7 papers
Latent Variable-Mediated Cross-Learning for Few-Shot Acoustic Impedance Imaging
Junheng Peng, Yong Li, Mingwei Wang +1
Acoustic impedance imaging is a fundamental yet severely ill-posed problem in subsurface analysis: the seismic wavelet is unknown, observations are band-limited, and labeled well-l…
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…
Physics-Informed Cross-Learning for Seismic Acoustic Impedance Inversion and Wavelet Extraction
Junheng Peng, Xiaowen Wang, Yingtian Liu +2
Seismic acoustic impedance inversion is one of the most challenging tasks in geophysical exploration. Many studies have proposed the use of deep learning for processing; however, m…
Encoder-Inverter Framework for Seismic Acoustic Impedance Inversion
Junheng Peng, Yingtian Liu, Xiaowen Wang +2
Seismic acoustic impedance inversion is a challenging problem in geophysical exploration, primarily due to the scarcity of well-logging data and the inherent nonlinearity of the ta…
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…
Strong noise attenuation of seismic data based on Nash equilibrium
Mingwei Wang, Yingtian Liu, Junheng Peng +2
Seismic data acquisition is often affected by various types of noise, which degrade data quality and hinder subsequent interpretation. Recovery of seismic data becomes particularly…