Optimization of CO2 Flooding Schemes for Unlocking Resources from Tight Oil Formations
Bibliographic record
Abstract
Abstract In this paper, techniques have been developed to experimentally and numerically evaluate performance of waterflooding and CO2 flooding for unlocking oil resources from tight formations. Experimentally, core samples collected from a tight formation with a permeability range of 0.081–0.790 mD are used to conduct a series of coreflooding experiments. The performance of four flooding schemes, i.e., waterflooding, near-miscible CO2 flooding, miscible CO2 flooding, and water-alterneating-CO2 flooding, are evaluated by the coreflooding experiments. The continuous CO2 flooding processes under either miscible or near-miscible condition lead to a superior oil recovery performance in comparison with the waterflooding process. Furthermore, the miscible water-alternating-CO2 flooding in tight cores leads to a higher recovery efficiency with less CO2 consumption compared to the continuous CO2 flooding processes. Most importantly, in the miscible water-alternating-CO2 flooding process, it is found that the pressure drop increases rapidly when water is injected, but decreases dramatically when CO2 is injected. This indicates that CO2 injection is able to significantly improve the fluid injectivity in tight formations. In general, the miscible water-alterneating-CO2 flooding process is found to be the most favorable flooding scheme for tight formations in terms of both recovery efficiency and fluid injectivity. Theoretically, numerical simulation is performed to match the experimental measurements obtained in the different flooding schemes. There exists a generally good agreement between the experimental measurements and simulated results for all the flooding schemes examined. The tuned numerical model is then employed to optimize the production pressure in the continuous CO2 flooding process and the water-alternating-gas (WAG) ratios in the miscible water-alternating-CO2 (CO2-WAG) flooding process, respectively. It is found that the optimum producing pressure in the continuous CO2 flooding process can be set as the minimum miscibility pressure (MMP) of the tight oil sample, while the optimum WAG ratio falls in the range of 4:1 to 8:1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".