Seismic data interpolation is a longstanding issue. Most current methods are only suitable
for randomly missing cases. To deal with regularly missing cases, an antialiasing strategy …

The trace interval in the common shot and receiver gathers is always inconsistent. The
inconsistency affects the final performance of seismic data processing, and the …

Multichannel singular spectrum analysis (MSSA) is an effective tool for processing
multidimensional time-series such as the reconstruction of high-dimensional seismic data …

We have determined an approach for simultaneous reconstruction and denoising of 3D
seismic data with randomly missing traces. The core in simultaneous reconstruction and …

Seismic studies exhibit gaps in the recorded data due to surface obstacles. To fill in the gaps
with self-supervised deep learning, the network learns to predict different events from the …

Strong noise in seismic data seriously affects many steps in seismic data processing and
imaging. While most traditional methods depend on carefully tuned input parameters by …

Data mining and analysis are critical for preventing or mitigating natural hazards. However,
data availability in natural hazard analysis is experiencing unprecedented challenges due to …

Full waveform inversion (FWI) is a promising technique for inverting a high-resolution
subsurface velocity model. The success of FWI highly depends on a fairly well initial velocity …

A real-world signal is always corrupted with noise. The separation between a signal and
noise is an indispensable step in a variety of signal-analysis applications across different …

The high-order Radon transform is adopted to eliminate incoherent noise that appears in
common receiver gathers when simultaneous source data are acquired. An iterative scheme …