Wed, Feb 12 2025 12 February, 2025

Eni launches supercomputer amid tech race in oil, gas industry

The supercomputer is the first to be deployed in Europe and is ranked fifth in a list of the world’s top 500 supercomputers.

An Eni supercomputer (Photo: Eni)

Italian energy major Eni has launched a new supercomputer amid a race to deploy AI capabilities among oil and gas companies.

The company said the resource will be primarily deployed for energy transition projects. At the same time, it sees the tool as a way to enhance its oil and gas production by aiding reserves discovery and driving efficiency.

The over 100 million-euro HPC6 supercomputing system was launched just before Christmas at Eni’s Green Data Centre located in Ferrera Erbognone in northern Italy.

The supercomputer has a computational power of up to 606 petaflop per second, or over 600 quadrillion mathematical operations per second.

The system, which was ranked fifth in a list of the world’s top 500 supercomputers, is the first to be deployed in Europe, the world’s first industrial-use supercomputer and the only non-U.S. system among the top 5 in the world, the company said.

The launch of HPC6 marks a “pivotal moment in Eni’s decarbonisation strategy, where technology and innovation differentiate Eni’s approach and deliver value creation through the development of new businesses related to the energy transition,” it said.

“The combination of HPC6 computational power and the internal know-how will help Eni to accelerate various energy transition projects, including material discovery for CO2 capture, plasma management in different tokamak configurations with reference to fusion energy, and improve the efficiency of wind farms, solar cells and batteries,” Eni told Gas Outlook.

A tokamak is a machine that produces thermonuclear fusion power.

HPC6 will also “offer the possibility to leverage its computational power for tuning Large Language Models (LLM) tailored to the energy sector, which would also support the energy transition,” it said.

LLMs are AI systems capable of understanding and generating human language.

Eni’s announcement comes as oil and gas companies ramp up efforts to deploy supercomputing to support their operations.

Shell partnered with AI solutions provider SparkCognition to improve subsurface imaging and exploration, in a bid to boost success rates and production.

Meanwhile, BP invested £5 million in U.S.-based Belmont Technology’s geoscience platform in order to deploy digital capabilities in its upstream business.

TotalEnergies CEO, Patrick Pouyanne described AI technology as a “revolution” for the industry, which will help develop oil and gas projects.

The company teamed up with technology company SLB to develop subsurface digital solutions to reduce the carbon intensity of hydrocarbon production and also develop CO2 storage.

“Advanced supercomputing capabilities, like Eni’s HPC6, and AI deployment have the potential to transform oil and gas operations by improving efficiency, accuracy, and decision-making,” Michel Ingenbleek, a Dutch-based technology and energy expert, told Gas Outlook.

This can help boost “operational efficiency” through tools like digital twins “exploration and reservoir analysis” which “can have a significant financial impact to get the size and characteristics of a reservoir better displayed and thus drive investment decisions, and on clean energy research.”

This includes “high computation on nuclear fusion modelling but also CCS and methane leakage modelling,” he said.

Against that backdrop, Eni’s decision to develop its own computation capabilities rather than relying on third party providers signals a different strategy by the Italian major.

While “most O&G producers use 3rd party providers of supercomputing” these resources might not be geared specifically towards the energy sector, and rely on pre-ordered time slots, he noted.

On the other hand, having proprietary computing resources might turn out to be “smart investments” and “become an income stream on its own” for companies like Eni.

Fossil fuels boost?

While AI deployment can support decarbonisation objectives, its use to optimise oil and gas operations raises the question of whether this might hinder — instead of promote — the energy transition by boosting fossil fuels production.

“Ultimately pricing for energy” including taxation on fossil fuels and subsidies to renewables “dictates which direction we go at what pace,” he said.

“While advanced computing resources can contribute positively to sustainability, they also risk prolonging reliance on fossil fuels by enabling more efficient exploration and production, thus possibly resulting in increased fossil fuel supply. “

“That being said, again, if the financial incentive leans towards renewables I imagine they would use the resources to gain an edge versus the competitors.”

“The debate around AI” deployment in the energy sector “will affect all supply chains and business sectors,” Massimo Rocca, board member of the European Energy Information Sharing and Analysis Centre, told Gas Outlook.

‘Within the electricity sector there are many promising projects for optimising grid development and grid maintenance,” he said.

“Solutions based on machine learning have already been deployed for some time” however “models focused on assessing the impact of adverse events” on assets “are being perfected,” as well as predictive models focused on managing interruptions of service, he said.

In that respect, AI can support the energy transition rather than hinder it, he said.

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