Review of application natural language processing (NLP) in geotechnical engineering
Volume Title: ICASGE2025
Paper ID : 1083-ICASGE (R1)
Authors
Civil Engineering Department, College of engineering, king Saud University
Abstract
This review paper analyzes recent literature on applying Natural Language Processing (NLP) in geotechnical engineering. It focuses on seven key areas: automatic literature review, sentiment, risk analysis in project reports, processing borehole logs, geotechnical risk assessment, integration with Building Information Modeling (BIM), data preprocessing for machine learning, and parameter extraction for numerical simulations. The review explains the wide-ranging applications of NLP, including enhanced data analysis, automated reporting, improved risk management, and more efficient workflows. Through a systematic review of the recent work, the study underscores the transformative potential of NLP in addressing everyday challenges in the geotechnical domain. By emphasizing MLP's capacity to process and extract useful information from unstructured data, the article highlights an evolution in the field toward data-driven decision-making, which will reduce the need for manual analysis and expert judgment. The study highlights how NLP can assist in closing the gap between organized BIM and unstructured geotechnical data.
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