Investigation of Horizontal Well Fracture Extension Pattern Based on Downhole Pressure Data
Bibliographic record
Abstract
Abstract This paper presents the results of an investigation into fracture growth pattern in three horizontal wells, each fractured multiple times. The completion system was selected such that it allowed recording of the bottom-hole pressure in two critical locations; at the frac port which was being fractured, and, within the previously fractured part of the same wellbore. Downhole cups isolated the two locations from each other. The data show remarkable results. All fractures initiated axially and re-oriented to become perpendicular to the minimum principal stress (MPS). The re-orientation details varied widely between different fractures in the same well, and also between wells. In-spite of these variations, there was no communication within the formation between the multiple fractures. All fractures in the same well had the same value of MPS, and in fact nearly the same in all three wells. In one of the wells there was obstruction to proppant movement inside the fracture which caused increasing pressures during fracture extension. In one instance this resulted in screen-out very near the wellbore early in the treatment, and in another case inside the fracture and close to the end of the stage. Still, the high pressures encountered during these fractures did not cause communication with the previous fractures. The growth pattern in all fractures can best be described as off-balance, with no evidence of "complexity".
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".