TotalEnergies OneTech has launched an innovation project to optimize the positioning and sequencing of drilling wells in an oil reservoir (development of WISH and GENEPI codes). These tools need to be generalized and improved for greater efficiency (consideration of uncertainties, faster computation times). A CIFRE Thesis is offered to achieve this goal. The position holder will be based at the CSTJF in Pau, spending 80% of their working time at this technical center, with regular supervision by Pierre Biver (TotalEnergies reference for geostatistics and uncertainties) and N. Eberlee (specialist in generative designs for oil reservoir exploitation).

Academically, the candidate will spend 20% of his working time at the Laboratory of Complex Fluids and Reservoirs at the University of Pau and Pays de l’Adour, supervised by N. Beaudoin (Associate Professor) and G. Galliero (University Professor). 

The aim of the PhD is to generalize these methods and apply them to a concrete case operated by TotalEnergies.

The main missions are the following:

1) Consideration of uncertainties in reservoir model properties when constructing well patterns using WISH. 

2) Optimization of the number of wells inserted into the reservoir model when constructing well patterns using WISH. 

3) Optimization of the drilling sequence of wells proposed by WISH using the GENEPI method (notably in terms of numerical performance). 

4) Use of proxies for dynamic simulations in the WISH context (again for numerical performance reasons). 

5) Generalization of WISH to account for relatively regular well

You hold a Master's Degree in Geosciences or Engineering school

You are fluent French and Englis

You have good knowledge of geostatistics and flow simulators is essential, 

You have also knowledge of AI and advanced Python programing 

You have good communications skills, team spirit and you have good synthesis skills.