Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data
- DOI
- 10.1038/s41598-025-89199-3
- Published
- 2025-07-09
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-89199-3,
title = {Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data},
author = {Abu Bakker Siddique and Tanveer Alam Munshi and Nazmul Islam Rakin and Mahamudul Hashan and Sushmita Sarker Chnapa and Labiba Nusrat Jahan},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-89199-3},
url = {https://doi.org/10.1038/s41598-025-89199-3}
}RIS
TY - JOUR TI - Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data AU - Abu Bakker Siddique AU - Tanveer Alam Munshi AU - Nazmul Islam Rakin AU - Mahamudul Hashan AU - Sushmita Sarker Chnapa AU - Labiba Nusrat Jahan PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-89199-3 UR - https://doi.org/10.1038/s41598-025-89199-3 ER -
APA
Siddique, A. B., Munshi, T. A., Rakin, N. I., Hashan, M., Chnapa, S. S., & Jahan, L. N. (2025). Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data. Scientific Reports. https://doi.org/10.1038/s41598-025-89199-3
Source records
- crossref · retrieved 2026-09-27T02:56:40.593Z