Work

EnrgLLM: A Deep Dive into the Development, Training, and Deployment of a Customized Oil and Gas Language Model

Year: 2026

Type: conference-paper

Source: IPTC Summit on AI for the Energy Industry

DOI: 10.2523/iptc-25216-ms

Authors: J. Eckroth, J. Boden, K. Nasser, E. Rafie, R. M. Al-Harbi, O. Houzé, S. Seaton, S. Gipson

Institutions: Connect, Saudi Aramco (United States), Saudi Aramco (Saudi Arabia), Society of Petroleum Engineers

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

OpenAlex ID: W7123338929

FWCI:

Cites: 1

Cited by:

Related to: 10