Jersey City, NJ, United States of America

Victoria M Som De Cerff


Average Co-Inventor Count = 4.2

ph-index = 1

Forward Citations = 9(Granted Patents)


Company Filing History:


Years Active: 2022

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2 patents (USPTO):Explore Patents

Title: Innovations of Victoria M Som De Cerff

Introduction

Victoria M Som De Cerff is an accomplished inventor based in Jersey City, NJ (US). She has made significant contributions to the field of automated reservoir modeling and seismic interpretation. With a total of two patents to her name, her work exemplifies the intersection of technology and geology.

Latest Patents

Her latest patents include "Automated reservoir modeling using deep generative networks" and "Automated seismic interpretation systems and methods for continual learning and inference of geological features." The first patent provides a method for generating reservoir models using machine learning, which streamlines a traditionally time-intensive process. By utilizing geological data and concepts, her approach employs generative adversarial networks (GANs) to create accurate reservoir models. The second patent focuses on automated seismic interpretation, where trained models are used to analyze geophysical data and generate feature probability maps that represent subsurface geological features.

Career Highlights

Victoria is currently employed at ExxonMobil Upstream Research Company, where she applies her expertise in machine learning and geological modeling. Her innovative approaches have the potential to revolutionize how reservoir models are generated and interpreted, significantly impacting the energy sector.

Collaborations

Some of her notable coworkers include Huseyin Denli and Cody J Macdonald, with whom she collaborates on various projects within the company.

Conclusion

Victoria M Som De Cerff's contributions to automated reservoir modeling and seismic interpretation highlight her role as a leading inventor in her field. Her innovative patents demonstrate the power of machine learning in enhancing geological analysis and modeling.

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