3 major digitalization challenges and how petroleum companies overcome them
Organizations across industrial sectors are using simulations and comprehensive digital twins to improve throughput, sustainability and operational efficiency. But while some industries – such as automotive and aerospace – got a head start on these digitalization projects, the oil and gas sector has lagged.[1]
But with the new promises of artificial intelligence (AI), which also requires significant digitalization, crude oil producers are feeling the pressure to modernize.
This need for modernization, however, does not negate the digitalization challenges the oil and gas industry faced in the past. Fortunately, a recent episode of the Industry Forward Podcast discussed many of these issues and how to address them. Here is an abridged recap.
1. Oil price volatility disrupts digitalization investments
A digitalization challenge that is quite unique to the energy sector is perhaps the hardest to overcome: the ever-fluctuating price of oil as a commodity. Just within the last six years there have been catastrophic crashes and meteoric rises.
Take COVID, for example, in 2020 the crude oil futures prices momentarily went negative – yes, negative![2] Now, as of writing, in an environment of wars, geopolitical tensions, trade disputes, supply chain disruptions, tariffs and general uncertainty, the price is again just over $100 per barrel.[3]
Similar commodity price fluctuations occurred everywhere during the same time span, and often for the same reasons. But few, if any, had the same level of pricing whiplash as crude. And since oil is the primary product of the petroleum industry, its yo-yo pricing makes it hard to plan for the future. As a result, digitalization efforts do not always make the budget cuts when profits slump.
In the recent Industry Forward Podcast, Thiago Ribeiro, Global Head of Energy, Chemicals and Infrastructure at Siemens Digital Industry Software explained that when the price of oil is about $70 a barrel, oil companies tend to cut new technology investments. And when prices go back up, they do not always restart those projects.
The irony is that with digitalization technology the industry could better prepare for when oil prices drop. This is because leaders from the industry would be better able to use their data to predict downtime and supply line disruptions while optimizing throughput and uptime via simulations and comprehensive digital twins.
Other industries have already demonstrated the business value of these approaches. For example, PepsiCo has implemented AI-based comprehensive digital twins to optimize the operations of one of its Gatorade plants. Within three months the plant achieved a 20% increase in throughput and a 10 – 15% reduction in capital expenditures (CAPEX). Improvements like these can help organizations maintain profitability and operational efficiency during commodity downturns.
“So, when you have those high oil prices, this is the right moment to think about ‘what should I implement over here to think about the next time that the prices are going to be down, so I can extract the maximum value of the oil and gas that I’m extracting,’” Ribeiro agreed. “This is the power of digital transformation, to leverage the data that you have right now and be, on the average at least, … successful in any part of … the commodity cycle.”
2. Consistently changing regulations are a digitalization challenge
Another digitalization challenge affecting the oil and gas industry is that regulations have had significant and numerous changes within the past few decades. These regulations are important and necessary to ensure the safety of personnel, the public and the environment. But it is hard to optimize monitoring tools, simulations and comprehensive digital twins when the systems they observe are governed by ever shifting policies.
Ribeiro suggests this is one of many reasons the oil and gas industry is lagging other industries, like automotive and aerospace, from a digitalization perspective.[1] He does, however, highlight this as a positive – not a negative. He suggested that changing regulations created implementation uncertainty, but mature digital practices from other industries have reduced that risk.
Therefore, adopting digitalization technologies now is ideal as other industries have paved the way. The oil and gas sector can now follow suit using proven best practices, implementation strategies and technologies.
For example, the aerospace and automotive industries are no strangers to ever changing safety and environmental regulations. But competitive price points and the growing push towards smarter, better, faster and more sustainable cars and planes have forced those industries to jump headfirst into solving their digitalization challenges. As a result, there are a lot of opportunities for the oil and gas sector to benefit from cross-industry education.
Ribeiro said, “there are other industries that are much more advanced in terms of adopting high-tech digital technologies. And the good part of working for Siemens is that I get to interact with all these other industries as well, to pick up the best practices and bring that to our oil and gas industry.”
3. Incomplete data strategies mixed with complex lifecycles create a significant digitalization challenge
The oil and gas industry is very old. Old enough that many companies still operate decades-old systems that are purely analog. And the price of shutting down those systems, just to introduce sensors that monitor them, is a costly endeavor.
The industry is also exceptionally complex. It involves:
- Remote reservoirs
- Drilling below the sea
- Oil rigs
- Floating production storage and offloading (FPSO)
- Transportation
- Processing
On top of all that, there are numerous products made by this industry with various applications and customers including lubricants, petrochemicals, fuel and fertilizers.
The digitalization challenges affecting these subsystems, business segments, supply chains and processes are not easy to solve. And producing simulations and comprehensive digital twins that emulate these systems is even harder. “There are so many moving parts, that thinking about only your data is not enough,” Ribeiro said. “You need to have this holistic view, [to] capture data from every step of the process so we can identify the bottlenecks in the whole supply chain and act upon them.”
He added that fewer than one in five AI projects for large companies achieve the results expected. One that “creates a true competitive advantage that the companies are looking for.” It is a lack in data strategy that Ribeiro pegs as the reason for much of these failures.
To counteract this digitalization challenge, and improve the chances of success, Ribeiro says the key is to develop a data strategy as soon as possible. He added that a successful data strategy should be able to answer questions like:
- Where is my data?
- Is my data stored in different databases or legacy systems?
- Is any of my data siloed or within an isolated system?
- Is all my data stored digitally or is any of it strictly paper-based?
- Can all my data be communicated to a central system?
“So, accessibility is one of the first steps,” Ribeiro adds. “And the second one is to be able to integrate that data into what we call a data fabric, connecting all the gaps and all the data points to make sure that the models are going to be able to capture exactly what I want when I want it. That is the only way to go.”
For more on how to overcome digitalization challenges, listen to the podcast: Energy sectors’ digitalization is a must in an AI world.
[1] Rewired and running ahead: Digital and AI leaders are leaving the rest behind, January 12, 2024, | Article https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/rewired-and-running-ahead-digital-and-ai-leaders-are-leaving-the-rest-behind
[2] Crude Oil Futures Prices Turn Negative, Congressional Research Service, https://www.congress.gov/crs_external_products/IN/PDF/IN11354/IN11354.1.pdf, IN11354
[3] TradingView, “CL1! WTI Crude Oil Futures Chart (100.22, −1.51%),” TradingView, https://www.tradingview.com/chart/?symbol=NYMEX%3ACL1%21 (accessed October 27, 2026).
