Abstract: The invention is a data processing method and system for assisting geoscientists in identifying geological Lithostratigraphic analogues from unstructured text using theory-guided machine learning. The data processing system makes the necessary calculations to detect geological Lithostratigraphic entities and appropriate entity relations, accounting for space (local geography) and time (local succession) when using word associations to determine similarity. The system computes the reliability of that score, incorporating user feedback into the learned model. In particular, the data processing system operates on any digital unstructured text derived from academic literature, company reports, web pages and other sources. Similarity between the associations of words to geological Lithostratigraphic entities can be used to suggest global analogues to communities such as petroleum geoscientists in order to reduce petroleum exploration risk and improve field development decisions.