Multiscale Reconstruction of Vuggy Carbonates by Pore-Network Modeling and Image-Based Technique
Bibliographic record
Abstract
Summary Vugular carbonate rocks have a complicated flow behavior because of their multimodal porosity system, with different interconnectivity at the pore scale. In this study, a new hybrid algorithm to reconstruct a bimodal vugular porous medium is introduced by coupling the pore-network modeling approach (i.e., stochastic) with the image-based network technique (i.e., process-based). This work implements image-processing techniques to generate a lattice-based network of secondary porosity (i.e., vugs) on top of an initial pore-network model at the pore scale. The resulting multiscale model is designed to preserve vug-to-vug and vug-to-pore connectivity of overlapping vugs. Modifying the effective conductance of the overlapped vugs enables the calculation of permeability of the dual-porosity network by applying mass conservation and the Poiseuille law. The method is validated on samples from an Iranian carbonate formation. The matrix micropores obtained from the mercury-intrusion laboratory measurements are statistically reconstructed by a Nelder-Mead optimization algorithm. Our results show that during the addition of vugs into a network, the absolute permeability of the network increases monotonically with rising porosity before vug percolation. However, once vuggy pores percolate, the absolute permeability of the network increases tremendously. Moreover, the availability of vugs makes the network structure more complex as determined by the off-diagonal complexity measure. The results of this study help in understanding the behavior of vuggy formations observed in carbonate reservoirs.
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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".