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Record W2065727286 · doi:10.1190/tle31111362.1

Quantitative interpretation of the McKay oil sands thermal area: Canadian case study

2012· article· en· W2065727286 on OpenAlexaffabout
Laurie M. Weston Bellman, Amanda Knowles, Rozalia Pak

Bibliographic record

VenueThe Leading Edge · 2012
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsNatural Resources CanadaCanadian Natural ResourcesDiscovery Centre
Fundersnot available
KeywordsGeologyOil sandsResource (disambiguation)Petroleum engineeringInterpretation (philosophy)Consistency (knowledge bases)FaciesStage (stratigraphy)Mining engineeringStructural basinPaleontologyArchaeologyGeographyComputer science

Abstract

fetched live from OpenAlex

Southern Pacific Resource Corporation (STP) acquired 211 km of 2D seismic data in September 2007 and an additional 5.1 km2 of 3D in December 2010. The 2D survey was used as an exploration tool, which ultimately lead to the McKay Thermal Project in northeastern Alberta. Conventional seismic interpretation has been valuable in defining the structure and regional extent of the reservoir. However, the conventional seismic character lacks the detail or consistency to delineate subtle facies variations present in the reservoir. Risk reduction through increased understanding of the reservoir at this stage of an oil sands project has the potential for significant benefits as the project moves on to production. Seismic data have already proven beneficial in the evaluation phase of this project; the intent with this case study was to investigate the potential to derive more detailed information from the seismic about the reservoir character and fluid content using quantitative interpretation (QI) techniques.

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)0.001
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 score0.028
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.042
GPT teacher head0.307
Teacher spread0.266 · 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

Citations3
Published2012
Admission routes2
Has abstractyes

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