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Record W3091540880 · doi:10.11575/prism/38299

Business Case for Geothermal Energy Development to power LNG Project in BC

2020· article· en· W3091540880 on OpenAlexaboutno aff
Yaqub Adepoju

Bibliographic record

VenueOpen MIND · 2020
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsGeothermal energyGeothermal gradientPetroleum engineeringEngineeringGeology

Abstract

fetched live from OpenAlex

Geological uncertainties of the Mount Meager volcanic complex in British Columbia, Canada, are analyzed to evaluate the economic viability of a geothermal power plant. This study utilizes empirical petrophysical formulas combined with field data to estimate geologic properties, including rock porosity and permeability. Flow rate, outlet pressure and temperature for three different conceptual flow models, two types of closed loop systems and one open loop system, were simulated. An economic analysis was carried out to understand the impact of rock permeability uncertainty and geothermal aquifer temperature on technical feasibility and economics viability of a geothermal power plant the complex. This study found that Enhanced Geothermal System (EGS) implementation can deliver a mass flow rate of up to 63kg/sec of 197oC fluid from the subsurface in the study area. Sensitivity analyses suggests that permeability is critical for the project economics. De-risking rock permeability with further research and reducing well costs will improve the economic viability of geothermal resource development in British Columbia and should be pursued further.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.372
Threshold uncertainty score0.749

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.056
GPT teacher head0.335
Teacher spread0.279 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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