Yuexiang Hao

Title: Innovations of Yuexiang Hao in Seismic Prediction Methods

Introduction

Yuexiang Hao is a notable inventor based in Chengdu, China. He has made significant contributions to the field of seismic prediction, particularly in the quantitative assessment of shale total organic carbon (TOC). His innovative approach utilizes advanced neural network techniques to enhance the accuracy of geological predictions.

Latest Patents

Yuexiang Hao holds a patent for a "Seismic quantitative prediction method for shale TOC based on sensitive parameter volumes." This method involves determining a target stratum for TOC measurement, analyzing logging curves that correlate with TOC contents, and identifying sensitive parameters. By constructing sample data and training a radial basis function (RBF) neural network, he developed a prediction model that calculates TOC values based on seismic data.

Career Highlights

Yuexiang Hao is affiliated with Chengdu University of Technology, where he continues to advance research in seismic prediction methods. His work has garnered attention for its innovative use of neural networks in geological assessments. With 1 patent to his name, he is recognized for his contributions to the field.

Collaborations

Yuexiang Hao has collaborated with colleagues such as Chaorong Wu and Cheng Liu. Their joint efforts have furthered research in seismic prediction and enhanced the understanding of geological formations.

Conclusion

Yuexiang Hao's innovative methods in seismic prediction represent a significant advancement in the field. His work not only contributes to academic research but also has practical implications for the energy sector.