Deep learning reservoir porosity prediction based on multilayer long short-term memory network

W Chen, L Yang, B Zha, M Zhang, Y Chen - Geophysics, 2020 - library.seg.org
The cost of obtaining a complete porosity value using traditional coring methods is relatively
high, and as the drilling depth increases, the difficulty of obtaining the porosity value also …

Improving the signal‐to‐noise ratio of seismological datasets by unsupervised machine learning

Y Chen, M Zhang, M Bai… - Seismological …, 2019 - pubs.geoscienceworld.org
Seismic waves that are recorded by near‐surface sensors are usually disturbed by strong
noise. Hence, the recorded seismic data are sometimes of poor quality; this phenomenon …

Random noise attenuation based on residual convolutional neural network in seismic datasets

L Yang, W Chen, W Liu, B Zha, L Zhu - Ieee Access, 2020 - ieeexplore.ieee.org
Seismic random noise attenuation is a key step in seismic data processing. The random
seismic data recorded by the detector tends to have strong noise, and this noisy seismic …

Dictionary learning based on dip patch selection training for random noise attenuation

S Zu, H Zhou, R Wu, M Jiang, Y Chen - Geophysics, 2019 - library.seg.org
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 …

Fast waveform detection for microseismic imaging using unsupervised machine learning

Y Chen - Geophysical Journal International, 2018 - academic.oup.com
Automatic arrival picking of certain seismic or microseismic phases has been studied for
decades. However, automatic detection of continuous signal waveforms has been seldom …

Deblending of simultaneous source data using a structure-oriented space-varying median filter

Y Chen, S Zu, Y Wang, X Chen - Geophysical Journal …, 2020 - academic.oup.com
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 …

High-order directional total variation for seismic noise attenuation

X Liu, Q Li, C Yuan, J Li, X Chen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
High-amplitude noise could interfere with useful seismic signals, affecting our ability in
processing and interpreting seismic data. Thus, attenuating seismic noise is an important …

Full-waveform inversion and joint migration inversion with an automatic directional total variation constraint

S Qu, E Verschuur, Y Chen - Geophysics, 2019 - library.seg.org
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 …

An anti-aliasing POCS interpolation method for regularly undersampled seismic data using curvelet transform

H Zhang, H Zhang, J Zhang, Y Hao, B Wang - Journal of Applied …, 2020 - Elsevier
Seismic data interpolation are considered the key step in data pre-processing. Most current
interpolation methods are just suitable for random undersampled cases. To deal with regular …

Automatic high-resolution microseismic event detection via supervised machine learning

S Qu, Z Guan, E Verschuur, Y Chen - 2019 - academic.oup.com
Microseismic methods are crucial for real-time monitoring of the hydraulic fracturing dynamic
status during the development of unconventional reservoirs. However, unlike the active …