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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data

Crossref DOI link: https://doi.org/10.1038/s41598-025-89199-3

Published Online: 2025-07-09

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Siddique, Abu Bakker

Munshi, Tanveer Alam

Rakin, Nazmul Islam

Hashan, Mahamudul

Chnapa, Sushmita Sarker

Jahan, Labiba Nusrat
Funding

Funding for this research was provided by:

Shahjalal University of Science and Technology (SUST) Research Center
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Text and Data Mining valid from 2025-07-09

Version of Record valid from 2025-07-09
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Article History

Received: 6 November 2024

Accepted: 3 February 2025

First Online: 9 July 2025

Competing interests

: The authors declare no competing interests.

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