Cameron Keplinger
Date: 10/14/2024
ExxonMobil
For this case study, I chose to write about ExxonMobil, a major player in the oil and gas industry, due to my involvement in this sector as an oilfield pipe seller. Observing how a company like ExxonMobil leverages A.I. is particularly fascinating to me.
ExxonMobil, considered a "super major" in the industry, earned $12.1 billion in 2023. It was founded in 1999 from the merger of Exxon and Mobil and is currently led by CEO Darren Woods. With a market capitalization of over $500 billion, ExxonMobil has the resources to explore new ventures and technologies such as A.I., which could give them an edge over competitors like Shell, BP, and Chevron.
As artificial intelligence becomes more prevalent, large corporations like ExxonMobil have begun to implement A.I. to improve efficiency and reduce costs. Below are a few key examples of A.I. applications at ExxonMobil:
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Automated Drilling in Guyana
ExxonMobil has implemented an automated drilling system offshore in Guyana, which uses A.I. to maximize penetration while minimizing errors. This system enhances safety for operators and reduces repetitive tasks. It also allows for real-time decision making during drilling operations, adjusting parameters like pressure, torque, and rotation speed on the fly. -
Digital Twins
ExxonMobil also uses "digital twin" technology, which creates a virtual replica of real-world drilling environments. This technology allows ExxonMobil to simulate drilling in a controlled environment, helping predict potential outcomes. By using simulations, they can test various scenarios without needing to operate directly in the field. -
Data Gathering in the Permian Basin
Collaborating with Microsoft, ExxonMobil leverages machine learning to collect and analyze data in the Permian Basin. Their goal is to create a fully autonomous, closed-loop system that maximizes efficiency. -
Machine Learning in Refineries
ExxonMobil is also applying machine learning to create an "ideal operating environment" in its refineries. This initiative is expected to increase energy efficiency and reduce emissions, much like how GPS helps a trucker navigate traffic.
Although ExxonMobil’s A.I. initiatives are promising, their full impact is yet to be realized. CEO Darren Woods has noted that while A.I. is overhyped, it won’t solve every problem—highlighting the importance of human oversight in operations.
"AI is currently overhyped and won't solve all problems."
— Darren Woods, CEO of ExxonMobil
In my opinion, the future of A.I. in oil and gas, particularly at ExxonMobil, looks bright. As the company continues to explore production optimization and predictive maintenance, their operations will likely become more efficient and intelligent, satisfying shareholders and employees alike.
If I were to suggest a new A.I. technology for ExxonMobil, it would be a demand prediction system. This system could analyze data points such as world events, seasonal trends, and historical patterns to accurately forecast future demand for oil and gas. ExxonMobil could then scale its operations up or down based on these insights, making it more agile in an ever-changing market.
ExxonMobil is leveraging A.I. and machine learning to answer the fundamental question: "How can we provide value to shareholders?" Through innovations such as data collection and automated drilling, the company is on track to increase efficiency and profitability. As A.I. continues to evolve, ExxonMobil—and the oil and gas industry as a whole—will likely adopt even more advanced technologies to stay competitive in the future.
- ExxonMobil Corporate
- Artificial Intelligence at ExxonMobil
- ExxonMobil and Geothermal Energy
- A.I. Source: Gemini by Google / Chat GPT