Johan Sverdrup: The Digital Flagship
- Paal Frode Larsen (Equinor) | Tor Tønnessen (Equinor) | Florian Schuchert (Equinor) | Ahmed Khamassi (Equinor) | Haithem Jarraya (Equinor) | Henriette Dorthea Aarrestad (Equinor) | Vegard Imsland (Equinor) | Vibeke Lossius (Equinor)
- Document ID
- Offshore Technology Conference
- Offshore Technology Conference, 4-7 May, Houston, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2020. Offshore Technology Conference
- 6.3 Safety, 3.2.7 Lifecycle Management and Planning, 3.2 Well Operations and Optimization, 7.6.6 Artificial Intelligence, 3 Production and Well Operations
- Johan Sverdup, digital, megaproject, technology
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- 115 since 2007
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The sheer size of the 2.7-billion-barrel field and expected operations of more than 50 years, make Johan Sverdrup an exciting place to develop the solutions of the future. As such, the Johan Sverdrup field development has been called the digital flagship for the operator. Being a ‘flagship’ means Johan Sverdrup is not only meant to be a vehicle for digital innovation to improve safety, value-creation and carbon efficiency for the field itself, but the field development is also meant to drive digital solutions and ways of working that have the potential to be scaled-up for the benefit of the operator as a whole.
This paper starts by setting out the main digital focus areas for the Johan Sverdrup development, but drills down on exploring the areas where Johan Sverdrup is demonstrating real and tangible impacts already today. Examples include efforts to mature technology for automatic production optimization, a number of new pipe and seabed technology solutions (including fiber-optic PRM, fiber-optic monitoring of wells), and the step-wise development of a digital twin for Johan Sverdrup that will gives the opportunity to model and visualize key parts of the field.
The paper describes the ‘digital field-worker’ at Johan Sverdrup which is changing the way of working, both during the construction and completion phase, but also during operations. This ranges from efforts to automate and digitalize work processes offshore to more innovative solutions. Examples of the latter include Echo – a multi-player digital twin solution allowing real-time visualization and collaboration between onshore and offshore – as well as the iterative development of anomaly detection models (utilizing machine learning and artificial intelligence) to move from condition-based monitoring towards predictive maintenance.
|File Size||990 KB||Number of Pages||16|