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Project FORCE ML Competition 2020

General

Country:

Australia

Location:

Offshore, Ichthys

Projection:

Universal Transverse Mercator

Projection system:

WGS84, UTM, Zone 51S

Central meridian:

123º East

Scale factor at central merdidian:

0.9996

Latitude of origin:

0º N

False northing:

10000000 m

False easting:

500000 m

Data summary:

OpendTect project with 3D Seismic Data. For prediction of trained models only.

OpendTect license information:

License key protected parts of OpendTect (OpendTect Pro and the commercial plugins) can be used on this data set without license keys because the software does not check for license key when it runs on this data set.

Supported for OpendTect:

6.6 and onwards

Size:

7.9 GB (uncompressed), 7.3 GB (download)

License:

Creative Commons 4.0

Download:

Contributors

Competition organiser:

FORCE

Original seismic:

Geoscience Australia

Value added products:

dGB Earth Sciences created the OpendTect project.

FORCE

Geoscience Australia

dGB Earth Sciences created the OpendTect project.

FORCE ML Competition 2020 seismic example

Survey Parameters

Survey type:

Only 3D

Inline range and step:

1001, 3400, 1

Crossline range and step:

2040, 3040, 1

Z range and step:

1.5, 5.5, 0.004 Time

Inline bin size (m/line):

18.75

Crossline bin size (m/line):

12.5

Area (sq km):

563.05

Available Data

3D Seismic:

  • ichthys_3D_seismic_for_fault_competition

More Info

FORCE Machine Learning Competition 2020 information

Here you will find more information about the FORCE Machine Learning Competition 2020.

We show you how to get a headstart with OpendTect 6.6, and how to make and train your own models by using the OpendTect 6.6 Machine Learning plugin:

- the dgbes.com FORCE Machine Learning Competition 2020 webpage

- the Machine Learning Webinar videos on YouTube

- download and install OpendTect 6.6 beta

- Develop your own models documentation

- Machine Learning Workflow: Wells Log-Log Prediction (Density)

- Machine Learning Workflow: Wells Log-Log Prediction (Porosity)

- Machine Learning Workflow: Wells Lithology Classification

- Machine Learning Workflow: Seismic bodies (Supervised 3D)

- Machine Learning Workflow: Seismic Unet 3D Fault Predictor

- Machine Learning Workflow: 3D Seismic + Wells Rock Property Prediction

- Machine Learning Workflow: Seismic Image to Image Faults Prediction

Ichthys Seismic data set: Browse Basin

The Ichthys Seismic dataset is provided courtesy of Geoscience Australia and is available under CC BY 4.0 license.

It contains a very well-expressed polygonal fault system in the overburden, locally intersected by larger planar faults in the eastern part of the survey and a deeper faulted section in the Jurassic that is clearly dominated by more diffuse but human mappable fault zones.

The focus of the competition is to use a synthetic model trained algorithm that accurately maps the deeper and the shallow faulting and approximates human interpretation.

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