Yijie Zhou

Title: Yijie Zhou: Innovator in Reservoir Parameter Prediction

Introduction

Yijie Zhou is a prominent inventor based in Richmond, TX (US), known for his contributions to the field of reservoir parameter prediction. He holds a total of 3 patents that showcase his innovative approaches to seismic inversion and reservoir characterization.

Latest Patents

One of his latest patents is titled "System and method for prediction of reservoir parameters with uncertainty quantification." This method involves performing low frequency Markov Chain Monte Carlo (MCMC) processes on rock physics models to generate low frequency models (LFMs) of rock properties. A deep neural network is then trained using these LFMs and synthetic seismograms to produce a high frequency rock property model. The trained neural network can subsequently generate uncertainty quantification through broad-band MCMC processes.

Another significant patent is "System and method for reservoir structure characterization." This method includes obtaining well logs and seismic data, performing facies classification, and estimating wavelets from the seismic data. The process aims to identify layers within the reservoir and map its structure through global optimization techniques, ultimately generating a graphical representation of the reservoir structure.

Career Highlights

Yijie Zhou is currently employed at Chevron U.S.A. Inc., where he applies his expertise in reservoir engineering and seismic data analysis. His work significantly contributes to the advancement of technologies in the oil and gas industry.

Collaborations

He collaborates with notable colleagues such as Zhao Zhang and Sandra C. Saldana, enhancing the innovative efforts within his team.

Conclusion

Yijie Zhou's work in reservoir parameter prediction and characterization exemplifies the impact of innovative thinking in the energy sector. His patents reflect a commitment to advancing technology and improving methodologies in seismic data analysis.