Zhaoqi Gao is a prominent inventor based in Xi'an, China. He has made significant contributions to the field of seismic data analysis, holding 2 patents that showcase his innovative approaches. His work focuses on enhancing the accuracy and efficiency of seismic facies identification and inversion methods.

Latest Patents

Zhaoqi Gao's latest patents include an "Automatic seismic facies identification method based on combination of self-attention mechanism and U-shape network architecture." This method involves obtaining and preprocessing post-stack seismic data to construct a sample training and validation dataset. It also includes building an encoder through an overlapped patch merging module with down-sampling function and a self-attention transformer module with global modeling function. Additionally, a decoder is constructed using a patch expanding module with linear upsampling function, the self-attention transformer module, and a skip connection module with multilayer feature fusion function. The seismic facies identification model utilizes these components, including a Hypercolumns-U-Segformer (HUSeg), and incorporates a hybrid loss function for iterative training.

Another notable patent is the "Model-driven deep learning-based seismic super-resolution inversion method." This method maps each iteration of a model-driven alternating direction method of multipliers (ADMM) into each layer of a deep network. It learns proximal operators using a data-driven method to construct a deep network called ADMM-SRINet. The process includes obtaining label data for training, training the deep network, and inverting test data using the trained model. This innovative approach combines model-driven optimization with data-driven deep learning, enhancing the interpretability and reliability of inversion results.

Career Highlights

Zhaoqi Gao is affiliated with Xi'an Jiaotong University, where he contributes to research and development in seismic data analysis. His academic background and research initiatives have positioned him as a leading figure in his field.

Collaborations

Zhaoqi Gao collaborates with esteemed colleagues, including Jinghuai Gao and Hongling Chen, to advance research in seismic technologies. Their combined expertise fosters innovation and enhances the quality of their research outputs.

Conclusion

Zhaoqi Gao's contributions to seismic data analysis through his innovative patents and collaborative efforts highlight his role as a key inventor in this field. His work continues to influence

Profile summary based on public USPTO records.

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