Digitalisation and collaboration have dominated the oil and gas industry technology conversation for many years.
But the transition to cleaner energy has given these well-worn topics new urgency as operators and the services sector shift strategies to meet their own ambitious emissions-reduction targets — and the expectations of a broader public.
Digital technologies underpin the industry’s greenhouse gas-reduction strategies, from predictive analytics and artificial intelligence to make operations more efficient — and therefore less polluting — to the subsurface modelling and analysis involved in safely storing carbon dioxide underground.
“Reducing our own Scope 1 emissions is something we clearly have to continue to do and to get better at,” says Lee Hodder, vice president of upstream digital transformation at Shell, kicking off a discussion at Upstream's Technologies for Energy Transformation event.
Shell, which aims to reach an emissions intensity of zero by 2050, is among a handful of international operators that have set aggressive emissions-reduction targets.
“We are also getting better as an industry in actually quantifying our emissions,” he says, adding: “Data is going to be king on this.”
Dan Brennan, vice president of BakerHughesC3.ai, the joint venture of oilfield services giant Baker Hughes and artificial intelligence software company C3.ai, agrees.
“As we think about the opportunity of digital in the context of how we decarbonise and support the energy transition... there is a clear role for artificial intelligence and machine learning in helping make oil and gas more efficient,” he says.
Such efforts rely on a degree of what Valentina Riggins, senior vice president of customer relations at Worley, calls “data readiness”, in contrast to the upstream industry’s historic lack of co-ordination among its multiple formats for storing data.
“You need to have the right data in the right place at the right frequency in the right combination, so that you can create a real-time, AI-based model and actually be predictive,” Riggins says.
Efficiency, not emissions reduction, may have been the industry's primary motivation for better data management, but efficiency itself can have significant environmental benefits. And digital technologies are essential to making the big leaps necessary to meet tougher climate goals.
“If we really want to go towards greener energy, renewables, better managing our upstream assets and having less emissions, should we consider — in production spaces, for example — only traditional production data? Or should we include the maintenance data in that space and create standards accordingly? These are the debates that really should be held right across the industry,” she says.
Managing data and making it more broadly available has meant putting some meaningful action behind the collaboration talk, with some notable industry alliances and research initiatives to show for it.
(To view a full recording of the event, click here.)
Earlier this year, Shell, C3.ai, Baker Hughes and Microsoft launched the Open AI Energy Initiative, which is initially focusing on reliability and predictive maintenance for energy assets.
The Open Subsurface Data Universe project, created in 2018, is another example. The initiative brings software providers, operators and technology companies together to work on a common platform designed to eliminate traditional data silos and bring more efficiency to exploration and development workflows.
Before he became chief executive at Aker Solutions last August, Kjetel Digre held executive positions at Aker BP and Equinor, the latter where he was director of the Johan Sverdrup project.
“The issue we faced was really two-fold,” he says of data management at the Norwegian companies and in the wider industry.
“To collaborate around data, we first had to tidy up the foundation, because in the basement of it all we had this chaos of data, which we really had to orchestrate in a different way and contextualise.
"That is a starting point, and it happens with the operators and the end users in oil and gas.”
The second challenge was what Digre calls “this sort of philosophical question” around making data available for collaboration — “rather than have everything closed, and then see if we can open these small doors, we actually took a choice... that everything should be open, and then we selectively should just close a few [doors].”
To build applications for both the execution and operation of projects, Digre says, “we also need to make sure that competing on finding digital solutions doesn’t create all these dependencies, like sort of vertical lock-ins, which are outdated before they are put in operation".
The energy transition appears to be taking collaboration well beyond traditional joint industry projects and partnerships.
“Since we are talking about climate change and net zero, this becomes everyone’s problem," Riggins says.
Of data management, she adds: “Digital technology really brings the value at scale when it is applied at scale. So, if we are to really harvest artificial intelligence capability, we need to supply the data at scale as well. We cannot limit ourselves to just one operator’s data, only in [one] scenario.”
The oil price plunge early in the Covid-19 pandemic probably accelerated the trend for greater co-operation already under way.
“Over the last 12 months — maybe it was the environment we were in, but there was a natural reach-out to try to understand what partners are doing, what other companies are doing, a lot of questions about ‘how do you see this’, and really then trying to learn about where the touch points could be,” says Stan Knez, senior vice president, process technology at Technip Energies.
Industry belt-tightening in response to oil-price fluctuations is less a factor driving collaboration than the long-term transformation of the energy business, however.
“I am not seeing the cost piece as being the driver for it,” says Hodder. “I am actually seeing a change in attitude and almost a kind of humbleness in saying, ‘we can’t do this ourselves’.”