5 papers · 1 filter
An Efficient Self-supervised Seismic Data Reconstruction Method Based on Self-Consistency Learning
Mingwei Wang, Junheng Peng, Yingtian Liu +1
Seismic exploration remains the most critical method for characterizing subsurface structures in geophysics. However, complex surface conditions often cause a non-uniform distribut…
Prior-Driven Self-Supervised Lightweight Method for Seismic Signal Denoising
Junheng Peng, Yong Li, Yingtian LIu +1
Seismic exploration is currently the most mature approach for studying subsurface structures, yet the presence of noise greatly restricts its imaging accuracy. Previous methods sti…
DCMSA: Multi-Head Self-Attention Mechanism Based on Deformable Convolution For Seismic Data Denoising
Wang Mingwei, Li Yong, Liu Yingtian +2
When dealing with seismic data, diffusion models often face challenges in adequately capturing local features and expressing spatial relationships. This limitation makes it difficu…
High-resolution closed-loop seismic inversion network in time-frequency phase mixed domain
Yingtian Liu, Yong Li, Junheng Peng +2
Thin layers and reservoirs may be concealed in areas of low seismic reflection amplitude, making them difficult to recognize. Deep learning (DL) techniques provide new opportunitie…
The Nash-MTL-STCN Method For Prestack Three-Parameter Inversion
Yingtian Liu, Yong Li, Huating Li +3
Deep learning (DL) techniques have been widely used in prestack three-parameter inversion to address its ill-posed problems. Among these DL techniques, Multi-task learning (MTL) me…