The Application of Ultra-Lightweight Proppants to Cryogenic Liquid Nitrogen as a Fracturing Fluid: A Research Protocol
Bibliographic record
Abstract
Introduction: Hydraulic fracturing has rapidly gained popularity in the last decade, emerging as the leading method of natural gas extraction in the United States. The practice remains controversial, however, due to the release of greenhouse gases from burning shale gas as well as the contamination of freshwater used in fracturing fluids. Although waterless fracturing fluids have been developed, including those using nitrogen, carbon dioxide, oil, and alcohol, their application has been limited due to either reduced fracturing power or safety and environmental concerns. Recent research suggests that cryogenic liquid nitrogen may provide both a safe and environmentally-friendly alternative if its fracturing capabilities can be improved. Addition of ultra-lightweight proppants is a potential method of increasing the fracturing power of less viscous fluids. This research protocol thus aims to investigate the effect of ultra-lightweight proppant addition on the fracturing capabilities of liquid nitrogen. Methods: Three ultra-lightweight proppants will be combined at differing concentrations with liquid nitrogen and applied to samples of shale rock under triaxial stress. A control trial will also apply liquid nitrogen without the addition of any proppant. Fracturing power, measured on the basis of fracture length, will be assessed following each trial. Results: The results of these triaxial stress tests will provide measures of fracturing power for each proppant type and concentration combination and for liquid nitrogen independent of any proppant addition. Discussion: Analysis of these results will reveal whether the addition of ultra-lightweight proppants increases the fracturing capabilities of liquid nitrogen as well as identify the proppant type and concentration combination that affords liquid nitrogen the greatest fracturing power. Conclusion: The effect of ultra-lightweight proppant addition on the fracturing capabilities of liquid nitrogen has yet to be explored. Implementation of this protocol will thus open more avenues of research into sustainable and efficient fracturing using liquid nitrogen. Note: The authors of this article were invited by the URNCST Journal to publish this conference proceeding as a result of presenting a winning abstract at the Scinapse 2017-2018 Undergraduate Science Case Competition. A complete collection of abstracts presented at this conference was published by the URNCST Journal in March 2018 and can be found here: https://doi.org/10.26685/urncst.47.
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.008 |
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".