A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma.
- DOI
- 10.1021/acs.est.4c04413
- Published
- 2024 Dec 17
- Container
- Environmental science & technology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1021/acs.est.4c04413,
title = {A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma.},
author = {Ciulla F and Santos A and Jordan P and Kneafsey T and Biraud SC and Varadharajan C},
year = {2024},
journal = {Environmental science \& technology},
doi = {10.1021/acs.est.4c04413},
url = {https://doi.org/10.1021/acs.est.4c04413}
}RIS
TY - JOUR TI - A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma. AU - Ciulla F AU - Santos A AU - Jordan P AU - Kneafsey T AU - Biraud SC AU - Varadharajan C PY - 2024 JO - Environmental science & technology DO - 10.1021/acs.est.4c04413 UR - https://doi.org/10.1021/acs.est.4c04413 ER -
APA
F, C., A, S., P, J., T, K., SC, B., & C, V. (2024). A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma.. Environmental science & technology. https://doi.org/10.1021/acs.est.4c04413
Source records
- pubmed · retrieved 2026-11-10T08:06:40.728Z