Physicochemical Characterization of Produced Oils and Gases in Immiscible and Miscible CO<sub>2</sub> Flooding Processes
Bibliographic record
Abstract
In this paper, the oil and gas samples produced from tight sandstone reservoir core plugs in immiscible, near-miscible, and miscible CO 2 flooding processes at the reservoir temperature are experimentally characterized. First, the vanishing interfacial tension (VIT) technique is applied to determine the minimum miscibility pressure (MMP) of the light crude oil–CO 2 system. Second, a total of five CO 2 -coreflood tests are conducted under immiscible, near-miscible, and miscible conditions to thoroughly study the characteristics of the produced oils and gases during each CO 2 flooding process. In the immiscible case ( P inj < MMP), the produced oil becomes heavier and heavier during CO 2 injection in terms of its density, viscosity, molecular weight, and hydrocarbons (HCs). The produced gas contains up to 84–96 mol % HCs (dominantly C 4–7 ) extracted from the light crude oil by CO 2 at the beginning and 85–100 mol % CO 2 at the end of CO 2 injection. In the near-miscible case ( P inj ≈ MMP), the heaviest oil is produced at 0.4 pore volume (PV) of the injected CO 2, which is followed by a relatively lighter produced oil from CO 2 breakthrough (BT) at 0.6 PV to the end of CO 2 injection. The produced gas has 40–60 mol % HCs (dominantly C 5–8 ) at the beginning and then consists of almost 100% CO 2 after CO 2 BT. In the miscible case ( P inj > MMP), the produced oil becomes much lighter and lighter with the injected PV. The produced gas contains 20–75 mol % HCs (mainly C 5–8 ) at the very beginning and quickly becomes almost 100% CO 2 after CO 2 BT. In summary, this laboratory study provides the comprehensive characterization of the produced fluids in three distinct CO 2 flooding processes. These new experimental data will help to better evaluate the field-scale CO 2 -enhanced oil recovery (EOR) processes and design the future CO 2 -EOR projects as well.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".