Optimal Parametric Design for Water-Alternating-Gas (WAG) Process in a CO2-Miscible Flooding Reservoir
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Bibliographic record
Abstract
Summary A pragmatic method has been developed to efficiently design the production-injection parameters to optimize the water-alternating-gas (WAG) performance in a field-scale CO2-miscible flooding project. The net present value (NPV) is selected as the objective function, while the controlling variables are chosen to be the injection rates, ratios of gas slug size to water slug size (WAG ratio) and cycle time (i.e., the injection time for each gas or water slug) for the injectors and bottomhole pressures (BHPs) for the producers. A hybrid technique, which integrates the orthogonal array (OA) and Tabu technique into the genetic algorithm (GA), is then developed and employed to determine the optimum WAG production-injection parameters. Sensitivity analysis of the WAG parameters on oil recovery is conducted and a field case is finally presented to demonstrate the successful application of the newly developed technique.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it