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Record W2052997304 · doi:10.3997/2214-4609.20131615

Regional Simulations of the Well-related Migration Risk at Weyburn, the World’s Largest CO2 Project

2013· article· en· W2052997304 on OpenAlexaboutno aff
Andrew Cavanagh

Bibliographic record

VenueProceedings · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental sciencePopulationPetroleum engineeringGeologyFossil fuelEnhanced oil recoveryHydrology (agriculture)Geotechnical engineeringEngineeringWaste management

Abstract

fetched live from OpenAlex

The IEAGHG Weyburn-Midale CO2 Monitoring and Storage Project is an industrial-scale geological storage project associated with enhanced oil recovery at the Weyburn oil field, Saskatchewan, Canada. To date, over 17 Mt of CO2 has been stored at 1.4 km depth. The storage site and four overlying aquitards are penetrated by a large number of oil wells. The Weyburn region has more than 4,000 wells within a risk assessment area of 2,000 km2. This well density is typical of prospective CCUS storage areas in the USA and Canada. The average well separation is 275 meters, with about 5% of the population less than 20 meters apart. These wells are considered to have an elevated risk potential for leakage pathways above the storage site. The high well density and regional scale presents a major challenge for flow modeling. We use a hydrodynamic invasion percolation approach, assuming capillary limit conditions, to simulate CO2 migration throughout the region at a high resolution. The resolution is sufficient to identify wells that lie along migration pathways and trap structures where leakage may occur. This indicates a subset of 62 wells within the regional population of 4012 wells that are marked for further risk assessment.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.995

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)0.0060.000

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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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 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

Citations1
Published2013
Admission routes1
Has abstractyes

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