Daoyu Chen

Title: Daoyu Chen and Deep-Learning-Based Seismic Data Processing.

Introduction

Daoyu Chen is an inventor associated with Xi’an Jiaotong University in Shaanxi, China. His patent work addresses the processing of seismic data, with a focus on identifying and removing strong reflection layers using deep learning.

Latest Patents

Chen is credited with 1 patent: “Method of Stripping Strong Reflection Layer Based on Deep Learning.” The method uses a deep neural network’s nonlinear mapping function to establish a direct relationship between strong reflection signals and seismic data from a target work area. After the strong reflection layer is predicted, the method strips it from the data.

The patent describes training the network to identify the relationship between seismic data containing a strong reflection layer and the layer’s seismic event. It also aims to avoid empirical parameter adjustment, relying instead on training samples prepared to reflect the actual conditions of the target work area.

Career Highlights

Chen’s listed invention applies deep learning to a specific challenge in seismic data processing. Its approach is designed to predict strong reflection layers from relevant training data and then remove them from seismic records.

Collaborations

Chen’s listed coworkers include Jinghuai Gao and Yajun Tian. His association with Xi’an Jiaotong University provides the institutional context for his patent work.

Conclusion

Daoyu Chen’s patent presents a deep-learning-based method for predicting and stripping strong reflection layers, with training samples tailored to the conditions of the target work area.