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Record W2183719660

Evaluation of geothermal energy as a heat source for the oilsands industry in Northern Alberta (Canada)

2012· article· en· W2183719660 on OpenAlexaboutno aff
Jacek Majorowicz, Martyn Unsworth, Allan W. Gray, Greg Nieuwenhuis, Tayfun Babadagli, Nathaniel John Walsh, Simon Weides, R. Verveda

Bibliographic record

VenueAGU Fall Meeting Abstracts · 2012
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPrecambrianGeologyGeothermal gradientBasementGeothermal energySedimentary rockGeochemistryNatural gasPetroleum engineeringMineralogyPetrologyGeomorphologyArchaeologyEngineeringPaleontologyWaste managementGeography
DOInot available

Abstract

fetched live from OpenAlex

•Athabasca oilsands : Temperatures > 60°C will only be found in Precambrian basement (granite) at depth in excess of 3km. Heat needed for extraction and processing. Calculations considered the thermal output of an EGS doublet system producing water at 100°C and included energy needed to operate pumps. This system produces net energy when the flow rate is greater than >30l /s. The financial cost is comparable with the cost of burning natural gas if flow rates are greater than 50llitres per second and if the system operates for at least 30 years. 100 EGS doublets drawing water at 100oC from wells in the deep sedimentary basin or granitic basement could save >3MT of CO2 per year. Current oilsands operations generate 40MT of CO2 per year. Introduction

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.270
Teacher spread0.244 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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