm

z, m

m

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0.10.2

0.30.4

0.10.2

0.30.4

0.5

0.1

0.2

0.3

0.4

0.5

x, mmy, mm

z, m

m0.1

0.20.3

0.40.5

0.10.2

0.30.4

0.5

0.1

0.2

0.3

0.4

0.5

x, mmy, mm

z, m

m

0.10.2

0.30.4

0.5

0.10.2

0.30.4

0.5

0.1

0.2

0.3

0.4

0.5

x, mmy, mm

z, m

m

0.10.2

0.30.4

0.5

0.10.2

0.30.4

0.1

0.2

0.3

0.4

0.5

x, mmy, mm

z, m

m

0.10.2

0.30.4

0.10.2

0.30.4

0.1

0.2

0.3

0.4

0.5

x, mmy, mm

z, m

m

INSIDE CB

= 0.14

OUTSIDE CB

= 0.21

= 2.79K= 3.4e‐13 m2

= 2.15K= 5.3e‐13 m2

= 2.56K= 4.4e‐13 m2

= 1.77K= 1.3e‐12 m2

= 1.76K= 1.2e‐12 m2

= 1.81K= 1.3e‐12 m2

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Recursive Function

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Raw Tomography Images

Binary Images

Medial Axis

Shortest Flow Path

Isolated Pore Space

Effective Permeability

Image Segmentation

Dijkstra’s Algorithm

FEM/LBM

Level Set Method

Recursive Function

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Connected Porosity vs. Porosity• Only the connected pore space affects the 

effective permeability

• Isolated pore space should be 

treated as inactive voxels in LBM simulation 

to reduce computational 

cost

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Isolated Pore Space

Connected Pore Space

Flow  Direction

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Recursive Functions

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1

24

3

7 86

5

9

12

15

10

1311

14

1816

19

17

20

PROGRAM MAIN1. Activate all vertices along the flow path 

as active nodes and mark them as visited vertices

2. While there exists at least one active node 

3. call the recursive function MARKNEIGHBOR

EXIT

FUNCTION MARKNEIGHBOR1. IF at least one neighbors of the active 

nodes has not yet been visited1. Activate the unvisited neighbor vertices2. Mark them as visited vertices.  3. Deactivate the old active nodes with 

unvisited neighbor(s). 4. Call the recursive function 

MARKNEIGHBOR2. ELSE

1. Deactivate the active nodes with no unvisited neighbor. 

3. EXITEXIT

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Connected and Isolated Pore Space of Compaction Bands

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Inside CB

Outside CB0.00E+00 5.00E‐02 1.00E‐01 1.50E‐01 2.00E‐01 2.50E‐01

OUTSIDE3

OUTSIDE2

OUTSIDE1

CB3

CB2

CB1

CONNECTED POROSITY OCCLUDED POROSITY

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Finite Element/Lattice Boltzmann Hybrid Method

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Raw Tomography Images

Binary Images

Medial Axis

Shortest Flow Path

Isolated Pore Space

Effective Permeability

Image Segmentation

Dijkstra’s Algorithm

FEM/LBM

Level Set Method

Recursive Function

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Homogenization of Effective Permeability Across scale

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LBMFEM

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Lattice Boltzmann/Finite Element Flow Transport Simulation

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• Statistical ensemble– Equation of state

– Balance of momentum

0f v ft

( ) 0pp F f

t m

• Macroscopic  Continuum– Balance of mass

– Balance of momentum

0vt

1( ) 0u u u pt

Kij1 Kij2

Kij3 Kij4

P1

P2

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Size of Representative Elementary Volume 

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Effective Permeabilities Inside and Outside Compaction Bands

K zz = 3.5e‐13 m2

K zz = 14.0e‐13 m2

Inside CB

Outside CB

FEM/LBM Scheme

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Conclusion

• The geometrical changes of micro‐structure due to the formation of compaction bands are examined.

• Level set, graph theory, lattice Boltzmann and finite element methods are used as tools in this study.

• Increased tortuosity, reduction of connected porosity are main factors that lead to permeability reduction of compaction band. 

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Page 28: Capturing Effective Permeabilities of Field Compaction bands

Acknowledgement

• Dr. Nicolas Leonir from Ecole des Ponts Paris Tech, Université Paris‐Est

• Dr. David Salac from Northwestern University• Prof. John Rudnicki from Northwestern University

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Page 29: Capturing Effective Permeabilities of Field Compaction bands

Thank you for your attention!

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