1 citations · 1 across the 9 of their papers we have counts for
11 papers
A Review of Deep-learning-based Seismic Data Denoising and Its Promising Paradigm Shift to Foundation Models
Xintong Dong, Zhengyi Yuan, Changxin Wei +3
Denoising is a long-standing and widely-concerned topic in seismic data processing, for it can significantly increase the signal-to-noise ratio of seismic data. Numerous deep learn…
A Frequency-Aware Dynamic Knowledge Distillation Framework: An Effective Tool for Bridging Low- and High-Frequency Seismic Information
Jun Ma, Xinyang Wang, Xintong Dong
Seismic data contain rich information across different frequency bands, with low-frequency components primarily characterizing large-scale geological structures and high-frequency…
Transcending Classical Neural Network Boundaries: A Quantum-Classical Synergistic Paradigm for Seismic Data Processing
Zhengyi Yuan, Xintong Dong, Xinyang Wang +2
In recent years, a number of neural-network (NN) methods have exhibited good performance in seismic data processing, such as denoising, interpolation, and frequency-band extension.…
Light-weighted foundation model for seismic data processing based on representative and non-redundant pre-training dataset
Xintong Dong, Wenshuo Yu, Jun Lin +3
In the fields of computer vision (CV) and remote sensing (RS), foundational models typically follow the "big data + large model parameters" paradigm. However, the application of th…
PreAdaptFWI: Pretrained-Based Adaptive Residual Learning for Full-Waveform Inversion Without Dataset Dependency
Xintong Dong, Zhengyi Yuan, Jun Lin +3
Full-waveform inversion (FWI) is a method that utilizes seismic data to invert the physical parameters of subsurface media by minimizing the difference between simulated and observ…
Transformer for seismic image super-resolution
Shiqi Dong, Xintong Dong, Kaiyuan Zheng +3
Seismic images obtained by stacking or migration are usually characterized as low signal-to-noise ratio (SNR), low dominant frequency and sparse sampling both in depth (or time) an…
Self-Supervised Diffusion Model for 3-D Seismic Data Reconstruction
Xinyang Wang, Qianyu Ge, Xintong Dong +2
Seismic data reconstruction is an effective tool for compensating nonuniform and incomplete seismic geometry. Compared with methods for 2D seismic data, 3D reconstruction methods c…
MAE-GAN: A Novel Strategy for Simultaneous Super-resolution Reconstruction and Denoising of Post-stack Seismic Profile
Wenshuo Yu, Shiqi Dong, Shaoping Lu +1
Post-stack seismic profiles are images reflecting containing geological structures which provides a critical foundation for understanding the distribution of oil and gas resources.…
Transformer For Low-frequency Extrapolating of Seismic Data
Zheng Cong, Xintong Dong, Shaoping Lu +2
Full waveform inversion (FWI) is used to reconstruct the physical properties of subsurface media which plays an important role in seismic exploration. However, the precision of FWI…
Modeling Seismic Wave Propagation in TTI Media Using Residual Perfectly Matched Layer
Yuqin Luo, Xintong Dong, Shiqi Dong +4
The perfectly matched layer(PML) is commonly used in wave propagation, radiation and diffraction problems in unbounded space domains. A new implementation scheme of PML is presente…
Seismic Interpolation Transformer for Consecutively Missing Data: A Case Study in DAS-VSP Data
Ming Cheng, Jun Lin, Xintong Dong +2
Distributed optical fiber acoustic sensing (DAS) is a rapidly-developed seismic acquisition technology with advantages of low cost, high resolution, high sensitivity, and small int…