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Record W3119914109

Comparing depositional environments and porous zones in the 400 million-year-old sabkhas of subsurface Alberta

2017· article· en· W3119914109 on OpenAlexaffabout
Sara Lubura, François Maréchal, Jenni Scott

Bibliographic record

VenueURSCA Proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsMount Royal University
Fundersnot available
KeywordsGeologyPetrographyDiagenesisEvaporiteSedimentary rockFaciesDevonianDolomiteSedimentary depositional environmentWell loggingStyloliteGeochemistryPorosityThin sectionPetrologyPaleontologyGeomorphologyGeotechnical engineeringGeophysicsStructural basin
DOInot available

Abstract

fetched live from OpenAlex

Using subsurface core and well logs, a comparison of sedimentary deposits in evaporite-containing formations of the Devonian hypersaline seas of Alberta was done. Thin sections from the Nisku Formation were examined using a petrographic microscope to determine how and when brine and hydrocarbons moved through two porous zones, identified by well logs from the same area. These two zones within core and thin sections were compared with other zones from which only well logs were available. Through measurements of the porosity, permeability, and timing of diagenesis from petrography, it is determined that areas of high neutron and density log responses correlate with cemented zones within the core. This research has a direct impact on the understanding of how evaporitic facies can cause different responses within well logs. Our understanding of how well logs, accompanied by core and thin section analysis, can give insight into the movement of fluids and gases in subsurface Alberta is also aided. * Indicates faculty mentor.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.338

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 head0.015
GPT teacher head0.214
Teacher spread0.200 · 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 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
Published2017
Admission routes2
Has abstractyes

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