Geir Evensen has worked within R&D related to the development of data-assimilation methods for ocean and weather forecasting and petroleum technology since 1992. He is currently chief scientist at NORCE (www.norceresearch.no) where he focuses on the development of iterative ensemble-smoother methods for nonlinear data assimilation and parameter estimation while managing the DIGIRES project.
He has previously managed several international research projects focusing on the implementation and use of ensemble data assimilation for state and parameter estimation in various disciplines.
He invented the Ensemble Kalman Filter/Smoother now being used operationally for assimilation of observations in among others ocean and weather forecasting systems.
He developed ensemble methods for history matching of reservoir models, which have become the most popular approach used in the petroleum industry.
He led the development and implementation of Fast-Model-Update, an ensemble-based workflow for reservoir model management and updating, which is now in operational use as a multidisciplinary integrated modeling workflow in Equinor.
He has also published the book Data Assimilation: The Ensemble Kalman Filter, Springer 2009, and more than 70 scientific publications related to data assimilation.