Experimental Investigation of Production Characteristics of the Gravity-Assisted Inert Gas Injection (GAIGI) Process for Recovery of Waterflood Residual Oil: Effects of Wettability Heterogeneity
Bibliographic record
Abstract
The impact of reservoir heterogeneities in terms of wettability at the macroscopic scale on the recovery efficiency of the gravity-assisted inert gas injection (GAIGI) process was investigated through a systematic experimental study for tertiary recovery of waterflood residual oil. Isolated inclusions of oil-wet consolidated glass beads were embedded in a continuum of unconsolidated water-wet glass beads to create heterogeneous packed columns. In comparison to water-wet homogeneous porous media, such heterogeneous media allowed us to establish higher waterflood residual oil saturation whose amount varied linearly with the volume fraction of oil-wet heterogeneities in the packing. Experimental results obtained from tertiary gravity drainage experiments demonstrated that the continuity of water-wet portions of the heterogeneous porous medium facilitates the tertiary oil recovery through the film flow mechanism, provided that the oil-spreading coefficient is positive. In addition, owing to the high waterflood residual oil content of the heterogeneous media tested, the oil bank formation occurred much earlier and grew faster, resulting in a higher oil recovery factor. However, having favorable wettability conditions in homogeneous porous media resulted in slightly lower reduced residual oil saturation after the GAIGI process compared to that in the heterogeneous media with the same condition of withdrawal rate. A relationship between the oil recovery factor at gas breakthrough and gravity number was developed for the heterogeneous and homogeneous media. The recovery factor at gas breakthrough versus gravity number in homogeneous media follows a similar trend as that of homogeneous water-wet porous media. However, at a given gravity number, the recovery factor of heterogeneous media was greater than that of the homogeneous media.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".