Oil production characteristics and CO2 storage mechanisms of CO2 flooding in ultra-low permeability sandstone oil reservoirs
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Bibliographic record
Abstract
Using the ultra-low permeability reservoirs in the L block of the Jiangsu oilfield as an example, a series of experiments, including slim tube displacement experiments of CO 2 -oil system, injection capacity experiments, and high-temperature, high-pressure online nuclear magnetic resonance (NMR) displacement experiments, are conducted to reveal the oil/gas mass transfer pattern and oil production mechanisms during CO 2 flooding in ultra-low permeability reservoirs. The impacts of CO 2 storage pore range and miscibility on oil production and CO 2 storage characteristics during CO 2 flooding are clarified. The CO 2 flooding process is divided into three stages: oil displacement stage by CO 2 , CO 2 breakthrough stage, CO 2 extraction stage. Crude oil expansion and viscosity reduction are the main mechanisms for improving recovery in the CO 2 displacement stage. After CO 2 breakthrough, the extraction of light components from the crude oil further enhances oil recovery. During CO 2 flooding, the contribution of crude oil in large pores to the enhanced recovery exceeds 46%, while crude oil in medium pores serves as a reserve for incremental recovery. After CO 2 breakthrough, a small portion of the crude oil is extracted and carried into nano-scale pores by CO 2 , becoming residual oil that is hard to recover. As the miscibility increases, the CO 2 front moves more stably and sweeps a larger area, leading to increased CO 2 storage range and volume. The CO 2 full-storage stage contributes the most to the overall CO 2 storage volume. In the CO 2 escape stage, the storage mechanism involves partial in-situ storage of crude oil within the initial pore range and the CO 2 carrying crude oil into smaller pores to increase the volume of stored CO 2 . In the CO 2 leakage stage, as crude oil is produced, a significant amount of CO 2 leaks out, causing a sharp decline in the storage efficiency.
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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 | 0.000 | 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 it