Illustration: S&P Global Energy CERA.
Narrowing the gap between question and decision point
That’s what the role AI is playing when it comes to getting intelligence to the market quickly and trustworthily. Here, Paul Webber explains how his company is achieving that with CERA Titan, the company’s new platform for upstream market data and insights
“I recently put a photo of myself on LinkedIn when I was on a rig in the North Sea,” says Paul Webber, VP, Head of Global Upstream Product & Content, S&P Global Energy CERA, when we meet on Teams. Paul is leading the product management team in Upstream at S&P Global Energy CERA, and in that role, he oversees developments on the CERA Titan Platform, which serves as the interface between customers and S&P Global Energy’s database and analytical capability.
“I took that photo in the year 1996,” he continues. “Four years later in my career, I consulted a spreadsheet of exploration and appraisal wells drilled across the North Sea as part of my new market intelligence job. Now, twenty-six years later, we still go back to the same data, and the wells that have obviously been drilled since. The value of that data is still there, but the way we consult it has changed a lot.”
AI has recently formed a critical role in the way E&P data is being used in the intelligence space. “We are seeing AI as part of the core of our digital offering, and have therefore built our CERA Titan platform around that, rather than use it as a bolt-on to what we already had before AI came to the fore,” says Paul.
Solving problems
“Our solution goes beyond a large language model that is just summarising large datasets into a summary,” Paul continues. “Let’s not use AI to find problems. We want to start with the problem and let AI solve it.”
“And what is that problem?” I ask.
“The problem,” replies Paul, “is that individuals working at operators and any other companies interested in E&P data still spend too much time finding the right data that answers the questions they have. That’s the problem that we want to solve with the AI-assisted way of querying our data. We want to narrow the gap between the question and the decision point.”
“We all know that once you make a call on where you’d like to focus your research on, let’s say a certain country, the next thing that usually happens is a search for data across different sources. We aim to take that away, and provide a service that finds the relevant data straight away, such that users can much more effectively focus on what they are really after and not go into the data rabbit holes that we all know exist along the way.”
And Paul is also adamant that his solution goes beyond a simple data query.
“The other thing we want to do is to provide a more proactive supporting mechanism of the search workflow,” he says. “For instance, if I’m looking at a certain area for legacy data, and there is a licensing round currently ongoing in that specific country, our software will suggest to the user if he or she wants to put the currently open blocks on a map. There is no need for the user to actively be aware that there is a licensing round happening at that time. That’s what AI is for.”
“The third item we strive towards,” Paul continues, “is the ability of the platform to summarise data into an executive summary. You know situations where you’re being asked to pull together one slide for an executive presentation within a few hours. These stressful occasions happen all the time in a fast-paced environment that comes with working in a competitive industry. Our platform has the ability to do exactly that. It’s not always a hefty report people are after, it may more often be an orderly summary that can be consumed quickly.”
Fast-paced technology and trust
In contrast to what is sometimes said about the relatively slow pace with which the industry is adopting new technology, Paul sees that the E&P industry has been at the forefront of new technology for a long time.
“That’s not only through the recent advance in AI,” he says, “it’s across the spectrum. Look at what drilling technology has gone through with the evolution in bit technology and managed pressure drilling, in addition to how seismic acquisition and processing technology has evolved over the past twenty years.”
This touches on an important topic that is often overlooked in the discussion about fast-paced technology, and in this case, the advance of the use of AI in the workplace. And that is trust.
“We want our customers to trust the data they will now have at their fingertips in a very short time,” says Paul. “The only way to build that trust is to have a stringent workflow of checks and a well-maintained structured database for AI to tap into. When that is in order, people will trust the analyses put out by an AI-assisted system.”
“In other words, we need the guardrails to be in place,” reiterates Paul, “especially when the deterministic responses that people require from us – i.e. how many discoveries were made in Brazil in 2024? – are returned within seconds.”
It’s the people behind it
But having the prompt answers to a question presented in a format determined by the end-user is in fact only the result of what can represent decades of intelligence-gathering work.
“At the very beginning are the analysts who do their day-to-day jobs across many parts of the world to build and maintain the database that we rely on for our data queries,” says Paul. “And it’s these analysts who are still the backbone of what CERA Titan is.”
“Because at the end of the day, especially when it comes to an analysis of newly obtained data – for instance the results of a newly drilled well – it is the context that our analysts provide that is still a key ingredient of our offering.”
“So yes,” Paul concludes, “AI narrows the gap between question and decision point, but equally, the work we do also still relies on having boots on the ground in all the areas we report on.”
To learn more about CERA Titan click here.
