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Record W4378229469 · doi:10.3997/2214-4609.2023101146

Geostorage for CCS and Renewable Energy in Eastern Canada- North Sea Scale Opportunities

2023· article· en· W4378229469 on OpenAlexaffabout
Grant Wach, Bill Richards, D.R. Brown, T. Kelly, K. Martyns-Yellowe, L. Morris, C. Skinner, Denise O’Connor

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEnvironmental scienceRenewable energyGreenhouse gasGeologyEngineeringOceanography

Abstract

fetched live from OpenAlex

Summary Geostorage for CCS and Renewable Energy in Eastern Canada- Lessons for the World Eastern Canada has considerable potential for Geostorage of CO2, for compressed air storage, and storage of hydrogen onshore and offshore. The storage of CO2 will reduce accumulations of CO2 in the Earth’s atmosphere and help mitigate toxic atmospheric greenhouse gas emissions. Compressed air storage and the storage of hydrogen are linked to the increased production of renewable energy, particularly through electricity generated from wind turbines. Storage is the key to make renewable electricity both dispatchable and of high quality. Dynamic simulation models of CO2 and methane were completed for outcrops of Triassic braid channels, highlighting stratigraphic and diagenetic influence on fluid flow over 120 months. A geocellular model of Mesozoic deltaic sands from offshore Nova Scotia for 10 years. Economics show that a typical Sable production well (100 BCF) would be worth more as a geostorage well for CO2, assuming greenhouse gas tax at $100/t, than as a gas well. Injection of sour (H2S) gas from the Deep Panuke operations into the Sable field prove that an effective CO2 storage system. The Margin has potential for $30 billion in revenue – with costs <$10–20 billion.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score1.000

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)0.0010.000

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 head0.037
GPT teacher head0.231
Teacher spread0.194 · 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.

Study designNot applicable
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

Citations1
Published2023
Admission routes2
Has abstractyes

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