activity
20182021
most citedInvestigating the Pilot Point Ensemble Kalman Filter for geostatistical inversion and data assimilation

23 citations · 35 across the 5 of their papers we have counts for

collaborators

6 papers

stat.AP202123 cited

Investigating the Pilot Point Ensemble Kalman Filter for geostatistical inversion and data assimilation

Johannes Keller, Harrie-Jan Hendricks Franssen, Wolfgang Nowak

Parameter estimation has a high importance in the geosciences. The ensemble Kalman filter (EnKF) allows parameter estimation for large, time-dependent systems. For large systems, t…

cs.LG202111 cited

Finite Volume Neural Network: Modeling Subsurface Contaminant Transport

Timothy Praditia, Matthias Karlbauer, Sebastian Otte +3

Data-driven modeling of spatiotemporal physical processes with general deep learning methods is a highly challenging task. It is further exacerbated by the limited availability of…

stat.CO20211 cited

Sequential pCN-MCMC, an efficient MCMC method for Bayesian inversion of high-dimensional multi-Gaussian priors

Sebastian Reuschen, Fabian Jobst, Wolfgang Nowak

In geostatistics, Gaussian random fields are often used to model heterogeneities of soil or subsurface parameters. To give spatial approximations of these random fields, they are d…

stat.AP2020

Surrogate-based Bayesian Comparison of Computationally Expensive Models: Application to Microbially Induced Calcite Precipitation

Stefania Scheurer, Aline Schäfer Rodrigues Silva, Farid Mohammadi +4

Geochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex biogeochemical process in subsurface…

cs.DC2019

Using Surrogate Models and Data Assimilation for Efficient Mobile Simulations

Christoph Dibak, Wolfgang Nowak, Frank Dürr +1

Numerical simulations on mobile devices are an important tool for engineers and decision makers in the field. However, providing simulation results on mobile devices is challenging…

cs.CE2018

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario

Markus Köppel, Fabian Franzelin, Ilja Kröker +8

A variety of methods is available to quantify uncertainties arising with\-in the modeling of flow and transport in carbon dioxide storage, but there is a lack of thorough compariso…