A Productive Summer for PSS-GEO Research

This 2026 summer has been particularly productive for PSS-GEO, with 3 peer-reviewed articles and 1 technical article presenting results from our recent research and development. Tow of them are available in First Break online!

In June, our peer-reviewed article in First Break presented our work on machine-learning-based fluid prediction, where the algorithms learn from well data and transfer this knowledge to predict fluids directly across seismic volumes.

"Fluid type prediction from seismic data using machine learning: A workflow from well logs to seismic recognition". Read in First Break, by Vita Kalashnikova, Elena Karaseva, Rune Øverås, Jury Ampilov

In September, another important article was published, presenting the results of more than two years of validation of our 2022 predictions. What started with predictions tested against only a few wells has now grown into a substantial statistical study based on 164 wells, providing a much broader assessment of the technology and its performance.

«Qualitative analysis of sandstone reservoirs predicted by Rune Inversion in the North Sea Megagrid».

Read in First Break, by Vita Kalashnikova, Rune Øverås, Vlad Sopivnik, Alena Finogenova and Barbara Eva Klein.

It is particularly rewarding to see research move beyond the initial prediction stage and become something that can be tested against new data over several years. The full methodologies, results and statistics are presented in the published articles.

Two publications, two different technologies, and another step forward in turning seismic data into reliable subsurface information.