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(H)EXASHRINK: MULTIRESOLUTION COMPRESSION OF LARGE STRUCTURED HEXAHEDRAL MESHES
WITH DISCONTINUITIES IN GEOSCIENCES
Jean-Luc Peyrot, Laurent Duval, Sébastien Schneider Frédéric Payan and Marc Antonini
Presented by Shuo Zheng
1 Tuesday, September 27, 2016
Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
2 Tuesday, September 27, 2016
Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
2 Tuesday, September 27, 2016
Geosciences study Earth’s geological characteristics
Huge heterogeneous mass of information
Geosciences
Types of rocks and fluids
Geological structure
Fluid flow simulation
3 Tuesday, September 27, 2016
Introduction Context of geosciences
Need of a numerical model that gathers information to analyze, process them, and finally make decisions
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Numerical model
Analysis
Prediction
Simulation
Decision
Introduction Context of geosciences (cont.)
Geometry
Properties
5 Tuesday, September 27, 2016
Stratigraphic surface and faults 3D model
Associated properties
Introduction What are geosciences models composed of?
Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
6 Tuesday, September 27, 2016
Contributions
Numerical models carry a huge amount of information – Inefficient management, processing, storage and transmission
– Especially with limited memory and bandwidth devices
Reduce the quantity of information, while maintaining coherency and valuable information
HexaShrink: Multiresolution compression to build a hierarchy of geometrical models (aka. meshes) of increasing resolutions
7 Tuesday, September 27, 2016
Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
8 Tuesday, September 27, 2016
9 Tuesday, September 27, 2016
HexaShrink Visual objective
Resolution -4 Resolution -5 Resolution -6 Resolution -7
Resolution 0
Resolution -1 Resolution -2 Resolution -3
Structured hexahedral meshes…
… having geometrical discontinuities (geological fault network)
10 Tuesday, September 27, 2016
HexaShrink What does it compress?
Each vertex is defined by its coordinate along pillar
A mesh of cell dimensions has vertices,
whose coordinates are regrouped within the ZCORN matrix
11 Tuesday, September 27, 2016
HexaShrink What does it compress? (cont.)
],,[ kji NNN ]2,2,2[ kji NNN
Z
Z
Within each group of contiguous coefficients at resolution , compute one
coefficient to represent/approximate the group at lower resolution
Detail coefficients are used during decompression to recover the original
group at resolution from the approximation coefficient
12 Tuesday, September 27, 2016
HexaShrink Principle of the ZCORN matrix compression
Analysis
Original group of 8 coefficients Approximation and detail coefficients
Synthesis
Approximation and detail coefficients Original group of 8 coefficients
L
L
1L
Compression as a three-stage process:
1. Removing the redundancy from the ZCORN matrix
2. Fault segmentation
3. Morphological transform: Multiresolution transform which preserves the discontinuities
13 Tuesday, September 27, 2016
HexaShrink Step-by-step description
Where is the redundancy within ZCORN matrix?
ZCORN contains 8 times the same value at interior free-fault nodes
14 Tuesday, September 27, 2016
HexaShrink Step-by-step description: remove redundancy
An interior free-fault node and its 8 surrounding cells
Splitting view of the node and its 8 vertices
Distance=0 between every 2 vertices
Z
Where is the redundancy within ZCORN matrix?
ZCORN contains 4 times the same value at interior vertical fault nodes
15 Tuesday, September 27, 2016
HexaShrink Step-by-step description: remove redundancy
An interior vertical fault node and its 8 surrounding cells
Splitting view of the node and its 8 vertices
Distance=0 only between up and down vertices
Z
At each node, TOP vertices have always the same coordinates
as their respective DOWN vertices
16 Tuesday, September 27, 2016
HexaShrink Step-by-step description: remove redundancy
BTL BTR
FTL FTR
BDL BDR
FDL FDR
TOP
ver
tice
s D
OW
N v
erti
ces
coordinates can be removed from ZCORN matrix
coordinates remain in the ZCORN matrix
Z
Z
Z
Detect the fault configuration at every node using the coordinates
of the DOWN vertices
17 Tuesday, September 27, 2016
HexaShrink Step-by-step description: fault segmentation
Free-fault node
Corner fault node Horizontal fault node
Vertical fault node
T-fault node Cross-fault node
Z
Example
18 Tuesday, September 27, 2016
HexaShrink Step-by-step description: fault segmentation
Based on a fault prediction
19 Tuesday, September 27, 2016
HexaShrink Step-by-step description: morphological transform
Fau
lt c
on
figu
rati
on
at
Res
. 0 OR
OR OR
OR OR
OR OR
OR
OR
OR
O
R
OR
O
R
OR
O
R
OR
OR
OR O
R O
R
Predicted fault configuration at Res. -1 and Res. -2
20 Tuesday, September 27, 2016
HexaShrink Step-by-step description: morphological transform
A B
E F
C D
G H
I J
M N
K L
O P
Group G + Predicted fault conf. at Res. l
A B
E F
C D
G H
I J
M N
K L
O P
BDL coefs. within group G at Res. l
BDL coefs. Morphological transform on
BDL coefs
A B
E F
C D
G H
I J
M N
K L
O P
1 0
0 1
C: approximation coef. because at
extremities
Distance w.r.t. fault Predicted fault at Res. l
ZCORN can be split into 4 submatrices which contain only the coordinate
of 1 vertex per node among the four ones BDL, FDL, BDR and FDR
Morphological transform is applied separately on each of these
4 submatrices
2D example of morphological transform applied on submatrice BDL
Cell borders Nodes Faults
Z
Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
21 Tuesday, September 27, 2016
22 Tuesday, September 27, 2016
Results Visual multiresolution meshes
Original free-fault mesh (Resolution 0)
[80,45,26]
Resolution -1 [40,22,13]
Resolution -2 [20,11,6]
Resolution -3 [10,5,3]
Resolution -4 [5,2,1]
Mesh without faults
23 Tuesday, September 27, 2016
Results Visual multiresolution meshes (cont.)
Original faulted mesh (Resolution 0) [149,189,16]
Resolution -1 [74,94,8]
Resolution -2 [37,47,4]
Resolution -3 [18,23,2]
Resolution -4 [9,11,1]
Mesh with faults…
…preserved across resolutions
24 Tuesday, September 27, 2016
Results Visual multiresolution meshes (cont.)
Original faulted mesh (Resolution 0) [100,100,21]
Resolution -1 [50,50,10]
Resolution -2 [25,25,5]
Resolution -3 [12,12,2]
Resolution -4 [6,6,1]
Mesh with faults
25 Tuesday, September 27, 2016
Results Comparison with JPEG2000 3D*
Original top layer surface
Resolution -2 obtained with JPEG2000 3D Resolution -2 obtained with HexaShrink
*JPEG2000 3D: ITU-T T.809, “JPEG2000 image coding system: Extensions for three-dimensional data” May 2011, ISO/IEC 15444-10:2011
26 Tuesday, September 27, 2016
Results Comparison with JPEG2000 3D* (cont.)
*JPEG2000 3D: ITU-T T.809, “JPEG2000 image coding system: Extensions for three-dimensional data” May 2011, ISO/IEC 15444-10:2011
Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
27 Tuesday, September 27, 2016
Conclusion and future works
HexaShrink:
Geometry is well-preserved over the resolutions New lossless progressive compression technique Handles large structured hexahedral meshes having
discontinuities Can be used to speed-up the simulation time (upscaling
for instance) Extend this technique to unstructured or even hybrid volume meshes Compression of properties Article is being written at Computational Geosciences Journal
28 Tuesday, September 27, 2016
29 Tuesday, September 27, 2016
Thank you for your attention
Questions might be asked at