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Record W4405291884 · doi:10.4138/atlgeo.2024.012

Geothermal data from southeastern New Brunswick: implications for potential geothermal energy projects and carbon sequestration in eastern Canada

2024· article· en· W4405291884 on OpenAlexaffabout
Dave Keighley, Joseph DeLuca

Bibliographic record

VenueAtlantic Geoscience · 2024
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of New Brunswick
FundersU.S. Department of Energy
KeywordsGeothermal gradientGeothermal energyGeologyBoreholeEarth scienceGeochemistryPaleontology

Abstract

fetched live from OpenAlex

To date, assessing the feasibility of Enhanced Geothermal Systems (EGS) in New Brunswick has been limited by the lack of information pertaining to geothermal gradients. Existing maps have incorporated less than a dozen datapoints, mostly from dedicated investigations in and adjacent to the central uplands that cross the province from southwest to northeast. To supplement this data, provincial records that report Bottom Hole Temperatures from exploration boreholes have been reviewed and coarsely filtered for dubious data. This process has contributed over 100 additional datapoints in the southeastern half of the province that have been converted to geothermal gradients to supplement previous maps. The updated geothermal map of southeastern New Brunswick indicates that geothermal gradients across the region average ~20.5 K/km, which is below the global average of 25 K/km. Locally, however, potential anomalies exist where geothermal gradients are well above the global average. These anomalies, pending further assessment, are associated with relatively shallow-depth salt intrusions. Elsewhere, the presence of high geothermal conductivity salt deposits has produced “salt chimneys” whereby overlying, near-surface rocks have steeper geothermal gradients than adjacent regions. Accordingly, whereas average values for regional geothermal gradients are not conducive to economic large-scale EGS using current technologies and may also lower the potential for economic sequestration of supercritical CO2, small-scale, lower temperature, shallow, geothermal systems may be feasible in localities associated with salt intrusions, particularly if further analysis supports a “salt-chimney” effect.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.759

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 science0.0010.000
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 head0.031
GPT teacher head0.252
Teacher spread0.222 · 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 designSimulation or modeling
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

Citations2
Published2024
Admission routes2
Has abstractyes

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