Impact of effective stress on permeability for carbonate fractured-vuggy rocks
Bibliographic record
Abstract
To gain insight into the flow mechanisms and stress sensitivity for fractured-vuggy reservoirs, several core models with different structural characteristics were designed and fabricated to investigate the impact of effective stress on permeability for carbonate fractured-vuggy rocks (CFVR). It shows that the permeability performance curves under different pore and confining pressures (i.e. altered stress conditions) for the fractured core models and the vuggy core models have similar change patterns. The ranges of permeability variation are significantly wider at high pore pressures, indicating that permeability reduction is the most significant during the early stage of development for fractured-vuggy reservoirs. Since each obtained effective stress coefficient for permeability (ESCP) varies with the changes in confining pressure and pore pressure, the effective stresses for permeability of four representative CFVR show obvious nonlinear characteristics, and the variation ranges of ESCP are all between 0 and 1. Meanwhile, a comprehensive ESCP mathematical model considering triple media, including matrix pores, fractures, and dissolved vugs, was proposed. It is proved theoretically that the ESCP of CFVR generally varies between 0 and 1. Additionally, the regression results showed that the power model ranked highest among the four empirical models mainly applied in stress sensitivity characterization, followed by the logarithmic model, exponential model, and binomial model. The concept of “permeability decline rate” was introduced to better evaluate the stress sensitivity performance for CFVR, in which the one-fracture rock is the strongest, followed by the fracture-vug rock and two-horizontal-fracture rock; the through-hole rock is the weakest. In general, this study provides a theoretical basis to guide the design of development and adjustment programs for carbonate fractured-vuggy reservoirs.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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 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".