Chemical enhanced oil recovery from shale‐rich tight carbonate reservoirs using 2‐butoxyethanol as a mutual solvent and diluted seawater
Bibliographic record
Abstract
Abstract Oil production from tight reservoirs due to their very low permeability and high capillary pressure requires complex operations and materials, so that hydraulic fracturing in these reservoirs is recommended before any chemical injection. This operation turns the reservoir into a fractured one that can produce more oil by activating the imbibition mechanism. The interfacial tension (IFT) of oil and water and reservoir rock wettability as key parameters of overproduction from this type of reservoir can affect this mechanism. In this study, the potential of 2‐butoxyethanol as a mutual solvent for enhanced oil recovery (EOR) was investigated with a focus on the oil production under imbibition in this type of reservoir through performing experiments and calculations of IFT, oil swelling, contact angle, and oil production. The analysis of the results shows that the mechanisms of IFT reduction, wettability alteration, and oil swelling, which all directly affect the oil production under imbibition, reached the desired values using 2‐butoxyethanol in the appropriate concentration along with the dilution of seawater. The lowest values for interfacial tension and contact angle at 0.03 M concentration of the solvent and 5000 ppm salinity at 90°C temperature were 1.315 mN/m and 71.57°, respectively. These values are much lower compared to the values obtained by similar additives, while solvents, unlike 2‐butoxyethanol, are effective in much higher volume ratios. The oil swelling increased by about 14% using 2‐butoxyethanol due to its mass transfer between water and oil phases through the interface. Finally, the oil recovery factors of 42% and 59% were achieved under one‐ and multi‐dimensional spontaneous imbibition (ODSI and MDSI), respectively.
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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".