Joint optimization of oil well placement and controls
By Mathias C. Bellout, D. Echeverría Ciaurri, Louis J. Durlofsky, Bjarne A. Foss, J. Kleppe. Computational Geosciences, 2012
157 citations recorded by the source corpus.
Subfields: Mechanical Engineering, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/febfbdc2eef9e2fb082c5d8fb9301645f64e2080
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
- Bjarne A. Foss
- Mathias C. Bellout
- R. Hanea
- M. Jesmani
- Thomas Donald Humphries
- Ronald D. Haynes
- D. Echeverría Ciaurri
- Obiajulu J. Isebor
In Ocean Engineering
- Bjarne A. Foss
- Mathias C. Bellout
- R. Hanea
- M. Jesmani
- Thomas Donald Humphries
- Ronald D. Haynes
- D. Echeverría Ciaurri
- Obiajulu J. Isebor
Citations in the corpus
- Joint optimization of well placement and control for nonconventional well types (2014, background): “Historically, genetic algorithms (GAs) have received the widest use (Bittencourt and Horne, 1997; Yeten et al., 2003; Güyagüler and Horne, 2004; Artus et al., 2006; Emerick et al., 2009).”
- Well placement optimization subject to realistic field development constraints (2016, methodology): “In [34], a heuristic repair technique is implemented in the form of an iterative sequence of projection operations.”
- A derivative-free methodology with local and global search for the constrained joint optimization of well locations and controls (2014, methodology): “[6] and Li and Jafarpour [33] found their joint approaches to outperform sequential procedures.”