Seismic stratigraphy interpretation via deep convolutional neural networks: A semi-supervised approa
To improving the performance of deep learning algorithms on seismic interpretation from a small amount of training data, this study...
GeoPy: A simple tool for Seismic in Python
Machine learning has been well recognized for subsurface data analysis in E&P. While the state-of-the-art ML algorithms have been...
Building a global seismic texture interpretation network
The primary goal of seismic interpretation is to understand seismic signals, categorize them into various patterns, connect each pattern...
Real-time seismic image interpretation via deconvolutional neural network
To address the limitation of low efficiency for classifying seismic features from large datasets, this study aims at implementing the...
Why using CNN for seismic interpretation? An investigation
This study first applies two most popular neural network frameworks, the multi-layer perceptron (MLP) network and the convolutional...
Seismic fault detection from post-stack amplitude by convolutional neural networks
This study aims at implementing popular CNN tool for the purpose of seismic fault detection, which is superior in two ways compared to...
Machine/deep learning-based seismic interpretation: An example of salt-body delineation
With the growing complexity of seismic data in both size and resolution, more efficient, accurate, and effective seismic interpretation...