Unsupervised deep learning framework for early detection of wellbore trajectory deviation in drilling operations.

Singh P, Vickram B, Benny A, Mariyam K, Dan S, Harishwaran R, Kumar BN, Abdullah MA

DOI: 10.3389/frai.2026.1942787
Published: 2026
Container: Frontiers in artificial intelligence
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2026.1942787,
  title = {Unsupervised deep learning framework for early detection of wellbore trajectory deviation in drilling operations.},
  author = {Singh P and Vickram B and Benny A and Mariyam K and Dan S and Harishwaran R and Kumar BN and Abdullah MA},
  year = {2026},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2026.1942787},
  url = {https://doi.org/10.3389/frai.2026.1942787}
}

RIS

TY  - JOUR
TI  - Unsupervised deep learning framework for early detection of wellbore trajectory deviation in drilling operations.
AU  - Singh P
AU  - Vickram B
AU  - Benny A
AU  - Mariyam K
AU  - Dan S
AU  - Harishwaran R
AU  - Kumar BN
AU  - Abdullah MA
PY  - 2026
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2026.1942787
UR  - https://doi.org/10.3389/frai.2026.1942787
ER  -

APA

P, S., B, V., A, B., K, M., S, D., R, H., BN, K., & MA, A. (2026). Unsupervised deep learning framework for early detection of wellbore trajectory deviation in drilling operations.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2026.1942787

Source records

pubmed · retrieved 2026-09-25T10:08:26.801Z