MétaCan
Menu
Back to cohort
Record W2326435604 · doi:10.2118/173890-pa

Particle-Size Analysis for the Pike 1 Project, McMurray Formation

2014· article· en· W2326435604 on OpenAlexaboutno aff
Matt Abram, Graham Cain

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsOil sandsGeologyPermeability (electromagnetism)PikeAsphaltPetroleum engineeringHydrology (agriculture)Geotechnical engineeringArchaeologyGeography

Abstract

fetched live from OpenAlex

The unconsolidated sands of the Lower Cretaceous McMurray formation are the primary host of the Athabasca oil-sands deposit in Alberta, Canada. Alberta has one of the world’s largest nonconventional hydrocarbon resources with an estimated 1.8 trillion bbl of heavy oil (ERCB ST98-2013). The Pike 1 Project is a joint venture between Devon Canada Corporation (operator) and BP Canada Energy Group ULC. The Pike 1 Project is currently under a multiyear appraisal program to evaluate the McMurray bitumen resources that are amenable to steam-assisted gravity drainage(SAGD). In the Pike 1 Project area, the particle-size distribution (PSD) of the middle McMurray reservoir sands is highly variable because of the complex nature of the depositional environment. In order to understand the McMurray reservoir sands, Devon has exercised rigorous laboratory sampling and quality-control procedures to confirm the comprehensiveness of the PSD data set. By use of an unsupervised hierarchical classification technique, a dynamically growing self-organizing tree algorithm was used to cluster all of the PSD histograms from within the bitumen net-pay zone into one of four sand classes on the basis of similarity. Each sand class has a distinct PSD and permeability range. Using the sand classes, Devon extracted select intervals of core that closely matched the PSD histogram of each class to provide physical samples, termed “sandprints,” to fulfill sand-control-testing objectives. Further work included integrating the sand classes within the Pike 1 geological model, 3D permeability mapping, and upscaled sand-class volumes for SAGD well-pad optimization. This paper describes the process by which Devon has evaluated and classified the Pike 1 PSD data set into distinct sand classes within the unconsolidated middle McMurray reservoir. Devon’s methodology of acquiring these sands, necessary for sand-control testing, is also discussed in detail, emphasizing the overall effectiveness of the process. By use of this innovative PSD classification process as a supporting tool to reservoir characterization, Devon intends to realize the following benefits: • SAGD horizontal-well-pair placement optimization • A more methodical approach to laboratory testing of horizontal-liner technology for SAGD producers and injectors • Improved reservoir management

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: none
Teacher disagreement score0.671
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
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 head0.011
GPT teacher head0.214
Teacher spread0.202 · 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

Citations54
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Canadian Petroleum TechnologySame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207