J. Carter
Gaussian Process Models for Well Placement Optimisation
Carter, J.; Vernon, I.
Citation
Carter, J., & Vernon, I. (2022). Gaussian Process Models for Well Placement Optimisation. . https://doi.org/10.3997/2214-4609.202244028
Presentation Conference Type | Conference Paper (Published) |
---|---|
Conference Name | ECMOR 2022 |
Publication Date | 2022 |
Deposit Date | Mar 27, 2023 |
Volume | 2022 |
Pages | 1-19 |
DOI | https://doi.org/10.3997/2214-4609.202244028 |
Public URL | https://durham-repository.worktribe.com/output/1135012 |
You might also like
A Bayesian Statistical Approach to Decision Support for TNO OLYMPUS Well Control Optimisation under Uncertainty
(2020)
Presentation / Conference Contribution
Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation Techniques
(2020)
Presentation / Conference Contribution
A Bayesian Optimisation Workflow for Field Development Planning Under Geological Uncertainty
(2020)
Presentation / Conference Contribution
Evaluation of Regions of Influence for Dimensionality Reduction in Emulation of Production Data
(2018)
Presentation / Conference Contribution
Systematic uncertainty reduction for petroleum reservoirs combining reservoir simulation and Bayesian emulation techniques
(2019)
Presentation / Conference Contribution
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search