Making every barrel count in a volatile commodity environment

The Strait of Hormuz crisis shows how vulnerable the supply chain is to geopolitics, making agility and resilience impossible to ignore, writes Nayef Bou Chaaya, vice president, Middle East, Turkey & Central Asia at AVEVA

The oil industry began the year determined to boost crude production to cover a looming global supply-demand gap. Yet on February 28, that challenge became far more acute than anyone could have predicted.

The onset of the US-Israel-Iran war and the ensuing Strait of Hormuz crisis has completely changed the mood inside the oil industry. The world is facing prolonged higher-for-longer oil prices where every barrel suddenly matters more, and every operational inefficiency starts eating directly into profits.

At the peak of the disruption, the market was dealing with the loss of around 12 million barrels per day of crude supply, according to Rystad Energy. That is roughly 11% of total global oil demand. On an annualized basis, it equates to more than four billion barrels of supply either trapped, delayed or prevented from reaching the market efficiently.

Oil prices had jumped from around USUS$80 per barrel before the conflict to above US$100. Some analysts project prices could still edge to $180 by the end of the year. That has created a rare profit window for producers outside the Middle East, who are trying to strike while the iron is hot and get as much as possible out of existing infrastructure while conditions remain favourable.

This is not just about drilling more wells

As time is of the essence – both for countries keen to get more supply and for oil majors who want to make the most of high prices – the focus is now on optimis

ing every drop.

Small improvements in uptime, throughput or refinery performance that might once have had limited commercial impact can now translate into millions of dollars in additional revenue. A compressor failure or unplanned shutdown that was once a routine maintenance headache is now enormously costly.

This is where predictive analytics can have an outsized impact, enabling producers to constantly monitor assets and catch problems before they escalate into equipment failure or shutdowns. The current geopolitical environment has only turbocharged this shift, accelerating the move towards industrial AI and integrated operational systems across the sector.

Rystad Energy estimates AI and digital technologies will create close to US$500 billion in cumulative value for exploration and production (E&P) companies between 2026 and 2030.

Not all crude is equal

Refiners are also dealing with another major challenge: crude availability has become much more unpredictable.

Refineries use blends and slates sourced from multiple regions, which all have different properties and refining characteristics. Texas crude behaves differently from Saudi crude. Saudi crude behaves differently from Abu Dhabi crude. Venezuelan crude behaves differently again.

In stable market conditions, those crude slates are relatively predictable. However, refiners are now forced to change their crude oil slate because certain crude streams are no longer accessible. This creates a much more complicated optimisation problem.

Historically, engineering teams would run a limited number of operational scenarios manually. Now industrial AI systems can run thousands of crude blend combinations simultaneously while incorporating crude prices, refined product prices, electricity costs, operational constraints and regional market demand – determining in near real-time exactly which combination will generate the highest profitability possible.

AI augments human strategy

Importantly, the industry is not treating AI as some magical black box replacing engineering expertise. Inside oil and gas, there is still a very strong understanding that AI is only as good as the underlying engineering models feeding it.

AI is extremely good at interpreting data, however, the actual engineering calculations still need to come from first-principles engineering models and thermodynamics.

I like to use a comparative aviation analogy. For example, let’s say passengers boarded a plane and someone announced that AI would be flying the entire flight. Most people would probably get off right away.

Yet, modern aviation already relies heavily on automation. Pilots still handle take-off, landing, direction, speed and oversight while automated systems manage most of the journey in between. Industrial AI is evolving in a similar manner.

Human operators still define objectives, constraints and desired outcomes while AI handles huge amounts of analytical work and scenario modelling faster than humans can manually. This practice matters in a conservative industry where operational mistakes carry enormous financial and safety consequences.

Counting the cost

Production accounting systems are also becoming strategically more important because relatively small discrepancies in incoming or outgoing shipments can seriously affect margins when oil prices are high. If a company purchases one million barrels but only receives 990,000, the financial implications suddenly become much more significant.

In sum, what this all means is that the market is increasingly rewarding operational integration as much as production scale.

While longer term, the industry will continue investing in energy diversification, right now the challenge is more immediate: keeping the world moving during one of the most volatile commodity environments in decades – and making every barrel count.

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