Comparison of supervised and unsupervised approaches for mudstone lithofacies classification: Case studies from the Bakken and Mahantango-Marcellus Shale …
Quantitative lithofacies modeling is important to understand the depositional and diagenetic
history, and hydrocarbon potential of unconventional resources at a regional scale. The …
history, and hydrocarbon potential of unconventional resources at a regional scale. The …
Machine learning algorithms for lithofacies classification of the gulong shale from the Songliao Basin, China
Lithofacies identification and classification are critical for characterizing the hydrocarbon
potential of unconventional resources. Although extensive applications of machine learning …
potential of unconventional resources. Although extensive applications of machine learning …
[图书][B] A primer on machine learning in subsurface geosciences
S Bhattacharya - 2021 - Springer
The application of traditional machine learning and emerging deep learning algorithms in
subsurface geosciences is now a hot topic. The advent of big data analytics is changing the …
subsurface geosciences is now a hot topic. The advent of big data analytics is changing the …
Hydrocarbon distribution pattern and logging identification in lacustrine fine-grained sedimentary rocks of the Permian Lucaogou Formation from the Santanghu basin
G Liu, B Liu, Z Huang, Z Chen, Z Jiang, X Guo, T Li… - Fuel, 2018 - Elsevier
A series of qualitative descriptions and quantitative analyses was used to determine the
lithofacies characteristics and hydrocarbon distribution pattern of Lucaogou Formation fine …
lithofacies characteristics and hydrocarbon distribution pattern of Lucaogou Formation fine …
Longmaxi-Wufeng Shale lithofacies identification and 3-D modeling in the northern Fuling gas field, Sichuan Basin
G Wang, Y Ju, C Huang, S Long, Y Peng - Journal of Natural Gas Science …, 2017 - Elsevier
Mineral composition and total organic carbon (TOC) content of shale is related with rock
brittleness and gas content, respectively. Shale lithofacies defined by them can effectively …
brittleness and gas content, respectively. Shale lithofacies defined by them can effectively …
Summarized applications of machine learning in subsurface geosciences
S Bhattacharya - A Primer on Machine Learning in Subsurface …, 2021 - Springer
Geoscientists have been implementing machine learning (ML) algorithms for several
classifications and regression related problems in the last few decades. ML's …
classifications and regression related problems in the last few decades. ML's …