In recent years, sparse representation is seeing increasing application to fundamental signal
and image-processing tasks. In sparse representation, a signal can be expressed as a linear …

Noise attenuation plays an important role in seismic data processing. We propose a novel
denoising method for seismic data based on unsupervised sparse feature learning. Our goal …

Automatic arrival picking of certain seismic or microseismic phases has been studied for
decades. However, automatic detection of continuous signal waveforms has been seldom …

In seismic data processing, the median filter is usually applied along the structural direction
of seismic data in order to attenuate erratic or spike-like noise. The performance of a …

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 …

Reverse-time migration (RTM) has the particular capacity for complex geological structure
imaging. However, massive storage and high computational costs caused by conventional …

As full-waveform inversion (FWI) is a nonunique and typically ill-posed inversion problem, it
needs proper regularization to avoid cycle skipping. To reduce the nonlinearity of FWI, we …

Microseismic methods are crucial for real-time monitoring of the hydraulic fracturing dynamic
status during the development of unconventional reservoirs. However, unlike the active …

Microseismic data processing and imaging are crucial for subsurface real-time monitoring
during hydraulic fracturing process. Unlike the active-source seismic events or large-scale …

Attenuation of noise in seismic data is a crucial and difficult task in analyzing seismic data.
We propose a new noise suppression algorithm in which the noise can be suppressed; …