Bibliographic record
Abstract
The start-up of Steam-Assisted Gravity Drainage (SAGD) process relies on months of non-productive steam circulation. A technology called Fast-and Uniform SAGD Start-up Enhancement (FUSE) has been developed to start up SAGD earlier using dilation mechanism. However, in some reservoirs there exist heterogeneities in inter-well zone along horizontal wells, which may cause uneven development of the dilation front, resulting in some low-mobility region un-swept. For the success of FUSE, it is crucial to temporarily block the high-mobility zones, so the injected fluid can penetrate into low permeability zones to form uniform dilation in the SAGD inter-well region. Using oil-in-water (O/W) emulsion as selective plugging agents seems a promising method due to the special advantages of controllable droplet size, non-permanent plugging, less formation damage of emulsion. In this work, to develop suitable oil-in-water emulsion systems, laboratory experiments and theoretical model were carefully designed. Emulsification tests were first conducted to screen suitable emulsifiers. Physicochemical properties of emulsion were characterized by stability, droplet size distribution, and rheological properties. Plugging behavior and conformance control performance of prepared emulsion were tested through sandpack flow experiments. Results show that O/W emulsion had good plugging performance when flowing in porous media with the largest sandpack permeability reductions greater than 99%. Interfacial tension significantly affects emulsion plugging behavior and conformance control ability. Emulsions with adequate interfacial tension possess favorable deformability and flexibility, which ensures they can alternately plug the heterogeneous sandpacks and obtain good conformance control performance. A new theoretical model, which incorporated physical properties of porous media, physicochemical properties of emulsion system, injection strategy and the interactions between porous media and emulsion, was developed to quantitatively describe the flow behaviors of emulsion in porous media. By appropriately choosing coefficients, the simulated results can have a well agreement to the experimental data. This work will greatly increase the understanding of emulsion flow in porous media, and provide technical guides for the optimization of the O/W emulsion injection in FUSE operation in oilfields.
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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 | 0.000 | 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 | 0.000 |
| 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".