Effects of Fractal Fracture Surface Roughness on Borehole Ballooning
Bibliographic record
Abstract
Borehole ballooning or breathing is commonly observed during drilling through fractured zones. It refers to small, partial, and continuous mud losses and significant rapid mud gains due to annular pressure fluctuations resulting from mud circulation and noncirculation. Better understanding of the factors controlling borehole ballooning and breathing is needed for correct interpretation of the symptoms observed while drilling and to avoid mixing this phenomenon with lost circulation and well kicks. We have developed a two‐dimensional transient model of borehole ballooning or breathing. The model considers the effects of Newtonian fluid rheology, and fracture roughness on the fracture volume change as a function of transient wellbore pressure fluctuations inherent in typical drilling operations. Different types of fracture surface roughness that are commonly observed in sedimentary rocks and the degree of roughness identified by a wide variety of fractal dimensions were considered. The model was solved numerically to investigate the effects of fractures' natural geologic properties (fracture roughness, fracture width, and fracture grid size) on the fluid loss and gain rate between the borehole and the fractured formation. Analyses of the importance of fracture roughness and nonlinear deformation approximations were provided and situations were identified where the roughness starts to become an effective parameter in the process. Rough fractures yielded lower values of fluid loss rate than smooth fractures even though they had the same average aperture. The observations suggested that the scale used in data collection and generating fracture surfaces and apertures is a critical point. Increasing fracture aperture to twice its original value diminished the effects of fracture surface roughness on borehole ballooning.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".