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Record W2131940485 · doi:10.1306/01021312054

Improved geostatistical models of inclined heterolithic strata for McMurray Formation, Alberta, Canada

2013· article· en· W2131940485 on OpenAlexaffabout
Mehran M. Hassanpour, Michael J. Pyrcz, Clayton V. Deutsch

Bibliographic record

VenueAAPG Bulletin · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeologyPaleontology

Abstract

fetched live from OpenAlex

Abstract The McMurray Formation of northern Alberta in Canada contains multiscale complex geologic features that were partially formed in a fluvial-estuarine depositional environment. The inclined heterolithic strata deposited as part of fluvial point bars contain continuous centimeter-scale features that are important for flow characterization of steam-assisted gravity drainage processes. These channels are common, extensive, and imbricated over many square kilometers. Modeling the detailed facies in such depositional systems requires a methodology that reflects heterogeneity over many scales. This article presents an object-based facies modeling technique that (1) reproduces the geometry of multiscale geologic architectural elements seen in the McMurray Formation outcrops and (2) provides a grid-free framework that models these geologic objects without relating them to a grid system. The grid-free object-based modeling can be applied to any depositional environment and allows for the complete preservation of architectural information for consistent application to any gridding scheme, local grid refinements, downscaling, upscaling, drape surface, locally variable azimuths, property trend modeling, and flexible model interaction and manipulation. Features millimeters thick or kilometers in extent are represented very efficiently in the same model.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
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 head0.014
GPT teacher head0.195
Teacher spread0.182 · 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 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

Citations52
Published2013
Admission routes2
Has abstractyes

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