Numerical Study of Stress Dependency of Absolute and Relative Permeability in Unconsolidated Sands
Bibliographic record
Abstract
ABSTRACT: Understanding the stress dependency of absolute and relative permeability in reservoir rocks is crucial to study subsurface fluid flow. Unconsolidated sands usually have a high stress sensitivity compared to other rock types. However, unconsolidated rocks often fall apart when being tested and therefore one may not get usable results from laboratory experiments. This study employs a digital rock workflow to simulate the stress dependency of fluid flow properties by coupling a finite element analysis (FEA) micro-mechanics model with a Lattice Boltzmann (LB) fluid flow model. The numerical model is validated against laboratory measurements of stress-dependent porosity and permeability in Ottawa unconsolidated sands. The results demonstrate that increasing stress alters pore connectivity and reduces porosity and absolute permeability. The simulations indicate that relative permeability of the non-wetting phase tends to decrease with increasing stress. However, relative permeability of the wetting phase may increase or decrease conditioned by the capillary number and viscosity ratio. This study highlights the critical role of pore-scale interactions in stress-permeability relationships and provides a framework for predicting subsurface fluid behavior in unconsolidated formations. These findings have significant implications for reservoir characterization and geomechanical applications.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".