CGG (www.cgg.com) is a global technology and HPC leader that provides data, products, services and solutions in Earth science, data science, sensing and monitoring. Our unique portfolio supports our clients in efficiently and responsibly solving complex digital, energy transition, natural resource, environmental, and infrastructure challenges for a more sustainable future. CGG employs around 3,400 people worldwide.

Our expertise, specialized HPC and digital technologies support advanced and secure cloud-based workflows, expert geoscience data transformation and AI, machine learning and data science services. Today, our HPC supports over 700 users with 500 petaflops of compute power.

The quantification of reservoir uncertainties is important in subsurface modelling. Seismic inversion is intensively used, in particular with the development of different stochastic inversion approaches. Applying it to large volumes of data and providing a large number of realisations can become challenging. The SPDE (stochastic partial differential equations) approach makes it possible to solve geostatistical problems on large volumes of data. A current research project studies its adaptation to the problem of seismic characterization of reservoirs and in particular the stochastic inversion of seismic data. In this context, integrated in the CGG Reservoir Research department, the intern will participate in the theoretical development and implementation of a prototype.

This innovative methodology will be developed during the internship and must be implemented then tested, first on small volumes of synthetic data then on real data in order to validate its application, and to understand the impact of the different parameters as well as the limitations. The application of such approach to other domains will be further investigated to provide uncertainties estimation in the different workflows currently used by CGG.

• Last year of Engineer School or Master’s degree with strong skills in Mathematics, Physics and Numerical computation
• Analytical approach to problem solving
• Collaborating with external R&D partners
• Theoretical bases of statistics/geostatistics and if possible knowledge of the SPDE approach
• Strong knowledge of Python and C++
• Knowledge of geophysics is not essential but will be useful
• Curiosity, interest for research and teamwork

• Remunerated internship depending on level of education
• Access to company restaurant with subsidized price
• Reimbursement of 50% of public transportation card in Ile-de-France region
• Relocation assistance (housing allowance + train tickets) for students coming from outside of Ile-de-France region.

Please apply with a resumé in English or French

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