Heerema Marine Contractors has successfully slashed 2.5 days off the North Atlantic transit of its massive semi-submersible crane vessel Sleipnir using a data-driven voyage optimization pilot developed by French ocean intelligence firm Amphitrite. By combining five years of historical operational data with high-resolution oceanographic modeling, the platform reduced the sailing distance by 240 nautical miles and cut overall CO2 emissions by up to 18% without increasing fuel consumption.
Paris, France | July 13, 2026 – In a major milestone for offshore decarbonization, Heerema Marine Contractors has successfully slashed 2.5 days off the North Atlantic transit of its flagship semi-submersible crane vessel (SSCV), Sleipnir.
The operational breakthrough was achieved during a joint pilot project with French ocean intelligence firm Amphitrite. By deploying a data-driven, vessel-specific voyage optimization platform, the team reduced the transit distance by 240 nautical miles and cut overall CO2 emissions by up to 18%, all while maintaining higher average speeds without increasing fuel consumption.
The success of the pilot highlights a growing shift in the maritime sector toward precision routing. Rather than relying on generic weather forecasting, modern voyage planning is moving toward machine-learning models trained on a vessel’s unique hydrodynamic profile.
Technical Profile: The World’s Largest SSCV Meets Ocean AI
To understand the scale of these efficiency gains, it is necessary to look at the massive operational footprint of the Sleipnir and the high-resolution data model designed by Amphitrite:
| Parameter | SSCV Sleipnir (Heerema) | Voyage Optimization Platform (Amphitrite) |
| Asset Type | World’s Largest Semi-Submersible Crane Vessel | AI-Powered Ocean Intelligence Platform |
| Key Dimensions | 220m length / 102m beam | Vessel-specific machine learning model |
| Key Capabilities | Dual 10,000-tonne revolving cranes (20,000t lift capacity) | Blends satellite data, in-situ ocean sensors, and weather |
| Fuel System | Dual-fuel (LNG & Marine Gas Oil / MGO) | 5-year operational data training set supplied by Heerema |
| Primary Route | Rotterdam, Netherlands to New York, USA | Real-time English Channel, North Atlantic, and Gulf Stream tracking |
Navigating the Winter Atlantic: Tailwinds and the Gulf Stream
The Sleipnir was mobilizing from its home base in Rotterdam to New York to install a massive offshore wind substation. Navigating the North Atlantic during the harsh winter months presented a demanding proving ground for Amphitrite’s machine-learning model, with rapidly changing winds, waves, and strong ocean currents.
The optimization strategy was executed in three distinct tactical phases:
1. The Channel Departure (Tidal Synchronization)
Immediately after departing Rotterdam, the system calculated the exact sailing window required for the Sleipnir to ride favorable tidal currents through the English Channel, securing early fuel-efficiency gains.
2. The Westward Leg (Storm Avoidance)
As the vessel moved into open water, the model predicted a developing Atlantic storm. Instead of following a standard great-circle route, the platform routed the Sleipnir further north. This allowed the massive crane vessel to ride favorable tailwinds on the edge of the storm system while keeping the vessel and crew safe from extreme wave impact.
3. The Return Leg (Gulf Stream Optimization)
On the return voyage to Europe, the system recommended a counter-intuitive route. Rather than taking the shortest geographical path, the platform directed Sleipnir directly into the core of the Gulf Stream. By harnessing the favorable ocean currents, the vessel’s speed over ground surged to 14.6 knots, drastically cutting transit time despite covering a physically longer distance.
The Bunkering & Decarbonization Angle: SSCVs like the Sleipnir are among the most energy-intensive assets in the maritime sector. Because their transit phases demand high fuel consumption, achieving an 18% reduction in emissions represents a massive volume of saved fuel (whether LNG or Marine Gas Oil), directly improving the commercial viability of offshore wind mobilizations.
Fleet-Wide Ocean Intelligence
The partnership goes beyond a single transit. The pilot forms part of Heerema’s broader integration of Amphitrite’s Ocean Bulletin, which equips crews and shoreside operational teams with real-time oceanographic intelligence for voyage planning and offshore project preparation across its entire fleet.
“Improving fleet efficiency is fundamental to our decarbonization strategy,” said Alejandro Velez Isaza, Decarbonization Engineer at Heerema Marine Contractors. “Working with Amphitrite not only demonstrated the value of vessel-specific voyage optimization, but also gave us a better understanding of how Sleipnir behaves during transit. Those insights create further opportunities to optimize fuel consumption during one of the most energy-intensive phases of our operations.”
Thomas Joyce, Head of Business Development at Amphitrite, added “Offshore vessels such as Sleipnir operate in highly dynamic environments, where currents, waves, and weather can materially affect performance. By bringing these factors into routing decisions, we can help crews and operators make better-informed choices that reduce transit time, fuel consumption, and emissions.”
About Heerema Marine Contractors
Heerema Marine Contractors is a global expert in offshore energy solutions. With over 60 years of experience, the company specializes in the engineering, transport, installation, and removal of offshore structures for the global energy sector. Committed to creating sustainable value for its clients and stakeholders, Heerema manages the full scope of project execution, delivering safe, innovative, and efficient marine solutions. The contractor operates a premier fleet of heavy-lift assets, including the world’s largest semi-submersible crane vessel, Sleipnir, which boasts a record-breaking tandem lifting capacity of 20,000 metric tonnes.
About Amphitrite
Amphitrite is a French ocean intelligence company developing AI-powered solutions for voyage optimization, offshore planning, and maritime operations. Originating from research at CNRS and École Polytechnique, Amphitrite combines satellite data, in-situ observations, ocean modeling, and vessel-specific machine learning to help shipping and offshore operators improve efficiency, reduce fuel consumption, and support operational decision-making at sea.
Source: Heerema Marine | Amphitrite