10 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…
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…
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…
Semi-Supervised Learning for AVO Inversion with Strong Spatial Feature Constraints
Yingtian Liu, Yong Li, Junheng Peng +1
One-dimensional convolution is a widely used deep learning technique in prestack amplitude variation with offset (AVO) inversion; however, it lacks lateral continuity. Although two…
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…