Phd Position in Computational Geosciences
Il y a 2 mois
BRGM - The geothermal resource is already used in 90 countries to supply electricity and/or heat. Despite these definite advantages, geothermal exploration - an obligatory step preceding exploitation - entails major challenges related to the uncertainty of the characterisation and there is so far no consensus or established good practise to follow.
Usually, Exploration phase of a deep geothermal project is expensive and a long process, going through the design of a tedious geomodel elaboration. It is indeed crucial to characterise and estimate how much energy is potentially available underground, to support the next exploration phase, such as acquiring new data and mitigate risks.
A key challenge for deep geothermal exploration is to speed-up the evaluation of the potential, while mitigating the risk of misinterpretation, along with an uncertainty assessment.
The main purpose of the project is therefore to develop a fast-track model to match the available data while taking into account uncertainty with a multi-scenario type of approach.
A special attention will be brought to the data with a prior analysis, adapted machine-learning-based processing and fast fluid flow modelling.
This project will employ or develop a series of in-house open-source codes for: data processing, reservoir simulation and data assimilation techniques and methodologies. Requested start date : 01/09/2023
**Contract type**: CDD 3 years
A MSc degree or equivalent in geoscience or reservoir engineering or applied mathematics or physics, or related area.
- Strong numerate and programming skills
- Sound and quantitative understanding of geological fluid flow
- Good communication and writing skills in English and the ability to collaborate are important
**It is a plus if you have**:
- Experience in fluid flow modelling in porous media
- Experience in machine learning
- Knowledge in geothermal systems
- A short motivation letter covering your research interest and relevant experience.
- Your CV including a list of publications if applicable and contact details for two references unless reference letters are attached.
- Copies of academic qualifications.
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