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Cutting emissions with artificial intelligence

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Innovation & digitalisation

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“Part of the solution to the energy transition and the fight against climate change are huge quantities of computer code. That’s my area of expertise, and it’s my way of contributing,” says Olav Landstad.

Artificial Intelligence (AI) will undoubtedly be a major part of the future, and as project manager for AI at Equinor, Olav Landstad has already seen the potential of AI and started achieving concrete results. Four years ago, however, when he joined us, he hadn’t foreseen how crucial this technology would become in the energy transition.

On the screen before him at his office in Fornebu, pages of code scroll by. It might look like a computer program from the 1990s, but in reality, it’s quite futuristic.

“I would probably admit to being a bit of a nerd,” laughs Olav.

Together with the rest of his team, he’s working on finding solutions for how Equinor can reduce CO₂ emissions from our oil and gas production using machine learning, a field within artificial intelligence. Although the technology is new to many, it’s something he has long been fascinated by.

“It’s almost a bit crazy how it has taken off recently, and how AI has become mainstream today. Nerds like me have long believed, perhaps even known, that this technology would be an important part of the future,” says Olav.

And he’s right. AI, digitalisation, and new technology are key focus areas for us in Equinor. For us, it’s about producing energy more efficiently and, not least, about reducing emissions. And Olav and his team are already hard at work on this.

“Machines have always fascinated me. How they work and how they solve problems. So perhaps it’s not so surprising that I ended up working with it,” says Olav.

Although he dreamed of becoming a football player and a cross-country skier, it was his interest in machines that led him to start engineering studies. There, he was able to delve into technology, including AI. It was also during his studies that he became interested in optimisation.

“Optimisation is about more than just solving the task. You have to solve the task in the best possible way. So, I thought that if I could get a job that combined optimisation and artificial intelligence, that would be the dream job!”

And when he started at Equinor after his degree, this dream became a reality — working in a focus group on AI and optimisation. But it wasn’t just the combination of his two favourite interests, along with a perfect route for his gravel bike, that made the job exciting. It was also the amount of data.

“AI needs data, and the more data, the more you can achieve. Equinor has enormous quantities of data going back through over 50 years of operation. It’s a unique resource and a clear advantage when trying new things with AI,” says Olav. He continues:

“What’s more, I was very motivated by the fact that the energy sector will undergo significant changes in the coming years, which require us to think differently.”

A lot has happened in the four years Olav has worked for us. Artificial intelligence has gone from being nerdy to something everyone is talking about. Furthermore, our energy transition plan was launched in 2022 and now permeates our entire company. Broad efforts are underway to develop and adopt technologies that can support the transition plan.

“I feel there is a broad understanding that technology and innovation will be crucial to succeeding with the energy transition, and that this is something we are genuinely committed to. It’s very motivating,” says Olav.

Together with his team, Olav is now looking at how AI can be used to operate Equinor’s plants in more efficient ways, with lower carbon emissions and better profitability. Among other things, they’re working on optimising the supply of power from the world’s largest floating offshore wind farm, Hywind Tampen, which supplies electricity to the Snorre and Gullfaks platforms in the area. The interplay between wind and weather and the platforms’ own power production from gas turbines is now being optimised.

“We aim to complete an AI model for optimising our power consumption soon. What we have done is to train artificial intelligence, using historical data from the operation of our facilities. The model will utilise this knowledge to identify areas where we can cut consumption, with the goal being to cut several hundred thousand tonnes of greenhouse gas emissions,” says Olav, enthusiastically.

“It’s fun to be able to say that part of the solution to the challenges the world faces consists of lines of computer code – and that some lines of code can have such a significant impact,” says Olav.

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