AI/machine learning

Oil, Gas Companies Deploy AI in the Fight To Reduce Carbon Emissions

For oil and gas companies to remain in existence in the second half of the 21st century, they must find ways to dramatically reduce, if not eliminate, their output of carbon dioxide and other greenhouse gases. Artificial intelligence technology could provide one tool to help the energy industry accomplish that staggeringly difficult goal.

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Credit: Igor Borisenko/Getty Images/iStockphoto.

For oil and gas companies to remain in existence in the second half of the 21st century, they must find ways to dramatically reduce, if not totally eliminate, their output of carbon dioxide and other greenhouse gases. Artificial intelligence (AI) technology could provide one tool to help the energy industry accomplish that staggeringly difficult goal.

According to an August 2020 report by the National Oceanic and Atmospheric Administration on the impacts of atmospheric carbon dioxide on climate change, CO2 levels—mostly caused by the burning of fossil fuels—rose to about 410 parts per million in 2019, the highest level seen on earth in more than 3 million years.

Oil and gas companies, especially the big international ones, are under increasing pressure to reduce their carbon footprint in accordance with the Paris Agreement’s goal to limit global warming to well below 2°C, preferably to 1.5°C, compared to preindustrial levels. Most major companies have set carbon-reduction targets. BP and Royal Dutch Shell both have vowed to achieve net zero carbon emissions by 2050.

ExxonMobil has focused on more modest short-term climate goals, such as reducing greenhouse-gas intensity of its upstream operations by 15–20% compared with 2016 levels by 2025.

AI technology, which has the ability to harness large volumes of data from divergent sources to come up with solutions to problems, has the potential to not only increase global productivity but also lower overall emissions of carbon and other potent greenhouse gases, according to a recent report published by Microsoft in association with PWC.

“Using AI for environmental applications has the potential to boost global GDP by 3.1–4.4% while also reducing global greenhouse gas emissions by around 1.5–4.0% by 2030,” the report states.

“These AI technologies can help the industry optimize energy management by using digital twins to better monitor and distribute energy resources and provide predictive forecasting,” said Darryl Willis, corporate vice president of Energy at Microsoft. A digital twin is a digital representation of a physical piece of equipment or an entire system.

“They can also be used to create visualize simulations, improve decision-making, reduce operational costs, and manage and extend the life cycle of physical assets,” he said.

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