Applied Mathematics Engineer Intern Build automatically realistic implicit structural models for deep leaning (5-6 months)

APPLIED MATHEMATICS ENGINEER INTERN - BUILD AUTOMATICALLY REALISTIC IMPLICIT STRUCTURAL MODELS FOR DEEP LEANING (5-6 MONTHS) Montpellier - France JOB TITLE: Applied Mathematics Engineer Intern - Build automatically realistic implicit structural models for deep leaning (5-6 months) LOCATION: Montpellier, France ABOUT SCHLUMBERGER: We are Schlumberger, the leading provider of technology and services to the energy industry. Throughout much of the oil and gas lifecycle in over 120 countries; we design, develop, and deliver technology and services that transforms how work is done. We define the boundaries of the industry by unleashing our talented people’s energy. We’re looking for innovators to join our diverse community of colleagues and develop new solutions and push the limits of what’s possible. If you share our passion for discovery and want to find out what you could really do, then here is the place to do it. JOB SUMMARY: Our Subsurface Structural Modeling team has for mission the elaboration of industrial numerical code for building structural models of the underground. Those models are essential to understand the history of the underground and its structure, enabling to search for subsurface resources (ore, geothermal, oil and gas, water). Our current technology is based on the well known implicit technic representing each conformal horizon as an iso-value of a function to be computed. This interpolation problem is formulated as a least-square minimization problem which is numerically costly to solve. Meanwhile, artificial intelligence (AI) has spread over a wide range of domains in particular geoscience world. AI has proven to be an outstanding approach for solving problems that until now were requiring massive computational efforts. The idea proposed herein aims to explore the application of the deep learning to the implicit structural modeling. The aim of this internship is to develop a tool to automatically build realistic synthetic structural models in 2D and 3D for training a neural network. The algorithm should be able to generate diverse structures with realistic folding and faulting features depending on a set of parameters randomly selected. ESSENTIAL RESPONSIBILITIES AND DUTIES: The theme of this internship is twofold: * Design and develop an algorithm to automatically build diverse structural models with realistic folding and faulting features (C++/python) * Interact with data scientists for ML part. QUALIFICATION: * Penultimate or final year COMPETENCIES: * Bibliographical research and Mathematical formulation * Implementation of a prototype (C++ or python) * Report and Technical discussions Schlumberger is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.