Geophysics ML Internship: Guided FWI & Petrophysics

Viridien; Saint-Nicolas-de-la-Grave; On-site; EUR 8,900 - 13,000; Full time

Benefits offered by this job

International culture

Subsidized company restaurant

Works council benefits

Public transport 50% reimbursement (ÎI

Mobility incentive

Gym access

Employee assistance program

Job summary

Viridien seeks a final-year Master’s student to work on an internship applying advanced machine learning to Earth imaging challenges. You will develop and test methods for full-waveform inversion, focusing on integrating petrophysical information into elastic parameter estimation and seismic imaging in a geophysical context.

The six-month role involves research in signal processing, wave propagation, numerical optimization and AI to advance reservoir-focused FWI and elastic modelling for

Qualifications

• Last year of Master’s degree in Mathematics, Physics, Computer Science, Artificial intelligence, Data science, or Natural Sciences with a Math/Physics specialization.
• Solid understanding of machine learning algorithms and neural network architecture.
• Excellent coding skills in Python, C/C++, CUDA, FORTRAN.
• Fluent English (read, written, spoken).

Responsibilities

• Investigate the potential of using neural networks to incorporate petrophysical information for guiding full-waveform inversion (FWI) from both methodology and development perspectives.
• Develop a neural network model to map petrophysical parameters (porosity, lithology, saturation) to elastic parameters (Vp, Vs, density, …)
• Integrate the neural network mapping into the FWI framework, allowing the inversion to be guided by petrophysical information.

Skills

Machine learning

Neural networks

Analytical thinking

Fluent English

Education

Master's degree in Mathematics/Physics/CS/AI/Data Science/Natural Sciences with Math/Physics focus

Tools

Python

C/C++

CUDA

FORTRAN

Job description

Viridien seeks a final-year Master’s student to work on an internship applying advanced machine learning to Earth imaging challenges. You will develop and test methods for full-waveform inversion, focusing on integrating petrophysical information into elastic parameter estimation and seismic imaging in a geophysical context.

The six-month role involves research in signal processing, wave propagation, numerical optimization and AI to advance reservoir-focused FWI and elastic modelling for