Experimental and Numerical Study of Improving Heavy Oil Recovery by Alkaline Flooding in Sandpacks
Bibliographic record
Abstract
Abstract Chemical flooding has great potential for enhancing heavy oil recovery, especially for reservoirs where thermal methods are not feasible. It has been shown that the formation of emulsions during chemical flooding can effectively improve sweep efficiency and, consequently, increase heavy oil recovery. The mechanism of flow of oil-in-water (O/W) emulsion in porous media has been extensively studied and simulated using the filtration theory. Few studies have been done for the modelling of water-in-oil (W/O) emulsion flow in heavy oil reservoirs. This study experimentally investigated the effective viscosity of W/O emulsion in porous media. Alkaline flooding tests were performed in channelled sandpacks to demonstrate the effectiveness of sweep efficiency improvement by the in-situ produced W/O emulsions. High tertiary oil recoveries were obtained for all these tests. The alkaline flooding process was simulated by including the observed flow behaviour of extra resistance to water phase flow caused by the formation of W/O emulsions, as well as the adsorption of chemicals, interfacial tension reduction, and in-situ generation of W/O emulsions. These laboratory results and the developed simulation technique are proposed as an improvement to the simulation and design of the field-scale projects of chemical flooding for heavy oil recovery. Introduction Many heavy oil reservoirs in Western Canada are not suitable for steam injection techniques due to thin pay thickness. Both field and laboratory results demonstrate that waterflooding of heavy oil reservoirs can only achieve a very low oil recovery. The main causes for the poor sweep efficiency of waterflooding for these heavy oil reservoirs are very adverse mobility ratio, natural area and vertical reservoir heterogeneity and heterogeneity induced by primary production(1,2). Therefore, improving mobility ratio and blocking water flow through channels are essential for improving heavy oil recovery. The in-situ formation of emulsions during alkaline flooding has been recognized as one of the efficient methods to improve sweep efficiency for heavy oil recovery(3,4,5). The effectiveness of alkaline flooding for acidic crudes was recognized as early as in the 1920s(6). Jennings et al.(3) proposed the mechanism of emulsification and entrapment for alkaline flooding. They carried out caustic flooding tests using a heavy oil. Their results showed that the in-situ produced O/W emulsions tended to plug water fingering and channels, resulting in improved sweep efficiency. Johnson(7) summarized possible mechanisms of alkaline flooding to improve oil recovery: dispersion and entrainment, wettability reversal, and emulsification and entrapment. The formation of W/O emulsions was also observed as a mechanism of improving oil recovery(8,9).
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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 | 0.002 | 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".