Literature review on deep learning for the segmentation of seismic images
BAA Monteiro, GL Canguçu, LMS Jorge, RH Vareto… - Earth-Science …, 2024 - Elsevier
This systematic literature review provides a comprehensive overview of the current state of
deep learning (DL) specifically targeted at semantic segmentation in seismic data, with a …
deep learning (DL) specifically targeted at semantic segmentation in seismic data, with a …
Seismic stratigraphic interpretation based on deep active learning
Seismic stratigraphic interpretation plays an important role in geophysics and geosciences.
Recently, deep learning has been explored for seismic stratigraphic interpretation. However …
Recently, deep learning has been explored for seismic stratigraphic interpretation. However …
Semi-supervised seismic stratigraphic interpretation constrained by spatial structure
Seismic stratigraphic interpretation plays an important role in geophysics and geoscience.
Recently, deep learning has been widely applied to seismic stratigraphic interpretation …
Recently, deep learning has been widely applied to seismic stratigraphic interpretation …
Unsupervised Seismic Facies Deep Clustering Via Lognormal Mixture-Based Variational Autoencoder
H Hua, F Qian, G Zhang, Y Yue - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
Seismic facies analysis (SFA) is a crucial step in the interpretation of subsurface structures,
with the core challenge being the development of automatic approaches for the analysis of …
with the core challenge being the development of automatic approaches for the analysis of …
Geology-constrained dynamic graph convolutional networks for seismic facies classification
Knowing a land's facies type before drilling is an essential step in oil exploration. In seismic
surveying, subsurface images are analyzed to segment and classify the facies in that …
surveying, subsurface images are analyzed to segment and classify the facies in that …
Self-supervised learning for efficient seismic facies classification
K Chikhaoui, M Alfarraj - Geophysics, 2024 - library.seg.org
Seismic facies classification is an important task in seismic interpretation that allows the
identification of rock bodies with similar physical characteristics. Manual labeling of seismic …
identification of rock bodies with similar physical characteristics. Manual labeling of seismic …
Resolution enhancement for a seismic velocity model using machine learning
To address complex subsurface structures, a high-resolution velocity model must be
constructed. Conventionally, algorithms such as full waveform inversion (FWI) have been …
constructed. Conventionally, algorithms such as full waveform inversion (FWI) have been …
KG-Unet: a knowledge-guided deep learning approach for seismic facies segmentation
XY Zhang, WL Wang, GM Hu, XM Yao - Earth Science Informatics, 2024 - Springer
The accurate segmentation of seismic facies is of great significance to the study of
sedimentary facies and the exploration and development of oil and gas resources. In recent …
sedimentary facies and the exploration and development of oil and gas resources. In recent …
Accurate identification of salt domes using deep learning techniques: Transformers, generative artificial intelligence and liquid state machines
K Souadih, A Mohammedi… - Geophysical …, 2024 - Wiley Online Library
Across various global regions abundant in oil and natural gas reserves, the presence of
substantial sub‐surface salt deposits holds significant relevance. Accurate identification of …
substantial sub‐surface salt deposits holds significant relevance. Accurate identification of …
[HTML][HTML] Determining the Level of Threat in Maritime Navigation Based on the Detection of Small Floating Objects with Deep Neural Networks
M Łącki - Sensors, 2024 - mdpi.com
The article describes the use of deep neural networks to detect small floating objects located
in a vessel's path. The research aimed to evaluate the performance of deep neural networks …
in a vessel's path. The research aimed to evaluate the performance of deep neural networks …