Solutions for Some of
Our Largest Partners

British Petroleum Quote Logo

In six months we went from concept to proven.
- Brian Pugh, Chief Innovation Officer

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Unsynchronized well arrival increases downtime

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AI-driven system-level queuing model

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Automated well arrival synchronization


Impact: Increased profitability and reduced environmental impact

• 20% production uplift

• 22% reduction in operating costs

• 74% reduction in methane emissions


Halliburton Quote Logo

We view the relationship with Kelvin as another step toward bringing industry-leading intelligence to the market.
- Michael Segura, Vice President of Production Enhancement at Halliburton

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Insight

Uneven pump management increase service cost

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Real time load imbalance detection

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Automated load redistribution


Impact: Market leading capabilities deployed in under 90 days

• Multi-year R&D pipeline translated into production ready solution

• $10M reduction in annual operating expenses


Schneider Electric Logo

Using Kelvin, our development teams can transform their ideas into production-ready algorithms faster than ever before.
- Helenio Gilabert, Senior Director, Digital Transformation Edge Solutions at Schneider

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Unplanned pump failures causing downtime

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AI image classification of pump cycle cards

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Automated equipment failure prediction


Impact: Field scale, edge ML applications drive increased profitability

• 40% reduction in energy consumption

• 15% production uplift

• Increased operator efficiency


Santos Quote Logo

Kelvin Intelligent Control Software enabled easy system optimization, application deployment and ongoing model management while delivering productivity gains.
- Glenn Lydyard, Technology Operations (Digital)

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Reliance on manual asset recovery decreasing asset performance

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Automatic detection of failure events

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Autonomous recovery from failure events


Impact: Reduced downtime and production uplift

• 8% production uplift

• 95% reduction in manual operator interventions


Shell Logo

In a short amount of time we were able to prove the concept that operators and 'smart' software can work together to build reports and track key data, a bit step forward to our vision of reporting by exception only.
- Vittorio Spoldi, P. Eng, Well Performance Engineer, Shell

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Insight

Reliance on manual workflows created poor data quality and low operator efficiency

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ML event detection on streaming data

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Real-time event driven workflow automation


Impact: Increased data quality and operator efficiency

• Idea to execution completed in under 30 days

• Generalized ML model deployed across all active jobs without re-training

• Seamless OT-IT integration