Lithology prediction app

This web app tries to predict a rocks protolith from major element geochemistry, using an algorithm trained on over half a million labelled global geochemical data. When you input your major element data, the model will try to predict if your sample is either igneous or sedimentary.

The rock will then be classified into a lithology based on the protolith prediction, using either the TAS igneous classification (Middlemost, 1994) or the SandClass sedimentary classification after Herron (1988).

The web app is live and available here.

This predictor is a trained balanced random forest model based on major element geochemistry. Because of the chemical similarity between some rock types (such as felsic igneous rocks and arkosic sediments) there will always be the potential for miss-classifications. The model performs better on some compositions than others. The classified lithology is also based on major element geochemistry and not mineralogy and is therefore subject to all the limitations associated with chemical classification of rocks, particularly sediments.

To asses the quality of the model please visit the GitHub repo and view the model_assessment notebook.

This predictor is a reformulation of the original work published by Hasterok et al 2019. Chemical identification of metamorphic protoliths using machine learning methods. Computers and Geosciences. 132, 56-68