Modeling of Asphaltene Precipitation Due to Steam and n-alkane Co-injection in the ES-SAGD Process
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".