Modelling a gas injection experiment incorporating embedded fractures and heterogeneous material properties
Bibliographic record
Abstract
This study focuses on the modelling of a gas injection experiment to assess the effects of incorporating heterogeneous material properties. The numerical model considers a two-phase flow coupled hydro-mechanical problem, and includes embedded fractures that open with deformation, thereby enhancing permeability. The approach used is integrated in the CODE_BRIGHT software, which allows for the consideration of geomaterials with a spatially correlated heterogeneous field of porosity that follows a normal distribution. This spatial correlation can be either isotropic or anisotropic. A key aspect of this approach is that material properties such as intrinsic permeability, diffusivity or cohesion are defined as a function of porosity. Consequently, these properties also exhibit heterogeneity with spatial correlation and, eventually, anisotropy. The results derived from the numerical model align well with in-situ measurements. The study also includes sensitivity analyses to the variation of critical variables. The calibration of the model has been validated through a similar experiment. The findings indicate that the consideration of heterogeneous material properties can have a significant influence on gas injection problems, particularly when a hydraulic fracture is formed.
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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".