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Record W2549581297

Overpressure conditions and reservoir compartmentalization on the Scotian Margin

2013· article· en· W2549581297 on OpenAlexaff
Carla Dickson, Nova Scotia, Grant Wach

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOverpressureGeologyMargin (machine learning)Hydrostatic pressureMechanics
DOInot available

Abstract

fetched live from OpenAlex

Overpressure has been identified as a serious risk element in several offshore basins around the world including the Scotian margin; it has been mapped on the Scotian margin at a low resolution but the causes for overpressure have not been resolved. Previous work (Yassir and Bell, 1994; Wade, MacLean and Williams 1995; Wielens 2003; Play Fairway Analysis 2012) indicated overpressure on the Scotian margin was variable and not readily predictable. Negative aspects and unknowns of overpressure are it can occur with similar magnitude at varying depth in wells in the same field, and may not be related to specific formations or burial depths, formation temperature and hydrocarbon maturity. High pressures exceeding the expected hydrostatic pressures are present in some wells but not in others; the regional pressure gradient and distribution outside the wells is unknown. A positive aspect of overpressures is they are recognized as a potential indicator element for active hydrocarbon systems.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.485

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

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