Experiment Observations of Miscible Displacement of Heavy Oil With Hydrocarbon Solvents
Bibliographic record
Abstract
This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 97854, "Experimental Observations of Miscible Displacement of Heavy Oils With Hydrocarbon Solvents," by D. Salama and A. Kantzas, U. of Calgary, prepared for the 2005 SPE International Thermal Operations and Heavy Oil Symposium, Calgary, 1–3 November. The increased interest in secondary production (or post-cold production) of heavy oil and the rise of oil prices have renewed interest in solvent-based methods for heavy-oil recovery. Although the vapor-extraction (vapex) process is favored, other methods are worth investigating. Also, the relative merit of mass-transfer and viscous mechanisms in the overall recovery efficiency remains a topic of debate. This study of mass-transfer phenomena in heavy-oil/ and bitumen/solvent systems was performed in an effort to determine dispersion coefficients. Introduction Heavy oil and oil sands will be an important part of Canada's oil supply. One-third of the world's oil is in Canada in the form of heavy oil and bitumen. The world's heavy-oil resources total approximately 10 trillion bbl, nearly three times the conventional oil in place in the world. Alberta contains nearly 2 trillion bbl of oil. Approximately one-fourth of the oil production of Canada is from oil sands. Here, in-situ recovery processes are thermal or nonthermal. Thermal processes use heat to reduce the viscosity of the heavy oil in situ, thus mobilizing the heavy oil. Examples include cyclic-steam stimulation, steam-assisted gravity drainage, and steamflooding. Nonthermal processes rely on dilution of the oil to reduce the heavy-oil viscosity. Examples include CO2 injection, miscible floods, and vapex. Displacement in the case of immiscible floods, such as waterflooding, generally is not complete, but a fluid can be displaced completely from the pores by a miscible fluid. In the case of miscible fluids, there are no residual saturations. Hence, sol-vent floods present an attractive in-situ process for the recovery of the heavy oil. However, the major challenge in miscible floods is for the miscible phase to access a significant fraction of the resident oil. In solvent-based enhanced-oil-recovery techniques, several mechanisms affect the rate of oil recovery, given that accessibility is provided. These mechanisms include mass transfer, viscous forces, and gravity drainage. The solvent diffuses and/or disperses into the heavy oil, reducing its viscosity. The solvent/oil mixture then drains and is recovered from the production well. This study focused on the mass-transfer process in miscible sol-vent floods by experimentally observing the miscible displacement of heavy oils by hydrocarbon solvents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".