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Locally tuned Large Language Model (LLM) to empower digitalization of borehole logs for 3D stratigraphic modelling
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AI
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B
DOI：10.1016/j.tust.2026.108013.png)
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Abstract
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• A novel LLM-empowered method is proposed to automatically digitalize borehole logs for 3D stratigraphic modelling. • A locally deployed LLM, called StratumGPT, is developed from DeepSeek and fine-tuned using a regional dataset. • Performance of StratumGPT on borehole log digitalization and stratigraphic classification is compared with a general model. • The proposed method is illustrated using real-world database and locally deployed StratumGPT, with data confidentiality.
Keywords:
Geological text classification
Borehole logs
Artificial intelligence
Digitalization
Data confidentiality
Fine-tuning optimization
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