Examples on how to use Subsurface Toolbox packages in workflows. Each example is located in a folder that contain a Jupyter Notebook and a subfolder with any resources/data if applicable.
This repository can best be used with the Pixi package manager:
With pixi installed, navigate to the folder of the cloned repository and run the following to install all dependencies required for the various examples:
pixi install
predict_sand_thickness
Demonstrates the use of GeoST
Example of using GeoST in combination with scikit-learn to use borehole data in conjunction with elevation, geological map and geomorphological map data to train a gradient boost regressor that is capable of predicting the total thickness of sand within the first 4 m below the surface in a complex area of channel belts and floodplains. To open the notebook in a browser:
pixi run thickness
offshore_seismic_edit
Demonstrates the use of DeltaSEIS
Example of using DeltaSeis for editing marine seismic data including coordinate transformation and fixes to the positinging data as well as performing heave corrections and tide corrections to the data. This greatly improves the information value of the data by a highly increase interpretability. To open the notebook in a browser:
pixi run seismic