[HTML][HTML] Current state and future directions for deep learning based automatic seismic fault interpretation: A systematic review
Automated seismic fault interpretation has been an active area of research. Since 2018,
Deep learning (DL) based seismic fault interpretation methods have emerged and shown …
Deep learning (DL) based seismic fault interpretation methods have emerged and shown …
Machine learning for subsurface geological feature identification from seismic data: Methods, datasets, challenges, and opportunities
Identification of geological features from seismic data such as faults, salt bodies, and
channels, is essential for studies of the shallow Earth, natural disaster forecasting and …
channels, is essential for studies of the shallow Earth, natural disaster forecasting and …
CNN-BiLSTM hybrid neural networks with attention mechanism for well log prediction
Well logging is a significant method of formation description and resource assessment in
exploration and development of oil, natural gas, minerals, groundwater, and sub-surface …
exploration and development of oil, natural gas, minerals, groundwater, and sub-surface …
Imputation of missing well log data by random forest and its uncertainty analysis
Well logs are commonly used by geoscientists to infer and extrapolate physical properties of
subsurface rocks. However, at some depth intervals, well log values might be missing due to …
subsurface rocks. However, at some depth intervals, well log values might be missing due to …
Seismic fault detection using convolutional neural networks with focal loss
Fault detection is a fundamental and important research topic in automatic seismic
interpretation since the geometry of faults usually reveals the accumulation and migration of …
interpretation since the geometry of faults usually reveals the accumulation and migration of …
MTL-FaultNet: Seismic data reconstruction assisted multi-task deep learning 3D fault interpretation
W Wu, Y Yang, B Wu, D Ma, Z Tang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Seismic fault interpretation is of extraordinary significant for hydrocarbon reservoir
characterization and drilling hazard mitigation. In recent years, deep learning-based seismic …
characterization and drilling hazard mitigation. In recent years, deep learning-based seismic …
Geochemical anomaly identification and uncertainty quantification using a Bayesian convolutional neural network model
Geochemical prospecting plays an important role in mineral exploration. In recent years,
deep learning algorithms (DLAs) have been applied in map** geochemical anomalies …
deep learning algorithms (DLAs) have been applied in map** geochemical anomalies …
A reliable Bayesian neural network for the prediction of reservoir thickness with quantified uncertainty
LL Bao, JS Zhang, CX Zhang, R Guo, XL Wei… - Computers & …, 2023 - Elsevier
In seismic exploration, reservoir prediction plays a significant role since it can reveal the
characteristics of a reservoir through attribute analysis. Multi-attribute reservoir prediction …
characteristics of a reservoir through attribute analysis. Multi-attribute reservoir prediction …
Uncertainty estimation in AVO inversion using Bayesian dropout based deep learning
C Junhwan, O Seokmin, B Joongmoo - Journal of Petroleum Science and …, 2022 - Elsevier
Amplitude versus offset (AVO) inversion is the process of transforming seismic reflection into
elastic properties such as P-and S-impedance to estimate the interval properties and …
elastic properties such as P-and S-impedance to estimate the interval properties and …
Data-driven lithology prediction for tight sandstone reservoirs based on new ensemble learning of conventional logs: A demonstration of a Yanchang member, Ordos …
Y Gu, D Zhang, Y Lin, J Ruan, Z Bao - Journal of Petroleum Science and …, 2021 - Elsevier
Lithologies are significant indicators to get deep insight of depositional and mineralogical
properties of target formations, and the classic approach of achieving them is crossplot …
properties of target formations, and the classic approach of achieving them is crossplot …