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Record W2326477311 · doi:10.1021/ef100763j

Hydrocarbon Depletion of Athabasca Core at Near Steam-Assisted Gravity Drainage (SAGD) Conditions

2010· article· en· W2326477311 on OpenAlexaff
Luis Alberto Pineda-Perez, Lante Carbognani, Ronald J. Spencer, Brij Maini, Pedro Pereira‐Almao

Bibliographic record

VenueEnergy & Fuels · 2010
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsAlberta Glycomics Centre
Fundersnot available
KeywordsSteam-assisted gravity drainageOil sandsChemistryHydrocarbonCore (optical fiber)Petroleum engineeringSpecific gravityChemical engineeringEnvironmental chemistryMineralogyGeologyOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

The present study shows the feasibility of preparing hydrocarbon (HC)-depleted cores with a laboratory setup operated at near steam-assisted gravity drainage (SAGD) oil production conditions (200−240 °C and 2.5 MPa). One Athabasca core was selected for this purpose. HC contents remaining within the spent core match typical levels from industrial production ranging from 30 to 40 wt %. These HC contents were found independent from using liquid- or vapor-phase H 2 O, suggesting that surface chemistry at the mineral−organic interface plays a leading role in HC partition. Characterization of the HC fractions from the steam-depleted cores showed that short residence times (1 h) at 200−220 °C provided upgrading levels of about 1−2% based on the original HC present in these cores. Light HC components were generated coincidently with aquathermolysis mechanisms widely described in the literature. The remaining HCs attached to the core minerals were found downgraded in comparison to the initial HC present in the virgin core. These low-quality non-mobile materials are targeted for further production of valuable products. One may think of in situ gasification to generate H 2 .

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.225
Teacher spread0.214 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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