Integrated Geophysical, Geochemical, Geotechnical and Machine-Learning Dataset for Clay-Mineral Characterisation in the Western Niger Delta, Nigeria

This dataset supports the study “Integrated Geophysical, Geochemical, Geotechnical and Machine-Learning Characterisation of Ferruginous Kaolinite and Sand-Dominated Sediments in the Western Niger Delta, Nigeria.” The dataset comprises electrical resistivity and induced polarization measurements, X-ray fluorescence geochemical data, iron speciation data, Atterberg limits, and the traverse-level machine-learning dataset used for clay-mineral/material classification and liquid-limit prediction. Data were collected from 17 traverses across Ugborikoko, Uwheru and Otor-Ogor in the Western Niger Delta, Nigeria. The package also contains Python scripts used for the machine-learning analyses and supporting documentation, including a data dictionary and reproducibility information.