PET
PET is a toolbox for ensemble based Data-Assimilation and Optimization, developed and maintained by the data-assimilation and optimization group at NORCE Norwegian Research Centre AS.
Software
Hello world!
DAPPER Permalink
DAPPER is a set of templates for benchmarking the performance of data assimilation (DA) methods. The tests provide experimental support and guidance for new developments in DA.
NEDAS Permalink
NEDAS is a light-weight Python solution for implementing ensemble data assimilation methods for geophysical models, it utilizes MPI for parallelization and has a modular function-based design that allows algorithmic flexibility. NEDAS is an ideal test envir...
MiniRes Permalink
A lean (2D, two-phase) petroleum reservoir simulator in Python, with an adjoint model included. Small (the physics fit in 400 lines), fast, and validated against ECLIPSE and JutulDarcy. Runnable in the browser (no installation).
EnKF-seir Permalink
Multi-group SEIR model with age classes in an ensemble DA system for predicting spread of the Coronavirus.
Interactive Sequential-decision Geosteering Benchmark
The project allows to compare the decision skills of people and robots for a synthetic multi-target geosteering scenario. The code includes: Server, Client, and Ensemble-Based Decision Support System with uncertainties updated using the EnKF. The Benchmark ...
spade-gan-inversion
Leveraging the latest conditional Generative Adversarial Networks (GANs) with spatially adaptive denormalization (SPADE), we establish a novel ensemble-based workflow that effectively captures complex geological patterns. The code performs Bayesian history-...
EnKF-analysis Permalink
Fortran-90 routines for EnKF analysis. Stochastic and SQRT formulations with subspace inversion.