There are a lot of exciting conversations and events happening these days, with all sorts of topics floating around – finance, capital investment for energy projects, how to leverage CCS/CCUS to achieve decarbonisation goals, how to start a digital transformation journey, are we witnessing the best times of LNG? What’s the impact of AI in the industry – and what type of real-world applications exist? How can we harness the power of AI, and attract the best talent to help us get there?
Many thoughts, and many perspectives. Today, I’ll be sharing some of mine.
Oil demand is expected to peak by 2030 before entering a slow but steady decline. One study predicts that the ‘fossil slice of the primary energy pie shrinks… from 80% now to just below 50% in 2050.’ Looking at the recent upsurge in LNG investment for the short-term future to compensate for this shrinking slice and move the industry towards more carbon-neutral operations, it seems operators and investors agree. We also see a renewed spark of interest in nuclear and the potential it has to drive energy efficiency when implemented correctly and under strict regulations.
Many companies are looking for investment opportunities, taking an explore-exploit approach to find the most effective strategies for increasing the use of AI and AI-based technologies, whether in-house or vendor-supplied. Countries are showing, not just telling – most recently, Saudi Arabia’s sovereign wealth fund (or PIF – Public Investment Fund) announced that it is seeking to create a USD 40 billion pot to invest in AI.
At the same time, the investment community is actively searching for companies that are proving the effectiveness of AI elements incorporated into their business models. What sort of AI projects are the top drivers? Well, it’s hard to say, but both operators and investors are hungry to explore this avenue and sniff out strong use cases with proven value.
Regulatory pressure to move towards net-zero emissions will inspire further exploration of digital solutions that can accelerate more sustainable operations while helping to bridge a growing skills gap. In the bigger picture, the oil and gas industry is struggling to attract talent while at the same time dealing with a rapidly ageing workforce that will see more than 50% of the current United States energy industry workers retiring within the next 10 years. Digital technology provides a way for companies to attract and upskill a younger, less experienced workforce that is eager to innovate on cleaner energy solutions.
Companies have already started setting targets for decarbonisation, but many of these lack a strategy for how they’ll succeed in meeting these goals. Again, technology can help – like those supporting carbon capture not only for storage but also for enhanced oil recovery. Who will carry the cost of developing technology for this purpose? Long-standing energy majors have the capacity to fund internal innovation, but mid- and small-size players will increasingly need an upper edge to stay in the game. Commercialised CCS technology could help bridge this gap.
When we discuss digital twin solutions, many companies say that they already have something similar in place. We’re not sure what it will take to bring AI into existing infrastructure, but we know it’s a must-do. AI will drastically change how we operate our assets. From our perspective as a software provider specialising in an end-to-end digital performance model, the best way to get that upper edge is to put your data in context, make sure the quality is where it should be, and use it where necessary and as much as possible. This needs cooperation between us as providers and our customers. Together, we can figure out what your ideal solution needs to look like.
Do it for a specific use case; the same goes for other trending technologies, too. As an industry, we can’t afford to make the same mistakes we did with machine learning – an overabundance of one-off pilot projects that were never built for scale. Don’t pursue digitalisation as an R&D project on the outskirts of your organisation. Bring the right technology into the centre and make it the springboard for new ways of working. Industries like healthcare and finance are leading the way, applying Artificial Intelligence for real use cases including AI-powered diagnostics and implementing an AI-based fraud detection system, respectively.
It might seem like a premature statement, but that’s where the industry is heading. A digital twin can bring billions of data points to a single point of view, giving you the situational awareness you need. An AI-powered digital twin can do even more, bringing in autonomous decision-making support at a scale and speed that’s never been seen before. This is the level-up in performance and energy efficiency that companies will need to thrive, not survive in an increasingly complex energy landscape. If you’re not doing something to make AI part of your operations today, you’re already falling behind.
The energy industry needs AI, but AI also needs the energy industry. AI has an insatiable appetite for energy, and we already have an energy supply crunch. OpenAI CEO Sam Altman recently warned us about this during the Davos 2024 session ‘Technology in a Turbulent World’: “We do need way more energy in the world than we thought we needed before… We still don’t appreciate the energy needs of this technology.”
All the more reason to start thinking about where this energy will come from and how technology can help us balance the growing energy demand with the growing requirements for reliable—and increasingly renewable—energy sources.
