Robust multi-objective field development optimization for the mariner asset

Autor: Hanea, R.G., Bjorlykke, O.P., Hashmi, Y., Feng, T., Fonseca, R.M.

Publikováno v: SPE Reservoir Simulation Conference 2019, RSC 2019, 10-11 April 2019, Houston, TX, USA

In this paper we present our results, challenges and learnings, over a two-year period wherein robust multi-objective optimization was applied at the Mariner asset which is being currently developed. Many different problems were solved with different

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ef591d67bb5c34efa11e7142552fd779
http://resolver.tudelft.nl/uuid:6f7a055b-a55c-41a0-b5af-b1554de16c47

A case study of the history matching of a sector of the nome field using the ensemble Kalman filter

Autor: Szklarz, S.P., Hanea, R.G., Peters, E.

Publikováno v: 73rd European Association of Geoscientists and Engineers Conference and Exhibition 2011-Incorporating SPE EUROPEC 2011, 23 May 2011 through 26 May 2011, Vienna, 4, 3067-3077

In the history matching process reservoir parameters are estimated so they can be further used in a simulator to reproduce the past behaviour of the reservoir. During the last two decades the methodology evolved from manual methods to computer assist

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5da9915f6d0ddebcf8676c230c9fdd00
http://resolver.tudelft.nl/uuid:cee86b0f-5bbb-4886-a26e-087d9027b801

Error subspace filtering for atmospheric chemistry data assimilation modeling

Autor: Hanea, R.G.

Publikováno v: None

not available

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::7a250e061788a086382b5f68866db2e7
http://resolver.tudelft.nl/uuid:c9d57c31-3359-47be-a8f6-98b2c1e7ebe8

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Use of Deep-Learning-Accelerated Gradient Approximation for Reservoir Geological Parameter Estimation.

Autor: Xiao, Cong, Liu, Ting, Zhang, Lufeng, Li, Zhun

Publikováno v: Processes; Oct2024, Vol. 12 Issue 10, p2302, 26p