(H)EXASHRINK: MULTIRESOLUTION COMPRESSION OF LARGE...
Transcript of (H)EXASHRINK: MULTIRESOLUTION COMPRESSION OF LARGE...
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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
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Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
2 Tuesday, September 27, 2016
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Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
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Geosciences study Earth’s geological characteristics
Huge heterogeneous mass of information
Geosciences
Types of rocks and fluids
Geological structure
Fluid flow simulation
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Introduction Context of geosciences
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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.)
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Geometry
Properties
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Stratigraphic surface and faults 3D model
Associated properties
Introduction What are geosciences models composed of?
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Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
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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
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Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
8 Tuesday, September 27, 2016
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HexaShrink Visual objective
Resolution -4 Resolution -5 Resolution -6 Resolution -7
Resolution 0
Resolution -1 Resolution -2 Resolution -3
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Structured hexahedral meshes…
… having geometrical discontinuities (geological fault network)
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HexaShrink What does it compress?
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Each vertex is defined by its coordinate along pillar
A mesh of cell dimensions has vertices,
whose coordinates are regrouped within the ZCORN matrix
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HexaShrink What does it compress? (cont.)
],,[ kji NNN ]2,2,2[ kji NNN
Z
Z
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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
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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
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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
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HexaShrink Step-by-step description
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Where is the redundancy within ZCORN matrix?
ZCORN contains 8 times the same value at interior free-fault nodes
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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
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Where is the redundancy within ZCORN matrix?
ZCORN contains 4 times the same value at interior vertical fault nodes
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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
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At each node, TOP vertices have always the same coordinates
as their respective DOWN vertices
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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
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Detect the fault configuration at every node using the coordinates
of the DOWN vertices
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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
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Example
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HexaShrink Step-by-step description: fault segmentation
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Based on a fault prediction
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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
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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
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Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
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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
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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
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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
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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
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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
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Outline
• Introduction
• Contributions
• HexaShrink
• Results
• Conclusion and future works
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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
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Thank you for your attention
Questions might be asked at