Channel Fracturing - A Paradigm Shift in Tight Gas Stimulation
Bibliographic record
Abstract
Abstract The hydraulic Channel Fracturing technique relies on the engineered creation of a network of open channels within the proppant pack, which provides for highly conductive paths for the flow of fluids from the reservoir to the wellbore. This paper provides a comprehensive summary of the implementation of this technique in ultra-low permeability, gas-bearing formations. The Lance formation in the Jonah field near Pinedale, Wyoming was selected for this study. This formation comprises fluvial sand bodies with 0.0005 to 0.05 mD permeability and 35 to 55% gas saturation. The formation requires hydraulic fracturing for economic production. Key historical issues for the stimulation of this formation using gelled fluids and sand as proppant are limited fluid recovery and consequential formation and fracture conductivity impairments. Slick-water treatments have rendered moderate gains in production mainly in low-prospect zones with some occurrence of near-wellbore screen-outs. Moderate increases in production from using ceramic proppants have been gained at the expense of significant increase in stimulation costs. Hydrocarbon production, treating pressure and fracturing fluid recovery data from a thirteen-well campaign in the Jonah field are summarized in the manuscript. Results indicate that the implementation of the channel fracturing technique increased initial gas production and estimated recovery over conventional fracturing methodologies. Positive features that were also observed during this campaign such as reduced net pressure increase estimates from pre- and post-frac shut-in pressure measurements, reduced tendency for vertical fracture growth and elimination of near-wellbore screen-outs are also reported and discussed. It is concluded that the Channel Fracturing technique is a viable alternative to conventional fracturing methods for more efficient and effective stimulation of complex tight gas formations.
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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 | 0.002 | 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".