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Publikasjoner
- Simulations of the effect of smectite-to-illite transition in shales on permeability and overpressures using a stochastic approach, a Norwegian margin case study
- Digitized uncertainty handling of pore pressure and mud-weight window ahead of bit: north sea example
- Storage Resources for Future European CCS Deployment; A Roadmap for a Horda CO2 Storage Hub, Offshore Norway
- Deliverable D3.2.4 Storage options relevant for the Norwegian cluster and their development, Norway
- Uncertainty modelling of minimum horizontal stresses and porepressures in deeply buried grabens. What's next in modelling?
- Statistical modeling for real-time pore pressure prediction from predrill analysis and well logs Les publikasjonen
- Porosity, permeability and compaction trends for Scandinavian regoliths
- Workflow for Uncertainty Modelling of Pore Pressure and Mud Weight Window ahead of Bit - Example of Pre-drill Results from the North Sea
- CO2 Storage Capacity Estimates for a Norwegian and a Swedish Aquifer Using Different Approaches - From Theoretical Volumes, Basin Modelling to Reservoir Models
- Assessment of the Cenozoic Erosion Amount Using Monte Carlo Type-Petroleum Systems Modeling of the Hammerfest Basin, Western Barents Sea
Annen formidling
- Managing pore pressure for regional CO2 storage resources - SINTEF experience and tools
- Processing machine-learning fault scores from 3-D seismic to map fault density in the overburden of CO2-reservoirs
- Real-time Automated Pore Pressure And Wellbore Stability Updates In A Digital Twin
- Real-time Automated Pore Pressure And Wellbore Stability Updates in A Digital Twin, Using Smart Agents And Log Predictions Ahead of Bit, Example From Norwegian Continental Shelf"
- Fault stability modelling approaches
- CO2 Storage Forum: Terminology around storage risk
- CO2 storage
- How to evaluate caprock units using ML, Horda Platform area
- Upscaling from lab to basin scale modelling: Smectite-illite transition and the effect on shale permeabilities, caprock integrity and rock mechanical properties
- Machine learning to estimate fault density in overburden - a puzzle piece in de-risking of CO2 storage