Coupling Immiscible CO2 Technology and Polymer Injection to Maximize EOR Performance for Heavy Oils
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary With approximately 90% of Saskatchewan's original heavy oil in place remaining in the ground, there is excellent potential for the application of enhanced oil recovery (EOR) methods and new technologies. The goal of the study discussed in this paper was to investigate if a new proposed process--coupling CO2 and polymer injection--can increase EOR performance for heavy oil reservoirs. The oil recovery performance of three EOR modes [water-alternating-gas (CO2 WAG) injection, polymer-alone flood and coupled CO2 and polymer injection] was compared in laboratory-scale linear coreflood tests in waterflooded cores. The immiscible CO2 WAG process recovered 15.3% original oil in place (OOIP) with 6.16 MSCF/stb gas utilization. Under a controlled maximum pressure drop across the core, the polymer-alone (0.4 wt%) flood produced an additional 12.93% OOIP above the initial waterflood recovery. However, the coupled CO2 and polymer injection process (using a polymer concentration of only 0.2 wt%) gave better recovery efficiency (18.7% OOIP) than the polymer-alone flood. Moreover, it had much better gas utilization than the CO2 WAG run, consuming only 2.0 MSCF/stb, or one-third of the amount of CO2 used in that run to recover the same amount of oil. This performance comparison demonstrates two of the biggest advantages of coupled CO2 and polymer injection: it can effectively reduce the pressure drop across the core and can obtain encouraging recovery if the optimal polymer concentration is added to the water.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it