Experimental and Numerical Investigations of Borehole Ballooning in Rough Fractures
Bibliographic record
Abstract
Summary Borehole ballooning/breathing is a combined mud-loss/-gain event observed during drilling operations in naturally fractured formations. Factors controlling this phenomenon must be well understood to correctly interpret its symptoms observed during drilling to avoid mixing ballooning with other formation flow incidents that might lead to unwarranted well-control procedures. A mathematical model defining the ballooning process was developed and solved numerically using finite-difference approximation. It was shown that fracture roughness and fracture deformation play a significant role in the flow of drilling fluid in and out of a single fracture. In this study, the focus was mainly on the effect of fracture roughness (characterized by the fractal dimension of the fracture surface) and fracture aperture. The main goal of this work was to compare the numerical-model results with laboratory-scale experimental observations. Therefore, experiments were performed to study the mud-loss and -gain events in artificially fractured rock samples. Cylinders of Berea sandstone, Indiana limestone, and granite were used for the experiments (1-in. diameter, 3-in. length). Two different fracture types were used to analyze the effect of fracture-surface roughness on the flow of drilling fluid in and out of the fracture. To create smooth fracture surfaces, cores were cut precisely into two equal pieces using a blade. Alternatively, axial load was applied on the cylindrical rock samples until a longitudinal fracture with a rough surface was generated. The results of experimental observations and numerical-model study on the importance of fracture roughness were provided. Situations where the degree of roughness becomes critical were identified.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".