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Record W2749446312 · doi:10.1306/eg.0206171600917003

Geothermal energy potential of the Western Canada Sedimentary Basin: Clues from coproduced and injected water

2017· article· en· W2749446312 on OpenAlexaffabout
Grant Ferguson, L. Ufondu

Bibliographic record

VenueEnvironmental Geosciences · 2017
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGeologyGeothermal gradientGeothermal energySedimentary rockStructural basinGeochemistryGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

ABSTRACT Development of geothermal energy in sedimentary basins is an attractive option given the availability of data from the oil and gas industry. Previous geothermal studies in sedimentary basins have focused on temperatures and petrophysical properties. In this study, the focus is placed on historical reservoir performance. In the Western Canada Sedimentary Basin, estimated temperatures and measured fluid production and injection rates at existing wells are combined to provide a per-well estimate of thermal power production. Nearly 700 of these hypothetical geothermal wells would produce 1 MW of power, and a total of 6 GW could be produced if all wells were converted to geothermal wells. Many of these wells may not be suitable for immediate use because of temperature anomalies resulting from injection of cooler water into target strata. Further research is needed to characterize the magnitude and extent of these anomalies. Geothermal potential should also be considered in the development of oil and gas resources in sedimentary basins.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.173
Teacher spread0.168 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations14
Published2017
Admission routes2
Has abstractyes

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