Rossen Parashkevov

Title: Innovations of Rossen Parashkevov in Hydrocarbon Reservoir Simulation

Introduction

Rossen Parashkevov is a notable inventor based in Houston, TX (US), recognized for his contributions to the field of hydrocarbon reservoir modeling. With a total of 8 patents to his name, he has made significant strides in utilizing machine learning techniques to enhance the simulation of fluid flow in porous media.

Latest Patents

Among his latest patents, Parashkevov has developed methods and systems for machine-learning based simulation of flow. One of his innovative approaches involves generating a reservoir model that comprises multiple sub-regions. This method utilizes a training simulation to obtain a set of training parameters, which include state variables and boundary conditions for at least one of the sub-regions. A machine learning algorithm is then employed to approximate an inverse operator of a matrix equation, which provides solutions for fluid flow through porous media. Additionally, the method allows for the generation of a data representation of a physical hydrocarbon reservoir, stored in a non-transitory, computer-readable medium based on the simulation results.

Career Highlights

Rossen Parashkevov is currently associated with ExxonMobil Upstream Research Company, where he applies his expertise in machine learning and reservoir modeling. His work focuses on improving the efficiency and accuracy of hydrocarbon extraction processes through advanced simulation techniques.

Collaborations

Throughout his career, Parashkevov has collaborated with esteemed colleagues, including Xiaohui Wu and Yahan Yang, contributing to the advancement of innovative solutions in the field of hydrocarbon research.

Conclusion

Rossen Parashkevov's innovative work in hydrocarbon reservoir simulation exemplifies the intersection of machine learning and engineering. His contributions continue to shape the future of energy resource management.