Soazig Leveque

Title: Soazig Leveque and Real-Time Reservoir Boundary Identification

Introduction

Soazig Leveque is an inventor associated with Schlumberger Technology Corporation. Her patented work addresses the use of deep-learning models to identify subsurface reservoir boundaries in real time.

Latest Patents

The provided information lists one patent for Leveque: “Using deep-learning models to automatically identify subsurface reservoir boundaries in real time.” The disclosure describes a boundary identification system that determines borders in subsurface geological features, including reservoirs. It uses an ensemble of image-to-image machine-learning models to generate reservoir boundaries from inversion result profiles and images. The system can produce these boundaries in real time, while diversified inputs and ensembling individual model outputs during inference can further improve accuracy. The listed patent count is 1 patent.

Career Highlights

Leveque’s listed invention applies machine learning to the interpretation of subsurface geological data. The work focuses on generating reservoir boundaries efficiently and accurately from inversion results.

Collaborations

The provided information names Zhenhua Li and Fei Wang as Leveque’s coworkers. It does not specify their roles in the patent or describe the nature of their collaboration.

Conclusion

Soazig Leveque’s listed patent combines ensemble deep-learning methods with subsurface data analysis to support real-time identification of reservoir boundaries.