Primary and Secondary Oil Recovery From Different Wettability Rocks by Countercurrent Diffusion and Spontaneous Imbibition
Bibliographic record
Abstract
Abstract This study investigates optimum matrix oil recovery strategies in naturally fractured reservoirs (NFR) for different wettabilities and rock types. We compare the recovery efficiencies of two cases: (a) the primary counter-current spontaneous imbibition followed by the diffusion of a miscible phase (secondary recovery) and (b) primary diffusion of miscible fluid without pre-flush of matrix by the spontaneous imbibition. For these recovery strategies, the effects of the matrix shape factor, matrix wettability, and type of miscible displacing phase on the rate of recovery and development of residual oil saturation were clarified experimentally. Cylindrical Berea sandstone and Indiana limestone samples with different shape factors were obtained by cutting the plugs 1, 2.5, and 5 cm in diameter and 2.5, 5, and 10 cm in length. All sides were coated with epoxy except one end. Static imbibition experiments were conducted on vertically situated samples where the matrix-fracture interaction took place upward direction. Mineral oil and crude oil were used as oleic phases. Brine was selected as aqueous phases for the primary spontaneous imbibition recovery. For primary and secondary miscible displacement experiments n-heptane was used as solvent. Wettability of water-wet Berea sandstone samples was altered to weakly water-wet to observe its effects on the dynamics of spontaneous counter-current imbibition and diffusion. Parametric analyses were performed for the appraisal of secondary and tertiary recovery potential of naturally fractured reservoirs by immiscible and miscible fluid injections. The optimal recovery strategies (recovery rate, recovery time and ultimate recovery) for different rock properties were identified and classified. In water-wet cases, starting the recovery with capillary imbibition followed by diffusion was found the optimal way, i.e. both effective and efficient. For limestone or aged sandstone samples, starting the recovery by diffusion yielded a faster recovery rate and higher ultimate recovery.
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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 | 0.000 |
| 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) | 0.001 | 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".