[PDF][PDF] An overview of content-based image retrieval methods and techniques
Numerous devices for image capture have emerged in the digital environment of the present
day. Using image processing techniques, it is now easier than ever to store a large number …
day. Using image processing techniques, it is now easier than ever to store a large number …
Hybrid machine learning models for estimating total organic carbon from mineral constituents in core samples of shale gas fields
CM Saporetti, DL Fonseca, LC Oliveira… - Marine and Petroleum …, 2022 - Elsevier
The analysis of total organic carbon (TOC) contents is an important activity in exploring
potentially hydrocarbon-generating intervals. Petroleum source rocks have, by definition …
potentially hydrocarbon-generating intervals. Petroleum source rocks have, by definition …
NMR log response prediction from conventional petrophysical logs with XGBoost-PSO framework
A combined approach that exploits both the eXtreme Gradient Boosting (XGBoost) method
and the Particle Swarm Optimization (PSO) method was used here to predict the nuclear …
and the Particle Swarm Optimization (PSO) method was used here to predict the nuclear …
[HTML][HTML] Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields
Rock samples' TOC content is the best indicator of the organic matter in source rocks. The
origin rock samples' analysis is used to calculate it manually by specialists. This method …
origin rock samples' analysis is used to calculate it manually by specialists. This method …
Approaches for the short-term prediction of natural daily streamflows using hybrid machine learning enhanced with grey wolf optimization
AD Martinho, CM Saporetti, L Goliatt - Hydrological Sciences …, 2023 - Taylor & Francis
This paper presents the development of hybrid machine learning models to forecast the
natural flows of water bodies. Five models were considered under the analysis: extreme …
natural flows of water bodies. Five models were considered under the analysis: extreme …
[HTML][HTML] Enhancing lithofacies machine learning predictions with gamma-ray attributes for boreholes with limited diversity of recorded well logs
DA Wood - Artificial Intelligence in Geosciences, 2021 - Elsevier
Derivative and volatility attributes can be usefully calculated from recorded gamma ray (GR)
data to enhance lithofacies classification in wellbores penetrating multiple lithologies. Such …
data to enhance lithofacies classification in wellbores penetrating multiple lithologies. Such …
Carbonate/siliciclastic lithofacies classification aided by well-log derivative, volatility and sequence boundary attributes combined with machine learning
DA Wood - Earth Science Informatics, 2022 - Springer
Derivative and volatility attributes calculated for well-log versus depth sequences extract
characteristics that can be usefully exploited by automated machine-learning (ML) …
characteristics that can be usefully exploited by automated machine-learning (ML) …
CE-SGAN: Classification enhancement semi-supervised generative adversarial network for lithology identification
F Zhao, Y Yang, J Kang, X Li - Geoenergy Science and Engineering, 2023 - Elsevier
Lithology identification, the process of recognizing and distinguishing lithology using specific
methods, is a fundamental task in the fields of formation evaluation and reservoir …
methods, is a fundamental task in the fields of formation evaluation and reservoir …
STNet: Advancing Lithology Identification with a Spatiotemporal Deep Learning Framework for Well Logging Data
Q Pang, C Chen, Y Sun, S Pang - Natural Resources Research, 2024 - Springer
In the realm of oil and gas exploration, accurate identification of lithology is imperative for the
assessment of resources and the refinement of extraction strategies. While artificial …
assessment of resources and the refinement of extraction strategies. While artificial …
Well log analysis and comparison of supervised machine learning algorithms for lithofacies identification in pab formation, lower indus basin
Abstract Machine learning uses higher-order statistical computation for model prediction by
combining statistics with advanced algorithms. These predictions can be used to infer the …
combining statistics with advanced algorithms. These predictions can be used to infer the …