Characterization of reservoir simulation models using a polynomial chaos‐based ensemble Kalman filter

By G. Saad, Roger G. Ghanem. 2009

67 citations recorded by the source corpus.

Subfields: Atmospheric Science, Environmental Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/51582be94511b9fc706107d1044ecb07eae0a82d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. M. Christie
2. Youssef M. Marzouk
3. Jasper A. Vrugt
4. Sergey Oladyshkin
5. Wolfgang Nowak
6. Ahmed H. Elsheikh
7. Holger Class
8. Mohammad Hossein Ahmadi

In Environmental Engineering

1. Jasper A. Vrugt
2. Sergey Oladyshkin
3. Diederik Jacques
4. Wolfgang Nowak
5. Eric Laloy
6. Holger Class
7. B. Rogiers
8. Dirk Mallants

In Ocean Engineering

1. Eric Laloy
2. Ahmed H. Elsheikh
3. Sergey Oladyshkin
4. Holger Class
5. M. Christie
6. Youssef M. Marzouk
7. Jasper A. Vrugt
8. Wolfgang Nowak

Citations in the corpus

• An introduction to sampling via measure transport (2016, background): “Focusing for a moment on the specific problem of Bayesian inference, another class of approaches related to the transport map framework are the sampling-free Bayesian updates introduced in [74, 48, 47, 54, 75].”
• Bayesian updating via bootstrap filtering combined with data-driven polynomial chaos expansions: methodology and application to history matching for carbon dioxide storage in geological formations (2013, methodology): “Even the EnKF has been combined with polynomial chaos expansion for accelerated and accurate computation of the required covariance matrices (see [71], [30], and also related work [67]).”
• Efficient posterior exploration of a high‐dimensional groundwater model from two‐stage Markov chain Monte Carlo simulation and polynomial chaos expansion (2013, background): “…[e.g., Li and Zhang, 2007; Li et al., 2009] or global sensitivity analysis [e.g., Fajraoui et al., 2011; Ciriello et al., 2013], but rarely within the context of parameter estimation [some notable exceptions are Saad and Ghanem, 2009; Zeng and Zhang, 2010; Fajraoui et al., 2012] and MCMC sampling.”
• Surrogate accelerated sampling of reservoir models with complex structures using sparse polynomial chaos expansion (2015, methodology): “The choice of the polynomial chaos expansions as a proxy model was pioneered by Ghanem and Spanos [27] and has been applied to various engineering problems [28, 29, 30, 31, 57, 33, 77].”