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Felicity Bradstock

Felicity Bradstock

Felicity Bradstock is a freelance writer specialising in Energy and Finance. She has a Master’s in International Development from the University of Birmingham, UK.

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How AI Is Breathing New Life Into Oil And Gas Operations

  • AI is projected to significantly grow in the oil and gas sector between 2022 and 2027, with 92% of companies planning investments.
  • Leading energy companies, including Shell, BP, and ExxonMobil, are pioneering AI applications, enhancing everything from drilling processes to safety measures.
  • Despite the transformative potential of AI, its adoption in the energy sector lags behind its pace of development in other industries.
AI

The use of artificial intelligence (AI) and other digital technologies in the oil and gas industry has increased dramatically in recent years and is expected to continue growing over the coming decades. Modernisation and digitalisation were already starting to be welcomed by the oil and gas industry, but the Covid-19 pandemic restrictions drove an acceleration in the adoption of a range of new technologies, which has since continued.

AI is now viewed as a game changer for the oil and gas industry, used to reduce operational costs, improve sustainability, and speed up processes. According to market research carried out by Mordor Intelligence, the use of AI in the oil and gas market is expected to increase at a CAGR of 10.81 percent between 2022 and 2027. And a recent Ernst & Young survey showed that 92 percent of oil and gas companies around the globe are investing in AI or have plans to do so within the next 5 years. 

Despite the accelerated adoption of AI technologies, the rate at which companies are adopting AI remains slower than the speed at which it's being developed and applied in other sectors. Kumar Lakshmipathi, principal solutions architect for Amazon Web Services, explained “In the energy sector, we’re not seeing adoption as we should… Compared to other industries, this is not what we see.” 

AI could be applied in a variety of ways in the oil and gas industry, such as to monitor and improve safety, increase operational performance, or provide insights and forecasts. The use of AI could significantly improve supply chain management, with the potential to reduce errors by between 20 and 50 percent. This is seen as increasingly important following the supply chain disruptions during and following the Covid pandemic. The delays in the manufacturing and delivery of energy components created a significant backlog in the industry, with many operations experiencing cost and time increases. Using AI to manage supply chain systems could help to alleviate these pressures in the future. 

New AI technologies can also dramatically help to improve safety standards, enhancing company ESG practices and potentially preventing disasters. Better monitoring of oil and gas platforms could help to improve worker safety, further mitigating the chance of health and safety issues. This technology can also be used for the monitoring of pipelines and other infrastructure to prevent leaks and oil spills. This could help companies save millions in losses as well as avoid major damage to the environment. 

To date, some of the leading energy companies in AI adoption include Shell, BP, and ExxonMobil. Shell has introduced AI technologies across its whole oil and gas supply chain, with more than 160 active projects by May this year. It has used these technologies to reduce gas extraction costs and automate drilling systems to help drill operators better understand the environment. It has also introduced the Shell AI Residency Programme to give data scientists and AI engineers experience with a range of AI projects at Shell. The oil major is also using AI technology in its renewable energy operations, to predict the varying demand for EV charging stations through the day to supply power appropriately.  

Meanwhile, ExxonMobil is using AI to assess the viability of a region for drilling. In its recent Guyana operations, the firm used closed-loop automation, which controls the drilling process without human intervention. The use of this technology has allowed rig workers to shift their attention to other important tasks, helping to reduce the need for engineers to carry out repetitive tasks that can be managed by machines. Exxon is also using AI in its Permian basin operations in the U.S. to improve efficiency. 

And the British oil major BP has partnered with Microsoft since 2017 to implement its Azure cloud solutions to improve drilling processes, leading to a reduction in drilling time. BP has since partnered with Bluware to use deep learning to enhance subsurface data interpretation by eliminating manual, time-consuming interpretation of seismic data.

The firm also recently invested $5 million in the start-up Belmont Technology’s Series A financing to improve the company’s AI and digital capabilities in its Upstream business. This follows a wide range of other investments in AI companies to enhance decision-making. BP has also trialled the AI-driven Spot robot at one of its refineries, using the robot to gather data, detect abnormalities and emissions, and take workers out of potentially hazardous situations. 

Innovative digital technologies, such as AI, are becoming vital to the running of oil and gas operations, used to reduce times and costs as well as to enhance worker and environmental safety. More companies, big and small, are now open to adopting AI technology, particularly following the challenges faced during the Covid pandemic. However, the rollout of the most up-to-date AI technology is still lacking in the energy sector, with significant room for improvement. 

By Felicity Bradstock for Oilprice.com

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Leave a comment
  • DoRight Deikins on August 08 2023 said:
    «In its recent Guyana operations, the firm used closed-loop automation, which controls the drilling process without human intervention.» Wow, closed-loop automation has been around since the 50s (that's the 1950s). Long before AI was even a thing, OK even before computers were a thing (OK, they weren't much more than research tools for universities and fast calculators for banks/accounting departments).

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