Design and Deployment of a New Fracturing Port Technology to Increase Stage Number Capability of Openhole Multistage Systems
Bibliographic record
Abstract
Abstract The Lower Huron Shale is of Upper Devonian age and produces in Ohio, Tennessee, Kentucky and West Virginia. This formation is a good candidate for hydraulic fracturing due to naturally occurring fractures and faults. Since the early 1900s, wells in the Lower Huron have typically been drilled and completed open hole with a variety of fracture treatment plans. However, to maximize production in the area, horizontal drilling using open hole multistage system (OHMS) completions began in the mid 2000s. Studies in the Lower Huron led to operators require longer laterals with increased stage numbers in order to maximize production; however, the limitations of OHMS restricted the potential of many wells. In order to deal with these limitations, the repeatable fracturing port (RFP) was developed. The RFP utilizes the same size ball to activate more than one fracture port – essentially multiplying the number of isolated stages. A field study in the Lower Huron demonstrated the benefits of using RFP technology, as the system functioned effectively and increased the number of potential stages. The success of RFP technology in the Lower Huron has been echoed throughout the U.S. and Canada, as increased knowledge continues to improve the technology and well performance.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".