SPE News

SPE, Aramco Americas, and i2k Connect Explore an AI-Powered Language Model for the Energy Industry

The three companies signed a Memorandum of Understanding to explore the development of an energy-specific large language model.

MOU signing in the Aramco booth at ATCE with representatives from SPE, Aramco Americas, and i2K Connect Inc. From left, Med Kamal, SPE 2023 President; Nabeel Al Afaleg, Aramco Americas President and CEO; and Reid Smith, i2k Connect Inc. CEO and cofounder.

At the recent SPE Annual Technical Conference and Exhibition, a Memorandum of Understanding (MOU) was signed by SPE, Aramco Americas, and Houston-based software company i2k Connect Inc. to explore the development of a large language model (LLM) that is energy-industry specific.

The goal is to advance SPE’s current artificial intelligence (AI)-driven research portal, which includes technical literature from OnePetro, to help energy professionals with research, identify industry experts, and solve E&P problems others may have previously encountered.

OnePetro is considered the definitive resource on upstream oil and gas with contributions from 22 publishing partners and access to more than 314,000 items. SPE manages the multisociety library and contributes approximately 50% of the technical content.

ChatGPT and other similar natural language processing tools mimic human conversations to assist people with questions and tasks. The unique aspect of this MOU is to explore the development of an AI tool that can answer technical questions specific to the energy industry.

“SPE is pleased to begin discussions with Aramco Americas and i2k Connect Inc. on a potential energy-specific large language model. Our collective aim is for the research portal to not only provide conversational answers to questions, like ChatGPT does, but also reference the original sources so the answer can be validated,” said 2023 SPE President Med Kamal.

An important first step is to create a roadmap for using SPE technical content to accelerate the creation of an LLM, allowing professionals to connect with data that can be extracted, analyzed, and summarized to reduce time and lead to insightful knowledge for decision-making.