Application of New Fracturing Technique Improves Stimulation Success for Openhole Horizontal Completions
Bibliographic record
Abstract
Proposal A relatively new technique for applying fractures (both proppant fracs and acid fracs)1–3 in horizontal openhole and uncemented liner completions is giving operators a more effective method for stimulation of underachieving wells. The process incorporates the known technologies of hydrajetting and fracturing in a novel way to achieve individual fracture placement at several selected locations along the lateral without the need for mechanical isolation methods, usually with only one service trip to the location. Depending on the number of fracturing stages desired, most job times vary from 6 to 12 hr if there are no hole-entry, tool, or logistic problems. Use of this new stimulation process continues to expand in the USA and Canada, and during the fourth quarter of 2002 and the first half of 2003, application of this process was successfully expanded beyond these original development areas to include offshore South America and a region of northern Asia. Before the end of 2003, numerous other locations around the globe are also planning to implement this stimulation technology on underperforming horizontal completions. Although this stimulation technique can also be used for cemented liners, its unique ability to control fracture placement in openhole and uncemented liner applications will be the focus of this paper. Only a brief review the basic technology is presented here, as numerous earlier publications provide more detail. New case histories will be presented wherein the application of this process has provided the operator with a distinct improvement in well completion economics.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".