Testing and Implementation of AI/ML Solutions for Seismic geomorphology, Inversion and Reservoir Characterization workflows

Beicip-Franlab; Rueil-Malmaison; On-site; EUR 6,700 - 13,000; Full time

Job summary

Beicip-Franlab is seeking a final-year student for an internship focused on evaluating, validating and implementing AI/ML solutions in seismic geophysics workflows. You will work with AI/ML approaches to enhance geomorphology, inversion and reservoir characterization, while gaining deep exposure to geophysical methodologies using Python and related tools.

The role involves benchmarking AI/ML-assisted solutions on seismic data, assessing data quality, and developing validated workflows to support

Qualifications

• Final-year student enrolled in a master’s degree or engineering program, with a background in geophysics or geosciences.
• Knowledge of seismic interpretation and/or signal processing, together with programming skills in Python is expected.
• An interest in AI/ML methods and their application to geoscience is essential.

Responsibilities

• Become familiar with geophysical workflows and software (seismic geomorphology, inversion, reservoir characterization) and understand parameters and quality-control criteria.
• Test and benchmark AI/ML-assisted solutions on seismic datasets and compare outputs with expert interpretations.
• Analyze influence of data quality and workflow parameters on performance and define validation metrics.
• Propose, prototype and implement workflow improvements using fit-for-purpose AI/ML methods.
• Consolidate results into validated workflows, usage recommendations and demonstration material for future integration.

Skills

Python

Machine Learning

Seismic interpretation

Signal processing

Programming

Education

Master's degree or engineering program

Tools

InterWell

Anaconda

Visual Studio

NetBeans

Job description

Beicip-Franlab is a leading geoscience consulting company that supports client decision-making across all energy sectors, backed by research and development from the IFPEN Group. The company is actively developing and evaluating AI/ML solutions across its geophysical workflows, from seismic geomorphology to inversion and reservoir characterization. In this context, the internship will focus on the evaluation, validation and implementation of AI/ML solutions across key seismic geophysics workflows, with applications spanning seismic geomorphology, inversion, reservoir characterization and quality control. Through these applications, the intern will develop a strong understanding of the underlying geophysical methodologies while assessing how AI/ML approaches can enhance, accelerate and support expert-driven workflows.

Main Tasks Undertaken During The Internship

• Become familiar with the relevant geophysical workflows and software, including seismic geomorphology, inversion and seismic reservoir characterization, and understand the key parameters, uncertainties and quality-control criteria used by specialists.
• Test and benchmark selected AI/ML-assisted solutions on representative seismic datasets and previous consulting projects, comparing their outputs with expert interpretations or reference results and identifying strengths, limitations, false detections and potential failure modes.
• Analyze the influence of seismic data quality, geological context, input attributes and workflow parameters on the performance of the selected solutions and define relevant validation metrics and benchmark criteria.
• Propose, prototype and implement workflow improvements, including parameter recommendation, automated quality control, error detection or decision-support approaches using fit-for-purpose AI/ML methods (e.g. machine learning, LLM-based approaches or decision-support methods).
• Consolidate the results into validated workflows, usage recommendations and demonstration material supporting future integration of the developed solutions into Beicip-Franlab geoscience applications.

Software Used

Mainly InterWell specialist software, together with an IDE depending on the programming language used, such as Anaconda, Visual Studio, or NetBeans for prototyping.

The internship will be supervised by a senior geophysicist and software engineer.

Final-year student enrolled in a master’s degree or engineering program, with a background in geophysics or geosciences. The candidate should be a fast learner, rigorous, and eager to understand geophysical workflows and master technical software. Knowledge of seismic interpretation and/or signal processing, together with programming skills in Python, is expected. An interest in AI/ML methods and their application to geoscience is essential.

#ET