AI & Generative AI Now Standard in Oil & Gas Solutions

No technologies dominate headlines like AI, generative AI and machine learning (ML) these days. 

Now considered “table stakes,” or a minimum entry requirement, software vendors are embedding such tech in all manners of oil and gas solutions. AI can evaluate large datasets for patterns better than humans can. It can flag potential equipment failures for repair before damage occurs and can drive automated decision-making to improve oil production. And generative AI, which uses massive datasets to deliver information and answer questions, opens up even more possibilities for the industry.

Of course, implementing AI and generative AI solutions means companies will have to take into consideration the state of existing data and accept the fact that AI will change work in unexpected ways, experts said at recent events in Houston.

Brad Davis, CEO of RIOT SCADA, said during the AI in Oil & Gas conference in April that it’s helpful to think of ML as being similar to how humans learn to beat a video game level by incrementally improving as they replay the level. ML requires a huge amount of pristine data, he noted. It can be easy to taint that data, as in the example of Netflix profiles which run on ML.

“This is why my wife won’t let me on her Netflix account, because I screw up her algorithm,” he said.

Deep learning, he said, handles large-scale pattern recognition and can be useful for things like detecting leaks and flare emissions.

Generative AI Potential

When generative AI is used to enhance SCADA data, or the data related to controlling, monitoring and analyzing industrial equipment and processes, it can improve employee performance across the board, according to a joint Stanford University and MIT study published in 2023.

For example, a person comfortable working with data may have a productivity level of 80% compared to 60% for one who struggles with data and does not care to use a data dashboard, Davis said.

The 2023 study revealed that generative AI boosted by 34% the productivity of employees uncomfortable with data-driven environments to 94% productivity, while generative AI upped the productivity of employees already comfortable working with data from 80% to 91%.

That improvement happens by “taking data outside the realm of data and putting it in the realm of conversation,” he said.

In short, generative AI makes it possible to interact with data in a completely different way, Catalina Herrera, field chief development officer at Dataiku, said during the same event.

“We talk to data, ask questions of the data,” she said.

Generative AI can be used to increase general productivity and remove dull, menial tasks, Brent Railey, chief data and analytics officer at Chevron Phillips Chemical Co., said during the same event.

He urged companies to be strategic in how they adopt AI and generative AI technologies, not least because AI’s success hinges on the quality of the data it uses.

“Generative AI will uncover your data governance problems,” he said. “Trying to fix your data quality problems is like boiling the ocean.”

Given the importance of data quality, Alina Parast, senior vice president and CIO at ChampionX, said during the same event that no data is brought into the company’s enterprise data lake until “it’s clean and validated.”

Ben T. Wilson, director of products and solutions at Amazon Web Services (AWS), said during CERAWeek by S&P Global that AI loves complexity but the data it uses must be of high quality.

“AI is very much garbage in, garbage out. If you have high-quality data, in other words, accurate data, whether it’s IoT (Internet of Things) type data or maintenance data, then you’re going to get much better results from your AI,” Wilson said.

Although generative AI has massive potential, Wilson cautioned that the tech is still young.

“I don’t think I see anything that’s mature in generative AI yet. Generative AI is so new, it’s been around for 18 months. We can’t expect maturity in it,” he said.

Despite this fact, Bill Vass, AWS’ vice president of engineering, who also spoke at CERAWeek, said he sees a future where generative AI is as ubiquitous and helpful as spell check.

And in much of the same way that spell check has not put writers out of business, generative AI coding capabilities will not replace software engineers, he said. Amazon CodeWhisperer, for instance, handles the drudgery of writing software code, he said.

As a software engineer, Vass said, “the hard part is figuring out what you want to do. And once you’ve figured it out, it’s busy work to do the coding.”

Gino Hernandez, head of digital for ABB Energy Industries, said during CERAWeek that the company is launching a generative AI bot for diagnosing asset failure and repair using natural language.

“You’re able to ask the asset, ‘When was the last time you failed? When it failed last time, what did you do?’ And then most importantly, the operator can ask, ‘Well, how do I fix this?’” he said. “And it’s a game changer.”

Gen AI is also expected to boost software engineering productivity by 50%, resulting in cleaner code with better documentation and more cybersecurity, he said.

“We have hundreds of R&D engineers developing our software. If I could unlock 50% more capacity of that organization, that is huge,” he said.

Vivek Chidambaram, senior managing director at Accenture Strategy, urged business leaders to become familiar with AI, noting that while Canadian author Malcolm Gladwell popularized the idea that 10,000 hours of practice results in expertise, leaders need far less experience with AI to lead effectively.

“About 1% to 2% of that time is the minimum amount of time that you need to put in as a leader. Otherwise you’re simply not in the game. The same sort of thing has to apply to the rest of the organization,” he said during CERAWeek.

Chidambaram noted that throughout history, technology has destroyed some jobs and created others and suggested that AI will probably create jobs that at present “we can’t comprehend.”

Chase Lochmiller, Crusoe Energy Systems co-founder and CEO, is optimistic about AI’s effect.

“I definitely view it as more friend than foe. I think there’s a lot of talk around AI taking people’s jobs, but I’m sort of the opinion that AI can be a catalyst for the greatest job-creating event in the history of humanity,” he said during CERAWeek. “When we invented the tractor, it might have taken some farming jobs, but it freed up human capacity to go pursue other interests and higher leverage, more productive things for society.”

Capitalism will likely drive AI adoption.

“If you don’t adopt fast enough, your competitors will,” he said.

And the change is definitely coming. 

“We’re sort of facing … a Darwinian event for corporations in terms of the genie’s not going back in the bottle. We’ve broken through this level of productivity gains that people are able to get from AI, and it’s at a moment of rapid exponential increase in the development of this technology,” Lochmiller said.