04 20180419 blug voxelmodellingworkshop tiles challenges and pitfalls in... · robin de mol, guy de...

Challenges and pitfalls in building a marine voxel model

Lars Kint, Nathan Terseleer, Dries Van den Eynde , Vera R.M. Van Lancker

Vasilis Hademenos, Tine Missiaen,Robin De Mol, Guy De Tré

Jan Stafleu, Sytze van Heteren

3D‐models and voxel‐models in geologyBLUG workshop

Brussels, 19th April 2018

TILES

Started in 1976 (~ 30 x 103 m³/yr >106 m³/yr in the ‘90s)

‐ Extent and sustainability of the resource?‐ How to define concessions and legal limits to extraction?‐ Effects of extraction on the system?‐ Evolution of the seabed in areas of extraction?

4D Decision Support System

Sand exploited for the industry and beach nourishmentextraction areasmonitoring areas

The TILES project3D Voxel Model Concl. & PerspectivesIrregular voxelsDataIntroduction

Transnational and Integrated Long-term marine Exploitation StrategiesMarine aggregate extraction

3D Voxel Model Concl. & PerspectivesIrregular voxelsDataIntroduction

Lars Kint Vasilis Hademenos Robin De Mol

3D Voxel Model Concl. & PerspectivesIntroduction Irregular voxelsData

Data structure3D Voxel Model Concl. & PerspectivesIntroduction Irregular voxelsData

+ Data Uncertainty

Data pool3D Voxel Model Concl. & PerspectivesIntroduction Irregular voxelsData

Gilson Heritage (1898‐1939)

1930s grab samples

1974: PhD André Bastin

1976, 1984, 1986: 1st vibro coring campaigns

1984: British Telecom International

1985: Wartel and Vansieleghem

1986, 1988, 1989: 1st very deep cores

2006: Quest4D-project

2002 Hanson Aggregates Belgium NV

+ many more …

1960s re‐analyzed 1930s grab samples

2010: NEMO

2004‐now: Wind farm data BELWIND, C‐POWER, NOBELWINDUpcoming Data RENTEL, NORTHER

1984, 1989: British Geological Survey

1977‐2009: Databank Ondergrond Vlaanderen

1991, 1993: MAST I en II-project


Lithological descriptionsand numerical values

2861 boreholes or samples 15680 subsamples

Database

Grain size distributionsand percentages







Database

Depth [m] #2018< 1 9181 - 5 1058≥ 5 445

Depth [m] #2018< 1 3231 - 5 447≥ 5 93






Database

Year #2018< 1970 3971970-2000 1577≥ 2000 414

Year #2018< 1970 2481970-2000 440≥ 2000 211

Harmonisation & Standardisation3D Voxel Model Concl. & PerspectivesIntroduction Irregular voxelsData

Normal text on the slide

EU‐FP7 Geo‐Seas for geological and geophysical data

http://www.geoseas.eu/

Wentworth (1922) & Folk (1954)

EU‐FP7 SeaDataNet for oceanographic data

https://www.seadatanet.org/

Libraries and Common Vocabularies

Metadata3D Voxel Model Concl. & PerspectivesIntroduction Irregular voxelsData

Acronym SeaDataNetC16 SeaDataNet sea areas

C17 ICES Platform Codes

C32 International Standards Organisation countries

GS3 Geo-Seas adjusted Folk sediment lithology classes

GS4 Geo-Seas geological sample colour

L05 SeaDataNet device categories

L11 SeaDataNet depth measurement reference planes

L22 SeaVoX Device Catalogue

Acronym Name + DescriptionCDI The Common Data Index provides online unified access to harmonized datasets managed by the distributed data centers, using a shopping

basket mechanism. High detailed insight in geographical coverage and other metadata features are given by partners data holdings. It is thekey to data discovery and data delivery.User manual and instructions are present for updating EDMED, EDMERP, EDIOS, EDMO and CSR (see below) .

CSR Cruise Summary Reports is merely the reporting on cruises of field experiments at sea, a first level inventory of measurements and collectedsamples. Traditionally submitted by the Chief Scientist’s to his/her National Oceanographic Data Centre (NODC) not later than two weeks afterthe cruise.

EDIOS: The European Directory of the Ocean Observing Systems, an information system for marine observing and monitoring programmes, stationsand platforms (including moored buoys, coastal installations, seabed stations, drifting buoys, sampling stations, etc.). Routine, repeated andconsistent long-term observations of the marine environmental conditions are made available for us in (near) real-time, including information onlocation, measured parameters, data availability, responsible institutes and links to data-holding agencies.

EDMED The European Directory of Marine Environmental Data refers to marine data sets and collections held within European research laboratories.Range of disciplines: meteorology; physical, chemical and biological oceanography; sedimentology; marine biology and fisheries; environmentalquality; coastal and estuarine studies; marine geology and geophysics; etc. Range of data format: digital databases or files, analogue records,paper charts, hard-copy tabulations, photographs and videos, geological samples, biological specimens etc.

EDMERP The European Directory of Marine Environmental Research Projects covers simply marine research projects described as metadatafactsheets with their most relevant aspects, to support users in identifying interesting research activities and connecting them to involvedresearch managers and organizations across Europe. Range of disciplines: meteorology; physical, chemical and biological oceanography;sedimentology; marine biology and fisheries; environmental quality; coastal and estuarine studies; marine geology and geophysics; etc.

EDMO The European Directory of Marine Organizations provides up-to-date addresses and activity profiles of data holding centers, governmentaland private organizations, monitoring agencies and research institutes involving oceanographic and marine research, data management andacquisition activities.

Countries Sea areas Service (platforms) Ship

Metadata3D Voxel Model Concl. & PerspectivesIntroduction Irregular voxelsData

Gear, sampling and analyzing method

Gear Acronym

Box core BC

Geodoff core (steek) GD

Geodoff core straight flush (spuit) GS

Geodoff core contra flush (MK II spuit) MK

Grab sample G

Gravity core V

Hammer core (steek) AS

Trilflip core DW

Vibro core SG

Zenkovitch core (steek) H, HT, T, AS

Country Acronym

Belgium BEL

France FRA

Great‐Britain GBR

Boring + ICES statistical rectangle + Number E.g., BR010001Boring + Country + Number E.g., BBEL0001Year + Gear + Number E.g., 68G001…

Coordinate system

Nomenclature

Reference depth

Main and secondary lithology3D Voxel Model Concl. & PerspectivesIntroduction Irregular voxelsData

Folk (1954)

Percentages Grain size distributions

Wentworth (1922)

Ranges Mean Median (D50) Percentiles

Shell , Organic and Glauconite contentPatina & ColourChrono‐ & Lithostratigraphy

Other geological data

Uncertainty3D Voxel Model Concl. & PerspectivesIntroduction Irregular voxelsData

Vintage• Vintage/Antiquity• Sediment Dynamics and Transport

Sampling• Device• Lithology

Concl. & PerspectivesIntroduction Irregular voxelsData 3D Voxel Model

Voxel : Spatially defined volume containing resource‐related informationWhy : Assign multiple values to a voxel and calculate volumes by specified queries based on them

Boreholes Geological layer models Voxel model

Multi-step approach going from collation and interpretation of borehole and seismic data to creation and assessment of layer and voxel models.


Building a marine voxel model

CoresSeismic profiles

Velocity model: time depth

Boundaries between geological units

Stratigraphical classification of each core sample

Holocene

Pleistocene

Tertiary


Data interpretation

Top Palaeogene

-6m to -70m

Top Pleistocene

-3m to -40m

Seafloor Bathymetry

0m to -48m

Ostend

Zeebrugge


Bounding surfaces

UPPER HOLOCENE

PLEISTOCENE

PALEOGENE

LOWER HOLOCENE

VOXEL SIZE 200 X 200 X 1 m4 LAYER VOXEL MODEL


Voxelization

ISATIS : Sequential Indicator Simulation Moving neighborhood 10 km x 10 km x 1 m Runs 100 iterations

Classification TNONumber Name Sand / Non‐

sand0 Other /unknown Not applicable

1 Not in use

2 Clay Non‐sand

3 Silt Non‐sand

4 Not in use

5 Fine sand Sand

6 Medium sand Sand

7 Coarse sand Sand

8 Gravel Sand

9 Not in use

10 Sand, grain sizeunknown

PROBABILITY HOLOCENE MEDIUM SANDPROBABILITY HOLOCENE FINE SAND


Interpolation

Medium sand

Coarse sand

Fine sand

Clay

Silt

‘Most likely’ lithological class derived from Soares using global proportions of each lithoclass in

each unit


ENTROPY AS A MEASURE OF

UNCERTAINTY

UNCERTAIN

CERTAIN


Uncertainty mapping


Bounding surfaces addition effects

200 X 200 X 1 m

100 X 100 X 0.5m


Model comparisons

Concl. & PerspectivesIntroduction Data 3D Voxel Model Irregular voxels

Traditional "regular grid" voxel model

Challenges:

• data is sparse and not uniformly distributed• different data sources combined in one model

might have a different resolution• how to deal with multiple data points that fall in

the same voxel?• how to deal with voxels that contain no data?• how to update the model when new data

becomes available in the future?

(1) Image source: https://en.wikipedia.org/wiki/File:Voxels.svg

(1)

How to choose the voxel size?


Octree-based data structure (simplified 2D example)

Start:

Bounding box"1 huge voxel"



Insert data

OK if voxel is empty



Insert data

If not empty:

split into smaller voxels



After 10 inserts


Visual exploration of the Hinderbanks

Color scale:

probability medium sand(0% - 50% - 100%)


Advantages

Supports (theoretically) infinite resolution

Seamlessly integrates different data sets into single model

Minimal loss of information

Can be incrementally updated with new data

Can generate differently optimized reusable voxel models


Introduction Data 3D Voxel Model Irregular voxels Concl. & Perspectives

Conclusions

Efficiently target user‐defined suitable areas for extraction

Estimate resource volume and quality(and help defining legal limits to concessions)

Easily identify areas with poor data coverage

Introduction Data 3D Voxel Model Irregular voxels Concl. & Perspectives

PerspectivesIntroduction Data 3D Voxel Model Irregular voxels Concl. & Perspectives

Use as input to a hydro‐sediment‐morpho model (4D model)

Build a resource decision support system (DSS)

TILES – Final ConferenceBelspo Research project

Plateosaurus‘Ben’

Marine sands as a precious resource‘A guided tour through the past, present and future’

What?

Friday, 1 June 2018When?

Museum of Natural SciencesVautierstr. 29 - 1000 Brussels (Belgium)

Where?

04 20180419 blug voxelmodellingworkshop tiles challenges and pitfalls in... · robin de mol, guy de...

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