Výsledky vyhledávání - "Gisela Vanegas"

Conditioning Model Ensembles to Various Observed Data (Field and Regional Level) by Applying Machine-Learning-Augmented Workflows to a Mature Field with 70 Years of Production History

Autor: Torsten Clemens, John Nejedlik, Pascale Neff, Gisela Vanegas

Publikováno v: SPE Reservoir Evaluation & Engineering. 24:809-826

SummaryForecasting production from hydrocarbon fields is challenging because of the large number of uncertain model parameters and the multitude of observed data that are measured. The large number of model parameters leads to uncertainty in the prod

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6ea59addf7847f796502870c48d5f201
https://doi.org/10.2118/205188-pa

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Deriving Alkali Polymer Parameter Distributions from Core Flooding by Applying Machine Learning in a Bayesian Framework to Simulate Incremental Oil Recovery

Autor: Torsten Clemens, Dominik Steineder, Gisela Vanegas, Markus Zechner

Publikováno v: Day 2 Wed, December 02, 2020.

Various physico-chemical processes are affecting Alkali Polymer (AP) Flooding. Core floods can be performed to determine ranges for the parameters used in numerical models describing these processes. Because the parameters are uncertain, prior parame

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::38e1bbcb4a212173aa7ab3dfabd230a3
https://doi.org/10.2118/200578-ms

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