In recent years, supervised-deep-learning methods have shown some advantages over
conventional methods in seismic data denoising, such as higher signal-to-noise ratio after …

Effective and efficient arrival picking plays an important role in microseismic and earthquake
data processing and imaging. Widely used short-term-average long-term-average ratio …

Seismic background noise often damages the desired signals, thereby resulting in some
artifacts in the seismic imaging that follows. Since about 2016, some supervised-deep …

High-quality seismic data are the basis for stratigraphic imaging and interpretation, but the
existence of random noise can greatly affect the quality of seismic data. At present, most …

Distributed optical fiber acoustic sensing (DAS) is a new and rapid-developing detection
technology in seismic exploration. Unfortunately, due to the weak energy of scattered optical …

The importance of low-frequency seismic data has been already recognized by
geophysicists. However, there are still a number of obstacles that must be overcome for …

Recorded seismic signals are often corrupted by noise. We have developed an automatic
noise-attenuation method for single-channel seismic data, based upon high-resolution time …

Distributed acoustic sensing (DAS) is a new tool with low cost, sensitive signal capture, and
complete coverage for vertical seismic profile (VSP) acquisition. Although DAS has obvious …

Seismic exploration is a kind of exploration method for oil and gas resources. However, the
disturbance of numerous random noise will decrease the quality and signal-to-noise ratio …

Lots of low-frequency noise including random noise and surface waves seriously reduces
the quality of desert seismic data. However, the suppression for desert low-frequency noise …