Katy, TX, United States of America

Dongzhuo Li

This inventor holds 1 USPTO granted patent. Top assignee: Exxonmobil Upstream Research Company. Active years: 2026.


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: The Innovative Contributions of Dongzhuo Li

Introduction

Dongzhuo Li is a notable inventor based in Katy, Texas. He has made significant contributions to the field of geophysics through his innovative patent. His work focuses on enhancing the understanding and characterization of geophysical bodies, which is crucial for various applications in exploration and resource management.

Latest Patents

Dongzhuo Li holds a patent titled "Method and system for augmented inversion and uncertainty quantification for characterizing geophysical bodies." This computer-implemented method introduces a machine-learning-augmented inversion technique that facilitates the characterization of uncertainties in geophysical bodies. The method allows for the estimation of wavelets without the need for well-log calibration, making it particularly useful during pre-discovery exploration phases when well log data is not available. By incorporating a priori knowledge about subsurface conditions and utilizing machine learning, this methodology enhances the robustness of inversion processes, even when prior distributions are not well balanced.

Career Highlights

Dongzhuo Li is currently employed at ExxonMobil Upstream Research Company, where he applies his expertise in geophysics and machine learning. His innovative approach to uncertainty quantification and geophysical characterization has positioned him as a valuable asset in the field.

Collaborations

He collaborates with talented colleagues, including Huseyin Denli and Cody MacDonald, to further advance research and development in geophysical methods.

Conclusion

Dongzhuo Li's contributions to the field of geophysics through his innovative patent demonstrate the importance of integrating machine learning with traditional methods. His work not only enhances the understanding of geophysical bodies but also aids in decision-making processes in exploration.

Profile summary based on public USPTO records.
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