Evaluating the Performance of CO2 Foam and CO2 Polymer Enhanced Foam for Heavy Oil Recovery: Laboratory Experiments in Unconsolidated and Consolidated Porous Media
Bibliographic record
Abstract
Abstract Enhanced oil recovery (EOR) from heavy oil reservoirs is challenging. The higher viscosity of oil in such reservoirs, add more challenges and severe the difficulties during any EOR method (i.e. high mobility ratio, inadequate sweep, reservoir heterogeneity) compared to that of EOR from light oil reservoirs. Foam has gained interest as one of the EOR methods especially for challenging and heterogeneous reservoirs containing light oil. However, the foam and especially polymer enhanced foam (PEF) potential for heavy oil recovery is less studied. The current study aims to evaluate the performance of CO2 foam and CO2 PEF during heavy oil recovery from both unconsolidated (i.e. sandpack) and consolidate (rock sample) porous media with the help of fluid flow experiments. The injection pressure profile, oil recovery, and CO2 gas production were monitored and recorded to analyze and compare the performance of CO2 foam and PEF for heavy oil recovery. A visual sandpack made of glass column and a core-flood system capable of measuring the pressure at different sections of the core were used in this study. Homogenous and fractured sandstone core samples, as well as a fractured carbonate core sample, were selected for the core-flood study. Static stability results revealed slower liquid drainage and collapse rates for PEF compared to that of foam even in the presence of heavy crude oil. The addition of polymer significantly improved the performance of CO2 foam flooding during heavy oil recovery in dynamic experiments. This result was inferred from faster propagation rate, higher dynamic stability, and higher oil recovery of CO2 PEF over CO2 foam injection. Moreover, the visual analysis demonstrated more stable frontal displacement and higher sweep efficiency of PEF compared to the conventional foam flooding. In the fractured porous media, additional heavy oil recovery was obtained by liquid diversion into the matrix area rather than gas diversion inferred from pressure profile and gas production data. The results obtained from this study show that CO2 PEF could significantly improve the heavy oil recovery and CO2 sequestration, especially in homogeneous porous media.
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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".