Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Demet Erbas"'
Autor:
Demet Erbas, Michael Andrew Christie
Publikováno v:
Oil & Gas Science and Technology - Revue de l'IFP. 62:155-167
Bayesian inversion techniques for assessing reservoir performance uncertainties involve generating multiple reservoir models conditioned to the available field data. This process requires sampling in a high-dimensional parameter space to identify goo
Publikováno v:
Journal of Computational Physics. 217:143-158
Uncertainty quantification is an increasingly important aspect of many areas of computational science, where the challenge is to make reliable predictions about the performance of complex physical systems in the absence of complete or reliable data.
Publikováno v:
All Days.
This paper focuses on studies carried out to explore possibilities to improve both areal and vertical sweep efficiency in mature WAG patterns in the Magnus oil field. Magnus tertiary miscible gas injection started in 2002 through a WAG scheme taking
Publikováno v:
Energy Sources. 22:543-556
Water produced constitutes a large amount of waste fluids during the production operation of an oil field. Underground injection for disposing of the waste water from hydrocarbon production is an engineering problem due to the possibility of leakage
Publikováno v:
All Days.
BP has been operating miscible gas injection projects in a variety of challenging environments throughout the world for over three decades. Numerous innovative techniques have been used to optimize oil recovery and the results have been reported in a
Autor:
Chris Davies, Phillip Trussell, Tim P. Moulds, David J. Cox, Demet Erbas, Ewan D. Laws, Neil Strachan
Publikováno v:
All Days.
Magnus is a high productivity oil field in the northern North Sea. First oil was produced in 1983 and the plateau of 150 MSTB/D ended in 1995. In the post-plateau period a variety of reservoir management techniques have been employed to arrest declin
Autor:
Demet Erbas, Michael Andrew Christie
Publikováno v:
All Days.
Generating multiple history-matched reservoir models by stochastic sampling to quantify the uncertainty in oil recovery predictions has recently aroused interest in the industry. Coupling a stochastic sampling algorithm with a Bayesian analysis poten
Autor:
Michael Andrew Christie, Gillian Elizabeth Pickup, Vasily Demyanov, Sullivan, Alannah Eileen O., Hashem Monfared, Demet Erbas, Pinggang Zhang, Hirofumi Okano, Monika Valjak
Publikováno v:
Heriot-Watt University
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1846d8faf3d9cd907fc5fa4cbbd19061
https://researchportal.hw.ac.uk/en/publications/2d2c8742-101f-420f-a9a8-af8e8ecebb10
https://researchportal.hw.ac.uk/en/publications/2d2c8742-101f-420f-a9a8-af8e8ecebb10