An experimental approach to investigating permeability reduction caused by solvent‐induced asphaltene deposition in porous media
Bibliographic record
Abstract
Abstract Permeability reduction resulting from asphaltene deposition in porous media needs to be accounted for by reservoir simulators. Two questions have to be answered in order to quantify the reduction in permeability. The first question is how much asphaltene is deposited in porous media and the second one is how much permeability reduction is associated with a certain amount of asphaltene deposition. This article focuses on answering the latter by conducting laboratory experiments. Sand packs with known porosity, permeability, and sand grain size distribution were saturated with oil. Heptane was used to flood the oil‐saturated sand packs. After flooding with heptane, each sand pack was divided into ten smaller sand packs and the permeability of each small sand pack as well as the amount of deposited asphaltene in each one of them were measured. A method was developed to quantify the amount of deposited asphaltene within different cross sections of the sand packs. Results have been reported in terms of the mass of asphaltene in milligrams deposited on one gram of sand grain. The formation damage factor for each sand pack segment has been reported as the ratio between the permeability of the segment before extracting asphaltene to its permeability after extracting asphaltene. This ratio varied between 0.4–0.9. Asphaltene deposition varied between 1–20 mg/1 g of sand grain. Comparing the experimental results with the result predicted by one of the current correlations showed that the correlation does not accurately predict permeability reduction.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".