Quantitative and Visual Characterization of Asphaltenic Components of Heavy-Oil and Bitumen Samples after Solvent Interaction at Different Temperatures and Pressures
Bibliographic record
Abstract
Abstract Due to inefficiency of steam injection caused by technical, economic, and operational reasons, solvent methods have received special attention in heavy oil and bitumen recovery recently. A solvent can be injected in the form of vapor extraction process at reservoir temperature. Hot solvent injection can be applied to improve the recovery rate at lower temperatures than steam injection. These solvent driven recovery processes are quite complex on account of their "asphaltene destabilization" that takes place due to changes in temperature, pressure, and solvent dissolved in oil. As a result of this destabilization, the asphaltene precipitates, flocculates, and eventually plugs the pores in the reservoir. In this research, the de-asphalting of a heavy oil sample was evaluated in a PVT cell with optical visualization. The experiments were undertaken at different temperature ranges (50°C to 80°C) and pressure (30psig to 500psig), which is the suggested range for hot solvent injection. Three light hydrocarbons (propane, n-hexane, and n-decane) were used as solvents. Applying standard SARA analysis (ASTM D2007 and ASTM D2549), the characteristics of the asphaltene precipitated at the bottom of the PVT cell, were determined quantitatively. Moreover, a methodology for "asphaltene precipitation concentration analysis" was developed in order to determine the effect the temperature, pressure, and solvent type had on asphaltene destabilization. This quantitative analysis was complemented through visual observations of asphaltene characteristics on the PVT cell as well as using optical microscopy. In addition, the refractive index measurements at the onset of precipitation were used to evaluate the changes in the oil after interacting with the solvent at different temperatures and pressures. Finally, a comparative analysis of the esults was provided. Based on the quantitative and qualitative observations, the characteristics of asphaltene were classified in terms of their shape, size, and amount for different oil/solvent types, pressure, and temperature. This study will eventually lead to the identification of the effects of asphaltene characteristics on pore plugging during heavy-oil/bitumen recovery by gravity drainage from oilsands.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".