Method and System for Generating Geological Lithostratigraphic Analogues using Theory-Guided Machine Learning from Unstructured Text

A computer implemented process for suggesting space-time aware geological Lithostratigraphic analogues from text using theory-guided machine learning, the system comprising:

• receiving into memory:
• sentences of text, geographical lexicons, negation/negative terms, geological time lexicons and Natural Language Processing (NLP) rules,
• processing the data in the computer memory with a processor to detect geological Lithostratigraphic entity names,
• processing the data in the computer memory with a processor to compute similarity between Lithostratigraphic entities through word associations;
• and
• outputting the Lithostratigraphic entity-entity similarity (through cosine similarity or other method), by:
• applying a filter around the detected geological Lithostratigraphic entities, the filter having a dynamic width defined by a window length comprising the first mention of a Lithostratigraphic entity and a subsequent mention of a different Lithostratigraphic entity, word associations amalgamated where subsumed entity relations are inferred, removing geographical terms, the filter output providing an input to a learned statistical model weighting (from high to low) nouns, adjectives and verbs, from which Lithostratigraphic entity-entity similarity can be determined.