AI-Driven Oil Markets: Where Paper Prices Meet Reality
When Russia invaded Ukraine in February 2022, Western countries sanctioned Russian oil, causing prices to surge to almost $140 per barrel. However, most of that oil was merely re-routed through India and refined for sale to Europe.
In contrast, the US attack on Iran in February had a more significant impact on global oil supply, with 20 million bpd (barrels per day) removed from the market. Despite this disruption, oil prices did not skyrocket, hovering between $80 and $100 per barrel after an initial drop.
One reason for this stability was the release of strategic oil reserves by various countries, including the US, China, and others. The world absorbed over 1 billion barrels of lost supply since the Iran war began, but now faces the risk of future price spikes as these reserves are depleted.
The 'paper' price of oil, represented by WTI (West Texas Intermediate) futures prices, is not a reflection of actual market prices. In reality, buyers have been paying anywhere from $30 to $60 per barrel more than published prices for physical delivery of oil, with marked-up prices particularly high for refined products like gasoline and diesel.
Major energy companies, investment banks, sovereign wealth funds, and governments rely on advanced algorithms to analyze geopolitical risks and forecast oil prices. These AI systems can process millions of variables simultaneously, including satellite images of oil tankers, strategic reserves, weather patterns, military tensions, cyberattacks, interest-rate fluctuations, and social media sentiment.
The rapid-fire announcements from President Trump about deals with Iran have also been analyzed by these algorithms, creating a self-reinforcing cycle that can drive stock markets up or down. This 'mob psychology' has been automated, leading to higher real-world energy costs than reported.