Enhancing machine learning-based seismic facies classification through attribute selection: application to 3D seismic data from the Malay and Sabah Basins, offshore Malaysia-Reference-Cited by-同舟云学术

Enhancing machine learning-based seismic facies classification through attribute selection: application to 3D seismic data from the Malay and Sabah Basins, offshore Malaysia

Published:2024-08-12 Issue:1 Volume:10 Page:
ISSN:2363-8419
Container-title:Geomechanics and Geophysics for Geo-Energy and Geo-Resources
language:en
Short-container-title:Geomech. Geophys. Geo-energ. Geo-resour.

Author:

Babikir Ismailalwali,Abdul Latiff Abdul Halim,Elsaadany Mohamed,Pratama Hadyan,Sajid Muhammad,Mad Sahad Salbiah,Ishak Muhammad Anwar,Laudon Carolan

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s40948-024-00846-x.pdf

Reference47 articles.

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2. Al-Masgari AAS, Elsaadany M, Siddiqui NA, Abdul Latiff AH, Bakar AA, Elkurdy S, Hermana M, Babikir I, Imran QS, Adeleke T (2021) Geomorphological geometries and high-resolution seismic sequence stratigraphy of Malay basin’s fluvial succession. Appl Sci 11:1–29

3. Babikir I, Elsaadany M (2024) Machine learning-based seismic characterization of deepwater turbidites in the Dangerous Grounds area, Northwest Sabah, offshore Malaysia. Acta Geophys. https://doi.org/10.1007/s11600-024-01396-2

4. Babikir IAM, Salim AMA, Ghosh DP (2019) Lithogeomorphological facies analysis of Upper Miocene coal-prone fluviodeltaic reservoirs, Northern Malay Basin. Interpretation 7(3):T565–T579

5. Babikir I, Elsaadany M, Sajid M, Laudon C (2022b) Evaluation of principal component analysis for reducing seismic attributes dimensions: implication for supervised seismic facies classification of a fluvial reservoir from the Malay Basin, Offshore Malaysia. J Petrol Sci Eng 217(August):110911. https://doi.org/10.1016/j.petrol.2022.110911