The Cadzow rank-reduction method can be effectively utilized in simultaneously denoising
and reconstructing 5-D seismic data that depend on four spatial dimensions. The classic …

We propose to denoise and reconstruct the 3D seismic data simultaneously using an
unsupervised deep learning (DL) framework, which does not require any prior information …

As a major concern, the existence of unwanted energy and missing traces in seismic data
acquisition can degrade interpretation of such data after processing. Instead of analytical …

The seislet transform uses a prediction operator that is connected to the local slope or
frequency of seismic events. We have combined the 1D nonstationary seislet transform with …

The low-rank approximation method is one of the most effective approaches recently
proposed for attenuating random noise in seismic data. However, the low-rank …

Simultaneous seismic data denoising and reconstruction is a currently popular research
subject in modern reflection seismology. Traditional rank-reduction based 3D seismic data …

Prestack seismic inversion can be regarded as an optimization problem, which minimizes
the error between the observed and synthetic data under the premise of certain geological …

A sparse dictionary is more adaptive than a sparse fixed-basis transform since it can learn
the features directly from the input data in a data-driven way. However, learning a sparse …

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 …

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