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LLMs assessed for geothermal energy modeling and decision support

Researchers are exploring the use of large language models (LLMs) like ChatGPT, Gemini, and Claude to aid in the development and modeling of geothermal well arrays. A new approach utilizes Google's NotebookLM to generate quantitative geothermal benchmarks, which are crucial for evaluating rapidly advancing LLM capabilities. The study investigates the potential and limitations of LLMs in synthesizing geothermal data, improving numerical models, and facilitating auto-parallelization for applications like digital twins, aiming to transform decision-support in the geothermal sector. AI

IMPACT LLMs could accelerate the development of geothermal energy technologies by improving data analysis and modeling capabilities.

RANK_REASON The cluster contains an academic paper detailing novel research and methodology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLMs assessed for geothermal energy modeling and decision support

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The cluster contains an academic paper detailing novel research and methodology. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Edwin Ouko, Emmanuel Lujan, Alan Edelman, Robert Metcalfe ·

    Decision-Support and Modeling with Large Language Models for Geothermal Well Arrays

    arXiv:2608.22068v1 Announce Type: new Abstract: Geothermal well arrays, which organize multiple geothermal wells into carefully planned geometric configurations, provide opportunities to enhance energy production capacity and increase fault tolerance. The development and adoption…