Principles of seismic stratigraphy and seismic geomorphology I: Extracting geologic insights from seismic data
With the advent of widely available 3D seismic data, numerous workflows focused on
extracting subsurface stratigraphic information have been developed. We present here tools …
extracting subsurface stratigraphic information have been developed. We present here tools …
Successful leveraging of image processing and machine learning in seismic structural interpretation: A review
As a process that identifies geologic structures of interest such as faults, salt domes, or
elements of petroleum systems in general, seismic structural interpretation depends heavily …
elements of petroleum systems in general, seismic structural interpretation depends heavily …
An improved convolutional neural network with an adaptable learning rate towards multi-signal fault diagnosis of hydraulic piston pump
S Tang, Y Zhu, S Yuan - Advanced Engineering Informatics, 2021 - Elsevier
Hydraulic piston pump is a vital component of hydraulic transmission system and plays a
critical role in some modern industrials. On account of the deficiencies of traditional fault …
critical role in some modern industrials. On account of the deficiencies of traditional fault …
ECG arrhythmia classification by using a recurrence plot and convolutional neural network
BM Mathunjwa, YT Lin, CH Lin, MF Abbod… - … Signal Processing and …, 2021 - Elsevier
Cardiovascular diseases affect approximately 50 million people worldwide; thus, heart
disease prevention is one of the most important tasks of any health care system. Despite the …
disease prevention is one of the most important tasks of any health care system. Despite the …
Forecasting method of stock market volatility in time series data based on mixed model of ARIMA and XGBoost
Y Wang, Y Guo - China Communications, 2020 - ieeexplore.ieee.org
Stock price forecasting is an important issue and interesting topic in financial markets.
Because reasonable and accurate forecasts have the potential to generate high economic …
Because reasonable and accurate forecasts have the potential to generate high economic …
Deep learning for seismic lithology prediction
Seismic prediction has been a huge challenge because of the great uncertainties contained
in the seismic data. Deep learning (DL) has been successfully applied in many fields and …
in the seismic data. Deep learning (DL) has been successfully applied in many fields and …
Unsupervised 3-D random noise attenuation using deep skip autoencoder
Effective random noise attenuation is critical for subsequent processing of seismic data,
such as velocity analysis, migration, and inversion. Thus, the removal of seismic random …
such as velocity analysis, migration, and inversion. Thus, the removal of seismic random …
Sparse time-frequency analysis of seismic data: Sparse representation to unrolled optimization
N Liu, Y Lei, R Liu, Y Yang, T Wei… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Time–frequency analysis (TFA) is widely used to describe local time–frequency (TF) features
of seismic data. Among the commonly used TFA tools, sparse TFA (STFA) is an excellent …
of seismic data. Among the commonly used TFA tools, sparse TFA (STFA) is an excellent …
Seismic time–frequency analysis via empirical wavelet transform
Time-frequency analysis is able to reveal the useful information hidden in the seismic data.
The high resolution of the time-frequency representation is of great importance to depict …
The high resolution of the time-frequency representation is of great importance to depict …
[HTML][HTML] Tunnel boring machine vibration-based deep learning for the ground identification of working faces
Tunnel boring machine (TBM) vibration induced by cutting complex ground contains
essential information that can help engineers evaluate the interaction between a cutterhead …
essential information that can help engineers evaluate the interaction between a cutterhead …