Optimized Gas-Well Stimulating Using CO2-Miscible, Viscosified Hydrocarbon Fracturing Fluids
Bibliographic record
Abstract
Abstract The use of CO2-miscible, viscosified hydrocarbon fracturing fluids has been proven to be a very effective gas-well stimulation technique in Canada and the United States. Fluid recovery is enhanced after stimulation by this process. Anderson and Gruber presented the original concepts used in paper CIM 95-45, entitled "Carbonated Hydrocarbons for Improved Gas Well Fracturing Results." 1 This paper provides results of wells recently stimulated. Simplifications to the fluid and job design processes, and additional design considerations are introduced. New CO2 solubility data generated at 50°C, 85°C, and 120°C with 30%, 40%, and 50% CO2 in four different fracturing fluids are presented to provide a wider range of design data. Compositional data for a number of specialty fracturing fluids are introduced to illustrate their enhanced fluid-recovery capability compared to heavier fluids such as kerosene and diesel.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".