MétaCan
Menu
Back to cohort
Record W2071441888 · doi:10.2118/149411-ms

Modeling of Asphaltene Precipitation Due to Steam and n-alkane Co-injection in the ES-SAGD Process

2011· article· en· W2071441888 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Unconventional Resources Conference · 2011
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltAsphalteneOil sandsSteam injectionSteam-assisted gravity drainagePetroleum engineeringEnhanced oil recoverySolventDilutionPetroleumEnvironmental scienceWaste managementChemistryChemical engineeringMaterials scienceGeologyThermodynamicsOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Abstract The world energy demand is continuously increasing. Therefore heavy oil and bitumen reservoirs are driving more attentions for world energy supply. There are large amount of bitumen reserves in Canada. Only very small portion of bitumen reserves (~15%) in Alberta is mineable, and rest must be recovered using in-situ techniques. Bitumen viscosity can be reduced substantially by heating or dilution with a solvent. Steam Assisted Gravity drainage (SAGD) has been employed commercially to recover bitumen from Athabasca oil sands. This method requires large amount of water, facilities for water treatment, and natural gas to generate steam. There have been attempts to develop and optimize hybrid SAGD processes to reduce water consumption during bitumen recovery by steam. The co-injection of steam and solvent additives (e.g. ES-SAGD, SAP, SAS) can improve bitumen recovery due to its viscosity reduction by dilution with solvent and heating by steam. The experimental and pilot studies with steam and n-alkane co-injection shows enhanced oil recovery, and reduction in steam consumption (Nasr et. al., 1991, 2001, 2002, 2003). The phase behaviour of the bitumen and n-alkane solvents at SAGD operating condition is very complex and there is possibility of multiphase formation or asphaltene precipitation. The recent pore scale experimental study of this process has shown evidence of asphaltene precipitation during the ES-SAGD with n-alkanes (e.g. Pentane, Hexane) (Mohammadzadeh et. al., 2010). There are few published asphaltene precipitation data for Athabasca bitumen and n-alkanes at different temperature and pressure in the literature (Sabbag et. al. 2006). These data were used to develop an EoS model for the asphaltene precipitation using the CMG-WinProp Asph/Wax multiphase flash calculation. The asphaltene precipitation during the steam and n-alkane co-injection was studied using STARS thermal reservoir simulation model. This paper explains a method to characterize Athabasca bitumen based on the experimental SimDist data. A technique for tuning the solid solubility model parameters was addressed to develop asphaltene precipitation model for n-heptane and Athabasca bitumen. Also the asphaltene precipitation modeling with STARS, its effect on the steam chamber development and ES-SAGD performance are discussed.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.974

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 head0.036
GPT teacher head0.257
Teacher spread0.221 · 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