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Record W4384009788 · doi:10.1306/10242219118

Comparison of the morphology, facies, and reservoir quality of valley fills in the southern Athabasca Oil Sands Region, Alberta, Canada

2023· article· en· W4384009788 on OpenAlexaffabout
Cynthia A. Hagstrom, Stephen M. Hubbard, Sean C. Horner, Harrison K. Martin, Yang Peng

Bibliographic record

VenueAAPG Bulletin · 2023
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOil sandsGeologyFaciesGeochemistryMining engineeringGeomorphologyArchaeologyAsphaltGeographyStructural basin

Abstract

fetched live from OpenAlex

Abstract Valley fills in the McMurray Formation contain the main reservoirs of the southern Athabasca Oil Sands Region (AOSR), which are typically exploited by steam-assisted gravity drainage (SAGD). Despite the importance of the bitumen resources they contain, a comprehensive regional assessment of valley-fill geometry, planform morphology, and reservoir quality is lacking. To remedy this, a data set of 214 logged cores, hundreds of core photographs, 14,000 wire-line logs, and three-dimensional seismic data is used to map four McMurray Formation parasequence sets in the southern AOSR and determine the geometry and reservoir quality of associated valley fills. The valley fills represent a complex network of sediment-routing systems that ultimately moved sediment north, toward the Boreal Sea. They are mainly composed of fluvial or tidally influenced point-bar deposits laid by rivers of varying width and depth. Between valley fills, the reservoir parameters governed by depositional architecture (i.e., sandstone porosity, shale volume, and net-to-gross) vary by less than 3%, with few exceptions. At a high level, this suggests that for analogue-based SAGD production forecasting, all projects exploiting valley-fill deposits are potential analogues to one another, regardless of the valley fill’s stratigraphic age. The regional maps produced by this study can be used to investigate upstream–downstream sedimentological, ichnological, and morphological trends that may reveal critical insights into depositional processes and environments. Additionally, the devised stratigraphic framework can be employed when mapping point-bar deposits to predict facies changes in a formation that is particularly heterolithic and laterally discontinuous.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.474

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 head0.030
GPT teacher head0.263
Teacher spread0.233 · 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 designNot applicable
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

Citations4
Published2023
Admission routes2
Has abstractyes

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