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Peer-reviewedCC BY-NC-NDEnvironmental science & technology

Improving UAV Magnetic Surveys with a Theory-Guided Empirical Model for Locating and Characterizing Undocumented Orphaned Oil and Gas Wells.

  • Jiannan Wang1
  • Chunwei Chou1
  • Sébastien Biraud1
  • Andre Santos1
  • Hari Viswanathan2
  • Andrew Govert3
  • Yuxin Wu1
  1. 1Lawrence Berkeley National Laboratory , Berkeley, California94720, United States.
  2. 2Los Alamos National Laboratory , Los Alamos, New Mexico87545, United States.
  3. 3Hydrocarbons and Geothermal Energy Office, U.S. Department of Energy, Washington, District of Columbia20585, United States.
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Abstract

Undocumented orphaned oil and gas wells can pose risks through unintended releases of substances, yet they remain difficult to locate because records are incomplete and surface indicators are often absent. Unmanned aerial vehicle (UAV) magnetometry is increasingly used to identify steel-cased wells, but surveys commonly stop at target detection and provide limited guidance on how sensor height affects anomaly strength, burial-depth estimates, or confidence in non-detection. Here, we develop a physics-informed, calibrated empirical model between peak magnetic-anomaly amplitude and distance from the magnetometer to the top of steel casing. Using anomaly amplitude measured at known sensor height, the model provides three practical outputs: estimated casing-top burial depth where casing is not visible, maximum sensor height at which casing at a specified depth remains detectable, and correction of variable-height anomalies to a common reference height. We calibrate the relationship using multi-altitude UAV surveys at Wildcat Canyon Regional Park, California, and Osage Ranch, Oklahoma, and apply it at Hillman State Park, Pennsylvania, identifying one undocumented-well candidate supported by ground magnetometry and estimating burial depths for three documented wells consistent with independent depth constraints.

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Cite

BibTeXRIS
BibTeX
@article{wang2026improving,
  title = {{Improving UAV Magnetic Surveys with a Theory-Guided Empirical Model for Locating and Characterizing Undocumented Orphaned Oil and Gas Wells.}},
  author = {Jiannan Wang and Chunwei Chou and Sébastien Biraud and Andre Santos and Hari Viswanathan and Andrew Govert and Yuxin Wu},
  journal = {Environmental science \& technology},
  year = {2026},
  month = oct,
  doi = {10.1021/acs.est.6c02007},
  url = {https://europepmc.org/article/MED/42899642},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Improving UAV Magnetic Surveys with a Theory-Guided Empirical Model for Locating and Characterizing Undocumented Orphaned Oil and Gas Wells.
AU  - Jiannan Wang
AU  - Chunwei Chou
AU  - Sébastien Biraud
AU  - Andre Santos
AU  - Hari Viswanathan
AU  - Andrew Govert
AU  - Yuxin Wu
PY  - 2026
DA  - 2026/10/01
JO  - Environmental science & technology
DO  - 10.1021/acs.est.6c02007
UR  - https://europepmc.org/article/MED/42899642
AB  - Undocumented orphaned oil and gas wells can pose risks through unintended releases of substances, yet they remain difficult to locate because records are incomplete and surface indicators are often absent. Unmanned aerial vehicle (UAV) magnetometry is increasingly used to identify steel-cased wells, but surveys commonly stop at target detection and provide limited guidance on how sensor height affects anomaly strength, burial-depth estimates, or confidence in non-detection. Here, we develop a physics-informed, calibrated empirical model between peak magnetic-anomaly amplitude and distance from the magnetometer to the top of steel casing. Using anomaly amplitude measured at known sensor height, the model provides three practical outputs: estimated casing-top burial depth where casing is not visible, maximum sensor height at which casing at a specified depth remains detectable, and correction of variable-height anomalies to a common reference height. We calibrate the relationship using multi-altitude UAV surveys at Wildcat Canyon Regional Park, California, and Osage Ranch, Oklahoma, and apply it at Hillman State Park, Pennsylvania, identifying one undocumented-well candidate supported by ground magnetometry and estimating burial depths for three documented wells consistent with independent depth constraints.
SN  - 0013-936X
SN  - 1520-5851
ER  -