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Record W2319548438 · doi:10.1144/m35.38

Chapter 38 Thermal maturity of the Sverdrup Basin, Arctic Canada and its bearing on hydrocarbon potential

2011· article· en· W2319548438 on OpenAlexaffabout
Keith Dewing, Mark Obermajer

Bibliographic record

VenueGeological Society London Memoirs · 2011
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsSverdrupGeologyMaturity (psychological)Structural basinArcticBearing (navigation)OceanographyPaleontologyGeographyCartography

Abstract

fetched live from OpenAlex

Abstract Analysis of a large thermal maturity dataset indicates that the Carboniferous to Eocene Sverdrup Basin in the Canadian Arctic had a uniform response to thermal stress with depth for Mesozoic strata. Thermal maturity was established at the level of the widespread Upper Triassic Gore Point Member; a good seismic reflector, occurring in close vertical proximity to the two main oil-prone source rocks in the basin. The Gore Point Member is in the gas window ( R o >1.35%) in the northeastern part of the Sverdrup Basin, whereas in the western Sverdrup Basin its maturity does not exceed 1.2% R o . This would support the hypothesis that large quantities of gas found at the Drake, Hecla and Whitefish fields have derived from a deeper source, probably in Permian or lower Palaeozoic strata. A normal burial curve is established using boreholes drilled in areas with no structural complexity at time of maximum burial. Low-amplitude structures, including the Drake, Hecla and Whitefish fields, show little or no uplift following maximum burial in the Paleocene, indicating that these structures formed prior to the Eocene folding related to the Eurekan Orogeny. Because they were present at the time of maximum burial, they were available to be charged during hydrocarbon migration. In contrast, high-amplitude structures show evidence of large uplifts following maximum burial. They formed in the Eocene and hence post-date most hydrocarbon migration.

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 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 score0.145
Threshold uncertainty score0.987

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)0.0000.000

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 head0.175
Teacher spread0.163 · 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.

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

Citations17
Published2011
Admission routes2
Has abstractyes

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