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Record W4408932308 · doi:10.1088/1748-9326/adc6a0

Renewable energy production potential of abandoned and orphaned oil and gas wells and sites

2025· article· en· W4408932308 on OpenAlexafffundabout
Jade Boutot, Mary Kang

Bibliographic record

VenueEnvironmental Research Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsMcGill University
FundersEnvironment and Climate Change CanadaNatural Sciences and Engineering Research Council of CanadaFaculty of Engineering, McGill University
KeywordsRenewable energyFossil fuelProduction (economics)Natural resource economicsEnvironmental scienceEconomicsWaste managementEcologyEngineeringBiology

Abstract

fetched live from OpenAlex

Abstract Abandoned and orphaned oil and gas well sites may be repurposed for wind and solar energy, while the wells themselves can be redeveloped for geothermal energy production. We estimate the total number of abandoned and orphaned wells in Canada and the United States to be 3,485,480 of which 4% are orphaned and in need of government funding. When normalized by today’s oil production, the United States has twice the number of abandoned and orphaned wells compared to Canada. Across Canada and the United States, we find more than 15,000 gigawatt of wind capacity and 7 gigawatt of solar capacity at abandoned and orphaned well sites. More than 90% of abandoned and orphaned wells with available depth are better suited for shallow geothermal systems and heating applications, yet deep geothermal is possible at up to 10% of the wells. Repurposing oil and gas wells can help fulfill national energy transition goals and emission reduction targets, while providing an additional funding stream to manage their environmental risks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.254
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes3
Has abstractyes

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