As soon as this is done we can smoothly move and rotate our random line in any direction we want. In the video we show a dataset from the Australian North West Shelf.įirst we have pre-loaded the data into memory. Movie style QC your data with a random line in OpendTect The slider shows the input seismic flattened at Base Zechstein, the input pointsets, and the Machine Learning classification result in the mid Tubbergen. All classes were tracked from starting positions selected at seismic-to-well calibrated gamma-ray logs 6 from the well in the forefront and 4 from the well in the background.
We used the Thalweg tracker to create 10 pointsets with 10.000 locations each to serve as labeled class positions for a Convolutional Neural Network. Finding clean, thick, and extensive sands is commercially interesting as the Tubbergen has potential as geothermal energy source. The Late Carboniferous Tubbergen consists of alternating sandstones and claystones / shales and rare coal beds with variable extent and thickness. In this case we visualized patterns in the Tubbergen Formation in eastern Netherlands. This week we show another example of OpendTect’s Thalweg tracker / Machine Learning workflow. OpendTect v5 please refer to the v5-stable branchįor details please see the documentation or click one of the links below.A few weeks ago, we posted a new workflow for seismic facies classification.OpendTect v6.4 please refer to the 6.4 branch.OpendTect v6.6 please refer to the 6.6 branch.If you are interested in the latest source code for: All code is provided under the terms of the GNU General Public License Version 3.Īs of 24-June-2022 code development in the master branch is for OpendTect 6.8. This is the source code for a collection of plugins for the open source seismic interpretation system OpendTect.
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