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Record W4254097760 · doi:10.12972/ksmer.2014.51.5.715

Methods to Improve Cement Bond in SAGD Wells

2014· article· en· W4254097760 on OpenAlexaboutno aff
Minnyeong Yoon, Jongchan Lim, Junseog Yi, Jaewoong Kim

Bibliographic record

VenueJournal of the Korean Society of Mineral and Energy Resources Engineers · 2014
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsCementPetroleum engineeringBondGeologyEngineeringMaterials scienceMetallurgyBusiness

Abstract

fetched live from OpenAlex

Harvest Operations Corp (HOC) has drilled total of 15 producer and injector well pairs of SAGD (Steam Assisted Gravity Drainage) wells in north eastern Alberta, Canada, targeting McMurray oilsand formation.Operators in heavy oil reservoir including SAGD drilling operation often have troubles maintaining a good well integrity throughout the production.One of the most common problem operators have is steam leaking, either to a different formation or to surface, which is mostly caused from a bad cement bond quality.To improve the cement bond, HOC incorporated the unique well design, by lowering the surface casing setting depth, by using a special thermal cement blend, and by optimized cementing practice such as centralizer and stop collar design and squeezing Calcium Carbonate and Potassium Chloride solution.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.005
GPT teacher head0.200
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2014
Admission routes1
Has abstractyes

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