Artificial Intelligence Is Revolutionizing Oil and Gas - Here's How

Artificial Intelligence Is Revolutionizing Oil and Gas - Here's How

For many years, I have been analyzing and projecting, trying to predict the scope of modern technology's effect on our industry. Nanotechnology has occupied my thoughts often, but now it's time to focus on Artificial Intelligence, whose full potential to boost performance in the oil and gas sector is only beginning to be understood. 

BP is one of the companies devoting more resources to investigating the possibilities of AI for oil and gas exploration and production. According to BP's top technology experts, oil and gas is following on the footsteps of the automotive industry, which has rapidly become dependent on AI for its development, as cars become more and more “intelligent.”

In the case of oil and gas, we have largely depended on human skills, such as visual perception and the ability to adapt to changing contexts. According to BP's Dan Walker and Paul Stone, AI can develop systems that combine humans` best skills with what computers do best, for example, large-scale data analysis.

The experts imagine a future with “sensors with connectivity everywhere, recording data as often as you want them to and constantly creating new datasets.” 

In this scenario, all operations would be optimized thanks to the readily available and rapidly analyzed data about key variables, such as seismic trends and flow rates.

AI can improve the efficiency and safety of well-drilling, and boost productivity. It can also “help us to improve equipment reliability and predict maintenance requirements of our facilities," according to BP's engineers.

As BP evaluates which AI prototypes can have the greatest impact on the industry, in order to design trials, many other oil and gas companies are trying to catch up. One thing is for certain, whoever is not working on AI computing right now, will certainly be left behind.

Economic research firm MKM Partners projects that Artificial Intelligence is “a major segment, with a potential $15 billion opportunity by 2025.” This estimate largely takes into account the applications of AI for the oil and gas industry.

Earlier this year, BP, Chevron, and the rest of the upstream market leaders attended a conference entitled “Machine Learning, Deep Learning & AI in Oil and Gas,” which was held in Houston. The aim of the gathering was to help companies become more productive by effectively using data, in order to thrive in the current low oil price market.

It is estimated that by 2020, 25 billion devices will be connected to the cloud. Oil and gas needs to rapidly adapt to an industrial landscape where everything is controlled by sensors connected to devices capable of analyzing data and making predictions much faster and more efficiently than humans. 

Automating processes can allow us to obtain results we have hitherto only dreamed of. At the same time, it can help reduce costs and improve overall efficiency.

When machines are doing all the data processing and using algorithms to predict possible outcomes, engineers have more time to be creative, to focus on tasks computers cannot, at least not yet, do better than humans. 

Strategically placed sensors can also improve safety for workers, and this does not mean that humans will no longer be needed to run operations, it just means that they will have to be really good at working and interacting with AI processes and devices.

Artificial Intelligence is no longer the future of oil and gas. It is its present, and it's looking very bright.


Image Wikimedia Commons. ATTRIBUTION: Image by Tej3478

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Attorney Jimmy Vallee is an energy Mergers & Acquisitions lawyer, oil and gas industry commentator, and frequent resource for media outlets including USA Today, U.S. News & World Report, Oil & Gas Monitor and others. His new book, Giant Shifts: Energy Trends Reshaping America’s Future, released in May, 2017 hit #1 in two Amazon categories the week of its launch. Connect with Jimmy at [hidden email]  “Noted Energy Futurist” – Mensa AG 2016


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