Bibliographic record
Abstract
This article, written by Editorial Manager Adam Wilson, contains highlights of paper SPE 154391, ’Reducing Operational Time, Fluid Usage, Hydraulic Horsepower, Risk, and Downtime: Targeted Fracs Using CT-Enabled Frac Sleeves,’ by Luis Castro, SPE, Thomas Watkins, SPE, Brian Bedore, SPE, and Robert Holt, Baker Hughes, and Greg Manuel, Pioneer Natural Resources, prepared for the 2012 SPE/ICoTA Coiled Tubing and Well Intervention Conference and Exhibition, The Woodlands, Texas, 27-28 March. The paper has not been peer reviewed. Unconventional reservoirs are an increasingly important part of the hydrocarbon production pool in North America. Because reservoir conditions typically require hydraulic fracturing for economical production, a significant amount of resources are focused on making the fracturing process faster and more efficient and on lowering its environmental impact. A novel technique to create targeted annular hydraulic fractures rapidly involves deploying an activation tool on coiled tubing (CT) to open fracture sleeves in a horizontal well. The new technology uses fracture sleeves that are activated swiftly using a CT bottomhole assembly (BHA). The system, already used in thousands of fracturing stages in Canada, speeds up the completion process, uses less fluid, minimizes risks, and reduces overall downtime. Introduction Unconventional reservoirs in the United States are commonly stimulated using what is known as the “plug-and-perf ” (P&P) method. This method requires a tubing-conveyed perforating (TCP) device run, typically on CT, for the first stage to open a conduit for pumping down the casing. The first stage of the fracturing treatment is then pumped down through the open perforations. Once completed, a composite plug and perforating guns are run on wireline to isolate the first fracture stage and to perforate intervals in the second stage (each interval is commonly referred to as a “cluster”). Running wireline in horizontal wells requires pumping fluid from surface to push the wireline BHA through the wellbore like a piston. After retrieving the wireline from the well, the subsequent fracture treatment is pumped. This process is repeated until all stages are completed. After the fracture spread moves off of the location, a CT unit is commonly brought in to mill the composite plugs and allow the well to produce. Although this method is the one most commonly used, it has drawbacks. P&P fracs are time consuming: They require numerous days on location to prepare the well (i.e., running the TCP device, known as a toe-shoot), complete all the stages designed for the fracturing treatment, and finally mill the plugs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".