Efficiency Analysis of Greenhouse Gas Sequestration during Miscible CO<sub>2</sub> Injection in Fractured Oil Reservoirs
Bibliographic record
Abstract
During CO2 injection into naturally fractured oil reservoirs for enhanced oil recovery, the great portion of oil is recovered by matrix-fracture interaction. Diffusive mass transfer between matrix and fracture controls this process if CO2 is miscible with matrix oil. Oil expelled from matrix is replaced by CO2, and the matrix could be potentially a good storage medium for the long-term. For the cooptimization of the oil recovery and CO2 storage, i.e., maximizing the oil recovery while maximizing the amount of CO2 stored, we propose an efficiency analysis using a dimensionless term defined as the global effectiveness factor. The Biot number and Thiele modulus were incorporated in the development of the global effectiveness factor. Diffusion coefficients and the rate of mass-transfer constants were obtained from our previous finite element modeling study. We first defined and derived the dimensionless groups to be used in the efficiency analysis and then formulated a relationship between the dimensionless groups and the efficiency indicators, i.e., the ratios of total solute (oil) produced to total solvent injected and total solvent stored to total solvent injected. It was shown that the efficiency of the process can be represented by a dimensionless group that consists of well-known dimensionless numbers such as the Reynolds number, the Peclet number, the Sherwood number, and the global effectiveness factor.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".