Implications of Fracture Networks in Elastic Response of Heterogeneous Carbonate Reservoirs
Bibliographic record
Abstract
Abstract In this research, we explored how various fracture parameters could influence the elastic response of heterogeneous carbonates. Herein, 16 core plugs from a fractured carbonate formation are subjected to a comprehensive analysis including CT‐scanning, optical and electron microscopy, and XRD analysis to identify and characterize open fractures and their corresponding features. Subsequently, these samples underwent hydrostatic compression under reservoir conditions, during which ultrasonic wave velocities and strain were continuously measured while confining pressure was gradually increased to 65 MPa, pore pressure remained constant at zero, and temperature at 90°C. Our findings revealed that the presence of open fractures would cause a reduction in both compressional and shear wave velocities while causing strain variations. The extent of these changes, however, is notably influenced by fracture parameters, particularly connectivity, dip, and aperture. Furthermore, the study showed that the influence of stylolites and solution seams is the secondary influential factor, primarily impacting the P‐wave and increasing the strain. This research suggests that the impact of structural features, especially fractures, supersedes the role of porosity percentage in controlling the elastic properties of carbonate rocks. Furthermore, it was concluded that when fractures form a network, they exert a more pronounced impact on the elastic response compared to their isolated existence. This observation confirms that detection of fractures should be supplemented with a detailed assessment of their parameters. Collectively, this study provides valuable insights into how distinct fracture parameters would improve our interpretation of carbonate reservoirs elastic response, with a particular focus on wave velocities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".