Packerless Multistage Fracture-Stimulation Method Using CT Perforating and Annular Path Pumping
Bibliographic record
Abstract
Record high prices for oil and gas have increased the opportunity for producers to maximize the value of their assets. Under current market conditions, reservoirs previously considered marginal or even noneconomic can yield an acceptable return on investment and are increasingly considered for well completion. Many are lower-permeability formations that require fracture stimulation during the completion phase to deliver economic rates. In the latter part of 2004, a new stimulation technique was introduced to the industry, providing well operators a method to achieve multiple-zone fracture stimulation while controlling stimulation costs. By mid-2005, this new process had been evaluated by several operators in the US as well as Canada and Australia with very positive results.This new process offers the opportunity to perforate and stimulate multiple pay zones with a single well intervention, often within a single day. The technique employs a hydraulic jetting assembly on coiled tubing (CT) to erode perforations, immediately followed by pumping a fracture-stimulation treatment through the annulus between CT and casing. At the completion of the first fracturing stage, small-volume, high-proppant-concentration slurry is left in the wellbore to provide isolation of the just-stimulated zone from subsequent targets. In some applications, a wellbore screenout may also be induced to improve the temporary isolation of this zone. This sequence (perforate, stimulate, isolate) is repeated until all desired zones have been treated. Following the final stimulation stage, the well is cleaned out with CT and turned over to production. If needed, N2 gas can be pumped through the CT to kick-off the return flow.This paper describes the operational aspects, advantages, and limitations of using this new multistage perforating and fracturing technique with example field applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".