Case Study: Sleipner CO₂ Storage Project achieves greater confidence in CO₂ plume prediction with Computer Modelling Group’s AI-driven seismic interpretation and dynamic simulation

Sleipner CO₂ Storage Project improves plume prediction confidence with Computer Modelling Group

The Sleipner CO₂ Storage Project required a solution to accurately predict CO₂ plume migration for its carbon storage operations, a critical challenge for the success of its CCUS project. Computer Modelling Group Ltd. (CMG) addressed this by applying a novel workflow that integrated its GEM dynamic reservoir simulation software with third-party AI interpretation tools.

Computer Modelling Group developed a solution that used AI-driven seismic interpretation for efficient plume identification and integrated this data directly into simulation models. This enabled spatial history matching, which improved the accuracy of plume predictions and allowed for the quantification of plume growth. The outcome was a fundamental improvement in the confidence of CO₂ storage predictions, ensuring a more reliable assessment of the project's Area of Review.