Noise exposure has reached an alarming degree over the years because of rapid growth in
the industry, transportation, and urbanization. Therefore, it is a dire need to provide …

Predictive filtering (PF) in the frequency domain is one of the most widely used denoising
algorithms in seismic data processing. PF is based on the assumption of linear or planar …

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 …

We proposed a novel wavelet threshold denoising method based on the discrete wavelet
transform for noisy microseismic recordings. This algorithm can simultaneously suppress …

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 …

Carbonate reservoirs are typically characterized by low reservoir property values. In such
conditions, economically viable oil production is achieved by carrying out stimulation …

A microseismic (MS) monitoring system in a mine can monitor the MS signals generated by
coal rock rupture and blasting waves and can distinguish the two types of waves more …

Microseismic data recorded by surface arrays are often strongly contaminated by unwanted
noise. This background noise makes the detection of small magnitude events difficult. A …

We propose a novel approach for removing noise from multiple reflections based on an
adaptive randomized-order empirical mode decomposition (EMD) framework. We first flatten …

Microseismic data have a low signal-to-noise ratio (S/N). Existing waveform classification
and arrival-picking methods are not effective enough for noisy microseismic data with low …