Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Patrizia Anastasi"'
Publikováno v:
Day 2 Wed, January 25, 2023.
The reservoir model-based forecast uncertainty reduction requires the integration of multiple sources of information. Among them, production data are of great value. For this reason, a methodology able to manage them within the history matching proce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eecd0c8c081703e0743858ee957435ec
https://doi.org/10.2118/212679-ms
https://doi.org/10.2118/212679-ms
Publikováno v:
Day 3 Wed, November 17, 2021.
Improvements in reservoir simulation computational time thanks to GPU-based simulators and the increasing computational power of modern HPC systems, are paving the way for a massive employment of Ensemble History Matching (EHM) techniques which are i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90585246f36cbc2784b5881d8e980b40
https://doi.org/10.2118/207606-ms
https://doi.org/10.2118/207606-ms
Publikováno v:
Day 3 Wed, November 17, 2021.
Ensemble approaches are increasingly used for history matching also with large scale models. However, the iterative nature and the high computational resources required, demands careful and consistent parameterization of the initial ensemble of model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e060b11bda1eace155c119115e71f20d
https://doi.org/10.2118/207215-ms
https://doi.org/10.2118/207215-ms
Publikováno v:
Day 2 Wed, September 18, 2019.
A statistical screening methodology is presented to address uncertainty related to main geological assumptions in green field modeling. The goals are the identification of the entire range of uncertainty on production, learning which are the most imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a72450981783bff527b9a29f9ddbd0f
https://doi.org/10.2118/196712-ms
https://doi.org/10.2118/196712-ms