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Ensemble methods for history matching in reservoir modelling


Required Education : PhD
Start date : 1 November 2016
Mission duration : 1 an renouvelable 1 an
Deadline for applications : 15 October 2016
Salary : 3136 euros gross per month

CERFACS is recruiting a researcher with experience in data assimilation, if possible on ensemble methods (e.g. Ensemble Kalman Filter) or uncertainty quantification. The work involved is part of a collaboration between TOTAL and CERFACS on reanalysis (history matching) of an oil reservoir model (underground reservoir).

A first objective is to enrich the spectrum of methods currently used by the Centre Scientifique et Technique Total (CSTJF) in Pau, starting with data assimilation methods developed and implemented at CERFACS on multiple applications, as well as a thorough bibliographic work. The researcher will divide his/her time between Pau and Toulouse, in a proportion of one third / two thirds. It is not mandatory to have expertise on reservoir models, although this competence will be assessed in addition to the mathematical background required on statistical methods.

The first objective will be expanded, during the second year of post-doctorate position, to other relevant mathematical approaches for the modeling of oil fields: uncertainties, high performance computing, geological models, etc.

Contact : Ulrich RUEDE, ulrich.ruede at cerfacs.fr