Bibliographic record
Abstract
_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 212779, “Oil-in-Water Emulsion Formation in SAGD With Chemical Additives,” by S. Ali Ghoreishi, University of Calgary, and Javier O. Sanchez and Julian D. Otiz-Arango, ConocoPhillips, et al. The paper has not been peer reviewed. _ The study detailed in the complete paper aims at understanding the effect of a surfactant that the authors refer to as a high-temperature emulsifying agent (HEA) as an additive in the steam-assisted gravity drainage (SAGD) process. The work provides insights into the role of surfactants in forming oil-in-water (O/W) emulsions in steam-based bitumen production. A novel high-pressure/high-temperature (HP/HT) visual cell enables the rapid assessment of recovery processes and a better understanding of the active emulsifying mechanism in such a system. Introduction The authors conducted a pore-network micromodel experiment to analyze the effect of emulsifiers on the SAGD process. Hot water, with and without a priority emulsifying agent, was injected into a bitumen-saturated micromodel at 82°C. The surfactant solution can remove the residual oil from the invaded zone and forms O/W emulsions as it spreads in uninvaded regions. Experimental Setup The experimental setup includes a high-resolution imaging system, a lightbox, a precision syringe pump, a bitumen-transfer vessel, and an HP/HT cell (Fig. 1a). A borosilicate glass micromodel (Figs. 1b and 1c) was placed inside the vertical HP/HT cell, and the remaining space in the HP/HT cell was filled with a heat-resistant mineral oil. The heating jacket was mounted on the HP/HT cell, and a digital thermometer was connected to the heating jacket and placed between the heating jacket and the cell to monitor and control the temperature. The micromodel inlet was connected to the syringe pump. The remainder of the experimental process is detailed in the complete paper. Results and Discussion Effect of HEA on Emulsion Formation and Sweeping Patterns. In all experiments, the hot aqueous phase was injected at the rate of 5 μL/min into the micromodel fully saturated with Athabasca bitumen. The HP/HT cell was kept at a constant temperature of 82°C. The hot water injection was used as the base system to be compared with the HEA-solution injection. Water droplets trapped in the pockets of bitumen phase were observed at the later stages of displacement in flooded areas near the two-phase interface. Water droplets were first formed at the top of the micromodel, close to the injection port, and were pushed down toward the production port as injection continued. O/W droplets, in a much lesser quantity, also were formed during the displacement process close to the production port. An HEA solution with a concentration of 3,000 ppm was injected under the same conditions as the hot-water-injection scenario. The HEA solution also formed a chamber at the top of the micromodel with an advancing finger toward the production port. The injection of HEA solution completely cleaned the surface of the pores.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".