Blar i Publikasjoner fra Cristin på emneord "Ensemble based methods"
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Accounting for model errors of rock physics models in 4D seismic history matching problems: A perspective of machine learning
(Journal article; Peer reviewed, 2021)Model errors are ubiquitous in practical history matching problems. A common approach in the literature to accounting for model errors is to treat them as random variables following certain presumed distributions. While ... -
Assimilation of multiple linearly dependent data vectors
(Peer reviewed; Journal article, 2019)Assimilation of a sequence of linearly dependent data vectors, {dl}Ll=1 such that dl=BldLL−1l=1 , is considered for a parameter estimation problem. Such a data sequence can occur, for example, in the context of multilevel ... -
Combining direct and indirect sparse data for learning generalizable turbulence models
(Peer reviewed; Journal article, 2023)Learning turbulence models from observation data is of significant interest in discovering a unified model for a broad range of practical flow applications. Either the direct observation of Reynolds stress or the indirect ... -
Fast robust optimization using bias correction applied to the mean model
(Peer reviewed; Journal article, 2020)Ensemble methods are remarkably powerful for quantifying geological uncertainty. However, the use of the ensemble of reservoir models for robust optimization (RO) can be computationally demanding. The straightforward ... -
Learning from weather and climate science to prepare for a future pandemic
(Peer reviewed; Journal article, 2023)Established pandemic models have yielded mixed results to track and forecast the SARS-CoV-2 pandemic. To prepare for future outbreaks, the disease-modeling community can improve their modeling capabilities by learning from ... -
Offshore wind farm layout optimization using ensemble methods
(Peer reviewed; Journal article, 2023)When planning wind farms it is important to optimize the layout to increase production and reduce costs. In this paper we minimize the levelized cost of energy (LCOE) for a floating wind farm using wind data in an area ... -
A Stochastic Covariance Shrinkage Approach in Ensemble Transform Kalman Filtering
(Peer reviewed; Journal article, 2023)The Ensemble Kalman Filters (EnKF) employ a Monte-Carlo approach to represent covariance information, and are affected by sampling errors in operational settings where the number of model realizations is much smaller than ...