Impact of Adsorption on Mass Transfer in Fractured Reservoirs
Bibliographic record
Abstract
Abstract The analysis of fluid transport in fractured reservoirs is of great concern in petroleum and environmental engineering. The objective of this work is to study mass transfer between the matrix and the fracture network in such complex formations. In this study, the impact of adsorption on mass transfer in a fractured medium with variable fracture spacing is investigated. Development of a mathematical model for mass transfer in dual porosity systems enhances predictions of the rate of mass transfer between matrix and fracture. In addition, it provides a tool for an appropriate design of advanced oil and gas recovery processes. Mass transfer is modeled based on the advective-dispersive transport with adsorption in an infinite acting dual porosity reservoir under radially divergent and continuous injection. The fracture spacing has been taken into account by including the variable rock matrix block size distribution in the developed model. By employing this model, the effects of the adsorption rate on the mass transport in a subsurface environment are analyzed. The impact of the rate of adsorption on the accumulation of the injected tracer (catalyst) in a reservoir is investigated. An understanding of the effect of adsorption on advective-dispersive mass transport with variable fracture intensity can be a key finding to develop and design advanced oil recovery processes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".