Denver, CO, United States of America

Omer Gurpinar

This inventor holds 1 USPTO granted patent and 2 published patent applications and 3 EPO patents. Top assignee: Schlumberger Technology Corporation. Active years: 2024.

USPTO Granted Patents = 1 

% Patents Active = 100.0

 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Omer Gurpinar: Innovator in Machine Learning for Oilfield Operations

Introduction

Omer Gurpinar is a notable inventor based in Denver, Colorado, recognized for his contributions to the field of machine learning, particularly in oilfield production operations. His innovative approach combines advanced technology with practical applications in the oil and gas industry.

Latest Patents

Omer Gurpinar holds a patent for a "Machine learning proxy model for parameter tuning in oilfield production operations." This method involves training a proxy model to predict output from a reservoir model of a subterranean volume. The process includes receiving data representing an oilfield operation performed at least partially in the subterranean volume, predicting one or more performance indicators for the oilfield operation using the proxy model, and updating the reservoir model based on the predicted performance indicators.

Career Highlights

Throughout his career, Omer has worked with prominent companies in the industry, including Schlumberger Technology Corporation and Services Petroliers Schlumberger. His experience in these organizations has allowed him to develop and refine his innovative ideas, contributing significantly to advancements in oilfield operations.

Collaborations

Omer has collaborated with talented professionals such as David Rowan and Rajarshi Banerjee. These partnerships have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge solutions in the field.

Conclusion

Omer Gurpinar's work exemplifies the intersection of technology and industry, showcasing how machine learning can enhance oilfield production operations. His contributions continue to influence the field, paving the way for future innovations.

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