dageo: Data Assimilation in Geosciences

Dieter Werthmüller , Gabriel Serrao Seabra, Femke C. Vossepoel 

Data Assimilation combines computer models with real-world measurements to improve estimates and forecasts of dynamical systems such as oceans, atmosphere, and subsurface reservoirs. The Python package dageo is a tool to apply data assimilation in geoscience applications. Currently, it encompasses the Ensemble Smoother with Multiple Data Assimilation (ESMDA) method and provides tools for reservoir engineering applications. The package includes localization to help with relatively small ensembles, Gaussian random field generation for generating heterogeneous parameter fields, and integration capabilities with external simulators.

An additional feature of dageo is a two-dimensional single-phase reservoir simulator that models pressure changes over time and well behavior for both injection and production scenarios. This simulator is particularly useful for educational purposes, providing a practical platform for students and researchers to learn and experiment with data assimilation concepts and techniques. The software features an online documentation, with examples that guide users through learning ESMDA concepts, testing new ideas, and applying methods to real-world problems.