The Ensemble Kalman Filter in Reservoir Engineering--a Review
University of Bergen · International Research Institute of Stavanger · +2 more institutions
Abstract
Introduction and Background There has been great progress in data assimilation within atmospheric and oceanographic sciences during the last couple of decades. In data assimilation, one aims at merging the information from observations into a numerical model, typically of a geophysical system. A typical example where data assimilation is needed is in weather forecasting. Here, the atmospheric models must take into account the most recent observations of variables such as temperature and atmospheric pressure for better forecasting of the weather in the next time period. A major challenge for these models is that they contain very large numbers of variables. The progress in data assimilation is because of both…
Citation impact
- FWCI
- 109.79
- Percentile
- 100%
- References
- 0
Authors
5Topics & keywords
- Ensemble Kalman filter
- Data assimilation
- Data science
- Kalman filter
- Computer science
- Meteorology
- Environmental science
- Artificial intelligence
- Life below water