Accurate and real-time sea surface salinity (SSS) prediction is an elemental part of marine
environmental monitoring. It is believed that the intrinsic correlation and patterns of historical …

Blended acquisition is still open to improve the efficiency of seismic data acquisition.
Deblending is an essential procedure to provide separated gathers for subsequent …

Deep-learning (DL) methods have recently been introduced for seismic signal processing.
Using DL methods, many researchers have adopted these novel techniques in an attempt to …

Acquisition of incomplete data, ie, blended, sparsely sampled, and narrowband data, allows
for cost-effective and efficient field seismic operations. This strategy becomes technically …

In inverse problems, uncertainty quantification (UQ) deals with a probabilistic description of
the solution nonuniqueness and data noise sensitivity. Setting seismic imaging into a …

It is well known that source deghosting can best be applied to common-receiver gathers,
whereas receiver deghosting can best be applied to common-shot records. The source …

Distributed acoustic sensing in vertical seismic profile (DAS-VSP) acquisition plays an
important role in reservoir monitoring. But the field data can be noisy and associated with …

Incorporating prior knowledge on model unknowns of interest is essential when dealing with
ill-posed inverse problems due to the nonuniqueness of the solution and data noise …

Seismic data go through a sequence of pre-processing steps before being made into an
image. Although some work has been done to assess the uncertainties in the final images …

Among the many promising applications of deep learning technology, one is in the area of
seismic data processing, including trace interpolation. Convolutional neural network (CNN) …