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Most oil platforms in the world operate at only 77% of their potential, and McKinsey has just calculated that artificial intelligence alone can cut costs in half and increase value by 30% in just one year.

Written by Douglas Avila
Published on 12/04/2026 at 17:32
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McKinsey report reveals that the efficiency of offshore oil platforms is only 77%, with global losses of 10 million barrels per day and $200 billion in wasted revenue — and that analytics with artificial intelligence can reverse this scenario in just 12 months

The efficiency of offshore oil platforms worldwide is far below what it should be. According to benchmarks from McKinsey published in the report “Why oil and gas companies must act on analytics,” authored by consultants Anders Brun, Monica Trench, and Thijs Vermaat, the typical offshore platform operates at only 77% of its maximum production capacity. Globally, this 23% difference represents about 10 million barrels of oil per day that are not being produced.

In financial terms, the impact is devastating. The lost revenue amounts to $200 billion per year worldwide. However, McKinsey points out that the rigorous use of advanced analytics and artificial intelligence can increase the Net Present Value (NPV) of operations by up to 30% and cut unit operational costs in half in just one year. Therefore, the technology already exists — what is lacking is large-scale adoption.

A pilot in the North Sea brutally exposed the problem of offshore oil platform efficiency

Semi-submersible platform in the North Sea where McKinsey tested analytics for offshore oil platform efficiency

To validate its numbers, McKinsey conducted a pilot on a mature semi-submersible platform in the North Sea. This installation operated with approximately 100 wells and produced about 80,000 barrels of oil per day. Advanced analytics identified operational bottlenecks and recommended prescriptive actions to achieve optimal production conditions.

The most revealing result came from the analysis of the teams. The production difference between the best and worst control room teams exceeded 5%. In another asset adjusted for operational conditions, this variation reached 12%. Thus, on a platform producing 80,000 barrels/day, a 12% difference represents nearly 10,000 barrels lost daily — not due to technical failure, but due to suboptimal human decisions.

  • Tested platform: mature semi-submersible, North Sea, ~100 wells
  • Production: 80,000 barrels of oil per day
  • Variation between teams: 5% to 12% difference in production
  • Cause: human operational decisions, not equipment failure

How artificial intelligence transforms offshore oil platform efficiency into real numbers

Control room with analytics and AI dashboards for offshore oil platform efficiency

The solution involves three technological fronts that already exist and work. Firstly, prescriptive analytics identify optimal operating conditions and recommend real-time adjustments. Additionally, predictive maintenance systems anticipate failures before they occur. Consequently, digital twins create virtual replicas of entire platforms to simulate scenarios.

The optimized operational model has already demonstrated a 25% reduction in maintenance hours for offshore assets. This way, teams are reallocated from repetitive tasks to priority activities, such as preventing unplanned shutdowns. Consequently, every hour of maintenance eliminated represents a direct gain in production and cost reduction.

Ahmed Hashmi, BP’s director of exploration and extraction technology, summarized the industry’s vision: “It’s not just about automating the platform, but about automating everything that comes before it.” Therefore, McKinsey projects that the rigorous use of these technologies can raise the NPV by 30% and cut unit operational costs by up to 50% in just 12 months.

The Gulf of Mexico leads the race for offshore oil platform efficiency in deep waters

In the Gulf of Mexico, McKinsey identified a potential of 2 million barrels per day in new deepwater projects by 2030, representing 20% of the global deepwater supply. Thus, the breakeven of projects in the Gulf is $2 to $3 per barrel lower than the global average, making the region highly competitive.

The adoption of predictive maintenance and remote operations in the Gulf of Mexico promises to further enhance this advantage. Additionally, technologies such as tie-backs — which connect new wells to existing platforms — allow for recovery of up to 70% via technology, without the need for new installations. Thus, the global trend of investing billions in technology for platforms intensifies each year.

Brazil needs to accelerate to avoid falling behind in the offshore efficiency race

Offshore worker using a tablet with predictive maintenance data for offshore oil platform efficiency

Brazil, with its production of 5.3 million barrels per day and strong presence in deep waters in the pre-salt, has much to gain from adopting these technologies. McKinsey projects a growth in demand for floating rigs in the country of 6% per year between 2019 and 2027. Therefore, every percentage point of efficiency recovered in Brazilian offshore drilling operations can represent billions of reais in added value.

If Brazilian platforms also operate close to the global benchmark of 77%, the improvement margin with AI would be equivalent to thousands of extra barrels per day without drilling a single new well. However, specific data on the implementation of analytics in Petrobras operations is not available in McKinsey’s public reports.

Still, the scenario is clear: operators that do not adopt artificial intelligence and advanced analytics in the coming years risk losing competitiveness in a market where every barrel counts. On the other hand, those that invest first will have a decisive advantage in costs and productivity — and the clock is already ticking.

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Douglas Avila

I've been working with technology for over 13 years with a single goal: helping companies grow by using the right technology. I write about artificial intelligence and innovation applied to the energy sector — translating complex technology into practical decisions for those in the middle of the business.

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