Evidence map›Paper›PMID 42461235›Full record

ArticleEnvironmental science & technology2026

Locating Undocumented Wells Using Historical Oil and Gas Exploration Maps: A Case Study in Osage County, Oklahoma.

Jaisree Iyer, Janice Yang, Whitney Kirkendall, Samuel O'Connor, Benjamin Le, Hewei Tang, Andre Santos, Sébastien C Biraud, Fabio Ciulla, Charuleka Varadharajan

Abstract read
In one paragraph

Article in Environmental science & technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jaisree IyerLawrence Livermore National Laboratory , 7000 East Ave., Livermore, California94550, United States.ORCID 0000-0002-1154-3030
Janice YangLawrence Livermore National Laboratory , 7000 East Ave., Livermore, California94550, United States.
Whitney KirkendallLawrence Livermore National Laboratory , 7000 East Ave., Livermore, California94550, United States.
Samuel O'ConnorLawrence Livermore National Laboratory , 7000 East Ave., Livermore, California94550, United States.
Benjamin LeLawrence Livermore National Laboratory , 7000 East Ave., Livermore, California94550, United States.
Hewei TangLawrence Livermore National Laboratory , 7000 East Ave., Livermore, California94550, United States.
Andre SantosLawrence Berkeley National Laboratory , 1 Cyclotron Road, Berkeley, California94720, United States.ORCID 0000-0002-7320-7649
Sébastien C BiraudLawrence Berkeley National Laboratory , 1 Cyclotron Road, Berkeley, California94720, United States.ORCID 0000-0001-7697-933X
Fabio CiullaLawrence Berkeley National Laboratory , 1 Cyclotron Road, Berkeley, California94720, United States.ORCID 0000-0002-2637-1737
Charuleka VaradharajanLawrence Berkeley National Laboratory , 1 Cyclotron Road, Berkeley, California94720, United States.ORCID 0000-0002-4142-3224

Funding

Lawrence Livermore National Laboratory NALivermore Lab Foundation Fellowship Program NAMickey Leland Energy Fellowship NAU.S. Department of Energy NA
6 · The paper itself

Abstract

Undocumented oil and gas wells lack reliable information about their locations and characteristics, making them difficult to identify. These wells can result in unanticipated delays and costs in the development of nearby surface and subsurface resources, and, if improperly plugged, can cause contamination. This study leverages historical petroleum exploration maps to locate such wells, focusing on Osage County, Oklahoma. Two sets of early 20th century oil and gas exploration maps by the United States Geological Survey were georeferenced and analyzed using a computer vision model to detect well symbols. The locations of detected wells were compared to the location of known wells in the database from the Bureau of Indian Affairs Osage Agency to identify potential undocumented wells. The analysis yielded over 500 potential undocumented wells, with dry holes constituting the largest fraction. Field verification confirmed the presence of some undocumented wells. Comparison with prior work revealed limited overlap, underscoring the complementary value of historical oil and gas maps for locating undocumented wells. This approach demonstrates the utility of integrating historical cartographic resources with modern geospatial and machine learning techniques to improve the identification and management of undocumented wells.

Indexed as

Oil and Gas FieldsOklahomaPetroleumPetroleumautomated symbol detectiondry holesforgottengeoreferencinglostoil and gas mapsorphaned wellsunknown or undocumented wellsYOLO

Identifiers

PMID42461235
PMCPMC13449896

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.