Well placement optimization with the covariance matrix adaptation evolution strategy and meta-models

By Zyed Bouzarkouna, Didier Yu Ding, Anne Auger. Computational Geosciences, 2011

117 citations recorded by the source corpus.

Subfields: Mechanical Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/e9542b80d1a9ee11e875ddb06a823e308cb006c3

How researchers see this paper

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

In Mechanical Engineering

1. R. Hanea
2. M. Jesmani
3. Bjarne A. Foss
4. Mathias C. Bellout
5. Thomas Donald Humphries
6. Ronald D. Haynes

In Ocean Engineering

1. R. Hanea
2. M. Jesmani
3. Bjarne A. Foss
4. Mathias C. Bellout
5. Thomas Donald Humphries
6. Ronald D. Haynes

Citations in the corpus

• Well placement optimization subject to realistic field development constraints (2016, methodology): “Another key algorithm is the covariance matrix adaptation evolution strategy (CMA-ES) [20].”
• Joint optimization of well placement and control for nonconventional well types (2014, background): “This approach, which was proposed in Cagnina et al. (2008), has the advantage of being simple to implement and not requiring any parameter tuning (unlike penalty function based approaches), while also allowing particles to be initialized to infeasible positions.”