Company Filing History:
Years Active: 2024
Title: Innovations of Charles Hai Wang in Petroleum Reservoir Modeling
Introduction
Charles Hai Wang is an accomplished inventor based in Houston, TX (US). He has made significant contributions to the field of petroleum engineering, particularly in the modeling and prediction of reservoir behavior. With a total of 2 patents, his work focuses on enhancing the efficiency and accuracy of reservoir simulations.
Latest Patents
Wang's latest patents include "Petroleum reservoir behavior prediction using a proxy flow model" and "Optimized methodology for automatic history matching of a petroleum reservoir model with Ensemble Kalman Filter (EnKF)." The first patent involves training a deep neural network (DNN) to model a proxy flow simulation of a reservoir using production data. This method employs an ensemble Kalman filter (EnKF) to assimilate new data, allowing for continuous updates and improved predictions of reservoir behavior. The second patent outlines a method for history matching a reservoir model based on actual production data, utilizing geological data to generate an ensemble of reservoir models. This innovative approach transforms production data into normal distributions for more accurate predictions of future reservoir behavior.
Career Highlights
Charles Hai Wang is currently employed at Landmark Graphics Corporation, where he applies his expertise in reservoir modeling and simulation. His work has been instrumental in advancing methodologies that optimize the extraction of resources from petroleum reservoirs.
Collaborations
Wang collaborates with talented professionals in his field, including Yevgeniy Zagayevskiy and Hanzi Mao. Their combined efforts contribute to the development of cutting-edge technologies in petroleum engineering.
Conclusion
Charles Hai Wang's innovative patents and contributions to petroleum reservoir modeling demonstrate his commitment to advancing the field. His work not only enhances the understanding of reservoir behavior but also improves the efficiency of resource extraction.